Modeling cohesion change in group psychotherapy: the influence of group leader behaviors and client characteristics
|Institution:||Iowa State University|
|Keywords:||Psychology (Counseling Psychology); Psychology; Counseling Psychology; cohesion; group therapy; growth curve analysis; patient-provider relationships; Counseling Psychology; Medicine and Health Sciences|
|Full text PDF:||http://lib.dr.iastate.edu/etd/15175|
Cohesion, the sense of belonging individuals feel toward groups they are a part of, is a well-documented predictor of group psychotherapy outcomes. Meta-analyses reveal a reliable association between cohesion and reductions in psychological distress (r = .25; Burlingame, McClendon, & Alonso, 2011a) as well as between cohesion and task performance (r =.17; Gully, Devine, & Whitney, 2012). Despite this, few studies have attempted to carefully examine predictors of cohesion during the life of a psychotherapy group. Given contradictory findings on the trajectory of cohesion across time (e.g. Kivlighan & Lilly, 1997; Taube-Schiff et al., 2007; Tschuschke & Dies, 1994), as well recent evidence that differences between therapists predict the growth of cohesion (e.g. Bakali, Wilberg, Hagtvet, & Lorentzen, 2010), the present investigation sought to model changes in cohesion by analyzing early leader interventions while accounting for client- and group-level characteristics. For the present investigation, 128 volunteer clients and 14 group therapists participated in 23 separate time-limited psychotherapy groups. Client characteristics (attachment style, self-esteem, and psychological distress), therapist characteristics (counseling self-efficacy), first-session therapist behaviors (structuring, verbal interaction, and emotional facilitation), and group characteristics (number of members, member attendance) were used to predict changes in cohesion across time. For the methodology, a Latent Growth Curve (LGC) Analysis under a Hierarchical Linear Modeling (HLM) framework was used; with client ratings serving as indicators of the outcome variable (cohesion), level 1 representing the effects of time, level 2 representing client characteristics, and level 3 representing group characteristics (including leader behaviors and self-efficacy). Results indicated that a piecewise linear-quadratic model best fit the data, with group membership explaining between 3-20% of the variability in cohesion change. Significant individual level predictors included gender, race, and anxious and avoidant attachment. Significant group-level predictors included structuring behaviors, which were moderated by the presence of behaviors thought to facilitate an emotional climate. Limitations and possible areas of future research are discussed and implications for the theory and practice of short-term group psychotherapy are provided.