Antecedents, clinical and psychological characteristics of a large sample of individuals who have self-harmed recruited from primary care and hospital settings in Pakistan
Bibliographic record
Abstract
Background Suicide is one of the leading causes of mortality worldwide, and the majority of suicide deaths occur in low- and middle-income countries. Aims To evaluate the demographic and clinical characteristics of individuals who have presented to health services following self-harm in Pakistan. Method This study is a cross-sectional baseline analysis of participants from a large multicentre randomised controlled trial of self-harm prevention in Pakistan. A total of 901 participants with a history of self-harm were recruited from primary care clinics, emergency departments and general hospitals in five major cities in Pakistan. The Beck Scale for Suicide Ideation (BSI), Beck Depression Inventory (BDI), Beck Hopelessness Scale (BHS) and Suicide Attempt Self Injury Interview assessment scales were completed. Results Most participants recruited were females ( n = 544, 60.4%) in their 20s. Compared with males, females had lower educational attainment and higher unemployment rates and reported higher severity scores on BSI, BDI and BHS. Interpersonal conflict was the most frequently cited antecedent to self-harm, followed by financial difficulties in both community and hospital settings. Suicide was the most frequently reported motive of self-harm ( N = 776, 86.1%). Suicidal intent was proportionally higher in community-presenting patients (community: N = 318, 96.9% v. hospital: N = 458, 79.9%; P < 0.001). The most frequently reported methods of self-harm were ingestion of pesticides and toxic chemicals. Conclusions Young females are the dominant demographic group in this population and are more likely to attend community settings to seek help. Suicidal intent as the motivator of self-harm and use of potentially lethal methods may suggest that this population is at high risk of suicide.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".