Blood Glucose Levels and Diabetes Family Conflict in Black Adolescents with Type 1 Diabetes During the COVID-19 Pandemic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The coronavirus 2019 (COVID-19) pandemic escalated family stress and prompted interruptions of regular healthcare visits. Such pandemic-related disruptions may be particularly deleterious among Black youth with chronic health conditions, such as type 1 diabetes. The present study leveraged longitudinal data from a multi-center randomized clinical trial (Clinicaltrials.gov [NCT03168867]) and a follow-up ancillary study focused on effects of COVID-19 to examine blood glucose trajectories and diabetes family conflict among Black adolescents with type 1 diabetes and their caregivers. Throughout the primary and ancillary studies, both adolescents and caregivers reported on their experience of diabetes family conflict across seven study visits. At each of these visits, the adolescent's hemoglobin A1c (HbA1c) was measured as an indicator of their blood glucose levels; further, HbA1c data during the study window was also extracted from the electronic medical record. Results demonstrated that HbA1c among the sample was linearly improving prior to the pandemic, but improvement halted following the onset of COVID-19. Following COVID-19 onset, average HbA1c remained stable, but higher than the recommended level. Higher mean levels of diabetes family conflict across the study were associated with higher HbA1c on average. However, diabetes family conflict did not predict changes in HbA1c trajectories pre- or post-pandemic onset. These findings highlight the potential stagnation of improving health-related outcomes during the COVID-19 pandemic for Black adolescents with type 1 diabetes and the need for further longitudinal work examining the familial and systemic factors contributing to the negative health consequences of the COVID-19 pandemic.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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