The Anatomy of Rural-Urban Youth Suicidal Ideation – Who is at Greatest Risk. What Factors to Target. How to Intervene.
Why this work is in the frame
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Bibliographic record
Abstract
Suicide embodies a considerable but often preventable loss of life. As the second leading cause of death for young people in Canada between the ages of 15 and 24, nearly one-quarter of all annual deaths for this age group are accounted for by those who have died by suicide. Greater still is the prevalence of suicidal behaviour. Annually, suicide and suicidal behaviours across the age span are estimated to cost the Canadian economy $2.2 billion. Given the high personal costs to victims, survivors, and taxpayers, it seems crucial that prevention strategies be implemented to reduce the high rate of suicide and suicidal behaviours, as well as to promote mental health, particularly in youth. The promotion of positive mental health and well-being is especially relevant for youth living in rural areas. Fewer mental health resources are available in rural communities than in urban centres. Moreover, youth living in rural, low population density areas often do not believe that their anonymity and right to privacy would be protected if they were to seek mental health services. The present research was carried out to provide a potential foundation for stimulating mental health promotion and suicide prevention approaches, differing by rural and urban community and by gender, before such concerns emerge. Through a survey of 813 (459 rural youth; 354 urban youth) secondary school youth in Eastern Ontario, we examined the inverse association between suicidal ideation and engagement in extracurricular activities, such as sports, music, drama, or community groups. Who is at greatest risk: It was found that rural youth reported significantly more suicidal thoughts than did urban youth (p < .01). Perceived social support accounted for rural and urban differences, while difficulties coping with daily stressors accounted for gender differences, in self-reported suicidal ideation. Thus, “red flags” for communities at risk could include perceived deficits in social support within a given community, as well as having a number of young females who indicate poor coping with daily stressors. What factors to target: Depressive symptoms, risk behaviours, self-esteem, and social support differed in importance in the prediction of suicidal ideation based on rural-urban setting and gender. Results reflecting differences underscore the importance of examining such factors in mental health research. A “one size fits all” approach to youth mental health promotion and suicide prevention does not appear to be a prudent strategy. How to intervene: Youth engagement was explored as one possible means of intervention. In rural youth, personally meaningful engagement and engagement in a number of activities was directly inversely related to suicidal ideation. Regression analyses involving interaction analyses were carried out with youth engagement as a moderator for mental health indicators such as depressive symptoms, risk behaviours, self-esteem, and social support in the prediction of suicidal ideation. Through simple slope analyses, it was found that youth engagement significantly reduces the relationships between suicidal ideation and mental health indicators, particularly for males (p < .001). Therefore, youth engagement appears to be more universally beneficial for rural youth, given that rural dwelling appears to be a risk factor for suicidal ideation. Moreover, for male youth at risk for suicidal ideation, given depressive symptoms, risk behaviours, low self-esteem, and low perceived social support, youth engagement may be of particular benefit. With knowledge of who is at greatest risk for suicidal ideation, what factors to target, and a possible intervention road map, we can reach youth and foster resiliency before suicidal thoughts emerge.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it