Implementing an Activity Tracker to Increase Motivation for Physical Activity in Diabetic Patients in Primary Care: a SWOT Analysis
Bibliographic record
Abstract
Abstract Objectives: To explore the feasibility of implementing an activity tracker to increase motivation for physical activity among patients with type 2 diabetes in primary care setting, and to assess patient satisfaction with this technology.Design: Mixed methods study using a satisfaction and acceptability questionnaire on an activity tracker (participants) and a questionnaire based on the SWOT (strengths, weaknesses, opportunities, and threats) analysis elements (team).Setting: Academic Primary Health Centre in Quebec City, Canada.Participants: 15 participants with type 2 diabetes who took part in the intervention group, and 7 members of the research team and health professionals who contributed to this project.Methods: Quantitative variables were expressed as mean ± standard deviation (SD). Qualitative variables from selected answers were reported in frequency tabs. Qualitative variables from open questions were synthesized in a matrix and ranked according to apparition frequency and global importance. A thematic analysis was performed by the first author and validated by two coauthors separately. The information gathered was triangulated to propose recommendations that were then approved by the team. Both quantitative and qualitative results were combined for recommendations.Main findings: In total, 86% of the participants were satisfied with their activity tracker use, and 79% did with the technical support provided by the team. The main strengths of the team members’ perspective were the study design, the team, and the device. The weaknesses were the budgetary constraints, the turnover, and the technical issues. The opportunities were the primary care setting and the common technology. The threats were the recruitment, the administrative challenges, and the technological difficulties.Conclusion: Patients with type 2 diabetes were satisfied with their activity tracker used to improve motivation for physical activity. Research team members agreed that implementation can be done in primary care, but some challenges remain for using this tool in clinical practice regularly.
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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 | 0.015 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".