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Original Articles

Psychometric Properties of the Assessment of Recovery Capital (ARC) Instrument in a Diverse Low-Income Sample

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Abstract

Background: Recovery capital is a theoretical construct elucidating the resources that support recovery from addiction. The 50-item Assessment of Recovery Capital (ARC) instrument and related brief-format versions are the predominant measures of this construct. However, some of the ARC’s psychometric properties are not well-established, particularly in racially and economically diverse populations. Objectives: We aimed to determine if the ARC is a valid and reliable measure of recovery capital in a diverse sample. Methods: Paper-and-pencil survey data were collected between March 2017 and May 2018 from a low-income, racially diverse sample of adults in recovery (N = 273). Participants were recruited from nontreatment community settings throughout a mid-sized northeastern U.S. city. They completed the ARC and sociodemographic questions. To determine the ARC’s reliability and factor structure, we used item-level analyses and Cronbach’s alpha, followed by confirmatory and exploratory factor analyses. Results: Several items performed poorly, having means close to response extremes and problematically small variances. Cronbach’s alpha for the full measure was α = .92; however, alphas for the majority of subscales were below .70. The a priori 10-factor model solution failed, preventing interpretation of the confirmatory factor analysis results. Exploratory factor analysis revealed that although the 10-factor model marginally fit the data, items did not load together as proposed. Not once did all five subscale items load highly on the same factor. Conclusions/Importance: The ARC has substantial weaknesses in its theoretical alignment, item performance, and psychometric properties with diverse populations. We recommend the development of a new multidimensional, theory-aligned measure, following a rigorous measurement development protocol.

Acknowledgments

We acknowledge the Buffalo Center for Social Research and the Les Brun Pilot Funding Program for supporting the study. We thank our research assistants, in particular Loriann Devito and Paige Iovine-Wong, for their instrumental role in gathering study data. Eugene Maguin provided invaluable assistance with data analysis. We thank our community partner organizations, their staff, and all study participants for making this research possible.

Declaration of interest

The authors declare that they have no conflict of interest. The authors alone are responsible for the content and writing of the article.

Additional information

Funding

This work was supported by the Buffalo Center for Social Research at the University at Buffalo School of Social Work, Les Brun Pilot Funding Program.

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