RCT of Tailored Cognitive Behavioral Intervention Reduces Regimen-Related Distress—Relationship to Change in Medication Adherence and Glycemic Control at 12-Month Follow-Up
Bibliographic record
Abstract
Elevated regimen related distress (RRD) in type 2 diabetes (T2D) is associated with poor glycemic control and lower medication adherence but the strategy for and impact of reducing RRD in primary care is unclear. Data for this study comes from a prospective randomized controlled trial that evaluated the effectiveness of a 16-session severity tailored cognitive behavioral intervention plus lifestyle change counseling (n = 67; IG=intervention group) delivered by trained staff compared to usual care (n = 72; CG=control group), in 139 rural adult patients (mean age = 52.6 ± 9.5 years.; 72% black; BMI = 37.0 ± 9.0) with uncontrolled (mean A1c = 9.6 ± 2.0) T2D (52% on insulin) and co-morbid depressive (PHQ-2) or distress (DDS-2) symptoms at screening in an academic primary care clinic. At baseline and at 12-month follow-up: A1c, regimen-related distress (sub-score of DDS-17), depressive symptoms (PHQ-9), self-care behaviors (SDSCA), and medication adherence (ModMAS) were measured using validated instruments. There were no differences between groups at baseline in mean age, race, gender, or mean values for A1c, body mass index (BMI), PHQ-9, or RRD scores. At 12-month follow-up patients in the behavioral intervention group had significantly greater reduction in RRD scores than those in the control arm (-1.12 ± 1.vs. -0.31 ± 1.22; p = 0.001). Among intervention group patients only, those with an improvement in RRD score of ≥ 1 (n = 32) had substantially greater improvement in A1c [-1.3 ± 1.7 vs. -0.56 ± 1.9; p = 0.09] and self-care behaviors [+1.33 ± 1.38 vs. + 0.88 ± 1.2; p = 0.16] as well as significantly greater improvement in medication adherence [+1.6 ± 1.7 vs. +0.47 ± 2.2; p = 0.02]. A tailored cognitive behavioral intervention reduces RRD in patients with uncontrolled T2D and co-morbid behavioral problems and is associated with improved medication adherence that may be associated with improved glycemic control. Disclosure L. Lutes: None. D.M. Cummings: None. B. Hambidge: None. M. Carraway: None. S. Patil: None. A. Adams: None. C. Solar: None. K. Littlewood: None. S. Edwards: None. P. Gatlin: None.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".