Association between Health Risk Behavior and Suicidal Ideation, Continuous Sadness and Depression among Malaysian Youth
Bibliographic record
Abstract
BACKGROUND: Suicide is a global public health importance and a second leading cause of death in adolescents. It is more common among adolescents and is considered as a serious public health problem worldwide. This study aims to determine the association between health risk behavior with suicidal ideation, continuous sadness and depression among Malaysian youth.METHODS: A cross-sectional study was carried out among 4088 youth aged 13–17 years old from 50 selected schools. A stratified random sampling was used to select respondents from different classes. The students were randomly selected using the same software throughout the country. Verbal consent was obtained from the student and parents prior to data collection. A standardized self-administered questionnaire adapted from the United States’ Youth Behaviour Risk Surveillance Survey (YBRSS) were used.RESULTS: The rates of Continuous Sadness (CS), Depression (DP) and Suicidal Ideation (SI) were 34.3%, 13.2% and 7.9% respectively. The multivariable-adjusted odds ratio showed that sexual abuse was associated with SI 8.04 (95% CI: 4.66, 13.84), CS 5.72 (95% CI: 3.21, 9.82) and DP 4.68% (95% CI: 2.80, 7.83); alcohol use was associated with SI 1.62 (95% CI: 1.06, 2.47) and DP 1.67 (95% CI: 1.20, 2.33). Female was associated with all suicidal behaviours: SI 2.48 (95% CI: 1.90, 3.24), CS 2.07 (95% CI: 1.80, 2.37) and DP 1.41 (95% CI: 2.17, 1.71). Smoking and drug was not associated with CS, DP and SI.CONCLUSIONS: Given the well-founded concern of increasing risk of suicidal behaviour among youth, preventive efforts should adopt a more comprehensive approach in dealing with sexual abuse and alcohol abuse, especially in female.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".