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Record W2044608088 · doi:10.1002/nur.20112

Development and psychometric testing of the care in obstetrics: Measure for testing satisfaction (COMFORTS) scale

2006· article· en· W2044608088 on OpenAlexaff
Patricia A. Janssen, Cindy‐Lee Dennis, Birgit Reime

Bibliographic record

VenueResearch in Nursing & Health · 2006
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsChildren’s Health Research InstituteUniversity of British ColumbiaUniversity of TorontoBC Research (Canada)
Fundersnot available
KeywordsVarimax rotationCronbach's alphaChildbirthScale (ratio)NursingMedicineConstruct validityPatient satisfactionObstetric nursingHealth carePsychometricsPsychologyFamily medicineMEDLINEClinical psychologyPregnancy

Abstract

fetched live from OpenAlex

This paper describes the development and psychometric assessment of a scale to measure satisfaction with intrapartum and postpartum care in hospital: The Care in Obstetrics: A Measure For Testing Satisfaction (COMFORTS) scale. A sample of 415 participants completed the 40-item scale. Cronbach's alpha for the scale was .95. Evaluation of construct validity through principal components factor analysis with varimax rotation yielded six subscales: confidence in newborn care, postpartum nursing care, provision of choice, the physical environment, respect for privacy, and labor/delivery nursing care. The COMFORTS scale was able to discriminate between multiparous versus primiparous women, and between women cared for in single room maternity care versus in separate labor/delivery and postpartum rooms. Pending further validation, the COMFORTS scale has potential to measure women's satisfaction with childbirth care and contribute to an assessment of the quality of care 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.

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)0.008
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.217
GPT teacher head0.476
Teacher spread0.259 · 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 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

Citations65
Published2006
Admission routes1
Has abstractyes

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