Guiding Documents for Engaging with Remote Chronic Disease Management Programs as a Healthcare Provider: A Scoping Review
Bibliographic record
Abstract
Introduction: Chronic disease management programs (CDMP) that include education and exercise enhance outcomes and reduce healthcare costs. Remote CDMP have the potential to provide convenient, cost-effective, and accessible options for individuals, but it is unclear how to best implement programs that include education and exercise. This review identified and synthesized resources for implementing remote CDMP programs that incorporate education and exercise. Methods: Peer-reviewed and grey literature were systematically searched from January 1998 to May 2022. Covidence software was used for screening and extraction. The data were synthesized and presented in a narrative and tabular format. Results: Six peer-reviewed manuscripts and six grey literature documents published between 2006-2022 were included. All resources described individual programs targeting various chronic conditions. Provider training, consent, participant screening, and safety considerations were identified. Conclusions: Guidelines for remote CFMP programs are lacking. Additional work is needed to design remote CDMP guidelines incorporating education and exercise.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 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".