Shared decision-making: the perspectives of young adults with type 1 diabetes mellitus
Bibliographic record
Abstract
BACKGROUND: Shared decision-making (SDM) is at the core of patient-centered care. We examined whether young adults with type 1 diabetes perceived the clinician groups they consulted as practicing SDM. METHODS: In a web-based survey, 150 Australians aged 18-35 years and with type 1 diabetes rated seven aspects of SDM in their interactions with endocrinologists, diabetes educators, dieticians, and general practitioners. Additionally, 33 participants in seven focus groups discussed these aspects of SDM. RESULTS: Of the 150 respondents, 90% consulted endocrinologists, 60% diabetes educators, 33% dieticians, and 37% general practitioners. The majority of participants rated all professions as oriented toward all aspects of SDM, but there were professional differences. These ranged from 94.4% to 82.2% for "My clinician enquires about how I manage my diabetes"; 93.4% to 82.2% for "My clinician listens to my opinion about my diabetes management"; 89.9% to 74.1% for "My clinician is supportive of my diabetes management"; 93.2% to 66.1% for "My clinician suggests ways in which I can improve my self-management"; 96.6% to 85.7% for "The advice of my clinician can be understood"; 98.9% to 82.2% for "The advice of my clinician can be trusted"; and 86.5% to 67.9% for "The advice of my clinician is consistent with other members of the diabetes team". Diabetes educators received the highest ratings on all aspects of SDM. The mean weighted average of agreement to SDM for all consultations was 84.3%. Focus group participants reported actively seeking clinicians who practiced SDM. A lack of SDM was frequently cited as a reason for discontinuing consultation. The dominant three themes in focus group discussions were whether clinicians acknowledged patients' expertise, encouraged patients' autonomy, and provided advice that patients could utilize to improve self-management. CONCLUSION: The majority of clinicians engaged in SDM. Young adults with type 1 diabetes prefer such clinicians. They may fail to take up recommended health services when clinicians do not practice this component of patient-centered care. Such findings have implications for patient safety, improved health outcomes, and enhanced health service delivery.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".