Literature Collection
10K+
References
9K+
Articles
1400+
Grey Literature
4500+
Opioids & SU
The Literature Collection contains over 10,000 references for published and grey literature on the integration of behavioral health and primary care. Learn More
Use the Search feature below to find references for your terms across the entire Literature Collection, or limit your searches by Authors, Keywords, or Titles and by Year, Type, or Topic. View your search results as displayed, or use the options to: Show more references per page; Sort references by Title or Date; and Refine your search criteria. Expand an individual reference to View Details. Full-text access to the literature may be available through a link to PubMed, a DOI, or a URL. References may also be exported for use in bibliographic software (e.g., EndNote, RefWorks, Zotero).
![Pubmed](/themes/custom/academy2020/images/pubmed_img.png)
![Pubmed](/themes/custom/academy2020/images/pubmed_img.png)
![Pubmed](/themes/custom/academy2020/images/pubmed_img.png)
![Pubmed](/themes/custom/academy2020/images/pubmed_img.png)
INTRODUCTION: The RAINBOW randomized clinical trial validated the efficacy of an integrated collaborative care intervention for obesity and depression in primary care, although the effect was modest. To inform intervention optimization, this study investigated within-treatment variability in participant engagement and progress. METHODS: Data were collected in 2014-2017 and analyzed post hoc in 2018. Cluster analysis evaluated patterns of change in weekly self-monitored weight from week 6 up to week 52 and depression scores on the Patient Health Questionnaire-9 (PHQ-9) from up to 15 individual sessions during the 12-month intervention. Chi-square tests and ANOVA compared weight loss and depression outcomes objectively measured by blinded assessors to validate differences among categories of treatment engagement and progress defined based on cluster analysis results. RESULTS: Among 204 intervention participants (50.9 [SD, 12.2] years, 71% female, 72% non-Hispanic White, BMI 36.7 [6.9], PHQ-9 14.1 [3.2]), 31% (n = 63) had poor engagement, on average completing self-monitored weight in <3 of 46 weeks and <5 of 15 sessions. Among them, 50 (79%) discontinued the intervention by session 6 (week 8). Engaged participants (n = 141; 69%) self-monitored weight for 11-22 weeks, attended almost all 15 sessions, but showed variable treatment progress based on patterns of change in self-monitored weight and PHQ-9 scores over 12 months. Three patterns of weight change (%) represented minimal weight loss (n = 50, linear β1 = -0.06, quadratic β2 = 0.001), moderate weight loss (n = 61, β1 = -0.28, β2 = 0.002), and substantial weight loss (n = 12, β1 = -0.53, β2 = 0.005). Three patterns of change in PHQ-9 scores represented moderate depression without treatment progress (n = 40, intercept β0 = 11.05, β1 = -0.11, β2 = 0.002), moderate depression with treatment progress (n = 20, β0 = 12.90, β1 = -0.42, β2 = 0.006), and milder depression with treatment progress (n = 81, β0 = 7.41, β1 = -0.23, β2 = 0.003). The patterns diverged within 6-8 weeks and persisted throughout the intervention. Objectively measured weight loss and depression outcomes were significantly worse among participants with poor engagement or poor progress on either weight or PHQ-9 than those showing progress on both. CONCLUSIONS: Participants demonstrating poor engagement or poor progress could be identified early during the intervention and were more likely to fail treatment at the end of the intervention. This insight could inform individualized and timely optimization to enhance treatment efficacy. TRIAL REGISTRATION: ClinicalTrials.gov# NCT02246413.
PURPOSE OF REVIEW: We review recent literature on the adaptive assessment of complex mental health disorders and provide a detailed comparison of classical test theory and adaptive testing based on multidimensional item response theory. RECENT FINDINGS: Adaptive tests for a wide variety of mental health traits (e.g., depression, anxiety, mania, substance misuse, suicidality) are now available in a cloud-based environment. These tests have been validated in a variety of settings against lengthy structured clinical interviews with excellent results and even higher reliability than fixed-length tests. Applications include screening and assessments in emergency departments, psychiatric and primary care clinics, student health clinics, perinatal medicine clinics, child welfare settings, and the judicial system. The future of mental health measurement will be based on automated screening and assessments. Adaptive tests will provide increased precision of measurement and decreased burden of measurement. Integration into the electronic health record is important and now easily accomplished.