Systematic Review of the Military Career Impact of Mental Health Evaluation and Treatment
Bibliographic record
Abstract
INTRODUCTION: Military leaders are concerned that active duty members' fear of career impact deters mental health (MH) treatment-seeking. To coalesce research on the actual and perceived consequences of MH treatment on service members' careers, this systematic review of literature on the U.S. Military since 2000 has been investigating the following three research questions: (1) is the manner in which U.S. active duty military members seek MH treatment associated with career-affecting recommendations from providers? (2) Does MH treatment-seeking in U.S. active duty military members impact military careers, compared with not seeking treatment? (3) Do U.S. active duty military members perceive that seeking MH treatment is associated with negative career impacts? MATERIALS AND METHODS: A search of academic databases for keywords "military 'career impact' 'mental health'" resulted in 653 studies, and an additional 51 additional studies were identified through other sources; 61 full-text articles were assessed for eligibility. A supplemental search in Medline, PsycInfo, and Google Scholar replacing "career impact" with "stigma" was also conducted; 54 articles (comprising 61 studies) met the inclusion criteria. RESULTS: As stipulated by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, studies were summarized on the population studied (U.S. Military Service[s]), sample used, intervention type, comparison group employed, outcome variables, and findings. Self-referred, compared with command-directed, service members appear to be less likely to face career-affecting provider recommendations in non-deployed and deployed settings although the data for the latter are not consistent. Of the two studies that tested if MH treatment actually negatively impacts military careers, results showed that those who sought treatment were more likely to be discharged although the casual nature of this relationship cannot be inferred from their design. Last, over one-third of all non-deployed service members, and over half of those who screened positive for psychiatric problems, believe that seeking MH treatments will harm their careers. CONCLUSIONS: Despite considerable efforts to destigmatize MH treatment-seeking, a substantial proportion of service members believe that seeking help will negatively impact their careers. On one hand, these perceptions are somewhat backed by reality, as seeking MH treatment is associated with a higher likelihood of being involuntarily discharged. On the other hand, correlational designs cannot establish causality. Variables that increase both treatment-seeking and discharge could include (1) adverse childhood experiences; (2) elevated psychological problems (including both [a] the often-screened depression, anxiety, and posttraumatic stress problems and [b] problems that can interfere with military service: personality disorders, psychotic disorders, and bipolar disorder, among others); (3) a history of aggressive or behavioral problems; and (4) alcohol use and abuse. In addition, most referrals are self-directed and do not result in any career-affecting provider recommendations. In conclusion, the essential question of this research area-"Does seeking MH treatment, compared with not seeking treatment, cause career harm?"-has not been addressed scientifically. At a minimum, longitudinal studies before treatment initiation are required, with multiple data collection waves comprising symptom measurement, treatment, and other services obtained, and a content-valid measure of career impact.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".