VCOM Carolinas Research Day 2023

Biomedical Studies

Assessing the Effects of Recovery Capital on Substance Use Treatment Outcomes Trevor C. Doane, OMS III, Brett Cohen, OMS III, James Headid, OMS III, Emma Smith, OMS III, Alexis Stoner, PhD, MA, David Redden PhD Edward Via College of Osteopathic Medicine, Spartanburg, SC

Abstract # BIOM-2

Abstract

Methods

Conclusions

Background: Relapse prevention is both a short term and long term goal of substance abuse recovery and has been shown to be positively associated with recovery capital. Recovery capital is defined as the collection of one’s resources that contribute to the initiation and maintenance of sobriety. Adverse childhood experiences (ACE) are traumatic events that have been well documented as having a correlation with worse health outcomes including higher rates of drug use and addiction. Hypothesis: The aim of this paper is to identify components of recovery capital that deter or encourage positive treatment outcomes and determine if treatment models aimed at increasing recovery capital lead to improved recovery outcomes. Materials and Methods: Demographic information collected before and after program completion by a South Carolina residential recovery center whose treatment model focuses on enabling participants to attain recovery capital were analyzed, and statistical analyses were performed to determine the effects of recovery capital on treatment outcomes. Additionally, self reported data on adverse childhood experiences were collected. Results: Analyses did not provide statistically significant evidence of a difference between the ACE scores of individuals who completed the program and those who did not. There was no statistically significant difference in any individual components of recovery capital between those who completed the program and those who did not although a limitation was that recovery capital as an aggregate was not analyzed. Conclusion: Further work is currently underway to increase the power of the study by enrolling more participants to correct the possibility of a type 2 error; the studied factors may be associated with completing the program but the effect size for those associations are small to medium and a larger sample size is required to detect and declare those associations statistically significant. The study could also indicate that the variables investigated were not associated with completion of the program but other variables yet to be identified are. Illicit drug use disorders are common, with a lifetime prevalence of 2-3%, and increase the risk of hospitalization, adverse health effects and death with over 100,000 fatal overdoses occurring in 2021 (Merikangas & McClair, 2012, CDC 2022). However, treating substance abuse remains a challenge as many individuals struggle to maintain sobriety after completing treatment. One factor may be recovery capital defined as the collection of one’s resources that contribute to the initiation and maintenance of sobriety (Cloud and Granfield, 2008.) Things such as employment, housing, financial assets, family support, etc. would all be examples of a person’s recovery capital. Go Forth is a male only residential recovery center in Spartanburg that focuses on enabling participants to accrue recovery capital while in the program through classes as well as program requirements. Our research aims to answer two primary questions. First, does the Go Forth recovery model, which includes life skills training, lead to improved recovery outcomes? Secondly, by focusing on components of recovery capital, can risk factors and protective factors that have a direct impact on treatment outcomes and sobriety maintenance be identified? Introduction

Study Population: The sample population for our study included individuals at a local South Carolina residential recovery center called Go Forth Recovery. The total sample size for our study consisted of 44 program participants. A unique aspect of the Go Forth model is that all residents are male. Therefore, all 44 subjects in our study were male. Go Forth accepted individuals addicted to alcohol, opiates, cocaine, methamphetamine, marijuana and benzodiazepines. Patients were often using more than one substance prior to treatment. Materials: Demographic and recovery capital information was collected for each program participant at the time of admission to Go Forth, and again following program completion. The data forms accessed are incorporated into the Go Forth resident database, and information was transferred to an excel sheet to allow for easier statistical analysis. Any potential identifying information for our subjects in the data was de-identified. Data Collection: The initial demographic and recovery capital information for each participant was collected at the time of arrival at Go Forth as a part of their intake process. This information served as a baseline for each resident prior to the individual going through the treatment process. To collect the post-treatment data, a Go Forth program director contacted former participants and gathered the same types of information that were collected at intake. For our study, we focused primarily on the initial intake data collected. This allowed us to focus on the impact that recovery capital possessed prior to treatment had on treatment outcomes. Statistical Analysis: Analyses began by summarizing continuous variables, such as age and ACE scores, using sample means and variances. Categorical variables, such as completion status of Go Forth participation and race, were summarized using proportions. Inferential procedures examined which characteristics might be associated with completion of the Go Forth program. Of the 44 individuals for which we have data, 34 completed the program, 7 were deceased, and 3 were dismissed. This distribution, specifically the small sample size for dismissed, limited the number of analytic approaches that could be employed. Due to sample sizes, we collapsed deceased and dismissed into one combined category, using Fisher’s Exact test for to test for association between categorical variables and Wilcoxon Rank Sum for testing whether a continuous variable, such as age or ACES scores, differed between groups (completers vs deceased/dismissed). Two sample t-tests were avoided due to the small sample size and normal probability plots indicating potential non-normality. All tests were conducted using SAS 9.4

The present research addresses a gap in literature by investigating a male only residential recovery clinic focused on building recovery capital through life skills training, employment and forging social connections in addition to maintaining sobriety. ACE Scores • There was no statistically significant difference in ACE scores between individuals who completed the program and those who did not. • ACE scores have been well established in the literature as being associated with higher rates of drug abuse and addiction, but the impact of ACE scores on recovery has been less studied (Dube et al 2003, Felitti et al 1998). • These results suggest that GoForth’s unique style of recovery focused on recovery capital may be effective across a range of ACE scores, even higher ACE scores that are typically associated with higher rates of relapse (Derefinko et al 2019) Recovery Capital • No individual element of recovery capital was a predictor of successful completion of the GoForth program. • Grouped assessment of recovery capital was a better predictor of whether an individual would complete the program. However, the difference still did not rise to the level of statistical significance at (p = 0.200) when including a faith home in recovery capital. Limitations • The primary limitation in our study was the small sample size of our population which limited the power of the study. A second limitation is that incarceration rate was not compared between those completing the program and those who did not. Incarceration may be a confounding variable that impacts the attainment of recovery capital. Next Steps • Data collection is ongoing to increase the sample size and study power. When all data is gathered further analysis will be performed examining incarceration status, drug used and comparing completion rates to other facilities.

Results

Table 1. Differences in Recovery Capital Possessed by Graduates and Nongraduates of GoForth Recovery Program

References

Acknowledgements

Analyses did not provide statistically significant evidence of a difference in the distribution of ACES scores between completers and those who did not complete GoForth ( p = 0.550). No individual element of recovery capital was statistically significant although having a family connection (p = 0.566) and access to a faith home (p = 0.417) were the strongest predictors of completing the program. Access to a vehicle was actually a negative predictor of completing the program although this still did not rise to the level of statistical significance (p = 0.515). As expected, the grouped assessment of recovery capital was a better predictor of whether an individual would complete the program. However, the difference still did not rise to the level of statistical significance at (p = 0.200) when including a faith home in recovery capital and (p = .450) when a faith home was not included as part of recovery capital.

The authors would like to thank Nick Wildrick for his help in collecting as well as his dedication to helping others through his work at GoForth Recovery.

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