Individual and contextual factors associated with follow‐up use of diabetes self‐management education programmes: a multisite prospective analysis
Bibliographic record
Abstract
AIMS: Although a considerable body of research supports the efficacy of diabetes self-management education (DSME), these programmes are often challenged by high attrition rates. Little is known about factors influencing follow-up use of DSME services, thus the aim of this study was to identify these factors. METHODS: In this multisite prospective analysis, adults with Type 2 diabetes (n = 268) who attended one of two diabetes management centres (DMCs) were followed over a 1-year period from their initial visit. The influence of individual and contextual factors on the number of contacts with DMC providers was examined. Data were analysed within the context of the Health Behavioral Model of Health Services Utilization. RESULTS: In a multivariable negative binomial regression model, the number of contacts over 1 year was greater for those who were female, non-smokers, unemployed, self-referred to the DMC, lived closer to the DMC, had a lower body mass index, or had a longer known duration of diabetes. Follow-up use of services differed significantly between the two sites. Provider contacts were greater at the centre that offered flexible hours of services and a variety of optional educational modules. CONCLUSIONS: Healthcare professionals need to encourage ongoing use of DSME, particularly for individuals prone to lower follow-up use of these services. Providing services that are accessible, convenient, and can easily fit into patients' schedules may increase follow-up use. Further exploration into how operations and delivery of these services influence utilization patterns is strongly recommended.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".