Predictors of treatment adherence in young children with type 1 diabetes
Bibliographic record
Abstract
AIM: This paper reports a study to investigate whether diabetes-specific, demographic and psychosocial variables predict adherence in young children with type 1 diabetes. BACKGROUND: Paediatric diabetes rates are increasing worldwide; however, young children are neglected in treatment adherence research, despite the importance of adherence for health. Greater understanding of adherence in this group could enhance nurses' ability to provide care tailored to families' needs. METHOD: A cross-sectional study was carried out between 2001 and 2003 with 65 children aged 2-8 years and their mothers in Britain. Mothers were interviewed about children's diabetes care, nutritional analyses were conducted and mothers completed assessments of diabetes knowledge, parenting stress, family functioning and child psychological adjustment. Demographic and medical information was collected from patient records. FINDINGS: Consistent with older populations, blood glucose monitoring and dietary regimens showed greater adherence variability than injection frequency and injection time consistency. Better maternal diabetes knowledge correlated with less injection time variability, more frequent blood glucose monitoring, lower percentage energy intake from extrinsic sugars, lower glycosylated haemoglobin levels and fewer relationship difficulties. Longer diabetes duration, greater injection time variability and higher percentage energy intake from extrinsic sugars predicted less frequent blood glucose monitoring. More relationship difficulties and less frequent blood glucose monitoring predicted higher percentage energy intake from extrinsic sugars. CONCLUSIONS: Nurses can facilitate treatment adherence through provision of educational, practical and socio-emotional support. Nursing interventions should target blood glucose monitoring and dietary regimens in particular, and nurses should be sensitive to the various caretaking challenges presented to parents by different components of the diabetes regimen.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".