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Record W2619670834 · doi:10.5348/d05-2017-30-oa-6

Complex regional pain syndrome: Facilitating the use of self-management strategies

2017· article· en· W2619670834 on OpenAlexaff
Xuan Chi Julia Dao, Rosalie Blais-Hébert, Léonie Duranleau, Marie-Pier Durivage, June Litowski, Julie Turbide, André Bussières

Bibliographic record

VenueEdorium Journal of Disability and Rehabilitation · 2017
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité du Québec à MontréalCentre for Interdisciplinary Research in RehabilitationConcordia UniversityCentre de réadaptation Lethbridge-Layton-MackayMcGill University
Fundersnot available
KeywordsPsychological interventionIntervention (counseling)Self-managementContext (archaeology)Pain managementComplex regional pain syndromeMedicineQuality managementPsychologyKnowledge managementNursingPhysical therapyManagement systemComputer science

Abstract

fetched live from OpenAlex

Aims: While several interventions are used to treat complex regional pain syndrome (CRPS), patient adherence to recommended care including self-management is challenging. To understand the barriers and facilitators to using self-management strategies among CRPS patients; to explore educational tools used to enable self-management; and to develop knowledge translation interventions to address potential barriers using intervention mapping. Methods: Semi-structured interviews of patients were conducted to identify the determinants of self-management. Findings informed the development of a tailored theory-based intervention to increase adherence. Result: Theoretical domains identified were: Social influence, Beliefs about capabilities, Beliefs about consequences, Environmental context and resources. Various educational tools were provided by treating clinicians. Interventions should consider increasing knowledge about treatment outcomes, identifying health antecedents and promoting self-monitoring. Conclusion: Online educational interventions focusing on patient advice, self-monitoring, and techniques to increase the quality of the clinician-patient relationship may successfully address patient barriers to using self-management strategies.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.318

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.052
GPT teacher head0.307
Teacher spread0.255 · 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
Published2017
Admission routes1
Has abstractyes

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