An analysis of the relationship of coping resources and social support to the experience of distress in single parent women

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Virginia Tech


Mental health research recognized that a subgroup of the general population at risk for emotional disturbance is that of single parent women. A volunteer sample of 248 women was accessed from women's support groups for this study.

The purpose of this research was to assess the extent to which the single parent woman experiences distress, and the relationship between this distress level and the coping resources the single parent woman possesses. The level of social support, both in family and work environments, was also assessed in its relationship to distress.

The cognitive, coping strengths of women were measured by the use of the three Cognitive Trait Scales (Pearlin and Schooler, (1978). Three Family Environment Scales and three Work Environment Scales (Moos, 1986) measured the degree of support the single parent woman maintains. All nine of these scales were used as independent measures. The Brief Symptom Inventory (Derogatis, 1975) was the dependent measure and assessed the degree of somatic distress phenomena experienced by the respondent.

Research questions asked (1) whether there were differences in the degree of distress experienced by single parent women based on their demographic factors; (2) what was the relationship between cognitive strengths/coping resources and the level of distress in the single mother; (3) what was the relationship of family and work support systems to the experience of distress in the single parent woman? To answer the first question, ANOVA correlation comparisons were made by demographic distinctions; the latter two questions were analyzed by multiple regression techniques.

The Cognitive Traits Scales yielded the most significant results in this study. The demographic factors of number of children under 18, number of adults in the household, income, and number of losses experienced by the parent yielded modest but significant contributions to the model.