Associations of School Connectedness with Adolescent Suicidality: Gender Differences and the Role of Risk of Depression
Bibliographic record
Abstract
OBJECTIVE: Previous studies have not examined associations of school connectedness with adolescent suicidal behaviours stratified by gender, while including a measure of depression. We analyzed survey data to determine whether there are independent protective associations of higher school connectedness with suicidal behaviours in Canadian adolescents, while controlling for potential confounders, including risk of depression; and whether such associations differ by gender. METHOD: Using data from a stratified cluster sample of randomly selected classes of students in schools in 3 of Canada's Atlantic provinces, we used multiple logistic regression to examine whether associations of risk of depression, measured using the 12-item Center for Epidemiologic Studies-Depression scale, lessened protective associations of higher school connectedness with suicidal behaviours in grades 10 and 12 students, while stratifying by gender. RESULTS: After adjusting for risk of depression, higher school connectedness was independently associated with decreased suicidal ideation in both genders and with suicidal attempt in females. In males, higher connectedness was no longer protective for suicide attempt when risk of depression was included in the model. CONCLUSIONS: School connectedness, which is felt to have positive influences on many types of adolescent behaviour, appears to also be both directly and indirectly protective for suicidality. These effects may occur through different pathways in females and males. Given the protection it offers both genders, including those at risk and not at risk of depression, increasing school connectedness should be considered as a universal adolescent mental health strategy. Studies that examine school connectedness should include analyses that examine potential differences between males and females.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".