Does the Assessment of Recovery Capital scale reflect a single or multiple domains?

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 lif

Stability of the alcohol use disorders identification test in practical service settings

Ethan Sahker,1,2 Donna A Lancianese,1 Stephan Arndt1,3,4 1Iowa Consortium for Substance Abuse Research and Evaluation, 2Counseling Psychology Program, Department of Psychological and Quantitative Foundations, College of Education, 3Department of Psychiatry, Carver College of Medicine, 4Department of Biostatistics, College of Public Health, University of Iowa, Iowa City, IA, USA Objective: The purpose of the present study is to explore the stability of the Alcohol Use Disorders Identification Test (AUDIT) in a clinical setting by comparing prescreening heavy drinking questions and AUDIT scores over time. Because instrument stability is equal to test–retest reliability at worst, investigating the stability of the AUDIT would help better understand patient behavior change in context and the appropriateness of the AUDIT in a clinical setting.Methods: This was a retrospective exploratory analysis of Visit 1 to Visit 2 AUDIT stability (n=1,099; male [75.4%], female [24.6%]) from all patients with first-time and second-time records in the Iowa Screening, Brief Intervention, and Referral to Treatment project, October 2012 to July 7, 2015 (N=17,699; male [40.6%], female [59.4%]).Results: The AUDIT demonstrated moderate stability (intraclass correlation=0.56, 95% confidence interval: 0.52–0.60). In a multiple regression predicting the (absolute) difference between the two AUDIT scores, the participants’ age was highly significant, t(1,092)=6.23, p<0.001. Younger participants clearly showed less stability than their older counterparts. Results are limited/biased by the observational nature of the study design and the use of clinical service data.Conclusion: The present findings contribute to the literature by demonstrating that the AUDIT changes are moderately dependable from Visit 1 to Visit 2 while taking into account patient drinking behavior variability. It is important to know the stability of the AUDIT for continued use in Screening, Brief Intervention, and Referral to Treatment programming. Keywords: SBIRT, measurement, alcohol use, heavy drinking, service dat

Personalized prediction of Alzheimer's disease and its treatment effects by donepezil: an individual participant data meta-analysis of eight randomized controlled trials

Background:Patient characteristics may predict the progression of Alzheimer’s disease (AD) and may moderate the effects of donepezil. Objective:To build a personalized prediction model for patients with AD and to estimate patient-specific treatment effects of donepezil, using individual patient characteristics. Methods:We systematically searched for all double-masked randomized controlled trials comparing oral donepezil and pill placebo in the treatment of AD and requested individual participant data through its developer, Eisai. The primary outcome was cognitive function at 24 weeks, measured with the Alzheimer’s Disease Assessment Scale-cognitive component (ADAS-cog). We built a Bayesian meta-analytical prediction model for patients receiving placebo and we performed an individual patient data meta-analysis to estimate patient-level treatment effects. Results:Eight studies with 3,156 participants were included. The Bayesian prediction model suggested that more severe cognitive and global function at baseline and younger age were associated with worse cognitive function at 24 weeks. The individual participant data meta-analysis showed that, on average, donepezil was superior to placebo in cognitive function (ADAS-cog scores, –3.2; 95% Credible Interval (CrI) –4.2 to –2.1). In addition, our results suggested that antipsychotic drug use at baseline might be associated with a lower effect of donepezil in ADAS-cog (2.0; 95% CrI, –0.02 to 4.3). Conclusion:Although our results suggested that donepezil is somewhat efficacious for cognitive function for most patients with AD, use of antipsychotic drugs may be associated with lower efficacy of the drug. Future research with larger sample sizes, more patient covariates, and longer treatment duration is needed

Assessment of blinding in randomized controlled trials of antidepressants for depressive disorders 2000–2020: a systematic review and meta-analysis

Background In double-blind randomized controlled trials (RCTs) of antidepressants, blinding can be broken due to the apparent side effects, and unsuccessful blinding can lead to overestimation of effect sizes. New generation antidepressants with less severe side effects may be less susceptible to broken blinding. However, successfulness of blinding in new generation antidepressant trials and its influence on trial effect size estimates remain unclear. Methods Extending a previous systematic review assessing blinding successfulness in psychiatric trials (2000-2010), we searched PubMed/Medline for double-blinded antidepressant RCTs (2010-2020) for trials assessing blinding success. Our primary outcome was the degree of blinding successfulness, measured as kappa statistics between guesses and true allocations. We used random-effects meta-analysis to synthesize studies. We used meta-regression and Pearson's r to examine the relationship between blinding success and effect sizes. This study is registered with PROSPERO (CRD42021249973). Findings Among 154 eligible studies, 11 (7·1%) contained information on blinding assessment between 2010 and 2020. Five studies were added from the previous review, and altogether nine of the 16 studies provided usable data. Agreement in individual studies ranged from κ=-0·14 to 0·38. The summary agreement between guesses and the truth was 0·21 (95% CI: 0·14 to 0·28) among patients and 0·17 (95% CI: 0·05 to 0·30) among assessors. Blinding success was not associated with effect size (patients: r = 0·37, p = 0·32; assessors: r = 0·28; p = 0·72). Meta-regression also failed to find a significant relationship between blinding success and depression effect sizes (β=0·06, p = 0·09). Interpretation Less than 10% of the antidepressant RCTs reported blinding assessment. The results in new generation antidepressant trials indicated that patients and assessors were unlikely to be able to judge treatment allocation. There was little evidence that the extent of unblinding biased the effect size estimates of new generation antidepressants