Risk and Protective Factors for Suicide Attempt Among Indigenous Māori Youth in New Zealand: The Role of Family Connection
Bibliographic record
Abstract
The purpose of this study was to (1) describe risk and protective factors associated with a suicide attempt for Māori youth and (2) explore whether family connection moderates the relationship between depressive symptoms and suicide attempts for Māori youth. Secondary analysis was conducted with 1702 Māori young people aged 12–18 years from an anonymous representative national school-based survey of New Zealand (NZ) youth in 2001. A logistic regression and a multivariable model were developed to identify risk and protective factors associated with suicide attempt. An interaction term was used to identify whether family connection acts as a moderator between depressive symptoms and a suicide attempt. Risk factors from the logistic regression for a suicide attempt in the past year were depressive symptoms (OR = 4.3, p < 0.0001), having a close friend or family member commit suicide (OR = 4.2, p < 0.0001), being 12–15 years old (reference group: 16–18 years) (OR = 2.7, p < 0.0001), having anxiety symptoms (OR = 2.3, p = 0.0073), witnessing an adult hit another adult or a child in the home (OR = 1.8, p = 0.001), and being uncomfortable in NZ European social surroundings (OR = 1.7, p = 0.0040). Family connection was associated with fewer suicide attempts (OR = 0.9, p = 0.0002), but this factor did not moderate the relationship between depressive symptoms and suicide attempt (χ2 = 2.84, df = 1, p = 0.09). Family connection acts as a compensatory mechanism to reduce the risk of suicide attempts for Māori students with depressive symptoms, not as a moderating variable.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".