How does it feel to be a problem? Patients’ experiences of self‐management support in New Zealand and Canada
Bibliographic record
Abstract
BACKGROUND: The impact of long-term conditions is the "healthcare equivalent to climate change." People with long-term conditions often feel they are a problem, a burden to themselves, their family and friends. Providers struggle to support patients to self-manage. The Practical Reviews in Self-Management Support (PRISMS) taxonomy lists what provider actions might support patient self-management. OBJECTIVE: To offer providers advice on how to support patient self-management. DESIGN: Semi-structured interviews with 40 patient-participants. SETTING AND PARTICIPANTS: Three case studies of primary health-care organizations in New Zealand and Canada serving diverse populations. Participants were older adults with long-term conditions who needed support to live in the community. MAIN OUTCOME MEASURES: Qualitative description to classify patient narratives of self-management support according to the PRISMS taxonomy with thematic analysis to explore how support was acceptable and effective. RESULTS: Patients identified a relationship-in-action as the mechanism, the how by which providers supported them to self-manage. When providers acted upon knowledge of patient lives and priorities, these patients were often willing to try activities or medications they had resisted in the past. Effective self-management support saw PRISMS components delivered in patient-specific combinations by individual providers or teams. DISCUSSION AND CONCLUSIONS: Providers who establish relationships with patients can support them to self-manage and improve health outcomes. Delivery of taxonomy components, in the absence of a relationship, is unlikely to be either acceptable or effective. Providers need to be aware that social determinants of health can constrain patients' options to self-manage.
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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) | 0.000 | 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 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".