Peer-Delivered Cognitive Behavioral Training to Improve Functioning in Patients With Diabetes: A Cluster-Randomized Trial
Bibliographic record
Abstract
<h3>PURPOSE</h3> Cognitive behavioral therapy (CBT)–based programs delivered by trained community members could improve functioning and pain in individuals who lack access to such programs. We tested the effectiveness of a peer-delivered diabetes self-management program integrating CBT principles in improving physical activity, functional status, pain, quality of life (QOL), and health outcomes in individuals with diabetes and chronic pain. <h3>METHODS</h3> In this community-based, cluster-randomized controlled trial, intervention participants received a 3-month, peer-delivered, telephone-administered program. Attention control participants received a peer-delivered general health advice program. Outcomes were changes in functional status and pain (Western Ontario and McMaster Universities Osteoarthritis Index), QOL (Short Form 12), and physiologic measures (hemoglobin A<sub>1c</sub>, systolic blood pressure, body mass index); physical activity was the explanatory outcome. <h3>RESULTS</h3> Of 195 participants with follow-up data, 80% were women, 96% African Americans, 74% had annual income <$20,000, and 64% had high school education or less. At follow-up, compared with controls, intervention participants had greater improvement in functional status (–10 ± 13 vs –5 ± 18, <i>P</i> = .002), pain (–10.5 ± 19 vs –4.8 ± 21, <i>P</i> = .01), and QOL (4.8 ± 8.8 vs 3.8 ± 8.8, <i>P</i> = .001). Physiologic measures did not change significantly in either group. At 3 months, a greater proportion of intervention than control participants reported no pain or did other forms of exercise when pain prevented them from walking for exercise. <h3>CONCLUSION</h3> This peer-delivered CBT-based intervention improved functioning, pain, QOL, and self-reported physical activity despite pain in individuals with diabetes and chronic pain. Trained community members can deliver effective CBT-based interventions in rural and under-resourced communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".