GPs' approach to insulin prescribing in older patients: a qualitative study
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Bibliographic record
Abstract
BACKGROUND: Evidence suggests that insulin is under-prescribed in older people. Some reasons for this include physician's concerns about potential side-effects or patients' resistance to insulin. In general, however, little is known about how GPs make decisions related to insulin prescribing in older people. AIM: To explore the process and rationale for prescribing decisions of GPs when treating older patients with type 2 diabetes. DESIGN OF STUDY: Qualitative individual interviews using a grounded theory approach. SETTING: Primary care. METHOD: A thematic analysis was conducted to identify themes that reflected factors that influence the prescribing of insulin. RESULTS: Twenty-one GPs in active practice in Ontario completed interviews. Seven factors influencing the prescribing of insulin for older patients were identified: GPs' beliefs about older people; GPs' beliefs about diabetes and its management; gauging the intensity of therapy required; need for preparation for insulin therapy; presence of support from informal or formal healthcare provider; frustration with management complexity; and GPs' experience with insulin administration. Although GPs indicated that they would prescribe insulin allowing for the above factors, there was a mismatch in intended approach to prescribing and self-reported prescribing. CONCLUSION: GPs' rationale for prescribing (or not prescribing) insulin is mediated by both practitioner-related and patient-related factors. GPs intended and actual prescribing varied depending on their assessment of each patient's situation. In order to improve prescribing for increasing numbers of older people with type 2 diabetes, more education for GPs, specialist support, and use of allied health professionals is needed.
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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 | 0.002 | 0.006 |
| 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 | 0.000 |
| 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 it