Spirituality and Mental Well-Being in Combat Veterans: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Many veterans experience significant compromised spiritual and mental well-being. Despite effective and evidence-based treatments, veterans continue to experience poor completion rates and suboptimal therapeutic effects. Spirituality, whether expressed through religious or secular means, is a part of adjunctive or supplemental treatment modalities to treat post-traumatic stress disorder (PTSD) and is particularly relevant to combat trauma. The aim of this systematic review was to examine the relationship between spirituality and mental well-being in postdeployment veterans. METHODS: Electronic databases (MEDLINE, PsycINFO, CINAHL, Web of Science, JSTOR) were searched from database inception to March 2016. Gray literature was identified in databases, websites, and reference lists of included studies. Study quality was assessed using the Effective Public Health Practice Project Quality Assessment Tool and Critical Appraising Skill Programme Qualitative Checklist. RESULTS: From 6,555 abstracts, 43 studies were included. Study quality was low-moderate. Spirituality had an effect on PTSD, suicide, depression, anger and aggression, anxiety, quality of life, and other mental well-being outcomes for veterans. "Negative spiritual coping" was often associated with an increase mental health diagnoses and symptom severity; "positive spiritual coping" had an ameliorating effect. DISCUSSION: Addressing veterans' spiritual well-being should be a routine and integrated component of veterans' health, with regular assessment and treatment. This requires an interdisciplinary approach, including integrating chaplains postcombat, to help address these issues and enhance the continuity of care. Further high-quality research is needed to isolate the salient components of spirituality that are most harmful and helpful in veterans' mental well-being, including the incorporating of veterans' perspectives directly.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".