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Record W4404721064 · doi:10.3390/children11121424

Integrating Chronic Disease Management and Harm Reduction for Youth with Juvenile Idiopathic Arthritis Amid Canada’s Overdose Crisis

2024· article· en· W4404721064 on OpenAlexaffabout
Babatope O. Adebiyi, Kathryn A. Birnie, Heinrike Schmeling

Bibliographic record

VenueChildren · 2024
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicineChronic painHarm reductionMental healthPsychosocialContext (archaeology)Health carePublic healthPsychiatryNursingPolitical science

Abstract

fetched live from OpenAlex

Juvenile idiopathic arthritis (JIA) is a chronic autoimmune condition in children that often requires long-term pain management, which can include opioid use. In the context of Canada's ongoing overdose crisis, youth with JIA face risks due to potential opioid dependency and exposure to toxic drug supplies. This commentary proposes an integrated approach combining chronic disease management with harm reduction strategies specifically tailored for JIA patients. By incorporating multidisciplinary care, opioid stewardship, and harm reduction measures, this approach aims to address the dual challenges of managing chronic pain and mitigating substance use risks. Key recommendations include the development of integrated care models, enhanced access to multidisciplinary services, allocation of resources for specialized pain management, research, and mental health support, and investment in harm reduction initiatives. Additionally, comprehensive training for healthcare providers on the intersection of chronic pain, substance use, and mental health is essential. This integrated strategy not only supports the medical and psychosocial needs of youth with JIA but also offers a model for addressing the broader challenges faced by vulnerable populations in the overdose crisis. Adopting these measures will help protect this at-risk group, improve their quality of life, and contribute to the overall public health response to the overdose epidemic.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.576
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.024
GPT teacher head0.324
Teacher spread0.300 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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