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Record W4205291433 · doi:10.3138/ptc-2021-0043

High Patient Satisfaction with Examination by Advanced Practice Physiotherapists in an Orthopaedic Outpatient Shoulder Clinic: A Cross-Sectional Study Using Quantitative and Qualitative Methods

2022· article· en· W4205291433 on OpenAlexvenueno aff
Elisa Bak Bødskov, Camilla Palmhøj Nielsen, Lone Ramer Mikkelsen, Thomas Klebe, Mette Terp Høybye, Merete Nørgaard Madsen

Bibliographic record

VenuePhysiotherapy Canada · 2022
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCross-sectional studyPhysical therapyPatient satisfactionOutpatient clinicQualitative researchFamily medicineNursingPathology

Abstract

fetched live from OpenAlex

Purpose: To evaluate patients’ satisfaction with being examined and diagnosed in an orthopaedic outpatient shoulder clinic, determine whether a difference exists between levels of satisfaction among patients examined by advanced practice physiotherapists (APPs) and orthopaedic surgeons (OSs), and explore patients’ experiences with being examined by APPs. Method: One hundred and thirty-three patients participated in a cross-sectional questionnaire study using the Visit-Specific Satisfaction Instrument (VSQ-9). Primary outcome was satisfaction with “The visit overall” (item 9). Nine patients participated in semi-structured interviews, which were thematically analyzed. Results:There was no significant difference in satisfaction with “The visit overall” between patients examined by an OS (median: 75, 1st–3rd quartiles: 75–100) and an APP (median: 100, 1st–3rd quartiles: 75–100). The VSQ-9 total score was not significantly different between groups, but some items regarding direct interaction with the health provider were scored significantly higher in the APP group. Patients were particularly satisfied with APPs’ ability to explain during the consultation. Conclusions: The results showed high levels of satisfaction with examinations performed by both OSs and APPs with no difference between groups concerning “The visit overall.” From a patient perspective, the results support the use of APPs to examine and diagnose selected patients in an orthopaedic outpatient shoulder clinic.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.140
GPT teacher head0.567
Teacher spread0.427 · 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 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

Citations8
Published2022
Admission routes1
Has abstractyes

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