The International Journal of Psychosocial Rehabilitation

Peer-led vs. Clinician-led Recovery-Oriented
 Groups: What Predicts Attendance by Veterans?

Kathryn A. Bottonari, PhD
Charlie Norwood Veterans Administration Medical Center & Medical College of Georgia

Mark R. Schultz, PhD
Center for Health Quality and Economic Research, Edith Nourse Rogers Memorial Hospital

Sandra G. Resnick, PhD
VISN 1 MIRECC & Yale University School of Medicine

Lisa Mueller, PhD
VISN 1 MIRREC & Edith Nourse Rogers Memorial Hospital

Jack Clark, PhD
Center for Health Quality and Economic Research, Edith Nourse Rogers Memorial Hospital &
Boston University School of Public Health

Dolly C. Sadow, PhD, ABPP


Susan V. Eisen, PhD

Center for Health Quality and Economic Research, Edith Nourse Rogers Memorial Hospital &
Boston University School of Public Health



Bottonari K, Schultz M, Resnick S, Mueller L, Clark J, Shadow, DC, Eisen SV (2012).Peer-led 
vs. Clinician-led Recovery-Oriented Groups: What Predicts Attendance by Veterans?  

International Journal of Psychosocial Rehabilitation. Vol 16(2) 88-105

Susan V. Eisen, PhD
Health Research Scientist
Center for Health Quality Outcomes and Economic Research (CHQOER)
Edith Nourse Rogers Memorial Veterans Hospital
200 Springs Road (152), Bedford, MA 01730.

Author Note
This research was supported by VA grant IIR # D4464R from the Veterans Administration Rehabilitation Research & Development (RR&D) Service.  The work was conducted at the Bedford and West Haven Veterans Administration Medical Centers. The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs. This manuscript is the result of work supported with resources and the use of facilities at the Bedford VA and support to the first author through a VA Health Services Research Postdoctoral Fellowship. 

The Veterans Health Administration (VHA) is transforming its mental health services to incorporate a stronger focus on psychosocial rehabilitation and recovery. Peer-led groups may offer unique benefit in addition to conventional clinician-led services.  There is limited empirical evidence comparing attendance at peer-led services compared to clinician-led services among veterans.  Data were examined from the treatment arms (peer-led vs. clinician-led) of a 2-site, randomized study of recovery-oriented groups for veterans diagnosed with mental illness. Baseline self-report and interview data were examined as predictors of attendance over the course of the 12-week study, using negative binomial regressions. Results demonstrated modest attendance rates (3.8 + 4.3 groups out of 12 weeks), with no statistically significant difference in attendance or predictors of attendance between clinician-led vs. peer-led groups.  Age, education, AUDIT score, and site predicted attendance at the recovery-focused groups in a combined model. Future investigations are needed to examine factors to improve attendance.
Key Words: peer support, recovery model, veterans, attendance

In an effort to improve mental health services for veterans, the Veterans Health Administration (VHA) is working to incorporate a stronger focus on psychosocial rehabilitation and recovery throughout its treatment centers (Uniformed Mental Health Services Handbook, 2008).  A recent review of VHA psychosocial rehabilitation services highlights the increase in recovery-oriented services, including local recovery coordinators, peer support services, peer support technicians, family services, Veterans Mental Health Council, Psychosocial Rehabilitation and Recovery Centers, Mental Health Intensive Case Management, Therapeutic and Supported Employment Services, and Skills training (Goldberg & Resnick, 2010).  Mental health ‘recovery’ focuses on reclaiming one’s life and minimizing the effect of illness on quality of life (Davidson & Roe, 2007).  Davidson and colleagues (2009) define recovery-oriented services as being person-centered, strengths-based, and collaborative.  Ideally, the mental health consumer, friends, family, and treatment providers work together towards recovery. 

Peer support is one important component of recovery-oriented services, particularly in the VHA (Barber, Rosenheck, Armstrong, & Resnick, 2008; Hebert, Rosenheck, Drebing, Young, & Armstrong, 2008).  Empirical research has found positive effects for a range of peer support programs including improvements in practical knowledge, empowerment, in symptoms and social functioning;  development of new coping skills; and enhancement of quality of life, with decreases in symptoms and feelings of isolation, and reduced psychiatric hospitalization rates (e.g., Barbic, Krupa, & Armstrong, 2009; Burti et al. 2005; Campbell, 2004; Cook et al., 2009; Davidson et al., 1999; Fukui et al., 2010; Paulson, Herinckx, Demmler, Clarke, Cutter, & Birecree, 1999; Sells, Davidson, Jewell, Falzer, & Rowe, 2006; Solomon & Draine, 2001; Sledge, Lawless, Sells, Wieland, O'Connell, & Davidson, 2011; Yanos, Primavera, Knight, 2001).  Other recovery-oriented services have also been found to be effective, including supported employment programs, supportive housing, assertive community treatment and mental health case management (Drake & Bond, 2008; O'Connell, Kasprow, & Rosenheck, 2010; Rapp & Goscha, 2004). 

However, the effectiveness of these recovery-oriented programs may depend on the level of participant attendance. Empirical examination of this question has been hampered by noted difficulty in adequately measuring variables of adherence and attendance within recovery-oriented, peer-led interventions (Falzer, 2011). However, several recent studies of peer support/peer-led interventions have noted greater improvement with increased attendance. Cook and colleagues (2009) reported that participants who attended six or more recovery-oriented group sessions showed greater improvement than those attending fewer sessions. Similarly, Starnino and colleagues (2010) reported positive effects of their WRAP intervention with at least 75% participation in the program.  Swarbrick and colleagues (2009) found a relationship between years of attendance and empowerment, though they could not determine the predictor of this relationship. As such, research is needed to understand predictors of attendance and whether these factors vary as a function of the type of intervention being offered.

Review of the literature reveals investigations of both conventional, clinical-led intervention and peer-led (particularly with a focus on substance use groups); however, there is a limitation in that most studies focus on one particular type of intervention (i.e., peer-led or clinician-led but not both).  Empirical investigations of self-help group attendance have previously identified that older age, being single, having better coping skills, strong social functioning, more formal education, living in an urban area, and more significant mental health and substance use problems all predicted longer time in self-help treatment (Jonikas, Kiosk, Grey, Hamilton, McNulty, & Cook, 2010; Luke, Roberts, & Rappaport, 1993; Yanos, Primavera, Knight, 2001). Furthermore, investigations of a specific form of peer support, substance-use focused self-help groups (i.e., NA/AA), have identified increased attendance among those who were older, unemployed, African-American background, more highly educated, not religious, less socially isolated, previous substance use treatment, higher self-efficacy regarding sobriety, more arrests, earlier age of onset of substance use disorder, history of physical or sexual abuse, living in supportive housing, and more acute substance abuse/mental health problems (Brown, O’Grady, Farrell, Flechner, & Nurco, 2001; DiNitto, Webb, Rubin, Morrison-Orton, & Wambach, 2001; Laudet, Magura, Cleland, Vogel, & Knight, 2003; Kelly, & Moos, 2003; Schneider, Burnette, & Timko, 2008; Weiss et al., 2000). Investigations of attendance at more conventional clinician-led mental health services have found provided conflicting evidence with several investigations indicating that no-show to one’s appointments and/or lower attendance was predicted by younger age, less formal education, lack of sick leave, personality disorder diagnosis, particularly low or high functioning, no previous mental health treatment, substance abuse, fearful attachment style, interpersonal hassles (Fenger, Mortensen, Poulsen, & Lau, 2011; Ilardi & Kaslow, 2009) whereas others have identified higher attendance as predicted by social isolation, personality disorder, higher formal education, and more acute mental health disorder (Centorrino et al, 2001). Of direct relevance to veteran populations, Resnick and Rosenheck (2008) reported improvements in level of personal empowerment and confidence as well as overall functioning among veterans who participated in Vet-to-Vet as compared to veterans who had not participated in the program.  Their 2010 investigation reported that almost 88% of their sample drawn from an observational study had participated in Vet-to-Vet prior to the study period and approximately 50% attended at least one session during the study period.  Predictors of attendance included attending Vet-to-Vet prior to study enrollment, ongoing participation in the concurrent day program following completion of the study, lower recovery orientation, lower activities of daily living and older age (Resnick & Rosenheck, 2010). 

The present study expanded on these findings by a) examining attendance in both peer- and clinician-led recovery-oriented groups in the context of a randomized study, b) examining differences in attendance between peer-led (Vet-to-Vet) and clinician-led groups, and c) identifying predictors of attendance in both peer-led and clinician-led groups.

This investigation is part of a randomized study of a recovery-oriented group intervention led by either peer facilitators (Vet-to-Vet; Resnick, Armstrong, Sperrazza, Harkness, & Rosenheck, 2004), or by clinicians.  The intervention supplemented participants’ individualized treatment plans, which they continued during the 3-month study period.  Participants completed a baseline assessment (including a structured diagnostic interview) at enrollment and a follow-up assessment at the end of the intervention (3-months).

Eligibility criteria included being English-speaking, adult (at least 18 years old), having a mental health diagnosis, and having received mental health services through the VHA in the last 12 months.  We enrolled a convenience sample of veterans receiving mental health services from one of two participating sites. This analysis includes 198 veterans who consented to the study and were randomized to either the peer-led or clinician-led recovery groups. 

Demographic Characteristics:  Age, gender, race, employment, disability status and housing arrangements were obtained by structured interview at enrollment in the study. 

Psychological variables. We measured pre-intervention levels of hope (Snyder Hope Scale; Hope; Snyder et al., 1991), personal empowerment (Rogers Empowerment Scale; EMP; Rogers, Chamberlin, Ellison, & Crean, 1997, social support (MOS Social Support Survey; MOS; Sherbourne & Stewart, 1991), recovery (Recovery Assessment Scale; RAS; Corrigan, Giffort, Rashid, Leary, & Okeke, 1999), and patient activation (Patient Activation Measure; PAM; Hibbard, Stockard, Mahoney, & Tusler, 2004). All of these measures have demonstrated reliability and validity and most have been used in previous investigations examining recovery-oriented groups (e.g., Cook et al., 2009).

Mental Health and Substance Abuse Status. The pre-intervention (baseline) assessment included the following self-report measures of mental health symptoms and problems as well as substance use: Behavior and Symptom Identification Scale (BASIS-24, Eisen, Normand, Belanger, Spiro, & Esch, 2004), Veterans Short Form of the SF-12 (VR-12) from which we derived the Physical (PCS) and Mental (MCS) Component Scores (Kazis et al., 2004), Alcohol Use Disorders Identification Test, (AUDIT, Saunders, Aasland, Babor, De La Fuente, & Grant, 2006); Drug Abuse Screening Test; (DAST, Cocco & Carey, 1998).  Each of these measures has demonstrated reliability and validity and has been used extensively with veterans for both research and clinical purposes.  In addition to these self-report measures we assessed lifetime psychiatric diagnoses using the mood, anxiety, psychotic, and substance use disorder modules from the Structured Clinical Interview for DSM-IV Diagnosis (SCID-I, First, Spitzer, Gibbon, & Williams, 1997), from which we created four dichotomous variables indicating presence or absence of diagnoses in each of these categories.

Treatment Utilization. Participants self-reported their VA and non-VA care in the 3 months prior to study enrollment, including inpatient and outpatient mental health treatment, transportation difficulties regarding getting to treatment, and prior utilization of peer support.

Attendance.  The dependent variable was the total number of study-related groups attended during the 3-month study period, ranging from 0-12.

Sample Recruitment. Veterans were informed about the study via fliers posted in clinic waiting areas and presentations at community meetings within mental health programs at each site.  Veterans who expressed interest were given detailed information about the study by study personnel. All those who agreed to participate signed a written informed consent form approved by their VAMC’s Institutional Review Board (IRB).  After signing consent, the research interviewer informed the veteran which study arm s/he was randomized to, and told them when and where the group met.  Randomization was done separately by site to equalize randomization at each site.  Veterans were not paid for group attendance, but they were paid for up to $60 total for study assessments.  Attendance rosters were collected from the group leaders after every meeting.  Veterans were not considered ‘drop-outs’ unless they formally requested to be withdrawn from the study, which occurred in only two cases.  Rather, since attendance was the dependent (outcome) variable in this study, no attendance was considered a valid outcome. 

Sites. The study was conducted at two large VAMCs in the Northeast.  Veterans were recruited from several programs at Site 1, including a structured residential program, a day treatment program, an outpatient mental health clinic, a long-term inpatient unit, several community residential care (CRC) homes, and a state-run residence for veterans.  Recruitment at Site 2 was conducted at a VA Community Care Center, which provides a range of psychosocial, medical and educational services.  These two sites were selected for the study because they each have extensive, well-established recovery-oriented mental health services. 

Recovery Groups. The peer-led and clinician-led groups shared many features.  All  groups (i.e., Peer and Clinician at Site 1 and 2) met at least weekly for 45 minutes, were recovery-oriented, with a focus on psychosocial rehabilitation and community integration.  The peer-led groups used the Vet-to-Vet model.  They were led by two peer facilitators who received training regarding implementation of the Vet-to-Vet model.  In addition, they had weekly supervision and ongoing evaluation by both a professional and a peer supervisor.  Peer facilitators were other veterans in treatment for a mental illness.  As peer providers, they are encouraged to share their personal experiences during group meetings.  Peer facilitators were paid as independent contractors; thus they were not VA employees.  The peer-led (Vet-to-Vet) groups followed an established curriculum using recovery-focused written materials, such as the Recovery Workbook (Spaniol, Koehler, & Hutchinson, 1994), or Pathways to Recovery (Ridgway, McDiarmid, Davidson, Bayes & Ratzlaff, 2002).  Each meeting focused on a different workbook chapter introduced by the facilitators and following a read and discuss format in which facilitators and participants discuss the topic and share their experiences.  Examples of workbook chapters included managing life’s stresses, building personal support, setting personal goals, and recognizing strengths. Clinician-led groups were led by a master’s level mental health clinician.  Some of the clinician-led group leaders chose to use the same recovery-focused written materials as were used by the peer facilitators, although this was not required.  However, all clinician-led groups followed a recovery-oriented model focused on enhancing interpersonal and functional skills.  Although both Vet-to-Vet and clinician led groups were structured around recovery issues, they are not “manualized” therapies in which the precise contents of each session are documented in a manual; consequently, the content of each group could vary from week to week. 

Two major differences between the Vet-to-Vet and clinician-led groups were expectations regarding sharing/disclosure of personal information, and clinical training.  Peer leaders of the Vet-to-Vet groups were expected to share their own experiences with group participants, whereas clinician leaders were not.  Clinician group leaders have professional clinical training, whereas peer leaders have a much briefer training program, which is however, followed up with continued training and ongoing supervision.  Of course, peer leaders also have personal experience as both a veteran and a person with a serious mental illness.  

Site 1 had 4 clinician-led groups and 4 Vet-to-Vet groups which ran over a 2-year period, but ended when the last study participants completed their 3-month follow-up assessments because research grant funds used to pay the peer facilitators were depleted.  Site 2 had 1 rolling, clinician-led group and 5 rolling Vet-to-Vet groups over the course of the study.

Data Analysis
Data analyses were performed using SAS (SAS Institute Inc, 2008) and SPSS (SPSS Inc, 2009).  Self-report measures were scored using each measure’s published algorithms.  First, we computed descriptive statistics to examine attendance patterns for the sample as a whole and divided by study arm (clinician- vs. peer-led).  Second, we used negative binomial regression to assess association between type of group (peer- vs. clinician-led) and attendance.  Negative binomial regression is appropriate for this analysis because attendance is a count variable and because of the relatively large number of cases who did not attend any groups (Hilbe, 2007).  To identify predictors of attendance, and whether predictors might differ for peer- vs. clinician-led groups, we regressed attendance on each patient characteristic alone and in interaction with type of group (peer- vs. clinician-led). However, since none of the interactions with type of group were significant, we computed bivariate correlations to examine the relationship between participant characteristics and attendance (i.e., pearson correlations or point biserial correlations when one of the variables is binary).  Variables that were significant at p<.05 were entered into a negative binomial mixed-model regression to examine unique predictors of attendance. 

Sample Characteristics
As expected in a population of veterans, the majority of the sample were males (92%).  Average age was 52 + 10 years; 53% had some post-high school education.  Approximately one-quarter (28%) of the participants were non-Caucasian and 10% were Hispanic/Latino.  Mood disorders, substance use disorders and post-traumatic stress disorder (PTSD) or other anxiety disorders were all highly prevalent, occurring in more than 50% of study participants.  There were no statistically significant differences between study arms (peer- vs. clinician-led) in demographic characteristics, diagnosis category, or any of the T1 self-report measures with the exception of self-reported drug use (Peer-led group reported significantly higher use than the Clinician-led group; F(1,197)=5.64, p=0.0185).  Table 1 presents the sample characteristics.

Table 1.
Participant Characteristics















Age (years)


52 + 10









American Indian


African American/Black

Pac Islander











High School diploma or less

More than High School diploma






Relationship status





Never married









Lives alone




Has no source of social support




Has independent housing




Has paid job




Receives disability








Psychological  Characteristics












Patient activationa






163.6 (20.9)


Social Supporta








Mental Health/Substance Use Status and Diagnoses




Physical health (PCS, VR-12)a




Mental health (MCS, VR-12)a




Behavior and symptoms (BASIS-24)b




Alcohol Use (AUDIT)b




Drug Use (DAST-10)b




SCID-I  Diagnosis

Mood Disorder

PTSD/Other Anxiety Disorder

Psychotic Disorder

Substance Use Disorder












Treatment Use in 3 Months Before Study Entry




Outpatient medical care




Emergency medical care




Inpatient medical care




Outpatient mental health care




Emergency mental health care




Inpatient mental health care




Outpatient substance abuse treatment




Substance abuse detoxification




Inpatient substance abuse treatment




Stayed overnight for treatment




Problem getting to treatment (i.e., transportation problems)

Big Problem

Small Problem







Ever used mental health peer support services?




Ever used addiction peer support services?




Ever used other peer support services?




Note. aHigher scores are better; bLower scores are better; cMultiple responses accepted

Attendance at Recovery-Oriented Groups
Across the full sample participants attended an average of 3.8 + 4.3 groups over the 12 week study period.  Approximately one-quarter (26.5%) of the sample did not attend any study-related groups.  There was no significant difference in attendance by type of group with veterans assigned to peer-led groups attending 3.8 + 4.6 groups and veterans assigned to clinician-led groups attending 3.8 + 3.9 groups.  Since there were no group differences, attendance is presented for both groups combined (Figure 1). 

Predictors of Attendance.

The following baseline variables were significantly positively correlated with attendance (p<.05): older age, higher education, better mental health (MCS), more Hope and Psychotic Disorder diagnosis.  The following variables were significantly negatively correlated with attendance: emergency and inpatient mental health care, outpatient, detoxification, and inpatient substance abuse treatment, AUDIT and DAST scores,  any inpatient treatment in the past 3 months, and transportation difficulties getting to treatment (Table 2). Site was also a significant predictor of attendance. 

The following significant predictors were entered into a negative binomial regression model: age, education, overnight treatment, difficulty getting to treatment, AUDIT, DAST, Hope, MCS, SCID psychotic disorder diagnosis and site.  Because of high correlations between the AUDIT, DAST and substance abuse treatment variables, as well as between inpatient and emergency treatment we excluded the substance abuse and inpatient/emergency treatment variables from the regression model to minimize the impact of multicollinearity.

In the final model only age, education, AUDIT score, and site remained as significant predictors of attendance (see Table 2).  Older age and more education predicted better attendance.  Higher levels of alcohol use assessed by the AUDIT predicted lower attendance.  In addition, attendance was higher at Site 1 than Site 2.

Table 2. Association between Variables and Group Attendance


Correlation with attendance

F-value from final model


















Relationship Status



Lives Alone



Has no source of social support



Has independent housing



Has Paid Job



Receives Disability Income






Psychological  Characteristics



















Mental Health/Substance Use Status and Diagnoses















SCID-I  Diagnosis

Mood Disorder

PTSD/Other Anxiety Disorder

Psychotic Disorder

Substance Use Disorder












Treatment Use in 3 Months Before Study Entry

Outpatient medical care



Emergency medical care



Inpatient medical care



Outpatient mental health care



Emergency mental health care



Inpatient mental health care



Outpatient substance abuse treatment



Substance abuse detoxification



Inpatient substance abuse treatment



Stayed overnight for treatment



Transportation problem getting to treatment



Ever used mental health peer support services?



Ever used addiction peer support services?



Ever used other peer support services?





Study Characteristic





Note. *p<0.05, **p<0.01, HOPE=Snyder Hope Scale; EMP=Rogers Empowerment Scale; RAS=Recovery Assessment Scale; PAM=Patient Activation Measure; BASIS-24= 24-item Behavior and Symptom Identification Scale; PCS=Physical Component Score of VR-36; MCS=Mental Component Score of VR-36; AUDIT=Alcohol Use Disorders Identification Test; DAST=Drug Abuse Screening Test

This study examined attendance and predictors of attendance in peer-led and clinician-led groups within the VHA.  Although attendance levels were modest for both types of groups they were higher than that reported by Resnick and Rosenheck (2010), in which only 51.5% went to a group during their study period (though 87% had attended at least one Vet-to-Vet meeting before study entry).  Our investigation of potential predictors of attendance identified only age, education, AUDIT score, and site as statistically significant.  Older age, lower AUDIT scores, and higher level of education was associated with increased attendance, which is consistent with findings from Resnick and Rosenheck’s (2008) quasi-experimental study and (2010) investigation of Vet-to-Vet attendance, as well as several other studies (DiNitto et al., 2001; Laudet et al., 2003; Luke et al., 1993; Ogrodniczuk, Piper, & Joyce, 2006; Yanos et al., 2001).

Though unexpected, site was a significant predictor of attendance, with veterans at Site 1 attending an average of 5.3 groups in comparison to 2.2 groups at Site 2.  There were several site differences (e.g., in sample characteristics, facilitators and clinical programs) that could account for this effect.  Examination of demographic and clinical characteristics between participants at the two sites showed differences in race (higher percentage African-American at Site 2 than Site 1), Hispanic ethnicity (higher percentage of Hispanic veterans at Site 2), gender (more females at Site 2), recent substance use (more substance use at Site 2), and service use in the previous 3 months (higher level of service usage at Site 2).  This last finding is of interest as Site 2 reported higher level of service usage but attended fewer groups.  This may be consistent with the findings of Zemore and Kaskutas (2008), who noted in their investigation of day-hospital and residential programs, that attendance varied at curricular vs. extra-curricular (non-prescribed groups) as a function of type/intensity of current treatment.   As AUDIT score varied between site and also predicted attendance, it may be that self-reported alcohol use partially accounts for the site difference in attendance.  However, there may be other program characteristics and unmeasured site characteristics which also partially account for the site differences. 

The fact that only four variables remained as significant predictors, raises questions as to what other factors might predict attendance.  Participant satisfaction with the groups, cultural sensitivity of offerings, utilization of other treatment modalities, number of concurrent groups being attended, and engagement in other structured activities (e.g., work) could also be examined as possible predictors of attendance.  Furthermore, there is some evidence from the addiction literature that research should be addressing level of participation, rather than attendance, as a predictor of outcome (Weiss et al., 2005).

Strengths and Limitations
There are a number of strengths to this investigation.  First, the previous literature has been vague about participation rates in recovery-oriented services and our study design allowed us to systematically track and report attendance.  Second, although there is a growing body of literature on peer support services, this is the first randomized study examining peer-led versus clinician-led recovery-oriented groups for veterans with a mental illness.  Third, our study measured several patient-level factors, including demographics, psychological factors, mental health status, and treatment utilization variables, allowing us to investigate a wide range of possible predictors of attendance.

This study also has limitations.  First, there is an inherent paradox between the idea of a randomized clinical trial in which participants agree to attend whatever intervention is part of the randomized trial, and the ideals of personal empowerment and self-determination that are integral components of recovery-oriented mental health services.  Clinicians tend to assume that more treatment (i.e., higher attendance) is better than less treatment, whereas empowered consumers may prefer and benefit from less intervention.  A second limitation is that the study was conducted at only two sites in one region of the country and the sample was largely composed of middle-aged veterans who were longstanding recipients of VA mental health care.  Replication of these results with younger veterans and in a national sample would greatly enhance their generalizability.  Third, given the relatively short time frame of the study and the generally low attendance levels, it was not feasible to examine attendance patterns beyond the total number of groups attended during the study period.  It is possible that there are different predictors of attendance among those who attend a few groups and do not return versus those individuals who attend few groups at first, but more later on.  Finally, assessment of specific clinic and group leader characteristics might also be useful in understanding factors that affect attendance.

Future directions and clinical implications
The randomized study, of which this investigation is a component, is attempting to learn more about the content and outcome of recovery-oriented mental health groups.  Given the findings from this analysis, future work should focus in on mechanisms to increase motivation for treatment and also identification of appropriate treatment modalities. Though group leaders may often search for patient characteristics to explain non-attendance, one potentially obvious, but possibly overlooked, explanation may be that poor attendance is associated with the group not meeting patients’ needs (e.g., McKisack & Waller, 1996).  Alternatively, given that higher levels of education were predictive of increased attendance, it may be that a brief educational orientation to recovery-focused services may aid consumers in making an educated decision regarding the value of adding recovery-focused groups to their treatment plan. Pretherapy orientation has been shown to improve attendance at traditional psychotherapy groups (e.g., France & Dugo, 1985; Sheeran, Aubrey, & Kellett, 2007).  Finally, given that veterans have a choice between clinician-led and peer-led groups at their treatment facilities, future research might want to offer them an option to attend either and examine patterns of attendance when both  modalities are available. Beyond examination of attendance or adherence to recommended treatment interventions, recovery-focused, patient-centered care should continue to explore the kinds and quantities of services desired or preferred by consumers, as well as the links between services and clinical outcomes.



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