Online survey to assess parents’ experience and preferences for follow-up visits for children living with type 1 diabetes in Quebec, Canada: a study protocol
Bibliographic record
Abstract
INTRODUCTION: It is accepted that although patients may initiate a visit to a healthcare provider, follow-up visits are often based on recommendations from providers. This suggests that follow-up care, since not initiated by patients, may not reflect patients' perception of a need for care. However, few studies have examined the burden of regular follow-up care and patients' perceived value of such care. For parents of children with type 1 diabetes (T1D), follow-up visits are scheduled regardless of how well controlled the diabetes is. Our study examines how benefits and burden from the parents' perspective could affect their preferences in regard to the frequency of regular follow-up care. METHODS: We aim to develop an online patient survey to be distributed to parents of children living with T1D in the province of Quebec, Canada. The survey will be available in French and English, and distributed through diabetes clinics, on social media groups and forums for parents of children with T1D. The survey will be developed in collaboration with parents of children with T1D to ensure that it appropriately reflects the services in regular follow-up care and that the language is understandable and clear. ETHICS AND DISSEMINATION: All participants will be informed of the requirements and objectives of the survey at the beginning of the questionnaire and that the data collected will remain anonymous and confidential. Ethics approval for the study was obtained from the research ethics committee of the CHU de Québec-Université Laval. Results of the study will be shared with relevant stakeholders with the aim of improving practices and better meeting patients' and families' needs.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".