Participation and chronic disease self-management: Are we risking inequitable resource allocation?
Bibliographic record
Abstract
The Ottawa Charter for Health Promotion supported the empowerment of individuals to participate in their health care and have control over their health. For older adults with chronic conditions, the Chronic Disease Self-Management Program has been widely adopted as an adjunct to existing healthcare options. A growing body of literature has supported the positive impact of self-management programs on outcomes for people with a range of chronic conditions. However, evidence also suggests that participation in these programs is biased. This paper draws on pilot data to describe the profile of those people who inquire, enrol, attend, and complete CDSM courses in Queensland, Australia. As expected, there was evidence that males, Indigenous people, people of non-English speaking background, and those with multiple responsibilities were less likely to participate. Most importantly, participation was affected by a self-selection bias associated with health status. Those who were either unwell or well at the time of the course were unlikely to attend, minimising the preventative value of the CDSM program. Further, CDSM evaluation studies are likely to be inherently flawed and the distribution of health resources can become inequitable.
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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 | 0.019 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".