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Record W4405849796 · doi:10.1177/15589447241306143

Understanding Stakeholder Priorities in Dupuytren Disease: A Qualitative Study

2024· article· en· W4405849796 on OpenAlexaff
Marta Karpinski, Caroline Hircock, Lucas Gallo, Emily Dunn, Jessica Murphy, Manraj Kaur, Achilleas Thoma

Bibliographic record

VenueHand · 2024
Typearticle
Languageen
FieldMedicine
TopicDupuytren's Contracture and Treatments
Canadian institutionsImpactMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicinePhysical therapyOccupational therapyDupuytren's contractureQualitative researchActivities of daily livingRange of motionMuscle contractureContractureSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Currently, there is no recommended standard set of outcomes to report in Dupuytren disease treatment studies, nor are there guidelines on how the outcomes themselves should be reported. This study aimed to elicit the most salient issues for patients living with and undergoing treatment for Dupuytren disease, as well as for the hand surgeons, occupational therapists, and physical therapists caring for these patients. METHODS: A qualitative, interpretive description study employing one-on-one semi-structured interviews was conducted. Ten surgeons, 12 occupational and physical therapists, and 10 patients were interviewed. RESULTS: Priorities related to Dupuytren disease treatment and recovery differed by stakeholder group. Surgeons prioritized range of motion, recovery time, and recurrence. Physical and occupational therapists frequently mentioned range of motion, grip strength, activities of daily living, return to meaningful activities, wound healing, edema, lack of sensation, and pain as important treatment outcomes. Patients described extension deficit, activities of daily living, holding objects, and lack of sensation. CONCLUSIONS: Through the present study, we have identified outcomes of high importance to patients, hand surgeons, occupational therapists, and physical therapists. These results can be used to inform the development of a core outcome set for Dupuytren contracture.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.408

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 studies0.0000.000
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 head0.264
GPT teacher head0.399
Teacher spread0.136 · 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 designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

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