Conversation and Conformity Orientations as Predictors of Observed Conflict Tactics in Parent-Adolescent Discussions

Abstract

This research considers how observed tactics and patterns in parent-adolescent conflict relate to family orientations toward communication. Fifty families (mother, father, and mid-adolescent child) discussed family changes desired by each person. In high versus low conformity families, parents (fathers especially) pressured more, were more confrontational, and were less conciliatory, whereas children were less analytic and more apt to withdraw in response to parental demand. Fathers were especially conciliatory and analytic in families that combined high conversation orientation and low conformity (i.e., the pluralistic family type). The results confirm expected associations between family communication orientations and observed conflict patterns, suggesting that basic orientations to communication affect how families adapt to the communicative challenges of adolescence.

FUNDING

The research was assisted by a grant from the University of Montana to Alan Sillars.

*Editors’ note: A. Koerner did not participate in the review or editorial decision making regarding this manuscript.

Notes

¹ Schrodt (2005) used the Family Communication Environment Scale (FCES), which shares a number of items with the RFCP. FCES dimensions are treated as equivalent to conversation and conformity orientations in a meta-analysis by Schrodt et al. (2008).

² Koerner and Fitzpatrick (2002a) recommend standardizing RFCP scores by family role before combining them, thus eliminating potential bias due to perceptual differences between fathers, mothers, sons, and daughters. However, scores calculated in this manner correlated highly with scores that were not standardized prior to averaging (r = .99 for both conversation and conformity-orientation). Thus, we retained the simpler measures derived from averaging raw scores.

³The analysis was conducted using G*Power 3.1.5 software (Faul et al., 2007). A sample size of 49 was used for a bivariate regression model. Testing power using bivariate correlations is an appropriate technique to assess power for partial r of single predictors in multiple regression models (Algina & Olejnik, 2003).