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Cohesion in Group Therapy: A Meta-Analysis
Gary M. Burlingame, Debra Theobald McClendon, and Chongming Yang Brigham Young University
Cohesion is the most popular of the relationship constructs in the group therapy literature. This article reviews common definitions of cohesion, the most frequently studied measures, and a measure that may clarify group relations using two latent factors (quality and structure) to explain common variance among frequently used group relationship instruments. We present the results of a meta-analysis examining the relation between group cohesion and treatment outcome in 55 studies. Results indicate that the weighted aggregate correlation between cohesion and treatment outcome was statistically significant, r � .26, z � 6.54 (p � .01), reflecting a moderate effect size (d � .56). Heterogeneity of effect sizes was significant (Q � 260.84, df � 54, p � .001) and high (I2 � 79.3%), supporting moderator analyses. Six moderator variables were found to significantly predict the magnitude of the cohesion– outcome association (type of outcome measure, leader interventions to increase cohesion, theoretical orientation, type of group, emphasis on group interaction, and dose or number of group sessions). Patient contributions, diversity considerations, and evidence-based therapeutic practices are highlighted.
Clinical Impact Statement Question: Does the quality of the group therapeutic relationship predict patient improvement? Findings: Clinical efforts to enhance the therapeutic relationship in group optimize patient outcome irrespective of theoretical orientation. Meaning: Group cohesion improves outcomes in both inpa- tient and outpatient settings and across a variety of patient diagnoses. Next Steps: Test cohesion measure-informed care in group on failing states of relationship.
Keywords: group therapy, cohesion, psychotherapy relationship, meta-analysis
Cohesion is the most popular of several relationship constructs (e.g., alliance, group climate, and group atmosphere) in the clinical and empirical literature on groups. Over time it has become syn- onymous with the therapeutic relationship in group psychotherapy (Burlingame, Fuhriman, & Johnson, 2002). From the perspective of a group member, relationships comprise three structural com- ponents: member–member, member– group, and member–leader. From the perspective of the therapist, relationships include the same three components, as well as two additional ones: leader– group and, in the case of a cotherapist, leader–leader. The com- plexity of these multilevel structures coupled with their dynamic interplay has created an array of competing cohesion instruments and an absence of a consensual definition.
In this article, we review the multiple definitions and measures of group cohesion and then discuss a new measure that contains two latent factors— quality and structure—that explain common variance among these group therapy relationship instruments. We provide a clinical example to illustrate the multiple facets of cohesion in group work. We then present an original meta-analytic review of cohesion’s relation with outcome and discuss potential moderators. We highlight research limitations, patient contribu- tions, and diversity considerations. We end with a list of therapeu- tic practices that have been linked to increased cohesion. Our intent is to illuminate the coherence in the cohesion literature, present the meta-analytic conclusions, and offer measures and practices to improve treatment outcomes.
Definitions and Measures
Definitions of group cohesion have traveled a serpentine trail (Bednar & Kaul, 1994; Crouch, Bloch, & Wanlass, 1994; Kivlighan, Coleman, & Anderson, 2000), ranging from broad and diffuse (e.g., forces that cause members to remain in the group or sticking- togetherness) to focused (e.g., attractiveness or alliance) and structur- ally coherent (e.g., tripartite relationship; Yalom & Leszcz, 2005). Reviewers have pled for definitional clarity: “there is little cohesion in the cohesion research” (Bednar & Kaul, 1978, p. 800). Indeed, in- struments tapping group acceptance, emotional well-being, self- disclosure, interpersonal liking, and tolerance for personal space have been used as measures of cohesion. Behavioral definitions have included attendance, verbal content, early termination, physical seat-
Gary M. Burlingame and Debra Theobald McClendon, Department of Psychology, Brigham Young University; Chongming Yang, College of Family Home and Social Sciences, Brigham Young University.
This article is adapted, by special permission of Oxford University Press, by the same authors in J. C. Norcross & M. J. Lambert (Eds.). (2018), Psychotherapy relationships that work (3rd ed.). New York, NY: Oxford University Press. The Interdivisional APA Task Force on Evidence-Based Psychotherapy Relationships and Responsiveness was cosponsored by the APA Division of Psychotherapy/Society for the Advancement of Psycho- therapy.
Correspondence concerning this article should be addressed to Gary M. Burlingame, Department of Psychology, Brigham Young University, 238 TLRB, Provo, UT 84602. E-mail: gary_burlingame@byu.edu
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Psychotherapy © 2018 American Psychological Association 2018, Vol. 55, No. 4, 384 –398 0033-3204/18/$12.00 http://dx.doi.org/10.1037/pst0000173
384
ing distance, amount of eye contact, and the length of time group members engaged in a “group hug” (Hornsey, Dwyer, & Oei, 2007). The definitional challenges of cohesion are reflected by one team’s observation that “just about anything that has a positive valence [with outcome] has been interpreted at some point as an index of cohesion” (Hornsey, Dwyer, Oei, & Dingle, 2009, p. 272).
Ample evidence supports two definitional dimensions of cohesion. The first dimension is structural and is most often referred to as vertical and horizontal cohesion (Dion, 2000). Vertical cohesion rep- resents a member–leader relationship: a group member’s perception of the group leader’s competence, genuineness, and warmth. Hori- zontal cohesion describes a group member’s relationship with other group members and with the group as a whole. The second dimension of group cohesion is the quality of the relationship or the affective or emotional nature of cohesion (interpersonal and emotional support; Griffith, 1988).
Measures of cohesion frequently used in the group psychotherapy research include the following: Group Climate Questionnaire (GCQ; MacKenzie, 1981, 1983); Cohesion Scale Revised (Lieberman, Yalom, & Miles, 1973); Group Cohesion (Piper, Marrache, Lacroix, Richardsen, & Jones, 1983); Group Atmosphere Scale (Silbergeld, Koenig, Manderscheid, Meeker, & Hornung, 1975); Group Environ- ment Scale (Moos, 1986; Moos & Humphrey, 1974); Stuttgarter Bogen (Czogalik & Koltzow, 1987); Therapeutic Factor Inventory– Cohesion subscale (Lese & MacNair-Semands, 2000); and the Har- vard Group Cohesiveness Scale (Budman et al., 1987, 1989). The abovementioned order of presentation reflects the frequency of use in our meta-analysis to be presented in the following text; these mea- sures account for 82% of the measures used in the studies included in the meta-analysis.
Table 1 summarizes these cohesion measures. These measures promulgate some of the definitional difficulties outlined earlier. For instance, positive aspects of relationship quality assessed by the mea- sures in Table 1 include degree of self-disclosure, inclusion, likability, support, involvement, expressiveness, sense of relatedness, belonging, and trust. Some measures (GCQ and Group Environment Scale) go beyond affective elements and tap the work orientation of the group. Some measures explicitly address the relationship structure of hori- zontal and vertical cohesion (e.g., GCQ � member– group, GC � member–member, and member–leader), whereas others are less clear on which relationship structure members are being asked to assess. Generally speaking, little attention has been focused on how these intersect with the different relationship structures (member–member, member–leader, and member– group) found in group psychotherapy. Additionally, the research has not simultaneously studied two or more cohesion measures in the same study, which makes it impossible to determine if different or similar relationship constructs are being assessed.
Some of these difficulties may be clarified through the Group Questionnaire (GQ; Krogel, 2009). The GQ was an outgrowth of an earlier review of cohesion (Burlingame et al., 2002), which recog- nized these definitional and empirical challenges and created a toolkit of group relationship measures (Strauss, Burlingame, & Bormann, 2008). Creating the empirical foundation for the GQ, the first study (Johnson, Burlingame, Olsen, Davies, & Gleave, 2005) estimated the correlations of four commonly used measures of the group relation- ship (group climate, cohesion, alliance, and empathy) from this tool kit. The findings of this study supported three relationship quality factors that capture the affective (Positive Bond and Negative Rela-
tionship) and work (Positive Work) facets of group relationships. It also crossed these quality factors with three structural relationship factors (member–member, member– group, and member–leader) to capture the multiple alliances. A second study (Bormann & Strauß, 2007) collected data from inpatient psychodynamic groups and found the same three relationship quality factors but also found greater support for the structural components (member–member, member– leader, and member– group). A third study reported a similar two- dimensional model that varied by stage of treatment (Bakali, Baldwin, & Lorentzen, 2009). These three studies led to an item-reduction process that identified a subset of “practice friendly” items that would provide leaders with feedback about the relationship perceptions of group members (Gleave et al., 2017).
The GQ is a 30-item self-report measure of the quality of thera- peutic relationship in groups (Burlingame et al., 2017) developed by an international cooperation between researchers in the United States and Germany (Strauss et al., 2008). Empirically derived items are responded to by group members using a 7-point Likert-type scale from 1 (not true at all) to 7 (very true). The scale assesses three quality subscales: Positive Bond (13 items; e.g., “The group leaders were friendly and warm toward me” and “I felt that I could trust the other group members during today’s session”), Positive Work (eight items: e.g., “The group leaders and I agree on what is important to work on” and “The other group members and I agree about the things I will need to do in therapy”), and Negative Relationship (nine items: e.g., “The members were distant and withdrawn from each other” and “There was friction and anger between members”). The GQ items are organized by three structural dimensions: member–leader, member– member, and member– group.
The measure yields a score for each of the three scales, but not a total score. All three subscales have good internal consistency, with Positive Bond ranging from .79 to .92, Positive Work ranging from .85 to .91, and Negative Relationship ranging from .87 to .86 (Chap- man et al., 2012; Krogel et al., 2013; Thayer, 2012). The GQ dem- onstrates criterion validity, with acceptable correlations with the Working Alliance Inventory, GCQ, Therapeutic Factors Inventory, and Empathy Scale (Thayer & Burlingame, 2014). The three GQ subscales have clarified mixed findings in previous studies, addressed weakness found in other measures, and been used to suggest group composition guidelines (Kivlighan, Lo Coco, Gullo, Pazzagli, & Mazzeschi, 2017).
Clinical Example
Relationship quality and structure provide a practice-friendly framework to recognize cohesive group behavior. We selected a transcript from Session 14 of a 15-session therapy group (Burlin- game & Barlow, 1996)1 to illustrate the multidimensional com- plexity of group cohesion. The following dialogue includes all three relationship structures (member–member, member–leader, and member– group); the quality and structure categories are iden- tified by italics.
Leader to Steve: Steve, you OK? You seemed upset at the end of our last group meeting. (Leader– member; negative relationship probe)
1 This study obtained subject-informed consent that allowed for video- taping of all group sessions from which deidentified transcripts were created to support later process and qualitative research studies.
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385COHESION IN GROUP THERAPY
Steve: I need to apologize to you because I was a little bit abrupt with you last week and I . . . thought that was kinda tacky, uh . . . even though I said it was none of you damned business. [Group laughs] . . . But uh, what I meant was I’m not handling it well and, therefore, I cannot share anything with you. I have nothing to give [laughs] because I . . . uh, I’m not handling it well. (Member–lead- er; negative relationship)
Leader: You’ve done a lot of good work over the past few months but right now you feel like you’ve got nothing to give—that you’re no longer han- dling it well. (Leader–member; positive work)
Steve: I also feel badly that Susan is not here today; I miss her. (Member–member; positive bond)
Steve: I’ve been thinking about her and her crisis a great deal, and I almost called you [leader] up to get her phone number. I
Table 1 Cohesion Measures With a Strong Presence in the Cohesion–Outcome Meta-Analysis
Measure
Frequency used in
meta-analysis Common cohesion elements assessed Unique elements assessed
Group Climate Questionnaire (GCQ; MacKenzie, 1981, 1983)
16 Engaged: degree of self-disclosure, cohesion, and work orientation in group
Conflict: interpersonal conflict and distrust
Avoiding: degree to which individuals rely on the other group members or leaders, avoiding responsibility for their own change processa
Gross (1957) Cohesion Scale Revised (Lieberman, Yalom, & Miles, 1973)
9 Group fit, perceived inclusion, attraction to group activities, likability of members, and how well the group works together
Group Cohesion (Piper, Marrache, Lacroix, Richardsen, & Jones, 1983)
7 Member–member: Positive qualities: likability, trust, and ease
of communication Personal compatibility: attraction, similarity,
and desire for personal friendship Significance as a group member: personal
importance Member–leader: Positive qualities: likability, trust, attraction,
and ease of communication Dissatisfaction with leader’s role: discontent
with style, communication, and level of personal disclosure
Personal compatibility: similarity and desire for friendship
Group Atmosphere Scale (Silbergeld, Koenig, Manderscheid, Meeker, & Hornung, 1975)
5 Group Cohesion: Autonomy, Affiliation, Involvement, Insight, Spontaneity, Support, And Clarity
Aggression
Submission: group conformity Order, Practicality, and Variety contribute to
other aspects of perceived environment; Authors did not define these scales
Group Environment Scale (Moos, 1986)
3 Relationships within the group: Cohesion, Leader Support, and Expressiveness
Personal growth of group members: Independence, Task Orientation, Self Discovery, and Anger and Aggression
System maintenance and system change: Order and Organization, Leader Control, and Innovation
Stuttgarter Bogen (Czogalik & Koltzow, 1987)
3 Emotional relatedness: sense of relatedness with the group; ex: understood/misunderstood and comfortable/uncomfortable
How the individual is feeling about themselves in the group; e.g., spontaneous/hesitant, impulsive/self-controlled, inferior/superior, etc.
Therapeutic Factors Inventory–Cohesion Subscale (Lese & MacNair-Semands, 2000)
3 Group’s investment and commitment perceived by member’s sense of belonging and experience of acceptance and trust and cooperation in the group
Harvard Community Health Plan Group Cohesiveness Scale (Budman et al., 1987)
2 Fragmentation versus Global Cohesiveness: Withdrawal and Self-Absorption versus Interest and Involvement; Mistrust versus Trust; Disruption versus Cooperation; Abusiveness versus Expressed Caring; Unfocused versus Focused
Focuses on the group as a whole Observer ratings, rather than self-report
a The GCQ Avoiding scale has psychometric difficulties (low internal consistency and failure to load onto the factor structures) that have led us to recommend that it should not be scored or interpreted for clinical use (Burlingame et al., 2006; McClendon & Burlingame, 2011).
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386 BURLINGAME, MCCLENDON, AND YANG
know we’re not supposed to interact out- side . . . [As they are talking, Susan comes into the group, and the whole group cheers when she enters]. (Group–member; posi- tive bond toward Susan)
Leader to Susan: We wanted you to be here so bad, some of us were thinking that you had a crisis, and we were worried. (Leader–member; posi- tive bond)
Steve to Susan: Well, I’m glad you’re here . . . because I’ve been worried about you [Steve goes on to inquire about Susan’s situation.] (Mem- ber–member; positive bond)
Susan to Steve: Thank you. The reason I tore out of work so fast to get here is because I knew I’d get the reception I just got. [Susan starts to cry, and the group laughs lightly; the leader pats Susan on the shoulder, and Susan pats Mary on the knee] (Member– group/member; positive bond)
Steve to Susan: I apologize for being abrupt with you last week. That was tactless. I’m sorry. (Mem- ber–member; negative relationship)
Susan to Steve: It didn’t bother me, but I accept your apol- ogy. It means a lot to me that you’d check in with me on that. (Member–member; positive bond)
In this dialogue, we see Steve interacting with a notable level of interpersonal risk with the group leader and another group member with the group as a whole supporting the process. These types of interactions are evidence of a high level of cohesiveness within this group.
Results of Previous Meta-Analyses
Our last meta-analysis (Burlingame, McClendon, & Alonso, 2011a, 2011b) located 40 studies published across a 40-year span that tested the cohesion– outcome relation. Slightly less than half (43%) of the studies posted a significant correlation between cohesion and client improvement, with an average weighted cor- relation of r � .25. Total number of patients in that meta-analysis was 3,323.
A total of 19 possible moderators were tested, grouped by four categories: study, leader, member, and group characteristics. Five of these 19 moderators explained between-study variability in the weighted cohesion– outcome correlation: (a) age of group mem- bers was negatively correlated (r � �.63) with the cohesion– outcome relation, suggesting that younger members posted higher cohesion– outcome correlations; (b) leader theoretical orientation produced significantly different correlations: interpersonal (r � .58), psychodynamic (r � �.25), and cognitive-behavioral (r � .18); (c) group structure: interactive groups that were less struc- tured had a higher correlation (r � .38) than problem-specific groups that focused on a common theme; (d) group size: groups having five to nine members posted the highest correlation (r � .35) compared with groups with fewer than five members or more
than nine (r � .16); (e) group length: groups lasting between 12 and 19 sessions had higher correlations (r � .36) than groups with fewer than 12 sessions (r � .17), but, however, groups lasting 20 or more sessions posted a similar correlation (r � .31) to those in the 12 to 19 range.
We concluded our meta-analysis by noting that the average weighted correlation between cohesion– outcome was comparable with relationship variables studied in individual therapy and that the dominant theoretical orientations all produced significant cor- relations. Thus, cohesion appeared to be an evidence-based pro- cess in group treatment.
Meta-Analytic Review
In our initial meta-analysis (Burlingame et al., 2011a, 2011b), we relied upon five published group therapy meta-analyses to develop inclusion criteria. These criteria included groups that comprised at least three members; met for the purpose of coun- seling, psychotherapy, or personal growth; used at least one quan- titative measure of cohesion and outcome; produced data that allowed the calculation of effect sizes as weighted correlations; and reported in the English language.
Search Strategy
Our 2011 meta-analysis identified potential articles by searching PsycINFO, MedLine, and Google Scholar for publications be- tween January, 1969 and May, 2009. A total of 1,506 abstracts were retrieved using the following search terms: group psycho- therapy, group therapy, support groups, group counseling, cohe- sion, group cohesion, cohesiveness, and group climate. Each ab- stract was reviewed for fit with the inclusion criteria, and, if deemed promising, the article was retrieved and underwent a full text review. A total of 24 articles were included using this method. Next, the reference sections of these 24 articles were reviewed, and 42 unduplicated studies were identified and reviewed, resulting in six studies being included. Finally, six of the most frequently used cohesion measures (Group Environment Scale, Piper’s Cohesion Questionnaire Scale, GCQ, Group Atmosphere Scale, Shulz’s Co- hesion Questionnaire, and Gross Cohesion Scale; cf. Table 1) were searched using Google Scholar, yielding 1,027 abstracts. Ten additional studies were added, yielding a final data set of 40 studies.
Our updated meta-analysis followed a similar database search using a 2009 to 2016 time frame, which yielded 625 abstracts. These were reviewed using the same inclusion criteria noted earlier with one addition— groups had to last four or more sessions (Burlingame, Strauss, & Joyce, 2013). We eliminated 560 papers during the screening process and then conducted a full text review of 65 studies. Our previous meta-analysis focused upon estimating effect sizes using studies that assessed cohesion at a single point in time, and we identified 15 studies that fit this analysis. The reasons for eliminating the remaining 50 papers included the following: the absence of an outcome measure (k � 14), cohesion was repeatedly assessed with interactions (12), no statistical comparison between cohesion and outcome (nine), focus on alliance instead of cohesion (seven), the absence of a therapeutic focus (five), and incomplete data to compute effect size (three).
In all, we identified 55 studies of group therapy, a sample of 6,055 patients, that investigated the cohesion– outcome associa-
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387COHESION IN GROUP THERAPY
tion. A summary of study characteristics is provided in Table 2. The majority of studies were published after 2000 (median of 2005), although a fifth (k � 12) were published prior to 1990, capturing several classic papers (e.g., Braaten, 1989; Budman et al., 1989; Roether & Peters, 1972; Yalom, Houts, Zimerberg, & Rand, 1967). The average group lasted 22 sessions, comprised young adults (average age � 36), and was guided by a cognitive- behavioral, psychodynamic, or humanistic therapist. The vast ma- jority of groups were therapeutic, followed by psychoeducation and support.
Coding and Analysis
We selected and coded 20 variables derived from four main categories: study characteristics, leader characteristics, member characteristics, and group characteristics. Some of these variables have been found to moderate outcome in previous group therapy meta-analyses. The largest numbers of coded variables were asso- ciated with the group itself. Specifically, we were interested in the degree of structure and group member interaction associated with the group treatment given the recent emphasis on manual-based treatments. The variables were as follows:
• Five study characteristics as follows: year of publication, attrition, type of cohesion, type of outcome measure, and when cohesion was assessed.
• Three leader characteristics as follows: clinical experience, theoretical orientation, and single leader versus coled groups.
• Four member characteristics as follows: gender, age, diagno- sis, and treatment setting.
• Eight group characteristics as follows: specific leader inter- ventions to increase cohesion, groups that allowed greater interaction among members, type of group (psychoeduca- tional, psychotherapy, and personal growth), homogeneous (identical or similar diagnoses and presenting problems) ver- sus heterogeneous composition, group size (small, medium, and large groups), session length, treatment setting, and num- ber of group sessions (dose of therapy).
The original meta-analysis used eight raters (one graduate student and seven undergraduate students) trained on a codebook using studies not included in the analysis. They achieved an 85% crite- rion level of agreement with high interrater reliability (� � .73). After achieving this criterion, raters were paired and independently coded identical articles in the meta-analysis so that each article was double-coded by two raters. Complete agreement was required with discrepancies resolved by the graduate student and the senior author. In the update, the senior author trained a single undergrad- uate rater using an identical process, and the two independently rated articles. Interrater agreement of dually coded articles was very high (97%), and the small number of discrepancies (3%) were resolved by the senor author.
In the current analysis, a number of studies used several out- come and cohesion measures, creating multiple cohesion– outcome correlations from a single study. When this occurred, we averaged the values (weighted by n) so that only one correlation per study was included. Following calculation of the aggregate correlation,
Table 2 Characteristics of Studies Included in Meta-Analysis
Variable % N
Number of studies 55 Year of publication (median) 2005 Overall number of clients 6,055 Average age of clients 36.0 Average number of sessions 21.8 Theoretical orientation of group
Cognitive/behavioral 35 23 Psychodynamic/existential 23 15 Humanistic/interpersonal/supportive 20 13 Eclectic 6 4 Unknown 15 10
Primary diagnosis Informal 32 17 Anxiety disorder 13 7 Mood disorder 11 6 Substance disorder 8 4 Eating disorder 6 3 Personality disorder 8 4 Medical condition (not somatic disorder) 4 2 Others or unknown 19 10
General psychological distress 26 20 Depression 20 15 Anxiety 18 14 Quality of life/general well being 12 9 Interpersonal problems/relationships 13 10 Self esteem 7 5 Others 5 4
Country North America 46 25 Europe 26 14 Canada 18 10 Australia 11 6
Location University Counseling Center 2 1 Clinic or Private Practice 7 4 Hospital 36 20 Community Mental Health Center 7 4 Classroom Setting 9 5 Others or Unknown 38 21
Setting Inpatient 18 10 Outpatient 67 37 Mixed or unknown 15 8
Format Psychoeducation (structured, didactic instruction,
and topic-oriented) 9 5 Counselling/therapy (decrease symptoms through
therapy) 79 42 Task (group problem solving, accomplish a goal,
and nontherapy) 2 1 Support (12 steps, cancer survivor group, and
alcoholics anonymous) 4 2 Analog (pretended group for study and not for
real symptoms) 4 2 Mixture of counseling/therapy with task 2 1
Process No description in the study 89 47 Described how processes would be enhanced 11 6
Leadership of group Single leader 46 16 Coled by two leaders 49 17 Mixed (some single and some coled) 5 2
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388 BURLINGAME, MCCLENDON, AND YANG
we examined the degree of heterogeneity in the results across studies using the Q statistic (Berkeljon & Baldwin, 2009). If heterogeneity was found, variability among the study’s effect size mean would be higher than what would be expected from sampling error. Thus, when heterogeneity exists, moderator results are ulti- mately interpreted with more confidence. A random effects model was used; random effects assume that studies are selected from a population of studies and that variability between studies is the result of sampling error. This analytic model is recommended as a more conservative test (Hedges & Vevea, 1998; Lipsey & Wilson, 2001).
Results
Prior reviews have concluded that group cohesion demonstrates a positive relation with patient improvement in nearly every pub- lished report (Tschuschke & Dies, 1994). Our 2002 narrative review concluded that approximately 80% of published studies demonstrated a statistically significant positive association be- tween group cohesion and treatment outcome (Burlingame et al., 2002).
The results from the current meta-analysis (with each study depicted in Table 3) paint a more complex picture of the cohesion– outcome association. Slightly more than half (53%, k � 29) of the studies posted a statistically significant correlation between cohe- sion and patient improvement, with additional three studies having p values in the trend range (p � .10). The weighted aggregate correlation of the 55 included studies was statistically significant, r � .26 (95% CI [.20, .31], p � .01), reflecting a moderate effect (d � .56) between cohesion and outcome. The 95% confidence interval (.20 –.31) for our updated meta-analysis falls within the confidence interval of our previous meta-analysis (.17–.32).
Heterogeneity of effect sizes was significant (Q � 260.84, df � 54, p � .001) and high with I2 � 79.3%, which supports explo- ration of effect size variance with moderator analyses. However, it’s noteworthy that 73% (k � 11) of the new studies (identified with a� in Table 3) produced a statistically significant relation compared with the 43% reported in our last meta-analysis. This pattern suggests stronger support for the cohesion– outcome rela- tion in more recent research. Thus, it is unlikely that the size of the correlation was overestimated in our previous meta-analysis due to studies that did not control for intragroup dependency because most recent studies statistically controlled for group influence.
Orwin’s fail safe N was estimated to address the file-drawer problem and 1,571 unpublished studies with a correlation of .01 would be needed to nullify our weighted aggregate correlation of r � 0.26; 107 unpublished studies with a correlation of .10 would be needed to nullify our weighted correlation of r � 0.26. This seems unlikely because less than 10% of our 55 studies met both criteria.
We created two graphic portrayals of our effect sizes to visually assist the reader in understanding the findings. The first (see Figure 1) is the typical forest plot that depicts whether an individual study favored a positive or negative relationship between cohesion and outcome. Figure 1 is useful in identifying outliers on either side of the weighted aggregate correlation of r � .26. The second por- trayal of the effect sizes shown in Table 3 is a funnel plot, which is typically used to check for publication bias. These were plotted using the standard error as the y-axis. Absence of bias is indicated
by a higher number of studies symmetrically falling near the average and within the 95% confidence interval lines.
There is some evidence for heterogeneity with a small but equivalent number of studies falling outside either side of the 95% confidence interval line (Figure 2). Interestingly, neither sample size nor cohesion measure explains these heterogeneous effect sizes. Studies with small samples produced both large (Tschuschke and Dies, 1994) and small (Kipnes et al., 2002) estimates. Simi- larly, the same measure of cohesion produced large (GCQ-Hurley/ GQ-Lecomte) and small (GCQ-Rice/GQ-Kipnes) effect size esti- mates. The overall conclusion from 55 studies published across a 50-year span is that there was sufficient precision to produce a robust estimate of the relation between cohesion and outcome.
Mediators and Moderators
Few empirical studies examine moderator or mediator vari- ables for the cohesion– outcome link (Hornsey et al., 2007), although recent studies have started to include them. Mediators have been proposed (e.g., member acceptance, support, self- disclosure, and feedback), but there has been little progress in the literature due to the varied definitions and confounds with group cohesion (Hornsey et al., 2007). With the 15 new studies, one of the five moderators that significantly explained between- study cohesion– outcome differences in our last meta-analysis fell away (group size). Six moderators were found to be significant (type of outcome measure, leader interventions to increase cohe- sion, theoretical orientation, type of group, emphasis on group interaction, and dose or number of group sessions). Each is de- scribed in more detail in the following text.
Study Characteristics
Four of the study characteristics (publication year, attrition, cohesion measure, and time of cohesion assessment) failed to explain variability in the average weighted cohesion– outcome effect sizes depicted in Figure 1. However, type of outcome measure was found to be a significant moderator (Table 4; Q � 24.98, df � 9, p � .01). Higher weighted averages were found on both interpersonal and self-esteem measures (Inventory of Inter- personal Problems and Rosenberg Self-Esteem Scale), but these results are heavily influenced by the two student growth group studies (Hurley, 1989; Kivlighan & Lilly, 1997). Thus, it remains unclear how these outcome measures might operate in clinical populations, and caution is advised on overinterpreting this mod- erator. Two measures (Symptom Checklist and Beck Depression Inventory-II) that assess general psychiatric and depressive symp- toms, respectively, were used in nearly half (44%) of the studies posting reliable values near the meta-analytic average. Thus, the cohesion– outcome relation appears to be well supported when outcome is defined by general psychiatric and depressive symp- toms. This conclusion finds further support in weighted correla- tions for similar measures that were used less frequently (e.g., OQ-45 and Profile of Mood States). Moreover, because the Symp- tom Checklist 90-Revised (SCL-90R) and Beck Depression Inven- tory were also two of the most frequently used instruments to evaluate the effectiveness of group psychotherapy, the generaliz- ability to outcome appears sound.
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389COHESION IN GROUP THERAPY
Table 3 Sample Size, Average Weighted Correlations, Cohen’s D, and Lower/Upper Limits
Study Sample
size Weighted correlation
95% CI
Cohen’s d
95% CI
LL UL LL UL
Antonuccio, Davis, Lewinsohn, and Breckenridge (1987) 106 .00 �0.19 0.19 .00 �0.39 0.39 Beutel et al. (2006) 134 .23�� 0.07 0.39 .48�� 0.13 0.83 Bonsaksen, Borge, and Hoffart (2013)� 80 .19T �0.03 0.39 .53� 0.08 0.98 Braaten (1989) 110 .21� 0.02 0.38 .43� 0.06 0.80 Budman et al. (1989) 90 .63�� 0.48 0.74 1.61�� 1.12 2.10 Crino and Djokvucic (2010)� 27 .17 �0.18 0.49 .33 �0.45 1.11 Crowe and Grenyer (2008) 30 .20 �0.17 0.52 .40 �0.34 1.14 Eltink, Van der Helm, Wissink, and Stams (2015)� 128 .30�� 0.13 0.45 1.62�� 1.21 2.03 Falloon (1981) 51 .16 �0.13 0.41 .32 �0.25 0.89 Flowers, Booraem, and Hartman (1981) 16 .56� 0.09 0.83 1.36� 0.18 2.54 Gillaspy, Wright, Campbell, Stokes, and Adinoff (2002) 49 .19 �0.10 0.44 .38 �0.19 0.95 Grabhorn, Kaufhold, and Overbeck (2002) 48 .18 �0.11 0.44 .37 �0.22 0.96 Hilbert et al. (2007) 138 .24�� 0.07 0.39 .49�� 0.16 0.82 Hoberman, Lewinsohn, and Tilson (1988) 42 .38� 0.08 0.61 .81 0.16 1.46 Hornsey, Olsen, Barlow, and Oei (2012)� 30 .29 �0.07 0.59 .62 �0.14 1.38 Hurley (1989) 374 .70�� 0.64 0.75 1.96�� 1.71 2.21 Hurley (1997) 678 .35�� 0.28 0.41 .75�� 0.59 0.91 Joyce, Piper, and Ogrodniczuk (2007) 107 .09 �0.10 0.28 .19 �0.20 0.58 Kelly, Deane, and Baker (2015)� 124 .28�� 0.11 0.43 .58�� 0.23 0.93 Kipnes, Piper, and Joyce (2002) 12 .00 �0.57 0.57 .00 �1.25 1.25 Kirchmann et al. (2009)� 289 .25�� 0.13 0.35 .51�� 0.27 0.75 Kivlighan and Lilly (1997) 30 .36� �0.01 0.63 .76� 0.00 1.52 Lecomte, Leclerc, Wykes, Nicole, and Abdel Baki (2015)� 66 .43�� 0.21 0.61 .94�� 0.43 1.45 Levenson and Macgowan (2004) 61 .33�� 0.09 0.54 .70� 0.17 1.23 Lipman et al. (2007) 38 .15 �0.18 0.45 .30 �0.37 0.97 Lorentzen, Sexton, and Høglend (2004) 12 .30 �0.33 0.75 .63 �0.64 1.90 Mackenzie and Tschuschke (1993 16 .46T �0.05 0.78 1.04 �0.08 2.16 Marmarosh, Holtz, and Schottenbauer (2005) 102 .54�� 0.38 0.66 1.27�� 0.84 1.70 Marziali, Munroe-Blum, and McCleary (1997) 17 .19 �0.32 0.61 .38 �.64 1.40 May et al. (2008) 132 .18� 0.01 0.34 .36� 0.01 0.71 Norton and Kazantzis (2016)� 373 .14� 0.04 0.24 .28� 0.08 0.48 Norton, Hayes, and Springer (2008) 54 .30� 0.03 0.52 .62 0.07 1.17 Oei and Browne (2006) 162 �.03 �0.19 0.12 �.07 �0.38 0.24 Ogrodniczuk and Piper (2003) 107 .22� 0.03 0.39 .45� 0.06 0.84 Ogrodniczuk, Piper, and Joyce (2006) 75 .22T �0.01 0.42 .44 �0.03 0.91 Ogrodniczuk, Piper, and Joyce (2005) 39 .42�� 0.13 0.65 .94�� 0.25 1.63 Owen, Antle, and Barbee (2013)� 126 .30�� 0.13 0.45 .63�� 0.28 0.98 Paulus, Hays-Skelton, and Norton (2015)� 221 .38�� 0.26 0.48 .81�� 0.54 1.08 Petry, Weinstock, and Alessi (2011)� 239 .19� 0.04 0.33 .39�� 0.14 0.64 Pisetsky et al. (2015)� 190 .18� 0.04 0.32 .37� 0.08 0.66 Quirk, Miller, Duncan, and Owen (2013)� 105 .28�� 0.09 0.44 .58�� 0.19 0.97 Ratto and Hurley (1995) 33 .23 �0.12 0.53 .48 �0.23 1.19 Rice and Tonigan (2012)� 66 .20 �0.05 0.42 .65� 0.14 1.16 Rice (2001) 59 .00 �0.26 0.26 .00 �0.51 0.51 Roether and Peters (1972) 51 �.18 �0.43 0.10 �.37 �0.94 0.20 Rugel and Barry (1990) 28 .10 �0.28 0.46 .20 �0.56 0.96 Ryum, Hagen, Nordahl, Vogel, and Stiles (2009) 27 .15 �0.24 0.50 .31 �0.47 1.09 Shechtman and Mor (2010)� 164 .22� 0.02 0.41 .16 �0.15 0.47 Taft, Murphy, King, Musser, and DeDeyn (2003) 107 .18� �0.01 0.36 .37 �0.02 0.76 Taube-Schiff, Suvak, Antony, Bieling, and McCabe (2007) 34 .43� 0.10 0.67 .94� 0.21 1.67 Tschuschke and Dies (1994) 16 .72�� 0.34 0.89 2.06�� 0.77 3.35 van Andel, Erdman, Karsdorp, Appels, and Trijsburg (2003) 38 .19 �0.14 0.48 .39 �0.28 1.06 Woody and Adessky (2002) 48 .17 �0.12 0.43 .33 �0.26 0.92 Wright and Duncan (1986) 27 .13 �0.26 0.49 .27 �0.51 1.05 Yalom, Houts, Zimerberg, and Rand (1967) 25 .11 �0.30 0.48 .22 �0.60 1.04 Random ES .26�� 0.20 0.31 .56�� 0.43 0.69
Note. CI � confidence interval; LL � lower limit; UL � upper limit. � � new articles added to update our previous meta-analysis. T p � .05 and � .10. � p � .05. �� p � .01.
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390 BURLINGAME, MCCLENDON, AND YANG
Five cohesion measures produced a statistically significant weighted correlation (Table 4), but there were no reliable differ- ences in the size of this correlation between measures (Q � 6.10, df � 8, p � .64). The conclusion to be drawn is that any of these five measures appear to be a reasonable choice for clinicians and researchers alike. However, the Group Climate Questionnaire– Engaged (GCQ-E) continues to dominate the field; with only five items, it is a particularly practice-friendly choice.
Member Variables
None of the group member variables (gender, age, diagnosis, and treatment setting) explained clinically significant differences in the cohesion– outcome relation. The cohesion-outcome relation continues to be a reliable predictor in both inpatient and outpatient settings (r � .28 and r � .25, respectively). Furthermore, the positive association of group cohesion and client outcome was demonstrated across all three major diagnostic classifications: Axis I (r � .22), Axis II (r � .44), and V codes (r � .29).
Leader Variables
The majority of studies (k � 33) used either single (16) or coled (17) groups, and there was no difference in weighted correlations for these two types of leadership (r � .23 and r � .25, respec- tively). There was a significant difference in the cohesion– outcome relation when examining the theoretical orientation of the group leader (Q � 9.43, df � 4, p � .05). Leaders espousing an interpersonal orientation posted the highest cohesion– outcome relation (r � .48, k � 4). Other theoretical orientations posted significant, but lower values: psychodynamic (r � .27, k � 9), cognitive-behavior (r � .22, k � 19), supportive (r � .22, k � 4), and eclectic (r � .22, k � 3). In our last meta-analysis, only interpersonal, psychodynamic, and cognitive-behavioral therapies posted statistically significant cohesion– outcome correlations. The addition of 15 studies to the analysis added two more group approaches, leading to the conclusion that there is sufficient evi- dence to consider cohesion as an evidence-based relationship factor for groups guided by interpersonal, psychodynamic, cognitive-behavioral, supportive, and eclectic orientations.
Figure 1. Weighted effect size for cohesion– outcome relationship.
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Group Variables
In the past, we (Burlingame, MacKenzie, & Strauß, 2004; Fuhriman & Burlingame, 1994) have suggested that a true test of the cohesion– outcome relation would be to examine studies that emphasized the importance of cohesion as a therapeutic strategy and contrast them with studies that lacked this emphasis. If group cohesion was undervalued or neglected by a group leader, its presence would likely be diminished and perhaps attenuate its association with outcome. We were unable to test this proposition
in our last meta-analysis due to an insufficient number of studies reporting this as an explicit focus. With 15 new studies in this meta-analysis, we were able to test it in this moderator analysis.
Greater attention to cohesion (e.g., group process) was associ- ated with higher weighted correlations (Q � 6.33, df � 1, p � .01). Six studies reported using methods to enhance cohesion: pregroup video tapes (Kivlighan & Lilly, 1997) and in-session interventions to build safety and group cohesion (Lecomte, Leclerc, Wykes, Nicole, & Abdel Baki, 2015). The difference in correlation was modest but consistent with our previous prediction; the studies focusing on group process interventions had a larger cohesion– outcome value (r � .40) compared with the 47 studies (two studies were unratable on this variable) that did not describe such inter- ventions (r � .22).
Another newly identified moderator in this updated analysis was group type (Q � 19.64, df � 5, p � .01). Two group types, volunteer members and task group, produced higher correlations (r � .58 and r � .56, respectively) than psychoeducation, therapy, and support groups (r � .22, r � .24, and r � .25, respectively). However, correlations for the psychoeducation groups (k � 5) and therapy groups (k � 42) had a sufficient number of studies to produce reliable correlations. The analog group type correlations, although higher, were based upon only one or two studies each, needing more study to support generalizability. Thus, our take- home message from this analysis is that the cohesion– outcome link appears equivalent in psychotherapy, psychoeducation, and support groups. As noted with the analog groups, the support groups also need more study to support generalizability.
Two of the three group moderators from our last meta-analysis continued to be significant. Groups that emphasized greater inter- action among group members (r � .36, k � 11) when contrasted with problem-specific groups (r � .23, k � 42) comprising mem- bers with similar diagnoses produced higher cohesion-outcome correlations (Q � 4.29, df � 1, p � .05).
Table 4 Weighted Correlations and Ranges by Cohesion and Outcome Measures
Frequently used cohesion and outcome measures Weight
correlation
95% CI
Z value p value Times usedLL UL
Cohesion measures Group Atmosphere Scale (GAS-C; Silbergeld et al., 1975 .28 .15 .39 4.30 �.01 5 Group Cohesion (GC; Piper et al., 1983) .26 .13 .37 4.00 �.01 7 Group Environment Scale (Moos, 1986) .10 �.06 .25 1.2 .23 3 Stuttgarter Bogen (Czogalik & Koltzow, 1987) .55 �.01 .85 1.91 .06 3 Harvard Community Health Plan Group Cohesiveness Scale (Budman et al., 1987) .41 �.27 .82 1.20 .23 2 Group Climate Questionnaire (Mackenzie, 1981) .26 .13 .39 3.88 �.01 16 Gross Cohesion Scale (Gross, 1957) .26 .12 .38 3.54 �.01 9 Therapeutic Factors Inventory–Cohesion Subscale (Lese & MacNair-Semands, 2000) .26 .17 .34 5.35 �.01 3
Outcome measures Outcome Questionnaire (OQ/OQ-45; Lambert et al., 2013) .26 .11 .39 3.32 �.01 2 Inventory of Interpersonal Problems, IIP-Circumplex (Horowitz et al., 1988) .30 .21 .39 6.19 �.01 4 Therapy Project List-90 (TPL-90; Braaten, 1989) .21 .07 .33 3.04 �.01 2 Rosenberg Self-Esteem Scale (Rosenberg, 1965) .53 .41 .64 7.16 �.01 2 Profile of Mood States (POMS; McNair, Lorr, & Droppleman, 1981) .32 .08 .53 2.59 .01 2 Beck Anxiety Inventory (BAI; Beck, Epstein, Brown, & Steer, 1988) .13 .02 .23 2.65 .02 3 Beck Depression Inventory-II (BDI-II; Beck, Steer, & Brown, 1996) .25 .11 .39 3.32 �.01 11 Symptom Checklist (SCL-90; Derogatis, 1977) .30 .14 .44 3.70 �.01 13
Note. CI � confidence interval; LL � lower limit; UL � upper limit. Test of heterogeneity indicated that effect sizes did not vary significantly across cohesion measures (Q � 6.10, df � 8, p � .64) but varied across different outcome measures (Q � 24.98, df � 9, p � .va01).
Figure 2. Funnel plot of standard error by Fisher’s Z.
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392 BURLINGAME, MCCLENDON, AND YANG
Dose, or number of group sessions, was also again found to moderate the cohesion– outcome effects (Q � 7.55, df � 2, p � .05). However, there was a change from our last report in regards to number of sessions. In our last analysis, there was no statisti- cally significant difference between groups lasting 13 to 19 and 20 or more sessions, but in the updated meta-analysis there appears to be an association between dose and the cohesion– outcome corre- lation. Groups lasting 20 or more sessions posted the highest correlation (r � .41, k � 11), followed by groups lasting 13 to 19 sessions (r � .27, k � 7), and fewer than 13 sessions (r � .21, k � 27).
Previously, we found that group size moderated the cohesion– outcome relation, with groups containing five to nine members producing the largest correlation. In our update, this difference disappeared with small groups (�five members) and moderately sized groups (five–nine members) posting equivalent and signifi- cant correlations (r � .37 and r � .32, respectively). However, it is important to note that there was only one study in the small group condition, attenuating our confidence in an equivalence conclusion. Large groups having more than nine members did not produce a statistically significant cohesion– outcome correlation.
Patient Contributions
There is little research on patient contributions to the cohesion– outcome relation. Two studies included in our earlier meta-analysis found that member interpersonal style moderated the cohesion– outcome relation (Dinger & Schauenburg, 2010; Schauenburg, Sammet, Rabung, & Strack, 2001). Patients who described themselves as “too cold” posted a positive linear cohesion– outcome relation (higher cohesion � better outcome), but patients who described themselves as “too friendly” posted the opposite result. We raised the question, “Could a member’s inter- personal style explain past mixed cohesion-outcome findings?” We then answered, “Unfortunately, the jury is out on this ques- tion” (Burlingame, 2010, p. 123).
Since our last meta-analysis, Tasca and colleagues have exam- ined how the attachment style of group members might moderate group treatment outcomes and the cohesion– outcome relation. A 16-week group psychodynamic interpersonal psychotherapy (Tasca, Mikail, & Hewitt, 2005) was provided to 102 women diagnosed with binge eating disorder. Cohesion was measured weekly via the GCQ and outcomes assessed prepost therapy (Gal- lagher, Tasca, Ritchie, Balfour, & Bissada, 2014). Attachment style was assessed using the Need For Approval subscale of the Attachment Styles Questionnaire (Feeney, Noller, & Hanrahan, 1994), and homogenously composed groups comprised either high- or low-attachment anxiety patients. They found that cohesion increased over time, but neither the level nor rate of cohesion change differed between the high- and low-anxiety patients (Gal- lagher, Tasca, Ritchie, Balfour, & Bissada, 2014). Surprisingly, increased cohesion was not related to the frequency of binge eating, but this was explained by an interaction with the anxiety condition. Higher cohesion was associated with better binge eating outcomes for the high attachment condition; however, higher co- hesion was not associated with better outcomes for the low attach- ment anxiety condition. The authors suggested that “experiencing a growing sense of cohesiveness may offer a secure base to those
high in attachment anxiety and need for approval, leading to a decrease in the frequency of binge eating” (p. 48).
Although the most promising evidence for patient contribution lies in attachment style moderating effect on the size of the cohesion– outcome, the three articles (Gallagher, Tasca, Ritchie, Balfour, & Bissada, 2014; Gallagher, Tasca, Ritchie, Balfour, Maxwell, & Bissada, 2014; Tasca et al., 2013) all use data from the same study of 102 binge eating disorder patients. Thus, we are still in need of additional studies testing member attachment style as a moderator. At this point, we cannot know if the need for approval, which appears to make a member more susceptible to the group’s influence, is unique to eating disorders (Illing, Tasca, Balfour, & Bissada, 2011) or if it is generalizable to other clinical populations.
Limitations of the Research
The most significant limitation of the cohesion literature is the disparity in how the construct is defined. A summary of the content assessed by the eight primary measures (Table 1) used in over 80% of the studies herein reveals some similarity, but major differences in content and the relationship structure are apparent. Differences in how cohesion is defined is further limited by the absence of research that compares how well these measures correlate with one another. Almost all cohesion– outcome studies use a single mea- sure, and the two validity studies noted earlier compared four different measures, making empirical comparisons impossible. The limited empirical light shed on how different cohesion mea- sures might correlate comes from the psychometric work on the GQ that originally began by comparing the most popular relation- ship measure (GCQ: GCQ—16 studies) with the Cohesion sub- scale of the Therapeutic Factors Inventory. Stated differently, the construct validity and criterion validity of cohesion measures are weak.
We also fall short in having sufficient research to establish a strong causal link between cohesion and outcome. The dominant methodology that assesses cohesion once during the life of a group and then correlates it with prepost differences in outcome is insufficient to make causal inferences. Although there is promising research testing the interaction between the cohesion– outcome link and attachment style, findings rely upon a single study. There is an embarrassing paucity of research into the contribution of patient factors and the cohesion– outcome association. We await research on the effect of therapists, which is hampered in group treatment by the large number of groups needed for each therapist to tease apart therapist from group effects.
Future research to clarify the similarities and differences between the frequently used cohesion measures is needed. Prog- ress on this is essential, and the careful psychometric research needed will not be glamorous or likely to win professional recognition. However, empirical knowledge about the con- structs underlying our measurement tools is a requirement to make meaningful conclusions. The repeated assessment of both cohesion and outcome throughout the course of group treatment is a shortcoming that needs to be addressed. Two studies over the past decade are insufficient to accrue the empirical founda- tion to make causal inferences about the effect of cohesion on outcome over time.
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Diversity Considerations
There is a paucity of research on the association among diver- sity, cohesion, and group therapy outcome. In fact, we could not locate a single cohesion– outcome study that addressed diversity, so our meta-analysis is silent on diversity. However, a handful of alliance studies were located (k � 7) that were not included in the meta-analysis. One (Walling, Suvak, Howard, Taft, & Murphy, 2012) looked at how race/ethnicity predicted change in the work- ing alliance for intimate partner violence perpetrators treated in cognitive-behavioral therapy groups. Because these findings tap member–therapist alliance, we review them here.
The study investigated the link between group alliance and treatment outcome with men, nearly half (45%) of whom identified as a racial or ethnic minority (African American, Asian, Hispanic, and Native American). They were treated in 16-week, 2-hr cognitive-behavioral therapy groups that were racially heteroge- neous. Results indicated that the average client-group alliance increased over time; however, for therapist-rated alliance, some members increased and others decreased, and when these were aggregated, there was no significant temporal trend. Interestingly, race/ethnicity (i.e., minority status compared with Caucasian) was not significantly associated with change in the alliance over time for therapist, but member ratings of alliance showed Caucasian members reporting a significant increase over time with minorities reporting no change. The authors also examined the link between alliance and treatment outcome (change in physical abuse behav- ior) and found that aggregated client alliance ratings were not related to outcome. However, there was a significant interaction: Caucasians and minority members who grew in group alliance benefited from treatment, but minority members who reported no growth had poorer outcomes. Client ratings of alliance for colead- ers were nearly identical, irrespective of whether the client’s race/ethnicity matched or differed from the leader.
The authors understandably interpreted these results within a diversity frame and suggested that changes in the working alliance are “differentially determined by the race/ethnicity of the client” (Walling et al., 2012, p. 188). Because the groups were heteroge- neous (minorities ranged from 30% to 70%), we wonder if the group influence played the pivotal role. More specifically, research suggests better outcomes for members who conform to the group norms/averages of cohesion. Could an alternative explanation of the race/ethnicity interaction be member similarity? Could group influence and race/ethnicity factors work in concert? We call for future cohesion– outcome studies that will address these and other issues of diversity.
Therapeutic Practices
Our meta-analysis of 55 studies involving more than 6,000 group members generates the following therapeutic practices:
• Cohesion is reliably associated with and predictive of (r � .26, d � .56) group outcome. This repeated, robust result argues that group practitioners seriously consider routinely assessing, monitoring, and enhancing group cohesion for optimal patient outcomes.
• Cohesion is certainly involved with patient improvement in groups using cognitive-behavioral, psychodynamic, in- terpersonal, supportive, and eclectic orientations. Group
leaders of all theoretical orientations are encouraged to foster cohesion in its multiple manifestations.
• The cohesion– outcome link is strongest when a group leader emphasizes member interaction. Accordingly, group therapists are encouraged to do precisely that.
• The cohesion– outcome link is differentially related to leader behavior. When a leader implements specific interventions to support a positive group climate, higher cohesion– outcome correlations result. That research speaks directly to therapists paying attention to the three major relationship structures (member–member, member–leader, and member– group) promoting a positive affective and work relationship and handling conflict when it arises.
• Cohesion contributes to group outcome across clinical set- tings (inpatient and outpatient) and diagnostic classifications. Thus, leaders would be well advised to actively engage in interventions that foster and maintain cohesion regardless of their particular practice setting.
References
Studies identified with a single asterisk were included in the meta-analysis
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397COHESION IN GROUP THERAPY
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Received March 19, 2018 Revision received March 20, 2018
Accepted March 20, 2018 �
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398 BURLINGAME, MCCLENDON, AND YANG
- Cohesion in Group Therapy: A Meta-Analysis
- Definitions and Measures
- Clinical Example
- Results of Previous Meta-Analyses
- Meta-Analytic Review
- Search Strategy
- Coding and Analysis
- Results
- Mediators and Moderators
- Study Characteristics
- Member Variables
- Leader Variables
- Group Variables
- Patient Contributions
- Limitations of the Research
- Diversity Considerations
- Therapeutic Practices
- References