Jointly managing arthritis
Bibliographic record
Abstract
The objective of this article is to explore information needs of children with juvenile idiopathic arthritis (JIA) and their parents in order to develop a web-based psychoeducational program aimed at improving their quality of life. A qualitative study design was used. A purposive sample of children (n = 41; 8-11 years) with JIA and parents (n = 48) participated in parent-child interviews (n = 29), and four child-focus and four parent-focus group interviews. Transcribed data were organized into categories that reflected emerging themes. Findings uncovered three major themes: "living with JIA", "jointly managing JIA", and "need for a web-based program of JIA information and social Support". Subthemes for "Living with JIA" were as follows: "impact on participation", "worry and distress", and "receiving social support". Subthemes under "Jointly Managing JIA" included "obtaining JIA information", "communication and advocacy", and "strategies to manage JIA". Participants endorsed a web-based program as a way to access JIA information and social support. In order to jointly manage JIA, participants expressed the need for disease-specific information, management strategies, and social support and felt that the Internet was acceptable for delivering these disease-management strategies. Findings from this study will inform development and evaluation of an online program to help children and parents jointly manage JIA.
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 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 | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".