Depressive symptoms predict non‐completion of a structured exercise intervention for people with Type 2 diabetes
Bibliographic record
Abstract
AIM: To quantify the impact of depressive symptoms on completion of exercise-based rehabilitation for Type 2 diabetes management. METHODS: Depressive symptoms were assessed using the Center for Epidemiological Studies Depression scale in a prospective cohort of consecutive patients with Type 2 diabetes entering a 6-month hybrid (home- and clinic-based) exercise rehabilitation programme. Attendance at exercise sessions was monitored and programme completion/non-completion was ascertained. RESULTS: Of the programme participants (n=624, mean age 55.6±10.5 years, 47% male), 26.8% endorsed significant depressive symptoms (depression score ≥16) and 68.1% completed the intervention, attending 54.6±30.0% of supervised exercise sessions. Baseline depressive symptoms (depression scale score ≥16) increased the risk of non-completion [hazard ratio 1.49 (95% CI 1.10-2.03); P = 0.010], and predicted fewer sessions attended (β=-2.1, P= 0.002) in adjusted models. A depression score threshold of ≥10 (48.4% of participants) predicted non-completion [hazard ratio 1.60 (95% CI 1.19-2.17); P= 0.002) with optimum accuracy. Non-completions resulting from lack of interest (18.9 vs. 11.0%; P= 0.026) and medical complications (14.6 vs. 6.6%; P= 0.006) were more common among participants with depression scores ≥10. Greater hazard ratios for depression scores ≥10 were observed in subgroups not currently using insulin [hazard ratio 1.70 (95% CI 1.24-2.33); P= 0.001), or an antidepressant [hazard ratio 1.83 (95% CI 1.32-2.54); P<0.001]. CONCLUSIONS: Depressive symptoms were highly prevalent among participants with Type 2 diabetes entering exercise-based rehabilitation, and even mild depressive symptoms posed a significant barrier to completion. Depression screening may help target additional supports to facilitate completion of exercise interventions for people with Type 2 diabetes.
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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 | 0.000 | 0.000 |
| 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".