Trial reportPloS one2020
Variability in engagement and progress in efficacious integrated collaborative care for primary care patients with obesity and depression: Within-treatment analysis in the RAINBOW trial.
Trial report in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT02246413 (RCT on Co-management of Obesity, Depression, and Elevated CVD Risk in Primary Care-- Engaging Self-regulation Targets to Understand the Mechanisms of Behavior Change and Improve Mood and Weight Outcomes), which is not on this map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
RCT on Co-management of Obesity, Depression, and Elevated CVD Risk in Primary Care-- Engaging Self-regulation Targets to Understand the Mechanisms of Behavior Change and Improve Mood and Weight Outcomes
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Integrated Behavioral Interventions for Adults with Comorbid Obesity and Depression: a Systematic Review.Current diabetes reports · 2022Pooled it
- Depression and weight loss trajectories during an integrated behavioral intervention: Within-treatment analysis of the RAINBOW trial.PloS one · 2025Trial
- Sex Moderates Treatment Effects of Integrated Collaborative Care for Comorbid Obesity and Depression: The RAINBOW RCT.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2021Trial
- Trial
- Understanding mechanisms of integrated behavioral therapy for co-occurring obesity and depression in primary care: a mediation analysis in the RAINBOW trial.Translational behavioral medicine · 2021Trial
- Trial
- The ENGAGE-2 study: Engaging self-regulation targets to understand the mechanisms of behavior change and improve mood and weight outcomes in a randomized controlled trial (Phase 2).Contemporary clinical trials · 2020Trial
- Review
- Change in suicidal ideation, depression, and anxiety following collaborative care in the community.BMC primary care · 2024Article
- Developing weight navigation program to support personalized and effective obesity management in primary care settings: protocol for a quality improvement program with an embedded single-arm pilot study.Primary health care research & development · 2022Article
- Seeking a pot of gold with integrated behavior therapy and research to improve health equity: insights from the RAINBOW trial for obesity and depression.Translational behavioral medicine · 2021Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
14 authors.
Funding
Abstract
introductionThe 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.
methodsData 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.
resultsAmong 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.
conclusionsParticipants 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 registrationClinicalTrials.gov# NCT02246413.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.