Low physical activity and high sedentary behaviour are associated with adolescents’ suicidal vulnerability: Evidence from 52 low‐ and middle‐income countries
Bibliographic record
Abstract
AIM: To examine the relationships of physical activity (PA) and sedentary behaviour (SB) with suicidal thoughts and behaviour among adolescents in low- and middle-income countries (LMICs). METHODS: Global School-based Student Health Survey data from 206 357 students (14.6 ± 1.18 years; 51% female) in 52 LMICs were used. Students reported on suicidal ideation, suicide planning, suicide attempts, PA, leisure-time SB and socio-demographic characteristics. Multilevel mixed-effects generalised linear modelling was used to examine the associations. RESULTS: High leisure-time SB (≥3 hours/day) was independently associated with higher odds of suicidal ideation, suicide planning and suicide attempts for both male and female adolescents. Insufficient PA (<60 mins/day) was not associated with higher odds of ideation for either sex; however, it was associated with planning and attempts for male adolescents. The combination of insufficient PA and high SB, compared with sufficient PA and low SB, was associated with higher odds of suicidal ideation and suicide planning for both male and female adolescents, and suicide attempts for male adolescents. CONCLUSION: High SB may be an indicator of suicidal vulnerability among adolescents in LMICs. Low PA may be a more important risk for suicidal thoughts and behaviours among male, than female, adolescents. Promoting active lifestyle should be integrated into suicide prevention programmes in resource-poor settings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".