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Mental Health During the COVID-19 Pandemic

Frequently asked questions, mental health resources.

NIH has compiled a library of resources related to COVID-19 and mental illnesses and disorders, including condition-specific and population-specific resources.

An Urgent Issue

Both SARS-CoV-2 and the COVID-19 pandemic have significantly affected the mental health of adults and children. In a 2021 study, nearly half of Americans surveyed reported recent symptoms of an anxiety or depressive disorder, and 10% of respondents felt their mental health needs were not being met. Rates of anxiety, depression, and substance use disorder have increased since the beginning of the pandemic. And people who have mental illnesses or disorders and then get COVID-19 are more likely to die than those who don’t have mental illnesses or disorders.

Mental health is a focus of NIH research during the COVID-19 pandemic. Researchers at NIH and supported by NIH are creating and studying tools and strategies to understand, diagnose, and prevent mental illnesses or disorders and improve mental health care for those in need.

How COVID-19 Can Impact Mental Health

If you get COVID-19, you may experience a number of symptoms related to brain and mental health, including:

Cognitive and attention deficits (brain fog)

Anxiety and depression

Suicidal behavior

Data suggest that people are more likely to develop mental illnesses or disorders in the months following infection, including symptoms of post-traumatic stress disorder (PTSD). People with Long COVID may experience many symptoms related to brain function and mental health.

How the Pandemic Affects Developing Brains

The impact of the COVID-19 pandemic on the mental health of children is not yet fully understood. NIH-supported research is investigating factors that may influence the cognitive, social, and emotional development of children during the pandemic, including:

Changes to routine

Virtual schooling

Mask wearing

Caregiver absence or loss

Financial instability

Not Everyone Is Affected Equally

While the COVID-19 pandemic can affect the mental health of anyone, some people are more likely to be affected than others. People who are more likely to experience symptoms of mental illnesses or disorders during the COVID-19 pandemic include:

People from racial and ethnic minority groups

Mothers and pregnant people

People with financial or housing insecurity

People with disabilities

People with preexisting mental illnesses or substance use problems

Health care workers

People who belong to more than one of these groups may be at an even greater risk for mental illness.

Telehealth’s Potential to Help

The pandemic has prevented many people from visiting health care professionals in person, and as a result, telehealth has been more widely adopted during this time. Telehealth visits for mental health and substance use disorders increased significantly from 2020 to 2021 and now make up nearly half of all total visits for behavioral health.

Widespread adoption of telehealth services may help people who otherwise would not be able to access mental health support, such as people in rural areas or places with few providers.

I have a preexisting mental illness. Is COVID-19 more dangerous to me?

COVID-19 can be worse for people with mental illnesses. Data suggest that people who reported symptoms of anxiety or depression had a greater chance of being hospitalized after a COVID-19 diagnosis than people without those symptoms.

The Centers for Disease Control and Prevention (CDC) reports that having mood disorders and schizophrenia spectrum disorders can increase a person’s chances of having severe COVID-19. People with mental illnesses who belong to minority groups are also more likely to get COVID-19. And people with schizophrenia are significantly more likely to get COVID-19 and more likely to die from it.

Despite these risks, effective treatments are available. If you have a preexisting mental illness and get COVID-19, talk to your health care professional to determine the treatment plan that’s appropriate for you.

I’m experiencing symptoms of a mental illness or disorder. What should I do?

If you are experiencing symptoms of anxiety, depression, or any other mental illness or disorder, there are ways you can get help. For immediate help:

Call or text the 988 Suicide & Crisis Lifeline at 988 (para ayuda en español, llame al 988)

Call or text the Disaster Distress Helpline , 1-800-985-5990 (press 2 for Spanish)

The Substance Abuse and Mental Health Services Administration can help you find mental health or substance use specialists.

Talk to your health care professional or mental health care professional. Together, you can work on a plan to manage or reduce your symptoms.

What research is NIH doing on the mental health impacts of COVID-19?

The National Institute of Mental Health (NIMH) and other NIH Institutes have created research initiatives to address mental health for people in general and for the most vulnerable people specifically. Examples of this research include:

NIH's Researching COVID to Enhance Recovery (RECOVER) Initiative has launched RECOVER-NEURO , a clinical trial that will test interventions to combat cognitive problems caused by Long COVID, including brain fog, memory problems, difficulty with attention, thinking clearly, and problem solving.

NIMH launched a five-year research study called RECOUP-NY to promote the mental health of New Yorkers from communities hard-hit by COVID-19. The study will test the use of a new care model called Problem Management Plus (PM+) that can be used by non-specialists.

A study funded by NIMH is examining the use of mobile apps to address mental health disparities .

The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) is funding research to understand the effects of mask usage for children , including any impacts on their emotional and brain development.

NIMH is funding research on the impacts of the pandemic on underserved and vulnerable populations and on the cognitive, social, and emotional development of children .

The National Institute on Alcohol Abuse and Alcoholism (NIAAA) is funding research on how COVID-19 and SARS-CoV-2 affect the causes and consequences of alcohol misuse .

A collaborative study supported by NIMH and the National Center for Complementary and Integrative Health (NCCIH) enrolled more than 3,600 people from all 50 U.S. states to understand the stressors affecting people during the pandemic.

Mental Health Resources by Topic

A library of resources related to COVID-19 and mental illnesses and disorders

Page last updated: September 28, 2023

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Mental health and the pandemic: What U.S. surveys have found

The coronavirus pandemic has been associated with worsening mental health among people in the United States and around the world . In the U.S, the COVID-19 outbreak in early 2020 caused widespread lockdowns and disruptions in daily life while triggering a short but severe economic recession that resulted in widespread unemployment. Three years later, Americans have largely returned to normal activities, but challenges with mental health remain.

Here’s a look at what surveys by Pew Research Center and other organizations have found about Americans’ mental health during the pandemic. These findings reflect a snapshot in time, and it’s possible that attitudes and experiences may have changed since these surveys were fielded. It’s also important to note that concerns about mental health were common in the U.S. long before the arrival of COVID-19 .

Three years into the COVID-19 outbreak in the United States , Pew Research Center published this collection of survey findings about Americans’ challenges with mental health during the pandemic. All findings are previously published. Methodological information about each survey cited here, including the sample sizes and field dates, can be found by following the links in the text.

The research behind the first item in this analysis, examining Americans’ experiences with psychological distress, benefited from the advice and counsel of the COVID-19 and mental health measurement group at Johns Hopkins Bloomberg School of Public Health.

At least four-in-ten U.S. adults (41%) have experienced high levels of psychological distress at some point during the pandemic, according to four Pew Research Center surveys conducted between March 2020 and September 2022.

Young adults are especially likely to have faced high levels of psychological distress since the COVID-19 outbreak began: 58% of Americans ages 18 to 29 fall into this category, based on their answers in at least one of these four surveys.

Women are much more likely than men to have experienced high psychological distress (48% vs. 32%), as are people in lower-income households (53%) when compared with those in middle-income (38%) or upper-income (30%) households.

In addition, roughly two-thirds (66%) of adults who have a disability or health condition that prevents them from participating fully in work, school, housework or other activities have experienced a high level of distress during the pandemic.

The Center measured Americans’ psychological distress by asking them a series of five questions on subjects including loneliness, anxiety and trouble sleeping in the past week. The questions are not a clinical measure, nor a diagnostic tool. Instead, they describe people’s emotional experiences during the week before being surveyed.

While these questions did not ask specifically about the pandemic, a sixth question did, inquiring whether respondents had “had physical reactions, such as sweating, trouble breathing, nausea, or a pounding heart” when thinking about their experience with the coronavirus outbreak. In September 2022, the most recent time this question was asked, 14% of Americans said they’d experienced this at least some or a little of the time in the past seven days.

More than a third of high school students have reported mental health challenges during the pandemic. In a survey conducted by the Centers for Disease Control and Prevention from January to June 2021, 37% of students at public and private high schools said their mental health was not good most or all of the time during the pandemic. That included roughly half of girls (49%) and about a quarter of boys (24%).

In the same survey, an even larger share of high school students (44%) said that at some point during the previous 12 months, they had felt sad or hopeless almost every day for two or more weeks in a row – to the point where they had stopped doing some usual activities. Roughly six-in-ten high school girls (57%) said this, as did 31% of boys.

On both questions, high school students who identify as lesbian, gay, bisexual, other or questioning were far more likely than heterosexual students to report negative experiences related to their mental health.

Mental health tops the list of worries that U.S. parents express about their kids’ well-being, according to a fall 2022 Pew Research Center survey of parents with children younger than 18. In that survey, four-in-ten U.S. parents said they’re extremely or very worried about their children struggling with anxiety or depression. That was greater than the share of parents who expressed high levels of concern over seven other dangers asked about.

While the fall 2022 survey was fielded amid the coronavirus outbreak, it did not ask about parental worries in the specific context of the pandemic. It’s also important to note that parental concerns about their kids struggling with anxiety and depression were common long before the pandemic, too . (Due to changes in question wording, the results from the fall 2022 survey of parents are not directly comparable with those from an earlier Center survey of parents, conducted in 2015.)

Among parents of teenagers, roughly three-in-ten (28%) are extremely or very worried that their teen’s use of social media could lead to problems with anxiety or depression, according to a spring 2022 survey of parents with children ages 13 to 17 . Parents of teen girls were more likely than parents of teen boys to be extremely or very worried on this front (32% vs. 24%). And Hispanic parents (37%) were more likely than those who are Black or White (26% each) to express a great deal of concern about this. (There were not enough Asian American parents in the sample to analyze separately. This survey also did not ask about parental concerns specifically in the context of the pandemic.)

Looking back, many K-12 parents say the first year of the coronavirus pandemic had a negative effect on their children’s emotional health. In a fall 2022 survey of parents with K-12 children , 48% said the first year of the pandemic had a very or somewhat negative impact on their children’s emotional well-being, while 39% said it had neither a positive nor negative effect. A small share of parents (7%) said the first year of the pandemic had a very or somewhat positive effect in this regard.

White parents and those from upper-income households were especially likely to say the first year of the pandemic had a negative emotional impact on their K-12 children.

While around half of K-12 parents said the first year of the pandemic had a negative emotional impact on their kids, a larger share (61%) said it had a negative effect on their children’s education.

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John Gramlich is an associate director at Pew Research Center .

How Americans View the Coronavirus, COVID-19 Vaccines Amid Declining Levels of Concern

Online religious services appeal to many americans, but going in person remains more popular, about a third of u.s. workers who can work from home now do so all the time, how the pandemic has affected attendance at u.s. religious services, economy remains the public’s top policy priority; covid-19 concerns decline again, most popular.

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COVID-19 pandemic triggers 25% increase in prevalence of anxiety and depression worldwide

Wake-up call to all countries to step up mental health services and support.

In the first year of the COVID-19 pandemic, global prevalence of anxiety and depression increased by a massive 25%, according to a scientific brief released by the World Health Organization (WHO) today. The brief also highlights who has been most affected and summarizes the effect of the pandemic on the availability of mental health services and how this has changed during the pandemic.

Concerns about potential increases in mental health conditions had already prompted 90% of countries surveyed to include mental health and psychosocial support in their COVID-19 response plans, but major gaps and concerns remain.

“The information we have now about the impact of COVID-19 on the world’s mental health is just the tip of the iceberg,” said Dr Tedros Adhanom Ghebreyesus, WHO Director-General. “This is a wake-up call to all countries to pay more attention to mental health and do a better job of supporting their populations’ mental health.”

Multiple stress factors

One major explanation for the increase is the unprecedented stress caused by the social isolation resulting from the pandemic. Linked to this were constraints on people’s ability to work, seek support from loved ones and engage in their communities.

Loneliness, fear of infection, suffering and death for oneself and for loved ones, grief after bereavement and financial worries have also all been cited as stressors leading to anxiety and depression. Among health workers, exhaustion has been a major trigger for suicidal thinking.

Young people and women worst hit

The brief, which is informed by a comprehensive review of existing evidence about the impact of COVID-19 on mental health and mental health services, and includes estimates from the latest Global Burden of Disease study, shows that the pandemic has affected the mental health of young people and that they are disproportionally at risk of suicidal and self-harming behaviours. It also indicates that women have been more severely impacted than men and that people with pre-existing physical health conditions, such as asthma, cancer and heart disease, were more likely to develop symptoms of mental disorders.

Data suggests that people with pre-existing mental disorders do not appear to be disproportionately vulnerable to COVID-19 infection. Yet, when these people do become infected, they are more likely to suffer hospitalization, severe illness and death compared with people without mental disorders. People with more severe mental disorders, such as psychoses, and young people with mental disorders, are particularly at risk.

Gaps in care

This increase in the prevalence of mental health problems has coincided with severe disruptions to mental health services, leaving huge gaps in care for those who need it most. For much of the pandemic, services for mental, neurological and substance use conditions were the most disrupted among all essential health services reported by WHO Member States. Many countries also reported major disruptions in life-saving services for mental health, including for suicide prevention.

By the end of 2021 the situation had somewhat improved but today too many people remain unable to get the care and support they need for both pre-existing and newly developed mental health conditions.

Unable to access face-to-face care, many people have sought support online, signaling an urgent need to make reliable and effective digital tools available and easily accessible. However, developing and deploying digital interventions remains a major challenge in resource-limited countries and settings.

WHO and country action

Since the early days of the pandemic, WHO and partners have worked to develop and disseminate resources in multiple languages and formats to help different groups cope with and respond to the mental health impacts of COVID-19. For example, WHO produced a story book for 6-11-year-olds, My Hero is You, now available in 142 languages and 61 multimedia adaptations, as well as a toolkit for supporting older adults available in 16 languages.

At the same time, the Organization has worked with partners, including other United Nations agencies, international nongovernmental organizations and the Red Cross and Red Crescent Societies, to lead an interagency mental health and psychosocial response to COVID-19. Throughout the pandemic, WHO  has also worked to promote the integration of mental health and psychosocial support across and within all aspects of the global response. 

WHO Member States have recognized the impact of COVID-19 on mental health and are taking action. WHO’s most recent pulse survey on continuity of essential health services indicated that 90% of countries are working to provide mental health and psychosocial support to COVID-19 patients and responders alike. Moreover, at last year’s World Health Assembly, countries emphasized the need to develop and strengthen mental health and psychosocial support services as part of strengthening preparedness, response and resilience to COVID-19 and future public health emergencies. They adopted the updated Comprehensive Mental Health Action Plan 2013-2030, which includes an indicator on preparedness for mental health and psychosocial support in public health emergencies.

Step up investment

However, this commitment to mental health needs to be accompanied by a global step up in investment. Unfortunately, the situation underscores a chronic global shortage of mental health resources that continues today. WHO’s most recent Mental Health Atlas showed that in 2020, governments worldwide spent on average just over 2% of their health budgets on mental health and many low-income countries reported having fewer than 1 mental health worker per 100 000 people.

Dévora Kestel, Director of the Department of Mental Health and Substance Use at WHO, sums up the situation: ”While the pandemic has generated interest in and concern for mental health, it has also revealed historical under-investment in mental health services. Countries must act urgently to ensure that mental health support is available to all.”

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• Published: 09 July 2021

Public mental health problems during COVID-19 pandemic: a large-scale meta-analysis of the evidence

• Xuerong Liu   ORCID: orcid.org/0000-0002-9236-5773 1 ,
• Mengyin Zhu   ORCID: orcid.org/0000-0001-5561-9570 1 ,
• Rong Zhang   ORCID: orcid.org/0000-0003-4516-4116 2 ,
• Jingxuan Zhang   ORCID: orcid.org/0000-0002-8979-5107 1 ,
• Chenyan Zhang   ORCID: orcid.org/0000-0002-2945-6584 3 ,
• Peiwei Liu   ORCID: orcid.org/0000-0003-2660-1106 4 ,
• Zhengzhi Feng   ORCID: orcid.org/0000-0001-6144-5044 1 &
• Zhiyi Chen   ORCID: orcid.org/0000-0003-1744-4647 1 , 2  

Translational Psychiatry volume  11 , Article number:  384 ( 2021 ) Cite this article

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The coronavirus disease 2019 (COVID-19) pandemic has exposed humans to the highest physical and mental risks. Thus, it is becoming a priority to probe the mental health problems experienced during the pandemic in different populations. We performed a meta-analysis to clarify the prevalence of postpandemic mental health problems. Seventy-one published papers ( n  = 146,139) from China, the United States, Japan, India, and Turkey were eligible to be included in the data pool. These papers reported results for Chinese, Japanese, Italian, American, Turkish, Indian, Spanish, Greek, and Singaporean populations. The results demonstrated a total prevalence of anxiety symptoms of 32.60% (95% confidence interval (CI): 29.10–36.30) during the COVID-19 pandemic. For depression, a prevalence of 27.60% (95% CI: 24.00–31.60) was found. Further, insomnia was found to have a prevalence of 30.30% (95% CI: 24.60–36.60). Of the total study population, 16.70% (95% CI: 8.90–29.20) experienced post-traumatic stress disorder (PTSD) symptoms during the COVID-19 pandemic. Subgroup analysis revealed the highest prevalence of anxiety (63.90%) and depression (55.40%) in confirmed and suspected patients compared with other cohorts. Notably, the prevalence of each symptom in other countries was higher than that in China. Finally, the prevalence of each mental problem differed depending on the measurement tools used. In conclusion, this study revealed the prevalence of mental problems during the COVID-19 pandemic by using a fairly large-scale sample and further clarified that the heterogeneous results for these mental health problems may be due to the nonstandardized use of psychometric tools.

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Mental disorders following COVID-19 and other epidemics: a systematic review and meta-analysis

Introduction.

Since the end of 2019, the coronavirus disease 2019 (COVID-19) outbreak has continued to spread worldwide. Researchers rapidly identified the cause of COVID-19 to be the transmission of serious acute respiratory syndrome by a novel coronavirus (SARS-CoV-2) [ 1 ]. Unfortunately, due to the lack of effective cures and vaccines, the ability of public medical systems to guard against COVID-19 is deteriorating rapidly. Although approved vaccines are now available, their safety is still a concern [ 2 , 3 ]. Further, because of reports regarding the potential to be reinfected with COVID-19, public panic is still spreading even though COVID-19 transmission has been contained substantially [ 4 ]. To date, projections regarding the end of the COVID-19 pandemic around the world are still far from optimistic. There were more than 158.95 million confirmed cases and 3.30 million deaths by May 11, 2021 (supported by Johns Hopkins University), a situation that has led to unprecedented losses and stress.

COVID-19 not only threatens physical health but has also led to mental health sequelae (i.e., loss of family, job loss, social constraints and uncertainty, and fear about the future) [ 5 , 6 , 7 ]. In general, mental health problems, including depression and anxiety, have had major negative impacts on the public during the COVID-19 pandemic [ 8 , 9 ]. Previous studies showed that mental health problems, such as depression, anxiety, insomnia, and post-traumatic stress disorder (PTSD), suddenly increased after the COVID-19 outbreak: 53.8% of respondents rated the psychological impact of the outbreak as moderate or severe; 16.5% of participants reported moderate to severe depressive symptoms; 28.8% of participants reported moderate to severe anxiety symptoms; and 24.5% of participants showed psychological stress [ 10 ]. Moreover, such mental health problems were worse in confirmed patients and healthcare workers. As a typical example, one early study revealed acute anxiety symptoms in 98.84% of confirmed patients and depression symptoms in 79.07% of confirmed cases [ 11 ]. In addition, an early investigation concerning the mental health status of 400 public health workers found that 31% of public health workers had anxiety symptoms, and 24.5% of them had depressive symptoms [ 12 ]. In this vein, it seems that the mental health sequelae of the COVID-19 pandemic warrant more attention. In addition, with the development of the epidemic situation, long-term isolation due to the increasing number of confirmed and suspected patients has caused losses to life and property, which has not only caused considerable psychological stress in the population but has also had physiological effects, such as insomnia and PTSD.

In brief, the COVID-19 pandemic has exposed public health to dramatic risks and resulted in unacceptable mental and physiological stresses. Despite considerable research, two critical concerns regarding mental health problems during the COVID-19 pandemic remain. One concern in previous studies is that the conclusions regarding the prevalence of these mental health problems are highly heterogeneous, irrespective of whether they are derived from original investigations or meta-analyses [ 13 , 14 ]. Another is that early investigations were almost all done during the peak of the COVID-19 pandemic and thus may overestimate the scale of mental health problems. Thus, the main purpose of this study is to provide comprehensive statistical results regarding the impact of COVID-19 on individual mental health through a large-scale meta-analysis of the existing research in this field and to provide an evidence-based reference for the prevention and control of psychological crises during this pandemic. It is noteworthy that this study employs a larger data pool than any of the existing meta-analyses to date. Further, much effort has been made to perform an in-depth investigation of the patterns of mental health problems triggered by the COVID-19 pandemic, including population-, region-, and measurement-specific patterns.

Materials and methods

To improve reproducibility and standardization, all the pipelines and protocols were in line with the Cochrane Handbook and were double-checked by using the PRISMA checklist [ 15 ]. This meta-analysis has been preregistered on OSF for open access ( https://doi.org/10.17605/OSF.IO/A5VMK ).

Search strategy and selection criteria

A systematic search was conducted for studies published from January 1, 2020 to July 1, 2020 (the period from the commencement of the outbreak to its initial control in China) in PubMed, EMBASE, the Cochrane Library, EBSCO, Web of Science, CNKI (Chinese database), WANGFANG DATA, the Chinese Biomedical Literature Service System, and public information release platforms (WeChat Subscription or microblogs). According to the indices of the various databases, keywords, including “2019 novel coronavirus,” “COVID-19,” “novel coronavirus pneumonia,” “NPC,” “2019-nCoV,” “mental health,” “anxiety,” “depression,” “psychological health,” “sleep,” “insomnia,” “Posttraumatic stress disorder,” and “PTSD,” were adopted to retrieve published surveys of psychological status during the COVID-19 epidemic from January 1, 2020 to July 1, 2020. In addition to identifying any target studies that may have been missed, we checked the reference list of each selected paper. The population was divided into three categories according to the probable psychological stress intensity experienced: public health workers, confirmed patients, and the general population (see Fig. 1 , Supplemental information, and Table S1 ).

This flowchart is coincide with the broad-certified 2020 PRISMAstatement. Small sample size was predefined as < 30 participants.

Data extraction and quality assessment

The following data were extracted from each article by two researchers independently: study type; total number of participants; participation rate; region; percentage of physicians, nurses, and other healthcare workers screened in the survey; number of male and female participants; assessment methods used and their cutoffs; and the total number and percentage of participants who screened positive for depression, anxiety, insomnia or PTSD. If any of this information was not reported, the necessary calculations (e.g., transforming the percentage of healthcare workers to the number of healthcare workers) were performed. The accuracy of the extracted or calculated data was confirmed by comparing the collection forms of the two investigators.

In addition, two authors independently evaluated the risk of bias of the included cross-sectional studies using a modified form of the Newcastle-Ottawa scale. Potential disagreements were resolved by a third author. Specifically, the quality assessment criteria were as follows: sample representativeness and size; comparability between respondents and nonrespondents; ascertainment of depression, anxiety, and insomnia; and adequacy of the descriptive statistics. The total quality scores ranged between 0 and 5; studies scoring ≥3 points were regarded as having a low risk of bias, while studies scoring <3 points were regarded as having a high risk of bias (see Table S1 ).

Encoding and statistical analysis

The two investigators (XL and MZ), who performed the literature search, also extracted the data from the included studies independently. Disagreements were resolved with the third investigator (ZC) or by consensus. Then, the following variables were extracted: author, date of publication, age, gender, region, sample size, method, number of positive cases, and positivity rate. All these analytical procedures were performed with the CMA software (V3). In particular, given the heterogeneity within and between studies, random-effects models were used to estimate the average effect and its precision, which would give a more conservative estimate of the 95% confidence intervals (CIs). The I 2 statistic and Cochran’s Q test were conducted to assess statistical heterogeneity.

Prior researchers held that the fixed-effects model is ideally suited to the meta-analysis of a nonheterogeneous data pool ( I 2  < 50%, P value ≥0.1) [ 16 ]. Conversely, the random-effects model should be used when there is heterogeneity between the studies ( I 2  > 50%). According to the factors that may affect the heterogeneity between studies, moderation analysis was further carried out for distinct cohorts (i.e., health workers, confirmed and suspected patients, the general population) and distinct sample sources (China, other countries). A funnel chart was created for visual inspection to determine whether the included studies showed publication bias; Egger’s test and Kendall’s test for the quantitative analysis of publication bias were also used, with p  > 0.05 indicating no publication bias.

In the current study, 896 Chinese and English studies were initially retrieved. According to the inclusion and exclusion criteria, 71 papers were eligible for inclusion in the data pool for the meta-analysis, and the total number of respondents reached 146,139 (see Table 1 and Table S2 ).

Heterogeneity test

The results of the heterogeneity test on the prevalence of mental problems in patients with COVID-19 showed that the heterogeneity across studies was large ( I 2  > 98%, P  < 0.05), which suggested that the random-effects model was needed to analyze the total effect. Importantly, to increase the robustness of the results and reduce the heterogeneity between studies, population, nationality, and subgroup were analyzed as possible moderators.

Prevalence of mental problems

Four symptoms related to stress were selected as the mental problems, and the related symptoms and symptom groups were analyzed according to the definitions given in each study. The prevalence of anxiety was 32.6% (95% CI: 29.1–36.3; N  = 86,035, see Fig. 2 ). In addition, the prevalence of depression was 27.60% (95% CI: 24.0–31.6; N  = 90,156, see Fig. 3 ). Likewise, insomnia prevalence during the COVID-19 pandemic was 30.30% (95% CI: 24.6–36.6; N  = 62,202, see Fig. 4A ). Finally, 16.70% of participants were found to meet the criteria for PTSD during the COVID-19 pandemic in this meta-analysis (95% CI: 8.9–29.2; N  = 17,169, see Fig. 4B ).

The squares colored by orange represent the point estimation foreffect towards corresponding study, with the large square size for high effect size. The orange diamond represent meta-analytic effect size.

The squares colored by orange represent the point estimation for effect towards corresponding study, with the large square size for high effect size. The orange diamond represent meta-analytic effect size.

Moderation analysis

Given the high heterogeneity, we assumed that there were some potential moderators, including the cohort (confirmed patients, healthcare workers, and the general population), region (China and other countries), and measurement tool. The results demonstrated a significantly higher prevalence of mental health problems in confirmed patients than in others (see Table S3 ). Further, the prevalence of mental health problems was found to be lower in China than in other countries. In addition, these findings derived from the moderation analysis revealed the moderating role of the measurement tool, with the results varying significantly across different scales (see Table S3 and Figs. S1–3).

Publication bias assessment

A funnel plot was first used for qualitative analysis of the publication bias. As shown in Figure S4 , a symmetrical distribution was found for the four psychological symptoms. In addition, Begg’s rank test was performed to quantitatively analyze the publication bias. The results showed that there was no publication bias in the studies regarding anxiety (Kendall’s tau = 0.044, p  = 0.614), depression (Kendall’s tau = −0.046, p  = 0.647), insomnia (Kendall’s tau = −0.096, p  = 0.592), or PTSD (Kendall’s tau = −0.145, p  = 0.533).

In this study, a meta-analysis was performed to clarify the mental health situation in the population during the COVID-19 pandemic with respect to anxiety, depression, sleep problems, and PTSD. The results showed that the detection rate of anxiety symptoms in a total of 86,035 cases was 32.6% (95% CI: 29.1–363); the detection rate of depression symptoms in a total of 90,156 cases was 27.6% (95% CI: 24.0–31.6); the detection rate of insomnia symptoms in a total of 62,202 cases was 30.3% (95% CI: 24.6–36.6); and the detection rate of PTSD symptoms was 16.7% in a total of 17,169 cases (95% CI: 8.9–29.2). Furthermore, the moderator analysis showed that mental health problems (i.e., anxiety and depression) had the highest prevalence in COVID-19 patients, and fewer anxiety, depression, and sleep problems were observed in healthcare workers than in the general population. Overall, this study provided solid evidence of the mental health situation during the COVID-19 pandemic and indicated the potential heterogeneity across cohorts, regions, and measurement tools.

Furthermore, regarding anxiety symptoms, health workers accounted for 32.7% (95% CI: 27.9–38.2) of the detection rate; the general population accounted for 29.5% (95% CI: 25.2–34.3). A total of 25.8% (95% CI: 20.4–31.0), and 25.3% (95% CI: 20.4–32.0) of depressive symptoms were found in health workers and the general population, respectively. The highest detection rate of insomnia, which was 37.3% (95% CI: 32.1–42.8%), was found in health workers, and the general population represented 26.1% of cases (95% CI: 18.2–36.1). The detection rate of PTSD was 30.6% (95% CI: 9.1–65.9) in health workers and just 9.3% (95% CI: 4–19.8) in the general population. Moving beyond previous studies, this meta-analysis covered the latest COVID-19-related articles and examined more publications than its predecessors. In contrast to the existing research conclusions, this study found that the mental health problems of healthcare workers are the same as those of the general population, suggesting that the existing research may overestimate the mental health problems of healthcare workers (i.e., one study showed that 50.4% of healthcare workers reported symptoms of depression, 44.6% symptoms of anxiety, and 34.0% insomnia) [ 17 ]. This may be because in the early stage of COVID-19, the pressures experienced by healthcare workers were considerable due to the sudden workload and lack of adequate understanding of the COVID-19 pandemic. However, in later stages, as an understanding of COVID-19 improved, healthcare workers became familiar with the situation and gained a more comprehensive understanding of the disease. This led to higher self-regulation ability under the circumstance of the epidemic even though the stress level of the first-line workers was high. Therefore, a very important conclusion of this study is that the mental health problems of healthcare workers are not as serious as previously thought, and lagging research conclusions may lead to label effects, which in turn worsen the mental health status of healthcare workers. In addition, we found that the detection rate of mental health problems in infected patients is higher in the COVID-19 pandemic than it was during the SARS outbreak [ 18 ]. For example, during SARS, the detection rate of anxiety symptoms was 35.7% (95% CI: 27.6–44.2), and that of depressed mood was 32.6% (95% CI: 24.7–40.9); in contrast, we found anxiety and depression rates of 63.9% (95% CI: 29.6–88.2) and 55.4% (95% CI: 32.8–76.0), respectively, in the COVID-19 context. During the outbreak of SARS in 2003, information dissemination was less developed than at present, and the public understanding of the virus was based on official information, which made the spread of rumors and concomitant psychological distress less likely. This shows that we should pay attention not only to the spread of the virus but also to the spread of false/fake information about the virus.

The second core finding of this study is that the detection rates of anxiety, depression, insomnia, and PTSD in other countries are higher than those in China. Existing study demonstrated the higher anxiety and depression symptoms in overseas Chinese lived in Italy than do of overseas Chinese lived in mainland China [ 19 ]. This may be because China was the first country to have an outbreak of the diseases and has taken a series of effective measures. Civil society organizations took responsibility for isolating residents in every community and helped solve practical life difficulties. At the individual level, home isolation, social distancing, and the wearing of personal protective equipment such as face masks were implemented to prevent community transmission nationwide. Due to the development of advanced technology, residents have had easy access to reliable information and medical guidance, which can reduce misinformation and the impact of rumors. The public was well educated on the seriousness of COVID-19 complied cooperatively with the national approach of hand washing, mask wearing, social distancing, and universal temperature monitoring. All citizens were keenly aware of their roles in preventing the virus from spreading. To strike a balance between epidemic control and normal social and economic operations, industrial activities have gradually resumed in phases and batches since February 8, 2020 [ 20 ]. The supply of daily necessities was kept stable in every stage of the outbreak to ensure the smooth operation of society. The WHO-China Joint Mission report said that China has rolled out perhaps the most ambitious, agile, and aggressive disease containment efforts in history [ 21 ]. By striking contrast, the number of confirmed cases outside China is quickly climbing following an exponential growth trend. The total number of COVID-19 cases outside China has reached 333,706,43, including 999,603 deaths as of September 29, 2020. Furthermore, we also conjecture that the reason why fewer pandemic impacts were seen in mainland China is that the well-established psychological rescue system strongly guards against the potential panic arising from the COVID-19 pandemic. Specifically, Chinese governmental intervention agencies provide professional psychological intervention services for patients with confirmed diseases or mental disorders, front-line medical staff, and other key groups in special places such as designated hospitals and isolated hospitals. In addition, public psychological rescue organizations offer free 24/7 on-call professional psychological advice to the public. Ultimately, massive open online courses were released to enrich the Chinese public’s understanding of the COVID-19 pandemic, which has significantly strengthened belief in the ability to control this disaster [ 22 ]. In addition, the comparative analysis of the results obtained with different measurement tools showed heterogeneity and poor consistency across the tools. Therefore, it is suggested that reliable measurement tools should be established in future research to avoid deviation in research results caused by measurement tools.

This study adjusted the prevalence of mental health problems reported in previous studies by analyzing more recent studies and thus provided a more accurate picture of the mental health status of the population. Previous studies have provided very timely and important evidence to prove that the COVID-19 pandemic is a threat to individual mental health. However, most of the surveys were performed in the early and peak periods and may overestimate the prevalence of these problems. Moreover, for the sake of timeliness in sharing research findings, low-quality articles were published in some journals. Therefore, this study also adopts the method of quality control evaluation to exclude articles with lower quality and obtain more accurate and unbiased conclusions. In general, the detection rate of mental health problems found in this study was lower than that in previous studies. There may be two reasons for this. First, stricter quality control was adopted in this study, making the analysis results more accurate and unbiased. Second, more new studies were included in this study; that is, the investigation time extended from the initial stage to the peak of the pandemic and then to the later stage of COVID-19 pandemic in the present study. Therefore, the results of this study may reflect that, with better control and understanding of the epidemic situation, people’s mental health status has improved, which is a good sign.

This study has several limitations. First, the sample sizes were not matched well, with the number of healthcare workers being smaller than the number of people from the general population. Second, the international sample was insufficient, and the research on Chinese people significantly exceeded than that on people from other countries. Third, the impact of specific epidemic status was not taken into account. In future studies, covariates can be added to the meta-analysis to control the epidemic situation of samples in different regions.

In conclusion, our systematic review and meta-analysis provide a timely and comprehensive synthesis of existing evidence, confirming the presence of mental health problems in patients (including suspected patients) as well as insomnia and PTSD in medical staff. The findings help to quantify staff support in the context of a pandemic when stratified and customized interventions are needed to enhance resilience and reduce vulnerability. With the continuous emergence of new evidence, we can further update the meta-analysis and perform follow-ups to analyze the factors related to the epidemic situation to facilitate national-level planning, improve the hierarchical intervention of the mental health security system, and address similar public health events in the future.

Data and code availability

Study protocols and hypotheses were preregistered on the Open Science Framework (OSF) ( https://osf.io/a5vmk/ ). Raw data, protocols, and analysis scripts are available openly at the OSF ( https://osf.io/a5vmk/ ).

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Acknowledgements

Special appreciations to Dr. Yancheng Tang (Peking University, Beijing, China; School of Business and Management, Shanghai International Studies University, Shanghai, China) for his comments on scientific contexts. Many thanks to Xi Luo and Ke Xu (Army Medical University, Chongqing, China) for their contributions to English writing. This study was supported by the People’s Liberation Army of China (PLA) Key Researches Foundation (CWS20J007).

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Department of Medical Psychology, Army Medical University, Chongqing, China

Xuerong Liu, Mengyin Zhu, Jingxuan Zhang, Zhengzhi Feng & Zhiyi Chen

School of Psychology, Southwest University, Chongqing, China

Rong Zhang & Zhiyi Chen

Cognitive Psychology Unit, The Institute of Psychology, Faculty of Social and Behavioural Sciences, Leiden University, Leiden, Netherlands

Chenyan Zhang

Department of Psychology, University of Florida, Gainesville, FL, USA

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XL and ZC: conceptualization, methodology, software, writing—original draft and visualization; MZ, JZ, and RZ: writing—review and editing, methodology, or validation; PL and CZ: writing—revision; RZ and XL: replication analysis and validation; ZC: formal analysis and validation; ZC and ZF: conceptualization, supervision, project administration, and funding acquisition.

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Liu, X., Zhu, M., Zhang, R. et al. Public mental health problems during COVID-19 pandemic: a large-scale meta-analysis of the evidence. Transl Psychiatry 11 , 384 (2021). https://doi.org/10.1038/s41398-021-01501-9

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DOI : https://doi.org/10.1038/s41398-021-01501-9

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Research Article

Mental health during the COVID-19 pandemic: Impacts of disease, social isolation, and financial stressors

Roles Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Human-Computer Interaction Institute & Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America

Roles Conceptualization, Formal analysis, Writing – original draft

Affiliation School of Journalism, Fudan University, Shanghai, China

Roles Conceptualization, Supervision, Writing – original draft, Writing – review & editing

Affiliation Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America

• Robert E. Kraut, 
• Han Li, 

• Published: November 23, 2022
• https://doi.org/10.1371/journal.pone.0277562
• Peer Review
• Reader Comments

Although research shows that the Covid-19 pandemic has led to declines in mental health, the existing research has not identified the pathways through which this decline happens.

The current study identifies the distinct pathways through which COVID-induced stressors (i.e., social distancing, disease risk, and financial stressors) trigger mental distress and examines the causal impact of these stressors on mental distress.

We combined evidence of objective pandemic-related stressors collected at the county level (e.g., lack of social contact, infection rates, and unemployment rates) with self-reported survey data from over 11.5 million adult respondents in the United States collected daily for eight months. We used mediation analysis to examine the extent to which the objective stressors influenced mental health by influencing individual respondents’ behavior and fears.

County-level, day-to-day social distancing predicted significantly greater mental distress, both directly and indirectly through its effects on individual social contacts, worries about getting ill, and concerns about finances. Economic hardships were indirectly linked to increased mental distress by elevating people’s concerns about their household’s finances. Disease threats were both directly linked to mental distress and indirectly through its effects on individual worries about getting ill. Although one might expect that social distancing from people outside the home would have a greater influence on people who live alone, sub-analyses based on household composition do not support this expectation.

This research provides evidence consistent with the thesis that the COVID-19 pandemic harmed the mental well-being of adults in the United States and identifies specific stressors associated with the pandemic that are responsible for increasing mental distress.

Citation: Kraut RE, Li H, Zhu H (2022) Mental health during the COVID-19 pandemic: Impacts of disease, social isolation, and financial stressors. PLoS ONE 17(11): e0277562. https://doi.org/10.1371/journal.pone.0277562

Editor: Mohammad Hayatun Nabi, North South University, BANGLADESH

Received: March 17, 2022; Accepted: October 30, 2022; Published: November 23, 2022

Copyright: © 2022 Kraut et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Most of the data reported in this paper are publicly available at a Github repository maintained by the Delphi research group at Carnegie Mellon University and available through R and python APIs ( https://cmu-delphi.github.io/delphi-epidata/api/covidcast.html ). These data come from multiple sources, with data licensing handled separately for each source. The de-identified survey data are available to researchers associated with universities or non-profit organizations. Researchers who want access to the survey data should submit an information request on Facebook’s COVID-19 Symptom Survey – Request for Data Access page ( https://dataforgood.facebook.com/dfg/tools/covid-19-trends-and-impact-survey#accessdata .)

Funding: rek NSF BCS 2030074 US National Science Foundation https://www.nsf.gov/ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Robert Kraut is a part-time employee of Meta, the company that partnered with Carnegie Mellon University to collect the data. Kraut had no role in data collection and as part of the data-use agreement was not allowed direct access to the data.

Introduction

By July 2022, the COVID-19 pandemic had infected over 88 million people in the United States and caused over a million deaths [ 1 ]. The Lancet’s COVID-19 Commission on Mental Health Task Force concluded that there was clear evidence that psychological distress increased during the early months of COVID-19 and that the pandemic was harming mental health [ 2 ]. Vahratian and colleagues at the National Center for Health Statistics at the CDC, using cross-sectional surveys from almost 800,00 respondents, documented a 14% increase in the number of US adults experiencing symptoms of anxiety or depression in the seven days prior to its surveys [ 3 ].

However, the existing research has not convincingly identified the distinct pathways through which COVID-induced stressors trigger mental distress nor disentangled the causal relationships among them. Most research has treated the pandemic as an undifferentiated whole, showing for example that indicators of mental distress were higher in locations [ 4 ] or at times with higher infection rates [ 5 – 7 ] or among specific groups of people, such as healthcare professionals [ 8 ]. While this type of research demonstrates that the pandemic was associated with increases in mental distress, it rarely differentiates distinct stressors associated with the pandemic and how they influence mental distress.

A small number of studies have attempted to differentiate the influence of distinct stressors associated with the pandemic, such as risks of disease and death, unemployment and loss of income, and social isolation resulting from stay-at-home policies and individual choices, and even fewer have attempted to examine the impact of these stressors simultaneously. We are aware only of recent research by Kämpfen et al [ 9 ], who used a large national probability survey of US adults conducted for three weeks in March 2020 to examine the extent to which disease and financial or social stressors predicted changes in symptoms of anxiety and depression. The stressors respectively were respondents’ perceived risk of getting infected and dying from Covid-19, their concerns that they would run out of money, and self-reported reductions in their social activities. They found that all three of these stressors predicted worse anxiety and depression outcomes, as measured by higher PHQ-4 scores [ 10 ] after controlling for relevant demographic variables, including sex, age, educational, race, and marital status. Alimoradi et al [ 11 ] found that sleep problems appear to have been common during the COVID-19 pandemic and were associated with higher levels of psychological distress among the general population, healthcare professionals, and COVID-19 patients.

Although an excellent start, this research has important limitations that undercut the conclusion that these stressors cause increases in anxiety and depression. Perhaps the most important are the related problems of endogeneity, common method bias, and reverse causation. Both the stressors and the mental health outcome were measured via respondents’ self-reports. Therefore, it is plausible that people who had higher levels of generalized anxiety and depression also perceived greater risk and had greater anxiety from the specific stressors the survey targeted. That is, respondents’ generalized mental distress may have led them to perceive higher risks independent of their objective risk. Similarly, those with higher levels of generalized anxiety and depression may have been more likely to practice social distancing.

The main substantive goal of our research is to examine the causal impact of distinct pandemic-related stressors on mental health. We examine the disease, financial, and social stressors identified by Kämpfen et al [ 9 ]. Our methodological goal is to reduce threats to causal interpretation by combining evidence of objective pandemic-related stressors with self-reported survey data and using mediation analysis to examine the extent to which the objective stressors influence mental health by influencing individual respondents’ behavior and fears. In contrast to most previous research, we examine the relationship between changes in pandemic-related stressors and mental health not just at the beginning of the pandemic but over a long, 8-month period and collect population-weighted data from over 11.5 million US adult respondents.

A simplified path model is presented in Fig 1 summarizing our hypotheses about how objective community-level stressors (i.e., social distancing, disease severity, and financial stressors) predicted mental distress, mediated by individual respondents’ social isolation and worries about disease and finances. We hypothesize that the pandemic could plausibly harm mental health through three distinct routes. First, the pandemic could increase mental distress by increasing fears of getting the disease [ 12 ]. Second, pandemic-induced social distancing, a result of both public health recommendations and individual decisions to limit exposure, could influence mental distress in a more complicated way. On the one hand, the hypothesis that social distancing would increase mental distress is based on decades of research demonstrating that social contact is associated with better physical and mental health and that loneliness and social isolation are associated with increased depression and mortality [ 13 – 15 ]. On the other hand, social distancing could also reduce people’s exposure to disease, which in turn could reduce their fears about getting ill and their overall mental distress. In addition, social distancing could also reduce employment opportunities for some people, such as restaurant workers, but increase employment for other occupations, such as warehouse workers or delivery drivers, or lower commuting and other work-related expenses for others, such as white-collar workers. Thus, to better understand the impact of social distancing policies and norms, we hypothesize that county-level social distancing can also influence mental distress by influencing personal social contact, illness worries, and financial worries. Third, the pandemic could lead to financial hardships and fears about them caused by economic slowdowns, which in turn could cause mental distress [ 16 ].

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0277562.g001

The solid lines labeled ‘A’ represent the degree to which county-level distancing and stressors influence respondents’ social contact and their individual worries, and the solid lines labeled ‘B’ represent the association between respondents’ social contact and their individual worries, and their mental distress. The dotted lines labeled ‘C’ represent the direct pathway between the county-level stressors and respondents’ mental distress. The product of ‘A’ and ‘B’ represents indirect effects of the county-level stressors on distress, which are mediated by their effects on respondents’ social contact and their individual worries about the illness and household finances.

Study design and data collection

We used time-series data from the COVID-19 Trends and Impact Survey [ 17 ], a collaborative project between Facebook and academics to support COVID-19 research. Each day Facebook invited a random sample of users in the United States at least 18 years old to take a survey designed and collected by Carnegie Mellon University’s (CMU) Delphi Group by placing a notification at the top of their News Feed. The survey was anonymous and did not collect any personally identifiable information.

The current paper relies on 11,974,779 survey responses from 239 cross-sectional samples gathered daily from April 6 to November 30, 2020. Although some respondents may have taken the survey more than once, because of the anonymous nature of the data collection we cannot identify surveys completed by the same person, and we therefore treat them as independent. Each survey response was weighted to adjust for non-response and coverage biases so that the distribution of age, gender, and county of residence in the survey samples were representative of the general population of the United States. (For details of the weighting see [ 17 ]). The demographic characteristics of the weighted sample closely matches data from the 2019 American Community Survey (ACS), except for an overrepresentation of highly educated respondents (See S1 Table ).

The survey asked respondents questions about COVID-19 symptoms they and other household members had. It also asked questions about the depression, anxiety, in-person social contact, and COVID-related stressors respondents were experiencing, the focus of this paper. Respondents also described their demographic characteristics, including their household composition, their gender, and their approximate age.

The survey data included respondents’ Federal Information Processing System (FIPS) county code, which allowed responses to be joined with county-level data from multiple sources describing daily and cumulative infection rates of COVID-19 in the county [ 17 ], unemployment rates [ 18 ], and the time county residents spent outside of the household as estimated from mobile devices [ 19 ]. We also estimated from the survey data daily county-level worries about illness and finances and county-level social contact by first removing the respondent’s data and then calculating the 2-week moving average surrounding the respondent’s survey date. These county-level variables are treated as potential causes that could influence mental distress directly or indirectly, by influencing the respondent-level predictors of interest, including social contact and worries about disease and finances.

Ethics statement

The Carnegie Mellon University Institutional Review Board (IRB) reviewed the research plan and granted approval under exempt review on 7/10/2020, (study id STUDY2020_00000292).

Table 1 below describes the measures of all variables used in the analyses.

https://doi.org/10.1371/journal.pone.0277562.t001

Analysis logic

We used structural equation modeling, done with the Stata SEM package [ 20 ], to implement the mediation analysis represented in Fig 1 ‘s path diagram. The maximum likelihood estimation was used in the analysis. The mediation analysis examines the potential causal pathways through which day-to-day variation in objective, county-level disease threat, financial threat, and social distancing could influence respondents’ mental distress either directly or mediated by respondents’ individual social contact and worries about disease and finances. To control for static characteristics of respondents’ locations, we first centered each variable by the county-identification FIPS code, which removes all fixed effects associated with that geographic area, such as its size, economic prosperity, demographics, and other unmeasured static differences. What remains is the day-to-day variability in respondents’ mental distress, disease and financial worries, and county-level stressors.

The use of both respondent-level variables collected via the survey and county-level ones from multiple sources reduces many threats to assessing causation from observational data. Because the variation in county-level stressors and social distancing are outside of any single respondent’s control, we can treat them as exogenous variables that can directly influence respondent-level variables but not be caused by them, eliminating possibilities of reverse causation. For example, changes in county-level disease threat (e.g., infection rates) and financial threat (e.g., unemployment rates) are exogenous variables that could influence respondents’ mental distress directly or indirectly through their worries about getting ill or their concerns about household finances. Similarly, changes in the time residents of a county spent outside their home, reflecting both government regulations and evolving local norms, are exogenous variables that could influence a respondent’s mental distress both directly or indirectly through its effect on their social distancing behavior and their worries about disease and finances. The multiple levels of analysis reduce the likelihood that unobservable variables, like respondents’ socio-economic status, work-status, or disability, jointly influence their social contact and their mental distress. The multiple levels of analysis also reduce common-method bias, in which associations are inflated because potential causes (e.g., financial worries) and consequence (e.g., mental distress) are measured using similar measures from a single source [ 21 ].

Tables 2 and 3 below show descriptive statistics and correlations among the variables.

https://doi.org/10.1371/journal.pone.0277562.t002

https://doi.org/10.1371/journal.pone.0277562.t003

Fig 2 shows how self-reported mental distress (depression and anxiety), county-level predictors and mediators varied over time. In addition to these time-varying variables, analyses reported below included several static covariates: respondents’ self-reported gender, approximate age, and whether the respondent lived alone or with others in the household.

(A) Self-reported mental distress. (B) Respondent-level endogenous mediating variables (disease and financial worries and social contact). (C) County-level exogenous predictor variables (disease and financially-related stressors and social distancing). All variables were normalized to the range of 0 to 1 before averaging. Averages vary over both location and time.

https://doi.org/10.1371/journal.pone.0277562.g002

Table 4 and Fig 3 summarize the mediation analysis, showing how county-level social distancing and disease and financial threats predict respondents’ mental distress both directly and indirectly through their influence on respondents’ social contacts with people outside their household and the worries they report having about getting ill and household finances. Table 4 also shows the direct effects of respondents’ demographics (age bracket, gender, and household composition) on their mental distress. The unit of analysis is a survey response. Because continuous variables have been standardized at the county level, the coefficients reflect the effects on respondents’ mental distress in standard deviation units resulting from a change of a binary predictor from zero to one (e.g., living alone to living with others) or the increase of a continuous variable by one standard deviation from its county-level base rate. Because of the very large sample size, all coefficients are reliably different from zero at the p < .0001 level. The structural equation mediation model is a good fit to the data (SRMR = .006), where an SRMR less than 0.08 indicates a good model fit [ 22 ]. Multicollinearity is not a problem, as all VIF values are lower than 2.5 (mean VIF = 1.1).

https://doi.org/10.1371/journal.pone.0277562.g003

https://doi.org/10.1371/journal.pone.0277562.t004

Fig 3 shows both direct effects of county-level stressors on respondents’ mental distress and effects mediated by respondent-level worries about disease, social contact, and household finances. The three coefficients on the dotted lines respectively represent the total effect, the direct effect, and the indirect effect of county-level variables on mental distress. Note, all coefficients in Fig 3 are highly significantly different from zero, with all p-values < .0001.

Effects of covariates

Women, younger respondents, and respondents living alone reported greater mental distress compared to men, older respondents and those living with others respectively. The associations of mental distress with these demographic characteristics are all consistent with prior research. For example, Salk et al’s meta-analysis revealed that women are substantially more likely to be diagnosed with depression and show depressive symptoms across multiple cultures [ 24 ]. Abundant research also demonstrates the links between social integration and both physical and mental health [ 25 ]. For example, people who live alone are almost twice as likely to report symptoms of depression compared to those who live with others in their household [ 26 ]. Although not the focus of the current project, survey findings showing less mental distress among respondents in households with other adults or children are consistent with one of our core hypotheses: social contact is a preventative for mental distress. However, because household composition is something that people choose, and people who are predisposed to mental distress may be more likely to choose to live alone, the association of household composition and mental distress is not itself strong evidence of a causal relationship between social contact and mental health. In contrast, an association of social distancing at the county level with mental distress is stronger causal evidence of the role of social contact, because it is unlikely that respondents with greater than average mental distress choose to live in a county during a period in which social distancing is greater than average.

Effects of disease threat, social distancing, and financial threat on respondents’ mental health

Disease threat..

The mediation analysis in Table 4 shows that overall greater threat of disease in an area is associated with more mental distress ( β = .013, p = 0.000). Because the county-level disease threat is associated with individual respondents’ worries that they or a family member would get ill from the disease ( β = .041, p = 0.000), and these worries about the disease are associated with their mental distress ( β = .205, p = 0.000), nearly 65% of the total effect of county-level disease threat is mediated by individual worries about disease ((.041 x .205)/.013). This mediation result suggests that objective risks of illness have their effects on mental distress to a large extent by elevating individual worries about becoming ill.

Social distancing.

Overall, social distancing at the county level is associated with increased mental distress ( β = .011, p = 0.000). Because county-level social distancing is associated with individual respondents’ having less social contact outside the home ( β = -.06, p = 0.000), more disease worries ( β = .016, p = 0.000), and more financial worries ( β = .007, p = 0.000) and because these individual level behaviors and worries are associated with mental distress ( β = -.042, .205, and .158 respectively, p = 0.000), the mediation analysis suggests that social distancing in a county affects respondents’ mental distress to a large extent by reducing their contact with others outside their homes, as well as increasing their worries about disease and finances. Approximately 63% of the total effect of county-level social mobility on mental distress is indirect and mediated by respondents’ self-reported reductions in social contact outside of their households, and disease and financial worries (((-.06 x -.042) + (.016x.205) + (.007x.158))/.011 = .628).

The total effect of county-level social distancing on mental distress is small but practically important because it is a policy lever at the disposal of government authorities, and because of the many millions of people whose mental health might be affected by social distancing policies and norms. The small effect size may be the result of other factors that influence respondents’ social mobility besides objective social distancing policies and norms, such as whether they are employed outside the home, their gender, or their household composition, which can also influence their mental distress.

In addition, lock-down orders and other reductions in opportunities for social contact outside the household may cause people to spend more time interacting with others in their household and thus compensate for the impact of social distancing on mental health. That is, for people who live with others, the greater social contact they have within the home may compensate for reductions in social contacts outside it. To examine this possibility, we tested whether the mental health benefits of greater county-level social mobility were greater for respondents living alone than for those living with another in their household. We added an interaction term between social distancing and live with someone to the SEM model. S2 Table shows the results. As a reminder, 76% of respondents lived with at least another adult or a child and 24% lived alone. The lack of a statistical interaction between county-level social distancing and living with others suggests that social distancing was not more harmful in terms of increasing mental distress among people who live alone ( β = -.002, p = 0.089). The marginal analysis shows that a standard deviation increase in county-level social distancing was associated with a .0044 standard deviation increase in mental distress both among those who lived alone and those living with another person.

Financial threat.

Overall, financial threat at the county level was associated with more mental distress ( β = .004, p = 0.000). This result is consistent with Witteveen and Velthorst’s findings in six European countries showing a “positive relationship between instantaneous economic hardships during the COVID-19 lockdown and expressing feelings of depression and health anxiety” [ 16 ]. A systematic review of research on COVID-19-related fear and anxiety and job-related outcomes also shows that fear of COVID-19 was associated with increased future career anxiety, decreased job satisfaction, and perceived job insecurity [ 27 ]. Because county-level financial threats were associated with respondents worrying more about household finances ( β = .056, p = 0.000), and respondent-level financial worries are in turn associated with greater mental distress ( β = .158, p = 0.000), the mediation analysis suggests that county-level financial threat affects respondents’ mental distress partially by increasing their personal worry about household finances ( β = .009, p = 0.000). Surprisingly, though, the direct effect of county-level financial threats was to reduce mental distress ( β = -.005, p = 0.000). To rule out the possibilities of multicollinearity due to a correlation between social distancing and county-level financial threats ( r = .184), we conducted an additional analysis excluding social mobility. The result shows a robust negative effect of county-level financial threats on mental distress ( β = -.004, p = 0.000). If county-level financial threats raised personal financial concerns which in turn increased mental distress, why was the direct effect of county-level financial threats to reduce mental distress? It may be that even though unemployment and concerns about finances in the county exacerbated mental distress by raising personal worries about finances, the 2020 Coronavirus Aid, Relief, and Economic Security Act (CARES Act) and other government stimulus programs reduced the actual financial pain associated with the pandemic, but these effects of government stimulus programs were not reflected in the county-level employment data we had available. Moreover, considering the overrepresentation of adults with higher education in the survey samples, those highly educated individuals might have been in white collar occupations less subject to the economic hardships caused by the pandemic.

This research provides evidence consistent with the thesis that the COVID-19 pandemic harmed the mental well-being of adults in the United States and identifies specific stressors associated with the pandemic that seem responsible for increasing mental distress. The current study distinguished objective stressors from respondents’ perceptions of stress, thereby reducing common method biases that have inflated the associations between stressors and mental distress in earlier research. Note that mental distress correlates ten times more highly with these measures of disease and finances worries and social contact, all of which were measured by self-report at the respondent level (mean absolute correlation = .195), than with parallel measures of disease and financial threat and social distancing measured at the county level (mean absolute correlation = .019). This substantial difference in strength of association is consistent with the speculation that Kämpfen et al’s results [ 9 ] were inflated by common method variance.

The analyses show that objective disease stressors outside of respondents’ control, as measured by county-level COVID-19 infection rates and the likelihood of other county residents knowing someone with COVID symptoms and being worried about getting ill, increased individuals’ mental distress in part by increasing their own worries that they or other family members would get ill. Overall objective financial stressors, as measured by county-level unemployment rates and county-level perceptions that the pandemic was harming household finances, were associated with greater mental distress, and these effects were mediated by the extent to which these financial stressors caused respondents to become worried about harm to their own household’s finances. However, the direct effect of the financial stressors seemed to be to lower mental distress. Future research is needed to examine the mechanism for this direct effect; for example, did federal government stimulus programs reduce the actual financial pain and associated mental distress during times of high unemployment, and what role did sociodemographic variables play?

The reduction in social contact caused by the pandemic is especially interesting. Reductions in social contact outside of the household, which were partially caused by official lock-down orders and informal norms in a county, were associated with greater mental distress. Authorities issued shutdowns and stay-at-home orders and people voluntarily reduced outside social contact to reduce their risk of becoming infected with the disease, and to the extent that these actions reduced people’s worries about getting COVID, they also reduced mental distress. However, to the extent that these efforts also reduced people’s social contact outside the home, they had the undesirable side effect of increasing mental distress. Surprisingly, the harmful effects of social distancing policies and behavioral norms in increasing mental distress applied equally to those who lived alone and those who lived with others. This latter result is consistent with previous research showing benefits from social interaction with coworkers, acquaintances, and other weak ties even among people who have greater than average strong-tie interactions [ 28 ] and benefits from social interactions in social spaces outside the home [ 29 ]. We believe one can balance the benefits of reduced social contact to slow the spread of disease with the mental health harms to social isolation. For example, having social interactions online, through text chats, emails, phone calls, and video sessions may successfully substitute for in-person social interactions. Very little research has examined the impact that modality of communication has on mental well-being [ 30 ].

This study has several methodological limitations that should be considered when interpreting the findings. Respondents’ mental distress was measured by two questions assessing depression and anxiety. Follow-up research should use more robust and clinically validated measures of psychological distress. While the survey data were representative of US adults in terms of age, gender and region, there was a sampling bias associated with education; the survey respondents were more educated than average US citizens. Additionally, follow-up research should examine how community-level predictors, like poverty and social inequality, and individual-level ones, like occupational status, moderate the stresses associated with the pandemic.

Despite these limitations, this research allows us to make stronger causal claims than possible with more conventional, respondent-level survey research about the impact of COVID-related stressors on mental health, because it examines pathways through which pandemic-related reductions in social mobility and increases in disease and financial stressors, measured at the county level and therefore out of respondents’ control, influence respondent-level social contacts and worries, which in turn lead to increases in mental distress.

Although the focus of this research was to understand how pandemic-related stressors were influencing mental health during the COVID-19 pandemic, it also extends our theoretical understanding of how social support works. Decades of research have provided strong and consistent evidence that social ties and social support improve many aspects of personal health, including all-cause mortality [ 31 , 32 ], physical health [ 33 , 34 ] and mental health [ 35 ], but the mechanisms are still murky [ 25 ]. It is unclear whether the component of support that is most valuable is the perception that support will be available when needed (i.e., perceived support), the explicit exchange of support during times of stress, especially from strong ties, or merely the accumulation of everyday social interactions [ 25 , 36 – 38 ]. Results of the current research are consistent with the thesis that mundane social interactions can lead to well-being. Week-to-week changes in the frequency of social contacts in the community seem to lead to changes in respondents’ mental distress, suggesting that to some extent it is social interactions that people actually engage in outside the home that confer benefits, rather than slower-to-change perceived social support. While our data show that people who are living with others have less mental distress, they also show that social contact outside of the household, and presumably with less intimate ties, also confers benefits over and above social contact within the home.

Data sharing

Most of the data reported in this paper are publicly available in the Epidata API, maintained by the Delphi research group at Carnegie Mellon University and available through R and Python clients. These data come from multiple sources, with data licensing handled separately for each source. The de-identified survey data are available to researchers associated with universities or non-profit organizations. Researchers who want access to the survey data should submit an information request on Facebook’s COVID-19 Symptom Survey–Request for Data Access page [ 39 ].

Supporting information

S1 table. characteristics of the study sample, compared to 2019 american community survey supplemental estimates..

https://doi.org/10.1371/journal.pone.0277562.s001

S2 Table. Mediation analysis predicting mental distress from county-level and respondent-level variables, including the interaction between Social distancing and Live with someone .

https://doi.org/10.1371/journal.pone.0277562.s002

Acknowledgments

The authors would like to thank Alex Reinhart for statistical advice and Aya Betensky for editorial assistance.

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• 19. Delphi Group. SafeGraph Social Distancing Metrics; 2020. In: Safegraph, editor.: Carnegie Mellon University; 2020. https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/safegraph.html
• 20. StataCorp. Stata Statistical Software. 17 ed. College Station, TX: Stata Corporation; 2021.
• 33. Leppin A, Schwarzer R. Social support and physical health: An updated meta-analysis. In: Schmidt LR, Schwenkmezger P, Weinman J, Maes S, editors, Theoretical and applied aspects of health psychology. Harwood Academic Publishers; 1990. pp.185–202
• 39. Meta Data for Good. COVID-19 Trends and Impact Survey: Meta; 2021. https://dataforgood.facebook.com/dfg/tools/covid-19-trends-and-impact-survey#accessdata .

• COVID-19 and your mental health

Worries and anxiety about COVID-19 can be overwhelming. Learn ways to cope as COVID-19 spreads.

At the start of the COVID-19 pandemic, life for many people changed very quickly. Worry and concern were natural partners of all that change — getting used to new routines, loneliness and financial pressure, among other issues. Information overload, rumor and misinformation didn't help.

Worldwide surveys done in 2020 and 2021 found higher than typical levels of stress, insomnia, anxiety and depression. By 2022, levels had lowered but were still higher than before 2020.

Though feelings of distress about COVID-19 may come and go, they are still an issue for many people. You aren't alone if you feel distress due to COVID-19. And you're not alone if you've coped with the stress in less than healthy ways, such as substance use.

But healthier self-care choices can help you cope with COVID-19 or any other challenge you may face.

And knowing when to get help can be the most essential self-care action of all.

Recognize what's typical and what's not

Stress and worry are common during a crisis. But something like the COVID-19 pandemic can push people beyond their ability to cope.

In surveys, the most common symptoms reported were trouble sleeping and feeling anxiety or nervous. The number of people noting those symptoms went up and down in surveys given over time. Depression and loneliness were less common than nervousness or sleep problems, but more consistent across surveys given over time. Among adults, use of drugs, alcohol and other intoxicating substances has increased over time as well.

The first step is to notice how often you feel helpless, sad, angry, irritable, hopeless, anxious or afraid. Some people may feel numb.

Keep track of how often you have trouble focusing on daily tasks or doing routine chores. Are there things that you used to enjoy doing that you stopped doing because of how you feel? Note any big changes in appetite, any substance use, body aches and pains, and problems with sleep.

These feelings may come and go over time. But if these feelings don't go away or make it hard to do your daily tasks, it's time to ask for help.

Get help when you need it

If you're feeling suicidal or thinking of hurting yourself, seek help.

• Contact your healthcare professional or a mental health professional.
• Contact a suicide hotline. In the U.S., call or text 988 to reach the 988 Suicide & Crisis Lifeline , available 24 hours a day, seven days a week. Or use the Lifeline Chat . Services are free and confidential.

If you are worried about yourself or someone else, contact your healthcare professional or mental health professional. Some may be able to see you in person or talk over the phone or online.

You also can reach out to a friend or loved one. Someone in your faith community also could help.

And you may be able to get counseling or a mental health appointment through an employer's employee assistance program.

Another option is information and treatment options from groups such as:

• National Alliance on Mental Illness (NAMI).
• Substance Abuse and Mental Health Services Administration (SAMHSA).
• Anxiety and Depression Association of America.

Self-care tips

Some people may use unhealthy ways to cope with anxiety around COVID-19. These unhealthy choices may include things such as misuse of medicines or legal drugs and use of illegal drugs. Unhealthy coping choices also can be things such as sleeping too much or too little, or overeating. It also can include avoiding other people and focusing on only one soothing thing, such as work, television or gaming.

Unhealthy coping methods can worsen mental and physical health. And that is particularly true if you're trying to manage or recover from COVID-19.

Self-care actions can help you restore a healthy balance in your life. They can lessen everyday stress or significant anxiety linked to events such as the COVID-19 pandemic. Self-care actions give your body and mind a chance to heal from the problems long-term stress can cause.

Take care of your body

Healthy self-care tips start with the basics. Give your body what it needs and avoid what it doesn't need. Some tips are:

• Get the right amount of sleep for you. A regular sleep schedule, when you go to bed and get up at similar times each day, can help avoid sleep problems.
• Move your body. Regular physical activity and exercise can help reduce anxiety and improve mood. Any activity you can do regularly is a good choice. That may be a scheduled workout, a walk or even dancing to your favorite music.
• Choose healthy food and drinks. Foods that are high in nutrients, such as protein, vitamins and minerals are healthy choices. Avoid food or drink with added sugar, fat or salt.
• Avoid tobacco, alcohol and drugs. If you smoke tobacco or if you vape, you're already at higher risk of lung disease. Because COVID-19 affects the lungs, your risk increases even more. Using alcohol to manage how you feel can make matters worse and reduce your coping skills. Avoid taking illegal drugs or misusing prescriptions to manage your feelings.

Take care of your mind

Healthy coping actions for your brain start with deciding how much news and social media is right for you. Staying informed, especially during a pandemic, helps you make the best choices but do it carefully.

Set aside a specific amount of time to find information in the news or on social media, stay limited to that time, and choose reliable sources. For example, give yourself up to 20 or 30 minutes a day of news and social media. That amount keeps people informed but not overwhelmed.

For COVID-19, consider reliable health sources. Examples are the U.S. Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO).

Other healthy self-care tips are:

• Relax and recharge. Many people benefit from relaxation exercises such as mindfulness, deep breathing, meditation and yoga. Find an activity that helps you relax and try to do it every day at least for a short time. Fitting time in for hobbies or activities you enjoy can help manage feelings of stress too.
• Stick to your health routine. If you see a healthcare professional for mental health services, keep up with your appointments. And stay up to date with all your wellness tests and screenings.
• Stay in touch and connect with others. Family, friends and your community are part of a healthy mental outlook. Together, you form a healthy support network for concerns or challenges. Social interactions, over time, are linked to a healthier and longer life.

Avoid stigma and discrimination

Stigma can make people feel isolated and even abandoned. They may feel sad, hurt and angry when people in their community avoid them for fear of getting COVID-19. People who have experienced stigma related to COVID-19 include people of Asian descent, health care workers and people with COVID-19.

Treating people differently because of their medical condition, called medical discrimination, isn't new to the COVID-19 pandemic. Stigma has long been a problem for people with various conditions such as Hansen's disease (leprosy), HIV, diabetes and many mental illnesses.

People who experience stigma may be left out or shunned, treated differently, or denied job and school options. They also may be targets of verbal, emotional and physical abuse.

Communication can help end stigma or discrimination. You can address stigma when you:

• Get to know people as more than just an illness. Using respectful language can go a long way toward making people comfortable talking about a health issue.
• Get the facts about COVID-19 or other medical issues from reputable sources such as the CDC and WHO.
• Speak up if you hear or see myths about an illness or people with an illness.

COVID-19 and health

The virus that causes COVID-19 is still a concern for many people. By recognizing when to get help and taking time for your health, life challenges such as COVID-19 can be managed.

• Mental health during the COVID-19 pandemic. National Institutes of Health. https://covid19.nih.gov/covid-19-topics/mental-health. Accessed March 12, 2024.
• Mental Health and COVID-19: Early evidence of the pandemic's impact: Scientific brief, 2 March 2022. World Health Organization. https://www.who.int/publications/i/item/WHO-2019-nCoV-Sci_Brief-Mental_health-2022.1. Accessed March 12, 2024.
• Mental health and the pandemic: What U.S. surveys have found. Pew Research Center. https://www.pewresearch.org/short-reads/2023/03/02/mental-health-and-the-pandemic-what-u-s-surveys-have-found/. Accessed March 12, 2024.
• Taking care of your emotional health. Centers for Disease Control and Prevention. https://emergency.cdc.gov/coping/selfcare.asp. Accessed March 12, 2024.
• #HealthyAtHome—Mental health. World Health Organization. www.who.int/campaigns/connecting-the-world-to-combat-coronavirus/healthyathome/healthyathome---mental-health. Accessed March 12, 2024.
• Coping with stress. Centers for Disease Control and Prevention. www.cdc.gov/mentalhealth/stress-coping/cope-with-stress/. Accessed March 12, 2024.
• Manage stress. U.S. Department of Health and Human Services. https://health.gov/myhealthfinder/topics/health-conditions/heart-health/manage-stress. Accessed March 20, 2020.
• COVID-19 and substance abuse. National Institute on Drug Abuse. https://nida.nih.gov/research-topics/covid-19-substance-use#health-outcomes. Accessed March 12, 2024.
• COVID-19 resource and information guide. National Alliance on Mental Illness. https://www.nami.org/Support-Education/NAMI-HelpLine/COVID-19-Information-and-Resources/COVID-19-Resource-and-Information-Guide. Accessed March 15, 2024.
• Negative coping and PTSD. U.S. Department of Veterans Affairs. https://www.ptsd.va.gov/gethelp/negative_coping.asp. Accessed March 15, 2024.
• Health effects of cigarette smoking. Centers for Disease Control and Prevention. https://www.cdc.gov/tobacco/data_statistics/fact_sheets/health_effects/effects_cig_smoking/index.htm#respiratory. Accessed March 15, 2024.
• People with certain medical conditions. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-with-medical-conditions.html. Accessed March 15, 2024.
• Your healthiest self: Emotional wellness toolkit. National Institutes of Health. https://www.nih.gov/health-information/emotional-wellness-toolkit. Accessed March 15, 2024.
• World leprosy day: Bust the myths, learn the facts. Centers for Disease Control and Prevention. https://www.cdc.gov/leprosy/world-leprosy-day/. Accessed March 15, 2024.
• HIV stigma and discrimination. Centers for Disease Control and Prevention. https://www.cdc.gov/hiv/basics/hiv-stigma/. Accessed March 15, 2024.
• Diabetes stigma: Learn about it, recognize it, reduce it. Centers for Disease Control and Prevention. https://www.cdc.gov/diabetes/library/features/diabetes_stigma.html. Accessed March 15, 2024.
• Phelan SM, et al. Patient and health care professional perspectives on stigma in integrated behavioral health: Barriers and recommendations. Annals of Family Medicine. 2023; doi:10.1370/afm.2924.
• Stigma reduction. Centers for Disease Control and Prevention. https://www.cdc.gov/drugoverdose/od2a/case-studies/stigma-reduction.html. Accessed March 15, 2024.
• Nyblade L, et al. Stigma in health facilities: Why it matters and how we can change it. BMC Medicine. 2019; doi:10.1186/s12916-019-1256-2.
• Combating bias and stigma related to COVID-19. American Psychological Association. https://www.apa.org/topics/covid-19-bias. Accessed March 15, 2024.
• Yashadhana A, et al. Pandemic-related racial discrimination and its health impact among non-Indigenous racially minoritized peoples in high-income contexts: A systematic review. Health Promotion International. 2021; doi:10.1093/heapro/daab144.
• Sawchuk CN (expert opinion). Mayo Clinic. March 25, 2024.

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The COVID-19 pandemic has had a huge impact on public health around the globe in terms of both physical and mental health, and the mental health implications of the pandemic may continue long after the physical health consequences have resolved. This research area aims to contribute to our understanding of the COVID-19 pandemics implications for mental health, building on a robust literature on how environmental crises, such as SARS or natural disasters, can lead to mental health challenges, including loneliness, acute stress, anxiety, and depression. The social distancing aspects of the COVID-19 pandemic may have particularly significant effects on mental health. Understanding how mental health evolves as a result of this serious global pandemic will inform prevention and treatment strategies moving forward, including allocation of resources to those most in need. Critically, these data can also serve as evidence-based information for public health organizations and the public as a whole.

Understanding the Mental Health Implications of a Pandemic

Introduction

The world is entering into a new phase with COVID-19 spreading rapidly. People will be studying various consequences of the COVID-19 pandemic and mental and behavioral health should be a core part of that effort. There is a robust literature on how environmental crises, such as SARS or natural disasters, can lead to mental health challenges, including loneliness, acute stress, anxiety, and depression. The social distancing aspects of the current pandemic may have particularly significant effects on mental health. Understanding how mental health evolves as a result of this serious global outbreak will inform prevention and treatment strategies moving forward, including allocation of resources to those most in need. Critically, these data can also serve as evidence-based information for public health organizations and the public as a whole.

The data will be leveraged to address many questions, such as:

• Which individuals are at greatest risk for high levels of mental health distress during a pandemic?
• As individuals spend more time inside and isolated, how does their mental health distress evolve?
• How do different behaviors (such as media consumption) relate to mental health? 

Read more about how our experts are measuring mental distress amid a pandemic.  

We have been working to ensure that measurement of mental health measures is a key part of large-scale national and international data collections relative to COVID-19.

Read more about conducting research studies on mental health during the pandemic. 

Mental Health Resources

See our resources guide here.

Members of the COVID-19 Mental Health Measurement Working Group

• M. Daniele Fallin, JHSPH
• Calliope Holingue, Kennedy Krieger Institute, JHSPH
• Renee M. Johnson, JHSPH
• Luke Kalb, Kennedy Krieger Institute, JHSPH
• Frauke Kreuter, University of Maryland, University of Mannheim
• Courtney Nordeck, JHSPH
• Kira Riehm, JHSPH
• Emily J. Smail, JHSPH
• Elizabeth Stuart, JHSPH
• Johannes Thrul, JHSPH
• Cindy Veldhuis, Columbia University School of Nursing

The Johns Hopkins COVID-19 Mental Health Measurement Working Group developed key questions to add to existing large domestic and international surveys to measure the mental health impact of the pandemic.

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The impact of coronavirus on mental health

Our research found that those who were more likely to struggle with their mental health before the pandemic were most affected by coronavirus.

What we found in our coronavirus research

Following on from research we did in 2020, we launched a survey in April 2021 to find out how people with mental health problems were coping.

We heard from almost 12,000 people across England and Wales. We found:

• Around a third of adults and young people said their mental health has got much worse since March 2020.
• 58% of people receiving benefits  said their mental health was poor.
• 88% of young people  said loneliness made their mental health worse during the pandemic.
• 1 in 5 adults did not seek support during the pandemic because they didn’t think their problem was serious enough.

"Since March 2020 my mental health deteriorated and by the end of 2020 I was at breaking point once again."

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Watch this video to hear from Anisah, Maccartney and Blake about their experiences during coronavirus.

First you'll hear from Anisah. Next you'll hear Blake, who found the change in his support during the pandemic made it difficult for him to cope. Finally you'll hear from Maccartney, who shares how he coped by reaching out for help.

"What we've been through is massive, and it's OK to give yourself time to deal with how you're feeling."

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Mental Health Research During the COVID-19 Pandemic: Focuses and Trends

Affiliations.

• 1 Law School, Changsha University, Changsha, China.
• 2 Department of Psychology, University of Toronto St. George, Toronto, ON, Canada.
• 3 Centre for Mental Health and Education, Central South University, Changsha, China.
• PMID: 35958839
• PMCID: PMC9360762
• DOI: 10.3389/fpubh.2022.895121

Background: The COVID-19 pandemic has profoundly influenced the world. In wave after wave, many countries suffered from the pandemic, which caused social instability, hindered global growth, and harmed mental health. Although research has been published on various mental health issues during the pandemic, some profound effects on mental health are difficult to observe and study thoroughly in the short term. The impact of the pandemic on mental health is still at a nascent stage of research. Based on the existing literature, we used bibliometric tools to conduct an overall analysis of mental health research during the COVID-19 pandemic.

Method: Researchers from universities, hospitals, communities, and medical institutions around the world used questionnaire surveys, telephone-based surveys, online surveys, cross-sectional surveys, systematic reviews and meta-analyses, and systematic umbrella reviews as their research methods. Papers from the three academic databases, Web of Science (WOS), ProQuest Academic Database (ProQuest), and China National Knowledge Infrastructure (CNKI), were included. Their previous research results were systematically collected, sorted, and translated and CiteSpace 5.1 and VOSviewers 1.6.13 were used to conduct a bibliometric analysis of them.

Result: Authors with papers in this field are generally from the USA, the People's Republic of China, the UK, South Korea, Singapore, and Australia. Huazhong University of Science and Technology, Hong Kong Polytechnic University, and Shanghai Jiao Tong University are the top three institutions in terms of the production of research papers on the subject. The University of Toronto, Columbia University, and the University of Melbourne played an important role in the research of mental health problems during the COVID-19 pandemic. The numbers of related research papers in the USA and China are significantly larger than those in the other countries, while co-occurrence centrality indexes in Germany, Italy, England, and Canada may be higher.

Conclusion: We found that the most mentioned keywords in the study of mental health research during the COVID-19 pandemic can be divided into three categories: keywords that represent specific groups of people, that describe influences and symptoms, and that are related to public health policies. The most-cited issues were about medical staff, isolation, psychological symptoms, telehealth, social media, and loneliness. Protection of the youth and health workers and telemedicine research are expected to gain importance in the future.

Keywords: COVID-19; bibliometric analysis; focuses; keyword clustering; mental health; trends.

Copyright © 2022 Liang, Sun and Tan.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The volume of COVID-19 and…

The volume of COVID-19 and mental health-related articles in 2020–2022.

Country or region co-occurrence.

Author co-occurrence.

Author co-occurrence groups.

Institutions' co-occurrence.

Keyword clustering.

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• Published: 11 November 2021

An evaluation of eye movement desensitization and reprocessing therapy delivered remotely during the Covid–19 pandemic

• Iain W. McGowan 1 ,
• Naomi Fisher 2 ,
• Justin Havens 3 &
• Simon Proudlock 4  

BMC Psychiatry volume  21 , Article number:  560 ( 2021 ) Cite this article

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In addition to having a negative impact on the physical and emotional health of the population, the global Covid–19 pandemic has necessitated psychotherapists moving their practice to online environments. This service evaluation examines the efficacy of Eye Movement Desensitization and Reprocessing (EMDR) Therapy delivered via the internet.

A real–world service evaluation was conducted from a self–selecting group of EMDR therapists that subscribe to either a JISCMail discussion list or either the UK or All Ireland National EMDR Associations. Author designed questionnaires were used to gather information on the efficacy of EMDR delivered online as well as client and therapist characteristics.

Thirty-three therapists provided efficacy data on a total of 93 patients. Statistically significant and clinically meaningful reductions were found in all four-psychometrics used both in adult and children and young people populations. Client outcome was not related to therapist experience.

Conclusions

EMDR delivered via the internet can be an effective treatment for clients experiencing mental health issues.

Peer Review reports

Eye Movement Desensitization and Reprocessing therapy (EMDR) is an effective, evidence–based treatment for the treatment of several mental health issues including post–traumatic stress disorder (PTSD), depression, anxiety and eating disorders. It is recommended as a first line intervention for people experiencing symptoms associated with PTSD by the ISTSS [ 1 ] and the World Health Organization [ 2 ]. The UK, National Institute of Health and Care Excellence (NICE) [ 3 ] recommend using EMDR where trauma focused Cognitive Behavioural Therapy (CBT) is unsuccessful or the client declines CBT.

EMDR is guided by the adaptive information processing model [ 4 ] The model posits that current PTSD symptomatology is a result of maladaptive information processing of unprocessed memories stored in the brain. EMDR therapy suggests that after a traumatic experience, information processing is developed using bilateral stimulation of each brain hemisphere “resulting in new learning, elimination of emotional distress, and development of cognitive insights” [ 5 ].

The Covid–19 pandemic has had a negative impact on the mental health of the general population. In the last year, several meta–analyses have been published reporting the negative impact Covid–19 has had on the general public [ 6 ], healthcare workers [ 6 ], people living with physical health problems such as cancer [ 7 ] and those with pre–existing mental health issues [ 8 ]. This impact has been felt globally. In China, Hao et al. (2020) [ 8 ] surveyed 76 people currently in treatment for a mental health problem and 109 without. They found statistically significant differences between the group in levels of PTSD symptoms experienced, depression, anxiety and insomnia. Similar findings are reported in Saudi Arabia [ 9 ], Pakistan [ 10 ] and the Philippines [ 11 ]. In the United Kingdom, Pierce et al. [ 12 ] report a significant decline of the mental health of the general population between the start of the pandemic and April 2020. Negative impacts of Covid 19 are found in the general population in Spain [ 13 ], amongst the student population in Greece [ 14 ] and the Philippines [ 11 ], and amongst healthcare workers in Italy [ 6 ].

Most Government responses to the Covid 19 pandemic included some form of, what became colloquially known in the UK as ‘lockdown’. However, social isolation and withdrawal have long been associated with the onset of mental health problems [ 15 ]. Consequently, the potential for harm from protective policies is apparent. Tien– Huy et al. (2021) [ 16 ] conducted a global survey across 63 countries to assess the impact of quarantine/ isolation on the psychological well–being of individuals ( n  = 1871). They found a statistically significant positive association between the number of days in quarantine and increased perceived stress levels. A significant positive association was also found between perceived stress levels and being exposed to a suspected or a confirmed positive case of Covid–19 [ 16 ].

Similar findings are reported by the TMGH–Global COVID–19 Collaborative (2021) [ 17 ]. This collaborative sought to examine the presence of PTSD in individuals in insolation/ quarantine. Drawing on results from 944 responses across 57 countries, they report that people experiencing symptoms of Covid − 19 and were forced to isolate reported more PTSD than those isolating for other reasons. Being made to isolate also increased the risk of developing PTSD in comparison to voluntarily entering a period of quarantine (OR: 2.92: 95% CI: 1.84–4.74: p  < 0.001).

It is important to recognise that, in addition to the pandemic, governments and their populations have also had to manage natural and man-made disasters that have had an impact on the mental health of individuals. For example, during 2020, the Philippines was hit by 22 tropical cyclones [ 18 ]. Rocha et al. (2021) [ 18 ] suggest that has resulted in population displacement, increased socio– economic burden on individuals and families and sudden bereavement which coupled with the pandemic may increase susceptibility to psychological distress.

Islam et al. (2021) [ 19 ] considered the psychological impact of multiple “converging systems” (p112) on the healthcare workforce. In a commentary article they argue that Yemeni healthcare workers are faced with longer working hours, no or delayed salary payments, exposure to traumatic events (either from Covid or as a result of war), an increased risk of catching Covid–19 and stigmatization. This, they contend has ed. to increased levels of PTSD, anxiety disorders, lower self-efficacy and “increased detachment from the workplace” (p113).

This has resulted in not only increased demand, but also limited access to mental health services due to mental health staff reallocation to Covid related duties, closure of out–patient services and restriction on businesses providing in person services. The initial United Kingdom Government response to the pandemic necessitated the closure of the majority of publicly funded and all private providers therapy offices requiring therapists to move their practice online.

Online psychotherapy is not new. For example, Christensen et al. [ 20 ] reported the effectiveness of the computerized MoodGym CBT programme for anxiety and depression over 15 years ago. More recently, Kuhn et al. [ 21 ] explored the effectiveness of a CBT based app designed to reduce PTSD symptoms. They report statistically significant improvements in PTSD symptoms, depressive symptoms and social functioning. NICE produced guidelines for the remote delivery of psychological therapies and recommended a number of ‘digital therapies’ for various mental health problems including depression, anxiety, substance misuse and body dysmorphic disorder [ 22 ]. Interestingly, no digital interventions for trauma specific presentations have been assessed. Additionally, these studies focus on therapy delivered through an app or webpage, where no therapist has direct involvement in the treatment.

Remote delivery of psychotherapy, where the client works with a therapist online or via the telephone [ 23 ] has been found to be both effective and acceptable to clients experiencing PTSD symptoms. Knaevelsrud & Maercker [ 24 ] compared CBT delivered via the internet against a waitlist control. They found statistically significant differences in PTSD symptomatology between the two groups after ten sessions delivered over a five-week period. Khun & Owen [ 21 ] carried out a systematic review. They found that PTSD therapy delivered remotely was as effective as in–person treatment although they note that the samples for the papers included in their reviews were primarily military veterans and male, limiting the generalization of their findings.

It is possible that online delivery of therapy could address some of the factors associated with dropout from therapy [ 25 ]. Low/ hourly paid work and travel time and cost have previously been identified as factors that drive attrition rates from therapy [ 26 ]. The flexibility afforded by online therapy may improve retention rates and, theoretically, clinical outcome [ 27 ].

Online EMDR

EMDR therapists have been successfully treating clients remotely over the internet [ 28 ]. However, peer reviewed reports on the efficacy of EMDR delivered via the internet are scant. Lenferink Meyerbroker & Boelen [ 29 ] specifically sought papers investigating the efficacy on EMDR online. They found a single uncontrolled study [ 30 ] that used internet-based CBT with a web based EMDR tool– iEMDR. The iEMDR is reported to be based on the standard eight–phase protocol outlined by Shapiro [ 4 ] adapted for internet delivery. The web link provided in the paper ( https://www.rapidtables.com/tool/EMDR.html ) is inactive, thus it is not possible to verify this claim. Fifteen participants started the intervention with 11 completing. Nine participants completed the follow up questionnaires, although the time to follow up is not reported. Spence et al. [ 30 ] reported statistically significant improvements in PTSD and anxiety symptoms. The small sample size and lack of control group should counsel against generalizing their findings.

Tarquinio et al. [ 31 ] investigated the efficacy of a single EMDR session in reducing anxiety and depression levels as well as the perceived subjective level of disturbance. Seventeen nurses who were in treatment for non–Covid related issues in France had a single session of EMDR, through a video conferencing platform, using the URG–EMDR protocol [ 24 ]. They report statistically significant reductions in anxiety, depression, subjective distress, fear of returning to their workplace and fearing for their safety in relation to Covid ( p  < 0.05).

Lazzaroni et al. (2021) [ 32 ] used the EMDR protocols for Acute and Recent Traumatic events [ 33 ] with a group of adolescents and young adults currently receiving mental healthcare services ( n  = 50 (age 13– 24 years)). The participants received 3 × 1 h sessions delivered online. Lazzaroni et al. report significant improvements in anxiety levels and post–traumatic symptomatology ( p  = 0.05) post intervention.

The small sample sizes and lack of control groups in the two studies above should impress the need for caution when interpreting these findings. However, the studies provide some evidence to support the use of EMDR online.

The bilateral stimulation inherent in EMDR therapy can be delivered in several ways from asking clients to follow the therapists’ hand or wand as the therapist moves it from side to side [ 34 ]. Alternate hand taps and butterfly hugs can also be used, as can smartphones applications that deliver sounds to alternate ears [ 35 ].

We are aware of on–going RCT’s investigating the effectiveness of EMDR in an online environment [ 36 ]. This paper seeks to expand the published literature on using EMDR online.

The aim of this service evaluation was to determine evaluate the efficacy of the online delivery of EMDR therapy. Specifically, we sought to answer the following questions;

Does EMDR delivered online reduce clinical symptoms of common mental health presentations?

Does the level of EMDR accreditation or number of years’ experience using EMDR influence the overall client outcome?

Recruitment of therapists & clients

EMDR therapists were recruited through the EMDR UK and Ireland JISCMail mailing list, and direct email from the EMDR UK Association (circulation 4200 therapists). The JISCMail list is an opt–in discussion forum where subscribers engage in discussion regarding EMDR. It currently has circa 1700 subscribers. Members of both the UK EMDR Association and the JISCMail mailing list are required to have undergone an approved training course and to be practicing under supervision in accordance with EMDR Europe and/or the EMDR International Association standards. We adopted a full population approach to the evaluation and as such all members of either organization were eligible to take part. No exclusion criteria were applied.

A generic mail was sent to all subscribers inviting them to take part. Interested therapists were directed to an online form that detailed the evaluation. Therapists deciding to participate provided details in respect of their level, EMDR experience, and clinical assessment tools used. Participating therapists were then asked to complete an online form giving anonymized information of client’s presentation and outcome. As the authors had no direct contact with the clients, therapists were instructed to ensure that clients had given informed consent for their anonymized data to be used. The EMDR UK Association provided support for a random draw of participating therapists where the prize was one of three £20 gift vouchers. Suggested text regarding consent for therapists to include in their treatment plans/ consent forms was provided. Recruitment of therapists and data collection took place from May 2020–Dec 2020. Google Forms was used to collect data.

Using the algorithm provided by the UK National Health Research Authority and UK Policy Framework for Health and Social Care Research definition of research [ 37 ] this project was not classified as research but as a service evaluation [ 38 ]. As such formal IRB ethical approval was not required [ 38 ]. All participants were provided with an electronic information sheet that detailed the background and the aims of the study as well as the requirements of taking part. Respondents gave written informed consent to take part in the evaluation, and all processes undertaken in the evaluation were carried out in accordance with relevant guidelines and policies.

Data collection and analysis

Author designed surveys were used to collect the data. Data collected from the therapists is reported below and participating therapists then provided anonymized data on their clients including their gender, age, primary psychiatric reason for referral, pre– and post–treatment scores and the outcome measures used in practice. Given the heterogeneity of the assessment and outcomes tools used by EMDR therapists, and this project’s status as an evaluation of existing practice we did not put any restriction on the measures used by the therapist. We asked participating therapists to provide overall pre and post treatment scores in relation to the Impact of Events Scale– Revised (IES–R) [ 39 ], the General Anxiety Disorder 7 scale (GAD–7) [ 40 ], the Public Health Questionnaire 9 scale (PHQ–9) [ 41 ] and the PTSD Checklist (PCL–5) [ 42 ] and any other assessment scales they normally use for each of their clients.. Thesescales are widely used in PTSD research and clinical practice and have been shown to have good reliability and validity. Twenty five of the 33 therapists used one of the four scales above.

Of the eight that did not use any of these scales, the Subjective Units of Distress and Validity of Cognition scales [ 4 ] used routinely in EMDR therapy were reported as outcomes by one of the therapists. Other scales used by therapists were the HADS ( n  = 1) [ 43 ], the CORE ( n  = 1) [ 44 ], GHQ ( n  = 1) [ 45 ], BDI ( n –1) [ 46 ], BAI ( n  = 1) [ 47 ], AUDIT ( n  = 1) [ 48 ], DES–II ( n  = 1) [ 49 ], the Worry about Sexual Outcomes scale ( n  = 1) [ 50 ], ITQ ( n  = 2) [ 51 ], the Moral Disengagement Scale ( n  = 1) [ 52 ], the Work and Social Adjustment Scale ( n  = 2) [ 53 ], the Driving Cognitions Questionnaire ( n  = 1) [ 54 ], and the CRIES 13 ( n  = 1) [ 55 ]. Recognizing the very small numbers using these different assessment tools we have not reported these in this paper.

Descriptive statistics are reported for both therapists and clients. The Shapiro–Wilk test for normality returned non–significant statistics suggesting normal distribution of data. Accordingly, Student t–test was used to identify significant differences between pre– and post–treatment scores. Statistical significance was set at 0.05 throughout. Minimal clinically important differences were calculated using the distribution method [ 56 ] where a difference of half the standard deviation is recognised as being clinically important. In order to address the second research question, a third dataset was constructed combining the therapist and client details to allow for cross tabulation of outcome and anonymized therapist details. The Pearson r correlation statistic was used to explore relationships between the length of time the therapist had been practicing EMDR and each of the clinical outcomes. Analysis of variance (ANOVA) was used to ascertain differences between level of accreditation and clinical outcome. A dichotomous variable of aged 18 or over and under the age of 18 was created. ANOVA was used to explore any differences in outcome by age of the client. JASP software was used to conduct the statistical analysis.

Thirty-three therapists provided data on a total of 93 different clients. The therapists’ mean length of time since training in EMDR was 8.5 years (sd: 4.8 yrs.: range (0.5–17.5 yrs). Eight of the therapists were trained to Consultant Level, 10 were accredited EMDR therapists and the 12 had completed initial EMDR training and were working towards accreditation.

Of the 93 clients for whom data was provided, 62 (66%) identified as female, 30 (33%) as male and 1 as non–binary (1%). Ages ranged from 10 years to 72 (mean 35.5 sd 15.6 years). Thirteen (14%) of the clients were under the age of 18 years.

Psychological trauma (simple and complex) was the most common reason for seeking help, followed by anxiety and depression. Table  1 shows the reasons for referral. One of the 93 participants sought help for Covid related problems.

Statistically significant and clinically important reductions in the reported client mean scores of the IES(R), the GAD–7, the PHQ–9 and the PCL–5 checklist was found (Table  2 ). Large effect sizes post–treatment was also found. Minimal clinically important difference thresholds were set at 9.10 (IES(R)), 2.61 (GAD–7), 3.64 (PHQ–9) and 6.64 (PCL–5). No significant relationship was found between length of time trained in EMDR and any of the clinical outcomes, nor was there any significant difference in the association between level of accreditation and clinical outcome. No significant differences were found in any of the four outcomes between genders or between those aged under 18 years and clients aged 18 and over.

This appears to be the first evaluation to report the efficacy of using the standard eight phase EMDR protocol delivered through an online medium. Using real world data, we have shown that EMDR can reduce symptomatology regardless of the age, gender or clinical presentation of the client. The findings also show that length of time practicing EMDR and level of accreditation in EMDR are not associated with outcome, suggesting that EMDR can be used successfully regardless of experience after EMDR training.

Notwithstanding the limitations outlined below, the large effect sizes found are encouraging. A recent systematic review [ 57 ] reported a small to moderate pooled effect size (Hedges g = 0.33) [ 57 ] across 23 studies using EMDR delivered in the same room as the client for the treatment of PTSD, and a large pooled effect size across 10 studies for the treatment of anxiety disorders (Hedges g = 1.07) [ 57 ].

We are also encouraged by the apparent similarities in efficacy reported by therapists working with children and young people and those working with the adult population. This is in keeping with studies that report EMDR as an effective treatment for children and young people (CYP) that have experienced a traumatic event and that clinical improvement using EMDR is independent of demographic variables such as age [ 58 ]. For example, in a meta– analysis comparing trauma based approaches to treating PTSD in CYP Khan et al. [ 58 ] reported EMDR to be more effective than CBT in reducing PTSD symptoms (SDM (95% CI) = − 0.43 (− 0.73 – –0.12), p  = 0.006) and anxiety symptoms (SDM (95% CI) = − 0.71 (− 1.21 – –0.21), p  = 0.005). Lazzaroni et al. (2021) [ 32 ] and Jeon et al. (2017) [ 59 ] have shown that age is not correlated with either reductions in PTSD symptoms [ 32 ] or Post Traumatic growth [ 59 ].

Our findings allude to EMDR being as effective when delivered remotely as face to face, in line with the findings of Kuhn & Owen [ 21 ] We also note that the effect sizes reported here are in excess of those reported in meta–analyses of the CBT interventions (0.66 < g < 0.83) delivered via the internet when compared to passive controls (no treatment or wait list control) [ 60 ]. Interestingly, they also found that internet CBT was superior to active control groups [ 60 ].

As with other psychotherapies, remote delivery of EMDR has significant potential benefits to clients including the reduction in travel time to and from appointments and loss of salary to attend appointments [ 25 ] as well as a reduction in stigma associated with mental health treatment [ 61 ]. Clients have control over their environment and smartphone apps that deliver clicks via earphones alternately give the client more control of the session [ 23 ]. Other applications such as bilateralstimulation.io also provide online platforms for the delivery of the bilateral stimulations used in EMDR. Additionally, internet delivered interventions have been found to be a cost–effective way to deliver psychological interventions [ 39 ].

Conversely, when considering working with clients remotely therapists need to be cognisant of potential distractions such as children, deliveries and phone calls during the sessions [ 23 ] [ 27 ]. Fisher (2021) [ 23 ] also acknowledges that the home environment may not always be a safe environment for the client to undergo EMDR therapy and therapists need to be cognisant of this when considering online work with clients.

Having access to the internet is, obviously, a pre–requisite for online therapy. Cleofas et al. (2021) [ 62 ] surveyed 952 college students and report that computer ownership and access to the internet are associated with lower levels of Covid–19 related anxieties. Rubin (2021) [ 63 ] argues that internet access should now be a social determinant of health. She notes that internet access increases with income. Subsequently, therapists need to be cognisant of the stigma associated with poverty [ 64 ] and the potential for those living in poverty to portray a more positive outlook than their current situation [ 65 ] when considering moving therapy online.

Limitations

This evaluation has several limitations. There is a potential for ‘gatekeeper bias’, where there is the possibility that therapists providing data may only have submitted data for clients that showed improvement. We also recognise that despite high initial interest, a relatively small number of therapists provided client data. This may suggest a self–selecting group with a bias toward online EMDR. The lack of a control group and small sample size of both therapists and clients also precludes us making any generalised claims. Although we note above that client outcome appears to be independent of level of experience as an EMDR therapist, we did not collect data on previous experience of online therapy undertaken by therapist prior to the pandemic. Subsequently, we cannot comment on therapist experience working online and the impact that that may have on clinical outcome. As noted above, we are aware of several on–going Randomised Controlled Trials exploring the effectiveness of EMDR in an online environment that may address these limitations.

This evaluation appears to be the first paper to report the efficacy of EMDR delivered online using real world practice data. Our findings show that a reduction in clinical symptoms can be achieved using EMDR online, however recognising the limitations of this evaluation we would urge caution in interpreting the findings. Clinical trials examining the clinical and cost effectiveness of online EMDR are required.

The Covid 19 pandemic required EMDR therapists to adopt creative and flexible responses to help meet the needs of the clients [ 18 ]. Office closures and travel restrictions to and from work meant that therapists had to move their work to online. The findings of this evaluation suggest that they did so successfully.

Availability of data and materials

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

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McGowan, I.W., Fisher, N., Havens, J. et al. An evaluation of eye movement desensitization and reprocessing therapy delivered remotely during the Covid–19 pandemic. BMC Psychiatry 21 , 560 (2021). https://doi.org/10.1186/s12888-021-03571-x

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Addressing the unprecedented behavioral-health challenges facing Generation Z

Nearly two years after the COVID-19 pandemic began in the United States, Gen Zers, ranging from middle school students to early professionals, are reporting higher rates of anxiety, depression, and distress than any other age group. 1 Ages for Generation Z can vary, with some analysis including ages as young as nine. In this article, we focus on those between the ages of 16 and 24, and define millennials as 25 to 40; Ramin Mojtabai and Mark Olfson, “National trends in mental health care for US adolescents,” JAMA Psychiatry , March 25, 2020, Volume 77, Number 7; Martin Seligman, The Optimistic Child: A Revolutionary Approach to Raising Resilient Children , Boston, MA: Mariner Books, 2007; Gen Z respondents are 1.5 times as likely to report having felt anxious or depressed, compared with the average respondent, according to the McKinsey Consumer Health Insights Survey, conducted in June 2021—a nationally representative survey of 2,906 responses, including 316 Gen Z responses. The mental-health challenges among this generation are so concerning that US surgeon general Vivek Murthy issued a public health advisory on December 7, 2021, to address the “youth mental health crisis” exacerbated by the COVID-19 pandemic. 2 Protecting youth mental health: US surgeon general’s advisory , Office of the Surgeon General, December 7, 2021.

About the authors

The article is a collaborative effort by Erica Coe , Jenny Cordina , Kana Enomoto , Raelyn Jacobson , Sharon Mei, and Nikhil Seshan, representing views of the McKinsey’s Healthcare Systems & Services and Public & Social Sector Practices.

A series of consumer surveys and interviews conducted by McKinsey indicate stark differences among generations, with Gen Z  reporting the least positive life outlook, including lower levels of emotional and social well-being than older generations. One in four Gen Z respondents reported feeling more emotionally distressed (25 percent), almost double the levels reported by millennial and Gen X respondents (13 percent each), and more than triple the levels reported by baby boomer respondents (8 percent). 3 These research efforts have been focused on Gen Zers between the ages of 16 and 24 when compared with samples of millennials (aged 25 to 40), Gen Xers (aged 41 to 56), and baby boomers (aged 57 to 76). And the COVID-19 pandemic has only amplified this challenge (see sidebar, “The disproportionate impact of the COVID-19 pandemic”). While consumer surveys are, of course, subjective and Gen Z is not the only generation to experience distress, employers, educators, and public health leaders may want to consider the sentiment of this emerging generation as they plan for the future.

The disproportionate impact of the COVID-19 pandemic

While Gen Z is less vulnerable to the physical impacts of the COVID-19 pandemic, they bear unique burdens due to their life stage, including emotional stress and grief from the pandemic, high rates of job loss and unemployment, and educational challenges from remote or interrupted learning. The effects of the pandemic may be especially felt by recent college graduates, many of whom have encountered difficulties finding jobs, had their previously secured job offers rescinded, or were unable to apply to graduate school due to the timing of the lockdowns in March 2020. In April 2020, workers aged 18 to 24 faced 27 percent unemployment, with 13 percent of this segment ceasing to look for work. While employment has largely recovered, this segment has exited the workforce at twice the rate of other age groups  since the start of the pandemic. The inequitable impact of the pandemic by race extends to Gen Z employment as well, where Black, Hispanic/Latino, and Asian American and Pacific Islander (AAPI) workers aged 18 to 24 faced up to 1.8 times the unemployment rates of their White counterparts. 1 McKinsey analysis of the US Census Bureau Current Population Survey as of November 2020.

In our sample, Gen Z respondents were more likely to report having been diagnosed with a behavioral-health condition (for example, mental or substance use disorder) than either Gen Xers or baby boomers. 4 Gen Z respondents were 1.4 to 2.3 times more likely to report that they had been diagnosed with a mental-health condition and 1.9 to 4.1 times more likely to be diagnosed with a substance-use disorder than both Gen Xers and baby boomers. Based on the McKinsey Consumer Behavioral Health Survey conducted in November–December 2020—a nationally representative survey of 1,523 responses, including an oversample of Gen Z respondents (aged 16 to 24, n = 874). Gen Z respondents were also two to three times more likely than other generations to report thinking about, planning, or attempting suicide in the 12-month period spanning late 2019 to late 2020.

Gen Z also reported more unmet social needs than any other generation. 5 Also referred to as social determinants of health or social needs, including income, employment, education, food, housing, transportation, social support, and safety. These basic needs, if unmet, can negatively affect health. In addition, factors such as race, ethnicity, gender and sexual orientation, disability, and age can influence health status. Fifty-eight percent of Gen Z reported two or more unmet social needs, compared with 16 percent of people from older generations. These perceived unmet social needs, including income, employment, education, food, housing, transportation, social support, and safety, are associated with higher self-reported rates of behavioral-health conditions. As indicated in a recent nationwide survey, people with poor mental health were two times as likely to report an unmet basic need as those with good mental health, and four times as likely to have three or more unmet basic needs. 6 2019 McKinsey Social Determinants of Health Survey, n = 2,010, where respondents included those with Medicare or Medicaid coverage, individuals with coverage through the individual market who had household incomes below 250 percent of the federal poverty level, and individuals who were uninsured and had household income below 250 percent of the federal poverty level.

As these young adults work to develop their resilience, Gen Zers may seek out the holistic approach to health they have come to expect, which includes physical health, behavioral health, and social needs, as future students, employees, and customers.

Characteristics of Gen Z consumers in the healthcare ecosystem

Gen Z’s specific needs suggest that improving their behavioral healthcare will require stakeholders to increase access and deliver appropriate, timely services.

Gen Z is less likely to seek help

Gen Z respondents were more likely to report having a behavioral-health diagnosis but less likely to report seeking treatment compared with other generations (Exhibit 1). For instance, Gen Z is 1.6 to 1.8 times more likely to report not seeking treatment for a behavioral-health condition than millennials. There are several factors that may account for Gen Z’s lack of seeking help: developmental stage, disengagement from their healthcare, perceived affordability, and stigma associated with mental or substance use disorders within their families and communities. 7 Before age 25, the human brain is not fully developed. Awareness of long-term consequences and the ability to curb impulsive behavior are some of the last functions to mature. Thus, adolescents and young adults, across generations and not just Gen Z, may be less likely to engage in activities such as routine or preventive healthcare. For more, see Investing in the health and well-being of young adults , Institute of Medicine and National Research Council, 2015.

Gen Z respondents identified as less engaged in their healthcare than other respondents (Exhibit 2). About two-thirds of Gen Z respondents fell into lower engagement segments of healthcare consumers, compared with one-half of respondents from other generations. Gen Z and other people in these less engaged segments reported that they feel less in control of their health and lifespan, are less health-conscious, and are less proactive about maintaining good health. One-third of Gen Z respondents fell into the least engaged segment, who reported the lowest motivation to improve their health and the least comfort talking about behavioral-health challenges with doctors. 8 Disadvantaged, disconnected users are more resigned to their health and less engaged and active in improving it. They value convenience but are often not engaged digitally.

Another driver for Gen Z’s reduced help-seeking may be the perceived affordability of mental-health services. One out of four Gen Z respondents said they could not afford mental-health services, which had the lowest perceived affordability of all services surveyed. 9 Services surveyed include healthcare, health insurance, internet services, necessary transportation, financial services, housing, and nutritious food. Across the board, Americans with mental and substance use disorders bear a disproportionate share of out-of-pocket healthcare costs for a range of reasons, including the fact that many behavioral-health providers do not accept insurance . “I found the perfect therapist for me but I couldn’t afford her, even with insurance,” said one Gen Z respondent. “The absolute biggest barrier to gaining mental-health treatment has been financial,” added another.

In addition, stigma associated with mental and substance use disorders and a lack of family support may be a substantial barrier in seeking mental healthcare. Many Gen Zers rely on parents for transportation or health insurance and may fear interacting with their parents about mental-health topics. This factor is particularly relevant for communities of color, who report perceiving a higher level of stigma associated with behavioral-health conditions. 10 Mental health: Culture, race, and ethnicity; A supplement to mental health; A report of the surgeon general , US Department of Health and Human Services, August 2001: A 1998 study cited in the supplement found that only 12 percent of Asians would mention their mental-health problems to a friend or relative (compared with 25 percent of Whites), only 4 percent of Asians would seek help from a psychiatrist or specialist (compared with 26 percent of Whites), and only 3 percent of Asians would seek help from a physician (compared with 13 percent of Whites). Children of immigrants also may internalize guilt because of their parents’ sacrifices or may have behavioral-health concerns minimized by their parents, who may state or think their children “have it much easier” than they did growing up. 11 Mental Health America , “To be the child of an immigrant,” blog entry by Kenna Chick, accessed December 1, 2021.

Gen Z relies on emergency care, social media, and digital tools when they do seek help

When they do seek support for behavioral-health issues, Gen Z may not be turning to regular outpatient mental-health services and instead may rely on emergency care, social media, and digital tools .

Gen Zers rely on acute sites of care more often than older generations, with Gen Z respondents one to four times more likely to report using the ER, and two to three times more likely to report using crisis services or behavioral-health urgent care in the past 12 months. Gen Z also makes up nearly three-quarters of Crisis Text Line’s users. 12 Everybody hurts 2020: What 48 million messages say about the state of mental health in America , Crisis Text Line, February 10, 2020. One Gen Z respondent expressed her frustration, saying, “Seems [like the] only option is an emergency room visit, otherwise I have to wait weeks to see a psychiatrist.”

Almost one in four Gen Zers also reported that it is “extremely” or “very” challenging to get help during a behavioral-health crisis. This lack of access is concerning for a generation two to three times more likely to report seeking treatment in the past 12 months for suicidal ideation or attempted suicide, than any other generation.

Many Gen Zers also indicated their first step in managing behavioral-health challenges was going to TikTok or Reddit for advice from other young people, following therapists on Instagram, or downloading relevant apps. This reliance on social media may be due, in part, to the provider shortages in many parts of the country: 64 percent of counties in the United States have a shortage of mental-health providers. Furthermore, 56 percent of counties in the United States are without a psychiatrist (corresponding to 9 percent of the total population), and 73 percent of counties are without a child and adolescent psychiatrist (corresponding to 19 percent of the total population). 13 Oleg Bestsennyy, Greg Gilbert, Alex Harris, and Jennifer Rost, “ Telehealth: A quarter-trillion-dollar post-COVID-19 reality ?,” McKinsey, July 9, 2021; Vulnerable Populations dashboard, McKinsey’s Center for Societal Benefit through Healthcare, accessed December 1, 2021.

Gen Z is less satisfied with the behavioral-health services they receive

Gen Zers say the behavioral healthcare system overall is not meeting their expectations—Gen Zers who received behavioral healthcare were less likely to report being satisfied with the services they received than other generations. For example, compared with older generations, Gen Z reports lower satisfaction with behavioral-health services received through outpatient counseling/therapy (3.7 out of 5.0 for Gen Z, compared with 4.1 for Gen X) or intensive outpatient (3.1 for Gen Z, compared with 3.8 for older generations). 14 Mean differences are significantly different, at a 90 percent confidence level. One Gen Z respondent said, “Struggling to find a psychologist whom I was comfortable with and cared enough to remember my name and what we did the week before” was the most significant barrier to care. Another said, “I have trust issues and find it difficult to talk with therapists about my problems. I also had a very bad experience with a therapist, which made this problem worse.”

Although we have seen high penetration of telehealth in psychiatry (share of telehealth outpatient and office visits claims were at 50 percent in February 2021), 15 Vulnerable Populations: Data Over Time Database, McKinsey Center for Societal Benefit through Healthcare, April 2021. Gen Z has the lowest satisfaction with tele-behavioral health (Gen Z rates their satisfaction with telehealth at a 3.8 out of 5.0, compared with older generations, who rate it 4.1) and digital app/tools (3.5 out of 5.0 for Gen Z, compared with 4.0 for older generations). 16 Mean differences are significantly different, at a 90 percent confidence level. Around telehealth, Gen Zers cited reasons for dissatisfaction such as telehealth therapy feeling “less official” or “less professional,” as well as more difficult to form a trusting connection with a therapist. For apps, Gen Z respondents noted a lack of personalization, as well as a lack of diversity—both in terms of the racial and ethnic diversity of the stories they presented, and in the problems that the apps offered tools to address. In creating and improving behavioral-health tools, it is crucial to employ a user-centered design approach to develop functionality and experiences that Gen Zers actually want.

In creating and improving behavioral-health tools, it is crucial to employ a user-centered design approach to develop functionality and experiences that Gen Zers actually want.

Gen Z cares about diversity when choosing a healthcare provider

Racial and ethnic diversity in the behavioral-health workforce is also important. According to McKinsey’s COVID-19 Consumer Survey, racial and ethnic minority respondents reported valuing racial and ethnic diversity when choosing a physician, citing their physician’s race more frequently than White respondents as a consideration. 17 Thirteen percent of Black respondents, 9 percent of Asian respondents, and 8 percent of Hispanic/Latino respondents cited their physician’s race when selecting the physicians that they see, compared with 4 percent of Whites. Because Gen Z cares deeply about diversity, there are opportunities to integrate care and early intervention by offering a more racially and ethnically diverse behavioral-health workforce and culturally relevant digital tools. 18 According to surveys conducted by the Pew Research Center, most Gen Zers see the country’s growing racial and ethnic diversity as a good thing: Ruth Igielnik and Kim Parker, “On the cusp of adulthood and facing an uncertain future: What we know about Gen Z so far,” Pew Research Center, May 14, 2020.

Potential stakeholder actions to address the needs of Generation Z

In our article “ Unlocking whole person care through behavioral health ,” we outline six potential actions integral to improving the quality of care and experience for millions with behavioral-health conditions. Many of those levers apply to Gen Z, but further tailoring is needed to best meet the needs of this emerging generation. Promising areas to explore could include the emerging role of digital and telehealth; the need for stronger community-based response to behavioral-health crises; better meeting the needs of Gen Z where they live, work, and go to school; promoting mental-health literacy; investing in behavioral health at parity with physical health; and supporting a holistic approach that embraces behavioral, physical, and social aspects of health.

Need for action now

Gen Z is our next generation of leaders, activists, and politicians; many of them have already taken on adult responsibilities as they start climate movements, lead social justice marches, and drive companies to align more closely with their values. Healthcare leaders, educators, and employers all have a role to play in supporting the behavioral health of Gen Z. By taking a tailored, generational approach to designing messages, products, and services, stakeholders can meaningfully improve the behavioral health of Gen Z and help them achieve their full potential. This investment could be viewed as a down payment on our future that will bear social and economic returns for years to come.

Erica Coe is a partner in McKinsey’s Atlanta office and coleads the Center for Societal Benefit through Healthcare, Jenny Cordina is a partner in the Detroit office and leads McKinsey’s Consumer Health Insights research, Kana Enomoto is a senior expert in the Washington, DC, office and coleads the Center for Societal Benefit through Healthcare, Raelyn Jacobson is an associate partner in the Seattle office, Sharon Mei is an expert in the New York office, and Nikhil Seshan is a consultant in the Philadelphia office.

The authors wish to thank Tamara Baer, Eric Bochtler, Emma Dorn, Erin Harding, Brad Herbig, Jimmy Sarakatsannis, and Boya Wang for their contributions to this paper.

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Disparities in Health and Health Care: 5 Key Questions and Answers

Nambi Ndugga and Samantha Artiga Published: Apr 21, 2023

Introduction

The COVID-19 pandemic and nationwide racial justice movement over the past several years have heightened the focus on health disparities and their underlying causes and contributed to the increased prioritization of health equity. These disparities are not new and reflect longstanding structural and systemic inequities rooted in racism and discrimination. Although growing efforts have focused recently on addressing disparities, the ending of some policies implemented during the COVID-19 pandemic, including continuous enrollment for Medicaid and the Children’s Health Insurance Program (CHIP), may reverse progress and widen disparities. Addressing health disparities is not only important from an equity standpoint, but also for improving the nation’s overall health and economic prosperity. This brief provides an introduction to what health and health care disparities are, why it is important to address disparities, what the status of disparities is today, recent federal actions to address disparities, and key issues related to addressing disparities looking ahead.

What are health and health care disparities?

Health and health care disparities refer to differences in health and health care between groups that stem from broader inequities . There are multiple definitions of health disparities. Healthy People 2030 defines a health disparity, as “a particular type of health difference that is linked with social, economic, and/or environmental disadvantage,” and that adversely affects groups of people who have systematically experienced greater obstacles to health. The Centers for Disease Control and Prevention (CDC) defines health disparities as, “preventable differences in the burden, disease, injury, violence, or in opportunities to achieve optimal health experienced by socially disadvantaged racial, ethnic, and other population groups and communities.” A health care disparity typically refers to differences between groups in health insurance coverage, affordability, access to and use of care, and quality of care. The terms “health inequality” and “inequity” are also sometimes used to describe unjust differences. Racism, which the CDC defines as the structures, policies, practices, and norms that assign value and determine opportunities based on the way people look or the color of their skin, results in conditions that unfairly advantage some and disadvantage others, placing people of color at greater risk for poor health outcomes.

Health equity generally refers to individuals achieving their highest level of health through the elimination of disparities in health and health care. Healthy People 2030 defines health equity as the attainment of the highest level of health for all people and notes that it requires valuing everyone equally with focused and ongoing societal efforts to address avoidable inequalities, historical and contemporary injustices, and health and health care disparities. The CDC describes health equity as when everyone has the opportunity to be as healthy as possible.

A broad array of factors within and beyond the health care system drive disparities in health and health care (Figure 1) .  Though health care is essential to health, research shows that health outcomes are driven by multiple factors, including underlying genetics, health behaviors, social and environmental factors, and access to health care. While there is currently no consensus in the research on the magnitude of the relative contributions of each of these factors to health, studies suggest that health behaviors and social and economic factors, often referred to as  social determinants of health , are the primary drivers of health outcomes and that social and economic factors shape individuals’ health behaviors. Moreover,  racism  negatively affects mental and physical health both directly and by creating inequities across the social determinants of health.

Health and health care disparities are often viewed through the lens of race and ethnicity, but they occur across a broad range of dimensions.  For example, disparities occur across socioeconomic status, age, geography, language, gender, disability status, citizenship status, and sexual identity and orientation. Research also suggests that disparities occur across the life course, from birth, through mid-life, and among older adults. Federal efforts to reduce disparities focus on  designated priority populations , including, “members of underserved communities: Black, Latino, and Indigenous and Native American persons, Asian Americans and Pacific Islanders and other persons of color; members of religious minorities; lesbian, gay, bisexual, transgender, and queer (LGBT+) persons; persons with disabilities; persons who live in rural areas; and persons otherwise adversely affected by persistent poverty or inequality.” These groups are not mutually exclusive and often intersect in meaningful ways. Disparities also occur within subgroups of populations. For example, there are differences among Hispanic people in health and health care based on length of time in the country, primary language, and immigration status . Data often also mask underlying disparities among subgroups within the Asian population.

Why is it important to address disparities?

Addressing disparities in health and health care is important not only from an equity standpoint but also for improving the nation’s overall health and economic prosperity . People of color and other underserved groups experience higher rates of illness and death across a wide range of health conditions, limiting the overall health of the nation. Research further finds that health disparities are costly, resulting in excess medical care costs and lost productivity as well as additional economic losses due to premature deaths each year.

What is the status of disparities today?

Disparities in health and health care are persistent and prevalent. Major recognition of health disparities began more than three decades ago with the Report of the Secretary’s Task Force on Black and Minority Health (Heckler Report) in 1985, which documented persistent health disparities that accounted for 60,000 excess deaths each year and synthesized ways to advance health equity. The Heckler Report led to the creation of the U.S. Department of Health and Human Services Office of Minority Health and influenced federal recognition of and investment in many aspects of health equity. In 2003, the Institute of Medicine’s Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care released the report, Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care , which identified systemic racism as a major cause of health disparities in the United States. Despite the recognition and documentation of disparities for decades and overall improvements in population health over time, many disparities have persisted, and, in some cases, widened over time.

Beyond coverage, people of color and other marginalized and underserved groups continue to experience many disparities in accessing and receiving care . For example, people in rural areas face barriers to accessing care due to low density of providers and longer travel times to care, as well as more limited access to health coverage. There also are inequities in experiences receiving health care across groups. For example, the KFF/The Undefeated 2020 Survey on Race and Health , found that one in five Black adults and one in five Hispanic adults report being treated unfairly treatment due to their race or ethnicity while getting health care for themselves or a family member in the past year. Nearly one-quarter (24%) of Hispanic adults and over one in three (34%) potentially undocumented Hispanic adults reported that it was very or somewhat difficult to find a doctor who explains this in a way that is easy to understand in a 2021 KFF survey.  Other KFF survey data from 2022 found that nearly one in ten (9%) of nonelderly adult women who visited a health care provider in the past two years said they experienced discrimination because of their age, gender, race, sexual orientation, religion, or some other personal characteristic during a health care visit. KFF data also showed that LGBT+ people were more likely than their non-LGBT+ counterparts to report certain negative experiences while getting health care, including a doctor not believing they were telling the truth, suggesting they are personally to blame for a health problem, assuming something about them without asking, and/or dismissing their concerns. The 2023 KFF/The Washington Post Trans Survey found that trans adults were more likely to report having difficulty finding affordable health care or a provider who treated them with dignity and respect compared to cisgender adults.

The COVID-19 pandemic has taken a disproportionate toll on the health and well-being of people of color and other underserved groups. Cumulative age-adjusted data showed that AIAN and Hispanic people have had a higher risk for COVID-19 infection and AIAN, Hispanic, and Black people have had a higher risk for hospitalization and death due to COVID-19. Beyond these direct health impacts, the pandemic has negatively impacted the mental health, well-being, and social and economic factors that drive health for people of color and other underserved groups, including LGBT+ people . As such, the pandemic may contribute to worsening health disparities going forward.

Concerns about mental health and substance use have increased since the onset of the pandemic, particularly among some groups. According to a 2022 KFF/CNN survey , 90% of the public think there is a mental health crisis in the U.S. today. Over the course of the pandemic, many adults reported symptoms consistent with anxiety and depression. Additionally, drug overdose deaths have sharply increased – largely due to fentanyl – and after a brief period of decline, suicide deaths are once again on the rise. These negative mental health and substance use outcomes have disproportionately affected some populations, particularly communities of color and youth. Drug overdose death rates were highest among AIAN and Black people as of 2021. Alcohol-induced death rates increased substantially during the pandemic, with rates increasing the fastest among people of color and people living in rural areas. From 2019 to 2021, many people of color experienced a larger growth in suicide death rates compared to their White counterparts. Additionally, self-harm and suicidal ideation has increased faster among adolescent females compared to their male peers. Findings from a 2023 KFF/The Washington Post survey found that more trans adults reported struggling with serious mental health issues compared to cisgender adults and were six times as likely as cisgender adults to have engaged in self-harm in the previous year (17% vs. 3%). There are also substantial disparities in mental health, including suicidality, among LGBT+ youth compared to their non-LGBT+ peers.

What are recent federal actions to address disparities?

In the wake of the COVID-19 pandemic, there has been a heightened awareness of and focus on addressing health disparities. The disparate impacts of COVID-19 and coinciding racial reckoning following the police killing of George Floyd contributed to a growing awareness of racial disparities in health and their underlying causes, including racism. Early in his presidency, President Biden issued a series of executive orders focused on advancing health equity, including orders that outlined equity as a priority for the federal government broadly and as part of the pandemic response and recovery efforts . Federal agencies were directed with developing Equity Action Plans that outlined concrete strategies and commitments to addressing systemic barriers across the federal government. In its Health Equity Plan, the Department of Health and Human Services (HHS) outlined a series of new strategies, including addressing increased pregnancy and postpartum morbidity and mortality among Black and AIAN women; addressing barriers that individuals with limited English proficiency face in obtaining information, services, and benefits from HHS programs; leveraging grants to incorporate equity consideration into funding opportunities, implementing equity assessments across its major policies and programs; investing in resources to advance civil rights; and expanding contracting opportunities for small, disadvantaged businesses. The plan builds on earlier efforts that included increasing stakeholder engagement, establishing the Office of Climate Change and Health Equity , and establishing the National Institutes of Health UNITE Initiative to address structural racism and racial inequities in biomedical research. Since the release of its Equity Action Plan, HHS has taken actions to extend postpartum coverage through Medicaid and CHIP; issued rules to strengthen patient protections, including nondiscrimination protections; and issued nondiscrimination guidance to ensure that telehealth services are accessible to people with disabilities and those with limited English proficiency.

The Centers for Medicare and Medicaid Services (CMS) released an updated framework to advance health equity, expand health coverage, and improve health outcomes for people covered by Medicare, Medicaid, CHIP, and the Health Insurance Marketplaces. The framework outlined five priorities including expanding the collecting, reporting, and analysis of standardized data on demographics and social determinants of health; assessing the causes of disparities within CMS programs and addressing inequities in policies and operations; building capacity of health care organizations and the workforce to reduce disparities; advancing language access, health literacy, and the provision of culturally tailored services; and increasing all forms of accessibility to health services and coverage. The Administration has also identified advancing health equity and addressing social determinants of health as key priorities within Medicaid and has encouraged states to propose Section 1115 Medicaid waivers that expand coverage, reduce health disparities, and/or advance “whole-person care.” States have increasingly requested and/or received approval for waivers that aim to advance equity . Further, a growing number of states have approved or pending waivers with provisions related to addressing health-related social needs , such as food and housing, often focused on specific populations with high needs or risks.

The Administration and Congress have taken a range of actions to stabilize and increase access to health coverage amid the pandemic. Early in the pandemic, Congress passed the Families First Coronavirus Response Act (FFCRA), which included a temporary requirement that Medicaid programs keep people continuously enrolled during the COVID-19 Public Health Emergency in exchange for enhanced federal funds. Primarily due to the continuous enrollment provision, Medicaid enrollment has grown substantially compared to before the pandemic, and the  uninsured rate  has dropped with differences in uninsured rates between people of color and White people narrowing. Coverage gains also likely reflected enhanced ACA Marketplace subsidies made available by the American Rescue Plan Act (ARPA) of 2021 and renewed for another three years in the Inflation Reduction Act of 2022, boosted outreach and enrollment efforts, a Special Enrollment Period for the Marketplaces provided in response to the pandemic, and low Marketplace attrition . Additionally, in 2019, the Biden Administration reversed changes the Trump Administration had previously made to public charge immigration policies that increased reluctance among some immigrant families to enroll in public programs, including health coverage. Most recently, the Consolidated Appropriations Act of 2023 included a requirement for all states to implement 12 months of continuous coverage for children, supporting their coverage stability. However, it also set the end of the broader Medicaid continuous enrollment provision for March 31, 2023, which could lead to coverage losses for millions of people, reversing recent coverage gains.

There have been growing federal efforts to address disparities in maternal health. Over the past few years, the Administration launched several initiatives focused on addressing inequities in maternal health. In April 2021, President Biden issued a proclamation to recognize the importance of addressing the high rates of maternal mortality and morbidity among Black people. At the end of 2021, the White House hosted its inaugural White House Maternal Health Day of Action during which areas of concern in maternal health outcomes were identified and the Administration announced actions aimed at solving the maternal health crisis. In June 2022, the Biden Administration released the Blueprint for Addressing the Maternal Health Crisis . The Blueprint outlines priorities and actions across federal agencies to improve access to coverage and care, expand and enhance data collection and research, grow and diversify the perinatal workforce, strengthen social and economic support, and increase trainings and incentives to support women being active participants in their care before, during and after pregnancy. In July 2022, CMS announced a Maternity Care Action Plan to support the implementation of the Biden-Harris Administration’s Blueprint for Addressing the Maternal Health Crisis. The action plan takes a holistic and coordinated approach across CMS to improve health outcomes and reduce inequities for people during pregnancy, childbirth, and the postpartum period. ARPA included an option, made permanent in the  Consolidated Appropriations Act , to allow states  to extend Medicaid postpartum coverage  from 60 days to 12 months. As of April 2023, the majority of states  have taken steps to extend postpartum coverage. The Human Resources and Services Administration also announced $12 million in awards for the Rural Maternal and Obstetrics Management Strategies Program (RMOMS), which is designed to develop models and implement strategies to improve maternal health in rural communities.

The Administration has also taken steps to address health disparities and discrimination experienced among LGBT+ people. On his first day in office, President Biden signed an Executive Order on “Preventing and Combating Discrimination on the Basis of Gender Identity or Sexual Orientation.” Since then, the Administration has taken multiple actions to address discrimination within health care specifically. In May 2021, the Biden Administration announced that the HHS Office for Civil Rights (OCR) would include gender identity and sexual orientation as it interprets and enforces the ACA’s prohibition against sex discrimination (Section 1557), reversing the approach taken by the Trump Administration. Additionally, the Administration has spoken out against state actions aimed at curtailing access to gender affirming care for transgender and gender nonconforming people, particularly policies targeting youth. In January 2023, the Administration released its Federal Evidence Agenda on LGBTQI+ Equity , a “roadmap for federal agencies as they work to create their own data-driven and measurable SOGI Data,” which the Administration views as central to understanding disparities and discrimination facing this community.

What are key issues related to health disparities looking ahead?

The end of the Medicaid continuous enrollment provision may lead to coverage losses and widening disparities. Following the ending of the Medicaid continuous enrollment provision on March 31, 2023, states resumed Medicaid redeterminations. KFF estimates that between 5 and 14 million people could lose Medicaid coverage, including many who newly gained coverage during the pandemic. Other research shows that Hispanic and Black people are likely to be disproportionately impacted by the expiration of the continuous enrollment provision. Moreover, some groups, such as individuals with limited English proficiency and people with disabilities may face increased challenges in completing the Medicaid renewal process increasing their risk of coverage loss even if they remain eligible for coverage. OCR has reminded states of their obligations under federal civil rights laws to take reasonable steps to provide meaningful language access for individuals with limited English proficiency and ensure effective communication with individuals with disabilities to prevent lapses in coverage amid the unwinding of the continuous enrollment provision. CMS issued guidance that provides a roadmap for states to streamline processes and implement strategies to reduce the number of people who lose coverage even though they remain eligible. The extent to which states simplify processes to renew or transition to other coverage and provide outreach and assistance to individuals more likely to face challenges completing renewal processes will impact coverage losses and potential impacts on coverage disparities.

The end of the COVID-19 Public Health Emergency (PHE) and the potential depletion of the federally purchased supply of COVID-19 vaccines, treatments, and tests may curtail access to these supplies for some individuals, particularly those who are uninsured. In response to the COVID-19 pandemic, the federal government spent billions of dollars in emergency funds to purchase COVID-19 vaccines, including boosters, treatments, and tests to provide free of charge to the public. In addition, Congress enacted legislation that included special requirements for their coverage by both public and private insurers, and the Administration issued guidance and regulations to protect patient access and promote equitable distribution. The upcoming end to the PHE on May 11, 2023, as well as the potential depletion of federally purchased supplies in the absence of any additional funding, could result in new or higher cost-sharing and/or reduced access to these products although these impacts may vary by product and the type of health coverage an individual has. People who are uninsured or underinsured face the greatest risk of access challenges, including limited access to free vaccines and no coverage for treatment or tests. Since people of color and people with lower incomes are more likely to be uninsured, they may be at a disproportionate risk of facing barriers to accessing COVID-19 vaccines, tests, and treatments once the PHE ends and the federal supply is depleted.

The  overturning of  Roe v. Wade may exacerbate the already large racial disparities in maternal and infant health. The decision to overturn the longstanding Constitutional right to abortion and elimination of federal standards on abortion access has resulted in growing variation across states in laws protecting or restricting abortion. These changes may disproportionately impact women of color, as they are more likely to obtain abortions, have more limited access to health care, and face underlying inequities that would make it more difficult to travel out of state for an abortion compared to their White counterparts. Restricted access to abortions may widen the already stark racial disparities in maternal and infant health, as some groups of color are at higher risk of dying from pregnancy-related reasons and during infancy and are more likely to experience birth risks and adverse birth outcomes compared to White people. It may also have negative economic consequences associated with the direct costs of raising children and impacts on educational and employment opportunities. Further, women from underserved communities may be at increased risk for criminalization in a post-Roe environment, as prior to the ruling, there were already cases of women being criminalized for their miscarriages, stillbirths, or infant death, many of whom were low-income or women of color.

Many states have implemented policies banning or limiting access to gender affirming care, especially for youth, as well as other legal actions that threaten access to care for LGBT+ people . Policies aimed at limiting access to gender affirming care may have significant negative implications for the health of trans and nonconforming people, particularly young people, including negative mental health impacts, and an increased risk of suicidality . Additionally, the recent Braidwood case on preventive care access directly affects LGBT+ people in its treatment of Pre-Exposure Prophylaxis (PrEP). It relies, in part, on religious protections arguments to limit access to the drug based on the plaintiff’s claim that it “facilitate[s] and encourage[s] homosexual behavior, prostitution, sexual promiscuity, and intravenous drug use.” If PrEP use declines as a result of the Braidwood decision, HIV incidence could increase , likely disproportionally impacting people of color and LGBT+ people. Efforts to curtail access to gender affirming care and the Braidwood decision are at odds with the Administration’s stated approach to health equity for LGBT+ people. How such policies play out in the longer term will be determined largely by the courts.

Evolving immigration policies may impact the health and well-being of immigrant families. When the PHE ends on May 11, 2023, Title 42 restrictions that suspended the entry of individuals at the U.S. border to protect public health during the COVID-19 emergency are expected to terminate. It is anticipated that when the authority ends, there will be an increase in immigrant activity at the U.S. border. The Biden Administration has announced  plans  to increase security and enforcement at the border to reduce unlawful crossings, expand “legal pathways for orderly migration”, invest additional resources in the border region, and partner with Mexico to implement the aforementioned plans. However, it remains to be seen how shifting policies will impact trends at the border and health and health care in that region. The future of the Deferred Action for Childhood Arrivals (DACA) program remains uncertain, and its implementation is currently limited subject to court orders . If the DACA program is found to be unlawful in pending court rulings, individuals would lose their DACA status and subsequently their work authorizations. The loss of status and work authorization may result in loss of employer-based health coverage, leaving people uninsured and unable to qualify for Medicaid, CHIP, or to purchase coverage through the Marketplaces. Additionally, although the Biden Administration reversed public charge regulations implemented by the Trump Administration as part of an effort to address immigration-related fears that limited immigrant families’ participation in government assistance programs, including Medicaid and CHIP, many families continue to have fears and concerns about enrolling in these programs, contributing to ongoing gaps in coverage for immigrants and children of immigrants.

Growing mental health and substance use concerns and ongoing racism, discrimination, and violence may contribute to health disparities. As previously noted, mental health and substance use concerns have increased since the onset of the pandemic, with some groups particularly affected. These trends may lead to new and widening disparities. For example, people of color have experienced larger increases in drug overdose death rates than White people, resulting in the death rate for Black people newly surpassing that of White people by 2020. Further, Black and Asian people have reported negative mental health impacts due to heightened anti-Black and anti-Asian racism and violence in recent years. Research has documented the negative health impacts, including negative impacts on mental health and well-being, of exposure to violence, including police and violence. Research shows African American and AIAN men and women, and Latino men are at increased risk of being killed by police compared to their White peers. Black and Hispanic adults also are more likely than White adults to worry about gun violence according to 2023 KFF survey data . Other KFF analysis shows that firearm death rates increased sharply among Black and Hispanic youth during the pandemic driven primarily by gun assaults and suicide by firearm. Research further shows that repeated and chronic exposure to racism and discrimination is associated with negative physical and mental health outcomes , including premature aging and associated health risks, referred to as “ weathering ,” as well as higher mortality .

Despite growing mental health concerns, people of color continue to face disproportionate barriers to accessing mental health care. Research suggests that  structural inequities  may contribute to disparities in use of mental health care, including lack of health insurance coverage and financial and logistical barriers to accessing care, stemming from broader inequities in  social and economic factors . Lack  of a diverse mental health care workforce, the  absence of culturally informed treatment options, and stereotypes  and  discrimination  associated with poor mental health may also contribute to limited mental health treatment among people of color.   Amid the pandemic, many states implemented telehealth behavioral health services to expand access to behavioral health care, and most states intend to keep these services. States are also adopting strategies to address workforce shortages in behavioral health. As states seek to expand access to behavioral health care, it will be important to ensure that services address the cultural and linguistic needs of diverse populations. Further, in 2022, the federal government mandated the suicide and crisis lifeline number that provides a single three-digit number (988) to access a network of over 200 local and state-funded crisis centers. The 988 number is expected to improve the delivery of mental health crisis care; however, it is unknown how well it will address the needs of people of color and other underserved populations.

In sum, disparities in health and health care for people of color and other underserved groups are longstanding challenges, many of which are driven by underlying structural and economic disparities rooted in racism. Addressing disparities is key not only from an equity standpoint but for improving the nation’s overall health and economic prosperity. Amid the COVID-19 pandemic, the federal government identified health equity as a priority and has since launched initiatives to address disparities wrought by the COVID-19 pandemic and more broadly. Alongside the federal government, states, local communities, private organizations, and providers have engaged in efforts to reduce health disparities. Moving forward, a broad range of efforts both within and beyond the health care system will be instrumental in reducing disparities and advancing equity.

• Racial Equity and Health Policy
• Coronavirus (COVID-19)
• Women's Health Policy
• Access to Care
• American Indian/Alaska Native
• Race/Ethnicity

Also of Interest

• How History Has Shaped Racial and Ethnic Health Disparities: A Timeline of Policies and Events
• Key Data on Health and Health Care by Race and Ethnicity
• Health Coverage by Race and Ethnicity, 2010-2022

In the pandemic, we were told to keep 6 feet apart. There’s no science to support that.

In a congressional appearance, infectious-disease expert Anthony S. Fauci characterized the recommendation as “an empiric decision that wasn’t based on data.”

The nation’s top mental health official had spent months asking for evidence behind the Centers for Disease Control and Prevention’s social distancing guidelines, warning that keeping Americans physically apart during the coronavirus pandemic would harm patients, businesses, and overall health and wellness.

Now, Elinore McCance-Katz, the Trump administration’s assistant secretary for mental health and substance use, was urging the CDC to justify its recommendation that Americans stay six feet apart to avoid contracting covid-19 — or get rid of it.

“I very much hope that CDC will revisit this decision or at least tell us that there is more and stronger data to support this rule than what I have been able to find online,” McCance-Katz wrote in a June 2020 memo submitted to the CDC and other health agency leaders and obtained by The Washington Post. “If not, they should pull it back.”

The CDC would keep its six-foot social distance recommendation in place until August 2022, with some modifications as Americans got vaccinated against the virus and officials pushed to reopen schools. Now, congressional investigators are set Monday to press Anthony S. Fauci, the infectious-disease doctor who served as a key coronavirus adviser during the Trump and Biden administrations, on why the CDC’s recommendation was allowed to shape so much of American life for so long, particularly given Fauci and other officials’ recent acknowledgments that there was little science behind the six-foot rule after all.

“It sort of just appeared, that six feet is going to be the distance,” Fauci testified to Congress in a January closed-door hearing, according to a transcribed interview released Friday. Fauci characterized the recommendation as “an empiric decision that wasn’t based on data.”

Francis S. Collins, former director of the National Institutes of Health, also privately testified to Congress in January that he was not aware of evidence behind the social distancing recommendation, according to a transcript released in May.

Four years later, visible reminders of the six-foot rule remain with us, particularly in cities that rushed to adopt the CDC’s guidelines hoping to protect residents and keep businesses open. D.C. is dotted with signs in stores and schools — even on sidewalks or in government buildings — urging people to stand six feet apart.

Experts agree that social distancing saved lives, particularly early in the pandemic when Americans had no protections against a novel virus sickening millions of people. One recent paper published by the Brookings Institution , a nonpartisan think tank, concludes that behavior changes to avoid developing covid-19, followed later by vaccinations, prevented about 800,000 deaths. But that achievement came at enormous cost, the authors added, with inflexible strategies that weren’t driven by evidence.

“We never did the study about what works,” said Andrew Atkeson, a UCLA economist and co-author of the paper, lamenting the lack of evidence around the six-foot rule. He warned that persistent frustrations over social distancing and other measures might lead Americans to ignore public health advice during the next crisis.

The U.S. distancing measure was particularly stringent, as other countries adopted shorter distances; the World Health Organization set a distance of one meter, or slightly more than three feet, which experts concluded was roughly as effective as the six-foot mark at deterring infections, and would have allowed schools to reopen more rapidly.

The six-foot rule was “probably the single most costly intervention the CDC recommended that was consistently applied throughout the pandemic,” Scott Gottlieb, former Food and Drug Administration commissioner, wrote in his book about the pandemic, “Uncontrolled Spread.”

It’s still not clear who at the CDC settled on the six-foot distance; the agency has repeatedly declined to specify the authors of the guidance, which resembled its recommendations on how to avoid contracting the flu. A CDC spokesperson credited a team of experts, who drew from research such as a 1955 study on respiratory droplets . In his book, Gottlieb wrote that the Trump White House pushed back on the CDC’s initial recommendation of 10 feet of social distance, saying it would be too difficult to implement.

Perhaps the rule’s biggest impact was on children, despite ample evidence they were at relatively low risk of covid-related complications. Many schools were unable to accommodate six feet of space between students’ desks and forced to rely on virtual education for more than a year, said Joseph Allen, a Harvard University expert in environmental health, who called in 2020 for schools to adopt three feet of social distance.

“The six-foot rule was really an error that had been propagated for several decades, based on a misunderstanding of how particles traveled through indoor spaces,” Allen said, adding that health experts often wrongly focused on avoiding droplets from infected people rather than improving ventilation and filtration inside buildings.

Social distancing had champions before the pandemic. Bush administration officials, working on plans to fight bioterrorism, concluded that social distancing could save lives in a health crisis and renewed their calls as the coronavirus approached. The idea also took hold when public health experts initially believed that the coronavirus was often transmitted by droplets expelled by infected people, which could land several feet away; the CDC later acknowledged the virus was airborne and people could be exposed just by sharing the same air in a room, even if they were farther than six feet apart.

“There was no magic around six feet,” Robert R. Redfield, who served as CDC director during the Trump administration, told a congressional committee in March 2022. “It’s just historically that’s what was used for other respiratory pathogens. So that really became the first piece” of a strategy to protect Americans in the early days of the virus, he said.

It also became the standard that states and businesses adopted, with swift pressure on holdouts. Lawmakers and workers urged meat processing plants, delivery companies and other essential businesses to adopt the CDC’s social distancing recommendations as their employees continued reporting to work during the pandemic.

Some business leaders weren’t sure the measures made sense. Jeff Bezos, founder of online retail giant Amazon, petitioned the White House in March 2020 to consider revising the six-foot recommendation, said Adam Boehler, then a senior Trump administration official helping with the coronavirus response. At the time, Amazon was facing questions about a rising number of infections in its warehouses, and Democratic senators were urging the company to adopt social distancing.

“Bezos called me and asked, is there any real science behind this rule?” Boehler said, adding that Bezos pushed on whether Amazon could adopt an alternative distance if workers were masked, physically separated by dividers or other precautions were taken. “He said … it’s the backbone of trying to keep America running here, and when you separate somebody five feet versus six feet, it’s a big difference,” Boehler recalled. Bezos owns The Washington Post.

Kelly Nantel, an Amazon spokesperson, confirmed that Bezos called Boehler and said the Amazon founder’s focus was the discrepancy between the U.S. recommendation and the WHO’s shorter distance. The company soon said it would follow the CDC’s six-foot social distancing guidelines in its warehouses and later developed technologies to try to enforce those guidelines. “We did it globally everywhere because it was the right thing to do,” Nantel said.

Boehler said he spoke with Redfield and Fauci about testing alternatives to the six-foot recommendation but that he was not aware of what happened to those tests or what they found. Fauci declined to comment. Redfield did not respond to requests for comment.

But challenging the six-foot recommendation, particularly in the pandemic’s early days, was seen as politically difficult. Rochelle Walensky, then chief of infectious disease at Massachusetts General Hospital, argued in a July 2020 email that “if people are masked it is quite safe and much more practical to be at 3 feet” in many school settings.

Five months later, incoming president Joe Biden would tap Walensky as his CDC director. Walensky swiftly endorsed the six-foot distance before working to loosen it, announcing in March 2021 that elementary school students could sit three feet apart if they were masked. Walensky declined to comment.

The most persistent government critic of the social distancing guidelines may have been McCance-Katz, who did not respond to requests for comment for this article. Trump’s mental health chief had spent several years clashing with other Department of Health and Human Services officials on various matters and had few internal defenders by the time the pandemic arrived, hampering her message. But while her pleas failed to move the CDC, her warnings about the risks to mental health found an audience with Trump and his allies, who blamed federal bureaucrats for the six-foot rule and other measures.

“What is this nonsense that somehow it’s unsafe to return to school?” McCance-Katz said in September 2020 on an HHS podcast, lamenting the broader shutdown of American life. “I do think that Americans are smart people, and I think that they need to start asking questions about why is it this way.”

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• Elsevier - PMC COVID-19 Collection

Mental health interventions and supports during COVID- 19 and other medical pandemics: A rapid systematic review of the evidence

Sophie soklaridis.

a Centre for Addiction and Mental Health, Toronto, Ontario, Canada

b Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada

c The Wilson Centre for Research in Education, Toronto, Ontario, Canada

d Department of Family & Community Medicine, University of Toronto, Ontario, Canada

Elizabeth Lin

Yasmin lalani, terri rodak, sanjeev sockalingam, associated data.

The data that support the findings of this study are available from the corresponding author, SS, upon reasonable request.

Novel coronavirus pneumonia (COVID-19) is a global reminder of the need to attend to the mental health of patients and health professionals who are suddenly facing this public health crisis. In the last two decades, a number of medical pandemics have yielded insights on the mental health impact of these events. Based on these experiences and given the magnitude of the current pandemic, rates of mental health disorders are expected to increase. Mental health interventions are urgently needed to minimize the psychological sequelae and provide timely care to affected individuals.

We conducted a rapid systematic review of mental health interventions during a medical pandemic, using three electronic databases. Of the 2404 articles identified, 21 primary research studies are included in this review.

We categorized the findings from the research studies using the following questions: What kind of emotional reactions do medical pandemics trigger? Who is most at risk of experiencing mental health sequelae? What works to treat mental health sequelae (psychosocial interventions and implementation of existing or new training programs)? What do we need to consider when designing and implementing mental health interventions (cultural adaptations and mental health workforce)? What still needs to be known?

Various mental health interventions have been developed for medical pandemics, and research on their effectiveness is growing. We offer recommendations for future research based on the evidence for providing mental health interventions and supports to those most in need.

1. Background

Global medical pandemics such as severe acute respiratory syndrome (SARS), Ebola virus disease and, most recently, novel coronavirus pneumonia (COVID-19) have not only sparked widespread fear of infection, but also affect mental health among the general public and health professionals who provide patient care [ 1 , 2 ]. Most recently, COVID-19 has triggered anxiety, and measures to contain the virus have caused uncertainty, isolation, and economic despair, which take their toll on mental health. Health professionals who care for patients during these crises are vulnerable not only to infection, but also to psychological distress, as population morbidity and deaths, and demand for health services increase [ 3 , 4 ]. Unique stressors for health professionals include burnout [ 5 ] and moral injury [ 6 ], and are exacerbated by shortages of medical supplies and health services during a time of unprecedented need [ 7 ]. Yet despite the need for mental health supports for patients, the general public, and people working in health care, health professionals have received little or no training in providing mental health care during pandemics [ 8 ]. Health professionals are asking for reassurance that their organizations will support them, do everything possible to protect them, and provide medical and social support if they or their families become infected [ 9 ]. The general public is asking that the health care system be a source of support for maintaining and restoring mental health in the midst of a pandemic [ 10 ]. To date, there is little information to guide the development and implementation of mental health interventions to support health professionals, patients, and the general public during medical pandemics [ 11 ].

Research indicates that people who have been affected by medical pandemics as survivors, caregivers, orphans, or health professionals working with infected patients are more likely to experience psychological distress, sleep disorders, anxiety, and post-traumatic stress disorder (PTSD) [ 2 , 3 , 5 , 6 , 9 ]. These symptoms can progress to suicidal ideation, substance abuse, and significantly reduced quality of life. Yet it is still not clear how best to respond to mental health challenges during a medical pandemic [ 12 ]. Given the critical situation with COVID-19, evidence-based information on existing mental health interventions is urgently needed in order to develop and deliver effective mental health interventions for people in need. This rapid systematic review aims to provide an up-to-date and robust synthesis of the evidence by reporting on implementation, evaluation, and outcomes regarding mental health interventions during medical pandemics within the last two decades.

We used the Preferred Reporting Items for Systematic Reviews and Metal Analysis statement guidelines (PRISMA) to conduct our review and report on the evidence regarding mental health interventions during medical pandemics [ 13 ]. We proceeded with the data abstraction process and therefore were not able to register our a priori protocol on PROSPERO. However, we reviewed the already registered reviews of human studies relevant to COVID-19 to minimize the potential of duplicating efforts.

2.1. Information sources, study selection and review process

A comprehensive search strategy was developed with the assistance of a librarian (TR) and was used to identify articles in four electronic databases: Medline (including Epub ahead of print, in process, and other non-indexed citations); Embase; APA PsycInfo; and the Cumulative Index to Nursing & Allied Health Literature (CINAHL). The year range for the search was “2003 to present” to ensure that the SARS literature was included. No language limits were applied. The full Medline search strategy can be found in Supplementary Appendix 1. The searches used database-specific subject headings and keywords in natural language. Database searches were run on March 27, 2020, April 16, 2020, and July 31, 2020 to capture the most recent publications. Reference lists of identified and other relevant articles were hand-searched to capture other potential evidence. This was a rapid review with the aim of being both systematic and expedient; therefore, we did not search the grey literature.

Each identified primary research study was evaluated using PICO (Population, Intervention, Comparison, Outcome) as specified in the Joanna Briggs Institute methodology [ 14 ], and included the following:

• (a) Population: Studies examining adults, children, and adolescents who participated in a mental health intervention, or health professionals who were trained to provide mental health interventions during or after a medical pandemic.
• (b) Intervention: Studies that report any type of mental health interventions and/or training programs using the following criteria: (1) main focus is mental health-related intervention and/or the implementation of a mental health intervention; (2) intervention occurs during or after a major public health event (e.g. disease outbreak, viral pandemic). An intervention is defined as a service performed for, with, or on behalf of a person or populations with the purpose of assessing, improving, maintaining, promoting, or modifying health, functioning, or health condition [ 15 ]. Reasons for exclusion included (1) off topic (i.e. not focused on mental health or pandemic setting); (2) not about intervention (e.g. prevalence studies, disaster preparedness, economic loss); (3) health-related disasters unrelated to disease (e.g. mass violence, natural disasters); (4) health trends described as epidemics (e.g. obesity); (5) systematic reviews (although their references were hand-searched for potentially relevant citations); and (6) full text in language other than English.
• (c) Comparison: Other treatment interventions associated with normal or usual care.
• (d) Outcomes: Studies reporting on the development, effectiveness, and acceptability for mental health interventions designed to improve health functioning.
• (e) Types of studies: To determine effectiveness or report on the outcome of a mental health intervention, we included quantitative study designs (randomized controlled trials [RCTs]; quasi-RCTs; controlled before-after studies; case-control, cohort, and cross-sectional studies; surveys; system-level case studies; and pre-post studies). To understand how individuals perceived and experienced an intervention, we included qualitative study designs.
• (f) Language: No initial limits were placed on language, however, non-English language studies for which interpretation could not be obtained were excluded.
• (g) Country: No limits.

Search terms used to capture the pandemic concept included “pandemic,” “outbreak,” “quarantine,” “shelter in place,” and names of specific epidemic diseases, such as “COVID-19,” “SARS,” and “Ebola.”

Search terms for the mental health concept included subject headings for mental health services and text words such as “mental health,” “mental disorder,” “psychiatry,” “use disorder,” “trauma,” “stress,” and names of specific disorders, in close proximity to intervention terms such as “program,” “service,” and “treatment.”

A total of 2404 titles and abstracts were screened for relevance and possible inclusion. The librarian and the first author independently applied the exclusion criteria to the possible citations. In total, 101 articles were selected for full-text review.

The articles were independently assessed by two reviewers (first author and either second or third author). Disagreements regarding eligibility were resolved by discussion among the reviewers. Through this process, 21 primary research studies were selected for inclusion. The number of articles identified at each stage of the selections process is listed in Fig. 1 .

Flow diagram.

2.2. Methodological quality assessment

The methodological quality of the primary research studies was evaluated using the quantitative and qualitative criteria developed by Kmet and colleagues [ 16 ]. The following quality criteria were considered: question/objectives; study design; methods of participant selection; data collection; describing and reporting of random allocation and/or blinding; robust description of outcome measures; sample size; reporting of variance for the main results; controlling for confounding; and verification and reflexivity (for qualitative studies) [ 16 ].

We performed a reviewer calibration by having two reviewers (second and last authors) independently rate three studies (two studies at the beginning of the review process and a third study calibration check toward the end). The ratings were compared, discrepancies were identified, and the underlying reasons for disagreement were discussed and resolved. The remaining 18 studies were then rated by the second author. Of the 21 studies, 12 met the criteria for high-quality studies (Kmet score > 80%), with seven studies reaching the very high–quality threshold (Kmet score > 90%) [ 17 ]. Table 1 shows the quality ratings for each study, as well as the percentage of missing or incomplete information for each rating criterion.

Quality assessment summary table.

a Quantitative criterion 7 (blinding of participants) not feasible in reviewed studies and therefore not included in this table.

Medium blue = fully met criterion.

Pale blue with X = partially met criterion.

No color with X = missing element.

Grey = not applicable.

We categorized the findings from the primary research studies using the following questions: What kind of emotional reactions do medical pandemics trigger? Who is most at risk of experiencing mental health sequelae? What works to treat mental health sequelae (psychosocial interventions and the implementation of existing or new training programs)? What do we need to consider when designing and implementing mental health interventions (cultural adaptations and mental health workforce)? What still needs to be known? The 21 primary research studies involved nine countries and covered five medical pandemics: MERS (n = 1), SARS (n = 2), influenza pandemics (n = 1), Ebola (n = 6), and COVID-19 (n = 11). Table 2 describes the characteristics of the primary research studies.

Characteristics of primary research articles.

17-HAMD = 17-item Hamilton Depression Scale.

AUDIT-3 = Alcohol Use Disorders Identification Test-C.

DASS21 = Depression, Anxiety, and Stress Scale.

GAD-7 = Generalized Anxiety Disorder (7 item scale).

HADS, HADS-D, HADS-A = Hospital Anxiety and Depression Scale; depression subscale, anxiety subscale.

HAMA = Hamilton Anxiety Scale.

IIP-32 = Inventory of Interpersonal Problems (32 item scale).

ISI = Insomnia Severity Index.

IES-R = Impact of Event Scale-Revised.

MTC-Q1, MTC-Q2 = MusicTeamCare-Q1, MusicTeamCare-Q2.

PCL-C = Post-Traumatic Stress Checklist - Civilian.

PHQ9 = Patient Health Questionnaire.

PRC = People's Republic of China.

ProQOL-5 = Professional Quality of Life Scale (5 items).

PSQI = Pittsburgh Sleep Quality Index.

PSS = psychosocial stress symptoms.

SARS = severe acute respiratory syndrome.

SAS = Self-rating Anxiety Scale (Zung).

SCL-25, SCL-90 = Symptom Checklist 25, Symptom Checklist 90.

SDS = Self-rating Depression Scale (Zung).

SRSS = Sleep State Self-Rating Scale.

STAI = Spielberger State-Trait Anxiety Scale (STAI).

TAU = treatment as usual.

WHOQOL-BREF = World Health Organization Quality of Life (abbreviated version).

3.1. What kind of emotional reactions do medical pandemics trigger?

All of the studies described the emotional stress that health professionals [ [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] ], non-specialists working in health care [ [29] , [30] , [31] ], patients [ [32] , [33] , [34] , [35] ], children [ 36 ], and members of the general public experience during a medical pandemic [ 37 , 38 , 39 ]. The first cases of a novel disease to emerge spark fear among health professionals and non-specialists working in health care because little or nothing is known about the disease or how it is transmitted [ 19 , [22] , [23] , [24] , 37 ]. Added to this fear is a sense of helplessness and uncertainty when the number of cases rises and continues to grow [ 19 ]. As colleagues and patients succumb to the illness, health professionals experience profound grief and sorrow.

Medical pandemics elicit strong emotional reactions, but health professionals cannot refuse to provide care for infected patients. They feel vulnerable, afraid that they will bring the disease home to their families, that they may die, that they will continue to lose colleagues. Many factors contribute to the stress that health professionals feel: the overwhelming workload, shortage of personal protection equipment, constant media coverage, lack of specific treatments, and inadequate support [ 24 ]. Psychological impacts of pandemics such as Ebola on children and their families include extreme stress, loss, and trauma [ 36 ]. The one study published to date on the public's psychological reaction to COVID-19 found that although people are feeling more stress and anxiety, positive reactions such as having faith in the future and feeling blessed for what one has have also surfaced [ 37 ]. Faced with uncertainty, it is common for people to seek positive solutions and social and group solidarity to maintain a sense of purpose and cohesiveness [ [19] , [20] , [21] , 25 , 37 ].

3.2. What are the mental health sequelae?

Of the five studies in our review that focused on the mental health sequelae of COVID-19, only one conducted a true pre- post-test to explore the impacts of medical pandemics on mental health in order to guide policy and interventions for affected populations [ 37 ]. The study used online ecological recognition, an approach based on machine-learning predictive models, to calculate word frequency and emotional and cognitive indicator scores from the postings of regular bloggers on a popular Chinese website. A paired sample t -test was used to examine differences in content before and after January 20, 2020, when COVID-19 was declared to be transmissible by humans. The authors found that negative reactions such as anxiety, depression, and indignation increased after the declaration, and positive experiences such as happiness and life satisfaction decreased. Another study also found cross-sectional associations between emotional well-being, an individual's knowledge about COVID-10, and their sense of control [ 38 , 39 ].

These findings for the general public were echoed in the remaining three COVID-19 studies, which examined the mental well-being of health professionals during medical pandemics [ 23 , 24 , 26 ]. Two studies assessed the mental health of medical staff working in Wuhan, in the Chinese province Hubei [ 23 ], and of health professionals treating patients exposed to COVID-19 in different regions of China [ 24 ]. Both studies found high rates of depression, anxiety, insomnia, and distress using the Patient Health Questionnaire, the Generalized Anxiety Disorder scale, the Insomnia Severity Index, and the Impact of Event Scale–Revised. For example, 70% of respondents reported psychological distress [ 24 ]. Psychological distress varied by gender (higher for women), health profession (higher for nurses), and level of exposure to COVID-19 (higher for those working in the epicenter of the pandemic) [ 23 , 24 ]. Higher rates of symptoms were also found in a third study that used a different set of assessment tools (Symptom Checklist 90, Self-rating Depression and Anxiety Scales, and Post-traumatic Stress Checklist–Civilian). The study also found poorer sleep quality (Pittsburgh Sleep Quality Index) among front-line staff who had higher risks of exposure to COVID-19 [ 26 ].

Some evidence suggests that delays in receiving mental health interventions result in higher rates of baseline negative psychological symptoms. For example, a study that examined the impact of a psychosocial support program for children in 40 Liberian communities identified as Ebola “hot zones” found that the two-month delay in receiving support may have exacerbated the distress that these children felt [ 36 ].

3.3. Who is most at risk of mental health sequelae?

Several studies identified specific populations that are more vulnerable during a medical pandemic and thus have a higher need for mental health interventions, which should be tailored to their specific needs. Among health professionals, women and nurses treating patients with COVID-19 warrant particular attention [ 23 , 24 , 26 ]. Study findings suggest that the relationship between levels of exposure to COVID-19 and levels of mental health symptoms mediates the kinds of support that health professionals prefer [ 23 ]. For example, physicians and nursing staff with higher levels of mental health problems showed more urgent desires to seek help from psychotherapists and psychiatrists while those with subthreshold or mild disturbances preferred to obtain services from medial sources [ 23 ]. Physicians and nursing staff who work at newly created or designated pandemic treatment hospitals at the epicenter of a crisis tend to be the hardest hit emotionally and mentally [ 22 , 24 , 28 ]. Children are another high-risk group. Given their low social status, dependence on caregivers, vulnerability to becoming orphaned during a medical pandemic, and the lack of child-oriented services, children require interventions that address their unique needs [ 36 ].

Our review also found that developing countries face challenges in coordinating efforts and ensuring the quality of training during a medical pandemic [ 29 , 30 ]. Although health professionals sometimes received support from other non-profit organizations, lack of coordination often meant that people received duplicate training from different organizations. Given the shortage of health professionals in developing countries, some non-specialist trainers became involved in providing education during a pandemic because they themselves needed psychological support, and delivering training was the only way they could learn to cope with the situation they were working in [ 29 ].

3.4. What works to treat mental health sequelae?

Sixteen studies on mental health interventions were grouped under two categories: psychosocial interventions (n = 8) and the implementation of existing or new training programs, guidelines, or system-level protocols (n = 8).

3.4.1. Psychosocial interventions

One qualitative study examined group therapy sessions for physicians and nurses who were providing care for SARS patients in Singapore [ 19 ]. The researchers did not measure the efficacy of the therapy, but used the information they gathered to explore the emotional impact on these health care providers. Two trends were identified: the first was the emergence of emotions such as fear, anger, and blame at the beginning of the outbreak. The second trend featured emotions such as grief, frustration, and loss as death tolls rose, including among colleagues. Overall, fear was the most common emotion. Lack of social support, created by the need for distancing, added to the stresses of providing care.

The second study evaluated the effectiveness of a complex three-phase training program for Ebola clinic staff, which was launched when the number of new Ebola cases in Sierra Leone was decreasing [ 20 ]. Phases 1 and 2 involved a well-being workshop and screen, and psychoeducation workshops. Trainees who scored above thresholds for well-being, anxiety, or depression were eligible to attend Phase 3, which involved a 6-week cognitive behavioral therapy (CBT) program delivered by colleagues. The study found some improvement in well-being, anxiety, and depression across all three phases. In Phase 3, CBT participants showed decreased anxiety, depression, PTSD, and stress symptoms, and improved sleep, sense of well-being, and relationships.

Two studies assessed mobile phone–delivered interventions—one for healthcare staff and one for patients. The first study examined the effectiveness of a music therapy intervention for staff working on a coronavirus unit in a hospital in Italy [ 28 ]. During the study, participants self-isolated in a hotel to minimize risk of infecting their families, and listened to playlists that focused on breathing, energy, and serenity. Playlists were customized for each participant based on their listening experience from the previous week. Participants reported their levels of tiredness, sadness, fear, and worry before and after listening to the customized playlists. The study found improvements in these symptoms, especially with the energy playlist, which showed significant changes in all four symptoms.

The second mobile-phone study focused on the impact of an individual consultation intervention on inpatients with suspected COVID-19 who were in quarantine wards in a tertiary hospital in Guangdong, China [ 35 ]. The intervention involved twice-daily 10-minute consultations with an onsite nurse who provided information and support. Participants were assessed using the Hospital Anxiety and Depression Scale before and at the end of the intervention and showed improvement in mood on the anxiety and depression subscales.

Four studies evaluated interventions using a randomized trial design. In the study that examined the impact of a psychosocial support program for Liberian children in Ebola “hot zones,” communities were randomly assigned to a 5-month or a 3-month arts-based program, and all children were eligible to participate [ 36 ]. Both groups showed significant decreases in stress, but there was no statistical difference between the two programs. In discussing why the longer program did not produce better results, the researchers noted that children in the shorter program started two months after those in the longer program and also had higher beginning levels of stress. They speculated that the two-month delay in receiving support may have exacerbated the distress that these children felt.

Three randomized controlled studies examined the efficacy of specific interventions aimed at reducing anxiety or depression symptoms in inpatients with COVID-19. One trial involved progressive muscle relaxation [ 32 ]. Compared with controls, participants in the five-day course showed significant improvement in anxiety and sleep, as measured by the Spielberger State-Trait Anxiety Scale and the Sleep State Self-Rating Scale. The second trial featured a four-session brief crisis intervention to improve resilience by building skills related to: adjustment skills, responsibility and factualism and spirituality [ 34 ]. The intervention group showed greater improvement on symptoms as measured by the Depression, Anxiety, and Stress Scale, SCL-25, and WHOQOL-BREF. In the third trial, which involved an Internet-based self-help intervention, participants showed reduced anxiety symptoms after one week, as assessed by the Hamilton Depression and Hamilton Anxiety scales and even further improvement by the second week [ 33 ]. The common thread in these three studies is the active and sustained involvement of patients in their own care.

3.4.2. Implementation of existing or new training programs, guidelines, and system-level protocols

Eight studies evaluated the implementation of existing or new training programs, guidelines, and system-level protocols. Four focused on the Ebola pandemic; two examined the SARS or influenza-related pandemics; one evaluated a psychosocial support system developed in response to COVID-19; and one used a system-level protocol developed for MERS as a case study.

The Ebola studies examined train-the-trainer programs [ 21 , 25 , 29 , 30 ]. Two also explored a CBT-based peer-to-peer training program [ 21 , 25 ]. One of the CBT-based studies of these involved qualitative interviews with clinical staff; the other assessed the impact of the intervention on clinical staff. Both studies identified implementation barriers and enablers. Among the barriers relevant to the setting (sub-Saharan Africa) were low literacy, cultural understanding of mental health problems, and lack of resources. Enablers included the novelty of the intervention and the opportunity for staff to create social networks. In one of these studies, there were no differences in baseline anxiety and depression symptoms between those holding roles with high versus low risk of exposure to infection [ 25 ]. The authors hypothesized that this finding could be due to factors such as better previous training for the high-risk group, which may have acted as a protective factor. The remaining two studies evaluated a psychological first aid program [ 29 , 30 ]. The first was a qualitative study that involved interviews with psychological first aid trainers, trainees, and administrators in Sierra Leone and Liberia [ 29 ]. Implementation relied on training non-specialists to deliver the intervention. The authors concluded that the quality of the train-the-trainer method varied and that the program content and short duration were better suited to people with more experience. The second study, conducted by members of the same research team, was a cluster-randomized controlled trial evaluating the psychological first aid training of primary care workers in Sierra Leone [ 30 ]. Compared with controls, trainees had improved scores for knowledge about psychological first aid–consistent psychosocial support, both shortly after training and 3 months later (i.e. 6-month post-baseline). Scenario responses (designed to assess whether participants could apply their knowledge in a practical situation), as well as professional attitudes (designed to assess participants' ability to be non-judgmental) also showed improvement for trainees, but only at the 6-month assessment. There was no statistical difference between trainees and controls on confidence levels. These results highlight the value of assessing the impact of training over time, possibly after trainees have a chance to apply what they have learned and to consolidate it with their post-training real-world activities.

The SARS and influenza-pandemic studies examined two very different aspects of dealing with pandemics. The first study examined the impact of a prevention plan on the mental health of nurses in the largest designated SARS hospital in Taiwan [ 22 ]. Anxiety, depression, and sleep quality were measured using the Zung Anxiety and Depression Self-Rating Scale and the Pittsburgh Sleep Quality Index. Nurses were assessed four times: before the program was implemented, 2 weeks and 4 weeks after implementation, and 3 months after the program concluded. Anxiety, depression, and sleep quality showed signs of improvement at 2 weeks, and mental health symptoms continued to decrease over time; however, sleep quality remained poor. The findings suggest that coping ability increases with perceived sense of control over stressful circumstances. The program provided an opportunity for nurses to learn more about SARS and about important prevention measures that buffer the negative impacts of work stress.

The second study assessed whether there was a dose-related response to three durations of a computer-assisted resilience training program for hospital workers [ 27 ]. The study assessed levels of confidence, pandemic self-efficacy, interpersonal problems (Inventory of Interpersonal Problems), and coping (Ways of Coping Inventory). Participants in the medium- and longer-length courses showed improvement across all measures, except coping where improvements were limited to participants who reported underusing coping strategies at baseline. The researchers concluded that, although the longer course was associated with improved outcomes, the findings need to be balanced against the higher dropout rate for this arm of the trial; therefore, they recommended considering the medium-length course as an effective option.

The need for a rapid response to support staff during COVID-19 was the focus of a French study [ 31 ]. In three days, researchers developed a psychosocial support program that was based on a hotline system. In that short time, they were able to gain support from official authorities; recruit and certify hotline responders (certified psychologists) and medical back-up (psychiatrists); create the hotline protocols and content; set up the hotlines; create an anonymized database; and advertise the program. Intended beneficiaries of the program were all staff in a regional group of 39 hospitals. Hotline responders provided rapid assessment, brief crisis resolution, and service referrals. Results supported the feasibility (149 calls within 26 days), spread (callers represented various professions and hospital departments), and utility (70% of callers were also referred to COVID-19 and other kinds of support).

Finally, a case study of a mental health service system protocol designed to address the needs of patients with MERS and their families in South Korea identified areas for improvement going forward [ 39 ]. The system was created for patients in quarantine and for families of MERS patients who had died or recovered. Administrative data collected on quarantined, recovered, and deceased patients were used to describe the flow of individuals through the designated protocols, which included physical and psychological monitoring and assessment by the provincial public health and community mental health centers. The study found that of the more than 6000 patients quarantined, 20% were identified as having emotional problems and 6% had emotional problems needing continual mental health care. Of this latter group, only 35% actually received the indicated care. In addition, having a national access point to provincial or local-level services was not effective, particularly for recovered patients or family members of deceased patients.

3.5. What do we need to consider when designing and implementing mental health interventions?

3.5.1. cultural considerations.

Two of the 21 studies identified in our study merely mentioned culture and the influence of environmental factors as limitations, without explaining how these factors influenced the implementation of mental health interventions for COVID-19 [ 32 , 34 ]. Only five studies, all from Liberia and focusing on the Ebola pandemic, discussed the importance of cultural adaptation to the local context in detail. The remaining 14 studies did not provide contextual or cultural factors related to the implementation of mental health interventions or training.

Two of the five studies described the challenges with implementing and sustaining a CBT intervention related to differing cultural conceptualizations of mental illness, low literacy levels, and competing priorities such as employment [ 21 , 25 ]. These studies describe adaptations to training materials to enhance cultural appropriateness. The interventions emphasized the importance of using or incorporating cultural rituals of healing that embody a community's belief system within mental health and psychosocial programming [ 36 ]. Mental health problems are often conceptualized in ways that differ from the Western biopsychosocial model; for example, they may be caused by witchcraft, evil spirits, or curses. Cultural differences in conceptualizing mental health can make it challenging for participants to understand novel approaches such as CBT that are the focus of many Western-based interventions or training programs [ 21 ]. Moreover, mental health screening and assessment tools such as the Patient Health Questionnaire and the Generalized Anxiety Disorder scale for measuring anxiety and depression were developed in the West and their reliability and validity have not been established in non-Western countries [ 25 ].

Literacy is another consideration. Because CBT typically involves written materials and homework, interventions need to be adapted for patients with low literacy. Validated adaptations of CBT materials for low-literacy populations in general are lacking [ 20 ], but one study that we identified adapted the intervention by including more diagrams and images to depict CBT concepts [ 25 ].

There are also cultural considerations in children's mental health. One study noted that the low status of children in some cultures may make the mental health of this population a low priority [ 36 ]. The authors relied on key partnerships with government ministries for ethical and cultural guidance on creating data collection instruments and collecting information in a culturally appropriate way [ 36 ]. Similarly, the authors of the study on psychological first aid interventions adapted the program's content to reflect the Liberian context during the Ebola outbreak [ 29 , 30 ]. The authors indicate that even when adaptations have been made, it is difficult to ensure the quality of training in delivering the intervention. The authors add that trainees are often expected to change their attitudes and beliefs, as well as learn new skills, and the effort involved in making these changes should not be underestimated [ 29 ].

One study noted that cultural adaptations alone may not be enough to increase the success of an intervention [ 20 ]. For example, in some countries, traditional healers command more respect than trained health professionals, which means that collaborating with them is important to deliver interventions that are effective and sustainable.

3.5.2. Mental health work force

The majority of studies describing mental health interventions or training in low-resource countries acknowledged a shortage of trained mental health professionals [ 21 , 25 , 29 , 32 ]. Although this might also be true in middle- and high-resource countries, none of the studies from China, Canada, France, or Iran provided information on the mental health work force. The one study from Italy indicated that newly recruited clinicians at designated COVID-19 hospitals had inadequate psychological training [ 28 ]. Another study from Liberia described the challenges of using a train-the-trainer model for psychological first aid training as a capacity-building response [ 29 ]. The authors describe how, in the country's economic climate, it was difficult to take people out of their current work environment to attend training. As a result, training sessions were shorter than would be ideal, which affected the quality of training. Because it was also difficult to find non-professionals who had education or training in mental health or psychological support, key ideas or approaches to the intervention were not always implemented as intended. Trainees who lacked adequate education in mental health were often unable to navigate the nuances of therapeutic encounters. Limited mental health knowledge and training time meant that training material could become diluted or misrepresented as successive groups of trainers provide the training.

3.6. What still needs to be known?

Several primary research studies discussed strengths and limitations to their work. Half of the studies noted recruitment bias, small sample size, and response bias as limitations to the generalizability of their findings [ [22] , [23] , [24] , 26 , 33 , [35] , [36] , [37] ]. Collecting data, especially in hectic times at the epicenter of a medical pandemic can be challenging for data collectors [ 36 ]. Incomplete data sets and missing information were common. Future studies should consider ways to distinguish between pre-existing and new mental health symptoms [ 23 ], use larger sample sizes to verify results [ 23 , 28 , 34 ], and adopt study designs such as randomized prospective studies to better determine correlations and causation [ 23 , 27 ].

4. Discussion

Previous medical pandemics have led to policies, working group recommendations, protocols, and interventions that are helping to guide responses to the COVID-19 pandemic. However, it is surprising that few published evaluations of these interventions exist, particularly those arising from SARS.

The primary research articles that do exist provide reasonably strong evidence for several conclusions and recommendations that can provide direction for dealing with COVID-19. The mental health sequelae of pandemics are significant and should be addressed in a timely, sustained way. The psychological response of healthcare workers to medical pandemics is complicated. These pandemics are extraordinary historical events that dramatically change health care services and delivery. When little or nothing is known about highly infectious and unusual viruses, lack of knowledge about the mode of transmission and risk of exposure for medical workers creates a sense of helplessness and uncertainty that lead to a general state of fear. Sources of distress include feelings of vulnerability or loss of control and concerns about one's health and the health of one's family and others, and about the spread of the virus.

A range of mental health services and supports are needed to meet the unique needs of specific groups with different vulnerabilities and risks. Health professionals and other people exposed to COVID-19, including children, are high-needs, high-risk groups. Resources are also needed to support the mental health needs of the general public. This review found that non-psychiatric mental health supports can be effective in addressing mental health concerns during medical pandemics [ 26 , 28 , 32 , 33 , [35] , [36] , [37] ]. Providing opportunities to create social networks and establishing protocols for ensuring safety enhance well-being among health professionals and the general public. Particular attention needs to be paid to cultural considerations when designing and implementing mental health interventions and training. Training non-specialists when mental health professionals are scarce builds capacity and empowers communities to deliver mental health interventions. However, training non-specialists requires time. Without adequate investment, trainees will not be able to provide the emotional and practical support that people need during a pandemic.

The high quality of more than half of the primary research studies that were reviewed in our study provides encouraging support for these recommendations. However, the range of the quality ratings (40–100%) suggests a need for caution. The main reason for lower quality ratings was insufficient, or sometimes lacking, descriptions of two elements: 1) the sampling strategy, sample characteristics, or the underlying population; and 2) discussion or acknowledgment of the limitations of sample size, particularly in quantitative studies. Information gaps for these two criteria create uncertainty about how applicable the findings might be when generalizing to other settings or populations.

Overall, this review revealed that various mental health interventions have been developed for medical pandemics and that research on their effectiveness is growing. However, few studies distinguished between pre-existing mental health problems and those that are triggered by medical pandemics. Studies of the SARS outbreak suggest the need for training and support to bolster the resilience of healthcare professionals, particularly those with a history of mental health problems, in dealing with future pandemics [ 40 , 41 ]. Resilience training for psychologically healthy health professionals will support them not only during the unpredictability of a medical pandemic, but also during regular clinical practice [ 27 , 41 , 42 ]. Our review also found promise in interventions in which people were actively involved in their care over a sustained period [ 32 , 33 ]. When designing mental health interventions for health professionals, we also need to know more about protective factors that buffer the negative psychological impacts during and after a medical pandemic. 42 This review showed some evidence for the importance of evaluating longer-term impacts of training because some impacts are not realized until several months after training [ 30 ].

Another area to explore is digital/social media interventions for mental health support [ 27 , 28 , 31 , 33 , 35 ]. The public health and health care measures used to address COVID-19 (e.g., physical distancing, isolation/quarantine), combined with the high levels of uncertainty and concern, create special stresses, especially on traditional and resource-intensive ways of providing care and support. Interventions that are synchronous (occur in real time) and asynchronous (occur online without real-time interaction) using digital and social media are an increasingly relevant focus for research. Developing and evaluating social media and digital health interventions are ways to extend and support existing interventions, as well as to involve patients and the general public more actively in their own care. The effectiveness of such interventions (both independently and in coordination with other programs), and the feasibility of developing and implementing them are rapidly growing concerns for future research.

4.1. Strengths and limitations of this systematic rapid review

There are limitations and strengths of this review. The search was limited to peer-reviewed publications written in English. Given the large amount of information from China, we would have included members of our team who could read Mandarin if that had been possible. Moreover, by focusing on peer-reviewed literature, we could not capture findings from the grey literature. Strengths of this review included a formal quality appraisal of the articles and a search process that ensured we were able to examine the most recently published articles possible.

4.2. Future research

There are positive signs that more is being done to address mental health during medical pandemics. Since the COVID-19 pandemic emerged, we found seven high-quality articles that focused on COVID-19 [ 23 , 24 , [32] , [33] , [34] , [35] , 37 ], of which two were randomized control trials of interventions [ 32 , 33 ]. In addition, as of August 11, 2020, a search on clinicaltrials.gov , using the terms “mental health interventions” and “COVID-19” for all countries, yielded 33 studies, of which eight focused on the mental health and well-being of health professionals and 25 focused on patients and the general public. We interpret these findings as showing global readiness to move toward study designs that better determine correlation and causation. There is a need for continued support and focus on evaluations in order to develop an even stronger evidence base for addressing future medical pandemics. This is the time to capitalize on the momentum for building a robust evidence base for COVID-19. Doing so will assist people in immediate need of mental health support and help to plan multi-pronged mitigation strategies for the future.

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

CRediT authorship contribution statement

Sophie Soklaridis contributed to the literature search, study design, figures, data collection, data analysis, data interpretation, and writing of the manuscript.

Elizabeth Lin contributed to the literature search, figures, study design, data collection, data analysis, quality assessment, data interpretation, and writing of the manuscript.

Yasmin Lalani contributed to data collection, data analysis, data interpretation, and writing of the manuscript.

Terri Rodak contributed to the literature search, study design, data collection, and writing of the manuscript.

Sanjeev Sockalingam contributed to the study design, figures, data interpretation, quality assessment, and writing of the manuscript.

Declaration of competing interest

Acknowledgement.

We would like to thank Hema Zbogar for her editorial support in preparing this manuscript.

Data availability

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.genhosppsych.2020.08.007 .

Appendix A. Supplementary data

Supplementary material 1

Supplementary material 2

Enhancing Student Mental Health During COVID-19