Relational Continuity from the Patient Perspective: Comparison of Primary Healthcare Evaluation Instruments
Bibliographic record
Abstract
UNLABELLED: The operational definition of relational continuity is "a therapeutic relationship between a patient and one or more providers that spans various healthcare events and results in accumulated knowledge of the patient and care consistent with the patient's needs." OBJECTIVE: To examine how well relational continuity is measured in validated instruments that evaluate primary healthcare from the patient's perspective. METHOD: 645 adults with at least one healthcare contact in the previous 12 months responded to six instruments that evaluate primary healthcare. Five subscales map to relational continuity: the Primary Care Assessment Survey (PCAS, two subscales), the Primary Care Assessment Tool - Short Form (PCAT-S) and the Components of Primary Care Index (CPCI, two subscales). Scores were normalized for descriptive comparison. Exploratory and confirmatory (structural equation modelling) factor analysis examined fit to operational definition, and item response theory analysis examined item performance on common constructs. RESULTS: All subscales load reasonably well on a single factor, presumed to be relational continuity, but the best model has two underlying factors corresponding to (1) accumulated knowledge of the patient and (2) relationship that spans healthcare events. Some items were problematic even in the best model. The PCAS Contextual Knowledge subscale discriminates best between different levels of accumulated knowledge, but this dimension is also captured well by the CPCI Accumulated Knowledge subscale and most items in the PCAT-S Ongoing Care subscale. For relationship-spanning events, the items' content captures concentration of care in one doctor; this is captured best by the CPCI Preference for Regular Provider subscale and, to a lesser extent, by the PCAS Visit-Based Continuity subscale and one relevant item in the PCAT-S Ongoing Care subscale. But this dimension correlates only modestly with percentage of reported visits to the personal doctor. The items function as yes/no rather than ordinal options, and are especially informative for poor concentration of care. CONCLUSION: These subscales perform well for key elements of relational continuity, but do not capture consistency of care. They are more informative for poor relational continuity.
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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 | 0.044 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".