Increasing Access to Chronic Disease Self-Management Programs in Rural and Remote Communities Using Telehealth
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: This study examined whether a telehealth chronic disease self-management program (CDSMP) would lead to improvements in self-efficacy, health behaviors, and health status for chronically ill adults living in Northern Ontario, Canada. Two telehealth models were used: (1) single site, groups formed by participants at one telehealth site; and (2) multi-site, participants linked from multiple sites to form one telehealth group, as a strategy to increase access to the intervention for individuals living in rural and remote communities. SUBJECTS AND METHODS: Two hundred thirteen participants diagnosed with heart disease, stroke, lung disease, or arthritis attended the CDSMP at a preexisting Ontario Telemedicine Network studio from September 2007 to June 2008. The program includes six weekly, peer-facilitated sessions designed to help participants develop important self-management skills to improve their health and quality of life. Baseline and 4-month follow-up surveys were administered to assess self-efficacy beliefs, health behaviors, and health status information. Results were compared between single- and multi-site delivery models. RESULTS: Statistically significant improvements from baseline to 4-month follow-up were found for self-efficacy (6.6±1.8 to 7.0±1.8; p<0.001), exercise behavior, cognitive symptom management, communication with physicians, role function, psychological well-being, energy, health distress, and self-rated health. There were no statistically significant differences in outcomes between single- and multi-site groups. CONCLUSIONS: Improvements in self-efficacy, health status, and health behaviors were equally effective in single- and multi-site groups. Access to self-management programs could be greatly increased with telehealth using single- and multi-site groups in rural and remote communities.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it