Development and psychometric properties of a short version of the Patient Continuity of Care Questionnaire
Bibliographic record
Abstract
INTRODUCTION: Hospitalization due to cardiac conditions is increasing worldwide, and follow-up after hospitalization usually occurs in a different healthcare setting than the one providing treatment during hospitalization. This leads to a risk of fragmented care and increases the need for coordination and continuity of care after hospitalization. Furthermore, international reports highlight the importance of improving continuity of care and state that it is an essential indicator of the quality of care. Patients' perceptions of continuity of care can be evaluated using the Patient Continuity of Care Questionnaire (PCCQ). However, the original version is extensive and may prove burdensome to complete; therefore, we aimed to develop and evaluate a short version of the PCCQ. METHODS: This was a psychometric validation study. Content validity was evaluated among user groups, including patients (n = 7), healthcare personnel (n = 15), and researchers (n = 7). Based on the results of the content validity and conceptual discussions among the authors, 12 items were included in the short version. Data from patients were collected using a consecutive sampling procedure involving patients 6 weeks after hospitalization due to cardiac conditions. Rasch analysis was used to evaluate the psychometric properties of the short version of the PCCQ. RESULTS: A total of 1000 patients were included [mean age 72 (SD = 10), 66% males]. The PCCQ-12 presented a satisfactory overall model fit and a person separation index of 0.79 (Cronbach's α: .91, ordinal α: .94). However, three items presented individual item misfits. No evidence of multidimensionality was found, meaning that a total score can be calculated. A total of four items presented evidence of response dependence but, according to the analysis, this did not seem to affect the measurement properties or reliability of the PCCQ-12. We found that the first two response options were disordered in all items. However, the reliability remained the same when these response options were amended. In future research, the benefits of the four response options could be evaluated. CONCLUSION: The PCCQ-12 has sound psychometric properties and is ready to be used in clinical and research settings to measure patients' perceptions of continuity of care after hospitalization. PATIENT OR PUBLIC CONTRIBUTION: Patients, healthcare personnel and researchers were involved in the study because they were invited to select items relevant to the short version of the questionnaire.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".