The Implementation of the Chronic Care Model with Respect to Dealing with the Biopsychosocial Aspects of the Chronic Disease of Diabetes
Bibliographic record
Abstract
In Brief PURPOSE: To enhance the learner's competence with information about the Chronic Care Model (CCM) with respect to dealing with the biopsychosocial aspects of diabetes. TARGET AUDIENCE: This continuing education activity is intended for physicians and nurses with an interest in skin and wound care. OBJECTIVES: After participating in this educational activity, the participant should be better able to: Apply information on the CCM and available assessment and evaluation tools to patient care scenarios. Correlate risk factors and outcomes for patients with combined diagnoses of depression and diabetes. Biopsychosocial illnesses, including diabetes, must be approached by clinicians who understand that not only are the biological factors, including the cause of the illness and the toll it takes on the body, important considerations, but that also psychological components experienced by the patient dealing with diabetes and social components are factors to be considered. This continuing education activity discusses the concept that understanding that integration of healthcare teams will yield higher outcomes for the patient while decreasing risk factors for comorbidities is imperative to managing chronic illnesses.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".