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Record W1970626467 · doi:10.1136/ebn.11.3.92

Adolescents learned self-management of arthritis by acquiring knowledge and skills and experiencing understanding from social supportCommentary

2008· letter· en· W1970626467 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEvidence-Based Nursing · 2008
Typeletter
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySelf-managementSocial skillsArthritisSocial supportMedical educationKnowledge managementDevelopmental psychologyMedicinePsychotherapistComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

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 …

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.684
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.116
GPT teacher head0.408
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it