The feasibility of a social media-based foot self-management education and support program for adults with diabetes: A partially randomized preference trial
Bibliographic record
Abstract
To assess the feasibility of Diabetic Foot Care Group (DFCG), a social media-based self-management education and support intervention, for people with diabetes (PWD) empowerment in diabetes-related foot ulceration prevention. A partially randomized preference trial was conducted among 32 PWD. DFCG was implemented through Facebook. Participants in the intervention group joined the DFCG in addition to their usual care, while the control group received usual care. Data were collected online using questionnaires on participants' DFCG acceptance, engagement and preliminary efficacy on nine diabetes foot care-related outcomes at baseline, one, and three months post-intervention. The participants' study intervention acceptability and engagement rates were 84.2% and 55.2%, respectively. DFCG efficacy rate compared to usual care was 88.9% to 22.2%. Three diabetes foot care-related outcomes increased significantly in the intervention group three-month post-intervention: foot self-care adherence (p = 0.001, ηp2 = 0.35), preventive foot self-care practice (p = 0.002, ηp2 = 0.33), and physical health status (p < 0.02, ηp2 = 0.23). DFCG is feasible and could effectively improve diabetes foot care-related outcomes. Social media is an innovative approach healthcare professionals could utilize to virtually support PWD in ongoing learning and engagement in optimal foot self-care activities. ClinicalTrials.gov, Identifier: NCT04395521
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".