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Record W3190276398 · doi:10.1016/j.msksp.2021.102434

Patient-centered care in musculoskeletal practice: Key elements to support clinicians to focus on the person

2021· article· en· W3190276398 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMusculoskeletal Science and Practice · 2021
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiopsychosocial modelMedicineMusculoskeletal painClinical PracticeRehabilitationKey (lock)NursingPatient-centered carePhysical therapyMEDLINEComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

Musculoskeletal rehabilitation, including physiotherapy, needs to move towards a broader biopsychosocial understanding of musculoskeletal conditions and the delivery of high-value care for people with persistent pain conditions, in which a patient-centered approach is a key feature. However, it has been reported that clinicians experience difficulties with integrating patient-centered care principles into their clinical practice. Based on a focused symposium about patient-centered care for patients with musculoskeletal conditions, held during the online 2021 World Physiotherapy Congress, the purpose of this article is to share key elements of the content of this symposium with a wider audience, aimed at enabling clinicians to enhance patient-centeredness in their current practice. These key elements include establishing meaningful connections, deciding together and self-management support. Moreover, challenges on patient-centered care in low/middle income countries will be discussed and recommendations to implement patient-centered care in clinical practice will be provided.

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.

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)0.004
metaresearch head score (Gemma)0.036
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.364
Teacher spread0.338 · 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