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An improved method for counting stressful life events (SLEs) when predicting mental health and wellness.
Psychology & Health 2018 October 9
OBJECTIVE: Checklists for registering stressful life events (SLEs) generally correlate negatively, but weakly, with mental health outcome measures. Thus, the present study examined various methodological approaches for improving these relationships.
DESIGN: A total of 1679 participants (women = 943, men = 736, M age-39.8) were randomly drawn from the general Norwegian population (response rate 34%). This prospective cohort study included two follow-ups at 10 (n = 1181) and 23 months (n = 942).
MAIN OUTCOME MEASURES: Satisfaction with life and absence of psychological distress (i.e. anxiety and depression) represented a joint measure for indexing 'mental wellness' (MW).
RESULTS: A simple count of SLEs weakly predicted MW, as expected, whereas the addition of a moderator (i.e. manageability of the event) substantially improved predictive power. Four additional moderators were examined: duration, impact, help-seeking and time since onset, but these were non-significant after inserting manageability into the model. This SLE counting method also retained its predictive power after including multiple criterion-related variables that substantially adjusted the longitudinal statistical model.
CONCLUSION: This new SLE counting method exhibited a considerable improvement to predicting mental health and well-being. It is well suited for use in epidemiological research requiring a short SLE checklist format with high predictive power.
DESIGN: A total of 1679 participants (women = 943, men = 736, M age-39.8) were randomly drawn from the general Norwegian population (response rate 34%). This prospective cohort study included two follow-ups at 10 (n = 1181) and 23 months (n = 942).
MAIN OUTCOME MEASURES: Satisfaction with life and absence of psychological distress (i.e. anxiety and depression) represented a joint measure for indexing 'mental wellness' (MW).
RESULTS: A simple count of SLEs weakly predicted MW, as expected, whereas the addition of a moderator (i.e. manageability of the event) substantially improved predictive power. Four additional moderators were examined: duration, impact, help-seeking and time since onset, but these were non-significant after inserting manageability into the model. This SLE counting method also retained its predictive power after including multiple criterion-related variables that substantially adjusted the longitudinal statistical model.
CONCLUSION: This new SLE counting method exhibited a considerable improvement to predicting mental health and well-being. It is well suited for use in epidemiological research requiring a short SLE checklist format with high predictive power.
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