Accounting for Context in Randomized Trials after Assignment.

Many preventive trials randomize individuals to intervention condition which is then delivered in a group setting. Other trials randomize higher levels, say organizations, and then use learning collaboratives comprised of multiple organizations to support improved implementation or sustainment. Other trials randomize or expand existing social networks and use key opinion leaders to deliver interventions through these networks. We use the term contextually driven to refer generally to such trials (traditionally referred to as clustering, where groups are formed either pre-randomization or post-randomization - i.e., a cluster-randomized trial), as these groupings or networks provide fixed or time-varying contexts that matter both theoretically and practically in the delivery of interventions. While such contextually driven trials can provide efficient and effective ways to deliver and evaluate prevention programs, they all require analytical procedures that take appropriate account of non-independence, something not always appreciated. Published analyses of many prevention trials have failed to take this into account. We discuss different types of contextually driven designs and then show that even small amounts of non-independence can inflate actual Type I error rates. This inflation leads to rejecting the null hypotheses too often, and erroneously leading us to conclude that there are significant differences between interventions when they do not exist. We describe a procedure to account for non-independence in the important case of a two-arm trial that randomizes units of individuals or organizations in both arms and then provides the active treatment in one arm through groups formed after assignment. We provide sample code in multiple programming languages to guide the analyst, distinguish diverse contextually driven designs, and summarize implications for multiple audiences.

Effect of Mobile Device-Assisted N-of-1 Trial Participation on Analgesic Prescribing for Chronic Pain: Randomized Controlled Trial.

OBJECTIVES: Opioids and non-steroidal anti-inflammatory drugs (NSAIDs) are frequently prescribed for chronic musculoskeletal pain, despite limited evidence of effectiveness and well-documented adverse effects. We assessed the effects of participating in a structured, personalized self-experiment ("N-of-1 trial") on analgesic prescribing in patients with chronic musculoskeletal pain. METHODS: We randomized 215 patients with chronic pain to participate in an N-of-1 trial facilitated by a mobile health app or to receive usual care. Medical records of participating patients were reviewed at enrollment and 6 months later to assess analgesic prescribing. We established thresholds of ≥ 50, ≥ 20, and > 0 morphine milligram equivalents (MMEs) per day to capture patients taking relatively high doses only, patients taking low-moderate as well as relatively high doses, and patients taking any dose of opioids, respectively. RESULTS: There was no significant difference between the N-of-1 and control groups in the percentage of patients prescribed any opioids (relative odds ratio (ROR) = 1.05; 95% confidence interval [CI] = 0.61 to 1.80, p = 0.87). There was a clinically substantial but statistically not significant reduction of the percentage of patients receiving ≥ 20 MME (ROR = 0.58; 95% CI = 0.33 to 1.04, p = 0.07) and also in the percentage receiving ≥ 50 MME (ROR = 0.50; 95% CI = 0.19 to 1.34, p = 0.17). There was a significant reduction in the proportion of patients in the N-of-1 group prescribed NSAIDs compared with control (relative odds ratio = 0.53; 95% CI = 0.29 to 0.96, p = 0.04), with no concomitant increase in average pain intensity. There was no significant change in use of adjunctive medications (acetaminophen, gabapentenoids, or topicals). DISCUSSION: These exploratory results suggest that participation in N-of-1 trials may reduce long-term use of NSAIDs; there is also a weak signal for an effect on use of opioids. Additional research is needed to confirm these results and elucidate possible mechanisms. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02116621.

Effectiveness of a Disability Preventive Intervention for Minority and Immigrant Elders: The Positive Minds-Strong Bodies Randomized Clinical Trial.

OBJECTIVE: To test the acceptability and effectiveness of a disability prevention intervention, Positive Minds-Strong Bodies (PMSB), offered by paraprofessionals to mostly immigrant elders in four languages. DESIGN: Randomized trial of 307 participants, equally randomized into intervention or enhanced usual care. SETTING: Community-based organizations in Massachusetts, New York, Florida, and Puerto Rico serving minority elders. Data collected at baseline, 2, 6, and 12 months, between May 2015 and March 2019. PARTICIPANTS: English-, Spanish-, Mandarin-, or Cantonese-speaking adults, age 60+, not seeking disability prevention services, but eligible per elevated mood symptoms and minor to moderate physical dysfunction. INTERVENTIONS: Ten individual sessions of cognitive behavioral therapy (PM) concurrently offered with 36 group sessions of strengthening exercise training (SB) over 6 months compared to enhanced usual care. MEASUREMENTS: Acceptability defined as satisfaction and attendance to >50% of sessions. Effectiveness determined by changes in mood symptoms (HSCL-25 and GAD-7), functional performance (SPPB), self-reported disability (LLFDI), and disability days (WHODAS 2.0). RESULTS: Around 77.6% of intervention participants attended over half of PM Sessions; 53.4% attended over half of SB sessions. Intent-to-treat analyses at 6 months showed significant intervention effects: improved functioning per SPPB and LLFDI, and lowered mood symptoms per HSCL-25. Intent-to-treat analyses at 12 months showed that effects remained significant for LLFDI and HSCL-25, and disability days (per WHODAS 2.0) significantly decreased 6-month after the intervention. CONCLUSIONS: PMSB offered by paraprofessionals in community-based organizations demonstrates good acceptability and seems to improve functioning, with a compliance-benefit effect showing compliance as an important determinant of the intervention response.

An Overview of Research and Evaluation Designs for Dissemination and Implementation.

The wide variety of dissemination and implementation designs now being used to evaluate and improve health systems and outcomes warrants review of the scope, features, and limitations of these designs. This article is one product of a design workgroup that was formed in 2013 by the National Institutes of Health to address dissemination and implementation research, and whose members represented diverse methodologic backgrounds, content focus areas, and health sectors. These experts integrated their collective knowledge on dissemination and implementation designs with searches of published evaluations strategies. This article emphasizes randomized and nonrandomized designs for the traditional translational research continuum or pipeline, which builds on existing efficacy and effectiveness trials to examine how one or more evidence-based clinical/prevention interventions are adopted, scaled up, and sustained in community or service delivery systems. We also mention other designs, including hybrid designs that combine effectiveness and implementation research, quality improvement designs for local knowledge, and designs that use simulation modeling.

Measuring Maladaptive Cognitions in Complicated Grief: Introducing the Typical Beliefs Questionnaire.

OBJECTIVES: Maladaptive cognitions related to loss are thought to contribute to development of complicated grief and are crucial to address in treatment, but tools available to assess them are limited. This paper introduces the Typical Beliefs Questionnaire (TBQ), a 25-item self-report instrument to assess cognitions that interfere with adaptation to loss. DESIGN: Study participants completed an assessment battery during their initial evaluation and again after completing treatment at 20 weeks. Test-retest reliability was assessed on a subsample of the participants who did not show change in complicated grief severity after the first 4 weeks of treatment. To examine latent structure of the TBQ, an exploratory factor analysis (EFA) was performed. SETTING: Academic medical centers in Boston, New York, Pittsburgh, and San Diego from 2010-2014. PARTICIPANTS: 394 bereaved adults who met criteria for complicated grief. MEASUREMENTS: The TBQ along with assessments of complicated grief symptoms and related avoidance, depression symptoms, functional impairment, and perceived social support. RESULTS: The TBQ exhibited good internal consistency (α = 0.82) and test-retest reliability (N = 105; intraclass correlation coefficient = 0.74). EFA indicated a five-factor structure: "Protesting the Death," "Negative Thoughts About the World," "Needing the Person," "Less Grief is Wrong" and "Grieving Too Much." The total score and all factors showed sensitivity to change with treatment. CONCLUSIONS: This new tool allows a clinician to quickly and reliably ascertain presence of specific maladaptive cognitions related to complicated grief, and subsequently, to use the information to aid a diagnostic assessment, to structure the treatment, and to measure treatment outcomes.

THE STRUCTURED CLINICAL INTERVIEW FOR COMPLICATED GRIEF: RELIABILITY, VALIDITY, AND EXPLORATORY FACTOR ANALYSIS.

BACKGROUND: Complicated grief (CG) has been recently included in the DSM-5, under the term "persistent complex bereavement disorder," as a condition requiring further study. To our knowledge, no psychometric data on any structured clinical interview for CG (SCI-CG) is available to date. In this manuscript, we introduce the SCI-CG, a 31-item "SCID-like" clinician-administered instrument to assess the presence of CG symptoms. METHODS: Participants were 281 treatment-seeking adults with CG (77.9% [n = 219] women, mean age = 52.4, standard deviation [SD] = 17.8) who were assessed with the SCI-CG and measures of depression, posttraumatic stress, anxiety, functional impairment. RESULTS: The SCI-CG exhibited satisfactory internal consistency (α = .78), good test-retest reliability (interclass correlation [ICC] 0.68, 95% CI [0.60-0.75]), and excellent interrater reliability (ICC = 0.95, 95% CI [0.89-0.98]). Exploratory factor analyses revealed that a five-factor structure, explaining 50.3% of the total variance, was the best fit for the data. CONCLUSIONS: The clinician-rated SCI-CG demonstrates good internal consistency, reliability, and convergent validity in treatment-seeking individuals with CG and therefore can be a useful tool to assess CG. Although diagnostic criteria for CG have yet to be adequately validated, the SCI-CG may facilitate this process. The SCI-CG can now be used as a validated instrument in research and clinical practice.

Trials of Intervention Principles: Evaluation Methods for Evolving Behavioral Intervention Technologies.

In recent years, there has been increasing discussion of the limitations of traditional randomized controlled trial (RCT) methodologies for the evaluation of eHealth and mHealth interventions, and in particular, the requirement that these interventions be locked down during evaluation. Locking down these interventions locks in defects and eliminates the opportunities for quality improvement and adaptation to the changing technological environment, often leading to validation of tools that are outdated by the time that trial results are published. Furthermore, because behavioral intervention technologies change frequently during real-world deployment, even if a tested intervention were deployed in the real world, its shelf life would be limited. We argue that RCTs will have greater scientific and public health value if they focus on the evaluation of intervention principles (rather than a specific locked-down version of the intervention), allowing for ongoing quality improvement modifications to the behavioral intervention technology based on the core intervention principles, while continuously improving the functionality and maintaining technological currency. This paper is an initial proposal of a framework and methodology for the conduct of trials of intervention principles (TIPs) aimed at minimizing the risks of in-trial changes to intervention technologies and maximizing the potential for knowledge acquisition. The focus on evaluation of intervention principles using clinical and usage outcomes has the potential to provide more generalizable and durable information than trials focused on a single intervention technology.

Optimal Design and Purposeful Sampling: Complementary Methodologies for Implementation Research.

Optimal design has been an under-utilized methodology. However, it has significant real-world applications, particularly in mixed methods implementation research. We review the concept and demonstrate how it can be used to assess the sensitivity of design decisions and balance competing needs. For observational studies, this methodology enables selection of the most informative study units. For experimental studies, it entails selecting and assigning study units to intervention conditions in the most informative manner. We blend optimal design methods with purposeful sampling to show how these two concepts balance competing needs when there are multiple study aims, a common situation in implementation research.

Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research.

Purposeful sampling is widely used in qualitative research for the identification and selection of information-rich cases related to the phenomenon of interest. Although there are several different purposeful sampling strategies, criterion sampling appears to be used most commonly in implementation research. However, combining sampling strategies may be more appropriate to the aims of implementation research and more consistent with recent developments in quantitative methods. This paper reviews the principles and practice of purposeful sampling in implementation research, summarizes types and categories of purposeful sampling strategies and provides a set of recommendations for use of single strategy or multistage strategy designs, particularly for state implementation research.

Approaches to Mixed Methods Dissemination and Implementation Research: Methods, Strengths, Caveats, and Opportunities.

Limited translation of research into practice has prompted study of diffusion and implementation, and development of effective methods of encouraging adoption, dissemination and implementation. Mixed methods techniques offer approaches for assessing and addressing processes affecting implementation of evidence-based interventions. We describe common mixed methods approaches used in dissemination and implementation research, discuss strengths and limitations of mixed methods approaches to data collection, and suggest promising methods not yet widely used in implementation research. We review qualitative, quantitative, and hybrid approaches to mixed methods dissemination and implementation studies, and describe methods for integrating multiple methods to increase depth of understanding while improving reliability and validity of findings.

Integrating Science and Engineering to Implement Evidence-Based Practices in Health Care Settings.

Integrating two distinct and complementary paradigms, science and engineering, may produce more effective outcomes for the implementation of evidence-based practices in health care settings. Science formalizes and tests innovations, whereas engineering customizes and optimizes how the innovation is applied tailoring to accommodate local conditions. Together they may accelerate the creation of an evidence-based healthcare system that works effectively in specific health care settings. We give examples of applying engineering methods for better quality, more efficient, and safer implementation of clinical practices, medical devices, and health services systems. A specific example was applying systems engineering design that orchestrated people, process, data, decision-making, and communication through a technology application to implement evidence-based depression care among low-income patients with diabetes. We recommend that leading journals recognize the fundamental role of engineering in implementation research, to improve understanding of design elements that create a better fit between program elements and local context.

Design of implementation studies for quality improvement programs: an effectiveness-cost-effectiveness framework.

Translational research applies basic science discoveries in clinical and community settings. Implementation research is often limited by tremendous variability among settings; therefore, generalization of findings may be limited. Adoption of a novel procedure in a community practice is usually a local decision guided by setting-specific knowledge. The conventional statistical framework that aims to produce generalizable knowledge is inappropriate for local quality improvement investigations. We propose an analytic framework based on cost-effectiveness of the implementation study design, taking into account prior knowledge from local experts. When prior knowledge does not indicate a clear preference between the new and standard procedures, local investigation should guide the choice. The proposed approach requires substantially smaller sample sizes than the conventional approach. Sample size formulae and general guidance are provided.

Cumulative sojourn time in longitudinal studies: a sequential imputation method to handle missing health state data due to dropout.

Missing data are ubiquitous in longitudinal studies. In this paper, we propose an imputation procedure to handle dropouts in longitudinal studies. By taking advantage of the monotone missing pattern resulting from dropouts, our imputation procedure can be carried out sequentially, which substantially reduces the computation complexity. In addition, at each step of the sequential imputation, we set up a model selection mechanism that chooses between a parametric model and a nonparametric model to impute eachmissing observation. Unlike usual model selection procedures that aim at finding a single model fitting the entire data set well, our model selection procedure is customized to find a suitable model for the prediction of each missing observation.

Endorsement of compulsory HIV vaccination policy among populations at high risk of HIV exposure (LA VOICES).

Compulsory vaccination is a frequently implemented policy option for ensuring comprehensive vaccine coverage. Ongoing controversies around human papillomavirus vaccine dissemination, and suboptimal coverage, suggest the value of assessing acceptability of compulsory vaccinations-particularly among likely target populations-in advance of their public availability to support evidence-informed interventions. With the first HIV vaccine to demonstrate partial efficacy in a large-scale clinical trial, we examined individual characteristics and attitudes associated with support for compulsory HIV vaccination policy among a diverse, representative sample of adults attending probable HIV vaccine dissemination venues in a large urban county. Participants were recruited using three-stage probability sampling from likely venues for future HIV vaccine dissemination. We used Audio-CASI to administer a 60-min structured questionnaire. Items included endorsement of compulsory HIV vaccination policy, sociodemographic characteristics, injecting drug use, vaccine attitudes and perceived HIV risk. Among 1,225 participants (mean age = 36.8 years; 55.6 % males, 37.6 % non-English speaking Hispanic, 78.8 % heterosexual, 25.7 % injection drug users), almost half (48.2 %) endorsed a compulsory HIV vaccination policy. Non-English speaking Hispanics compared to whites, participants with less than high school education, higher positive vaccine attitude scores and higher perceived HIV risk were significantly more likely, and people who inject drugs significantly less likely to endorse compulsory HIV vaccination. Public health interventions to promote positive vaccine attitudes and accurate perceptions of HIV risk among vulnerable populations, and strategies tailored for people who inject drugs, may build support for compulsory HIV vaccination policy and promote broad HIV vaccine coverage.

Optimal strategies to improve uptake of and adherence to HIV prevention among young people at risk for HIV acquisition in the USA (ATN 149): a randomised, controlled, factorial trial.

BACKGROUND: Pre-exposure prophylaxis (PrEP), condom use, post-exposure prophylaxis (PEP), and sexual partner reduction help to prevent HIV acquisition but have low uptake among young people. We aimed to assess the efficacy of automated text messaging and monitoring, online peer support, and strengths-based telehealth coaching to improve uptake of and adherence to PrEP, condom use, and PEP among adolescents aged 12-24 years at risk of HIV acquisition in Los Angeles, CA, USA, and New Orleans, LA, USA. METHODS: We conducted a four-arm randomised controlled factorial trial, assessing interventions designed to support uptake and adherence of HIV prevention options (ie, PrEP, PEP, condom use, and sexual partner reduction). We recruited young people aged 12-24 years who were at risk of HIV acquisition from 13 community-based organisations, adolescent medicine clinics, and organisations serving people who are unstably housed, people who were previously incarcerated, and other vulnerable young people, and through dating apps, peer referrals, and social venues and events in Los Angeles, CA, USA, and New Orleans, LA, USA. Young people who tested seronegative and reported being gay, bisexual, or other men who have sex with men, transgender men or women, or gender diverse (eg. non-binary or genderqueer) were eligible for inclusion. Participants were randomly assigned to one of four intervention groups in a factorial design: automated text messaging and monitoring (AMMI) only, AMMI plus peer support via private social media, AMMI plus strengths-based telehealth coaching by near-peer paraprofessionals, or AMMI plus peer support and coaching. Assignment was further stratified by race or ethnicity and sexual orientation within each interviewer's group of participants. Participants were masked to intervention assignment until after baseline interviews when offered their randomly assigned intervention, and interviewers were masked throughout the study. Interventions were available throughout the 24-month follow-up period, and participants completed baseline and follow-up assessments, including rapid diagnostic tests for sexually transmitted infections, HIV, and substance use, at 4-month intervals over 24 months. The primary outcomes were uptake and adherence to HIV prevention options over 24 months, measured by self-reported PrEP use and adherence, consistent condom use with all partners, PEP prescription and adherence, and number of sexual partners in participants with at least one follow-up. We used Bayesian generalised linear modelling to assess changes in outcomes over time comparing the four study groups. This study is registered with ClinicalTrials.gov (NCT03134833) and is completed. FINDINGS: We screened 2314 adolescents beginning May 1, 2017, to enrol 1037 participants (45%) aged 16-24 years between May 6, 2017, and Aug 30, 2019, of whom 895 (86%) had follow-up assessments and were included in the analytical sample (313 assigned to AMMI only, 205 assigned to AMMI plus peer support, 196 assigned to AMMI plus coaching, and 181 assigned to AMMI plus peer support and coaching). Follow-up was completed on Nov 8, 2021. Participants were diverse in race and ethnicity (362 [40%] Black or African American, 257 [29%] Latinx or Hispanic, 184 [21%] White, and 53 [6%] Asian or Pacific Islander) and other sociodemographic factors. At baseline, 591 (66%) participants reported anal sex without a condom in the past 12 months. PrEP use matched that in young people nationally, with 101 (11%) participants reporting current PrEP use at baseline, increasing at 4 months to 132 (15%) and continuing to increase in the AMMI plus peer support and coaching group (odds ratio 2·31, 95% CI 1·28-4·14 vs AMMI control). There was no evidence for intervention effect on condom use, PEP use (ie, prescription or adherence), PrEP adherence, or sexual partner numbers. No unanticipated or study-related adverse events occurred. INTERPRETATION: Results are consistent with hypothesised synergistic intervention effects of evidence-based functions of informational, motivational, and reminder messaging; peer support for HIV prevention; and strengths-based, goal-focused, and problem-solving telehealth coaching delivered by near-peer paraprofessionals. These core functions could be flexibly scaled via combinations of technology platforms and front-line or telehealth HIV prevention workers. FUNDING: Adolescent Medicine Trials Network for HIV/AIDS Interventions, US National Institutes of Health.

Effects of disease misclassification on exposure-disease association.

OBJECTIVES: We explore how misclassification in disease status can distort the exposure-disease association in a study with dichotomous disease and exposure status. METHODS: We define the difference in population odds ratios between populations with and without disease misclassification as population-level bias and derive the bias as a function of sensitivity and specificity for observed disease status. The magnitude and direction of bias can be elucidated through analytic derivations, as illustrated with numerical examples. RESULTS: Patterns of bias exist not only for nondifferential misclassification but also for some differential misclassification scenarios. We have provided conditions defined in terms of sensitivity and specificity that correspond to each pattern of bias. CONCLUSIONS: Caution is needed in interpreting results when misclassification is present. Our findings can be used to assess the effects of disease misclassification in a population when sensitivity and specificity are known or can be estimated.

GAP-REACH: a checklist to assess comprehensive reporting of race, ethnicity, and culture in psychiatric publications.

Growing awareness of health and health care disparities highlights the importance of including information about race, ethnicity, and culture (REC) in health research. Reporting of REC factors in research publications, however, is notoriously imprecise and unsystematic. This article describes the development of a checklist to assess the comprehensiveness and the applicability of REC factor reporting in psychiatric research publications. The 16-item GAP-REACH checklist was developed through a rigorous process of expert consensus, empirical content analysis in a sample of publications (N = 1205), and interrater reliability (IRR) assessment (N = 30). The items assess each section in the conventional structure of a health research article. Data from the assessment may be considered on an item-by-item basis or as a total score ranging from 0% to 100%. The final checklist has excellent IRR (κ = 0.91). The GAP-REACH may be used by multiple research stakeholders to assess the scope of REC reporting in a research article.

Does haste make waste? Prevalence and types of errors reported after publication of studies of COVID-19 therapeutics.

BACKGROUND: The COVID-19 pandemic spurred publication of a rapid proliferation of studies on potential therapeutic agents. While important for the advancement of clinical care, pressure to collect, analyze, and report data in an expedited manner could potentially increase the rate of important errors, some of which would be captured in published errata. We hypothesized that COVID-19 therapeutic studies published in the early years of the pandemic would be associated with a high rate of published errata and that, within these errata, there would be a high prevalence of serious errors. METHODS: We performed a review of published errata associated with empirical studies of COVID-19 treatments. Errata were identified via a MEDLINE and Embase search spanning January 2020 through September 2022. Errors located within each published erratum were characterized by location within publication, error type, and error seriousness. RESULTS: Of 47 studies on COVID-19 treatments with published errata, 18 met inclusion criteria. Median time from publication of the original article to publication of the associated erratum was 76 days (range, 12-511 days). A majority of errata addressed issues with author attribution or conflict of interest disclosures (39.5%) or numerical results (25.6%). Only one erratum contained a serious error: a typographical error which could have misled readers into believing that the treatment in question had serious adverse effects when in fact it did not. CONCLUSIONS: Despite accelerated publication times, we found among studies of COVID-19 treatments the majority of errata (17/18) reported minor errors that did not lead to misinterpretation of the study results. Retractions, an indicator of scientific misdirection even more concerning than errata, were beyond the scope of this review.

Designing a pilot sequential multiple assignment randomized trial for developing an adaptive treatment strategy.

There is growing interest in how best to adapt and readapt treatments to individuals to maximize clinical benefit. In response, adaptive treatment strategies (ATS), which operationalize adaptive, sequential clinical decision making, have been developed. From a patient's perspective an ATS is a sequence of treatments, each individualized to the patient's evolving health status. From a clinician's perspective, an ATS is a sequence of decision rules that input the patient's current health status and output the next recommended treatment. Sequential multiple assignment randomized trials (SMART) have been developed to address the sequencing questions that arise in the development of ATSs, but SMARTs are relatively new in clinical research. This article provides an introduction to ATSs and SMART designs. This article also discusses the design of SMART pilot studies to address feasibility concerns, and to prepare investigators for a full-scale SMART. We consider an example SMART for the development of an ATS in the treatment of pediatric generalized anxiety disorders. Using the example SMART, we identify and discuss design issues unique to SMARTs that are best addressed in an external pilot study prior to the full-scale SMART. We also address the question of how many participants are needed in a SMART pilot study. A properly executed pilot study can be used to effectively address concerns about acceptability and feasibility in preparation for (that is, prior to) executing a full-scale SMART.

The bereavement exclusion and DSM-5.

BACKGROUND: Pre-DSM-III (where DSM is Diagnostic and Statistical Manual), a series of studies demonstrated that major depressive syndromes were common after bereavement and that these syndromes often were transient, not requiring treatment. Largely on the basis of these studies, a decision was made to exclude the diagnosis of a major depressive episode (MDE) if symptoms could be "better accounted for by bereavement than by MDE" unless symptoms were severe and very impairing. Thus, since the publication of DSM-III in 1980, the official position of American Psychiatry has been that recent bereavement may be an exclusion criterion for the diagnosis of an MDE. This review article attempts to answer the question, "Does the best available research favor continuing the 'bereavement exclusion' (BE) in DSM-5?" We have previously discussed the proposal by the DSM-5 Mood Disorders Work Group to remove the BE from DSM-5. METHODS: Prior reviews have evaluated the validity of the BE based on studies published through 2006. The current review adds research studies published since 2006 and critically examines arguments for and against retaining the BE in DSM-5. RESULTS: The preponderance of data suggests that bereavement-related depression is not different from MDE that presents in any other context; it is equally genetically influenced, most likely to occur in individuals with past personal and family histories of MDE, has similar personality characteristics and patterns of comorbidity, is as likely to be chronic and/or recurrent, and responds to antidepressant medications. CONCLUSIONS: We conclude that the BE should not be retained in DSM-5.