Abstract
Recovery Dharma is a Buddhist-inspired mutual-aid recovery program for those with substance use disorders and behavioral addictions. The program combines meditation, emotion regulation techniques, literature, and Buddhist practices during meetings to help people achieve emotional balance and improve their well-being. Despite the growing popularity of Recovery Dharma, how the practices in this program predict recovery resources remain largely unknown. We conducted a study investigating whether mindfulness and difficulty regulating emotions can predict individuals’ recovery capital - a construct strongly correlated with positive recovery outcomes. Recovery Dharma members (n = 122; 88% White; 45% women) completed two online surveys six months apart. We conducted hierarchical linear regressions and found that mindfulness predicted unique variability in recovery capital. However, our final model that included difficulty regulating emotions explained a significantly larger portion of variability above and beyond demographic variation and mindfulness. In an exploratory analysis, we found that difficulty regulating emotions predicted recovery capital as a unidimensional construct, not any particular subconstruct. The results suggested that Recovery Dharma members’ emotion regulation skills were the strongest predictor of positive recovery outcomes, surpassing demographic characteristics and mindfulness. As such, the intentional cultivation and improvements in emotion regulation skills inherent in Buddhist practices within the Recovery Dharma framework may indicate positive long-term recovery outcomes.
Disclosure statement
Vanessa Wang holds volunteer position as board of director on Recovery Dharma Global (RDG). All remaining authors certify that they have no conflicts of interest to report.
Correction Statement
This article has been corrected with minor changes. These changes do not impact the academic content of the article.
Notes
1 We employed several strategies to identify potential bots during the data collection and cleaning. These strategies included regular monitoring during data collection for patterns that might indicate bot responses in the data, a time check for the minimum survey completion time (bots complete surveys faster than humans) during data cleaning, a comparison of IP addresses to determine if multiple responses came from the same computer. Additionally, the platform we used to collect our data (Qualtrics) is widely used in academia and has security measures that help deter bot responses.
2 Note that mindfulness, r = .272, p = .002, and DRE, r = -.431, p < .001, are predicted by recovery capital; however, these relationships are relatively equal to or weaker than mindfulness, r = .353, p < .001, and difficultly regulating emotions, r = -.396, p < .001, predicting recovery capital. Thus, there is a degree of bidirectionality to these relationships.
3 The increase in mindfulness and decrease of DRE in T2 supports the current literature that mindfulness is associated with decreased psychological distress and DRE with decreased quality of life (Conversano et al. Citation2020; Panayiotou et al. Citation2021). This finding may potentially indicate the effectiveness of the RD recovery approach. Future research may investigate the effectiveness of mindfulness and DRE in reducing psychological distress and addiction severity. However, this is out of the scope of this study and the hypothesis.
4 There were no assumption violations, including multivariate outliers, multivariate normality, nonlinearity, heteroskedasticity, and multicollinearity. To enhance the reproducibility and reduce the sample size limitations, we used bias-corrected and accelerated bootstrapping with 1000 simulated samples.
5 We did not add a covariate for 12-step involvement because previous and concurrent recovery efforts involve a large number of strategies, such as SMART, LifeRing, Women for Sobriety, Celebrate Recovery, Alcoholics for Christ, Moderation Management, harm reduction, professional therapy or counseling, medication-assisted, and self-help. We also did not find evidence of its covariation with mindfulness, ps > .200, DREs, ps > .733, or recovery capital, ps > .228, at either T1 or T2.
6 We initially aggregated race into a binary variable, with non-White people in a person of color group compared to a White group for statistical analyses due to the low representation of non-White individuals and to preserve power. The demographic variables in the model were not significant in any of the steps during the HLR, and there was no difference between completers and non-completers. Thus, we removed the use of the race variable in the study because such an aggregate method is inappropriate (Frey Citation2023).
7 Demographic variables did not predict recovery capital in any step in the HLR, so we removed them from this follow-up analysis. These analyses did not violate any assumptions.