UCD School of Medicine, Summer Student Research Awards 2017, 4th October 2017, UCD, Dublin, Ireland
Bibliographic record
Abstract
Juvenile idiopathic arthritis (JIA) is one of the most common causes of chronic musculoskeletal pain in youth, and can negatively impact quality of life 1;2 .Youth with JIA, their families and health care providers face a variety of challenging decisions when choosing pain management options.However, there seems to be a lack of information on how these decisions are made.The aim of this research was to explore and summarize decisional needs among youth with JIA, their caregivers, and health care providers, with a focus on pain management, to ultimately develop a decision support intervention.A systematic search was conducted in major electronic databases.Studies were included if they assessed decisional needs of youth with JIA from their own perspectives, those of their caregivers or health providers.Out of the 47 included articles, only 11 discussed pain specifically.Excerpts were extracted and a narrative analysis was conducted to classify them into the different domains of shared decision making using the NVivo10 system.The most common domains were: 1) pain as an important value for youth and families, 2) the need for more information on a variety of pain management options and 3) how coping with pain would be improved by providing more information.The results demonstrate that there is a need to provide more information to youth and caregivers about a wide variety of pain management options, and to support youth and families when making these decisions.A decision support intervention will be developed to address these needs in clinical practice.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.367 | 0.078 |
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".