MétaCan
Menu
Back to cohort
Record W4296061600 · doi:10.3389/fpsyt.2022.978703

Prevalence of depression, anxiety and post-traumatic stress in war- and conflict-afflicted areas: A meta-analysis

2022· review· en· W4296061600 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Psychiatry · 2022
Typereview
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of TorontoBrain and Cognition Discovery FoundationUniversity Health Network
FundersInstitute for Health Innovation and Technology, National University of Singapore
KeywordsAnxietyDepression (economics)Traumatic stressPsycINFOMeta-analysisMedicinePopulationPsychiatryClinical psychologyMental healthMEDLINEInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Background With the rise of fragility, conflict and violence (FCV), understanding the prevalence and risk factors associated with mental disorders is beneficial to direct aid to vulnerable groups. To better understand mental disorders depending on the population and the timeframe, we performed a systematic review to investigate the aggregate prevalence of depression, anxiety and post-traumatic stress symptoms among both civilian and military population exposed to war. Methods We used MEDLINE (PubMed), Web of Science, PsycINFO, and Embase to identify studies published from inception or 1–Jan, 1945 (whichever earlier), to 31–May, 2022, to reporting on the prevalence of depression, anxiety and post-traumatic stress symptoms using structured clinical interviews and validated questionnaires as well as variables known to be associated with prevalence to perform meta-regression. We then used random-effects bivariate meta-analysis models to estimate the aggregate prevalence rate. Results The aggregate prevalence of depression, anxiety and post-traumatic stress during times of conflict or war were 28.9, 30.7, and 23.5%, respectively. Our results indicate a significant difference in the levels of depression and anxiety, but not post-traumatic stress, between the civilian group and the military group respectively (depression 34.7 vs 21.1%, p < 0.001; anxiety 38.6 vs 16.2%, p < 0.001; post-traumatic stress: 25.7 vs 21.3%, p = 0.256). The aggregate prevalence of depression during the wars was 38.7% (95% CI: 30.0–48.3, I 2 = 98.1%), while the aggregate prevalence of depression post-wars was 29.1% (95% CI: 24.7–33.9, I 2 = 99.2%). The aggregate prevalence of anxiety during the wars was 43.4% (95% CI: 27.5–60.7, I 2 = 98.6%), while the aggregate prevalence of anxiety post-wars was 30.3% (95% CI: 24.5–36.9, I 2 = 99.2%). The subgroup analysis showed significant difference in prevalence of depression, and anxiety between the civilians and military group ( p < 0.001). Conclusion The aggregate prevalence of depression, anxiety and post-traumatic stress in populations experiencing FCV are 28.9, 30.7, and 23.5%, respectively. There is a significant difference in prevalence of depression and anxiety between civilians and the military personnels. Our results show that there is a significant difference in the prevalence of depression and anxiety among individuals in areas affected by FCV during the wars compared to after the wars. Overall, these results highlight that mental health in times of conflict is a public health issue that cannot be ignored, and that appropriate aid made available to at risk populations can reduce the prevalence of psychiatric symptoms during time of FCV. Systematic Review Registration https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=337486 , Identifier 337486.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.399
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.090
GPT teacher head0.388
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it