Assessment of self-management in patients with diabetes using the novel LMC Skills, Confidence and Preparedness Index (SCPI)
Bibliographic record
Abstract
AIMS: The LMC Skills, Confidence & Preparedness Index (SCPI) is an electronic tool designed to meet ISOQOL standards and (a) assess three dimensions: knowledge, confidence and preparedness; (b) provide a clinically meaningful measure; (c) provide immediate feedback to the healthcare provider. Internal consistency and external validity have been previously reported in a refractory diabetes cohort. This larger evaluation, broader in glycemic control, sought to assess clinical relevance to glycemia. METHODS: Participants with type 1 and type 2 diabetes were recruited from LMC Diabetes and Endocrinology specialist clinics, from April to October 2016. Participants completed the SCPI using a tablet. Demographic and laboratory data were extracted from the LMC Diabetes Patient Registry. RESULTS: In total, 529 patients met inclusion criteria and were included in psychometric analyses; 518 patients with established diabetes (>6 months) were assessed for SCPI - glycemia correlations. SCPI scores were found to have a high degree of validity, internal consistency, and test-retest reliability. Most importantly, the tool showed good external validity in its relation to glycemic control, both in tertile analysis, demonstrating a threshold effect consistent with a 'moderate' degree of poor control; and in overall correlation with HbA1c for the total SCPI score and two subscales (Skills and Confidence). CONCLUSIONS: The SCPI tool is a quick (25 items), easy to use measure of three domains - knowledge, confidence and preparedness. The instant scoring and specific feedback, as well as the relationship to glycemic control should provide significant value in the patient assessment in the diabetes clinic.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".