The moderating effect of gender on the relationship between coping and suicide risk in a Portuguese community sample of adults

Abstract

Background and aims(s): The study evaluated the contribution of coping strategies, based on the Toulousiane conceptualization of coping, to the prediction of suicide risk and tested the moderating effect of gender, controlling for depressive symptoms.

Method: A two-time data collection design was used. A community sample of 195 adults (91 men and 104 women) ranging in age from 19 to 65 years and living in several Portuguese regions, mostly in Alentejo, participated in this research.

Results: Gender, depressive symptoms, control, and withdrawal and conversion significantly predicted suicide risk and gender interacted with control, withdrawal and conversion, and social distraction in the prediction of suicide risk. Coping predicted suicide risk only for women.

Conclusions: Results have important implications for assessment and intervention with suicide at-risk individuals. In particular,the evaluation and development of coping skills is indicated as a goal for therapists having suicide at-risk women as clients.

Keywords:

• coping
• gender
• interaction
• suicide risk
• community-based sample

Declaration of interest

The authors report that they have no conflicts of interest.

Notes

¹ The test of significance for the highest order product term in a multiple regression is equivalent to testing the increment in R² associated with adding that term in a hierarchical regression.

² Corroborating this perspective are the results of a principal components analysis that we performed as an ancillary analysis on the five coping scales. Based on the Kaiser criterion (eigenvalue >1) and parallel analysis, two higher order factors emerged representing a positive coping factor (scales of Social Support, Control, and Social Distraction) and a negative coping factor (scales of Withdrawal and Conversion, and Refusal). Confirmatory factor analysis using AMOS 21 software indicated that a two-factor model fit the data well (χ²/df = 2.66; GFI= 0.98; CFI= 0.95; SRMR= 0.050).