Barriers to Exercise in Adults With Type 1 Diabetes and Insulin Resistance
Bibliographic record
Abstract
OBJECTIVE: Our aim in this study was to assess attitudes toward exercise and quality of life (QoL) in adults with type 1 diabetes (T1D) with and without insulin resistance (IR). METHODS: We pooled baseline pretreatment data from a subset of individuals with T1D from 2 randomized controlled trials. Estimated glucose disposal rate (eGDR), a validated surrogate marker of IR, was calculated using an established formula to classify individuals according to IR status with a cutpoint of <6 mg/kg/min for the determination of IR. Self-reported barriers to exercise were obtained using a validated questionnaire, the Barriers to Physical Activity in T1D (BAPAD-1). In addition, QoL was determined using the 36-item Short Form (SF-36) questionnaire. Differences between dichotomized variables were assessed using the independent t test, Mann-Whitney U test, or Fisher exact test. Linear regression was employed to explore the association of eGDR with BAPAD-1 and QoL scores, with sequential adjustment for potential confounders. RESULTS: Of the 85 individuals included in our study, 39 were classified as having IR. The mean BAPAD-1 total score was higher for individuals with IR (IR: 3.87±0.61; non-IR: 2.83±0.55; p<0.001). The highest exercise barrier scores for individuals with IR were risk of hypoglycemia (5.67±1.26) and risk of hyperglycemia (5.23±1.20), whereas the highest scoring exercise barrier scores for non-IR individuals were not diabetes-related, with low level of fitness (3.91±1.26) and physical health status, excluding diabetes (3.67±1.48), ranked highest. QoL scores were comparable between groups (p>0.05). CONCLUSIONS: Risk of hypoglycemia was the greatest barrier to exercise in individuals with T1D with IR, whereas non-diabetes-related barriers to exercise were more salient in individuals with T1D without IR.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".