The use of telehealth in attention-deficit/hyperactivity disorder: a survey of parents and caregivers
Bibliographic record
Abstract
The use of telehealth became widespread during the COVID-19 pandemic, including in child and adolescent attention-deficit/hyperactivity disorder (ADHD) services. Telehealth is defined as live, synchronous phone and video appointments between a healthcare provider and a parent and/or child with ADHD. There is a dearth of research on the use of telehealth within this population. The aim of this study was to examine parents' and caregivers' perceptions of telehealth for children and adolescents with ADHD. A cross-sectional survey design was employed. Recruitment of parents and caregivers of children and adolescents with ADHD was conducted online. The survey asked participants about their views of telehealth, previous experience, and willingness to use telehealth. Quantitative data were analysed using STATA. Qualitative data were analysed using content analysis. One hundred and twelve respondents participated in the survey. Participants were mostly female (n = 97, 86.6%) and aged between 45 and 54 (n = 64, 57.1%). Of the 61 (54.5%) participants with experience of telehealth, the majority reported that that they were at least satisfied with telehealth visits (n = 36, 59%), whilst approximately half rated their quality more poorly than in-person visits (n = 31, 50.8%). The majority of respondents (n = 91, 81.3%) reported that they would be willing to use telehealth for their child's future appointments. Most common reasons selected for wanting to use telehealth included saving time, improvements to the family routine, and reducing costs. Reasons selected for not wanting to use telehealth included not being able to receive hands-on care, belief that the quality of care is poorer than in-person consultations, and distraction of the child during telehealth visits. The study demonstrates that parents recognise deficits and benefits of telehealth, suggesting a need to build their trust and confidence in remote ADHD care.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".