The Anatomy of Rural-Urban Youth Suicidal Ideation – Who is at Greatest Risk. What Factors to Target. How to Intervene.
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».