MétaCan
Menu
Back to cohort
Record W2047693157 · doi:10.1002/pon.715

Psychometric refinement of an outpatient, visit‐specific satisfaction with doctor questionnaire

2003· article· en· W2047693157 on OpenAlexaffabout
D. Andrew Loblaw, Andrea Bezjak, P. Mony Singh, Andrew Gotowiec, David Joubert, Kenneth Mah, Gerald M. Devins

Bibliographic record

VenuePsycho-Oncology · 2003
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsMcMaster UniversityUniversity of CalgaryPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health NetworkSunnybrook Health Science Centre
Fundersnot available
KeywordsExploratory factor analysisDisengagement theoryConfirmatory factor analysisFamily medicinePatient satisfactionReliability (semiconductor)MedicineGoodness of fitClinical psychologyOutpatient clinicPsychologyPsychometricsStructural equation modelingGerontologyNursingStatistics

Abstract

fetched live from OpenAlex

Measuring patient's satisfaction with their physician is gaining interest but requires a questionnaire that is valid, reliable and acceptable to patients. We previously published a self-administered visit-specific satisfaction with physician questionnaire for cancer patients. Eighty outpatients at a Canadian Cancer Center completed the Princess Margaret Hospital Patient Satisfaction with Doctor Questionnaire and the FACT-G questionnaires along with demographic information just after clinic visit and again 3-5 days later. Exploratory factor analysis extracted two factors, labeled 'physician disengagement' and 'perceived support,' with average coefficient alpha values of 0.93 and 0.90. Test-retest reliability was 0.83 and 0.73, respectively, for the two factors. Confirmatory factor analysis applied to the data from 174 patients in the original study indicated excellent goodness of fit. PMH/PSQ-MD correlated moderately with FACT-G (average r=0.37, p<0.005). The PMH/PSQ-MD questionnaire is a brief, valid and reliable questionnaire that taps two complementary facets of patient satisfaction.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.093
GPT teacher head0.455
Teacher spread0.362 · 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

Citations46
Published2003
Admission routes2
Has abstractyes

Explore more

Same venuePsycho-OncologySame topicPatient Satisfaction in HealthcareFrench-language works237,207