Acculturation and Disparities in Telemedicine Readiness: A National Study
Bibliographic record
Abstract
Telemedicine provided older adults the ability to safely seek care during the coronavirus disease (COVID-19) pandemic. This study aimed to evaluate the potential impact of acculturation factors in telemedicine uptake between ethnic groups. As part of the National Health and Aging Trends Study 2018 survey, 303 participants (≥65 years) were interviewed. We assessed the impact of acculturation on telemedicine readiness by race and ethnicity. Compared to the white non-Hispanic immigrant population, Hispanic and Asian/Pacific Islander (API) populations had significantly lower telemedicine readiness and uptake. Limited English proficiency or older age at the time of migration was associated with telemedicine unreadiness and uptake in the Hispanic and API populations. Our findings suggested that acculturation factors play a substantial role in telemedicine uptake among older adult immigrants in the United States. Therefore, acculturation factors should be considered when promoting and adopting telemedicine technologies in older adults.
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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 | 0.001 | 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".