Global Assessment of Relational Functioning: A Dynamic Family Measure Predicting Outcome in Children With Diabetes
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Bibliographic record
Abstract
While the prevalence of type 1 diabetes (T1D) in the pediatric population has been increasing dramatically in recent years, most youths with T1D do not meet the treatment targets recommended by the American Diabetes Association. The multiple self-report scales for parents and adolescents that have been investigated in relation to treatment adherence and glycemic control in pediatric T1D show limited predictive abilities. This longitudinal observational study investigates whether the Global Assessment of Relational Functioning (GARF) can predict the medical outcome for newly diagnosed youths with T1D. The GARF is a brief structured interview assessing important areas of family functioning. The GARF assesses three main areas of family functioning: The organization, the emotional climate, and the problem-solving attributes of the family. Fifty-one youths recently diagnosed with diabetes and their families were recruited from a care facility in Canada. The age of the youths ranged from 1 to 16 years (M = 8.89; SD = 4.2), comprising 13 preschoolers, 28 school-aged children, and 10 teenagers. Including family members, a total of 139 people participated in the assessments. Correlations were sought between GARF scores, patients' serum glycosylated hemoglobin (HbA1c) and the frequency of ER visits, hospitalizations, episodes of ketoacidosis, severe hypoglycemia, insulin resistance, and mental health referrals over 21 months. The GARF score was significantly inversely correlated with outcome HbA1c scores (r = -0.61, p < 0.001), indicating that higher family functioning is associated with better metabolic control. These results suggest the GARF could be administered at diagnosis to predict diabetes outcome among a pediatric population.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it