Protective Factors against Self-Harm and Suicidality among Australian Indigenous Adolescents: A Strengths-Based Analysis of the Longitudinal Study of Indigenous Children
Bibliographic record
Abstract
Background: Understanding and encouraging social and emotional well-being (SEWB) among Indigenous adolescents is vital in countering the impacts of colonisation and intergenerational trauma. As self-harm and suicidality are considered markers of poor SEWB among Indigenous communities, we aimed to identify the individual-level and community-level factors protecting Indigenous adolescents from self-harm and suicidality. Methods: Data came from Footprints in Time—The Longitudinal Study of Indigenous Children (waves 10 and 11), conducted among Indigenous families across Australia. A strengths-based analysis fitted multilevel logistic regression to explore associations with factors proposed as protective against self-reported self-harm and suicidality among Indigenous adolescents. Results: Our study cohort included 365 adolescents with complete data for the variables of interest. Adolescents had a mean (SD) age of 14.04 (0.45) years and a sex ratio of almost 1:1, and most were attending school (96.2%). Previous self-harm was reported by 8.2% (n = 30); previous suicidality was reported by 4.1% (n = 15). Individual-level factors protecting against self-harm and suicidality were being male, living in a cohesive family, and having low total Strengths and Difficulty Questionnaire scores (p < 0.05 for all). Residing in major cities compared with regional/remote areas was protective against self-harm (OR 5.94, 95% CI 1.31−26.81). Strong cultural identity was not found to be a protective factor against self-harm and/or suicidality in the sample. Conclusions: This study identified key individual- and community-level factors that can protect Australian Indigenous adolescents against self-harm and suicidality, particularly family cohesion. Identifying strengths for this at-risk population can inform prevention strategies, particularly for rural living adolescents with high distress.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".