Self-Role Integration: A Person-Specific Predictor of Life Satisfaction and Prosocial Behavior

Abstract

We investigated whether a novel self-structural variable, self-role integration, incrementally predicts life satisfaction and prosocial behavior beyond dispositional trait predictors that are known from prior research to be linked to these outcomes. At Time 1, 223 participants (171 female) completed measures of life satisfaction, optimism, the Big Five personality traits, reward and punishment sensitivity (BIS/BAS), psychological distress, and prosocial behavior. They then completed an idiographic measure in which they selected from a list of trait terms to describe their actual self and a series of role-specific identities. At Time 2 (60 days later, N = 134), they again reported prosocial behavior. Self-role integration was computed from the linkages between actual self and role-identities derived from a Hierarchical Classes (HICLAS) analysis of each participant’s self-descriptive data. Self-role integration concurrently and prospectively predictive of prosocial behavior beyond significant trait-level predictors, and was marginally significantly correlated with life satisfaction beyond a set of trait-level predictors. Results demonstrate that a self-structural variable can add predictive utility to life satisfaction and prosocial behavior beyond dispositional traits.

Keywords:

• Measurement
• quality of life
• self-concept

Acknowledgments

The authors wish to acknowledge Joshua Wright, Ian Taras, and Helen Tan for their assistance in data collection.

Author Notes

Warren A. Reich is a social-personality psychologist at Hunter College in New York, NY.

Celeste Sangiorgio is a doctoral candidate in clinical psychology at St. John's University.

Jason Young is a social psychologist and Professor of Psychology at Hunter College in New York, NY.

Notes

1 Measures in the larger study included impulsivity, antisocial, and sex/drug risk behavior. None of these was correlated with the outcomes reported here but are available from the authors on request. All statistical analyses were performed using SPSS v.24. The structural analysis of self-descriptive data was modeled using the HICLAS software, which is available from the authors on request.

2 For exploratory purposes, we collected life satisfaction at Time 2 also. It was highly correlated with Time 1 life satisfaction, r = .77. All but one of the significant bivariate correlates were the same for Time 2 as for Time 1 life satisfaction, and none was significant after controlling for Time 1 life satisfaction. Since there was no reason to expect a 60-day change in life satisfaction, we do not report these results.

Additional information

Funding

This study was supported by PSC/CUNY Research Award 65445-00 43 to Warren A. Reich and Jason Young.