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Record W3093079746 · doi:10.1093/jpepsy/jsaa101

Sociodevelopmental Challenges Faced by Young People with Chronic Pain: A Scoping Review

2020· review· en· W3093079746 on OpenAlexaff
Abigail Jones, Line Caes, C. Meghan McMurtry, Christopher Eccleston, Abbie Jordan

Bibliographic record

VenueJournal of Pediatric Psychology · 2020
Typereview
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of GuelphMcMaster Children's Hospital
FundersPain Relief Foundation
KeywordsChronic painPsychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: Map the current literature investigating autonomy development, identity development, and peer relationships in young people aged 10-24 years with chronic pain. METHODS: A scoping review method was used to systematically search four databases (APA PsycNET, PubMed, Web of Science, and Cinahl) for peer-reviewed articles. Search results were screened against inclusion and exclusion criteria to ensure they met the objective. Eligible papers were assessed for quality, their data relating to the objective were extracted, and results are synthesized. RESULTS: Searches returned 3,815 papers after the removal of duplicates, with 42 papers included in the full review. The majority of papers investigated peer relationships (86%). Fewer papers investigated autonomy (43%) and identity (21%) development. Included papers were mostly quantitative (64%), with fewer qualitative (34%) and mixed-methods papers (2%). Overall, we found bidirectional relationships between chronic pain in young people, their social development, and a range of functional outcomes. However, the mechanisms underlying these relationships remain relatively unexplored. CONCLUSIONS: Review results are mapped onto the model proposed by Palermo et al. (2014). Guided by this model, clinical treatment for young people with chronic pain should consider social development. The model also sets out a future research agenda focused on exploring: (a) identity development, (b) the mechanisms underlying the relationships between social-developmental domains, pain, and outcomes, (c) a variety of participants and populations, and (d) a variety of methods, including longitudinal study designs.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.590
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.060
GPT teacher head0.391
Teacher spread0.331 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations42
Published2020
Admission routes1
Has abstractyes

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