Abstract
Background:
Mutual-help alternatives for addiction are numerous, and research attests to the benefits of involvement in such alternatives. Yet, virtually nothing is known about affiliation patterns over time among 12-step alternatives. We investigated the patterns, correlates, and outcomes of transitions in affiliation (including changing groups and dropping out) within alternatives for alcohol problems.
Methods:
We analyzed data from the Peer ALternatives for Addiction (PAL) Study, a longitudinal study comparing the nature and effectiveness of 12-step groups, WFS, LifeRing, and SMART (N=647). First, using all data, we compared affiliation patterns over time across 12-step and 12-step alternative members at baseline. Second, analyzing exclusively 12-step alternative members at baseline, we compared baseline characteristics and 6-month outcomes of those who changed and dropped out of (vs. retained) their primary groups at 6 months.
Results:
While drop-out rates were low, and similar, across groups, members of the alternatives were more likely (vs. 12-step) to change groups at 6 months, and transitioned predominantly to 12-step. Further, among the 12-step alternatives, both changing groups and dropping out was associated with lower group cohesion and satisfaction. Meanwhile, in multivariate analyses of 6-month outcomes, changing (vs. retaining) groups robustly predicted lower cohesion, higher negative affect, and lower quality of life, whereas dropping out was associated with lower odds of alcohol abstinence.
Conclusions:
While dropping out is known to be risky, changing groups is more common among the 12-step alternatives, and connotes risk of future problems that may be partially explained by dissatisfaction with the new group (usually 12-step).
Keywords: Mutual-help alternative, 12-step groups, Group affiliation, Group transition, Peer support, AUD
1. Introduction
1.1. Research on mutual-help group alternatives
Mutual-help groups are the most common form of help received among those receiving any help for an alcohol use disorder (AUD), and are broadly effective for supporting recovery from AUD1,2 Prior studies have substantiated the effectiveness of the 12-step approach to recovery in particular3–9. However, 12-step participation remains limited. For example, Kelly and Moos (2003)10, studying a Veterans’ Administration substance use treatment sample, found that 40% of participants who had attended 12-step groups during the 3 months prior to baseline had discontinued attendance at 1-year follow-up. More strikingly, Project MATCH found that 37% of substance use treatment participants receiving 12-step facilitation reported no meeting attendance during the 6 months after treatment, and another 26% reported less than weekly attendance11. Such high drop-out rates, reported even in the context of effective 12-step facilitation, suggest that alternatives to the 12-step approach are necessary. Findings that very few (8%) of those with an AUD seek any help within a given year10 and that there are many viable pathways to recovery11 also underline the need—and potential—for diverse options that can attract and help a wide spectrum of the population.
Currently, people have many mutual-help options that differ from the 12-step approach and have unique philosophical underpinnings. In 1975, 40 years after Alcoholics Anonymous (AA) was founded, the first secular alternative to 12-step emerged: Women for Sobriety (WFS)12. WFS’ emergence created a new pathway for the 12-step alternatives movement. Since then, many other secular alternatives have arisen, including the American Atheists Alcohol Recovery Group, in 1980; Secular Organization for Sobriety (SOS), in 1985; Rational Recovery, in 1986; Smart Recovery (SMART), in 1994; Moderation Management, in 1994; and LifeRing Secular Recovery (LifeRing), in 199911. The rise of these alternatives challenges the notion that the predominant 12-step model is a “one size fits all” solution.
In contrast to the numerous studies of 12-step groups, studies of 12-step alternatives for alcohol problems remain scarce. The most recent study of 12-step alternatives, called the Peer ALternatives for Addiction (PAL) Study13,14, was the first longitudinal, comparative survey of 12-step groups and the largest known secular, abstinence-based 12-step alternatives now available (i.e., WFS, LifeRing, and SMART); all participants reported a lifetime AUD. Analyses of the baseline data14 compared demographic and clinical characteristics of members of the alternatives to members of 12-step groups1 In comparison to 12-step group members, members of all alternatives were less religious; members of WFS and LifeRing were also older, and members of SMART and LifeRing were less likely to endorse a total abstinence goal. Additional analyses of the 6- and 12-month follow-up data13 examined the efficacy of mutual-help alternatives compared to 12-step groups. Results revealed that when controlling for alcohol recovery goal, higher primary group involvement2 was strongly associated with better outcomes regardless of group choice, including higher odds of abstinence from both alcohol and all substances across follow-ups. Thus, involvement in any of the studied groups provided similar benefits for resolving substance use and problems. The PAL Study has deepened understanding of secular 12-step alternatives as a potentially effective resource and raised important questions for future research.
1.2. The current study
The current study presents further analyses of the PAL Study data, and focuses on affiliation patterns (including retaining the same primary group, changing groups, and dropping out) across mutual-help groups over time. This investigation makes a key contribution because no known studies have addressed affiliation patterns among the 12-step alternatives over time, and because a better understanding of affiliation can inform providers as they assist clients in navigating the potential risks and benefits of affiliating or disaffiliating with mutual help groups.
Our two main aims were: (1) using the full sample (i.e., members of 12-step groups and the alternatives), to examine patterns of group affiliation over time (i.e., retaining one’s primary group, changing affiliation to any group at all, and dropping out), and (2) targeting 12-step alternatives only, to identify (a) factors that predict 6-month group affiliation status as well as (b) associations between 6-month affiliation status and participant outcomes at 6 months. We focused on the 12-step alternatives only for Aim 2 because it would be inappropriate to combine 12-step groups and 12-step alternatives for analysis, and because the number of participants who were affiliated with a 12-step group and then changed affiliations at 6 months was far too small (N=6) to permit an analysis analogous to that conducted on the 12-step alternative sample. Outcomes were assessed at 6 (not 12) months because the 6-month analysis is more consistent with our expectation that any effects for changes in affiliation would be immediate, not lagged. This expectation reflects findings that the most proximal indicators of 12-step involvement are typically the strongest predictors of recovery outcomes13,15,16. Further, <50% of the baseline sample had data at all waves, making analysis including all waves less reliable and more biased. However, we also include a sensitivity analysis with 12-month outcomes.
Aim 1 contributes to the literature by describing how affiliation patterns differ across 12-step groups and the alternatives. We hypothesized that (1) members of the 12-step alternatives would be more likely than 12-step members to change (vs. retain) their primary group over time, and that most of those changing groups among the 12-step alternatives would transition to 12-step groups. This hypothesis derives from the fact that in-person meeting availability is relatively limited among the alternatives: Reports indicate over 61,000 in-person AA meetings across the U.S17 compared to about 62 WFS, 163 LifeRing, and 1063 SMART meetings14. Relatedly, Zemore et al. (2017)14 reported that those who identified a mutual-help alternative as their primary group attended considerably fewer in-person meetings in the past month (averaging 4.4–5.3) than did 12-step members (at 12.6).
Aim 2 deepens the knowledge base on potential causes and consequences of changing groups and dropping out among the mutual help alternatives. For Aim 2(a), we conducted exploratory analyses of baseline3 correlates of 6-month affiliation status (again, retained one’s primary group, changed groups, or dropped out). For Aim 2(b), we examined associations between 6-month affiliation status (as above) and primary group cohesion, mental health, quality of life, and alcohol abstinence, also assessed at 6 months. We hypothesized that (2) changing (vs. retaining) one’s primary group would be associated with lower primary group cohesion at follow-up, considering the 12-step alternatives only. This is because a recent transition in groups would suggest little time to bond with those attending the new primary group. (Drop-outs have no primary group to rate on cohesion so no hypothesis is offered.)
Relatedly, we hypothesized that (3) both changing groups and dropping out (vs. retaining one’s primary group) would be associated with poorer mental health and quality of life at follow-up, again considering the 12-step alternatives only. This is because less bonding with a support group may imply lower social support, and because lower social support has been related to worse mental health, greater vulnerability to the negative effects of stress, and lower quality of life18–20. Finally, we hypothesized that (4) both changing groups and dropping out (vs. retaining one’s primary group) would be associated with lower odds of alcohol abstinence at follow-up, again considering the 12-step alternatives only. Abstinence rates can be expected to be lower among drop-outs because drop-outs no longer receive the benefits of mutual help involvement, and among both groups because of the predicted negative effects of group transitions on social support, mental health, and quality of life (detailed above), all of which are important to recovery21–26. Also, studies of 12-step groups have found that longer durations of attendance are associated with better abstinence outcomes even controlling for current attendance27,28, whereas changing affiliations necessarily shortens duration of attendance. This paper also includes an analysis of open-ended questions on what participants liked and disliked about their primary groups at 6 months. Our informal interactions with attendees suggested that people may change affiliations for a large variety of reasons.
2. Materials and methods
2.1. Sample recruitment and characteristics
The Peer Alternatives in Addiction (PAL) Study is a longitudinal study with three waves of data collection incorporating online surveys of 12-step, WFS, LifeRing, and SMART attendees. Surveys measured mutual-help participation; substance use; psychiatric and clinical variables; and demographics. Sample characteristics are generally similar to those of samples obtained via groups’ membership surveys14.
Baseline respondents were recruited in 2015 via collaboration with the Executive Directors of WFS, LifeRing, and SMART; LifeRing’s Board Chair; SMART’s President; and IntheRooms, an online meeting hub for those in recovery with a 12-step focus. Participants were required to be at least 18; be a U.S. resident; report a lifetime AUD; and report attending at least one in-person 12-step, WFS, LifeRing, or SMART meeting for alcohol/drug use in the past 30 days. Interested parties were directed to a study webpage, where they completed screening, and only eligible participants were advanced to the baseline survey. Baseline data were then subjected to extensive cleaning procedures to eliminate fraudulent cases. Participants with valid responses were recontacted to complete 6-month follow-ups, which were further inspected for major inconsistencies. This yielded final Ns of 647 at baseline, and 526 at 6 months (an 81% response rate)13,14.
2.2. Measures
2.2.1. Primary group affiliation at baseline and 6 months
Both baseline and 6-month surveys evaluated past-30-day meeting participation for each group under study. For respondents who indicated attendance at only one group, that group was coded as their “primary group;” those who indicated attending numerous groups were asked to (and did) identify a primary group. A three-level variable (“6-month affiliation status”) was used to code whether participants retained their primary groups, changed to another group, or dropped out at the 6-month survey.
2.2.2. Baseline predictors of changes in primary group affiliation
Basic demographic characteristics.
Baseline surveys assessed gender, age, marital status, race/ethnicity, religious self-identification, and socioeconomic status (i.e., education, annual household income, and employment status).
Alcohol recovery goal.
Baseline surveys included a single question29 asking participants to choose the one alcohol recovery goal that was most true for them at that time; response options ranged from total lifetime abstinence to controlled use. We dichotomized responses into two categories: lifetime total abstinence or another goal.
Primary group cohesion and satisfaction.
We utilized an adapted, 5-item version of the Cohesion Subscale of the Curative Climate Instrument30,31 to evaluate sense of cohesion with one’s primary group (baseline α=0.93). Participants were also asked to rate satisfaction with their primary groups on a scale from 0 (not at all) to 10 (completely).
Primary group involvement.
Current involvement in one’s primary group was assessed using a 5-item scale adapted from a standard 12-step involvement scale32. Items assessed number of in-person meetings attended in the past month and other aspects of involvement (e.g., sponsor or close friend in the group, home or regular group). Responses were recoded and averaged (baseline α’s=0.90–0.93 across groups). We also assessed number of lifetime 12-step meetings attended.
Lifetime and current alcohol, drug, and psychiatric severity.
We used 18 items adapted from the Alcohol Section of the CIDI33 to assess DSM-5 AUD symptoms34 in the lifetime and past year. We also used the 15-item Short Index of Alcohol Problems (SIP)35,36 to assess current alcohol problem severity (baseline α = 0.88) and 2 yes/no items drawn from prior scales assessing DSM-5 criteria37,38 to assess lifetime and past-year drug problems. Lifetime psychiatric severity was assessed using a 4-item scale including questions on prior mental health diagnosis, treatment, and medications (baseline α=0.76), and current psychiatric severity was assessed with an item from the Addiction Severity Index soliciting number of the past 30 days that participants were troubled by mental health problems39.
2.2.3. 6-month outcomes of changes in affiliation
Primary group cohesion and psychiatric problems.
Current mutual-help group cohesion and psychiatric problems at 6 months were assessed using the same measures as used at baseline.
Negative affect.
Negative affect in the past month was measured by an adapted version of the Positive And Negative Affect Schedule (PANAS-Short Form)40 assessing frequency of feeling upset, hostile, ashamed, sad, nervous, depressed, hopeless, and afraid (6-month α =0.91).
Quality of Life.
Current quality of life (QOL) was assessed by a question (“How would you rate your quality of life?”) drawn from the World Health Organization’s Quality of Life Scale41. Response options ranged from 0 (very poor) to 5 (very good).
Alcohol abstinence.
Alcohol abstinence at 6 months was assessed using a single item soliciting the last time participants had any alcohol. Participants answering “more than 6 months ago” were coded as abstinent, and all others were coded not abstinent.
2.2.4. Open-ended questions
Participants were asked two questions about what they liked and did not like about their current primary group at 6 months.
2.3. Analysis
For Aim 1, we used the full sample and examined overall patterns of group transition and drop-out. We first conducted descriptive analyses examining primary group affiliation (i.e., 12-step, WFS, LifeRing, SMART, or none) at baseline and 6 months. Next, to test Hypothesis 1 (regarding differences in affiliation patterns across members of the 12-step alternatives and 12-step groups), we used Chi-square tests comparing rates of a) changing (vs. retaining) one’s primary group and b) dropping out of (vs. retaining) one’s primary group at 6 months across those choosing a 12-step alternative (vs. 12-step) at baseline.
For Aim 2, we targeted exclusively those choosing a 12-step alternative as their primary group at baseline. As an exploratory analysis, we examined baseline correlates of 6-month affiliation status using bivariate tests of association (i.e., Chi-square tests, t-tests). To test Hypotheses 2, 3, and 4, we examined associations between 6-month affiliation status and 6-month outcomes (including primary group cohesion, psychiatric problems, negative affect, quality of life, and alcohol abstinence) using multivariate logistic and linear regressions. Baseline demographics, clinical variables, and 6-month primary group involvement were included as covariates in any models where they predicted the outcome at p<.05. We controlled for 6-month mutual help involvement in order to distinguish the effects of transitions in group affiliation from any associated differences in mutual help involvement, as prior PAL analyses13 showed that lower mutual help group involvement was associated with worse outcomes. If the outcome variables were measured at baseline, we also included these measures as covariates. Sequential models were used throughout: In Model 1, we entered only 6-month affiliation status; in Model 2, we added baseline demographics and clinical variables; and in Model 3, we added 6-month primary group involvement. As a sensitivity analysis, parallel models using the same controls, along with 12-month affiliation status, were used to predict 12-month outcomes. All analyses were implemented in SPSS Version 1842. For the open-ended questions, we categorized answers to questions on what participants liked as positive responses and answers to questions on what they disliked as negative responses. Then, using thematic analysis43, we extracted the main emergent themes (e.g. availability, fellowship, and program).
3. Results
3.1. Transitions between groups in the full sample
Table 1 shows baseline and 6-month primary group affiliation for all groups. While most people retained the same primary group across 6 months, a large minority changed groups or attended none (i.e., “dropped out”). Drop-out rates ranged from 8.1% for LifeRing to 10.3% for SMART, and dropping out (vs. retaining one’s primary group) was equally common among all the 12-step alternatives, compared to 12-step. However, partially as hypothesized, rates of changing (vs. retaining) groups over time were significantly higher for members of WFS (at 11.0%) and SMART (at 13.2%), and nonsignificantly higher for LifeRing (at 10.3%), vs. 12-step members (at 3.8%). As hypothesized, most of those who changed groups from a 12-step alternative to another group transitioned to a 12-group.
Table 1:
Transitions in primary group affiliation across 6 months (N=526).
| Primary Group Affiliation (PGA) at 6 months (N=526) | |||||||
|---|---|---|---|---|---|---|---|
| N | % 12-step | % WFS | % LifeRing | % SMART | % Nonea | % Total Changing Groupsb | |
| 12-step PGA @ baseline | 158 | 86.1 | 1.3 | 0 | 2.5 | 10.1 | 3.8 |
| WFS PGA @ baseline | 145 | 6.2 | 80 | 0.7 | 4.1 | 9.0 | 11.0* |
| LifeRing PGA @ baseline | 87 | 5.8 | 2.3 | 81.6 | 2.3 | 8.1 | 10.3 |
| SMART PGA @ baseline | 136 | 11 | 1.5 | 0.7 | 76.5 | 10.3 | 13.2** |
Pearson chi-square test for the rates of having no PGA at 6 months (vs. retaining groups at 6 months) across each mutual help alternative, compared to 12-step at baseline.
Pearson chi-square test for the rates of changing baseline primary group at 6 months (vs. retaining groups at 6 months) across each mutual help alternative, compared to 12-step at baseline.
p<0.05,
p<0.01,
p<0.001
3.2. Associations between 6-month affiliation status and baseline variables among the 12-step alternatives
Table 2 displays associations between 6-month affiliation status and baseline demographics among the 12-step alternatives only. Results show that people who changed (vs. retained) their primary groups were younger, more likely to identify as “spiritual,” and less likely to identify as “non-spiritual.” Additionally, people in the change group were less likely than those retaining a primary group to be Caucasian. There were no significant demographic differences between those who dropped out (vs. retained) their primary groups, except that drop-outs were more likely to be upper-middle-income.
Table 2:
Baseline demographics by 6-month affiliation status in the PAL sample, including only those choosing a 12-step alternative as their primary group at baseline (N=368).
| Retain group (N=291) | Change group (N=43) | Dropout group (N=34) | |
|---|---|---|---|
| Gender | |||
| % Female | 61.5 | 62.8 | 67.6 |
| Age | |||
| Mean (SD) | 52.6 (12.2) | 46.9 (14.0)** | 49.9 (12.4) |
| Marital status | |||
| % Single | 17.6 | 18.6 | 11.8 |
| % Sep./Wid./Divorced | 25.5 | 27.9 | 38.2 |
| % Married/Partnered | 56.9 | 53.5 | 50.0 |
| Race/Ethnicity | |||
| % White | 92.4 | 81.4* | 94.1 |
| % Non-White | 7.60 | 18.6 | 5.90 |
| Religious self-identification | |||
| % Religious | 12.2 | 14.0 | 20.6 |
| % Spiritual | 30.2 | 51.2** | 38.2 |
| % Non-spiritual | 57.6 | 34.9** | 41.2 |
| Education | |||
| % High school diploma or less | 23.4 | 26.2 | 23.5 |
| % Bachelor’s or AA degree | 41.6 | 54.8 | 47.1 |
| % Post-graduate training or degree | 35.1 | 19.0 | 29.4 |
| Annual household income | |||
| % $30,000 or less | 18.6 | 23.3 | 21.9 |
| % $30,001–60,000 | 28.0 | 34.9 | 9.40* |
| % $60,001–100,000 | 17.6 | 25.6 | 34.4* |
| % $100,000 plus | 35.8 | 16.3 | 34.4 |
| Employment status | |||
| % Employed full/part-time | 61.7 | 62.8 | 67.6 |
| % Unemployed | 4.8 | 7.0 | 11.8 |
| % Other | 33.4 | 30.2 | 20.6 |
Note. All comparisons are to the “retain group”.
p<0.05,
p<0.01,
p<0.001.
Table 3 shows associations between 6-month affiliation status and baseline clinical variables, again among the 12-step alternatives only. Results show that people who changed (vs. retained) primary groups were lower on primary group cohesion and satisfaction at baseline, though equivalent on primary group involvement. Additionally, the change group reported a higher mean number of lifetime 12-step meetings, more past-year AUD symptoms, and higher SIP scores than the retain group. Those dropping out were lower (vs. those retaining affiliations) on primary group cohesion and satisfaction, past-month in-person meeting count, and primary group involvement.
Table 3:
Baseline clinical variables by 6-month affiliation status in the PAL sample, including only those choosing a 12-step alternative as their primary group at baseline (N=368).
| Retain group (N=291) | Change group (N=43) | Dropout group (N=34) | |
|---|---|---|---|
| Current recovery goal | |||
| % Endorsing lifetime total abstinence | 58.0 | 62.8 | 48.5 |
| Current primary group cohesion and satisfaction | |||
| Mean (SD) group cohesion score (1–5) | 4.47 (0.56) | 4.12 (0.78)*** | 3.90 (0.87)** |
| Mean (SD) group satisfaction score (0–10) | 9.13 (1.09) | 8.60 (1.59)* | 8.56 (1.66)* |
| Current primary group involvement | |||
| Mean (SD) past-month in-person meetings, logged (0–4.51) | 1.55 (0.65) | 1.54 (0.99) | 0.73 (0.62)*** |
| Mean (SD) past-month online meetings | 2.70 (14.0) | 3.43 (7.63) | 1.97 (4.27) |
| Mean (SD) composite group involvement (0–1) | 0.71 (0.26) | 0.61 (0.32) | 0.36 (0.36)*** |
| Lifetime 12-step involvement | |||
| Mean (SD) lifetime 12-step meetings, logged (0–8.9) | 3.52 (1.96) | 4.74 (1.85)** | 3.27(1.78) |
| Current and lifetime alcohol problem severity | |||
| Mean (SD) lifetime AUD symptoms (2–11) | 9.22 (2.00) | 9.77 (1.69) | 8.71 (2.54) |
| Mean (SD) past-year AUD symptoms (0–11) | 3.39 (4.26) | 5.56 (4.79)** | 4.29 (4.45) |
| Mean (SD) past-year SIP (alcohol problems) score (0–1) | 0.32 (0.38) | 0.50 (0.41)** | 0.38 (0.41) |
| Current and lifetime drug problem severity | |||
| % Lifetime multiple DUD symptoms | 42.1 | 48.8 | 39.4 |
| % Past-year multiple DUD symptoms | 9.30 | 16.3 | 3.00 |
| Current and lifetime mental health (MH) severity | |||
| Mean (SD) lifetime composite MH problems (0–1) | 0.59 (0.34) | 0.67 (0.34) | 0.54 (0.35) |
| Mean (SD) days in past 30 troubled by MH problems | 5.63 (8.78) | 5.19 (7.76) | 8.12 (10.5) |
Note. All comparisons are to the “retain group”.
p<0.05,
p<0.01,
p<0.001
3.3. 6-month outcomes by 6-month affiliation status
Table 4 shows the results of multivariate models examining associations between changing and dropping out of (vs. retaining) one’s primary group and 6-month primary group cohesion, mental health outcomes, quality of life, and alcohol abstinence. As hypothesized, those who changed (vs. retained) primary groups at 6 months were significantly lower on cohesion with their new groups, higher on negative affect, and lower on quality of life, all at 6 months. These effects were somewhat diminished, though still significant, when comprehensively adjusting for baseline covariates (as in Model 2), and unaffected by adding 6-month primary group involvement (as in Model 3). Associations between changing (vs. retaining) groups and both psychiatric problems and alcohol abstinence were significant in Model 1, but adjusting for baseline covariates (as in Model 2) rendered these effects non-significant. Dropping out of (vs. retaining) one’s primary group was associated with only one outcome (i.e., lower alcohol abstinence) in Model 1. This association remained robust when controlling for baseline covariates (Model 2) and was explained by the lack of mutual help group involvement among drop-outs (Model 3).
Table 4:
Multivariate regression models of 6-month outcomes by 6-month affiliation status, including only those choosing a 12-step alternative as their primary group at baseline.
| Model 1 | Model 2 | Model 3 | |
|---|---|---|---|
| Primary group cohesionA | (N=331) | ||
| Standardized β | Standardized β | Standardized β | |
| Change (vs. Retain) group | −0.34*** | −0.20*** | −0.20*** |
| Dropout (vs. Retain) group | - | - | - |
| Psychiatric problemsB | (N=350) | ||
| Standardized β | Standardized β | Standardized β | |
| Change (vs. Retain) group | 0.12* | 0.08 | 0.08 |
| Dropout (vs. Retain) group | 0.00 | −0.01 | −0.01 |
| Negative affectB | (N=348) | ||
| Standardized β | Standardized β | Standardized β | |
| Change (vs. Retain) group | 0.21*** | 0.14** | 0.14** |
| Dropout (vs. Retain) group | 0.02 | 0.00 | −0.003 |
| Quality of life (QOL)B | (N=350) | ||
| Standardized β | Standardized β | Standardized β | |
| Change (vs. Retain) group | −0.21*** | −0.10* | −0.09* |
| Dropout (vs. Retain) group | −0.06 | −0.04 | 0.01 |
| Alcohol abstinenceC | (N=356) | ||
| OR | OR | OR | |
| Change (vs. Retain) group | 0.51* | 0.53 | 0.58 |
| Dropout (vs. Retain) group | 0.38* | 0.36* | 1.02 |
Note. Model 1 is a bivariate model entering 6-month affiliation, and Model 2 controls for baseline age, gender, marital status, employment status, past-12-month AUD symptoms, past-12-month multiple drug problems, past-12-month specialty substance abuse treatment, lifetime psychiatric severity, and outcome-specific controls (i.e., baseline primary group cohesion for the cohesion model A; baseline annual household income, current psychiatric problems, and QOL for the mental health models B; and baseline recovery goal for the abstinence model C). Model 3 adds 6-month primary group involvement.
p<0.05,
p<0.01,
p<0.001
Table A (see Supplementary Materials) presents our analyses with 12-month outcomes, which used similar predictor variables as in Table 4. The only significant finding was that changing (vs. retaining) groups at 6 months was associated with higher negative affect at 12 months.
3.4. Open-ended questions
We asked participants who changed their primary groups at 6 months to relate what they liked and disliked about their current primary group. We analyzed only the answers of those who switched to 12-step groups from the alternatives (N=29), as the number of people switching from one alternative to another was too small for analysis. Most (59%) reported mixed answers, citing both positive and negative aspects of their 12-step group at 6-month follow-up. However, of these 59%, about 18% cited the availability of meetings (e.g., “it can be found anywhere,” “there are so many meetings it is easy to fit a couple in my schedule”) as the only positive aspect. Another 10% reported negative aspects only, even though they chose 12-step as their primary group. A small minority (24%) reported positive aspects only, and 7% did not respond. Regarding what participants disliked most, 55% answered that they did not like the 12-step philosophy or approach, citing for example the “religious aspect of the program,” “concept of powerlessness,” “pressure to speak and do service work,” and “sponsorship.” Only 17% reported liking the 12-step program per se. The most common positive aspects cited were the feeling of fellowship (e.g., “makes you feel like part of a family,” “the social support,” “cohesiveness of the group”), mentioned by 31% of respondents, and availability, as noted, mentioned by 24% of respondents.
4. Discussion
4.1. Summary of results and main conclusions
This study’s primary goal was to evaluate transitions in group affiliation status, and their possible effects on outcomes, among those who attend the12-step alternatives for alcohol problems. The study promotes understanding of potential causes and consequences of transitions in affiliation over time among the mutual-help alternatives, a topic not studied in any known publication.
As hypothesized, results showed that members of 12-step alternatives were more likely to change affiliation than 12-step members, and they switched predominantly to 12-step. Further, several baseline differences emerged between those who retained, changed, and dropped out of their primary groups at 6 months. Namely, people in the change group were younger, were more spiritual, and had more lifetime 12-step experience (vs. the retain group), which may suggest that 12-step is a relatively good fit for such individuals. In fact, many of those who changed groups could be said to have returned to 12-step. Further analyses (not shown) showed that among all members of 12-step alternatives who changed groups, 65% both had prior 12-step experience and transitioned to a 12-step group. In other findings, those changing (vs. retaining) primary groups were (at baseline) lower on primary group satisfaction and cohesion; equivalent on mutual-help involvement; and higher on AUD severity. Thus, people in the change group participated intensively in their original groups despite relatively low satisfaction and cohesion, perhaps because their needs for mutual support were high. Supporting this reasoning, prior studies have consistently shown that higher AUD severity predicts higher 12-step group involvement44–46. Our qualitative findings similarly suggest a strong need for mutual support in this group: Over half of those who had changed to 12-step groups cited “meeting availability” or “fellowship” (i.e., support from others) as a positive aspect of 12-step groups. Dropouts were distinguished from those retaining their primary group affiliations mainly by lower group satisfaction, cohesion, and involvement at baseline.
Affiliation groups also differed on outcomes at 6-month follow-up. As expected, changing (vs. retaining) groups was strongly associated with lower group cohesion at 6 months. This may suggest that changing affiliations was not wholly successful in cementing supportive mutual-help networks, though it could be that cohesion and satisfaction would be higher some months or years in the future. We also predicted that the poor social networks resulting from group transitions would result in poorer mental health, quality of life, and thus alcohol abstinence. As expected, multivariate results suggested that changing (vs. retaining) primary groups was strongly associated with higher negative affect and lower quality of life at 6 months, while it was not associated with abstinence. However, odds ratios were consistent with negative effects for all outcomes. Contrary to expectations, there were no effects for dropping out (vs. retaining one’s primary group) on any 6-month outcomes except a strong negative effect on odds of abstinence; this effect was robust to all baseline confounds (ORs for Model 1=.38, Model 2=.36) and completely accounted for by the lack of mutual help involvement among drop-outs at 6 months (OR=1.02). These results provide further evidence of the potential benefits of mutual help involvement in sustaining good substance use outcomes.
Qualitative results shed some light on why changing (vs. retaining) groups predicted poorer functioning across several domains at follow-up, and suggest that changing affiliations was often driven more by necessity than by a strong preference for 12-step. Over half of those who changed from a 12-step alternative to a 12-step group reported that they did not like aspects of 12-step’s philosophy or approach, despite transitioning to a 12-step group. Further, meeting availability was commonly cited as a positive attribute of 12-step groups. This may imply that lack of meeting availability among the 12-step alternatives drives some, and especially those with high need for support, to transition to 12-step groups even despite lack of fit with 12-step philosophy and members.
4.2. Study limitations
As discussed previously14, a significant study limitation is that we cannot establish a baseline response rate, and thus cannot guarantee the representativeness of our mutual-help group samples. However, as the baseline data showed, our samples were very similar to samples obtained via internal surveys conducted by AA, WFS, LifeRing, and SMART14.
A second limitation is the small sample sizes available for individual groups. In consequence, we had to combine AA, NA, CA and MA for all analyses and WFS, SMART, and LifeRing for some analyses, despite likely differences across groups. Relatedly, low power might have made it difficult to detect relationships between affiliation status and study outcomes.
Third, the simultaneous measurement of 6-month primary group affiliation and outcomes suggests caution in inferring causality, particularly since the 12-month analysis differed somewhat. Although we assessed outcomes at 6 and not 12 months for both theoretical and empirical reasons, stricter temporal lagging between the independent and dependent variables would provide a cleaner interpretation surrounding causality.
Last, in each of the three PAL surveys (baseline, 6 months, and 12 months), a significant minority (10–18%) of participants reported attending a 12-step group along with a 12-step alternative, and others (3–5%) reported attending multiple 12-step alternatives. Although analyzing these respondents is outside the scope of the current study, future studies might address the potential benefits and downsides, if any, of attending multiple groups simultaneously.
4.3. Conclusions
Our findings highlight potential causes and effects of transitions in group affiliation among mutual-help alternatives for addiction, about which very little is known. Findings suggest that, for those attending a 12-step alternative for an alcohol problem, changing groups is relatively common and may often be driven more by the need for enhanced support than by the desire for a different group philosophy or approach. Relatedly, changing groups among attendees of the 12-step alternatives may create worse, not better, group cohesion, mental well-being, and quality of life. Meanwhile, dropping out may connote higher risk for maintaining abstinence, but not for poorer functioning in other areas.
Additional studies are needed both to better understand how those who cannot obtain sufficient help from mutual-help alternatives may be supported, and to track participants over longer time periods toward confirming and extending the present findings. In the meantime, clinicians should be aware that clients with more severe substance use problems may not get the intensive support they need from 12-step alternatives, due to low meeting availability, and that these clients may need extra emotional support and guidance in finding appropriate meetings. For example, clinicians might encourage clients to try a range of 12-step meetings to obtain a better fit, or to try maintaining affiliation with a 12-step alternative while also attending 12-step meetings. Online participation may also be helpful.
Supplementary Material
Highlights.
Changing groups was more common among members of the 12-step alternatives than 12-step members
Most members of the 12-step alternatives who changed groups transitioned to 12-step
Among the alternatives, both changing groups and dropping out was associated with lower group satisfaction and cohesion
Dropping out was associated with lower odds of alcohol abstinence at follow-up
Changing groups predicted lower group cohesion, higher negative affect, and lower quality of life at follow-up
Acknowledgements
This research was funded by a grant from the National Institute on Alcohol Abuse and Alcoholism of the National Institutes of Health (R21AA022747). The survey was conducted with the assistance of our collaborators, including Becky Fenner (Executive Director for Women for Sobriety); Byron Kerr and Robert Stump (Board Chair and Executive Director of LifeRing, respectively); Tom Horvath and Shari Allwood (President and Executive Director of SMART, respectively); Ronald Tannebaum and Kenny Pomerance (Co-Founders of IntheRooms.com); Shelley Osborn and Deborah Krug (the project management team at ICF International), and Deidre Patterson (Research Associate of the Alcohol Research Group). Dr. Timko was funded by a VA HSR&D Senior Research Career Scientist Award (RCS 00-001).
Role of Funding Sources This research was funded by a grant from the National Institute on Alcohol Abuse and Alcoholism of the National Institutes of Health (R21AA022747). Dr. Timko, one of the authors of this research, was funded by a VA HSR&D Senior Research Career Scientist Award (RCS 00-001). NIAAA and VA HSR&D had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Conflict of Interest All authors declare that they have no conflicts of interest.
We use the term “members” as a convenient shorthand to refer to all attendees of a give group who, if also attending another mutual help group, designate that group as their primary group. We acknowledge that not all such attendees may consider themselves members of that group.
“Involvement” refers to meeting attendance and participation in other aspects of involvement (e.g., having a sponsor or close friend in the group, having a home or regular group).
“Baseline” is defined here as the study baseline, not the participant baseline; participants are not necessarily new to their groups.
References
- 1.Dawson DA, Grant BF, Stinson FS, Chou PS. Maturing out of alcohol dependence: the impact of transitional life events. J. Stud. Alcohol March 2006;67(2):195–203. [DOI] [PubMed] [Google Scholar]
- 2.Edlund MJ, Booth BM, Han X. Who seeks care where? Utilization of mental health and substance use disorder treatment in two national samples of individuals with alcohol use disorders. J. Stu. Alcohol Drugs July 2012;73(4):635–646. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Kaskutas LA. Alcoholics Anonymous effectiveness: faith meets science. J. Addict. Dis 2009;28(2):145–157. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Project MATCH Research Group. Matching Alcoholism Treatment to Client Heterogeneity: Project MATCH posttreatment drinking outcomes. J. Stud. Alcohol January 1997;58(1):7–29. [PubMed] [Google Scholar]
- 5.Project MATCH Research Group. Matching Alcoholism Treatments to Client Heterogeneity: Project MATCH three-year drinking outcomes. Alcohol. Clin. Exp. Res September 1998;22(6):1300–1311. [DOI] [PubMed] [Google Scholar]
- 6.Timko C Outcomes of AA for special populations In: Galanter M, Kaskutas LA, Borkman T, Zemore SE, Tonigan JS, eds. Recent Developments in Alcoholism, Volume 18: Research on Alcoholics Anonymous and spirituality in addiction recovery. New York: Springer; 2008:373–392. [DOI] [PubMed] [Google Scholar]
- 7.Tonigan JS. Alcoholics Anonymous outcomes and benefits In: Galanter M, Kaskutas LA, Borkman T, Zemore SE, Tonigan JS, eds. Recent Developments in Alcoholism, Volume 18: Research on Alcoholics Anonymous and spirituality in addiction recovery New York: Springer; 2008:357–371. [DOI] [PubMed] [Google Scholar]
- 8.Tonigan JS, Toscova R, Miller WR. Meta-analysis of the literature on Alcoholics Anonymous: sample and study characteristics moderate findings. J. Stud. Alcohol January 1996;57(1):65–72. [DOI] [PubMed] [Google Scholar]
- 9.Ye Y, Kaskutas LA. Using propensity scores to adjust for selection bias when assessing the effectiveness of Alcoholics Anonymous in observational studies. Drug Alcohol Depend September 2009;104(1–2):56–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Grant BF, Goldstein RB, Saha TD, et al. Epidemiology of DSM-5 Alcohol Use Disorder: results from the National Epidemiologic Survey on Alcohol and Related Conditions III. JAMA Psychiatry. August 2015;72(8):757–766. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Kelly JF, White WL. Broadening the base of addiction mutual-help organizations. J. Groups Addict. Recover 2012;7(2–4):82–101. [Google Scholar]
- 12.White WL. Slaying the Dragon The history of addiction treatment and recovery in America. Bloomington, IL: Chestnut Health Publications; 1998. [Google Scholar]
- 13.Zemore SE, Lui CK, Mericle A, Hemberg J, Kaskutas LA. A longitudinal study of the comparative efficacy of Women for Sobriety, LifeRing, SMART Recovery, and 12-step groups for those with AUD. J. Subst. Abuse Treat. February 2018;88:18–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Zemore SE, Kaskutas LA, Mericle A, Hemberg J. Comparison of 12-Step groups to mutual help alternatives for AUD in a large, national study: differences in membership characteristics and group participation, cohesion, and satisfaction. J. Subst. Abuse Treat. February 2017;73:16–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Kelly JF, Urbanoski K. Youth recovery contexts: the incremental effects of 12-step attendance and involvement on adolescent outpatient outcomes. Alcohol. Clin. Exp. Res July 2012;36(7):1219–1229. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Witbrodt J, Ye Y, Bond J, Chi F, Weisner C, Mertens J. Alcohol and drug treatment involvement, 12-step attendance and abstinence: 9-year cross-lagged analysis of adults in an integrated health plan. J. Subst. Abuse Treat April 2014;46(4):412–419. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.General Services Office of Alcoholics Anonymous. AA Fact File [Accessed: 2019-03-07 Archived by WebCite® at https://www.aa.org/assets/en_US/m-24_aafactfile.pdf]2017.
- 18.Cohen S, Wills TA. Stress, social support, and the buffering hypothesis. Psychol. Bull 1985;98(2):310–357. [PubMed] [Google Scholar]
- 19.Pinquart M, Sörensen S. Influences of socioeconomic status, social network, and competence on subjective well-being in later life: a meta-analysis. Psychol. Aging 2000;15(2):187–224. [DOI] [PubMed] [Google Scholar]
- 20.Thoits PA. Mechanisms linking social ties and support to physical and mental health. J. Health Soc. Behav 2011;52(2):145–161. [DOI] [PubMed] [Google Scholar]
- 21.Groh DR, Jason LA, Keys CB. Social network variables in alcoholics anonymous: a literature review. Clin. Psychol. Rev March 2008;28(3):430–450. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Kelly JF, Stout RL, Magill M, Tonigan JS. The role of Alcoholics Anonymous in mobilizing adaptive social network changes: a prospective lagged mediational analysis. Drug Alcohol Depend April 1 2011;114(2–3):119–126. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.McLellan AT, Luborsky L, Woody GE, O’Brien CP, Druley KA. Predicting response to alcohol and drug abuse treatments: role of psychiatric severity. Arch. Gen. Psychiatry June 1983;40(6):620–625. [DOI] [PubMed] [Google Scholar]
- 24.Swendsen J, Conway KP, Degenhardt L, et al. Mental disorders as risk factors for substance use, abuse and dependence: results from the 10-year follow-up of the National Comorbidity Survey. Addiction. June 2010;105(6):1117–1128. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Saatçioğlu O, Yapici A, Çakmak D. Quality of life, depression and anxiety in alcohol dependence. Drug Alcohol Depend. 2008;27(1):83–90. [DOI] [PubMed] [Google Scholar]
- 26.Ugochukwu C, Bagot KS, Delaloye S, et al. The importance of quality of life in patients with alcohol abuse and dependence. Harv. Rev. Psychiatry 2013;21(1):1–17. [DOI] [PubMed] [Google Scholar]
- 27.Kissin W, McLeod C, McKay J. The longitudinal relationship between self-help group attendance and course of recovery. Eval. Program Plann August 2003;26(3):311–323. [Google Scholar]
- 28.Moos RH, Moos BS. Participation in treatment and Alcoholics Anonymous: a 16-year follow-up of initially untreated individuals. J. Clin. Psychol June 2006;62(6):735–750. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Hall SM, Havassy BE, Wasserman DA. Effects of commitment to abstinence, positive moods, stress, and coping on relapse to cocaine use. J. Consult. Clin. Psychol 1991;59(4):526–532. [DOI] [PubMed] [Google Scholar]
- 30.Fuhriman A, Drescher S, Hanson E, Henrie R, Rybicki W. Refining the measurement of curativeness: an empirical approach. Small Group Behav. May 1986;17(2):186–201. [Google Scholar]
- 31.Yalom ID. The Theory and Practice of Group Psychotherapy. 2nd ed. New York: Basic Books; 1975. [Google Scholar]
- 32.Humphreys K, Kaskutas LA, Weisner C. The Alcoholics Anonymous Affiliation Scale: development, reliability, and norms for diverse treated and untreated populations. Alcohol. Clin. Exp. Res August 1998;22(5):974–978. [DOI] [PubMed] [Google Scholar]
- 33.World Health Organization. Composite International Diagnostic Interview: Authorize Core Version 1.1 Geneva: World Health Organization; 1993. [Google Scholar]
- 34.American Psychiatric Association; Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5). Arlington, VA2013. [Google Scholar]
- 35.Alterman AI, Cacciola JS, Ivey MA, Habing B, Lynch KG. Reliability and validity of the alcohol short index of problems and a newly constructed drug short index of problems. J. Stu. Alcohol Drugs March 2009;70(2):304–307. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Miller WR, Tonigan JS, Longabaugh R. The Drinker Inventory of Consequences (DrInC): an instrument for assessing adverse consequences of alcohol abuse Project MATCH Monograph Series, Volume 4 (NIH Pub. No. 95–3911) [Accessed: 2015-03-03 Archived by WebCite® at http://www.webcitation.org/6Wl5CLTWX]. Rockville, MD: National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health;1995. [Google Scholar]
- 37.Borges G, Zemore SE, Orozco R, et al. Co-occurrence of alcohol, drug use, DSM-5 alcohol use disorder, and symptoms of drug use disorder on both sides of the U.S.-Mexico border. Alcohol. Clin. Exp. Res April 2015;39(4):679–687. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Saha TD, Compton WM, Chou SP, et al. Analyses related to the development of DSM-5 criteria for substance use related disorders 1. Toward amphetamine, cocaine, and prescription drug use disorder continua using Item Response Theory. Drug Alcohol Depend. April 1 2012;122(1–2):38–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.McLellan AT, Luborsky L, Cacciola JS, Griffith J. Guide to the addiction severity index: background, administration, and field testing results: Rockville, MD: U.S. Department of Health and Human Services, National Institute on Drug Abuse;1985. No. (ADM) 85–1419. [Google Scholar]
- 40.Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J. Pers. Soc. Psychol June 1988;54(6):1063–1070. [DOI] [PubMed] [Google Scholar]
- 41.The WHOQOL Group. The World Health Organization quality of life assessment (WHOQOL): position paper from the World Health Organization. Soc. Sci. Med November 1995;41(10):1403–1409. [DOI] [PubMed] [Google Scholar]
- 42.PASW Statistics 18 [computer program]. Chicago, IL: 2009. [Google Scholar]
- 43.Braun V, Clarke V. Using thematic analysis in psychology. Qual. Res. Psychol 2006;3(2):77–101. [Google Scholar]
- 44.Kelly JF, Myers MG, Brown SA. A multivariate process model of adolescent 12-step attendance and substance use outcome following inpatient treatment. Psychol. Addict. Behav December 2000;14(4):376–389. [PMC free article] [PubMed] [Google Scholar]
- 45.Emrick CD, Tonigan JS, Montgomery HA, Little L. Alcoholics Anonymous: what is currently known? In: McCrady BS, Miller WR, eds. Research on Alcoholics Anonymous: Opportunities and alternatives. New Brunswick, NJ: Rutgers Center of Alcohol Studies; 1993:41–78. [Google Scholar]
- 46.Kelly JF. Self-help for substance-use disorders: history, effectiveness, knowledge gaps, and research opportunities. Clin. Psychol. Rev October 2003;23(5):639–663. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.