kers full-time or volunteer workers. The analysis of variance was used to test for differences between motivational groups within employment status categories on the demographic variables of personal income, age, educational level and number of children. In addition, the analysis of variance was used to test the attitude variables of satisfaction with employment status, marital happiness, general happiness, husband's attitude, satisfaction with family relationships and sex role attitude.
Based on the analyses of collected data, Gittman (1975) concluded that relationships existed between motivation for full time employment and general happiness, and between motivation for part-time employment and age of subject and number of children. In addition Gittman concluded that relationships existed between motivation for full-time homemaking and age of subject, number of children, satisfaction with employment status and husband's attitudes, and between motivation for volunteer work and satisfaction with family relationships. Regarding income, like several other studies, Gittman found a slightly positive correlation between income and general happiness.
Kammann (1982) investigated the efficacy of personal
circumstances and life events as predictors of happiness. In this regard, three studies were conducted to identify mental processes that give circumstances their favorable and unfavorable meanings. The first study examined the gap between aspiration and achieve-ment in terms of income, education, physical fitness, leisure, and friends. As expected, most people wanted to be better off than they were and believed that if they were better off they would be happier. The sum of the gap between what was and what was desired predicted their unhappiness.
The second study demonstrated that happy people have a stronger "Pollyannna effect" than unhappy people, i.e., they identified a larger group of positive associations in their lives. The thi...