Acceptability, Feasibility, and Quality of Telehealth for Adolescent Health Care Delivery During the COVID-19 Pandemic: Cross-sectional Study of Patient and Family Experiences
Bibliographic record
Abstract
BACKGROUND: Data regarding the acceptability, feasibility, and quality of telehealth among adolescents and young adults (AYA) and their parents and caregivers (caregivers) are lacking. OBJECTIVE: The aim of this study was to assess the noninferiority of telehealth versus in-person visits by comparing acceptability with respect to efficiency, effectiveness, equity, patient-centeredness, and confidentiality. METHODS: Cross-sectional web-based surveys were sent to caregivers and AYA following video visits within an Adolescent Medicine subspecialty clinic in May-July 2020. Proportions of AYA and caregivers who rated telehealth as noninferior were compared using chi-squared tests. Feasibility was assessed via items measuring technical difficulties. Deductive thematic analysis using the Institute of Medicine dimensions of health care quality was used to code open-ended question responses. RESULTS: Survey response rates were 20.5% (55/268) for AYA and 21.8% (123/563) for caregivers. The majority of the respondents were White cisgender females. Most AYA and caregivers rated telehealth as noninferior to in-person visits with respect to confidentiality, communication, medication management, and mental health care. A higher proportion of AYA compared to caregivers found telehealth inferior with respect to confidentiality (11/51, 22% vs 3/118, 2.5%, P<.001). One-quarter (14/55) of the AYA patients and 31.7% (39/123) of the caregivers reported technical difficulties. The dominant themes in the qualitative data included advantages of telehealth for efficiency and equity of health care delivery. However, respondents' concerns included reduced safety and effectiveness of care, particularly for patients with eating disorders, owing to lack of hands-on examinations, collection of vital signs, and laboratory testing. CONCLUSIONS: Telehealth was highly acceptable among AYA and caregivers. Future optimization should include improving privacy, ameliorating technical difficulties, and standardizing at-home methods of obtaining patient data to assure patient safety.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".