adhd case study frankie

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Int J Environ Res Public Health

A Case Study in Attention-Deficit/Hyperactivity Disorder: An Innovative Neurofeedback-Based Approach

Associated data.

The data presented in this study are available on request from the corresponding author.

In research about attention-deficit/hyperactivity disorder (ADHD) there is growing interest in evaluating cortical activation and using neurofeedback in interventions. This paper presents a case study using monopolar electroencephalogram recording (brain mapping known as MiniQ) for subsequent use in an intervention with neurofeedback for a 10-year-old girl presenting predominantly inattentive ADHD. A total of 75 training sessions were performed, and brain wave activity was assessed before and after the intervention. The results indicated post-treatment benefits in the beta wave (related to a higher level of concentration) and in the theta/beta ratio, but not in the theta wave (related to higher levels of drowsiness and distraction). These instruments may be beneficial in the evaluation and treatment of ADHD.

1. Introduction

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common childhood disorders, affecting between 5.9% and 7.2% of the infant and adolescent population. The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders [ 1 ] describes ADHD as a neurodevelopmental disorder characterized by a persistent pattern of inattention, hyperactivity, and impulsivity manifesting in children before the age of 12 years old more frequently and with greater severity than expected in children of equivalent ages. Depending on the predominant symptoms, three types of presentation may be identified: predominantly hyperactive-impulsive, predominantly inattentive, and combined. There are two theories that attempt to explain the neurophysiological nature and characteristics of ADHD. Mirsky posited a deficit in attention as the main focus in ADHD, such that the failure is found in processes of activation [ 2 ]. The other theory was proposed by Barkley, who attributed the problems of ADHD to a deficit in behavioral regulation, where processes associated with the frontal cortex fail [ 3 ].

The determination of ADHD symptoms, along with the underlying neuropsychology, as outlined by the theories above, have led in recent years to the incorporation of evaluation and intervention techniques that do not solely focus on the behavioral aspects of the disorder. More specifically, techniques such as electroencephalography in ADHD evaluation and neurofeedback in interventions may provide greater benefits in detection and treatment.

The present study analyzes a specific case of ADHD with predominantly inattentive presentation, covering monopolar electroencephalogram recording (brain mapping called MiniQ) and intervention via neurofeedback.

The study was approved by the relevant Ethics Committee of the Principality of Asturias (reference: PMP/ICH/135/95; code: TDAH-Oviedo), and all procedures complied with relevant laws and institutional guidelines.

1.1. Evaluation of ADHD

The current diagnostic criteria for ADHD can be found in the DSM-5 [ 1 ] and in the International Statistical Classification of Diseases and Related Health Problems, eleventh revision, from the World Health Organization [ 4 ]. Various evaluation instruments are used to identify ADHD, from general assessments via broad scales such as the Wechsler scale, to more specific tests assessing execution (e.g., test of variables of attention, D2 attention test), symptoms (e.g., Conners scale, EDAH scale), and the evaluation of cortical activity (e.g., using quantitative electroencephalograms, qEEG).

One alternative to qEEG is monopolar EEG recording (fundamentally used in clinical practice), called MiniQ (software Biograph Infinity, ThoughtTech, Montreal, QC, Canada). The MiniQ is an instrument for evaluating brain waves from 12 cortical locations (international 10/20 system) [ 5 ]. This type of evaluation (monopolar EEG, MiniQ) lies somewhere between the traditional baseline (single-channel qEEG) and full brain mapping. The frequency ranges evaluated match the classics [ 6 , 7 ]: delta 1–4 Hz, theta 4–8 Hz, alpha 8–12 Hz, sensorimotor rhythm SMR 12–15 Hz, beta 13–21 Hz, beta3 or high beta 20–32 Hz, and gamma 38–42 Hz. Theta waves have been related to low activation, sleep states, and low levels of awareness, beta and alpha waves have been associated with higher levels of attention and concentration [ 8 ]. In addition, the MiniQ, in line with qEEG, provides the relationships or ratios of theta/alpha, theta/beta, SMR/theta and peak alpha. Previous research has established that the ratio between theta and beta waves is a better indicator of brain activity than each wave taken separately (see Rodríguez et al. [ 9 ]). Monastra et al. attempted to establish what values of the theta/beta ratio would be compatible with those seen in subjects with ADHD [ 7 ]. They indicated critical values (cutoff points) for ADHD in theta/beta absolute power ratio, using 1.5 standard deviations compared to the control groups and based on age, those cutoff points are: 4.36 (6–11 years old), 2.89 (12–15 years old), 2.24 (16–20 years old), and 1.92 (21–30 years old). Higher values than the cutoff points would indicate a profile that is compatible with a subject with ADHD.

The distribution of electrical brain activity must be analyzed considering each site and the expected frequency. A regulated subject is characterized by more rapid activity in the frontal regions (predominantly beta) which decreases toward the posterior (occipital) regions, where slower waves (theta and delta) are expected [ 10 , 11 ]. Slower brainwaves are expected to predominate in the right hemisphere compared to the left, in which faster waves predominate. More specifically, beta waves will predominate in the left hemisphere, alpha waves in the right hemisphere, and there will be similar levels of theta waves in both. In addition, during a task (e.g., reading or arithmetic) rapid (beta) waves are expected to increase.

In contrast, the electrical activity in a subject with predominantly inattentive ADHD is characterized by a predominance of theta waves (compared to beta) in the frontal regions, particularly on the left (F3). During tasks (e.g., reading or arithmetic), a subject with predominantly inattentive ADHD will exhibit increased slower (theta) waves, and there will be a slowdown in the frontal regions that hinders attentional quality, as suggested by researchers such as Clarke et al. [ 10 ] and more recently, Kerson et al. [ 12 ]. Studying the profile of cortical activation allows suitable intervention protocols to be established and tailored to each subject.

1.2. ADHD Intervention

Many studies have examined the efficacy of the various treatments and interventions aimed at improving symptoms associated with ADHD (inattention, hyperactivity, and impulsivity), such as medication, behavioral treatments, and neurofeedback (see Caye et al. [ 13 ]). Neurofeedback is a type of biofeedback which aims for the subject to be aware of their brain activity and to be able to regulate it via classical conditioning processes [ 14 , 15 ]. In neurofeedback training, a subject’s electrical brain activity is recorded via an electroencephalograph, and the signal is filtered and exported to a computer. Software then transforms and quantifies the brainwaves, presenting them in the form of a game with movement or sounds which give the subject feedback about their brain activity [ 16 ].

The use of neurofeedback in interventions for ADHD began in 1973, although the first study with positive results was published in 1976 [ 17 ]. Since then, various studies have reported benefits from using neurofeedback in infants, with improvements in behavior, attention, and impulsivity control (e.g., [ 18 , 19 , 20 , 21 , 22 ]). A meta-analysis by Arns et al. [ 14 ] concluded that treatment of ADHD with neurofeedback could be considered “effective and specific”, with a large effect size for attention deficit and impulsivity and a moderate effect size for hyperactivity. In a systematic review and meta-analysis, Van Doren et al. [ 21 ] found that neurofeedback demonstrated moderate benefits for attention and hyperactivity-impulsivity, which were maintained in subsequent follow-ups (between 2 and 12 months after the intervention). However, in a recent meta-analysis aimed at comparing the effects of methylphenidate and neurofeedback on the main symptoms of ADHD, Yan et al. [ 20 ] found methylphenidate to be better than neurofeedback, although the authors highlighted that the results were inconsistent between evaluators.

Neurofeedback training is normally done two or three times a week, and around 40 sessions are needed to see changes in symptomatology [ 13 ]. Although it is an expensive treatment that needs consistency and continuity, in the USA, around 10% of children and adolescents with ADHD have received neurofeedback [ 23 ]. The benefits of neurofeedback training may depend on the type of protocol used. The three most-commonly used protocols in subjects with ADHD are [ 14 ]: (1) theta/beta ratio; (2) sensorimotor rhythm, SMR; and (3) slow cortical potential. The most widely used of these three protocols is the theta/beta ratio, based on inhibition of theta and increasing beta, which usually improves SMR at the same time [ 13 ]. However, it is important to note that there is no recommended standard about the number, time or frequency of sessions, and there is no standard placement of NF screening when this type of protocol is administered [ 24 , 25 ]. In this context, the present study aims to provide a structure in which the neurofeedback intervention is adjusted based on the data provided by the previous assessment in a specific case.

The intervention protocol must be tailored to each individual case based on prior assessment, especially when using results from tests such as the MiniQ. In this context, the objective of the current study is to present the process of analyzing brainwaves in a case with ADHD (predominantly inattentive presentation) via the MiniQ test, the protocol for intervention using neurofeedback, and its efficacy. Although the alteration of brainwaves in specific areas in subjects with ADHD is well documented, and the efficacy of neurofeedback has been observed in various studies, the present study aims to provide a specific procedure for assessment and intervention. Researchers and professionals need specific protocols and procedures that allow them to determine what is effective for each individual case.

2. Methodology

2.1. description of the case.

This was a case study using monopolar electroencephalogram recording (brain mapping known as MiniQ) for subsequent use in an intervention with neurofeedback for a 10-year-old girl presenting predominantly inattentive ADHD.

2.1.1. Patient Identification

The subject was a 10-year-old girl in the fourth year of primary education. Her academic performance was poor, with the worst results in language, social sciences, and science. She found it difficult to go to school and was shy and reserved. She was the younger of two sisters, the older being an outstanding pupil. Her mother characterized her as a quiet girl who needed a lot of time to do any kind of task. In addition, during the study and academic tasks, she would often gaze into space, as if she were in her own world. Both her father and her mother evidenced concern for her school results, but also for her social relationships, as her self-absorption appeared in all contexts, making it hard for her to have conversations, pay attention to others, or follow the rules in games.

2.1.2. Reason for Consultation

The consultation was for poor academic performance, slowness doing tasks, and wandering attention from when she had started school, although that had increased in the previous year. Initially, the subject did not demonstrate any great willingness to attend the consultations, but over time, she demonstrated a participative attitude with good involvement in doing the tasks she was set.

2.1.3. History of the Problem

The subject’s school history was one of failure in the main school subjects. She had not had to repeat a school year, but her form tutors repeatedly raised this possibility with her parents. At the time of the study, there had been no clinical or educational psychology assessments. Previous diagnosis of ADHD was by her neuropediatrician one month before the assessment in the Psychology clinic consultation. From that point, guidelines were given for pharmacological treatment, which had not begun.

2.2. Proposed Evaluation and Intervention

2.2.1. evaluation: brainwave analysis with the miniq instrument.

An assessment was performed using a MiniQ (Monopolar, from Biograph Infinity). Assessment using the MiniQ is a two-step process (evaluation and interpretation) which is simple, relatively fast, and inexpensive.

The first step is to make the recording from the 12 cortical sites, which can be done with eyes closed or open, and either with or without tasks (reading or arithmetic). This gives information about the values of the different brainwaves at each site. To begin, electrodes are placed on the earlobes and two active electrodes in each of the sites indicated by the program. Before beginning the assessment for each site, the impedance level—the quality of the connection—for each of the electrodes must be checked, both on the ears and on the scalp, to avoid artefacts. When the impedance level is below 4, the recording process can begin. The subject is instructed to remain still and to look at the computer screen where there is an image of a landscape. They must keep their eyes open and keep silent. The program guides the application, which is based on the placement of electrodes in groups of two following the sequence: Cz–Fz, Cz–Pz, F3–F4, C3–C4, P3–P4, O1–O2, and T3–T4. For sites F3–F4, subjects are asked to read a story quietly and to do some simple arithmetic (e.g., 2 + 3, +5, +4, −1, +6, −3, etc.). Once recordings have been made at all of the sites, the program filters the data to remove artefacts. Finally, the recorded data is interpreted, and the values are analyzed, allowing the state of the subjects’ brainwaves to be determined. Applying the test takes approximately 60 min.

The second step is to analyze the collected data considering the site and the frequency ranges at each. The sites are labelled based on the four quadrants of the cortex: anterior, posterior, left hemisphere (odd numbers), and right hemisphere (even numbers). The instrument gives the results in two formats, an Excel spreadsheet and a PowerPoint. In addition to the measurements or wave values (delta, theta, alpha, sensorimotor rhythm SMR, beta, beta3, and gamma) at the sites noted above, the spreadsheet also includes the values for the ratios of theta/alpha, theta/beta, SMR/theta, and peak alpha. The PowerPoint presentation gives the same information, although over a background image of a brain, which allows scores to be seen at the relevant site (see Figure 1 ). With that information, it is possible to assess cerebral asymmetry, both anterior-posterior and right-left, according to each location.

Pre-treatment results from the MiniQ instrument. Note . T = theta; B = beta; T/B = theta/beta ratio. In subjects aged between 7 and 11 years old, values over 2.8 for the theta/beta ratio are compatible with a profile of ADHD.

The values of the theta/beta ratios are interpreted based on Monastra et al. (1999) [ 7 ], bearing in mind that in this case, the scores were relative power not absolute. Scores are indicative of ADHD when the values are over 2.5 for those up to 7 years old, over 2.8 for 7- to 11-year-olds, over 2.4 in adolescents, and over 1.8 in adults. Traditional ratios for ADHD indicators use absolute power values measured in peak volts (microvolts squared divided by the hertz value). Biograph for theta/beta ratio calculation uses relative power values (microvolts divided by the hertz value).

2.2.2. Intervention: Neurofeedback Protocols

The intervention was carried out using the Biograph Infiniti biofeedback software (Procomp2 from Thought Technology, Montreal, QC, Canada; https://thoughttechnology.com/ , accessed on 23 December 2021). Two protocols were used in the intervention process, an SMR protocol and a theta/beta protocol. The protocol and specific sites selected were based on the prior evaluation.

The SMR protocol used site Cz and was designed to work on three frequencies, theta, SMR, and beta3 [ 26 ]. The objective of this kind of protocol is to perform SMR (12–15 Hz) training to increase the production of this wave and inhibit the production of theta (4–7 Hz) and beta3 (20–32 Hz) activity. During the training sessions, the subject watches a videogame or a film on the screen. Following the neurofeedback dynamic, the game or the film progresses positively if the level of electrical activity increases and stops when the level of electrical activity falls. Reinforcement occurs when the value of theta and beta3 are below the set value and SMR is above a pre-determined threshold. The reinforcement consists of a sound and points awarded to the subject. The working thresholds are provided by the program automatically, although they can be modified manually by the therapist. The level of reinforcement is set by the therapist. Initially, it is set at 80%, and depending on how the subject masters the task, the reinforcement is reduced. The subject is not given explicit instructions about what they have to do; they are told “try to keep the animation on the screen moving”.

The theta/beta protocol works at site Fz. The aim of this protocol is to reduce the amplitude of theta waves and increase beta to work on concentration. The subject has to do tasks which consist of concentrating on a game that appears on the computer screen. The game presents a pink square (which represents the value of theta) and a blue square (representing the value of beta). The subject is told that the game involves trying to make the pink square as small as possible and the blue square as large as possible. The computer automatically generates the ranges over which the waves are worked, although they can be changed manually by the therapist. The desired working theta/beta ratio can also be set manually. The protocol begins with high ratios, close to three, such that the task is simple and the subject achieves reinforcement on many occasions. The ratio is progressively reduced according to the subject’s progress.

The intervention lasted for a year and consisted of 75 neurofeedback sessions. There were two phases to the training. The first phase, “the regulation phase”, covered the first 15 sessions, during which the SMR protocol was followed at Cz. The aim of this first phase was to strengthen SMR and inhibit theta and beta3 in the central region. These sessions were around 45 min each. To avoid tiredness, different presentations of neurofeedback were used (videogame or film) during the sessions, with five-minute breaks between each presentation.

The second phase ran from session 16 to session 75. In these sessions, the SMR protocol at Cz was applied for 20 min, followed by a five-minute break before the theta/beta protocol at Fz was applied for another 20 min. For the first six months of the intervention, sessions were 45 min, twice weekly. During the remaining six months, the sessions were weekly and remained 45 min long.

3.1. Brainwave Evaluation

Based on the information obtained over the evaluation of the case, and considering the prior diagnosis from her pediatric neurologist, the subject presented ADHD with predominantly inattentive presentation. As Figure 1 shows, her brainwave profile indicated scores for the theta/beta ratio of close to 2.8 in the central (Cz) and frontal regions (Fz). Considering the scores in Cz and Fz, the neurofeedback needed to include these sites. Furthermore, neurofeedback on frontal-midline theta (Fz) has been shown to be frequently more effective than neurofeedback protocols that do not include Fz [ 22 ].

Given the brainwave profile, the aim of the intervention was to reduce theta and increase beta in the frontal zones. That indicated using the SMR and theta/beta protocols [ 15 ].

3.2. Progression following Neurofeedback Intervention

Once the neurofeedback intervention was completed, brainwave activity was assessed again using the MiniQ. Figure 2 illustrates the change in theta, beta, and SMR, along with the theta/beta ratio at sites Cz and Fz. The results show a positive progression following the neurofeedback training.

Pre- and post-treatment activity in sites Cz and Fz.

Theta activity fell following the intervention, both at Fz (by 0.77) and at Cz (by 1.56). To put it another way, there was a reduction in the slow wave at both sites (mainly in the central region compared to the frontal region). This is in line with expected values of theta at the cortical level, as they should be higher in posterior areas and lower in frontal areas.

There was also an increase in beta at the two sites, with a 3.60-point increase at Fz and a 4.2-point increase at Cz. In this case, the intervention produced considerable increases in the rapid wave values at both sites, although the value was slightly higher in the central area than in the frontal. Values for beta waves are expected to be higher in frontal areas than central areas, and although that was not the case here, the values were very close. The SMR wave also increased notably, by 2.57 points at Fz and 2.89 points at Cz. In short, the intervention led to a slight reduction in the slow wave, with lower values at post-treatment (less distraction), and increases in fast waves, beta, and SMR, with higher values after the intervention (better ability to concentrate). The theta/beta ratio also decreased at post-treatment (basically due to the increase in beta), both at Fz (by 0.69) and Cz (by 0.96), from values close to those for ADHD to scores more indicative of a subject without ADHD.

In addition, as initially proposed, the assessment with the MiniQ also considered the subject’s activation levels during reading and arithmetic tasks. Measurement of these values was at sites F3 and F4. The subject did three types of task for two minutes each: Paying attention to the screen on which a landscape appeared, reading a story, and doing simple arithmetic (addition and subtraction). As Figure 3 shows, post-treatment scores were different than pre-treatment scores.

Pre- and post-treatment evolution in F3 and F4 areas with and without tasks.

In the first task (pay attention to the screen), the values for theta, beta, and beta3 at F3 and F4 all rose. In the second and third tasks (reading and arithmetic), there were variations in all of the waves, both slow and fast. These results indicate that there was no improvement during tasks following the intervention, because although the fast waves (beta and beta3) increased, the slow wave (theta) did not diminish. Following the intervention, the expectation was to have increased levels of beta and beta3 (especially at F3), while reducing levels of theta. However, as Figure 3 shows, the theta/beta ratio fell, with lower values post-treatment.

4. Discussion

The aim of this study was to present the process for detecting a case of ADHD (predominantly inattentive presentation) using the MiniQ test, along with the neurofeedback intervention protocol and its efficacy. In terms of detection, the MiniQ showed the subjects’ brain activity, which together with behavioral symptoms, provided details of their characteristic profile and allowed tailored treatment. Various studies in the literature have concluded that children with ADHD exhibit higher levels of theta waves and lower levels of beta waves, particularly in frontal areas [ 10 , 11 ]. In addition, the relationship between the theta and beta waves (the theta/beta ratio) had already been associated with ADHD symptomatology through the research by Monastra et al. [ 7 ] and Jarrett et al. [ 27 ].

In the current case study, the MiniQ was relatively simple to apply, and it provided large amounts of information related to brainwave values at the 12 different sites. More specifically, the EEG record of the 10-year-old subject showed lower levels of beta activity in the frontal regions and a higher level of theta activity in the frontal and central regions. However, the slow wave (theta) should be higher in posterior regions and fall in the central area, whereas the fast waves (beta and beta3) should be higher in the anterior regions and lower in the posterior. The subject’s theta/beta ratio was high (Cz: 2.05) and close to values seen in subjects with ADHD according to Monastra et al. [ 7 ]. and Jarrett et al. [ 27 ]. Although the theta/beta ratio was not high enough to clearly or exactly indicate the presence of ADHD with predominantly inattentive presentation, it is important to consider the full set of data provided by the MiniQ. It is also important to note that the diagnosis of ADHD was reported by the neuropediatrician, who usually uses behavioral criteria. At the same time, we cannot ignore the fact that the use of the theta/beta ratio has also been questioned by other works (e.g., [ 28 ]). In any case, the importance of the brainwave analysis lay in helping decide which intervention protocols to follow, along with the frequencies and the sites to use. The chosen neurofeedback protocols were the SMR protocol and the theta/beta protocol. There were 75 intervention sessions, 45 SMR at Cz and 30 theta/beta at Fz. Once the intervention was complete, the changes in theta, beta, beta3 and SMR waves were assessed using the MiniQ.

The intervention produced a variety of results. Firstly, there was a small reduction in theta activity and an increase in SMR, which would indicate better levels of attention. In addition, the theta/beta ratio fell to levels which were closer to those in subjects without ADHD. However, this improvement in the theta/beta ratio was due to increased beta rather than by the reduction of theta. Janssen et al. found similar results in 38 children with ADHD by analyzing the learning curve during 29 neurofeedback training sessions [ 29 ]. Their results indicated that while theta activity did not change over the course of the sessions, beta activity showed a linear increase during the study. In our study, the subject was able to significantly improve the levels of beta, but was hardly able to reduce theta activity, which is what would allow even greater improvements in attentional ability. Given this progress, the use of a protocol for inhibition of theta waves at Fz may be effective in strengthening the development of attention levels. Although there were no notable changes at other sites, such as F3 and F4, it is important to note that the intervention was carried out only at Cz and Fz.

On similar lines, during tasks after the intervention (reading and arithmetic), there was no reduction in theta but there was an increase in beta and beta3, again in line with the results from Janssen et al. [ 29 ]. For reading and arithmetic, one would expect, at least in subjects without ADHD, that in the frontal regions, values of slow waves would fall and fast waves would rise. However, in this study, there was no increase in beta waves in frontal regions during the tasks. This may indicate that although the neurofeedback intervention protocols in subjects with ADHD produce improvements in baseline activation (increased beta), the same does not happen with activation during the execution of tasks such as reading and arithmetic. In addition, Monastra et al. [ 7 ] showed that the activation profile of subjects with ADHD was similar with no task and during a reading task (unlike the control subjects, in whom activation increased during the reading task). Although this fact may be related to the ADHD profile, in our case study, with 75 neurofeedback sessions, we found no differences in the activation of frontal areas during a specific task, such as reading or mathematics.

As Enriquez-Geppert et al. [ 24 ] and Duric et al. [ 25 ] state, it is still necessary to develop specific procedures (which consider electrode placement and the specific theta/beta, SMR or slow cortical potential protocol) for intervention tailored to the different cases that professionals may find in clinical practice, in order to achieve better results. In this regard, it would be interesting to study theta/beta-ratio learning curves during intervention with neurofeedback, with the aim of achieving better results and making this tool as adaptive as possible in the future.

5. Conclusions

These results point toward the hypothesis that the low baseline cortical activation seen in subjects with ADHD would be found to be the basis of the disorder. While neurofeedback training may produce a positive progression, difficulties would persist, particularly during specific tasks in which subjects with ADHD are unable to achieve an ideal profile of brainwave activity for optimum performance. This is a reflection of the fact that the disorder persists throughout life, and hence, despite improvements in the cortical activation profile and the subject learning to strengthen their beta wave activity to concentrate, there will continue to be high levels of theta.

In this context, various studies such as Doppelmayr and Weber [ 30 ] and Vernon et al. [ 31 ] have reported the benefits of the SMR protocol and others, such as Arns et al. [ 13 ], Gevensleben et al. [ 32 ] and Leins et al. [ 33 ], have done the same with regard to the theta/beta protocol. However, other studies, such as Cortese et al. [ 34 ] and Logemann et al. [ 35 ], have not found improvements following neurofeedback intervention in children with ADHD. Considering these differences between previous studies, it would be interesting to establish the benefits of one or other of the protocols in interventions in children with ADHD. For example, in adults without ADHD symptoms, Doppelmayr and Weber [ 30 ] examined the efficacy of the theta/beta and SMR protocols. They found that the subjects who followed the SMR protocol were able to modulate their brain activity, whereas the theta/beta protocol did not provide benefits in regulation of brain activity.

It is also worth noting that, while previous studies employed similar protocols (SMR, theta/beta), the numbers of sessions and the session durations varied between studies. These variations may be related to the differences in the results and indicate the need to establish intervention protocols not only about what to work with (brain waves) but also how to do it (e.g., number of sessions, session duration, break schedules, etc.). At the same time, the present study underscores the need to tailor protocols to subjects’ profiles, along the same lines as previous studies, for instance Cueli et al. [ 16 ], who noted differences in the benefits of interventions based on the type of ADHD presentation. As authors such as Leins et al. [ 33 ] have indicated, most neurofeedback intervention programs combine two protocols, and it would be interesting to determine whether the combination is more effective than applying a single protocol.

In the future, it would be advisable to assess subjects’ levels of activation every 10 to 15 sessions of neurofeedback training in order to tailor the protocols to their progress and to study the theta/beta ratio learning curve as mentioned above. One limitation it is important to note is that multidomain assessments before, during, and after treatment (and adequate follow-up) should include blinding and sham inertness Another limitation of the present study is the lack of a behavioral assessment that would allow for an in-depth analysis of the subject’s progress in line with the protocol from Holtmann et al. [ 36 ]. At the same time, in spite of the limitations associated with case studies, such as not being able to produce generalizable results, the present work aims to be of some use to clinical and educational professionals so that they may consider intervention protocols for cases similar to the one described here.

Finally, despite the limitations described above, it would also be useful to consider the possibility of incorporating this type of training in more cases of subjects with ADHD, because neurofeedback intervention may offer long-term benefits in terms of improving the attentional abilities of subjects with ADHD, especially if one considers that approximately a third of ADHD patients do not respond to, or sufficiently tolerate, pharmacological treatment [ 37 ]. In this regard, it would be interesting to analyze the efficacy of new potential tools that combine neurofeedback and virtual reality and incorporate them into clinical practice [ 38 ].

Author Contributions

Conceptualization, P.C. and M.C.; methodology, all authors; formal analysis, M.C. and P.G.-C.; data curation, L.M.C. and P.G.-C.; writing—original draft preparation, P.C., M.C., and L.M.C.; writing—review and editing, P.G.-C.; visualization, P.C.; supervision M.C. and P.G.-C.; project administration, P.C. and P.G.-C.; funding acquisition, P.G.-C. All authors have read and agreed to the published version of the manuscript.

This study was made possible thanks to financing from the Ministry of Sciences and Innovation I + D + i project with reference PGC2018-097739-B-I00; and a pre-doctoral grant from the Severo Ochoa Program with reference BP19-022.

Institutional Review Board Statement

Ethical review and approval were waived for this study, because the study did not involve biological human experiment and patient data. The study was approved by the relevant Ethics Committee of the Principality of Asturias (reference: PMP/ICH/135/95; code: TDAH-Oviedo), and all procedures complied with relevant laws and institutional guidelines.

Informed Consent Statement

Informed consent was obtained from the family involved in this study.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

• Subscribe to journal Subscribe
• Get new issue alerts Get alerts

Secondary Logo

Journal logo.

Colleague's E-mail is Invalid

Your message has been successfully sent to your colleague.

Save my selection

An 8-Year-Old Boy with School Difficulties and "Odd Behavior"

Frankie is an 8-year-old boy seen in consultation because of school difficulties in second grade and "odd behavior." His family has been concerned about him for the past 2 years, and he has had psychological testing at school. His parents are seeking another evaluation now because they are concerned that his school performance is declining and his self-confidence is decreasing.

Frankie was born at term weighing 7 lb, 3 oz. Delivery was complicated by the "cord around the neck," but Apgar scores were 8 and 9, and he had no difficulties in the neonatal period. He went home with his mother. As an infant he was easily soothed and liked to be held. He sat at 6 months, crawled at 8 months, and walked alone at 14 months. He spoke three intelligible words at 1 year and was speaking in sentences by 2 years. He was fully toilet trained by 2 years, 9 months. He had no significant medical illnesses.

His parents began to be concerned about Frankie when his preschool teacher noted a concern about his fine motor skills. She remarked also that, although he had no problems socially, he seemed happy to play alone. From a very early age, he liked ropes and often carried around a length of rope as some children carry a blanket. He was never a difficult child or disruptive at home or in his preschool. The only problem his parents have had is that he tends to get extremely involved in a particular activity (watching TV, building with LEGO blocks), and it is very difficult to turn his attention away from that activity to a family task. At the same time, he is also noted to be easily distracted from tasks in which he has less investment.

Frankie's father is said to have attention-deficit hyperactivity disorder (ADHD) and learning disabilities, and he is being treated with a selective serotonin reuptake inhibitor (SSRI) for depression. He works as a successful carpenter and builder. A maternal uncle had Down syndrome and died at the age of 17 years as a result of heart disease. There is no other contributory family history. A 12-year-old sister is successful academically and socially. Frankie's mother is a librarian. The grandparents live nearby and share the parents' concerns about Frankie.

He was evaluated a year earlier by his pediatrician and thought to have attention deficit disorder, primarily because of distractibility and easy frustration. He is not oppositional but does have emotional outbursts and cries easily when frustrated. He was noted to carry with him a piece of rope and to play with it repetitively. A trial of methylphenidate was considered unsuccessful. An occupational therapy evaluation revealed low muscle tone and difficulty with visual-motor skills and handwriting. He was said to have "sensory integration problems," and twice-weekly occupational therapy interventions were recommended. His parents requested our opinion about this recommendation.

Frankie's academic work was considered average by his teacher in all areas, though weakest in spelling and reading. He was particularly strong in oral expression and noted to have excellent vocabulary and knowledge. He hesitated to participate in group activities and frequently needed considerable encouragement. On the other hand, he was noted to be liked by his peers and was not disruptive. His main weaknesses were considered to be in organization and attentional skills. Handwriting is difficult and slow, and thus written work is a particular challenge.

His parents noted that Frankie remembers "everything" in detail. He is very talkative and has a great sense of humor. He loves to speak in groups and is "a ham" when given a microphone. He enjoys crafts of all sorts and playing with LEGO blocks. He likes music. His favorite TV programs are educational ones, from which he seems to learn a lot of information easily. He has made several extensive presentations to his class based on what he has learned from such programs. Relationships among all members of the family are said to be excellent. Frankie continues to enjoy playing with ropes and similar objects, and his parents have made some rules to keep this from interfering in family activities. He participates in family and classroom activities.

The Behavioral Assessment System for Children (BASC) checklist was completed by both his teacher and his mother. The teacher's responses suggested concerns in the subscales of Anxiety/Depression, Attention, Adaptability, and Atypicality. Social Skills were a notable strength. The mother's responses suggested concerns in Attention, Adaptability, and Social Withdrawal.

Frankie's parents and teacher completed a checklist based on the DSM-IV criteria for ADHD. Both parents noted three items among the hyperactivity cluster and five among the inattentive cluster to be "often or very true" for Frankie. His teacher noted four inattentive items and two hyperactivity items to be true.

The Woodcock-Johnson Battery revealed a standard score of 100, with particular strength in Short Term Retrieval and relative weaknesses in Auditory Processing and Processing Speed. Math skills, reading, and written language were average, whereas knowledge in all areas was in the superior range. On the WISC-III, Frankie's Verbal IQ was 104 and Performance was 97. The highest subscales were Vocabulary (13) and Similarities (12); the lowest were Coding (6) and Symbol Search (6).

On evaluation, Frankie was a pleasant and cooperative young man who participated in all tasks and related appropriately. His neurological examination was normal. He held a pencil or crayon tensely and wrote slowly and laboriously with tremendous pressure. He did not appear to be anxious during the evaluation. He kept a short piece of rope with him at all times and occasionally fiddled with it. He complied with all requests passively and did not initiate conversation or activities. He had no difficulty making transitions from one activity to another even when specifically challenged.

There are several discrete conditions that may be applied in this case. Is it in the child's best interest to define which diagnosis fits him best? Is it acceptable to provide the parents and teachers with some guidelines for helping Frankie to succeed in school and at home, and to "wait and see" how he develops over time? Would some practitioners initiate a trial of a pharmacological intervention?

Full Text Access for Subscribers:

Individual subscribers.

SDBP Members

Institutional Users

Not a subscriber.

You can read the full text of this article if you:

• + Favorites
• View in Gallery

Patient Case #1: 19-Year-Old Male With ADHD

• Craig Chepke, MD, DFAPA, FAPA
• Andrew J. Cutler, MD

Stephen Faraone, PhD, presents the case of a 19-year-old male with ADHD.

EP: 1 . Prevalence of Adult ADHD

Ep: 2 . diagnosis and management of adults adhd compared to children.

EP: 3 . Diagnosing Adults With ADHD Based on Patient Presentation

EP: 4 . Unmet Needs in the Treatment of Adult ADHD

EP: 5 . Efficacy and Safety of Treatment Options Utilized in Adult ADHD

Ep: 6 . future of adult adhd, ep: 7 . patient case #1: 19-year-old male with adhd.

EP: 8 . Patient Case #1: Prompting an ADHD Consultation

Ep: 9 . patient case #1: differentiating between adhd and other psychiatric comorbidities, ep: 10 . patient case #1: co-managing adhd, ep: 11 . patient case #1: dealing with treatment delay in adult adhd, ep: 12 . patient case #2: a 23-year-old patient with adhd, ep: 13 . patient case #2: impressions and challenges in adult adhd, ep: 14 . patient case #2: dealing with comorbidities in adult adhd, ep: 15 . patient case #2: addressing non-adherence and stigma of adult adhd, ep: 16 . patient case #2: importance of an integrative approach in adult adhd, ep: 17 . case 3: 24-year-old patient with adhd, ep: 18 . case 3: treatment goals in adult adhd, ep: 19 . case 3: factors driving treatment selection in adult adhd, ep: 20 . implications of pharmacogenetic testing in adhd, ep: 21 . novel drug delivery systems in adhd and take-home messages.

Stephen Faraone, PhD: That's a good one, yes, I'd like that, it's a very creative one, thank you, thank you. OK, let's move on to the case presentation. This first patient is a 19-year-old male, who presented to his psychiatrist after being referred by his primary care provider, PCP for ADHD consultation, during the interview, he noted he was a sophomore in college and is taking 17 credits. This semester chief complaint includes a lack of ability to focus in class as well as struggling with time management. He complained that every time he's in class, he finds himself thinking about many other responsibilities he must complete at home and feels that he cannot control it. He has had this complaint for the past 6 years, but refused to seek help, because he feared being put on medication. In high school, he was assigned a counselor who taught him behavior techniques such as making a schedule, and going on walks, which he found to be very effective. However, these techniques were less effective once he started college. His symptoms tend to get worse before exams, he often feels very anxious, leading to horrible performance on exams, he claimed that he has been this anxious since he took his LSAT tests. Currently, he is on academic probation, and is not allowed to be part of the Student Work Program, which was his only source of income. The patient has no history of substance abuse, no history of taking any medications for his symptoms, and no history of suicidal thoughts.

Transcript edited for clarity

CDC Issues HAN Health Advisory Following DOJ Indictment of Digital Health Provider of Adderall

Treating ADHD in Children: Concerns, Controversies, Safety Measures

Onyda XR: The First and Only Liquid Nonstimulant ADHD Medication

ADHD in Older Adults

The Week in Review: May 20-24

FDA Clears Cingulate to File NDA for CTx-1301 in the Treatment of ADHD

2 Commerce Drive Cranbury, NJ 08512

609-716-7777

Design Thinking for Your ADHD with Frankie Berkoben

It’s a radical act to unapologetically design for strengths in a world that focuses on remedying deficits. It’s also the secret sauce when it comes to an authentic and fulfilling life. We all dream of rich support ecosystems that are effortless to maintain. Design thinking is an approach almost tailor-made for ADHD brains to help us get there!

In this webinar, executive & ADHD coach Frankie Berkoben will introduce what design thinking is, how to put theory into practice, and outline tools that create agency, momentum and freedom from decision fatigue.

We’ll cover common pitfalls and misconceptions around iterative problem-solving, how executive functions impact negativity bias, and why self-advocacy is a force multiplier in all areas of your life. Bring your favorite note-taking implements and prepare for a fun session!

Learning Objectives:

•  How to leverage design thinking to engineer systems and structures that support the way your brain works best
• Apply the scientific method and iterative problem-solving to nudge analysis paralysis out of the way
• How generating your own User Manual acts as a catalyst for reliably getting into a flow state

Course Features

• Duration 62 minutes
• Skill level All levels
• Language English
• Students 133
• Assessments Yes

Frankie Berkoben (she/her) is an executive & leadership coach who helps intimidatingly-smart ADHD tech professionals build lives that work WITH their brains. Formerly an engineering consultant, endurance cyclist, PhD & MBA dropout and no-code software nerd, she's also a public speaker and has delivered talks on ADHD & self-advocacy for company ERGs, on podcasts, via ADDA and the ADHD Coaches Organization, and at the International Conference on ADHD (2021, 2022). She offers group coaching, leadership coaching and private workshops.

Visit Frankie's website at http://www.franklyquiteadhd.com

Download Frankie's Free Gift

Building Your Authentic ADHD Life

For some reason the review process breaks down for me consistently so I will post my review here. Someone needs to address this on the back end and the UX end. I’ve never been able to leave reviews .

so, my score is a 5

Great webinar, worth your time and should be on everyone’s short-list.

My comments

I learned about Design Thinking when it was mentioned in one of my ADDA groups a few weeks back. Frankie did a nice job of applying these concepts to both the mundane and profound, such as applying critical thinking for practical projects or problems before us, or for how we wish to redesign our work, our life, our self-understanding, or step further into our ideal vision that reflects our authentic selves and capabilities yet to be unboxed. The presentation slides and info was done really well and very accessible and understandable and my brain didn’t hurt too much with too many disparate half-understood new ideas – like a an adolescent who just spent 8 hours bingeing on video games and skittles. Also, Frankie is a really thoughtful and thorough communicator. She did a superb job of articulating my experiences and reality as a neurodivergent person and clearly linking those experiences to the practical concepts she covered in the webinar. Very well done and worth the time! Nicely done! Bravo!

Is it possible to share the chat with this webinar? I know so much information is usually shared in the chat but Im not sure if they are posted somewhere afterwards. I always lose a good chunk of them even if I make it to watch the webinar live. Thank you 🙏

Leave A Reply Cancel reply

Your email address will not be published. Required fields are marked *

You May Like

Sleep – The Hidden Key to Success with ADHD with Heather Brannon, MD

Sleep – it’s something we all have to do. But for people with ADHD it’s something they hate to do or just can’t do....

How To Get Sh*T Done When You Don’t Feel Like It With Dani Donovan

Dani Donovan shares unique insights about the root causes behind chronic procrastination, and why standard productivity advice fails so many of us. Using her...

Open Q&A: Bring Your Best Questions with Ari Tuckman, PsyD

Bring your best questions for an open Q&A with a top ADHD expert. What have you always wondered about living with ADHD? What have...

Your Procrastination Profile: Why You Put Things Off and How Not to with Abigail Levrini, PhD

Why can’t I just DO IT?! As a psychologist, specializing in adult ADHD, this is the #1 question I get asked by my clients....

5 Simple Mindset Shifts For More Doing And Less Stressing With Alan P. Brown

Overwhelmed with too many to-dos? Feel you never have enough time? Can’t get motivated for difficult tasks? While better time management and productivity hacks...

Modal title

ADHD Case Study

• Introduction
• Conclusions
• Article Information

ADHD indicates attention-deficit/hyperactivity disorder; CVD, cardiovascular disease.

a Controls were derived from the same base cohort as the cases; thus, a case with a later date of CVD diagnosis could potentially serve as a control for another case in the study.

Crude odds ratios (ORs) were based on cases and controls matched on age, sex, and calendar time. Adjusted ORs (AORs) were based on cases and controls matched on age, sex, and calendar time and adjusted for country of birth, educational level, somatic comorbidities (type 2 diabetes, obesity, dyslipidemia, and sleep disorders), and psychiatric comorbidities (anxiety disorders, autism spectrum disorder, bipolar disorder, conduct disorder, depressive disorder, eating disorders, intellectual disability, personality disorders, schizophrenia, and substance use disorders).

The solid lines represent the adjusted odds ratios, and the shaded areas represent the 95% CIs. In restricted cubic splines analysis, knots were placed at the 10th, 50th, and 90th percentiles of ADHD medication use.

eTable 1. International Classification of Diseases (ICD) Codes from the Swedish National Inpatient Register

eTable 2. Type of Cardiovascular Disease in Cases

eTable 3. Risk of CVD Associated With ADHD Medication Use Across Different Average Defined Daily Doses

eTable 4. Risk of CVD Associated With Cumulative Duration of Use of Different Types of ADHD Medications

eTable 5. Sensitivity Analyses of CVD Risk Associated With Cumulative Use of ADHD Medications, Based On Different Cohort, Exposure, and Outcome Definitions

eFigure. Risk of CVD Associated With Cumulative Use of ADHD Medications, Stratified by Sex

Data Sharing Statement

• Long-Term ADHD Medications and Cardiovascular Disease Risk JAMA Medical News in Brief December 26, 2023 Emily Harris
• Long-Term Cardiovascular Effects of Medications for ADHD—Balancing Benefits and Risks of Treatment JAMA Psychiatry Editorial February 1, 2024 Samuele Cortese, MD, PhD; Cristiano Fava, MD, PhD

See More About

Select your interests.

Customize your JAMA Network experience by selecting one or more topics from the list below.

• Academic Medicine
• Acid Base, Electrolytes, Fluids
• Allergy and Clinical Immunology
• American Indian or Alaska Natives
• Anesthesiology
• Anticoagulation
• Art and Images in Psychiatry
• Artificial Intelligence
• Assisted Reproduction
• Bleeding and Transfusion
• Caring for the Critically Ill Patient
• Challenges in Clinical Electrocardiography
• Climate and Health
• Climate Change
• Clinical Challenge
• Clinical Decision Support
• Clinical Implications of Basic Neuroscience
• Clinical Pharmacy and Pharmacology
• Complementary and Alternative Medicine
• Consensus Statements
• Coronavirus (COVID-19)
• Critical Care Medicine
• Cultural Competency
• Dental Medicine
• Dermatology
• Diabetes and Endocrinology
• Diagnostic Test Interpretation
• Drug Development
• Electronic Health Records
• Emergency Medicine
• End of Life, Hospice, Palliative Care
• Environmental Health
• Equity, Diversity, and Inclusion
• Facial Plastic Surgery
• Gastroenterology and Hepatology
• Genetics and Genomics
• Genomics and Precision Health
• Global Health
• Guide to Statistics and Methods
• Hair Disorders
• Health Care Delivery Models
• Health Care Economics, Insurance, Payment
• Health Care Quality
• Health Care Reform
• Health Care Safety
• Health Care Workforce
• Health Disparities
• Health Inequities
• Health Policy
• Health Systems Science
• History of Medicine
• Hypertension
• Images in Neurology
• Implementation Science
• Infectious Diseases
• Innovations in Health Care Delivery
• JAMA Infographic
• Law and Medicine
• Leading Change
• Less is More
• LGBTQIA Medicine
• Lifestyle Behaviors
• Medical Coding
• Medical Devices and Equipment
• Medical Education
• Medical Education and Training
• Medical Journals and Publishing
• Mobile Health and Telemedicine
• Narrative Medicine
• Neuroscience and Psychiatry
• Notable Notes
• Nutrition, Obesity, Exercise
• Obstetrics and Gynecology
• Occupational Health
• Ophthalmology
• Orthopedics
• Otolaryngology
• Pain Medicine
• Palliative Care
• Pathology and Laboratory Medicine
• Patient Care
• Patient Information
• Performance Improvement
• Performance Measures
• Perioperative Care and Consultation
• Pharmacoeconomics
• Pharmacoepidemiology
• Pharmacogenetics
• Pharmacy and Clinical Pharmacology
• Physical Medicine and Rehabilitation
• Physical Therapy
• Physician Leadership
• Population Health
• Primary Care
• Professional Well-being
• Professionalism
• Psychiatry and Behavioral Health
• Public Health
• Pulmonary Medicine
• Regulatory Agencies
• Reproductive Health
• Research, Methods, Statistics
• Resuscitation
• Rheumatology
• Risk Management
• Scientific Discovery and the Future of Medicine
• Shared Decision Making and Communication
• Sleep Medicine
• Sports Medicine
• Stem Cell Transplantation
• Substance Use and Addiction Medicine
• Surgical Innovation
• Surgical Pearls
• Teachable Moment
• Technology and Finance
• The Art of JAMA
• The Arts and Medicine
• The Rational Clinical Examination
• Tobacco and e-Cigarettes
• Translational Medicine
• Trauma and Injury
• Treatment Adherence
• Ultrasonography
• Users' Guide to the Medical Literature
• Vaccination
• Venous Thromboembolism
• Veterans Health
• Women's Health
• Workflow and Process
• Wound Care, Infection, Healing

Others Also Liked

• Download PDF
• X Facebook More LinkedIn

Zhang L , Li L , Andell P, et al. Attention-Deficit/Hyperactivity Disorder Medications and Long-Term Risk of Cardiovascular Diseases. JAMA Psychiatry. 2024;81(2):178–187. doi:10.1001/jamapsychiatry.2023.4294

Manage citations:

© 2024

• Permissions

Attention-Deficit/Hyperactivity Disorder Medications and Long-Term Risk of Cardiovascular Diseases

• 1 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
• 2 Unit of Cardiology, Heart and Vascular Division, Department of Medicine, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
• 3 School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
• 4 Department of Applied Health Science, School of Public Health, Indiana University, Bloomington
• 5 Department of Psychological and Brain Sciences, Indiana University, Bloomington
• Editorial Long-Term Cardiovascular Effects of Medications for ADHD—Balancing Benefits and Risks of Treatment Samuele Cortese, MD, PhD; Cristiano Fava, MD, PhD JAMA Psychiatry
• Medical News in Brief Long-Term ADHD Medications and Cardiovascular Disease Risk Emily Harris JAMA

Question   Is long-term use of attention-deficit/hyperactivity disorder (ADHD) medication associated with an increased risk of cardiovascular disease (CVD)?

Findings   In this case-control study of 278 027 individuals in Sweden aged 6 to 64 years who had an incident ADHD diagnosis or ADHD medication dispensation, longer cumulative duration of ADHD medication use was associated with an increased risk of CVD, particularly hypertension and arterial disease, compared with nonuse.

Meaning   Findings of this study suggest that long-term exposure to ADHD medications was associated with an increased risk of CVD; therefore, the potential risks and benefits of long-term ADHD medication use should be carefully weighed.

Importance   Use of attention-deficit/hyperactivity disorder (ADHD) medications has increased substantially over the past decades. However, the potential risk of cardiovascular disease (CVD) associated with long-term ADHD medication use remains unclear.

Objective   To assess the association between long-term use of ADHD medication and the risk of CVD.

Design, Setting, and Participants   This case-control study included individuals in Sweden aged 6 to 64 years who received an incident diagnosis of ADHD or ADHD medication dispensation between January 1, 2007, and December 31, 2020. Data on ADHD and CVD diagnoses and ADHD medication dispensation were obtained from the Swedish National Inpatient Register and the Swedish Prescribed Drug Register, respectively. Cases included individuals with ADHD and an incident CVD diagnosis (ischemic heart diseases, cerebrovascular diseases, hypertension, heart failure, arrhythmias, thromboembolic disease, arterial disease, and other forms of heart disease). Incidence density sampling was used to match cases with up to 5 controls without CVD based on age, sex, and calendar time. Cases and controls had the same duration of follow-up.

Exposure   Cumulative duration of ADHD medication use up to 14 years.

Main Outcomes and Measures   The primary outcome was incident CVD. The association between CVD and cumulative duration of ADHD medication use was measured using adjusted odds ratios (AORs) with 95% CIs.

Results   Of 278 027 individuals with ADHD aged 6 to 64 years, 10 388 with CVD were identified (median [IQR] age, 34.6 [20.0-45.7] years; 6154 males [59.2%]) and matched with 51 672 control participants without CVD (median [IQR] age, 34.6 [19.8-45.6] years; 30 601 males [59.2%]). Median (IQR) follow-up time in both groups was 4.1 (1.9-6.8) years. Longer cumulative duration of ADHD medication use was associated with an increased risk of CVD compared with nonuse (0 to ≤1 year: AOR, 0.99 [95% CI, 0.93-1.06]; 1 to ≤2 years: AOR, 1.09 [95% CI, 1.01-1.18]; 2 to ≤3 years: AOR, 1.15 [95% CI, 1.05-1.25]; 3 to ≤5 years: AOR, 1.27 [95% CI, 1.17-1.39]; and >5 years: AOR, 1.23 [95% CI, 1.12-1.36]). Longer cumulative ADHD medication use was associated with an increased risk of hypertension (eg, 3 to ≤5 years: AOR, 1.72 [95% CI, 1.51-1.97] and >5 years: AOR, 1.80 [95% CI, 1.55-2.08]) and arterial disease (eg, 3 to ≤5 years: AOR, 1.65 [95% CI, 1.11-2.45] and >5 years: AOR, 1.49 [95% CI, 0.96-2.32]). Across the 14-year follow-up, each 1-year increase of ADHD medication use was associated with a 4% increased risk of CVD (AOR, 1.04 [95% CI, 1.03-1.05]), with a larger increase in risk in the first 3 years of cumulative use (AOR, 1.08 [95% CI, 1.04-1.11]) and stable risk over the remaining follow-up. Similar patterns were observed in children and youth (aged <25 years) and adults (aged ≥25 years).

Conclusions and Relevance   This case-control study found that long-term exposure to ADHD medications was associated with an increased risk of CVDs, especially hypertension and arterial disease. These findings highlight the importance of carefully weighing potential benefits and risks when making treatment decisions about long-term ADHD medication use. Clinicians should regularly and consistently monitor cardiovascular signs and symptoms throughout the course of treatment.

Attention-deficit/hyperactivity disorder (ADHD) is a common psychiatric disorder characterized by developmentally inappropriate inattentiveness, impulsivity, and hyperactivity. 1 , 2 Pharmacological therapy, including both stimulants and nonstimulants, is recommended as the first-line treatment for ADHD in many countries. 1 , 3 The use of ADHD medication has increased greatly in both children and adults during the past decades. 4 Although the effectiveness of ADHD medications has been demonstrated in randomized clinical trials (RCTs) and other studies, 5 , 6 concerns remain regarding their potential cardiovascular safety. 7 Meta-analyses of RCTs have reported increases in heart rate and blood pressure associated with both stimulant and nonstimulant ADHD medications. 5 , 7 - 9

As RCTs typically evaluate short-term effects (average treatment duration of 75 days), 7 it remains uncertain whether and to what extent the increases in blood pressure and heart rate associated with ADHD medication lead to clinically significant cardiovascular disease (CVD) over time. Longitudinal observational studies 10 - 12 examining the association between ADHD medication use and serious cardiovascular outcomes have emerged in recent years, but the findings have been mixed. A meta-analysis 13 of observational studies found no statistically significant association between ADHD medication and risk of CVD. However, the possibility of a modest risk increase cannot be ruled out due to several methodological limitations in these studies, including confounding by indication, immortal time bias, and prevalent user bias. Additionally, most of these studies had an average follow-up time of no more than 2 years. 13 , 14 Thus, evidence regarding the long-term cardiovascular risk of ADHD medication use is still lacking.

Examining the long-term cardiovascular risk associated with ADHD medicine use is clinically important given that individuals with a diagnosis of ADHD, regardless of whether they receive treatment, face an elevated risk of CVD. 15 Additionally, a substantial proportion of young individuals with ADHD continues to have impairing symptoms in adulthood, 16 necessitating prolonged use of ADHD medication. Notably, studies have indicated a rising trend in the long-term use of ADHD medications, with approximately half of individuals using ADHD medication for over 5 years. 17 Furthermore, evidence is lacking regarding how cardiovascular risk may vary based on factors such as type of CVD, type of ADHD medication, age, and sex. 13 Therefore, there is a need for long-term follow-up studies to address these knowledge gaps and provide a more comprehensive understanding of the cardiovascular risks associated with ADHD medication use. This information is also crucial from a public health perspective, particularly due to the increasing number of individuals receiving ADHD medications worldwide. 4

This study aimed to assess the association between cumulative use of ADHD medication up to 14 years and the risk of CVD by using nationwide health registers in Sweden. We hypothesized that longer cumulative use of ADHD medication would be associated with increased CVD risk. In addition, we aimed to examine whether the associations differ across types of ADHD medication, types of CVD, sex, and age groups.

We used data from several Swedish nationwide registers linked through unique personal identification numbers. 18 Diagnoses were obtained from the National Inpatient Register, 19 which contains data on inpatient diagnoses since 1973 and outpatient diagnoses since 2001. Information on prescribed medications was retrieved from the Swedish Prescribed Drug Register, which contains all dispensed medications in Sweden since July 2005 and includes information on drug identity based on the Anatomical Therapeutic Chemical (ATC) classification, 20 dispensing dates, and free-text medication prescriptions. Socioeconomic factors were obtained from the Longitudinal Integrated Database for Health Insurance and Labour Market studies. 21 Information on death was retrieved from the Swedish Cause of Death Register, 22 which contains information on all deaths since 1952. The study was approved by the Swedish Ethical Review Authority. Informed patient consent is not required for register-based studies in Sweden. The study followed the Reporting of Studies Conducted Using Observational Routinely Collected Health Data–Pharmacoepidemiological Research ( RECORD-PE ) guideline. 23

We conducted a nested case-control study of all individuals residing in Sweden aged 6 to 64 years who received an incident diagnosis of ADHD or ADHD medication dispensation 15 between January 1, 2007, and December 31, 2020. The diagnosis of ADHD ( International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ ICD-10 ] code F90) was identified from the National Inpatient Register. Incident ADHD medication dispensation was identified from the Swedish Prescribed Drug Register and was defined as a dispensation after at least 18 months without any ADHD medication dispensation. 24 Baseline (ie, cohort entry) was defined as the date of incident ADHD diagnosis or ADHD medication dispensation, whichever came first. Individuals with ADHD medication prescriptions for indications other than ADHD 25 and individuals who emigrated, died, or had a history of CVD before baseline were excluded from the study. The cohort was followed until the case index date (ie, the date of CVD diagnosis), death, migration, or the study end date (December 31, 2020), whichever came first.

Within the study cohort, we identified cases as individuals with an incident diagnosis of any CVD (including ischemic heart diseases, cerebrovascular diseases, hypertension, heart failure, arrhythmias, thromboembolic disease, arterial disease, and other forms of heart disease; eTable 1 in Supplement 1 ) during follow-up. For each case, the date of their CVD diagnosis was assigned as the index date. Using incidence density sampling, 26 up to 5 controls without CVD were randomly selected for each case from the base cohort of individuals with ADHD. The matching criteria included age, sex, and calendar time, ensuring that cases and controls had the same duration of follow-up from baseline to index date. Controls were eligible for inclusion if they were alive, living in Sweden, and free of CVD at the time when their matched case received a diagnosis of CVD, with the index date set as the date of CVD diagnosis of the matched case ( Figure 1 ). Controls were derived from the same base cohort as the cases. Thus, a case with a later date of CVD diagnosis could potentially serve as a control for another case in the study. 26

The main exposure was cumulative duration of ADHD medication use, which included all ADHD medications approved in Sweden during the study period, including stimulants (methylphenidate [ATC code N06BA04], amphetamine [ATC code N06BA01], dexamphetamine [ATC code N06BA02], and lisdexamfetamine [ATC code N06BA12]) as well as nonstimulants (atomoxetine [ATC code N06BA09] and guanfacine [ATC code C02AC02]). Duration of ADHD medication use was derived from a validated algorithm that estimates treatment duration from free text in prescription records. 25 The cumulative duration of ADHD medication use was calculated by summing all days covered by ADHD medication between baseline and 3 months prior to the index date. The last 3 months before the index date were excluded to reduce reverse causation, as clinicians’ perception of potential cardiovascular risks may influence ADHD medication prescription. This time window was chosen because routine psychiatric practice in Sweden limits a prescription to a maximum 3 months at a time. 27 Individuals with follow-up of less than 3 months were excluded.

We conducted conditional logistic regression analyses to estimate odds ratios (ORs) for the associations between cumulative durations of ADHD medication use and incident CVD. Crude ORs were adjusted for all matching variables (age, sex, and calendar time) by design. Adjusted ORs (AORs) were additionally controlled for country of birth (Sweden vs other), highest educational level (primary or lower secondary, upper secondary, postsecondary or postgraduate, or unknown; individuals aged <16 years were included as a separate category), and diagnoses of somatic (type 2 diabetes, obesity, dyslipidemia, and sleep disorders) and psychiatric comorbidities (anxiety disorders, autism spectrum disorder, bipolar disorder, conduct disorder, depressive disorder, eating disorders, intellectual disability, personality disorders, schizophrenia, and substance use disorders; eTable 1 in Supplement 1 ) before baseline. The association between cumulative ADHD medication use and incident CVD was assessed using both continuous and categorical measures (no ADHD medication use, 0 to ≤1, 1 to ≤2, 2 to ≤3, 3 to ≤5, and >5 years). To capture potential nonlinear associations, we used restricted cubic splines to examine ADHD medication use as a continuous measure throughout follow-up. 28 The associations were examined in the full sample and stratified by age at baseline, that is, children or youth (<25 years old) and adults (≥25 years old). Furthermore, to evaluate the association with dosage of ADHD medication, we estimated the risk of CVD associated with each 1-year increase in use of ADHD medication across different dosage groups categorized by the average defined daily dose (DDD; for instance, 1 DDD of methylphenidate equals 30 mg) during follow-up. 29

In subgroup analyses, we examined the associations between ADHD medication use and specific CVDs, including arrhythmias, arterial disease, cerebrovascular disease, heart failure, hypertension, ischemic heart disease, and thromboembolic disease (eTable 1 in Supplement 1 ). Additionally, we investigated the associations with CVD risk for the most commonly prescribed ADHD medications in Sweden, ie, methylphenidate, lisdexamfetamine, and atomoxetine, while adjusting for other ADHD medication use. We also examined sex-specific associations.

To further examine the robustness of our findings, we conducted 4 sensitivity analyses. First, we restricted the sample to ever users of ADHD medication to reduce unmeasured confounding between ADHD medication users and nonusers. Second, we assessed ADHD medication exposure over the entire follow-up period without excluding the 3 months prior to the index date. Third, to capture fatal cardiovascular events, we additionally included death by CVD in the outcome definition. Finally, we constructed a conditional logistic regression model that adjusted for propensity scores of ADHD medication use. Data management was performed using SAS, version 9.4 (SAS Institute Inc) and all analyses were performed using R, version 4.2.3 (R Foundation for Statistical Computing).

The study cohort consisted of 278 027 individuals with ADHD aged 6 to 64 years. The incidence rate of CVD was 7.34 per 1000 person-years. After applying exclusion criteria and matching, the analysis included 10 388 cases (median [IQR] age at baseline, 34.6 (20.0-45.7) years; 6154 males [59.2%] and 4234 females [40.8%]) and 51 672 matched controls (median [IQR] age at baseline, 34.6 [19.8-45.6] years; 30 601 males [59.2%] and 21 071 females [40.8%]) ( Figure 1 and Table 1 ). Median (IQR) follow-up in both groups was 4.1 (1.9-6.8) years. Among the controls, 3363 had received a CVD diagnosis after their index dates. The most common types of CVD in cases were hypertension (4210 cases [40.5%]) and arrhythmias (1310 cases [12.6%]; eTable 2 in Supplement 1 ). Table 1 presents the sociodemographic information and somatic and psychiatric comorbidities in cases and controls. In general, cases had higher rates of somatic and psychiatric comorbidities and a lower level of educational attainment compared with controls.

A similar proportion of cases (83.9%) and controls (83.5%) used ADHD medication during follow-up, with methylphenidate being the most commonly dispensed type, followed by atomoxetine and lisdexamfetamine. Longer cumulative duration of ADHD medication use was associated with an increased risk of CVD compared with nonuse (0 to ≤1 year: AOR, 0.99 [95% CI, 0.93-1.06]; 1 to ≤2 years: AOR, 1.09 [95% CI, 1.01-1.18]; 2 to ≤3 years: AOR, 1.15 [95% CI, 1.05-1.25]; 3 to ≤5 years: AOR, 1.27 [95% CI, 1.17-1.39]; and >5 years: AOR, 1.23 [95% CI, 1.12-1.36]) ( Figure 2 ). The restricted cubic spline model suggested a nonlinear association, with the AORs increasing rapidly for the first 3 cumulative years of ADHD medication use and then becoming stable thereafter ( Figure 3 ). Throughout the entire follow-up, each 1-year increase in the use of ADHD medication was associated with a 4% increased risk of CVD (AOR, 1.04 [95% CI, 1.03-1.05]), and the corresponding increase for the first 3 years was 8% (AOR, 1.08 [95% CI, 1.04-1.11]). We observed similar results when examining children or youth and adults separately ( Figure 2 ). The restricted cubic spline model suggested a similar nonlinear association, with higher AORs in children or youth than in adults, but the 95% CIs largely overlapped ( Figure 3 ). Furthermore, similar associations were observed for females and males (eFigure in Supplement 1 ). The dosage analysis showed that the risk of CVD associated with each 1 year of ADHD medication use increased with higher average DDDs. The risk was found to be statistically significant only among individuals with a mean dose of at least 1.5 times the DDD (eTable 3 in Supplement 1 ). For example, among individuals with a mean DDD of 1.5 to 2 or less (eg, for methylphenidate, 45 to ≤60 mg), each 1-year increase in ADHD medication use was associated with a 4% increased risk of CVD (AOR, 1.04 [95% CI, 1.02-1.05]). Among individuals with a mean DDD >2 (eg, for methylphenidate >60 mg), each 1-year increase in ADHD medication use was associated with 5% increased risk of CVD (AOR, 1.05 [95% CI, 1.03-1.06]).

When examining the risk for specific CVDs, we found that long-term use of ADHD medication (compared with no use) was associated with an increased risk of hypertension (AOR, 1.72 [95% CI, 1.51-1.97] for 3 to ≤5 years; AOR, 1.80 [95% CI 1.55-2.08] for >5 years) ( Table 2 ), as well as arterial disease (AOR, 1.65 [95% CI, 1.11-2.45] for 3 to ≤5 years; AOR, 1.49 [95% CI 0.96-2.32] for >5 years). However, we did not observe any statistically significant increased risk for arrhythmias, heart failure, ischemic heart disease, thromboembolic disease, or cerebrovascular disease ( Table 2 ). Furthermore, long-term use of methylphenidate (compared with no use) was associated with an increased risk of CVD (AOR, 1.20 [95% CI, 1.10-1.31] for 3 to ≤5 years; AOR, 1.19 [95% CI, 1.08-1.31]) for >5 years; eTable 4 in Supplement 1 ). Compared with no use, lisdexamfetamine was also associated with an elevated risk of CVD (AOR, 1.23 [95% CI, 1.05-1.44] for 2 to ≤3 years; AOR, 1.17 [95% CI, 0.98-1.40] for >3 years), while the AOR for atomoxetine use was significant only for the first year of use (1.07 [95% CI 1.01-1.13]; eTable 4 in Supplement 1 ).

In sensitivity analyses, we observed a similar pattern of estimates when the analysis was restricted to ever users of ADHD medications. Significantly increased risk of CVD was found when comparing ADHD medication use for 1 year or less with use for 3 to 5 or less years (AOR, 1.28 (95% CI, 1.18-1.38) or for use for more than 5 years (AOR, 1.24 [95% CI, 1.13-1.36]) (eTable 5 in Supplement 1 ). When assessing ADHD medication use across the entire follow-up period, and compared with no use, the pattern of estimates was similar to the main analysis (3 to ≤5 years: AOR, 1.28 [95% CI, 1.18-1.39]; >5 years: AOR, 1.25 [95% CI, 1.14-1.37]) (eTable 5 in Supplement 1 ). The analysis that included cardiovascular death as a combined outcome also had results similar to the main analysis. Moreover, when adjusting for propensity scores of ADHD medication use, the findings remained consistent (eTable 5 in Supplement 1 ).

This large, nested case-control study found an increased risk of incident CVD associated with long-term ADHD medication use, and the risk increased with increasing duration of ADHD medication use. This association was statistically significant both for children and youth and for adults, as well as for females and males. The primary contributors to the association between long-term ADHD medication use and CVD risk was an increased risk of hypertension and arterial disease. Increased risk was also associated with stimulant medication use.

We found individuals with long-term ADHD medication use had an increased risk of incident CVD in a dose-response manner in the first 3 years of cumulative ADHD medication use. To our knowledge, few previous studies have investigated the association between long-term ADHD medication use and the risk of CVD with follow-up of more than 2 years. 13 The only 2 prior studies with long-term follow-up (median, 9.5 and 7.9 years 30 , 31 ) found an average 2-fold and 3-fold increased risk of CVD with ADHD medication use compared with nonuse during the study period, yet 1 of the studies 30 included only children, and participants in the other study 31 were not the general population of individuals with ADHD (including those with ADHD and long QT syndrome). Furthermore, both studies were subject to prevalent user bias. Results from the current study suggest that the CVD risk associated with ADHD medication use (23% increased risk for >5 years of ADHD medication use compared with nonuse) is lower than previously reported. 30 , 31 Furthermore, we observed that the increased risk stabilized after the first several years of medication use and persisted throughout the 14-year follow-up period.

The association between ADHD medication use and CVD was significant for hypertension and arterial disease, while no significant association was observed with other types of cardiovascular events. To our knowledge, only 1 previous study 12 has examined the association between ADHD medication use and clinically diagnosed hypertension, and it found an increased risk, although the increase was not statistically significant. Furthermore, increased blood pressure associated with ADHD medication use has been well documented. 7 , 9 One study 32 found that blood pressure was mainly elevated during the daytime, suggesting that the cardiovascular system may recover at night. However, the cross-sectional nature of that study cannot preclude a long-term risk of clinically diagnosed hypertension associated with ADHD medication use. We also identified an increased risk for arterial disease. To date, no previous study has explored the association between ADHD medication use and arterial disease. A few studies have reported that ADHD medication may be associated with changes in serum lipid profiles, but the results were not consistent. 33 , 34 Further research is needed on the potential implications of ADHD medications for individuals’ lipid profiles. We did not observe any association between ADHD medication use and the risk of arrhythmias. A recent systematic review of observational studies of ADHD medication use reported an elevated risk of arrhythmias, but the finding was not statistically significant. 13 A review of RCTs also found that the use of stimulants was associated with an average increase in heart rate of 5.7 beats/min, 9 but no evidence of prolonged QT interval or tachycardia was found based on electrocardiograms. 7 Additionally, it is worth noting that some individuals receiving ADHD medications might be prescribed antiarrhythmic β-blockers to alleviate palpitation symptoms, thus potentially attenuating an association between ADHD medications and arrhythmias. Nevertheless, the absence of an association between ADHD medication use and clinically diagnosed arrhythmias in the present study does not rule out an increased risk for mild arrhythmias or subclinical symptoms, as palpitations and sinus tachycardia are not routinely coded as arrhythmia diagnoses. Further research is necessary to replicate our findings.

Regarding types of ADHD medication, findings of the present study suggest that increasing cumulative durations of methylphenidate and lisdexamfetamine use were associated with incident CVD, while the associations for atomoxetine were statistically significant only for the first year of use. Previous RCTs have reported increased blood pressure and heart rate with methylphenidate, lisdexamfetamine, and atomoxetine, 5 , 35 , 36 but the mechanisms behind these adverse effects are still a topic of debate; there might be differences in cardiovascular adverse effects in stimulants vs nonstimulants. 37

We found that the association between cumulative duration of ADHD medication use and CVD was similar in females and males. Previous investigations exploring sex-specific association found higher point estimates in females, although the differences were not statistically significant. 13 Research has indicated that females diagnosed with ADHD may demonstrate different comorbidity patterns and potentially have different responses to stimulant medications compared with males. 38 - 40 Therefore, additional studies are needed to explore and better understand the potential sex-specific differences in cardiovascular responses to ADHD medications.

A strength of this study is that data on ADHD medication prescriptions and CVD diagnoses were recorded prospectively, so the results were not affected by recall bias. The findings should, however, be interpreted in the context of several limitations. First, our approach for identification of patients with CVD was based on recorded diagnoses and there could be under ascertainment of cardiovascular diagnoses in the registers used. This means that some controls may have had undiagnosed CVD that did not yet require medical care, which would tend to underestimate associations between ADHD medication use and CVD. Second, exposure misclassification may have occurred if patients did not take their medication as prescribed. This misclassification, if nondifferential, would tend to reduce ORs such that the estimates we observed were conservative. Third, while we accounted for a wide range of potential confounding variables, considering the observational nature of the study and the possibility of residual confounding, we could not prove causality. It is possible that the association observed might have been affected by time-varying confounders. For example, other psychotropic medications and lifestyle factors could have affected both ADHD medication use and the occurrence of cardiovascular events. 41 , 42 Confounding by ADHD severity is also a potential factor to consider, as individuals with more severe ADHD symptoms may have more comorbidities and a less healthy lifestyle, which could affect the risk of CVD. Fourth, the study did not examine the risk of CVD among individuals with preexisting CVD. Individuals with preexisting CVD represent a distinct clinical group that requires careful monitoring; thus, evaluating the risk among them necessitates a different study design that carefully considers the potential impact of prior knowledge and periodic monitoring. Finally, the results by type of ADHD medication and type of CVD need to be replicated by studies with larger sample sizes.

The results of this population-based case-control study with a longitudinal follow-up of 14 years suggested that long-term use of ADHD medication was associated with an increased risk of CVD, especially hypertension and arterial disease, and the risk was higher for stimulant medications. These findings highlight the importance of carefully weighing potential benefits and risks when making treatment decisions on long-term ADHD medication use. Clinicians should be vigilant in monitoring patients, particularly among those receiving higher doses, and consistently assess signs and symptoms of CVD throughout the course of treatment. Monitoring becomes even more crucial considering the increasing number of individuals engaging in long-term use of ADHD medication.

Accepted for Publication: August 29, 2023.

Published Online: November 22, 2023. doi:10.1001/jamapsychiatry.2023.4294

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 Zhang L et al. JAMA Psychiatry .

Corresponding Authors: Zheng Chang, PhD ( [email protected] ) and Le Zhang, PhD ( [email protected] ), Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 171 65 Stockholm, Sweden.

Author Contributions: Dr Zhang and Prof Chang had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Zhang, Johnell, Larsson, Chang.

Acquisition, analysis, or interpretation of data: Zhang, Li, Andell, Garcia-Argibay, Quinn, D'Onofrio, Brikell, Kuja-Halkola, Lichtenstein, Johnell, Chang.

Drafting of the manuscript: Zhang.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Zhang, Li.

Obtained funding: Larsson, Chang.

Administrative, technical, or material support: Garcia-Argibay, D'Onofrio, Kuja-Halkola, Lichtenstein, Chang.

Supervision: Andell, Lichtenstein, Johnell, Larsson, Chang.

Conflict of Interest Disclosures: Dr Larsson reported receiving grants from Takeda Pharmaceuticals and personal fees from Takeda Pharmaceuticals, Evolan, and Medici Medical Ltd outside the submitted work. No other disclosures were reported.

Funding/Support: This study was supported by grants from the Swedish Research Council for Health, Working Life, and Welfare (2019-01172 and 2022-01111) (Dr Chang) and the European Union’s Horizon 2020 research and innovation program under grant agreement 965381 (Dr Larsson).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2 .

• Register for email alerts with links to free full-text articles
• Access PDFs of free articles
• Manage your interests
• Save searches and receive search alerts