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E-ISSN : 2733-4538
The current study was conducted to examine the applicability of the complete mental health model proposed by Keyes for explaining the relationship between mental health and suicidal behavior in the elderly. We examined the unique contribution of mental well-being to the prediction of suicidal behavior and the differences of categorical mental health diagnoses in terms of suicidal behavior. A total of 2,034 elderly people aged 65 years and over participated in this study. Hierarchical multiple regression analyses showed that mental well-being was a significant predictor of suicidal behavior after controlling for education, living arrangement, poverty, physical illness, and depressive symptoms. In addition, education, poverty, physical illness, and depression each contributed significantly to suicidal behavior after controlling for all other relevant predictors, and depression was the strongest predictor of suicidal behavior. While poverty and depression were significant predictors of suicidal behavior in men, mental well-being, physical illness, and depression were significant predictors of suicidal behavior in women. Next, comparisons of three categorical mental health diagnoses based on mental well-being indicated that the languishing group was more vulnerable to suicidal behavior than the moderately mentally healthy group, who in turn was more vulnerable to suicidal behavior than the flourishing group. Comparisons of five categorical mental health diagnoses based on the combination of mental well-being and depression indicated that the languishing and depression group was the most vulnerable to suicidal behavior and the complete mental health group was the least vulnerable to suicidal behavior of all groups. In conclusion, these results suggest that mental well-being may act as a protective factor for alleviating suicidal behavior, and provide support for the applicability of the complete mental health model for explaining the relationship between mental health and suicidal behavior in the elderly.
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