Glucofit: A pilot study evaluating a brief action planning intervention in individuals with type 2 diabetes following a community-based physical activity program
Bibliographic record
Abstract
There is a need to support physical activity (PA) participation among people with type 2 diabetes mellitus (DM). The Health Action Process Approach (HAPA) provides a framework for interventions; post-intentional factors which can translate intentions into behaviour are considered. Consistent with HAPA, action planning is one strategy that improves self-efficacy (SE) and hence which may support PA among people with DM. This pilot study evaluates the effects of a brief action planning (BAP) intervention among people with DM diabetes attending a community PA program. Adults with DM (n=22) recruited through a community PA program completed baseline measures of the HAPA constructs and self-reported PA. Participants engaged in supervised PA twice per week for 3 months. They received four weeks of BAP via telephone delivered by a BAP counselor once per week. Questionnaires were re-administered following the BAP. Ten (45.5%) participants completed the BAP calls. Paired t-tests revealed significant improvements in maintenance SE (p=.05) and task SE (p=.04) following BAP; there were trends toward improvements in planning SE (p=.15) and action control (p=.19). Overall PA was maintained post-BAP (p=.92), with a trend towards increases in low-intensity PA (p=.61). Findings from this pilot study suggest that BAP may be useful to improve maintenance SE for PA and maintain PA among people with DM following a community PA program. Further research with a larger sample is warranted to further understand the impact of BAP in supporting PA among people with DM.Acknowledgments: Centre for Collaboration, Motivation and Innovation (CCMI), Tait McKenzie Centre and the Tri-Lab
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".