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Record W4385235001 · doi:10.1186/s12969-023-00849-0

“I’d like more options!”: Interviews to explore young people and family decision-making needs for pain management in juvenile idiopathic arthritis

2023· article· en· W4385235001 on OpenAlexaffabout
Karine Toupin‐April, Isabelle Gaboury, Laurie Proulx, Adam M. Huber, Ciarán M. Duffy, Esi M. Morgan, Linda Li, Elizabeth Stringer, Mark Connelly, Jennifer E. Weiss, Michele Gibbon, Hannah Sachs, Aditi Sivakumar, Alexandra Sirois, Emily Sirotich, Natasha Trehan, Naomi Abrahams, Janice Cohen, Sabrina Cavallo, Tania El Hindi, Marco Ragusa, France Légaré, William B. Brinkman, Paul R. Fortin, Simon Décary, Rebecca Lee, Sabrina Gmuca, Gail Paterson, Peter Tugwell, Jennifer Stinson

Bibliographic record

VenuePediatric Rheumatology · 2023
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick ChildrenUniversity of TorontoArthritis SocietyCentre hospitalier universitaire de QuébecCentre for Interdisciplinary Research in RehabilitationUniversité LavalCentres Intégré Universitaires de Santé et de Services SociauxInstitut du Savoir MontfortCentre Hospitalier Universitaire Sainte-JustineBruyèreOttawa HospitalGovernment of CanadaStatistics CanadaUniversité de MontréalDalhousie UniversityUniversity of OttawaPublic Health Agency of CanadaUniversité de SherbrookeResearch CanadaIzaak Walton Killam Health CentreChildren's Hospital of Eastern OntarioCanadian Arthritis Patient AllianceQueen's UniversityCentre Hospitalier Universitaire de SherbrookeUniversity of British Columbia
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsThematic analysisMedicineQualitative researchQuality of life (healthcare)JuvenileHealth careFamily medicinePhysical therapyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Juvenile idiopathic arthritis (JIA) is a common pediatric rheumatic condition and is associated with symptoms such as joint pain that can negatively impact health-related quality of life. To effectively manage pain in JIA, young people, their families, and health care providers (HCPs) should be supported to discuss pain management options and make a shared decision. However, pain is often under-recognized, and pain management discussions are not optimal. No studies have explored decision-making needs for pain management in JIA using a shared decision making (SDM) model. We sought to explore families' decision-making needs with respect to pain management among young people with JIA, parents/caregivers, and HCPs. METHODS: We conducted semi-structured virtual or face-to-face individual interviews with young people with JIA 8-18 years of age, parents/caregivers and HCPs using a qualitative descriptive study design. We recruited participants online across Canada and the United States, from a hospital and from a quality improvement network. We used interview guides based on the Ottawa Decision Support Framework to assess decision-making needs. We audiotaped, transcribed verbatim and analyzed interviews using thematic analysis. RESULTS: A total of 12 young people (n = 6 children and n = 6 adolescents), 13 parents/caregivers and 11 HCPs participated in interviews. Pediatric HCPs were comprised of rheumatologists (n = 4), physical therapists (n = 3), rheumatology nurses (n = 2) and occupational therapists (n = 2). The following themes were identified: (1) need to assess pain in an accurate manner; (2) need to address pain in pediatric rheumatology consultations; (3) need for information on pain management options, especially nonpharmacological approaches; (4) importance of effectiveness, safety and ease of use of treatments; (5) need to discuss young people/families' values and preferences for pain management options; and the (6) need for decision support. Themes were similar for young people, parents/caregivers and HCPs, although their respective importance varied. CONCLUSIONS: Findings suggest a need for evidence-based information and communication about pain management options, which would be addressed by decision support interventions and HCP training in pain and SDM. Work is underway to develop such interventions and implement them into practice to improve pain management in JIA and in turn lead to better health outcomes.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.825

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.320
Teacher spread0.290 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2023
Admission routes2
Has abstractyes

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