The Diabetes Continuity of Care Scale: the development and initial evaluation of a questionnaire that measures continuity of care from the patient perspective*
Bibliographic record
Abstract
The purpose of the present study was to develop and pilot test a questionnaire to assess continuity of care from the perspective of patients with diabetes. Seven patient and two healthcare-provider focus groups were conducted. These focus groups generated 777 potential items. This number was reduced to 56 items after item reduction, face validity testing and readability analysis, and to 47 items after a preliminary factor analysis. Readability was assessed as requiring 7-8 years of schooling. Sixty adult patients with diabetes completed the draft Diabetes Continuity of Care Scale (DCCS) at a single point in time to assess the validity of the instrument. Patients completed the draft DCCS again 2 weeks later to assess test-retest reliability. A provisional factor analysis and grouping according to clinical sense yielded five domains: access and getting care, care by doctor, care by other healthcare professionals, communication between healthcare professionals, and self-care. The internal consistency (Cronbach's alpha) for the whole scale was 0.89. The test-retest reliability was r = 0.73. The DCCS total score was moderately correlated with some of the measures used to establish construct validity. The DCCS could differentiate between patients who did and did not achieve specific process and clinical indicators of good diabetes care (e.g. Hba1c tested within 6 months). The development of the DCCS was centred on the patient's perspective and revealed that the patient perspective regarding continuity of care extends beyond the concept of seeing one doctor. Initial testing of this instrument demonstrates that it has promise as a reliable and valid measure in this area.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".