Respectfulness from the Patient Perspective: Comparison of Primary Healthcare Evaluation Instruments
Bibliographic record
Abstract
UNLABELLED: Respectfulness is one measurable and core element of healthcare responsiveness. The operational definition of respectfulness is "the extent to which health professionals and support staff meet users' expectations about interpersonal treatment, demonstrate respect for the dignity of patients and provide adequate privacy." OBJECTIVE: To examine how well respectfulness is captured in validated instruments that evaluate primary healthcare from the patient's perspective, whether or not their developers had envisaged these as representing respectfulness. METHOD: 645 adults with at least one healthcare contact with their own regular doctor or clinic in the previous 12 months responded to six instruments, two subscales that mapped to respectfulness: the Interpersonal Processes of Care, version II (IPC-II, two subscales) and the Primary Care Assessment Survey (PCAS). Additionally, there were individual respectfulness items in subscales measuring other attributes in the Components of Primary Care Index (CPCI) and the first version of the EUROPEP (EUROPEP-I). Scores were normalized for descriptive comparison. Exploratory and confirmatory (structural equation modelling) factor analyses examined fit to operational definition. RESULTS: Respectfulness scales correlate highly with one another and with interpersonal communication. All items load adequately on a single factor, presumed to be respectfulness, but the best model has three underlying factors corresponding to (1) physician's interpersonal treatment (eigenvalue=13.99), (2) interpersonal treatment by office staff (eigenvalue=2.13) and (3) respect for the dignity of the person (eigenvalue=1.16). Most items capture physician's interpersonal treatment (IPC-II Compassionate, Respectful Interpersonal Style, IPC-II Hurried Communication and PCAS Interpersonal Treatment). The IPC-II Interpersonal Style (Disrespectful Office Staff) captures treatment by staff, but only three items capture dignity. CONCLUSION: Various items or subscales seem to measure respectfulness among currently available validated instruments. However, many of these items related to other constructs, such as interpersonal communication. Further studies should aim at developing more refined measures - especially for privacy and dignity - and assess the relevance of the broader concept of responsiveness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".