Factors Associated with Suicidal Thought and Help-Seeking Behaviour in Transition-Aged Youth versus Adults
Bibliographic record
Abstract
OBJECTIVE: Suicide is a leading cause of death for transition-aged youth (TAY), and yet few studies examine correlates of suicidal ideation specifically in this age demographic (age 18-24 years). The transition to adulthood is a unique context, marked by novel stressors (e.g., joining the workforce) and increased independence, which may influence risk factors for suicidal ideation. This study examined correlates of suicidal ideation in TAY and adults and contrasted profiles across age. METHODS: We used 4 biannual cycles (2005, 2007, 2009, 2011) of the Canadian Community Health Survey, a population-based cross-sectional survey on health. We used logistic regression to assess the association between suicidal ideation and depression, distress, alcohol use, smoking, exercise, sedentary behaviour, chronic illness, restrictions to daily living, perceived physical and mental health, and perceived social support independently in both TAY ( n = 4427) and adults ( n = 14,452). We subsequently assessed possible interactions with age (18-24 v. 25-44 years) and sex and differences in help-seeking behaviour in a combined model. RESULT: TAY exhibited higher rates of suicidal ideation than adults did ( P < 0.001). Numerous factors were associated with suicidal ideation in TAY. Notably, alcohol abstinence was associated with decreased suicidal ideation in TAY but not for adults. Moreover, when depressed, TAY were significantly less likely to have received professional mental health help than adults (odds ratio = 0.64, 95% CI, 0.43 to 0.94). CONCLUSIONS: Suicidal ideation is more prevalent in TAY than adults, and its consequences may be aggravated by poor treatment-seeking behaviour in at-risk (i.e. depressed) individuals. These different risk profiles substantiate the recent shift toward clinical interventions focusing on transition-aged youth, rather than traditional child (<18 years) and adult (>18 years) services.
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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 | 0.001 |
| 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".