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Record W2153156864 · doi:10.2106/jbjs.n.00811

Measuring Patient Satisfaction in Orthopaedic Surgery

2015· review· en· W2153156864 on OpenAlexaff
Brent Graham, Andrew Green, Michelle A. James, Jeffrey N. Katz, M.F. Swiontkowski

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2015
Typereview
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsPatient satisfactionPsychological interventionContext (archaeology)Reliability (semiconductor)MedicineConstruct validityPsychologyNursing

Abstract

fetched live from OpenAlex

In addition to their wish to understand the clinical results of orthopaedic interventions, clinicians, patients, and payers are increasingly interested in patient satisfaction, both with the process of care and with outcomes. The construct of satisfaction is complex and depends on the context in which care takes place, including the nature of treatment, its setting, and most importantly the expectation of patients prior to treatment. The characteristics of scales that are effective measures of satisfaction are the same as those of all effective measurement instruments--i.e., reliability, validity, and responsiveness. Measurement of patient satisfaction may be especially important in evaluations of established procedures and processes so that the value of those procedures and processes to patients can be more completely understood.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.007
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.352
GPT teacher head0.425
Teacher spread0.073 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations231
Published2015
Admission routes1
Has abstractyes

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