health behavior thesis

Health, Behavior and Society, PhD

Bloomberg school of public health, overview of phd program.

The PhD in Social and Behavioral Sciences program is designed for students seeking training for careers in social and behavioral sciences, health education, and health communication, most often in academic or research settings. The curriculum emphasizes the application of social and behavioral science perspectives to contemporary health problems. The training in this program focuses on the theoretical perspectives and methods of the social and behavioral sciences that enable scholars to understand and influence the social contexts and behaviors relevant to health.

The PhD degree represents outstanding scholarly achievement and the accomplishment of independent research. The University’s Doctor of Philosophy Board oversees the granting of all PhD degrees.

The following two areas are examples of significant work in the PhD program:

Social and Psychological Influences on Health

This area focuses on social and psychological factors and processes in the etiology and prevalence of disease, in healthcare-seeking behavior, adaptation and coping, and disease prevention. Students are exposed to current research on contextual factors and their relation to health knowledge, attitudes and beliefs; social and psychological factors in disease etiology; risk reduction; and cultural influences in public health, including cross-cultural studies.

This sociological and psychological conceptualization of health and illness, theories of stress and coping, and the special problems in the design and measurement of social and psychological variables are emphasized in the training of the PhD student. The interactive and independent roles of psychosocial factors for disease, with a focus on the social context in which illness is defined and treated, are emphasized. Major social structural divisions such as gender, socioeconomic status, and ethnicity are influential in health outcomes. The basic structure and function of health care systems of societies are also considered in their social-political context.

Health Education and Health Communication

Research and practice in this area focus on how principles from educational, behavioral, social, psychological, and communication theory influence health practices and behaviors conducive to optimal health in individuals, groups, and communities. Students are exposed to current research on health education and communication, with a particular focus on ecological models of health, evaluating multi-faceted intervention programs, and patient-provider communication.

Health education and communication programs are laboratories for the study of effective intervention strategies. Students in this area focus on needs assessment, planning, implementation, and evaluation of comprehensive health promotion programs with an eye toward improving both theory and practice. Specific intervention strategies of interest may include individual behavior change strategies based on learning theory and theories of psychosocial dynamics; use of mass media communication; interpersonal communication; mobilization of social and community support; and advocacy. Program implementation issues such as administrative and staff development and support are also considered. Interventions studied include those directed at patients, health care professionals, administrators, legislators, the general public, or combinations of the above.

Program Requirements

Course location and modality is found on the BSPH website .

Our doctoral curriculum is designed to help students master a set of program competencies through corresponding required and recommended courses. Courses listed as required must be taken by all doctoral students. Students should meet with their advisers prior to registering for courses each term to discuss the selection and sequence of HBS-recommended courses, as well as courses offered by other departments and divisions appropriate for their individual areas of interest.

Students are expected to take methods courses relevant to the field of their dissertation research. Students who wish to take advanced biostatistics courses ( PH.140.651 Methods in Biostatistics I - PH.140.654 Methods in Biostatistics IV ) in place of the basic requirements are encouraged to do so, provided they have the necessary background. To register for the advanced series, a working knowledge of calculus and linear algebra is required.

At the end of the first year of coursework, first-year doctoral students take the qualifying exam. This exam tests whether the student has mastered the basic knowledge of the field (as exemplified by the competencies) and whether the student is ready to specialize in a specific area of study.

Students take the Departmental and School-wide Preliminary Oral Examinations in sequence by the end of their third year in the PhD program. In these exams, the goal is for faculty members to examine the student’s readiness to conduct independent research. Upon passing, students pursue a research topic under the guidance of an academic adviser and faculty committee. The student’s written dissertation is presented in a formal public seminar and then defended at a closed oral examination. Most students complete the PhD within four to five years, and the School requires that students complete it within seven years.

Course Requirements - School

The School requires that at least 18 credit units must be satisfactorily completed in formal courses outside the student's primary department. Among these 18 credit units, no fewer than three courses (totaling at least 9 credits) must be satisfactorily completed in two or more departments of the Bloomberg School of Public Health. The remaining outside credit units may be earned in any department or division of the University. This requirement is usually satisfied with the biostatistics and epidemiology courses required by the department and taken in Year 1 of the PhD program.

Students who have completed a master’s program at the Bloomberg School of Public Health may apply 12 credits from that program toward this School requirement of taking at least 18 credit units outside the department. Contact the HBS Academic Office for further information.

Council on Education in Public Health (CEPH) Requirements

As of 2019-2020, all students matriculating into a graduate program in an accredited school of public health (such as BSPH) are required to take courses that expose them to content that covers 12 ‘introductory learning objectives’ before graduation. For PhD students in HBS, some of these exposures will come through regular program courses, and others will come through ½ credit “Cells to Society” (C2S) online modules developed by the school. The C2S modules will be offered at least twice a year and will be taken in the first 4 weeks of the term in which they are held.  Some courses fulfill more than one learning objective.  These courses need to be successfully completed prior to graduation, and it may be advisable to take some of them in years 2 and 3.   HBS PhD students will fulfill the CEPH requirements by taking the following courses:

• Explain public health history, philosophy and values:  552.601.81 Foundational Principles of Public Health 
• Identify the core functions of public health and the 10 essential services of public health:  552.601.81 Foundational Principles of Public Health
• 3a. Explain the role of quantitative methods and sciences in describing and assessing a population’s health: 140.62 1 Statistical Methods in Public Health 3b. Explain the role of qualitative methods and sciences in describing and assessing a population’s health:  410.710 Concepts in Qualitative Methods (or another qualitative course of at least 3 credits)
• Discuss the science of primary, secondary and tertiary prevention in population health, including health promotion, screening, etc.: 340.721 Epidemiological Inferences in Public Health
• List major causes and trends of morbidity and mortality in the US or other community relevant to the school or program: 340.721 Epidemiological Inferences in Public Health
• Explain the critical importance of evidence in advancing public health knowledge: 340.721 Epidemiological Inferences in Public Health  
• Explain effects of environmental factors on a population’s health:  552.607.81 Essentials of Environmental Health
• Explain biological and genetic factors that affect a population’s health. Choose 1 of the following :  552.608.81 Biologic, Genetic, and Infectious Bases of Human Disease ,  380.604.01 Life Course Perspectives on Health ,  550.631.81 Biological Basis of Public Health
• Explain behavioral and psychological factors that affect a population’s health:  410.650 Persuasive Communication
• Explain the social, political and economic determinants of health and how they contribute to population health and health inequities:  410.860 Graduate Seminar in Social and Behavioral Sciences
• Explain how globalization affects global burdens of disease:  552.611.81 Globalization and Health: A Framework for Analysis
• Explain an ecological perspective on the connections among human health, animal health and ecosystem health (e.g. One Health):  552.612.81 Essentials of One Health

Curriculum - Social and Behavioral Sciences

Note: Minimum of 16 credits (including special studies and thesis research) is required each term throughout the first 4 years of the PhD program. After Year 4, most students will elect to go part-time and register for 3 credits per term.

Students must take the free, non-credit mini-course “Introduction to Online Learning (IOL).” Students are now required to take IOL before beginning their first term. See:  https://courseplus.jhu.edu/core/index.cfm/go/course.home/cid/90/

Highly recommended for those students with little social and behavioral sciences background. Students should discuss this with their advisors to ensure that they have covered the course content and have met the learning objectives of this course in prior coursework. The course should be taken in 1st term by students who plan to take the course.

Students are required to discuss course selections with their advisors prior to registration. Students not taking PH.410.600 FUNDAMENTALS OF HEALTH, BEHAVIOR AND SOCIETY in 1st term are required to select at least one 1st term HBS course in addition to PH.410.860 GRADUATE SEMINAR IN SOCIAL AND BEHAVIORAL SCIENCES and PH.410.863 DOCTORAL SEMINAR IN SOCIAL AND BEHAVIORAL RESEARCH AND PRACTICE  (often this will be Sociological Perspectives/410.612).

Highly recommended for those students with little social and behavioral sciences research background. Students should discuss this with their advisors to ensure that they have covered the course content and have met the learning objectives of this course in prior coursework.

Recommended HBS Courses

Students should discuss the selection and sequence of recommended and other courses relevant to their research interests with their advisers. Students will select some recommended courses in their first year; other courses may be taken in their second and later years of the program. Note:  methodological training requirements in the next section.

The Department offers a flexible PhD curriculum. Students are strongly encouraged to balance breadth and depth, theory, and methodology in pursuing training in the Department. The Department has a broad focus, incorporating health education/health communication as well as social and psychological influences on health.

Students are strongly recommended to take at least 24 credits of taught (non-special studies) HBS classes before they sit for their departmental oral exams. For students with a prior master's in HBS or a BSPH MPH with an SBS concentration, 10 of these credits can be transferred.

HBS courses recommended for doctoral students and offered by term (list does not include required courses noted above):

School of Public Health course listings for courses in HBS and other departments: https://www.jhsph.edu/courses/

Students also have the opportunity to take courses in other divisions of the University. Contact Records and Registration regarding interdivisional course registration procedures .

Additional Requirements in Methodological Training

In addition to the specific required courses listed above, students are required to complete, prior to their preliminary oral examination , at least one course in each of four areas of methodological training in the social and behavioral sciences: quantitative methods (QN), qualitative methods (QL), evaluation methodologies (EV), and methods applications specific to the social and behavioral sciences (SBS). These courses should be taken for a letter grade and not on a Pass/Fail basis. From the menu of courses listed below, students should carefully choose methods training by considering both their previous training and future research goals. Departmental faculty should be consulted as needed.

One course in each of the four areas is considered the minimum; students are encouraged to build their methodological expertise in all areas relevant to their proposed thesis activities and scientific areas of interest. It is valuable for students to seek both breadth and depth in methods training. Therefore, we strongly recommend that students also elect an area of methodological focus and take multiple courses (3 or more) in this area .  We additionally recommend that all students take at least two courses in Qualitative area.

Students who would like to propose taking a methods course not currently listed in lieu of the listed courses may, with their adviser’s consent, request such a substitution in writing to the doctoral program director.

Note: Qualitative Reasoning in Public Health (550.604) cannot count towards fulfilling the qualitative requirements for HBS PhD students

HBS faculty instructor

Course/Credit Load

The Department strongly encourages doctoral students to register for fewer than 19 credits (including special studies and thesis research) in any one academic term. While a credit registration of more than 18 credits is possible through the registration system, departmental faculty think that the additional course burden prohibits doctoral students from dedicating the appropriate time needed for the educational activities being undertaken. Any decision to register for more than 18 credits should be carefully considered and discussed with the student’s adviser prior to registering. Doctoral students should register for a minimum of 16 credits each term; the maximum number of credits per term is 22.

Satisfactory Academic Progress

Doctoral students in the Department of Health, Behavior, and Society are expected to maintain satisfactory academic standards for the duration of the degree program. In the Department, satisfactory academic progress is defined as follows:

• A minimum grade point average (GPA) of 3.00. Any doctoral student who does not obtain the minimum 3.00 GPA by the end of the third term during the first year will not be permitted to sit for the written qualifying exams. In this situation, an appropriate course of action will be determined by the Department Chair. If students fall below a 3.0 GPA, they have 2 terms to regain at least a 3.0 GPA.
• All courses required for the program must be taken for a letter grade. All HBS departmental courses must be taken for a letter grade except with prior consent of the adviser. The pass/fail option may only be used for elective courses and only with the consent of the student’s adviser.
• No grades below a “B” in core courses. Any required course (or course taken to fulfill a methodological requirement) for which a grade of C or below is received) must either be retaken, or an alternative mechanism for material mastery must be agreed upon between the PhD program director, the adviser and the student. This should be successfully completed before taking the schoolwide oral exam. 
• All grades will be calculated into the student’s GPA.
• All doctoral students will have their transcripts evaluated at the end of their first year. This evaluation will be completed in conjunction with the qualifying exam review process.

Independent Developmental Plans (IDP)

It is now university policy that each Ph.D. student and Post Doctoral Fellow will develop an individual development plan (IDP) in conjunction with their adviser. This is in line with the 2014 NIH notice that strongly encourages the development of an institutional policy on Individual Development Plans for all graduate students and postdoctoral scholars who are supported by NIH funds. Beginning in 2017-2018, all matriculating PhD students must complete an IDP, review it with their adviser and submit a signed IDP form for departmental records on an annual basis.

The IDP is a mechanism for self-reflection as well as a communication and planning tool for the student and their faculty mentor/s. The IDP can be useful to make sure that the student's and the adviser’s expectations are clearly outlined and in agreement so that there are no big surprises, particularly at the end of the student’s training.

The goal of the IDP and the annual review process is to support the student in their success in the program and in attaining readiness for their intended future career. To this end, the IDP creates a structure for the student to:

• assess current skills, interests, and strengths;
• make a plan for developing skills to meet academic and professional goals; and
• communicate and collaborate with supervisors, advisers, and mentors about evolving goals and related skills.

The onus to engage in the IDP process is on the student, with the support and input of the adviser. Although the IDP is kept on file in the department, it is primarily a document for use by the student. Through the IDP process, it is possible that the student may decide to identify various additional mentors to whom they can go for expertise and advice.

Once an IDP is written, it is expected that it will be revisited and revised by the student and their adviser (and when appropriate, the dissertation committee) on an annual basis and that this review will be integrated into an annual review process for each student. It is expected that the department will keep a record of this document and of the process by which it was developed and revised.

There are three aspects of the HBS IDP that will be completed on an annual basis, and submitted to the HBS Doctoral Program Coordinator by January 15th of each year . The IDP summary and the signature form will both be kept in the student’s departmental file.

• Self-assessment and goal setting , primarily accomplished by the student through the completion of an assessment tool provided by the department. 
• The student should set up a meeting with their adviser specifically to review the IDP. The IDP should be forwarded to the adviser in advance of this meeting so that the adviser has time to review before the meeting. The student and the adviser should discuss the IDP and possibly revise (e.g. add goals or members of the mentorship team). 
• Both student and adviser should sign the signature form. The student must send electronic copies of the IDP and the form to the  HBS Doctoral Program Coordinator, cc'ing their adviser and the PhD program director.
• Annual Departmental and program feedback to the student . Written feedback will be provided from the department/program, that evaluates student progress in the program to date and the student's graduation trajectory, and progress toward stated career goals. Departmental feedback should be integrated into the IDP process. After Year 1, students will receive written departmental feedback before the beginning of the first term of each year .  The goals outlined in the IDP will be reviewed in preparation of this feedback. Other elements of the IDP will not factor into departmental feedback.

Ideas for Items/Topics to Consider in Creation/Review of the IDP

• Career goal for PhD program (long-term goals)
• Coursework plans/goals for Year 1 (other than required courses)
• Coursework plans/goals before embarking on dissertation
• Skills assessment (areas of strength and needs for additional training)
• Goals for establishment of professional identity and network
• Goals for research opportunities in coming year/entire PhD program
• Goals for teaching opportunities
• Goals for practice opportunities
• Funding targets/opportunities
• Preparation for qualifying exams

Year 2/3 (before departmental and schoolwide preliminary exams)

• Achievements/goals met over the past year
• Challenges faced over the past year
• Remaining coursework plans/goals (other than required courses)
• Goals related to identification of dissertation topic/focus
• Progress on identification of broader mentorship team/committee
• Progress on preparation of dissertation proposal

Years 3+ (after preliminary exams)

• Dissertation goals for the coming year
• Planned timeline for program completion and remaining activities and milestones
• Non-dissertation (research/teaching/practice) goals for remainder of program
• Identification of possible career opportunities

Departmental Qualifying Examination

As stated in the School’s Policy and Procedure Memorandum for doctoral degree programs, the examination should constitute a comprehensive inquiry into the student's grasp of the subject matter underlying their discipline. It should explore the student's understanding of scientific principles and methods as well as their substantive knowledge of the major field and related areas. 

Doctoral students become eligible for the departmental qualifying examination upon successful completion of the first-year required courses while maintaining the minimum GPA required. 

The exam is offered in June and is under the purview of the HBS Exam Committee.  Specific details on the nature of the exam and policies related to grading will be distributed well in advance of the exam.

Research Hours

The School requires all doctoral students to engage in research in addition to the research conducted as part of their dissertation, so that they will gain exposure to and experience in different research skills, and approaches. While HBS encourages students to work within the Department, students are free to pursue opportunities of interest throughout the School, University, or off-campus. Research hours can be fulfilled by engaging in either paid or unpaid research tasks.

The research hours can involve participation in any of the following aspects of research, including but not limited to:

• elements of research design (literature review and development of the conceptual framework of a study);
• community development and liaison activities;
• community needs assessment and its related social, epidemiological, behavioral, or political diagnosis;
• development and piloting of health interventions or materials;
• data collection;
• data analysis and interpretation;
• policy analysis;
• literature reviews;
• manuscript preparation;
• grant preparation and any other form of research approved by the adviser.

Students must discuss their plan for fulfilling the research hours requirement with their academic adviser and have the plan approved by their academic adviser prior to engaging in the research tasks. Students are expected to engage in at least two different research tasks, which may be related to a single study or two separate studies. These tasks should reflect different elements of the research design as outlined above. The student must identify a primary mentor to work with for each of the tasks, and this mentor must agree to serve in this capacity by signing the research hours form in advance. Up to 50% of the required hours can be accomplished through off-campus work, as long as the work has been approved by the student’s academic adviser. A student’s academic adviser can serve as a primary mentor for one but not both of the research tasks. A minimum of 300 hours for total work on research tasks is required, with at least 100 hours on each task.

The research hours should be completed between matriculation and the Departmental preliminary oral exam. Completion of this requirement will be monitored by the Department through submission of the Research Hours Form to the HBS Doctoral Program Coordinator. 

Departmental Preliminary Oral Examination

Students must successfully pass the Departmental preliminary oral examination before taking or scheduling the School-wide preliminary oral exam. The format of the exam is similar to the School-wide preliminary oral exam and is intended to determine if the student is academically prepared to pass the School-wide preliminary oral exam and to carry out independent dissertation research. Students must have successfully completed the departmental qualifying exam before taking the departmental or schoolwide oral exam.

The examination requires the student to prepare a dissertation protocol that will be examined by the committee members before the exam takes place. This protocol should be between 7,000 and 9,000 words (rough guide) and no more than 10,000 words. The proposal should provide the committee with the student's rationale for the proposed study and the research questions to be examined and the approach and methods the student proposes to use.

The departmental preliminary orals committee consists of four faculty members and an alternate. The student's adviser is included in the four committee members. All committee members should have primary appointments in the Department of Health, Behavior, and Society. (An exception is made when the student’s adviser has a primary appointment in another department and a joint appointment in HBS.) The senior faculty member from the department who is not the student's adviser will serve as chair of the committee. The exam is closed, with only the committee members and the student in attendance.

The student will coordinate the date of the exam with the exam committee members and will distribute a copy of the research proposal to all committee members at least three weeks before the exam is scheduled to be held . The student is required to complete the Departmental Oral Form, available from the HBS Doctoral Program Coordinator. The information required on this form includes the names of the committee members, the title of the research protocol, and the date, time, and location of the exam. Committee members will receive formal written notification of the exam date and time by memo.

Immediately following the examination, the committee evaluates the success or failure of the student. One of the following results must be reported to the HBS Doctoral Program Coordinator by the Committee Chair. The two main criteria to determine the outcome of this exam are:

• The student is academically prepared to pass the School-wide oral examination.
• The student is academically prepared to carry out their dissertation research. Note: The exam is an evaluation of the student’s general academic preparation and is not limited to an assessment of the student’s proposal or the details of the proposed study.

Based on the above criteria, students can then receive:

• Unconditional Pass: If the members each vote “unconditional pass” on the first ballot, this result is reported with no further discussion. If one or more members vote “conditional pass” or “fail,” then the committee should discuss the specific concerns of those members as discussed below.
• Conditional Pass: The committee may decide that further evidence of qualifications is necessary and impose a specific condition that the candidate must fulfill within a given period of time. Those who feel the need for a condition or failure must convince others or vice versa. The committee should make a concerted effort to reach a consensus. In the case of a conditional pass, the committee will remain appointed until the condition is removed. Terms of the condition and its removal must be reported in writing to the HBS Academic Office. Students will not be permitted to sit for the School-wide preliminary oral until the conditions have been removed. It is recommended that conditions are met within six months unless otherwise recommended by the examination committee.
• Reexamination by the same Committee
• Reexamination by a new committee.

HBS Guidelines for the Dissertation Proposal

Research Plan:  The student must provide a narrative project description that contains a detailed discussion of the following specific points.

• An introduction that describes the public health problem and brief overview of the sample, aims/research questions, and public health significance.    
• A literature review that describes the supporting literature and a synthesis of the themes, gaps, and weaknesses in the literature related to the social and behavioral aspects of the proposed project.  
• A conceptual framework and theoretical foundations discussion. 
• The methodology section will discuss sampling, recruitment, data collection procedures, measures, analysis, and steps that will be taken to protect human subjects as appropriate.
• The strengths and limitations of the proposed project.
• Timeline for completion of the proposed study.
• Other pertinent information deemed appropriate by the student and their adviser such as facilities and resources, timeline, etc. 

School-wide Preliminary Oral Examination

The School-wide preliminary oral examination takes place after the student has successfully completed the departmental qualifying examination and the departmental preliminary oral examination and completed PH.550.600 LIVING SCIENCE ETHICS - RESPONSIBLE CONDUCT OF RESEARCH (it is only offered in 1st term) . You will not be approved to complete the school-wide exam if you have not taken this course. The purpose of this examination, as stated in the School’s Policy and Procedure Memorandum (PPM), is to determine whether the student has both the ability and knowledge to undertake significant research in their general area of interest. Specifically, the examiners will be concerned with the student's:

• capacity of logical thinking;
• breadth of knowledge in relevant areas;
• ability to develop and conduct research leading to a completed dissertation.

Discussion of a specific research proposal, if available, may serve as a vehicle for determining the student's general knowledge and research capacity. However, this examination is not intended to be a defense of a specific research proposal.

It is a School requirement that the School-wide preliminary oral exam be taken by the end of the student's third year in residence and before significant engagement in their own research.  Note: The school has placed a time limit   of three years between matriculation into a degree program and successful completion of the preliminary oral   exam.  Students are encouraged to keep this time limit in mind when planning their academic schedule.

All requests for extensions beyond the stated time periods to take and pass the School-wide Preliminary Oral Examination or to complete the doctoral degree requirements must be approved by the Committee on Academic Standards. School policy regarding extension requests can be accessed at: https://my.jhsph.edu/Offices/StudentAffairs/RecordsRegistration/AcademicInformation/Pages/default.aspx . Contact the HBS Doctoral Program Coordinator for the most up-to-date information on extension policies.

The School-wide preliminary oral examination must be scheduled at least one month in advance by submission of a preliminary oral examination form to the HBS Doctoral Program Coordinator. Instructions on  scheduling the examination and information on committee composition are available on the Records and Registration website: https://my.jhsph.edu/Offices/StudentAffairs/RecordsRegistration/DoctoralCandidateInfo/Pages/default.aspx

After successful completion of School-wide preliminary oral exam, students register for 16 credits of PH.410.820 THESIS RESEARCH IN HEALTH BEHAVIOR AND SOCIETY each term (or a combination of Thesis Research and other courses totaling at least 16 credits) until completion of all degree requirements.

Dissertation Advisory Committee

The progress of each doctoral student is followed regularly, at least once a year, by a committee consisting of the dissertation adviser and two to four other faculty members. Other committee members can come from either inside and/or outside the student’s department. The student and their adviser, with the consent of the Department chair, decide on the composition of this committee. The objective of the Dissertation Advisory Committee is to provide continuity in the evaluation of the student’s progress during the dissertation phase of the student’s training. Students should form their advisory committees and obtain IRB approval soon after passing their preliminary oral exams and well before the Office of Graduate Education and Research deadline.

Each month, the Office of Graduate Education and Research will generate a report of the students who passed their Preliminary Oral Exam within the past three months. (Students receiving a conditional pass must meet the conditions before this contact is initiated.) An e-mail and “Dissertation Research Documentation Form” will be sent to the student and copied to the student’s Dissertation A (as identified on the Preliminary Oral Exam Committee) and the HBS Doctoral Program Coordinator. The form is to be completed and returned within three months of contact (or six months past preliminary oral exam date) to the Office of Graduate Education and Research for tracking and inclusion in the student’s academic file. A copy is kept by the HBS Doctoral Program Coordinator. 

As noted in the “Milestones” table of this handbook, students should schedule meetings with their advisers at least once per term to review their dissertation progress. Students are required to meet at least once per year with their Dissertation Advisory Committee and provide this committee with a written progress report and a copy of the “HBS Doctoral Dissertation Progress Evaluation Form” (available from the HBS Doctoral Program Coordinator) to be completed by the student’s adviser, attached to the progress report, and submitted to the HBS Doctoral Program Coordinator for the student’s file. The first progress report and evaluation form should be completed by one year from the date the "Dissertation Research Documentation Form” was submitted.

Completion of this requirement each year will be monitored by the student’s adviser and the HBS Doctoral Program Coordinator.

Dissertation Guidelines

All doctoral students must complete an original investigation presented in the form of a dissertation. The dissertation must be based on original research, worthy of publication, and acceptable to the Department of Health, Behavior, and Society and to a committee of dissertation readers. During the student’s application process, various research ideas may have been discussed with faculty members. However, each student’s dissertation proposal must be developed, reviewed, and found acceptable to departmental faculty while the candidate has been enrolled as a doctoral student .

The traditional doctoral dissertation consists of a statement of the problem and specific aims; a literature review; data and research methods; analyses and results; and a discussion of findings and their implications. The form these take will reflect the specific academic discipline or orientation guiding the student's research. Doctoral students also have the option of a manuscript-oriented dissertation as an alternative to the traditional dissertation. See the “Dissertation Policy for HBS Doctoral Students” at the end of this section for more information on manuscript formats.

Students should discuss the advantages and disadvantages of each option with their adviser before deciding on a dissertation strategy.

Completion of a satisfactory investigation of the principal subject and its presentation in the form of a dissertation, approved by a committee of the faculty, is the next step toward the doctoral degree. The material contained in the dissertation should be worthy of publication in a scientific journal in the field involved. To establish this committee, the student and adviser recommend four faculty members to serve as dissertation readers. These faculty members, one of whom is the dissertation adviser, should hold an appointment as Assistant Professor or higher and represent at least three departments of the University and at least two departments of the School of Public Health. One member must hold the rank of Associate Professor or Full Professor and not hold a joint appointment in the student’s department. This individual will serve as the Chair of the Final Oral Examination Committee. One adjunct or one scientist faculty member may serve on the Committee but not both. All faculty members must serve as Dissertation Readers representing the department of their primary faculty appointment.

The committee of readers may be increased to five members provided the conditions stated above are satisfied for four readers. If a fifth member was approved to serve as a Dissertation Reader, that individual does not have voting privileges on the Final Examination Committee.

Oral Defense of Dissertation

The oral defense of the dissertation by the candidate before a committee of the faculty is the final step for the doctoral degree candidate. Instruction and forms for the appointment of dissertation readers and scheduling the final oral exam can be accessed at https://my.jhsph.edu/Offices/StudentAffairs/RecordsRegistration/DoctoralCandidateInfo/Pages/default.aspx .

Records and Registration require that the “Appointment of Dissertation Readers & Final Oral Examination Committee” form be submitted at least one month in advance of the proposed date.

The completed form must be submitted to the HBS Doctoral Program Coordinator for review. The HBS Doctoral Program Coordinator will obtain the Department Chair's signature and forward the form to Records and Registration. Committee members should be given at least 30 days to properly read the dissertation before the defense, and the “Dissertation/Dissertation Approval Form,” signed by the adviser, should be included with the dissertation copies. The adviser should consult with committee members at least two weeks prior to the exam date to ensure that the student is ready to proceed with the exam.

Students must be continuously registered up to and including their term of completion. A doctoral student is not considered complete at the time they pass their final defense. Note that students must be registered in the term of their final oral exam. Doctoral students who schedule their exams after the end of 4th term must register for the summer term. They then have until the end of the add/drop period of the following term to complete all requirements. Students are considered complete:

• when copies of their acceptance letters from the Examining Committee Chair and Dissertation Adviser are on file in the Office of Records & Registration;
• the dissertation is submitted electronically to The Milton S. Eisenhower Library; and
• a pdf copy of the dissertation and a dissertation form submitted to the HBS Doctoral Program Coordinator once approved by the library.

Students should be sure to check both graduation and registration deadlines with the HBS Doctoral Program Coordinator well in advance.

Public Seminar

As a culminating experience, all doctoral students are required by the School to present a formal, public seminar. A room that holds no less than 25 people should be reserved for the public seminar. A three-hour period should be allowed for the final oral examination, consisting of the public seminar and session with the examination committee. It will begin with an approximately 45-minute public seminar followed by 15 minutes of Q&A with the audience. This will be immediately followed by the closed portion of the examination, which is closed to all except the doctoral candidate and the examination committee. Records and Registration posts the seminar announcement to the School's events calendar.

Dissertation Policy for HBS Doctoral Students

Students in HBS have the choice of completing a “traditional” doctoral dissertation or a manuscript-oriented dissertation. Ideally, this decision should be made by the time the student undergoes the departmental preliminary oral examination. There are advantages and disadvantages to each option which should be carefully discussed with the student’s adviser.

Each of these options is described briefly below.

The traditional doctoral dissertation generally consists of an abstract, five chapters, references, and any appendices. The outline of chapters below is merely a guide. The page numbers are rough estimates, and the form of the chapters will vary, reflecting the academic discipline or orientation of the student’s research.

Abstract: The abstract is a short overall summary of the work. It lays out the purpose(s) and aims of the study, the methods, and the key results and implications. The abstract generally is 2-3 double-spaced pages.

Chapter 1: Introduction: Statement of the Problem and Specific Aims. This chapter, which tends to be relatively short (5-6 double-spaced pages), provides an introduction to the dissertation. It describes briefly why this work was undertaken, what background conditions or data suggested it was an important problem, and what, then, this project was intended to accomplish.

Chapter 2: Literature Review. The literature review summarizes existing literature that informed the dissertation research. It is generally organized topically. The literature review tends to be a fairly detailed review, particularly for those topics most directly related to the content and methods of the dissertation. The literature review tends to be 30-60 pages in length.

Chapter 3: Methods. The content of the methods chapter varies tremendously with the methodological approach taken by the student for the dissertation research. With traditional empirical studies, it will generally include the specific aims, research questions, and/or hypothesis; a description of the source of study data, a description of the study instrument and its development, if relevant; a description of secondary data obtained, if relevant; analytic methods, including data cleaning, creation of a data set, creation of variables and/or qualitative codes, types of analyses done, and human subjects issues. The methods chapter ranges from 20-40 pages.

Chapter 4: Results. The results chapter reports the main findings of the dissertation. It is often organized by research question or specific aim or hypothesis but need not necessarily follow this format. The results chapter ranges from 25-50 pages.

Chapter 5: Discussion of Results and Policy Implications. The discussion chapter both summarizes key findings and discusses findings in light of existing literature and in light of their policy implications. Also included generally is a description of the study’s limitations and implications for future research. The Discussion chapter is generally 25-50 pages.

References: A listing of all citations used for the dissertation must be provided. The Department allows any standard format for references.

Appendices: Appendices can be used for many purposes. They can include study instruments, if relevant; they can include additional tables not included in the main body of the dissertation; also to be included must be a copy of the student’s CV. The traditional dissertation should be able to “stand alone” without appendices; however, such results should never be put in appendices that are key to the study’s main findings.

All components of the traditional dissertation will be judged by the committee to be one of the following: Acceptable, Acceptable with Revisions, or Unacceptable. Students, with guidance from their adviser, will rework their dissertation until all components are judged acceptable.

The manuscript dissertation consists of the following:

• A total of three (or more) papers, linked to the student’s dissertation topic. One of these papers may be the literature review, provided it is a comprehensive critical review, suitable for publication. ​If one of the three papers is not a literature review, the dissertation must still contain a chapter that critically surveys the literature.
• A chapter that integrates and discusses the findings reported in the manuscripts. It should include a discussion of the conclusions of the research, and it should make recommendations for further studies.
• An appendix outlining in detail the study methods and any accompanying data tables necessary to fully understand the data.

A manuscript-oriented dissertation must also meet the following criteria:

• The doctoral student must be the first author on the three manuscripts used to satisfy this requirement.
• No manuscript will be accepted as part of the dissertation if it was submitted for publication before the student passes the School-wide preliminary oral exam.

As is true for the traditional doctoral dissertation, all components of the manuscript-oriented dissertation will be judged to be one of the following: Acceptable, Acceptable with Revisions, or Unacceptable. Students, with guidance from their adviser, will rework their dissertation until all components are judged acceptable.

Role of Faculty Adviser in Relation to the Dissertation:

The adviser's role is to facilitate successful completion of the doctoral dissertation. The type of assistance provided should be tailored to the individual student's needs. Both the traditional dissertation and the manuscript-oriented dissertation must reflect work that is the student’s independent and original work. The adviser, then, can and should provide ongoing and critical feedback, but the research must be that of the student.

Maintaining this balance may be particularly challenging for manuscript-oriented theses. Even if the adviser (or another committee member) will be a co-author on a manuscript, the manuscripts must be viewed first and foremost as fulfilling the student's needs in the dissertation process, with publication as a secondary goal. Advisers or other committee members who are co-authors may not undertake the first draft of any portions of the manuscripts nor substantial re-writes. Whether an adviser will be a co-author on any manuscript should be decided early in the dissertation process.

Link to Thesis guidelines and deadlines

Link to School PPM on PhD Degree

Career Development Resources for PhD Students

The BSPH Career Services Office provides a variety of assistance including individual career coaching, a university-wide  job and employer database , career development  workshops and events , a list of  career resources , and an annual  career fair . More information is available here .

The Professional Development and Career Office (PDCO) provides professional development training and career services to support PhD students and Postdoctoral Scholars in designing their life. The PDCO supports academic careers by providing grant writing workshops, teaching opportunities at local undergraduate institutions, and an annual academic job search series. It also supports career exploration outside the academy by hosting alumni career panels, organizing an alumni mentorship program, running leadership workshops, and by offering paid internships in science policy, consulting, business development, etc. PDCO staff can also meet with PhD students or post-doctoral fellows one on one to meet their specific career goals.  The PDCO services are outlined here:  https://pdco.med.jhmi.edu . They also send monthly emails that list events for PhDs happening across the university (sent through the doctoral student listserv). 

Milestones for the PhD Program

Timetable for Completion of Degree Requirements

Please direct questions regarding the timetable for completion of degree requirements to the Office of Records & Registration ( [email protected] ).

For a full list of program policies, please visit the PhD in Social and Behavioral Sciences page where students can find our handbook.

Our curriculum is designed to help students master the following competencies:

• Design a research study using qualitative or quantitative methods to answer social science questions relevant to public health at a doctoral level
• Demonstrate that the theoretical perspective one begins with influences the scientific questions analyzed
• Critically discuss theoretical concepts and orientations in the social and behavioral sciences
• Integrate understanding of concepts related to multiple levels of determinants of health and inequality
• Demonstrate skills for oral presentation and defense of their research in both academic and professional settings
• Design public health interventions based on theoretical foundations to address health determinants outlined by the socioecological model
• Apply core methodological concepts and analytical approaches for social and behavioral sciences in public health 

According to the requirements of the Council on Education for Public Health (CEPH), all BSPH degree students must be grounded in foundational public health knowledge. Please view the list of specific CEPH requirements by degree type .

• Research article
• Open access
• Published: 11 June 2007

A review of health behaviour theories: how useful are these for developing interventions to promote long-term medication adherence for TB and HIV/AIDS?

• Salla Munro 1 ,
• Simon Lewin 2 ,
• Tanya Swart 3 &
• Jimmy Volmink 4  

BMC Public Health volume  7 , Article number:  104 ( 2007 ) Cite this article

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Suboptimal treatment adherence remains a barrier to the control of many infectious diseases, including tuberculosis and HIV/AIDS, which contribute significantly to the global disease burden. However, few of the many interventions developed to address this issue explicitly draw on theories of health behaviour. Such theories could contribute to the design of more effective interventions to promote treatment adherence and to improving assessments of the transferability of these interventions across different health issues and settings.

This paper reviews behaviour change theories applicable to long-term treatment adherence; assesses the evidence for their effectiveness in predicting behaviour change; and examines the implications of these findings for developing strategies to improve TB and HIV/AIDS medication adherence. We searched a number of electronic databases for theories of behaviour change. Eleven theories were examined.

Little empirical evidence was located on the effectiveness of these theories in promoting adherence. However, several models have the potential to both improve understanding of adherence behaviours and contribute to the design of more effective interventions to promote adherence to TB and HIV/AIDS medication.

Further research and analysis is needed urgently to determine which models might best improve adherence to long-term treatment regimens.

Peer Review reports

Theories may assist in the design of behaviour change interventions in various ways [ 1 – 3 ], by promoting an understanding of health behaviour, directing research and facilitating the transferability of an intervention from one health issue, geographical area or healthcare setting to another.

Ensuring treatment adherence presents a considerable challenge to health initiatives. Haynes et al. ([ 4 ], p2) have defined adherence as "the extent to which patients follow the instructions they are given for prescribed treatments". Adherence is a more neutral term than 'compliance', which can be construed as being judgmental. While programmes promoting adherence have focused on various health behaviours, this review focuses specifically on long-term adherence to tuberculosis (TB) and HIV/AIDS treatment. Non-adherence to treatment for these diseases has severe human, economic and social costs. Interrupted treatment may reduce treatment efficacy and cause drug resistance [ 5 ], resulting in increased morbidity and mortality and further infections. Without intervention, adherence rates to long-term medication in high income countries are approximately 50% [ 6 ], while adherence in low and middle income countries may be even lower [ 7 ].

TB and HIV present particular challenges to adherence. Both are chronic and infectious diseases that affect mainly the most disadvantaged populations and involve complex treatment regimens with potentially severe side effects; both are public health priorities and non-adherence may cause drug resistance [ 7 ]. These characteristics differentiate these diseases from other chronic diseases such as asthma and hypertension where, for example, drug resistance is not a key issue. Treatment adherence is also affected by beliefs about the origins, transmission and treatment of TB and HIV, often resulting in the stigmatisation of those affected [ 7 ]. The interaction of these factors make adherence for these diseases not only a priority but a complex health issue.

Various interventions have been designed to improve treatment adherence, but few theories describe specifically the processes involved. Currently, there are more than 30 psychological theories of behaviour change [ 8 ], making it difficult to choose the most appropriate one when designing interventions. This is a particular problem within the field of adherence to long-term medications, where the consequences of non-adherence may be severe. Existing theories therefore need to be examined further to determine their relevance to the issue of long-term medication adherence.

Leventhal and Cameron [ 9 ] identified five main theoretical perspectives related to adherence: 1) biomedical; 2) behavioural; 3) communication; 4) cognitive; and 5) self-regulatory. Each perspective encompasses several theories. More recently, the stage perspective has emerged, which includes the transtheoretical model. The most commonly used theories are those within the cognitive perspective [ 1 , 10 ] and the transtheoretical model [ 1 ]. This review includes a short description of theories within each of the five perspectives listed above, as well as the transtheoretical model. We locate these theories specifically within the realm of adherence to long-term medication, defined as medication regimens of three months or more; describe their key characteristics and evidence base; and examine their relevance and applicability with regard to adherence to long-term medication regimens for TB and HIV/AIDS. To our knowledge, the area of long-term adherence to medication has not yet been addressed in reviews of health behaviour theories.

While the focus of this review is on factors affecting consumers, we acknowledge that adherence is a complex and dynamic phenomenon, which relates to consumers, providers, health systems and broader socio-economic and political contexts. Although the theories chosen for this review focus mainly on providers and consumers, this is not the only area in which adherence can be promoted. The review is intended as an information source for those wishing to develop theory-based interventions focusing on intra- or interpersonal factors to increase TB and/or HIV treatment adherence.

A search was performed on MEDLINE, CINAHL, Pre-CINAHL, PsycInfo, ScienceDirect and ERIC databases using the keywords 'health and behaviour and (model or theory)'; '(model or theory); (adherence or concordance or compliance)', from the start date of each database to February 2005. Additional searches were performed in the University of Cape Town library, Google and Google Scholar. Citations were also identified from included papers. Finally, all databases consulted were searched again using the names of theories as keywords, with 'meta-analysis' or 'systematic review' in April 2005. Experts were consulted for comments and references. Published articles or book chapters in English, describing a particular theory, and articles that presented a meta-analysis of the theory, were included. Articles were excluded if they did not satisfy the aforementioned criteria. Where possible, interventions related to TB or HIV adherence were identified. No authors were contacted. Several additional randomised controlled studies or other articles were also included as examples of the use of theories in intervention development. In this paper we use the term 'theory', instead of 'model', and the term 'variable', instead of 'construct', when referring to a part of the theory.

Table 1 presents the theories included in this article and references to meta-analyses synthesizing the evidence for each. Below, we summarise each perspective and the theories within it and provide examples of its application to adherence behaviours [see additional file 1 ]. We then examine the usefulness of these theories in developing interventions to promote long-term adherence.

The biomedical perspective

The biomedical perspective incorporates the biomedical theory in which patients are assumed to be passive recipients of doctors' instructions [ 11 ]. Health or disease is traced back to biomedical causes, such as bacteria or viruses, and treatment is therefore focused on the patient's body [ 11 ]. In keeping with this mechanistic view of illness, mechanical solutions, such as prescribed pills, are preferred [ 12 ]; non-adherence is understood to be caused by patient characteristics, such as age and gender [ 12 ]. Technological innovations to promote adherence, such as Medication Event Monitoring Systems ® , are sometimes rooted in this perspective [ 7 ]. However, despite its implicit use by many health professionals, this perspective is infrequently used explicitly in interventions.

A fundamental limitation of this theory is that it ignores factors other than patient characteristics that may impact on health behaviours – for example, patients' perspectives of their own illness [ 7 ]; psycho-social influences [ 12 ]; and the impacts of the socio-economic environment. The socio-economic environment or demographics may, however, be markers for other factors that lend themselves to intervention even though they themselves cannot be changed [ 13 ]. The danger of using demographics as proxy variables for adherence is that certain groups that come to be seen as "lost causes" may be excluded (e.g. [ 14 ]). This biomedical theory has recently been integrated into a larger "biopsycho-socio-environmental" theory, which incorporates the wider socio-environmental context [ 11 ]. However, this theory is not located strictly within the biomedical approach. Due to the assumption that patients are passive and the focus on biomedical factors, it is unlikely that the biomedical theory can contribute significantly to TB or HIV medication adherence. Patients are generally active decision makers and do not merely receive and follow instructions passively. No meta-analyses specifically examining this perspective were identified.

Behavioural (learning) perspective

This perspective incorporates behavioural learning theory (BLT) which is focused on the environment and the teaching of skills to manage adherence [ 7 ]. It is characterised by the use of the principles of antecedents and consequences and their influence on behaviour. Antecedents are either internal (thoughts) or external (environmental cues) while consequences may be punishments or rewards for a behaviour. The probability of a patient following a specific behaviour will partially depend on these variables [ 7 ].

Behavioural learning theory.

Health belief model.

Protection motivation theory.

Revised protection motivation theory.

Social cognitive theory.

Theory of reasoned action.

Theory of planned behaviour.

Information motivation behavioural skills model.

Self regulation theory.

Transtheoretical model.

Adherence promoting strategies informed by this perspective, such as patient reminders, have been found to improve adherence [ 15 ]. Several interventions incorporating elements of BLT have also been reported to be effective for adherence to long-term medications [ 4 ]. However, a more recent meta-analysis examining adherence to highly active antiretroviral (ARV) therapy concluded that interventions with cue dosing and external rewards – approaches derived from BLT -were as efficacious as those without [ 16 ]. Another randomised controlled trial on ARVs reported a negative effect when using electronic reminder systems [ 17 ]. Further evidence is therefore needed on the effectiveness of these types of strategy.

BLT has been critiqued for lacking an individualised approach and for not considering less conscious influences on behaviour not linked to immediate rewards [ 12 ]. These influences include, for example, past behaviour, habits, or lack of acceptance of a diagnosis. The theory is limited, too, by its focus on external influences on behaviour. Programme planners should therefore consider carefully individuals' perceptions of appropriate rewards before using such theory to inform programme design. Interventions drawing on behavioural theory are often used in combination with other approaches, although seldom explicitly. No meta-analyses were found that examined this perspective.

Communication perspective

Communication is said to be "the cornerstone of every patient-practitioner relationship" [[ 11 ], p. 56]. This perspective suggests that improved provider-client communication will enhance adherence [ 7 , 11 ] and implies that this can be achieved through patient education and good health care worker communication skills – an approach based on the notion that communication needs to be clear and comprehensible to be effective. It also places emphasis on the timing of treatment, instruction and comprehension. An example of an intervention utilising this perspective is one that aims to improve client-provider interaction. Critiques of this perspective argue that it ignores attitudinal, motivational and interpersonal factors that may interfere with the reception of the message and the translation of knowledge into behaviour change [ 12 ].

A number of reviews have examined the effects of interventions including communication elements [ 18 – 21 ]. However, few of these have examined the effects of communication on health behaviours specifically. Two reviews focusing on interventions to improve provider-client communication showed that these can improve communication in consultations, patient satisfaction with care [ 18 ] as well as health outcomes [ 21 ]. However, these reviews also show limited and mixed evidence on the effects of such interventions on patient health care behaviours, such as adherence.

Communication components have been used within several adherence interventions but seldom explicitly or as the main component. Such interventions are unlikely to succeed in isolation in improving long-term adherence to medications because of the influence of external factors, such as the costs of accessing healthcare for treatment. Communication interventions are also typically restricted to provider-client interactions and additional social or financial support may thus be required.

Cognitive perspective

The cognitive perspective includes theories such as the health belief model (HBM), social-cognitive theory (SCT), the theories of reasoned action (TRA) and planned behaviour (TPB) and the protection motivation theory (PMT). These theories focus on cognitive variables as part of behaviour change, and share the assumption that attitudes and beliefs [ 22 ], as well as expectations of future events and outcomes [ 23 ], are major determinants of health related behaviour. In the face of various alternatives, these theories propose, individuals will choose the action that will lead most likely to positive outcomes.

These theories have noticeable weaknesses, however: firstly, that non-voluntary factors can affect behaviour [ 23 ]; devoting time to conscious deliberation regarding a repeated choice also seems uneconomical [ 22 ]. Secondly, these theories do not adequately address the behavioural skills needed to ensure adherence [ 7 ]. Thirdly, these theories give little attention to the origin of beliefs and how these beliefs may influence other behaviours [ 24 ]. In addition, it has been argued that they ignore other factors that may impact on adherence behaviour, such as power relationships and social reputations [ 25 ], and the possibility that risk behaviour may involve more than one person [ 26 ]. It has also been suggested that they focus on a single threat and prevention behaviour and do not include possible additional threats competing for the individual's attention [ 24 ].

• Health Belief Model

The HBM views health behaviour change as based on a rational appraisal of the balance between the barriers to and benefits of action [ 12 ]. According to this model, the perceived seriousness of, and susceptibility to, a disease influence individual's perceived threat of disease. Similarly, perceived benefits and perceived barriers influence perceptions of the effectiveness of health behaviour. In turn, demographic and socio-psychological variables influence both perceived susceptibility and perceived seriousness, and the perceived benefits and perceived barriers to action [ 1 , 7 ]. Perceived threat is influenced by cues to action, which can be internal (e.g. symptom perception) or external (e.g. health communication) (Rosenstock, 1974 in [ 7 ]).

High-perceived threat, low barriers and high perceived benefits to action increase the likelihood of engaging in the recommended behaviour [ 27 ]. Generally, all of the model's components are seen as independent predictors of health behaviour [ 28 ]. Bandura [ 29 ] notes, however, that perceived threats – especially perceived severity – have a weak correlation with health action and might even result in avoidance of protective action. Perceived severity may also not be as important as perceived susceptibility. Recently, self-efficacy was added into the theory [ 30 ], thereby incorporating the need to feel competent before effecting long-term change [ 31 ].

There are two main criticisms of this theory: firstly, the relationships between these variables have not been explicitly spelt out [ 32 ] and no definitions have been constructed for the individual components or clear rules of combination formulated [ 28 ]. It is assumed that the variables are not moderated by each other and have an additive effect [ 32 ]. If, for example, perceived seriousness is high and susceptibility is low, it is still assumed that the likelihood of action will be high -intuitively one might assume that the likelihood in this case would be lower than when both of the variables are high [ 22 , 32 ]. The HBM also assumes that variables affect health behaviour directly and remain unmoderated by behavioural intentions [ 22 ]. The second major weakness of HBM is that important determinants of health behaviour, such as the positive effects of negative behaviours and social influence, are not included [ 22 , 32 ]. In addition, some behaviours such as smoking are based on habits rather than decisions [ 33 ]. While the theory may predict adherence in some situations, it has not been found to do so for "risk reduction behaviours that are more linked to socially determined or unconscious motivations" [[ 12 ], p.165].

The two reviews identified that examined this theory had inconclusive results. A critical review [ 34 ] examined 19 studies which involved sick role behaviours, such as compliance to antihypertensive medication. While the four dimensions of the model produced significant effects in most of the studies included [ 34 ], the studies had considerable methodological gaps. A more recent meta-analysis [ 35 ] indicated that while the HBM was capable of predicting 10% of variance in behaviour at best, the included studies were heterogeneous and were unable to support conclusions as to the validity of the model. Therefore further studies are needed to assess the validity of this theory. When applying this theory to long-term medication adherence, it is also important for the influence of socio-psychological factors to be considered. For example, cultural beliefs about TB – such as its relationship with witchcraft [ 36 ] – may reduce an adherence intervention's effectiveness.

The protection-motivation theory

According to this theory, behaviour change may be achieved by appealing to an individual's fears. Three components of fear arousal are postulated: the magnitude of harm of a depicted event; the probability of that event's occurrence; and the efficacy of the protective response [ 37 ]. These, it is contended, combine multiplicatively to determine the intensity of protection motivation [ 22 ], resulting in activity occurring as a result of a desire to protect oneself from danger [ 37 ]. This is the only theory within the broader cognitive perspective that explicitly uses the costs and benefits of existing and recommended behaviour to predict the likelihood of change [ 23 ].

An important limitation of this theory is that not all environmental and cognitive variables that could impact on attitude change (such as the pressure to conform to social norms) are identified [ 37 ]. The most recent version of the theory assumes that the motivation to protect oneself from danger is a positive linear function of beliefs that: the threat is severe, one is personally vulnerable, one can perform the coping response (self efficacy) and the coping response is effective (response efficacy) [ 22 ]. Beliefs that health-impairing behaviour is rewarding but that giving it up is costly are assumed to have a negative effect [ 22 ]. However, the subdivision of perceived efficacy into categories of response and self efficacy is perhaps inappropriate – people would not consider themselves capable of performing an action without the means to do it [ 29 ].

A meta-analysis examining this theory found only moderate effects on behaviour [ 39 ]. The revised PMT may be less cumbersome to use than the TRA – it also does not assume that behaviour is always rational. [ 39 ]. The PMT may be appropriate for adherence interventions as it is unlikely that an individual consciously re-evaluates all of their routine behaviours such as, for example, taking long-term medication. However, the influence of social, psychological and environmental factors on motivation requires consideration by those using this approach.

Social-cognitive theory

This theory evolved from social learning theory and may be the most comprehensive theory of behaviour change developed thus far [ 1 ]. It posits a multifaceted causal structure in the regulation of human motivation, action and well-being [ 40 ] and offers both predictors of adherence and guidelines for its promotion [ 29 ]. The basic organising principle of behaviour change proposed by this theory is reciprocal determinism in which there is a continuous, dynamic interaction between the individual, the environment and behaviour [ 1 ].

Social-cognitive theory suggests that while knowledge of health risks and benefits are a prerequisite to change, additional self-influences are necessary for change to occur [ 41 ]. Beliefs regarding personal efficacy are among some of these influences, and these play a central role in change. Health behaviour is also affected by the expected outcomes – which may be the positive and negative effects of the behaviour or the material losses and benefits. Outcomes may also be social, including social approval or disapproval of an action. A person's positive and negative self-evaluations of their health behaviour and health status may also influence the outcome. Other determinants of behaviour are perceived facilitators and barriers. Behaviour change may be due to the reduction or elimination of barriers [ 41 ]. In sum, this theory proposes that behaviours are enacted if people perceive that they have control over the outcome, that there are few external barriers and when individuals have confidence in their ability to execute the behaviour [ 28 ].

A review reported that self efficacy could explain between 4% and 26% of variance in behaviour [ 42 ]. However, this analysis was limited to studies of exercise behaviour, and did not include reports that examined SCT as a whole. Due to its wide-ranging focus, this theory is difficult to operationalise and is often used only in part [ 43 ], thus raising questions regarding its applicability to intervention development.

Theory of planned behaviour and the theory of reasoned action

The first work in this area was on the TRA [ 44 ].

The TRA assumes that most socially relevant behaviours are under volitional control, and that a person's intention to perform a particular behaviour is both the immediate determinant and the single best predictor of that behaviour [ 45 ]. An intention to perform a behaviour is influenced by attitudes towards the action, including the individual's positive or negative beliefs and evaluations of the outcome of the behaviour. It is also influenced by subjective norms, including the perceived expectations of important others (e.g. family or work colleagues) with regard to a person's behaviour; and the motivation for a person to comply with others' wishes. Behavioural intention, it is contended, then results in action [ 44 ]. The authors argue that other variables besides those described above can only influence the behaviour if such variables influence attitudes or subjective norms. A meta-analysis examining this theory found that it could explain approximately 25% of variance in behaviour in intention alone, and slightly less than 50% of variance in intentions [ 45 ]. This suggests that support for this theory is limited.

Additionally, The TRA omits the fact that behaviour may not always be under volitional control and the impacts of past behaviour on current behaviours [ 22 ]. Recognising this, the authors extended the theory to include behavioural control and termed this the TPB. 'Behavioural control' represents the perceived ease or difficulty of performing the behaviour and is a function of control beliefs [ 45 ]. Conceptually it is very similar to self-efficacy [ 22 ] and includes knowledge of relevant skills, experience, emotions, past track record and external circumstances (Ajzen, in [ 46 ]). Behavioural control is assumed to have a direct influence on intention [ 45 ]. Meta-analyses examining the TPB have found varied results regarding the effectiveness of the theory's components [ 47 – 49 ]. Although not conclusive, the results of the analyses are promising.

Sutton [ 45 ] suggests that the TRA and TPB require more conceptualisation, definition and additional explanatory factors. Attitudes and intentions can also be influenced by a variety of factors that are not outlined in the above theories [ 22 ]. Specifically, these theories are largely dependent on rational processes [ 50 ] and do not allow explicitly for the impacts of emotions or religious beliefs on behaviour, which may be relevant to stigmatised diseases like TB and HIV/AIDS.

Information-motivation-behavioural skills (IMB) theory

This theory was developed to promote contraceptive use and prevent HIV transmission. IMB was constructed to be conceptually based, generalisable and simple [ 51 ]. It has since been tailored specifically to designing interventions to promote adherence to ART [ 52 ]

This theory focuses on three components that result in behaviour change: information, motivation and behaviour skills. Information relates to the basic knowledge about a medical condition, and is an essential prerequisite for behaviour change but not necessarily sufficient in isolation [ 51 ]. A favourable intervention would establish the baseline levels of information, and target information gaps [ 51 ]. The second component, motivation, results from personal attitudes towards adherence; perceived social support for the behaviour; and the patients' subjective norm or perception of how others with the condition might behave [ 7 ]. Finally, behavioural skills include factors such as ensuring that the patient has the skills, tools and strategies to perform the behaviour as well as a sense of self-efficacy – the belief that they can achieve the behaviour [ 51 ].

The components mentioned above need to be directly relevant to the desired behaviour to be effective [ 7 ]. They can also be moderated by a range of contextual factors such as living conditions and access to health services [ 52 ]. Information and motivation are thought to activate behavioural skills, which in turn result in risk reduction behavioural change and maintenance [ 51 ]. The theory is said to be moderately effective in promoting behaviour change [ 7 ], and has been shown to have predictive value for ART adherence [ 53 ]. However, no meta-analyses were identified that assessed the effects of this model. The advantage of IMB is its simplicity and its recent application to ART adherence suggests that it may be a promising model for promoting adherence to TB medication.

Self-regulation perspectives

Self-regulatory theory is the main theory in this domain. Developed to conceptualise the adherence process in a way that re-focuses on the patient [ 54 ], the theory proposes that it is necessary to examine individuals' subjective experience of health threats to understand the way in which they adapt to these threats. According to this theory, individuals form cognitive representations of health threats (and related emotional responses) that combine new information with past experiences [ 55 ]. These representations 'guide' their selection of particular strategies for coping with health threats, and consequently influence associated outcomes [ 56 ]. The theory is based on the assumption that people are motivated to avoid and treat illness threats and that people are active, self-regulating problem solvers [ 57 ]. Individuals, it is implicitly assumed, will endeavour to reach a state of internal equilibrium through testing coping strategies. The process of creating health threat representations and choosing coping strategies is assumed to be dynamic and informed by an individual's personality, and religious, social and cultural context [ 55 ]. In addition, a complex interplay exists between environmental perceptions, symptoms and beliefs about disease causation [ 54 ].

The self-regulation theory offers little guidance related to the design of interventions [ 7 ] and no meta-analyses examining evidence for the effectiveness of this theory were identified. While the theory seems intuitively appropriate, specific suggestions are needed as to how these processes could promote adherence.

Stage perspectives

The transtheoretical model (ttm).

This theory is most prominent among the stage perspectives. It hypothesizes a number of qualitatively different, discrete stages and processes of change, and reasons that people move through these stages, typically relapsing and revisiting earlier stages before success [ 58 , 59 ]. This theory is said to offer an "integrative perspective on the structure of intentional change" [[ 60 ], p. 1102] – the perceived advantages and disadvantages of behaviour are crucial to behaviour change [ 61 ].

The process of change includes independent variables that assess how people change their behaviour [ 62 ] and the covert and overt activities that help individuals towards healthier behaviour [ 63 ]. Different processes are emphasised at different stages.

Criticisms of TTM include the stages postulated and their coverage and definitions, and descriptors of change. According to Bandura [ 40 ], this theory violates all three of the basic assumptions of stage theories: qualitative transformations across discrete stages, invariant sequence of change, and non-reversibility. In addition, the proposed stages may only be different points on a larger continuum [ 29 , 58 , 63 ]. Bandura [ 29 ] suggests that human functioning is too multifaceted to fit into separate, discrete stages and argues that stage thinking could constrain the scope of change-promoting interventions. Furthermore, TTM provides little information on how people change and why only some individuals succeed [ 28 ].

Sutton [ 56 ] argues that the stage definitions included in the TTM are logically flawed, and that the time periods assigned to each stage are arbitrary. Similarly, there is also a need for more attention to measurement, testing issues and definition of variables and causal relationships [ 58 ]. The coverage and type of processes included may also be inadequate [ 63 ].

The TTM has received much practitioner support over the years, but less direct research support for its efficacy [ 3 , 10 ]. The meta-analyses identified for this review did not offer direct support for the theory; while one found that individuals use all 10 processes of change [ 64 ], another found that interventions that used the stage perspective were not more efficient than those not using the theory [ 65 ]. Further evidence of its efficacy is therefore needed. A strength of this theory is that it allows interventions to be tailored to individual needs. However, large-scale implementation of these interventions may be time consuming, complicated and costly. Its use may be more appropriate in areas where rapid behaviour change is not necessary.

This review has discussed a number of health behaviour theories that contribute to understanding adherence to long-term medications, such as those for TB and HIV/AIDS.

Although the use of theory to develop interventions to promote adherence offers several advantages, it also has some limitations. Firstly, there is little evidence that allows for the direct comparison of these theories [ 66 ]. Combining studies based on even one theory, in order to perform a meta-analysis to assess its effectiveness in predicting behaviours, is difficult due to various methodological problems in the original studies [ 60 ]. Furthermore, the number of theories in this field has proliferated over time, as theorists have examined different areas of behaviour and engaged in re-examining existing explanatory theories. Researchers, health planners and practitioners may therefore be overwhelmed by the multitude of theories available to them and the fragmented, and often contradictory, evidence. Questions also remain regarding the applicability of these theories to contexts other than those in which they were developed. Ashing-Giwa [ 67 ], for example, suggests that the above theories do not address socio-cultural aspects sufficiently. Issues such as the stigma attached to TB due to its perceived relation to HIV (especially in developing countries) may impact on the acceptability and the uptake of interventions. Further attention should therefore be given to the question of whether theories developed in the USA and the UK are applicable to individuals in other contexts where the disease burden from HIV/AIDS and TB is greatest.

Secondly, health behaviour change theories have tended to encompass a wide variety of health behaviours, each qualitatively different. The systematic reviews identified for this paper included studies ranging from smoking cessation to mothers limiting babies' sugar intake. Particular theories may be more applicable than others to improving adherence to specific health behaviours. For example, adherence to long-term medication will necessarily be different to a behaviour change required to take up exercise. In addition, achieving adherence to TB medication may be seen as an urgent issue for public health because of its infectiousness, and the recent emergence of extremely drug resistant strains [ 68 ]. It is difficult therefore to compare the effects of the theories across health categories or even within individual categories.

Thirdly, few studies were identified that had examined the selected health behaviour theories in relation to long-term medication adherence, or that had developed interventions to promote long-term adherence explicitly based on these theories, particularly for TB. Sumartojo's [ 13 ] assessment that a theory-based approach has largely been absent within the field of TB behavioural research appears to remain valid today.

The application of theories to the design of interventions remains a challenge for researchers and programme planners [ 69 ] and there is considerable debate concerning the effectiveness and usefulness of theory in informing intervention development (see [ 2 , 70 , 71 ]). Despite a variety of studies in a variety of fields, or perhaps because of this variation, we would argue that there is no clear evidence yet for the support of any of these theories within the field of adherence behaviours. This is not to say that these theories cannot be useful – rather, we have insufficient evidence to conclusively determine this.

While these discussions continue, research should aim to shed light on the key questions related to the theory-intervention debate: Do sound theories result in effective interventions? Does an effective intervention constitute proof of a theory's value? How might theory be used to inform the design of an effective intervention? And how can a theory be reliably tested? Some research work has already been undertaken in these areas: in a systematic review of antiretroviral treatment adherence interventions, Amico et al. [ 72 ] found that the use of theory in constructing an intervention did not account for variability in the intervention's efficacy. However, it is unclear how many of the 24 included studies in this review articulated a health behaviour change theory or the extent to which this was done.

Two possible approaches have been suggested to addressing the difficulties raised by the multitude of existing theories on health behaviour change. One approach is to attempt to identify variables common to these theories. This has been undertaken for 33 health behaviour change theories [ 7 ] in order to make psychological theories more accessible and easier to select. The results of this study provide some guidance on the most important variables in psychological theories, and may assist in the further development of health behaviour change theories. A second approach is to attempt to integrate the theories. While there is a need for such theoretical integration [ 73 ], we argue that researchers and theorists alike should be cautious when picking and choosing parts of other theories to develop further theories – so-called "cafeteria-style theorizing" – as the resulting theories may include redundant variables [[ 29 ], p. 285].

Because some theories share overlapping variables describing using different names [ 8 , 41 ], and most differences are due to an emphasis of one variable over another [ 1 ], it would serve the development of this field to conduct studies to identify particular variables that perform best in predicting behaviour change. For example, in a meta-analysis of randomised controlled trials testing antiretroviral treatment adherence interventions, Simoni [ 16 ] found that giving basic information to patients, and engaging them in discussion about helping them to overcome cognitive factors, lack of motivation and unrealistic expectations about adherence, were effective in improving adherence. Similarly, comparative studies between theories could be used to identify effective components [ 74 ]. The field of health behaviour theory remains dynamic, and it is important to continue developing existing theories and approaches as new evidence emerges.

Applying health behaviour theories to medication adherence for TB and HIV/AIDS

How optimal adherence for TB and HIV/AIDS can be ensured remains an important question. While large numbers of studies have explored patients' and health care providers' views regarding adherence to TB treatment [ 75 ] or have described programmes to improve adherence to these medications, there are still relatively few rigorous evaluations of interventions to promote adherence to TB and HIV/AIDS treatments [ 76 , 77 ]; even fewer have explicitly utilised behaviour change theories. For example, a systematic review of interventions to promote adherence to TB treatment [ 77 ] included ten trials, none of which used an explicit theoretical framework. A similar review identified seven different randomised controlled trials of interventions to promote adherence to antiretroviral therapy [ 76 ], of which only one employed an explicit theoretical framework. Similar figures have been reported in other domains: a review of guideline implementation studies showed that less than 10% of these provided an explicit theoretical rationale for their intervention [ 78 ]. Given the paucity of evidence to support any particular health behaviour theory, we cannot therefore suggest that these theories be used routinely to design adherence promoting interventions. However, since these theories may well have practical behaviour change potential, and since the problem of medication adherence remains significant for both clinical medicine and public health, further exploratory and explanatory research is needed.

A number of recommendations emerge from this review (Table 2 ): firstly, future research should focus not on the development of new theories but rather on the further examination of those already elaborated. Several key attributes that should be encompassed by theories explaining behaviour change have been suggested, including demonstrated effectiveness in predicting and explaining changes in behaviour across a range of domains; an ability to explain behaviour using modifiable factors; and an ability to generate clear, testable hypotheses. The theories should include non-volitional components (i.e. issues over which individuals do not have complete control) and take into account the influence of external factors, as perceived by individuals [ 2 , 70 ].

Secondly, further work is required to identify theories of health behaviour that are most applicable to improving adherence to long-term medication. Existing health behaviour theories should be tested systematically to establish which best predict effects on different kinds of behaviour for different groups of people in different contexts. For example, does a particular theory predict changes in adherence behaviour for both men and women with TB in both England and South Africa? Some researchers have argued that experimental research and increased clarity in theories and methods could assist in the identification of effective behaviour change techniques, thereby contributing to the development of evidence-based practice in health psychology and implementation research [ 2 , 3 ]. Similar efforts need to be made regarding the use of theories as applied to adherence behaviour.

Thirdly, the abundance of theories and their poor evidence base highlights the need to develop and trial interventions that utilise these theories appropriately (i.e. in concordance with the theory), with well defined and operationalised variables. This will help to advance the study of human adherence behaviour and allow for better informed decisions related to how to these theories could be more widely applied in practice. (See references [ 2 ] and [ 75 ] for guidance on developing theoretically informed interventions). We have compiled a number of examples [see additional file 1 ] of the application of such theories in practice.

Finally, reports of interventions to promote adherence to long-term medications for other health issues, such as diabetes, asthma and hypertension, should be reviewed to determine how many have drawn on theory in the design and testing of these interventions; the range of theories utilised and the ways in which this was done; and the ways in which the use of theory contributed to understanding the effects of these interventions. Many reviews of such interventions exist (for example, see [ 83 , 84 ]) and these could act as a starting point for such work.

It is also important to list some of the limitations of this review. Firstly, we have been unable to capture all the available data on tests of health behaviour theories. Secondly, this paper examines only theories constructed by researchers and does not explore the health theories held by those receiving treatment. These lay theories of adherence with regard to antiretroviral [ 81 ] and TB treatment [ 75 ] are discussed elsewhere.

It should also be noted that any understanding of individual health behaviour, and interventions to change this, must be located within the relevant social, psychological, economic and physical environments [ 28 ]. Much research on adherence to TB medication has indicated that poor adherence is commonly the result of factors outside the individual's control, including clinic and health care organisation factors (such as interruptions to drug supply and long distances to health facilities) and structural factors (such as poverty and migration) [ 13 , 82 , 83 ]. Similar issues have been reported for adherence to ART [ 84 ]. Any focus on changing the behaviours of individuals with TB or HIV should not result in the neglect of these other dimensions or the further disadvantaging of the poor and vulnerable, thereby widening health disparities. Interventions that focus on providers, the provider-patient relationship, health system and contextual factors therefore also need to be developed and evaluated [ 76 ].

There is no simple solution to the problem of adherence, or to the area of behaviour change. Health behaviour theories may shed light on the processes underlying behaviour change. However, an explicit theoretical basis is not always necessary for a successful intervention and further examination is needed to determine whether theory-based interventions in health care are more effective than those without an explicit theoretical foundation [ 2 , 70 ]. This review contributes to advancing this field by describing the commonly cited health behaviour theories, presenting the evidence and critique for each; discussing the applicability of these theories to adherence behaviour; and highlighting several recommendations for research and theory development. To understand and overcome the barriers to treatment adherence, considerable research is needed. However, given the importance of long-term medication adherence to global public health, particularly in relation to the HIV and TB epidemics, such research should receive much higher priority.

Abbreviations

Human immunodeficiency virus/Acquired immunodeficiency syndrome

Tuberculosis

Antiretroviral

Theory of reasoned action

Protection motivation theory

Health belief model

Theory of planned behaviour

Information-motivation-behavioural skills model

Antiretroviral therapy

Transtheoretical model

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The authors would like to acknowledge the Norwegian Health Services Research Centre, the GLOBINF Network, the London School of Hygiene and Tropical Medicine and the Effective Health Care Research Programme Consortium of the Liverpool School of Tropical Medicine for supporting Salla Munro during the preparation of this article. We would also like to thank Judy Dick and Sheldon Allen for their comments on drafts of this review; Sylvia Louw, Anna Gaze, and Joy Oliver for their administrative support; and Simon Goudie for his editing of the paper.

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Munro, S., Lewin, S., Swart, T. et al. A review of health behaviour theories: how useful are these for developing interventions to promote long-term medication adherence for TB and HIV/AIDS?. BMC Public Health 7 , 104 (2007). https://doi.org/10.1186/1471-2458-7-104

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DOI : https://doi.org/10.1186/1471-2458-7-104

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The application of health behavior theories to promote cervical cancer screening uptake

Affiliations.

• 1 Université Catholique de Louvain, Louvain, Belgium.
• 2 Faculty of Psychology and Educational Sciences, Université Catholique de Louvain, Louvain, Belgium.
• 3 Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, India.
• 4 Faculty of Public Health, Université Catholique de Louvain, Louvain, Belgium.
• PMID: 34231254
• DOI: 10.1111/phn.12944

Background: While cervical cancer is a major cause of mortality, its progress and survival rate can be improved through screening. Yet despite their wide availability, women's participation in cervical cancer screening (CCS) programs is often suboptimal, especially in low- and middle-income countries. Besides demographic and organizational characteristics, screening uptake is influenced by psychological factors, most of which are included in health behavior theories. This systematic review compared different health behavior theories in terms of their capacity to explain CCS uptake and inform CCS promotion campaigns.

Methods: A comprehensive search and analysis of published intervention and non-intervention (observational) studies that applied at least one health behavior theory to CCS participation.

Results: After quality screening, 48 observational and 21 intervention studies were identified that applied the Health Belief Model (HBM), Theory of Reasoned Action (TRA), Theory of Planned Behaviour (TPB), Transtheoretical model (TTM), Social-ecological Model (SEM), and/or Theory of Triadic Influence (TTI) to CCS. The HBM was most frequently used to explain behavior, whereas the TPB was better at explaining screening intentions. Tailored intervention studies focusing on all theoretical constructs were most effective in modifying perceptions and increasing CCS uptake.

Conclusions: Despite their inconsistent use, health behavior theories can explain CCS intentions and behavior and contribute to the development of targeted interventions to promote screening uptake.

Keywords: beliefs; cancer; health behavior theories; health behaviors; interventions; public health nursing education; screening; women's health.

© 2021 Wiley Periodicals LLC.

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Master of Public Health

Health behavior concentration.

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Prepares students to understand and apply theories of health behavior and health promotion to improve population health

The Health Behavior Concentration prepares students to understand and apply theories of health behavior and health promotion to improve population health. Students in the Health Behavior Concentration will gain experience in behavioral-social science frameworks and methodologies for designing, implementing, and evaluating interventions, and in disseminating and translating findings for diverse communities. The Health Behavior Concentration also emphasizes the roles of cultural competence, ethical practice, professionalism, and community collaboration as vital to the design and delivery of public health interventions. 

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Students who earn an MPH in Brown with a concentration in Health Behavior should be able to do the following:

• Explain the similarities and differences, strengths and weaknesses of predominant behavioral and social science theories for public health.
• Apply the component principles of behavioral and social science theories to health behaviors.
• Examine how behavioral and social science theories can be used to facilitate change in health-related behavior.
• Apply principles of health literacy and communication best practices to develop a brief health communication.
• Design health communications to promote behavior change that results in decreased risks for disease and/or promote wellness.
• Develop a plan to monitor and assess the reach, fidelity, and outcome of health communications.
• Examine the causes and consequences of health disparities from the perspective of multiple behavioral and social science perspectives.

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Complete both of the following courses:

• PHP2340 , Theories of Behavioral and Social Sciences in Public Health (Fall)
• PHP2380 , Health Communications (Spring)

Students must complete three courses from the following two lists and at least one course must come from the Social Determinants of Health and Diversity list:

Social Determinants of Health and Diversity

• PHP1650 , Race, Racism, and Health (Spring)
• PHP1680U,   Intersectionality and Health Inequities (Spring)
• PHP1810 , Community-Engaged Research in Public Health (Spring)
• PHP1821 , Incarceration, Disparities, and Health (Fall)
• PHP1920 , Social Determinants of Health (Fall)
• PHP2365 , Public Health Issues in LGBT Populations (Spring)
• PHP 2428: Health Justice (Every other Spring; not offered in Spring 2025)

Health Behavior Content-Focused Courses

• PHP1300 , Parenting Behaviors, and Child Health (Next offered in Spring 2025)
• PHP1540 , Alcohol Use, and Misuse (Next offered in Fall 2025)
• PHP1550 , Substance Use and Vulnerability to Addictions (Fall)
• PHP1551 , Substance Use Prevention, Treatment & Policy (Spring)
• PHP1600 , Obesity in the 21st Century: Causes, Consequences, and Countermeasures (Spring)
• PHP1610 , Tobacco, Disease and the Industry: cigs, e-cigs, and more (Spring)
• PHP1690 , Technology and Behavior Change (Next offered in Fall 2025) 
• PHP1880 , Meditation, Mindfulness, and Health (Fall)
• PHP1822 , Effective Health Communication With Medically Underserved Populations in an Applied Learning Setting (Spring)
• PHP1885 , Measuring Mindfulness (Spring)
• PHP1890 , The Craving Mind (Fall)
• PHP1998 , Public Health Nutrition (Fall)
• PHP2310 , Physical Activity & PH (Fall)

*Students taking the qualitative analytic sequence must also take PHP2061 , Qualitative Analysis in Public Health Research, as an elective.

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Qualitative analytic sequence and fall epidemiology, qualitative analytic sequence and spring epidemiology, quantitative analytic sequence and fall epidemiology, quantitative analytic sequence and spring epidemiology.

All in-person students are required to complete a thesis. Students in the Health Behavior Concentration work with faculty advisors to design a thesis project appropriate to their interests and career path in the behavioral health aspects of public health.

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Mass Shootings

Will new parental liabilities extend to online behavior, the crumbleys’ unprecedented verdict opens the door for parental liability..

Posted June 25, 2024 | Reviewed by Abigail Fagan

This spring marked a new era regarding how legal exposure can extend to parents of children with serious mental illness and a capacity for violence. In March, two separate juries found the parents of Oxford school shooter Ethan Crumbley guilty of manslaughter, with a judge sentencing them to at least 10 years in prison in April. To be clear, the majority of individuals with serious mental illness are not violent; quite the contrary.

As discussed in a previous post , this ruling should serve as a wake-up call for gun owners with children, prompting them to think more seriously about the responsibility they might one day have to take for the potential actions of dependents experiencing serious crises or emotional distress. That said, parents who are not gun owners also have reason to reflect on this development and consider how to best protect their children, families, communities and themselves.

While approximately 44% of U.S. adults report that they live in a household with a gun, more than 90% have access to the Internet—another potentially dangerous vehicle for those in the throes of mental health crises. With the power of digitally connected devices, such struggling individuals have been known to harass, defame and even threaten people online, acting in response to manic episodes , paranoid delusions and other psychoses, for example.

As a mental health attorney who counsels families of loved ones with mental health issues and substance use disorders, I hear directly from my clients about the prevalence of this dangerous online behavior. But too often, there isn’t a clear understanding of the very serious associated civil and criminal liabilities. These can be legally appropriate given the harm such online activity can cause, with damaging posts and images often circulating in perpetuity.

It is not a great leap to believe that our justice system might soon hold parents responsible for damaging online behaviors of children with clear, ongoing mental health issues following the court’s decision to hold the Crumbleys accountable for the real-world actions of their son.

Of course, it is a challenging task for any parent or guardian to confiscate a teenage or adult child’s device. Oftentimes, such “ punishment ” isn’t even the answer. Instead, family members should focus on addressing the underlying symptoms when, in fact, a serious mental health issue might be contributing to dangerous online activity. This includes seeking treatment, adjusting medications and staging interventions, as necessary. Serious cases might require hospitalization and the use of legal tools like mental health warrants, as well as counsel from attorneys who specialize in matters like defamation and harmful online speech. It is critical for families to be able to identify “red flag” behaviors, taking proactive measures to prevent a tragedy.

As an additional step, it may be appropriate—under certain scenarios—for parents to limit their children’s online activity by deactivating devices, changing WiFi passwords, removing them from Internet plans, etc. Such boundaries can set clear behavioral expectations, reinforcing positive change. Moving forward, parents and guardians can create roadmaps to help their children “earn back” their Internet privileges, with the potential for monitoring, which is increasingly considered a necessary parental practice for all children, regardless of whether or not they have a mental health issue and/or related issues.

Family members of children with serious mental illness already face innumerous complex challenges. Unfortunately, their legal exposure to the online actions of their children represents another potential issue, which—hopefully—can be managed with appropriate, proactive measures.

Carolyn Reinach Wolf is a mental health attorney guiding families through the complex landscape of legal issues that impact individuals with serious mental illness and/or substance abuse.

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There was a tour of the Behavioral Health Department for one of Fulton County's DSPs. Hear more from Medical Records Specialist Paula Ridgnal. We like to expose our individuals to different things. One of our DSPs said they wanted to come and see what you all do. It was very interesting and I'm glad I pushed forward to do it. We talked about a lot of interesting things like what happens during the commissioner meeting, what happens when you don't have a 7 second delay, where you all film interviews and shows, the split between Fulton Films and FGTV, the people who work here and what they do, etc.

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Adolescent Mental Health, Behavior Problems, and Academic Achievement

Jane d. mcleod.

1 Indiana University, Bloomington, IN, USA

Ryotaro Uemura

2 Keio University, Tokyo, Japan

Shawna Rohrman

Associated data.

Prior research on the association of mental health and behavior problems with academic achievement is limited because it does not consider multiple problems simultaneously, take co-occurring problems into account, and control for academic aptitude. We addressed these limitations using data from the National Longitudinal Study of Adolescent Health ( N = 6,315). We estimated the associations of depression, attention problems, delinquency, and substance use with two indicators of academic achievement (high school GPA and highest degree received) with controls for academic aptitude. Attention problems, delinquency, and substance use were significantly associated with diminished achievement, but depression was not. Combinations of problems involving substance use were especially consequential. Our results demonstrate that the social consequences of mental health problems are not the inevitable result of diminished functional ability but, rather, reflect negative social responses. These results also encourage a broader perspective on mental health by demonstrating that behavior problems heighten the negative consequences of more traditional forms of distress.

Sociologists maintain a long-standing interest in the social distribution of mental health problems. Literally hundreds of studies have been published on differences in levels of psychological distress or rates of psychiatric disorder based on gender, race-ethnicity, and socioeconomic status (see McLeod 2013 for a review). Although patterns are not always consistent, disadvantaged social statuses are generally associated with high levels of distress and high rates of disorder ( Thoits 2010 ), confirming the strong mark that social organization leaves on our feelings and behaviors.

Despite the dominance of research on the mental health implications of social organization, studies of the social consequences of mental health problems contribute equally to the sociological mission. In contrast to clinicians and epidemiologists, who view social consequences as indicators of disorder severity (e.g., Kessler et al. 2005 ), sociologists consider social consequences to be evidence of stigma and social exclusion (e.g., Link et al. 1987 , 1989 ). By invoking these concepts, sociologists reject the assumption that the social consequences of mental health problems follow necessarily from functional impairments in favor of the alternative that these consequences reflect fundamentally social processes.

Academic achievement is among the most thoroughly studied social consequences of mental health problems. Most studies come from outside the sociology of mental health, especially from sociology of education, social epidemiology, and developmental psychology (e.g., Campbell and von Stauffenberg 2007 ). These studies find that youth with mental health problems perform less well in school and attain lower levels of education than other youth. The association holds throughout the early life course—in elementary school (e.g., Alexander, Entwisle, and Dauber 1993 ; Farmer and Bierman 2002 ), in middle and high school ( Fletcher 2010 ; McLeod and Kaiser 2004 ; Needham 2009 ), and into the postsecondary years ( Hunt, Eisenberg, and Kilbourne 2010 ; Kessler et al. 1995 ; Miech et al. 1999 ; Needham 2009 ). It holds for multiple indicators of mental health problems, including internalizing and externalizing problems in young children ( McLeod and Kaiser 2004 ), psychological distress and depression in preadolescents and adolescents ( Needham, Crosnoe, and Muller 2004 ), and specific disorders such as attention deficit hyperactivity disorder (ADHD) ( Galéra et al. 2009 ). It also holds for behavior problems that are closely associated with mental health, including delinquency and substance use ( Lynskey and Hall 2000 ; Maguin and Loeber 1996 ; Staff et al. 2008 ). The consistency of the association across diverse mental health and behavior problems confirms their significance for attainment.

Despite many years of relevant research, empirical evidence for the association of mental health and behavior problems with academic achievement is limited in three key ways. First, few studies consider multiple problems simultaneously ( Breslau 2010 ). Many youth experience more than one problem ( Costello et al. 2003 ), which means that studies of single problems will produce biased estimates. Second, and related, even when they do consider multiple problems, studies have not determined whether some combinations of problems have stronger associations than others. To the extent that they do, estimates from studies that fail to take combinations into account may misrepresent the social consequences of mental health problems. Finally, many studies include only limited controls for academic aptitude, introducing ambiguity into the interpretation of the results. These limitations weaken our understanding of which problems matter most and why.

We address these limitations in our analysis by asking the following:

• Which mental health and behavior problems have the strongest associations with future academic achievement among adolescents, independent of academic aptitude?
• Which specific combinations of problems are most consequential for achievement?

We answer these questions using data from the National Longitudinal Survey of Adolescent Health, or Add Health, a prospective, longitudinal survey of U.S. adolescents. We rely on a broad definition of mental health and behavior problems and include in our analysis four types of problems that predict academic achievement: depression, attention problems, delinquency, and substance use. These problems cover the two major dimensions of emotional and behavioral problems: internalizing problems—inward-directed forms of distress such as depression and anxiety—and externalizing problems—outward-directed forms of distress such as conduct disorder and impulsive behavior. They also cover a range of “troubled and troubling” behaviors that are of concern to education scholars ( Hobbs 1982 ). Sociologists who study the social distribution of mental health problems have argued for expanding the range of outcomes beyond depression and distress to ensure a comprehensive analysis of the consequences of social inequalities for well-being ( Aneshensel, Rutter, and Lachenbruch 1991 ; Schwartz 2002 ). We advocate an equally expansive approach to the definition of mental health in analyses of social consequences.

Do Social Consequences Differ Across Problems and Why?

The answers to our questions inform a long-standing debate in research on the social consequences of mental health problems: whether the consequences are attributable to functional impairments or to negative social responses. In mental health research, this debate is associated with labeling theory (e.g., Gove 1982 ; Scheff 1966 ). Labeling theory attributes the social consequences of mental health problems to the stigma of mental illness labels and the anticipation and experience of social rejection that follow ( Link et al. 1987 ). Critics of labeling theory minimize the role of stigma and assert that the social consequences of mental health problems are attributable to the functional impairments, or symptoms, associated with the problems ( Gove 1982 ).

Although the two sides of the debate are often presented as irreconcilable, the truth likely lies in between ( Gove 2004 ). For example, in a sample of mental patients, Perry (2011) observed that symptoms of “behavioral and emotional excess” (e.g., delusions and hallucinations) elicited greater social rejection by acquaintances and strangers than symptoms of behavioral and emotional deficit (e.g., flat affect, anhedonia). In other words, even among persons who have been formally labeled, social responses depended on the specific nature of the impairment. In interactions with strangers and acquaintances, symptoms that were more overt and more disruptive to social interactions were associated with stronger negative responses.

The labeling theory debate resonates with research on the role of noncognitive traits in educational and occupational attainment. “Noncognitive trait” are productivity-related habits and traits that influence student success in formal educational settings, including aggressiveness, disruptiveness, emotional stability, self-discipline, effort, and self-esteem (see Farkas 2003 for a review). A central question in this line of research is whether noncognitive traits predict attainment independent of academic aptitude. To the extent that they do, theorists attribute the associations to subtle interactional and institutional processes that differentially value and reward student traits. Teachers prefer students who approach their work with positive attitudes, who are organized, and who are not disruptive in the classroom ( Henricsson and Rydell 2004 ; Mullins et al. 1995 ; Murray and Murray 2004 ) and they give heavy weight to work skills and habits when evaluating student performance ( Farkas 1996 ; Rosenbaum 2001 ). Beyond the classroom, schools reward students whose behaviors contribute to maintaining social order and punish students whose behaviors are disruptive or threatening ( American Psychological Association Zero Tolerance Task Force 2008 ). In short, regardless of students’ abilities to achieve, students’ behaviors importantly determine their eventual attainments.

Although different in the specifics, labeling theory and theories of noncognitive traits share a common interest in the extent to which diminished social achievements result from functional impairments or from negative social responses. At the most basic level, we engage this issue by controlling academic aptitude—the most relevant indicator of impairment—throughout the analysis. Adolescents with high levels of depression, attention problems, and delinquency score lower on standardized achievement tests and tests of verbal and performance IQ than youth with low levels of problems (see Hinshaw 1992 and Roeser, Eccles, and Strobel 1998 for reviews). Finding that the associations of youths’ problems with academic achievement remain significant with controls for academic aptitude would strengthen our claim that the associations reflect more than functional impairments.

Our analysis of differences in the associations across types of mental health and behavior problems engages this issue at a deeper level. Following from Perry's (2011) finding that different mental illness symptoms elicit different social responses in public settings, we hypothesize that different mental health and behavior problems elicit different responses in school settings. Theories of noncognitive traits imply that behaviors that signal a lack of interest in achievement and/or that are disruptive will elicit more negative responses than anxiety, passivity, and withdrawal. Because the behaviors associated with ADHD, delinquency, and substance use indicate disengagement and are more disruptive, we hypothesize that these problems will be more strongly associated with academic achievement than depression.

The few studies that have considered multiple types of problems simultaneously support this hypothesis. Attention problems, delinquency (or conduct problems), and substance use are more strongly associated with subsequent educational attainment than is depression ( Hunt et al. 2010 ; Johnson et al. 1999 ; Miech et al. 1999 ). However, none of these studies included measures of all three types of externalizing problems so we do not know whether certain externalizing problems impede academic success more than others.

Distinguishing attention problems from other externalizing problems is especially important because their interpretation is more ambiguous. Although considered an externalizing problem by clinical and epidemiological researchers, attention problems have direct bearing on learning and could be considered an indicator of aptitude. In a comprehensive analysis of data from six longitudinal studies, Duncan and colleagues (2007) observed that attention skills affected later elementary test scores net of aptitude but that other mental and behavior problems did not. If their finding extends to older ages, it would imply that, contrary to theories of noncognitive traits, non-learning-related traits have little influence on achievement processes.

Do Some Combinations of Problems Matter More Than Others?

Our second research question extends our interest in different types of problems to ask whether there are specific combinations of problems that have especially strong associations with academic achievement. The experience of co-occurring problems is an important source of heterogeneity among youth with mental health and behavior problems. Drawing on data from the Great Smoky Mountains Study, Costello and colleagues (2003) reported that adolescents with ADHD were two to seven times more likely than other adolescents to meet criteria for a depressive disorder. ADHD also increased the risk of conduct disorder—the psychiatric analogue of delinquency—by a factor of three, and substance use disorders increased the risk of mood disorders and conduct disorder by that much or more ( Costello et al. 2003 ; see Lewinsohn, Rohde, and Seeley 1995 for similar results). Evidence for the causal relationships reflected in these patterns is mixed, although it appears that the onset of ADHD and conduct problems precedes the onset of substance use and that depression precedes the onset of substance use, at least in boys (see Kessler 2004 for a review).

Accounting for combinations of problems in studies of academic achievement is important for empirical, practical, and theoretical reasons. Empirically, studies that fail to account for combinations of problems may underestimate associations because youth with the most consequential combinations are pooled with other youth in the estimates. Practically, knowing which combinations of problems are most strongly associated with academic failures informs interventions by identifying subsets of youth with greater need for services. Theoretically, knowing which combinations of problems matter most for academic achievement informs our evaluation of the relative importance of impairment versus social responses.

Clinical research suggests that youth who have more than one problem will face additional challenges in school simply because they are more impaired. For example, depressed youth who experience other mental health or behavior problems have more depressive episodes and use services at a higher rate than depressed youth who do not experience other problems ( Rohde, Lewinsohn, and Seeley 1991 ). Global functioning also declines with increases in the number of problems youth experience ( Lewinsohn et al. 1995 ). Finding that academic achievement declines with the number of problems regardless of which problems they are would suggest that increases in impairment are responsible for the association.

In contrast, theories of noncognitive traits imply that combinations of problems that involve delinquency and substance use will have especially strong associations with academic achievement because these problems are more likely to disrupt classrooms and generate punitive responses. Teachers judge oppositional behaviors as volitional and coercive, whereas they judge the behaviors associated with ADHD as involuntary ( Lovejoy 1996 ). Although most substance use occurs off school grounds, substance use that does occur in school, particularly smoking, may also be interpreted by school personnel as evidence of a defiant attitude ( Finn 2006 ). Finding that combinations of problems involving delinquency and substance use are more strongly associated with academic achievement than combinations of problems involving depression or attention problems would add support to explanations grounded in social responses.

In sum, the current study contributes to theory and research on the social consequences of mental health problems by estimating the associations of multiple problems with academic achievement simultaneously and by considering co-occurrences. The results of our analyses speak to a central debate regarding the relative importance of functional impairment versus social responses in those associations and, more generally, to theories of the role of noncognitive traits in attainment.

DATA AND METHODS

The data for the analysis come from the National Longitudinal Study of Adolescent Health, or Add Health. The Add Health is a longitudinal survey study of the health and well-being of U.S. adolescents that follows youth from the middle and high school years through the transition to early adulthood. A stratified sample of 80 high schools and 52 middle schools was selected into the study in 1994. Seventh through 12th grade youth who attended those schools were invited to participate in an in-school survey ( N = 90,118).

Of the youth who participated in the in-school survey, a randomly selected subsample of 20,745 participated in a subsequent Wave I in-home survey; an interview also was conducted with one of their parents. With the exception of the Wave I high school seniors, all respondents to the Wave I in-home survey were invited to participate in a Wave II interview approximately one year later ( N = 14,738 completed interviews) and a third wave of data collection in 2001-2002 ( N = 15,197). In 2008-2009, a fourth wave of data was collected from the original Wave I respondents ( N = 15,701). We included in our analysis 9th through 12th graders from the Wave I in-home survey who were also interviewed at Wave IV and who had valid sampling weights ( N = 6,315).

The sociodemographic profile of the sample highlights its representativeness. (See Appendix A in the online supplement [available at http://jhsb.sagepub.com/supplemental ] for complete descriptive statistics.) Women comprised just over half the sample (54 percent), and whites were the majority racial-ethnic group (54 percent), with sizable samples of African American and Latino/Latina youth (19 percent and 17 percent, respectively) and of youth with other racial-ethnic identities (10 percent). Roughly 56 percent of youth lived with both biological parents and 25 percent with single parents at Wave I, comparable to national figures ( Rawlings and Saluter 1995 ). Among the parents, 87 percent received a high school degree—also comparable to national figures ( U.S. Census Bureau 1994 )—and 34 percent received a college degree or higher.

Academic Achievement

We used two indicators of academic achievement as dependent variables: post–Wave I high school grade point average (GPA) and highest educational degree received. Our measure of post–Wave I high school GPA came from the Adolescent Health and Academic Achievement Study, a supplemental data collection that coded information from high school transcripts. Not all high school transcripts were coded, leaving a smaller sample for analyses of this outcome ( N = 4,701). We used post–Wave I GPA rather than cumulative high school GPA because pre–Wave I GPA could be a cause, rather than a consequence, of Wave I mental health and behavior problems. Using post–Wave I GPA eliminates most of the 12th graders from the analysis of this outcome but does not affect our conclusions. 1 Analyses that used a measure of GPA for all of the high school years (and that included all 12th graders) produced comparable results.

Highest educational degree received was based on respondent reports given at the Wave IV interview. We collapsed the original 13-category variable into the following: received no degree (1), received GED or high school equivalency (2), received high school diploma (3), completed technical training (4), completed some college classes (5), received bachelor's degree (6), or received higher degree (7). Although most people have completed their educations by their late 20s, some respondents may obtain more education in the future.

On average, this is a highly educated sample. The average highest degree received was 4.72, just below “some college.” The high levels of educational attainment are not surprising given that youth were recruited from schools. Nevertheless, some of these youth struggled academically. The average post–Wave I high school GPA was 2.55.

Mental Health and Behavior Problems

Unless otherwise noted, all measures of mental health and behavior problems were based on youth self-reports from the Wave I interview. To facilitate the analysis of combinations of problems, we constructed dichotomous measures for each type of problem. The pattern of main effects was the same for continuous versions of the variables.

Our measure of depression was based on a 19-item revision of the Center for Epidemiologic Studies-Depression Scale ( Radloff 1977 ). 2 The items index physical and psychological symptoms associated with depressive disorders, such as “you didn't feel like eating, your appetite was poor” and “you felt that you could not shake off the blues, even with help from your family and friends” (coded 0 = never or rarely during the past week to 3 = most of the time or all of the time during the past week). To compute a scale score, all available items were averaged for respondents who answered half of the items or more (α = .87 in this sample). We created a dichotomized measure of depression that represented youth with scores at or above the clinical cutoff (1.15 on the averaged scale; Roberts et al. 1990 ). Based on this measure, just over 10 percent of youth had high levels of depression, consistent with past epidemiological research ( Lewinsohn, Rohde, and Seeley 1998 ).

Our measure of attention problems was based on retrospective reports of ADHD symptoms from the Wave III data collection. Respondents answered 18 questions about how often they engaged in ADHD-related behaviors when they were between 5 and 12 years of age (e.g., you fidgeted with your hands or feet or squirmed in your seat; 0 = never or rarely, 1 = sometimes, 2 = often, or 3 = very often). As with the measure of depression, we averaged reports across the items whenever the respondent had valid values on half of the items or more (α = .90 in this sample). The items in the scale were based on the SNAP-IV, an instrument designed to assess ADHD in children ( Swanson 1992 ). Similar instruments, when used as retrospective reports, have shown adequate test-retest and internal consistency reliability as well as strong correlations with independent assessments of child behavior (e.g., Wierzbicki 2005 ). We dichotomized the measure of ADHD at the 80th percentile, which corresponded to a score of 1.11 (between “sometimes” and “often”). Supplemental analyses with a variable dichotomized at the 90th percentile produced substantively similar results (see endnotes). Although our cut point does not adhere to a clinical standard, high but subclinical levels of problems are associated with significant functional and social impairment ( Angold et al. 1999 ).

Following Haynie (2001) , we measured delinquency with an additive index based on youths’ self-reports of participation in 14 delinquent activities in the past year, each coded 0 (never) or 1 (one or more times). The items ranged from “painted graffiti” to “shot or stabbed someone.” We dichotomized the index at the 80th percentile to identify youth who were engaged in the very highest levels of delinquency (zero to three vs. four or more). (The end-notes describe results for a 90th percentile measure.)

Our measure of substance use was based on youths’ responses to a comprehensive series of questions about alcohol use (getting “drunk or ‘very, very high’”) in the past 12 months and about cigarette smoking and marijuana and other illicit drug use in the past 30 days. Following Nonnemaker, McNeely, and Blum (2003) , for each type of substance, we created dummy variables that distinguished youth who regularly used any of the substances from those who did not. 3 In addition, because some studies have found that cigarette use is more strongly associated with educational attainment than other types of substance use (see Breslau 2010 for a review), we present supplemental results for a disaggregated measure of substance use. The rate of regular substance use in the sample was 23 percent, with 14 percent of youth reporting regular cigarette use, 11 percent regular alcohol use, and 8 percent regular use of other drugs.

Combinations of Problems

Based on the dummy variables for specific mental health and behavior problems, we created a set of mutually exclusive dummy variables to represent specific combinations: for example, depression alone, attention problems alone, depression and attention problems. Although functionally equivalent to constructing multiplicative interactions among the dichotomous indicators, this coding strategy avoids multicollinearity and, when coupled with post-estimation contrasts, facilitates comparisons across all the different possible combinations of problems. The rates of specific combinations of problems were low, but the rates of combined problems overall were high. Roughly 29 percent of youth experienced any of the mental health problems alone, ranging from a low of 4 percent for depression to a high of 10 percent for attention problems. Roughly 20 percent of youth experienced more than one problem, ranging from a low of 0.5 percent for depression-attention problems-delinquency to a high of 4.6 percent for depression and substance use. (See Appendix A online for details.)

Academic Aptitude

We assessed academic aptitude with Wave I standardized vocabulary test scores (range = 14-149, M = 101.39) and a variable based on parents’ reports of whether the youth had a learning disability or received special education services during the 12 months prior to the Wave I parent interview (1 = yes, 0 = no, M = 0.13). 4

Social Background

Mental health problems and low academic achievement are more common among children from lower socioeconomic groups and from single-parent households ( Bradley and Corwyn 2002 ; Pallas 2003 ). To account for potential spuriousness, we controlled the following Wave I variables in all models: gender, race, whether the youth's family received public assistance, highest level of parental education, family income, and family structure. We also controlled for grade level and the youth's age because potential educational attainment is higher for the older students in the sample.

Analytic Strategy

We used regression models tailored to the two dependent variables: ordinary least squares for high school GPA and ordinal logistic for highest degree received. We began with models that included dichotomies for mental health and behavior problems along with controls for academic aptitude and social background, and then we ran models that included the full set of dummy variables for specific combinations of problems.

Although there were few missing values for most of the analysis variables, three variables were missing for more than 10 percent of the sample: family income (23 percent missing), public assistance receipt (13 percent missing), and special education/learning disability (12 percent missing). These variables came from the parents’ interviews and were missing when parents did not participate or did not report the information. To preserve cases for the analysis, we estimated models using the ICE (Imputation by Chained Equations) and MICOMBINE multiple imputation procedures in STATA 11.1 ( Royston 2005a , 2005b ). 5 Together, these procedures generated 15 data sets—each with a different set of missing data imputations. We estimated the models within each data set and combined the results to yield a single set of parameter estimates. 6

We began by predicting high school GPA and highest degree from the indicators for specific mental health and behavior problems, with controls for social background and academic aptitude. For each outcome, we estimated models that included each mental health or behavior problem alone followed by models that included all problems together. Coefficients for the control variables are omitted for parsimony of presentation.

According to Table 1 , attention problems, delinquency, and substance use all were associated with lower high school GPA whether considered alone or simultaneously. In contrast, depression was only significantly associated with high school GPA in models that did not include the other problems. The associations of mental health and behavior problems with high school GPA were strong in terms of statistical significance and modest in magnitude. Based on Model 5 in Table 1 , youth with high levels of attention problems had GPAs that were .14 points lower on average than youth who did not, roughly 16 percent of a standard deviation; the difference between youth who did and did not have high levels of delinquency (b = –.15) was of the same magnitude 7 ; the difference based on regular substance use was a little more than twice as large (b = –.34). The final model disaggregates the substance use measure by type of substance: cigarette, alcohol, and other drugs (including marijuana). Cigarette and alcohol use were both significantly associated with lower GPA, but the difference for cigarette use was about three times as large.

Coefficients from Regressions of Academic Achievement on Specific Problems

Notes : Coefficients for GPA are from ordinary least squares regression models; coefficients for highest degree are from ordinal logistic regression models. Standard errors are in parentheses. All models included controls for academic aptitude and social background.

Although the coefficients for the control variables are not included in the table, many were roughly the same size as those for mental health and behavior problems. For example, the coefficient for youth living in a single parent household was –.17, for those receiving public assistance was –.16, and for black versus white race was –.15—about the same size as for attention problems and delinquency. The coefficients for other common predictors of academic achievement, including special education/learning disability status (b = –.22) and having a parent who attained a college education or more (b = .29), were smaller than those for substance use. Thus, although the associations for mental health and behavior problems were modest, they were comparable to those for other major sociodemographic predictors.

The results for highest degree received closely paralleled those for high school GPA. Depression, attention problems, delinquency, and substance use all were associated with receiving a lower degree when considered alone. The association of depression with highest degree became nonsignificant when the other problems were included in the model. Exponentiated coefficients provide estimates of the odds of receiving the next highest degree with a one-unit increase in the independent variable, in this instance, the shift from having a low to a high value on the dichotomous indicators for mental health and behavior problems. For attention problems, having a high versus low level of problems was associated with .76 (e –.28 ) times the odds (i.e., 24 percent lower odds) of receiving the next highest degree. The comparable odds for delinquency and substance use were .66 (e –.42 ) and .43 (e –.84 ), respectively. 8 When we disaggregated the substance use measure by type (Model 6), cigarette use was the only type of substance use that was significantly associated with highest degree. Youth who smoked regularly had .38 times the odds of receiving the next highest degree.

One could argue for including high school GPA as a control in the models for highest degree received because it captures student performance ability. We did not include it in our initial models, because although GPA is a function of student performance, it also is a function of student motivation, teachers’ expectations for student performance, and teachers’ evaluations of student behavior ( Farkas 1996 ; Hamre and Pianta 2001 ). To the extent that GPA reflects motivations, expectations, and evaluations, controlling for GPA controls for part of the process through which youth problems affect achievement. Nevertheless, to provide the most conservative estimates, we estimated an additional model with GPA added (Model 7 in Panel B of Table 1 ). The coefficients for delinquency and substance use were reduced by about half but remained significant, and the coefficient for attention problems became marginally significant ( p = .093). Thus, even with the most stringent controls for academic aptitude, behavior problems had significant associations with educational attainment. 9

Specific Combinations of Problems

The next set of models takes us to our second research question: the role of combinations of problems in academic achievement. Our initial models may misrepresent the associations of problems with academic achievement if some combinations of problems are more consequential than others.

The left panel of Table 2 presents coefficients for models predicting high school GPA from specific combinations of problems, with controls for academic aptitude and social background. The variables for each specific problem represent youth who experienced that problem alone; the other variables represent youth who experienced specific combinations of problems (e.g., Dp-A = depression and attention problems). We did not estimate models for combinations involving the disaggregated measure of substance use as the sample sizes were prohibitively small.

Coefficients and Predicted Values from Regression of High School GPA on Combinations of Problems

Notes : Dp = depression alone; A = attention problems alone; D = delinquency alone; S = substance use alone.

Coefficients from ordinary least squares regression. Standard errors are in parentheses. Model included controls for academic aptitude and social background. N = 4,701.

With the exception of youth who only experienced depression, youth who experienced every other problem, alone or in combination, had lower average GPAs than youth without any problems. This indicates that depression in and of itself is much less consequential for academic achievement than are behavior problems.

The right panel of Table 2 presents predicted GPAs for youth with specific combinations of problems, along with the significance of post-estimation tests that compared the coefficients for youth with only one problem to those with combinations involving that same problem. For example, the significance level for Dp-D in the first column of the right panel represents the significance of the difference in the coefficients for the Dp-D versus Dp groups. We estimated the significance of the comparisons for all groups but only present the comparisons in “nested” groups, that is, Dp versus Dp-A and Dp versus Dp-A-D but not Dp-A versus D-S.

Our results support three main conclusions. First, according to the coefficients, attention problems, delinquency, and substance use were associated with earning a lower GPA but depression was not. Even in the absence of additional problems, youth who experienced any one of the externalizing problems had diminished achievement. Second, according to the post-estimation comparisons, youth who experienced combinations of problems generally had lower GPAs than youth who experienced only one problem, although the magnitude of the difference varied. Youth with depression who experienced other problems had lower GPAs than youth who experienced depression alone: the predicted GPA for youth with depression was 2.70 whereas that for youth with depression and delinquency was 2.46 and that for youth with depression and substance use was 2.23. Youth with attention problems who also experienced delinquency and substance use had lower GPAs than youth with attention problems alone. Youth with delinquency had lower GPAs when they also experienced substance use but not when they experienced depression or attention problems. In addition, adding depression, attention problems, or delinquency did not significantly diminish the low GPAs associated with substance use. These results confirm that depression did not increase the educational risk associated with other problems and that substance use had the most consistent association with academic achievement.

Third, although not immediately obvious from this table, youth with three or more problems generally did not have significantly lower GPAs than did youth with two problems. Indeed, with one exception, post-estimation comparisons revealed no significant differences in GPA for youth with two versus three problems. (The exception was for youth with depression, attention problems, and delinquency [Dp-A-D] who had significantly lower GPAs than youth with depression and delinquency [Dp-D; p = .03]). Some of the absence of difference can be attributed to small sample sizes but some reflects a true absence of meaningful differentiation. A quick glance at the predicted GPAs across the groups indicates that although there are differences, the differences do not follow an obvious pattern with respect to the number of problems youth experienced. Some predictions in the two-problem combinations were lower than those in the three-problem combinations and vice-versa. The predicted GPA for the group with all four problems was lower than for all others but, based on post-estimation comparisons, was not significantly different on a consistent basis. 10

Comparable results for highest degree received are presented in Appendix B online. We did not include high school GPA as a control in the model based on the reasoning given earlier: GPA may mediate the associations of youth mental health and behavior problems with educational attainment. 11

The three main conclusions from the analysis of high school GPA held for highest degree received, but some of the specific results differed. First, as for GPA, delinquency (b = –0.47, p < .01) and substance use (b = –0.83, p < .001) were associated with receiving a lesser degree and depression was not (b = –0.08, p = .64). However, unlike for GPA, attention problems were not associated with highest degree received either (b = –0.21, p = .10). This suggests that attention problems alone matter less for educational attainment than they do for high school performance. Second, youth who experienced more than one problem generally achieved a lower degree than youth who experienced only one problem. As for GPA, adding depression did not significantly diminish attainment for youth with other problems and adding substance use did. However, unlike for GPA, attention problems were associated with lower educational attainment for youth with depression and substance use, and delinquency was not associated with diminished educational attainment for youth with depression or attention problems. This suggests that co-occurring attention problems heighten the risk of low attainment associated with other problems. Third, having three or more problems was not associated with significantly lower attainment than having two problems.

Our analysis addressed two key questions for research on the association of mental health and behavior problems with academic achievement: Which specific problems most strongly predict academic achievement? Are certain combinations of problems more consequential than others? We found that attention problems, delinquency, and substance use were more strongly associated with achievement than was depression and that youth who experienced two or more problems earned lower GPAs and attained lower levels of education than youth who experienced only one problem. More specifically, having an additional externalizing problem—especially substance use—was associated with a significant decline in GPA and attainment. The associations were independent of academic aptitude, lending credence to the general conclusion that mental health and behavior problems are important determinants of status attainment outcomes ( Farkas 2003 ).

Our results confirm previous evidence that regular substance use is associated with diminished academic achievement (e.g., Breslau et al. 2008 ; Ellickson et al. 1998 ; Lynskey and Hall 2000 ; Newcomb et al. 2002 ). Although many studies that evaluate the association of substance use with academic achievement do not consider multiple substances simultaneously, those that do support our finding that cigarette use is the strongest predictor ( Breslau 2010 ). Why cigarette use is so consequential has not yet been established. One obvious explanation—that the association is spurious due to social background, risk propensity, cognitive impairment, or behavioral disinhibition—has been disconfirmed ( Lynskey and Hall 2000 ; Staff et al. 2008 ). Another explanation attributes the association to diminished academic motivation, especially as reinforced by deviant peer associations ( Breslau 2010 ). However, in our analysis of highest degree received, we controlled GPA, a reasonable if imperfect proxy for motivation, and observed significant residual effects of cigarette use. We propose an alternative: that cigarette use is more likely to elicit strong negative sanctions from school authorities and that these sanctions diminish attainment. According to the National Center on Addiction and Substance Use (2011) , most schools respond to substance use punitively rather than therapeutically ( American Psychological Association Zero Tolerance Task Force 2008 ). Because youth are more likely to smoke cigarettes at school than they are to use alcohol ( Finn 2006 ), the effect of punitive disciplinary policies would be especially pronounced for that substance ( McNeely, Nonnemaker, and Blum 2002 ).

We also observed that delinquency was negatively associated with GPA and educational attainment whether considered alone or in combination with other problems. Research on delinquency and academic success typically assumes that poor academic performance predicts future delinquency ( Maguin and Loeber 1996 ). Because our measure of delinquency was taken prior to the measures of academic achievement, our analysis provides strong evidence for the reverse. Further strengthening our conclusion, the association of delinquency was independent of attention problems—a commonly discussed precursor of both delinquency and poor academic performance ( Satterfield, Hoppe, and Schell 1982 ).

Previous evidence for the association of depression with academic achievement is both more limited and more mixed. Major epidemiological surveys find that early-onset depression is not associated with subsequent educational attainment independent of other mental disorders (e.g., Breslau et al. 2008 ; Miech et al. 1999 ). In contrast, studies using the Add Health report a significant effect of adolescent depression on high school completion and college entry ( Fletcher 2008 ; Needham 2009 ). Our analyses establish that the discrepancy is attributable to our controls for other mental health and behavior problems: We observed a significant effect for depression that became nonsignificant with controls for other problems. For scholars interested in the reciprocal associations between social disadvantage and psychological distress (for which depression is a common indicator), the most important implication of our results is that the causation runs predominantly from disadvantage to distress rather than the reverse. That the same is not true for more disruptive problems highlights the need for a more differentiated framework for the associations of mental health and behavior problems with social attainments.

Such a framework could begin with the debate that motivated our analysis: whether the social consequences of mental health problems are the inevitable result of functional impairments or whether they depend on negative social responses. Three findings support the latter position. First, we observed significant associations independent of academic aptitude (and, for substance use and delinquency, independent of attention problems). Second, problems that disrupt activities, challenge teacher authority, and are likely grounds for punitive action—especially delinquency and substance use—were more strongly associated with academic achievement than depression. Third, although youth who experienced multiple problems achieved less academically than youth who experienced only one problem, academic achievement did not decline consistently with the number of problems. Together, these findings provide strong evidence that impairments associated with behavior problems are not the sole determinants of their negative social consequences. In the case of highest degree received, the learning impairments associated with attention problems do appear to increase the risk of low attainment associated with other problems, but attention problems alone are inconsequential.

Beyond its contributions to this debate, our analysis carries lessons for sociologists of mental health and stratification researchers. For sociologists of mental health, our results suggest the value of incorporating a broad array of emotional and behavioral dysfunctions into our analyses, consistent with the practice of developmental scholars ( Achenbach et al. 1981 ). Sociologists of mental health have tended to maintain a narrow focus on “distress,” often as represented by depression. Some scholars conceptualize substance use as a “masculine” expression of distress analogous to depression (e.g., Aneshensel et al. 1991 ), but others assert that substance use represents “bad behavior” rather than distress ( Mirowsky and Ross 1995 ). Delinquency and other threatening behaviors have receive comparatively little attention ( Schwartz 2002 ; Umberson, Williams, and Anderson 2002 ). Our results demonstrate that even if distinct from “distress,” substance use and delinquency are important components of the complex problems youth experience in the real world ( Mirowsky and Ross 2002 ) and that they have profound social consequences.

For stratification researchers, our analysis demonstrates that the thoughts, feelings, and behaviors that characterize mental health and behavior problems are relevant to how adolescents fare in the educational system. Most research on noncognitive traits focuses on conscientious work habits, self-confidence, and the like. Although there is direct evidence for teachers’ differential evaluations of these traits ( Farkas 2003 ), less is known about how teachers evaluate mental health and behavior problems. As the effect sizes for these problems are greater than or equal to those for traditional predictors of academic achievement, they deserve greater attention from stratification researchers.

We acknowledge three features of our analysis that limit our conclusions. First, we did not have access to formal diagnostic measures. Although our dichotomized indicators captured high levels of problems, the associations we observed might be stronger for problems that meet diagnostic criteria for major mental disorders ( Breslau 2010 ). Second, we lacked information on academic achievement in earlier grades. The process we observed may have begun much earlier in youths’ educational careers, driven either by the effects of early mental health problems on later academic achievement or the effects of early academic failures on later mental health problems ( Roeser et al. 1998 ). Consistent with the latter possibility, some research indicates that youth initiate cigarette use as a means of coping with poor achievement ( Schulenberg et al. 1994 ). Third, the causal sequence among the co-occurring problems youth experienced remains uncertain. Co-occurring substance use could represent a coping response for youth with depression or attention problems. If so, models that include substance use would underestimate the effects of other problems because they control for the mediational process that produces their effects. Arguing against this possibility, depression and attention problems were more weakly associated with academic achievement even before the control for substance use was introduced. Nevertheless, knowing more about the origins of co-occurring problems would deepen our understanding of how mental health and behavior problems come to affect achievement.

Despite these limitations, our analysis advances research on the social consequences of mental health problems in three important ways: by highlighting the special relevance of disruptive problems within school settings; by demonstrating that youth with co-occurring problems face more academic challenges than other youth; and by providing evidence that although abilities powerfully shape future attainments, so too do subtle evaluative processes.

Supplementary Material

Acknowledgments.

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by grant R01 HD050288 from the National Institute of Child Health and Human Development.

Jane D. McLeod is professor of sociology and associate dean for social & historical sciences and graduate education in the College of Arts and Sciences at Indiana University. Jane is currently engaged in research on the life course outcomes of high-risk youth and is co-editor (with Ed Lawler and Michael Schwalbe) of the Handbook of the Social Psychology of Inequality .

Ryotaro Uemura is a project assistant professor in the International Center at Keio University, Japan. His current research examines the associations of individuals’ social structural positions with social attitudes in cross-national context.

Shawna Rohrman is a doctoral candidate in sociology at Indiana University. Her dissertation research examines racial disparities in health and well-being during the transition to adulthood. She is also interested in the health effects of prejudice and discrimination among youth.

1 Of the youth who reported that they were in 12th grade at Wave 1, 23 had valid post–Wave I GPA information. Five were in their 4th year of high school at Wave I and continued into a 5th year after that; three were in the 4th year of high school at Wave I but were taking 11th grade courses in that year; one was in the 3rd year of high school at Wave I but had an average of 12th-grade-level courses in that year; and 13 were in the 3rd year of high school at Wave I and had an average of 11th-grade-level courses in that year. According to the education data, one of these youth started high school in 1999, which we take to be a coding or reporting error.

2 The items in the Add Health were not identical to the original CES-D scale. Two items from the original scale were not used: “I had crying spells” and “My sleep was restless.” One new item, “You felt life was not worth living,” was added. One item was reworded from “I could not get going” to “It was hard to get started doing things.”

3 Youth were defined as regular smokers if they smoked 20 days or more. Regular alcohol use was defined as getting “drunk or very, very high” two or three days a month or more. Regular drug use was defined as using any drugs three or more times in the past 30 days.

4 In preliminary analyses, we also included youth reports of how often they had trouble getting their homework done and a measure of whether they had ever repeated a grade as indicators of aptitude. Because these indicators could be consequences of mental health and behavior problems, we removed them from our analysis. Results were substantively the same.

5 Most variables were imputed with prediction equations that included all other variables in the analysis. The exceptions were race, parental education, and family structure, which were passively imputed. Per von Hippel (2007) , we included dependent variables in the imputation procedure but restricted the analysis of each dependent variable to cases with valid values. Because of this restriction, the sample size for the analysis of GPA was 4,701. No cases with valid values for the weight variable had missing values on highest degree received.

6 There is some debate about how many imputed data sets should be used in this type of procedure. Although the use of five data sets has become standard practice, some evidence suggests that five may not be sufficient in all cases ( Graham, Olchowski, and Gilreath 2007 ). We chose 15 data sets for our analysis based on Graham et al.'s analysis of power and efficiency in multiple imputation procedures for models with modest effect sizes.

7 Results for models with measures dichotomized at the 90th percentile show a similar overall pattern with somewhat larger coefficients (e.g., b = –.22 for attention problems and b = –.29 for delinquency in Model 5; p < .001 for both).

8 The 90th percentile dichotomizations of attention problems and delinquency showed similar patterns. The 90th percentile delinquency measure had a stronger association (b = –.68, p < .001 in Model 5). The 90th percentile attention problems measure had a slightly weaker association (b = –.25, p < .001 in Model 5).

9 Previous studies of depression and academic achievement have found a stronger association for young women than for young men (e.g., Needham 2009 ). We reestimated the models for women and men separately; we also estimated gender differences in the associations of problems using multiplicative interactions. Depression was not significantly associated with academic achievement for either group or either outcome. Moreover, there was only one significant gender difference in the associations: attention problems predicted a lower GPA and lower degree attainment more strongly for girls than for boys.

10 The average GPA for the group with all four problems was significantly lower than that for the group with depression and delinquency (Dp-D, p < .01), attention problems and delinquency (A-D, p < .05), and depression and attention problems (Dp-A, p < .05) but was not lower than that for any other group with 2 or more problems.

11 In supplemental analyses where we controlled for GPA, several of the coefficients remained statistically significant: substance use alone (S; b = –.44, p < .001) and four combinations involving substance use (A-S, b = –.61, p < .001; D-S, b = –.69, p < .001; Dp-A-S, b = –1.30, p < .001; and A-D-S, b = –.77, p < .01). The significant contrasts of nested problem combinations all involved attention problems (A vs. A-S, p < .01; A vs. C-A-S, p < .001; A vs. A-D-S, p < .01).

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Guest Essay

Surgeon General: Why I’m Calling for a Warning Label on Social Media Platforms

By Vivek H. Murthy

Dr. Murthy is the surgeon general.

One of the most important lessons I learned in medical school was that in an emergency, you don’t have the luxury to wait for perfect information. You assess the available facts, you use your best judgment, and you act quickly.

The mental health crisis among young people is an emergency — and social media has emerged as an important contributor. Adolescents who spend more than three hours a day on social media face double the risk of anxiety and depression symptoms, and the average daily use in this age group, as of the summer of 2023, was 4.8 hours . Additionally, nearly half of adolescents say social media makes them feel worse about their bodies.

It is time to require a surgeon general’s warning label on social media platforms, stating that social media is associated with significant mental health harms for adolescents. A surgeon general’s warning label, which requires congressional action, would regularly remind parents and adolescents that social media has not been proved safe. Evidence from tobacco studies show that warning labels can increase awareness and change behavior. When asked if a warning from the surgeon general would prompt them to limit or monitor their children’s social media use, 76 percent of people in one recent survey of Latino parents said yes.

To be clear, a warning label would not, on its own, make social media safe for young people. The advisory I issued a year ago about social media and young people’s mental health included specific recommendations for policymakers, platforms and the public to make social media safer for kids. Such measures, which already have strong bipartisan support, remain the priority.

Legislation from Congress should shield young people from online harassment, abuse and exploitation and from exposure to extreme violence and sexual content that too often appears in algorithm-driven feeds. The measures should prevent platforms from collecting sensitive data from children and should restrict the use of features like push notifications, autoplay and infinite scroll, which prey on developing brains and contribute to excessive use.

Additionally, companies must be required to share all of their data on health effects with independent scientists and the public — currently they do not — and allow independent safety audits. While the platforms claim they are making their products safer, Americans need more than words. We need proof.

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Federal grant will address shortage of physician assistants trained in rural behavioral health services

BY Michele Coffill

Grand Valley's Physician Assistant Studies department received a five-year, $1.8 million federal grant to address the shortage of physician assistants who work in rural locations and are trained in behavioral health services.

Theresa Bacon-Baguley, professor and associate dean of research for the College of Health Professions, said the grant from U.S. Department of Health and Human Services, Health Resources and Services Administration (HRSA) will be used to train physician assistant studies (PAS) students, faculty and clinical preceptors to integrate behavioral health into their primary care services.

It's a crucial need in rural areas, Bacon-Baguley said. 

"We equate rural to mean northern Michigan or the Upper Peninsula, but there are locations an hour from Grand Rapids that are rural," she said. "We are training our students, faculty and preceptors to recognize behavioral health issues before they become a crisis."

Bacon-Baguley said this HRSA grant is a natural extension of the federal grant that helped establish Grand Valley's satellite PAS program in Traverse City. That program will celebrate its 10th anniversary next year. Nearly 80 percent of Grand Valley's PAS graduates, in Traverse City and Grand Rapids, practice in a rural setting.

Jill Ellis, associate professor and program director of PAS, said students can apply now for the rural behavioral health certificate course that begins in January. The project also provides a stipend for student housing. Over the five-year grant period, 90 students will be trained and a clinical coordinator will build new and enhance existing partnerships to expand the program's reach.

Andrew Booth, associate professor and department chair of PAS, said this grant makes Grand Valley's Physician Assistant Studies program unique.

"There are only a few other programs that offer this. Plus, it's a boost to a student's resume," Booth said. "Our students will be able to implement this training immediately when they graduate." 

PAS faculty members Martina Reinhold and Amanda Reddy are also part of the grant team.

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Jun 18, 2024

ICYMI: California providers break ground on three new behavioral health centers during first weeks of June

What you need to know: California providers, with support from the Newsom administration, have begun construction on three new behavioral health care centers with funding from the Behavioral Health Continuum Infrastructure Program. Following voter passage of Proposition 1, even more behavioral health treatment sites will be funded and built in the coming years.

SACRAMENTO  – In case you missed it, California has supported the groundbreakings of three new behavioral health centers in just the last month to increase Californians’ access to both out-patient and in-patient care.

The sites include a Community Wellness and Prevention Center to serve youth in the Oakland area, an outpatient behavioral health center in Modesto to serve children, youth, and their families in the Central Valley, and a behavioral health and physical health care campus called the Wellness Village that will serve individuals of all ages in the Coachella Valley who need mental health and substance use disorder treatment.

We are following through on our promise to move forward full steam ahead on new behavioral health centers and support for Californians – especially young people – who are struggling. Just as we ask our local officials to step up, use the tools available to them, and take accountability, my administration is doing the same. These new centers will soon be providing care and services to people across our state and are a beacon of more to come. Governor Gavin Newsom

These efforts, part of California’s Mental Health for All Initiative, represent just a fraction of the historic investments made by this administration to provide grant funding to local governments, businesses, non-profits, and tribal organizations to construct new sites and expand existing sites.

These funds will especially help children, youth, transition-age youth up to 25 years old, and pregnant or postpartum individuals and their families with mental health and/or substance use disorders. In 2025 and 2026, even more behavioral health treatment sites for all ages will be funded and built thanks to Proposition 1.   

Oakland Safe Passages:

On June 6, Safe Passages broke ground on a new Community Wellness and Prevention Center to serve youth in the Oakland area. The Department of Health Care Services (DHCS) awarded Safe Passages $9 million to build a safe space to address gaps in mental health and substance use disorder treatment for children and youth transitioning to adulthood. The wellness center will enable Safe Passages to serve more than 4,800 community members with critical resources and provide community-derived models of mental health services, meaning they are created and implemented with significant participation from the community they serve.

Center for Human Services:

On June 10 in Modesto, construction began on a new outpatient behavioral health center to serve children, youth, and their families in the Central Valley. DHCS awarded Center for Human Services more than $5 million to build a safe space to address gaps in mental health and substance use disorder treatment. This will enable Center for Human Services to serve more than 1,425 new community members with critical resources annually.

Riverside University Health System:

On June 12, Riverside University Health System broke ground on a new behavioral health and physical health care campus called the Wellness Village that will serve individuals in the Coachella Valley who need mental health and substance use disorder treatment. DHCS awarded Riverside University Health System more than $80 million to build a safe space to address gaps in behavioral health treatment. The portions of the campus funded through this effort will enable Riverside University Health System to provide critical resources to more than 20,900 community members annually.

Why this matters

Through the Behavioral Health Continuum Infrastructure Program , DHCS awards funding to eligible entities to construct, acquire, and expand properties and invest in mobile crisis infrastructure to further expand the range of community-based behavioral health treatment options for people with mental health and substance use disorders. Like Prop 1, this program aims to address various long-standing gaps in the behavioral health care system and meet the growing demand for services and support throughout the lifespans of people in need. 

How we got here

DHCS was authorized through 2021 legislation to award $2.2 billion in Behavioral Health Continuum Infrastructure Program competitive grants. In addition, DHCS is authorized to distribute roughly $4 billion in Behavioral Health Continuum Infrastructure Program grants under Proposition 1 bond funds. Proposition 1 consists of the Behavioral Health Services Act and Behavioral Health Bond Act of 2024, which dedicates up to $4.4 billion for Behavioral Health Infrastructure. Please see the Behavioral Health Continuum Infrastructure Program website for more information about grant recipients and additional details about all funding rounds.

Learn more about California’s Mental Health for All initiative.

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