A REVIEW OF TECHNOLOGY-BASED INTERVENTIONS IN IMPROVING TYPE-2-DIABETES MANAGEMENT IN CHINESE AMERICANS
Bibliographic record
Abstract
Health disparities of type 2 diabetes (DM2) in America is an ongoing crisis. Despite this, technology has been helpful in managing DM2 in the non-Hispanic White, Hispanic, and African American populations and has been proven effective. Furthermore, it may be used to supplement health provider DM2 care through telemedicine to lower hemoglobin A1c (A1c), a gold standard DM2 measurement, and other DM2-related outcomes, such as glycated hemoglobin. The purpose of this study was to review current literature on the use of telemedicine in assisting DM2 management in racial ethnic minorities and to discuss how to adjust the telemedicine DM2 management program to be applied to Chinese Americans. In addition, it is worthy to note that the role of nurses makes a substantial difference in the effectiveness of technological management of DM2 from being culturally sensitive and sending catered messages to address specific patient 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".