Does the Assessment of Recovery Capital scale reflect a single or multiple domains?
Received 28 March 2017
Accepted for publication 15 June 2017
Published 19 July 2017 Volume 2017:8 Pages 39—43
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Amy Norman
Peer reviewer comments 2
Editor who approved publication: Professor Li-Tzy Wu
Stephan Arndt,1–3 Ethan Sahker,1,4 Suzy Hedden1
1Iowa Consortium for Substance Abuse Research and Evaluation, 2Department of Psychiatry, Carver College of Medicine, 3Department of Biostatistics, College of Public Health, 4Department of Psychological and Quantitative Foundations, Counseling Psychology Program College of Education, University of Iowa, Iowa City, IA, USA
Objective: The goal of this study was to determine whether the 50-item Assessment of Recovery Capital scale represents a single general measure or whether multiple domains might be psychometrically useful for research or clinical applications.
Methods: Data are from a cross-sectional de-identified existing program evaluation information data set with 1,138 clients entering substance use disorder treatment. Principal components and iterated factor analysis were used on the domain scores. Multiple group factor analysis provided a quasi-confirmatory factor analysis.
Results: The solution accounted for 75.24% of the total variance, suggesting that 10 factors provide a reasonably good fit. However, Tucker’s congruence coefficients between the factor structure and defining weights (0.41–0.52) suggested a poor fit to the hypothesized 10-domain structure. Principal components of the 10-domain scores yielded one factor whose eigenvalue was greater than one (5.93), accounting for 75.8% of the common variance. A few domains had perceptible but small unique variance components suggesting that a few of the domains may warrant enrichment.
Conclusion: Our findings suggest that there is one general factor, with a caveat. Using the 10 measures inflates the chance for Type I errors. Using one general measure avoids this issue, is simple to interpret, and could reduce the number of items. However, those seeking to maximally predict later recovery success may need to use the full instrument and all 10 domains.
Keywords: social support, psychometrics, quality of life
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