Adolescents learned self-management of arthritis by acquiring knowledge and skills and experiencing understanding from social supportCommentary
Bibliographic record
Abstract
J N Stinson Dr J N Stinson, University of Toronto and Hospital for Sick Children, Toronto, Ontario, Canada; jennifer.stinson@sickkids.ca What are the self-management needs of adolescents with juvenile idiopathic arthritis (JIA) and the acceptability of a web-based self-management programme? Descriptive exploratory qualitative study. 4 rheumatology clinics in paediatric tertiary care centres in Canada. 36 adolescents 12–20 years of age (mean age 15 y, 67% women) who had JIA. Exclusion criteria were major cognitive impairment and comorbid medical or psychiatric illness. Adolescents participated in individual semi-structured interviews lasting 20–40 minutes (n = 25) or focus groups lasting 40–75 minutes (n = 11). Interviews were audiotaped, transcribed verbatim, and analysed for themes using an iterative process. Adolescents developed self-management strategies by “letting go” of parents or care providers who had previously managed their disease. 2 main strategies were acquiring knowledge and skill to manage the disease and experiencing understanding through social support . (1) Acquiring knowledge and skill to manage the disease involved …
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".