Experiencing Positive Health, as a Family, While Living With a Rare Complex Disease: Bringing Participatory Medicine Through Collaborative Decision Making Into the Real World (Preprint)
Bibliographic record
Abstract
UNSTRUCTURED Physician–patient collaboration was recognized as a critical core of participatory medicine more than a century ago. However, the subsequent focus on scientific research to enable cures and increased dominance of physicians in health care subordinated patients to a passive role. This paternalistic model weakened in the past 50 years—as women, minorities, and the disabled achieved greater rights, and as incurable chronic diseases and unrelieved pain disorders became more prevalent—promoting a more equitable role for physicians and patients. By 2000, a shared decision-making model became the pinnacle for clinical decisions, despite a dearth of data on health outcomes, or the model’s reliance on single patient or solo practitioner studies, or evidence that no single model could fit all clinical situations. We report about a young woman with intractable epilepsy due to a congenital brain malformation whose family and medical specialists used a collaborative decision-making approach. This model positioned the health professionals as supporters of the proactive family, and enabled them all to explore and co-create knowledge beyond the clinical realm. Together, they involved other members of the community in the decisions, while harnessing diverse relationships to allow all family members to achieve positive levels of health, despite the resistance of the seizures to medical treatment and the incurable nature of the underlying disease.
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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 | 0.013 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".