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Record W4408745551 · doi:10.1136/bmjopen-2024-095573

Suicidal behaviours and associated factors among Bangladeshi medical students: a systematic review and meta-analysis (2000–2024)

2025· review· en· W4408745551 on OpenAlexfundno aff
Mantaka Rahman, M H M Imrul Kabir, Sharmin Sultana, Ibtisam Abdullah, Afroza Tamanna Shimu

Bibliographic record

VenueBMJ Open · 2025
Typereview
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
FundersWomen's College HospitalTrent UniversityNottingham Trent University
KeywordsSuicidal ideationMedicineMeta-analysisPsycINFOSystematic reviewCritical appraisalMEDLINEObservational studyPoison controlPsychiatrySuicide preventionFamily medicineClinical psychologyAlternative medicineEnvironmental healthPathology

Abstract

fetched live from OpenAlex

Objectives Suicidal behaviours are common among medical students, and the prevalence might vary across various regions. Even though various systematic reviews have been conducted to assess the suicidal behaviours among medical students in general, no review has ever explored or carried out a sub-analysis to show the burden of suicidal behaviours among Bangladeshi medical students. Design This is a systematic review and meta-analysis of prevalence studies among Bangladeshi medical students. The review applied truncated and phrase-searched keywords and relevant subject headings for study identification using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Data sources PubMed (Medline), Scopus, PsycINFO and Google Scholar databases were searched between January 2000 and May 2024. Eligibility criteria for selecting studies The designed study included cross-sectional, case series, case reports and cohort studies of Bangladeshi medical students reporting suicidal behaviours (suicidal ideation, suicidal planning or suicidal attempts). Only freely accessible, full-text articles in English were included for analysis. Data extraction and synthesis Study screening, data extraction and methodological assessment were performed by two independent reviewers. Risk of bias was assessed using the Joanna Briggs Institute critical appraisal tool. A random-effects meta-analysis model was conducted to pool prevalence rates, complemented by narrative synthesis. Heterogeneity was assessed using the I 2 statistic. Results Data were obtained from 6 eligible studies, including 1625 medical students (691 male) of Bangladesh. The pooled prevalence of lifetime suicidal behaviours was 25%, for suicidal ideation (95% CI: 14% - 37%, I 2 =91%; p<0.01), 6% for suicidal plan (95% CI: 2% - 12%, I 2 =91%; p<0.01), and 8% for suicidal attempt (95% CI: 1% - 17%, I 2 =96%; p<0.01). The factors associated with suicidal ideation were female gender, depression, familial suicidal history and drug addiction. Only depression and drug addiction were significantly associated with suicidal attempts, while hanging was the most attempted method. Conclusions Suicidal behaviours particularly, suicidal ideation, are high among Bangladeshi medical students. However, very few studies were done in this country to quantify the burden and its associated factors. PROSPERO registration number CDR 42023493595.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.045
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0160.038
Bibliometrics0.0130.011
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
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 head0.281
GPT teacher head0.585
Teacher spread0.305 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations9
Published2025
Admission routes1
Has abstractyes

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