People with diabetes foot complications do not recall their foot education: a cohort study
Bibliographic record
Abstract
BACKGROUND: The purpose of this study is to document what and how diabetes specific foot health information was provided during a podiatry consultation, and what information was retained at 1 month post consultation. METHODS: This project was embedded within a prospective cohort study with two groups, podiatrists and people with diabetes. Data collection included the Problem Areas in Diabetes Questionnaire (PAID), Montreal Cognitive Assessment (MoCA), information covered during the consultation, method of delivery and perceived key educational message from both participant perspectives at the time of the appointment and 1 month post appointment. RESULTS: There were three podiatrists and 24 people with diabetes who provided information at the two time points. Diabetes education provided by the podiatrists was mostly verbal. The key educational message recalled by both groups differed at the time of the appointment (14 out of 24 of responses) and at 1 month post the appointment time (11 out of 24 of responses). CONCLUSIONS: Education is a vital component to the treatment regime of people with diabetes. It appears current approaches are ineffective in enhancing understanding of diabetes impact on foot health. This study highlights the need for research investigating better ways to deliver key pieces of information to this population.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".