Document Type

Thesis

Degree Name

Master of Arts (MA)

Department

Psychology

Program Name/Specialization

Social Psychology

Faculty/School

Faculty of Science

First Advisor

Dr. Pamela Sadler

Advisor Role

Advisor

Abstract

In three studies, this research describes the development and potential application of a new self-report measure, the Interpersonal Self-Talk Scale (IPSTS). Based on Kiesler’s (1983) Interpersonal Circle: Acts Version, and the Revised Interpersonal Adjective Scales (IAS-R; Wiggins et al., 1988) the IPSTS was designed to measure the distinct interpersonal qualities of self-talk. In Study 1 (N = 316), a principal components analysis of the IPSTS items yielded two underlying dimensions of dominance and affiliation. The preliminary octant subscales displayed good internal consistency reliability and circumplex structure, and the IPSTS was shown to measure a construct that is reasonably distinct from interpersonal style, interpersonal behaviors, values, efficacies, and problems. In addition, the moderate correlations between the affiliative dimension of the IPSTS and measures of self-compassion (Neff, 2003) and self-criticism (Gilbert et al., 2004) suggest that affiliative self-talk is common to these self-relationships. In Study 2 (N = 300), the psychometric properties of the IPSTS, along with its relationships with other measures, replicated well, resulting in the final, 49-item measure. Given that self-talk is a vital aspect of people’s ability to cope with challenges (Rogelberg et al., 2012), Study 3 (N = 33) assessed how well people’s typical trait self-talk (as measured by the IPSTS) predicted their self-talk style and their mood in a challenging situation. Although the results suggested limited relationships between trait self-talk and state self-talk, trait self-talk style may contribute to maintaining positive affect and preventing negative affect when coping with challenges. Limitations of the research and implications for the IPSTS are discussed.

Convocation Year

2015

Convocation Season

Fall

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