Interpersonal Motives and Supportive Communication

Abstract

This study examined the relationship between individuals’ interpersonal communication motives and their self-reported use of social support behaviors. College students (N = 133) completed a questionnaire based on their communication with a friend. Parents (N = 119) completed a questionnaire based on their communication with one of their children. Parents higher in their affection and pleasure motives were more likely to provide emotional and social support. Friends higher in their affection, inclusion, and pleasure motives were more likely to provide emotional support. In both samples, individuals higher in their affection and control motives provided more advice support.

Keywords:

• Advice
• Emotional Support
• Friendship
• Interpersonal Motives
• Parent-Child
• Social Support

Notes

Note. Wilks's Λ = .58; F(18, 312) = 3.41, p < .001.

Note. Wilks's Λ = .43; F(18, 639) = 12.20, p < .001.

*p < .01.

A confirmatory factor analysis (CFA) was conducted on each measure. Criteria were adopted from Hu and Bentler (1999) and Browne and Cudeck (1993), who suggested that the nonnormed fit index (NFI) and comparative fit index (CFI) should be above .90 to indicate a reasonably good fit and the root mean square error of approximation (RMSEA) should be less than .05 to indicate a good fit or between .05 and .08 to indicate an acceptable fit. The support measure presented a significant chi-square test; degrees of freedom were approximately a 3:1 ratio, χ²(464, N = 252) = 1,424.016, p < .001. The model fit values were as follows: CFI = .76, NFI = .69, and RMSEA = .09, indicating a poor fit to the data. The interpersonal motives measure presented a significant chi-square test; degrees of freedom were approximately a 4:1 ratio, χ²(350, N = 252) = 1,390.22, p < .001. The model fit values were as follows: CFI = .71, NFI = .65, and RMSEA = .10, indicating a poor fit to the data. A closer examination of both the support and interpersonal model estimates indicated that the models could not be improved through item deletion. Previous studies utilizing these measures have not reported CFA findings. The CFA results indicate that, possibly, these measures warrant refinement.

Levine (2005; Levine, Hullett, Turner, & Lapinski, 2006) argued that all measures in every study should be tested by confirmatory factor analyses (CFAs), and that we can learn which measures are generalizable and which measures have problems. Further, one CFA result is not enough to invalidate a measure; but, if future studies fail to confirm the structure via CFAs, scrutiny of the measures would be warranted.

Additional information

Notes on contributors

Brandi N. Frisby

Brandi N. Frisby (PhD, West Virginia University, 2010) is an assistant professor in the Department of Communication at the University of Kentucky.

Matthew M. Martin

Matthew M. Martin (PhD, Kent State University, 1992) is a professor in the Department of Communication Studies at West Virginia University.