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Record W2965477610 · doi:10.17294/2330-0698.1696

Measuring Patients’ Perceptions of Health Care Encounters: Examining the Factor Structure of the Revised Patient Perception of Patient-Centeredness (PPPC-R) Questionnaire

2019· article· en· W2965477610 on OpenAlexafffundabout
Bridget Ryan, Judith Belle Brown, Paul F. Tremblay, Moira Stewart

Bibliographic record

VenueJournal of patient-centered research and reviews · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsCentre for Family MedicineWestern University
FundersOntario Ministry of Health and Long-Term Care
KeywordsPerspective (graphical)PerceptionPatient-centered careHealth carePsychologyNursingConceptual frameworkPatient careMedicineComputer scienceSociology

Abstract

fetched live from OpenAlex

Purpose: Given the ongoing desire to make health care more patient-centered and growing evidence supporting the provision of patient-centered care, it is important to have valid tools for measuring patient-centered care. The patient-centered clinical method (PCCM) is a conceptual framework for providing patient-centered care. A revision to the PCCM framework led to a corresponding need to enhance the Patient Perception of Patient-Centeredness (PPPC) questionnaire. The original PPPC was aligned with the components of the PCCM conceptual framework and developed to measure patient-centeredness from the patient’s perspective. The purpose of this study was to examine the factor structure of a revised version of the PPPC (ie, PPPC-R). Methods: Eleven new items were added to the original 14 items. The modified questionnaire was administered to patients in primary health care teams in Ontario, Canada. The confirmatory factor analysis was conducted on a subset of 381 patients who had seen a family physician. Results: The initial proposed 4-factor model first tested with a confirmatory factor analysis (CFA) did not fit adequately. Exploratory factor analysis was therefore used as a second step to modify the model and to identify weak items. A 3-factor exploratory model with 18 of the original 25 items was converted into a final hypothetical CFA model that had a good fit (χ2(132) = 176.795, P < 0.01; CFI = 0.991; RMSEA = 0.030). The third factor contained only 2 items and so is interpreted with caution. Conclusions: The validity of the PPPC-R is supported by some congruence between the conceptual framework (the PCCM) and the statistical analysis (CFA), but there is not a 1:1 correspondence. The components of the PCCM represent conceptually what is important when teaching, researching, and providing patient-centered care, whereas the PPPC-R represents patient-centered care as it is experienced by the patient.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.273
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.254
GPT teacher head0.430
Teacher spread0.176 · 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

Citations37
Published2019
Admission routes3
Has abstractyes

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