FACTORS AFFECTING THE CHANGE IN PATIENT PERCEPTIONS OF PATIENT-CENTRED CARE OVER TIME
Bibliographic record
Abstract
Introduction: The relationship between patient-centred care and health outcomes is important to the development of quality primary care practices. A systematic review of studies that investigated this relationship (since 2000) was conducted to summarize the effects of patient-centred care. Moreover, this review found that the timing of implementing patient-perceived patient-centred care measures relative to the patient physician interaction in question varied from five days to one year and studies capturing these recalled perceptions did not report on the impact of the timing of measurement, which threatened the validity of their results. Over such varied elapsed time periods, patients’ perceptions of the patient-centred care they received from an earlier time point are likely subject to change. Inadequate account of changes in patient perceptions over time may have been in part due to insufficient research on factors affecting recall of patient-centred care. Objective: To determine the factors that affect changes in patient perceptions of patient-centred care over time using a conceptual framework derived from the cognitive psychologie literature. Methods: Secondary analysis of patients (n = 315) visiting family physicians (n = 39) practicing in Southwestern Ontario. Patient perception scores of patient-centred care collected at Tl (immediately following the visit) and at T2 (approximately two months later asking patients to recall the patient-centredness of their visit at Tl) both using the 14-item PPPC allowed for the study of change in patient perceptions over time. Analysis: ANCOVA was used on a sample of 253 patients from 32 physicians to test three main hypothesized effects: (1) elapsed time, (2) post-Tl health visits, and (3) change in symptom discomfort on change in patient perceptions from Tl to T2, controlling for clustering and additional covariates. Results: The main effects were not significantly related to changes in patient perceptions; however, among the covariates, patients’ who perceived more negatively of their health at T2 and were more anxious at Tl had a significantly greater change in their perceptions. Conclusions: Studies implementing patient perception measures later in time relative to the patient-physician interaction in question should consider the potential for the above-mentioned factors to impact changes in patients’ perceptions of patient-centred care.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".