Health Care Professional and Caregiver Attitudes Toward and Usage of Medical Podcasting: Questionnaire Study
Bibliographic record
Abstract
BACKGROUND: Podcasts are used increasingly in medicine. There is growing research into the role of podcasts in medical education, but the use of podcasting as a tool for pediatric parent/caregiver health education is largely unexplored. As parents/caregivers seek medical information online, an understanding of parental preferences is needed. OBJECTIVE: We sought to explore health care professional and parent/caregiver awareness and views on podcasting as a health education tool. METHODS: This survey study was conducted and distributed via in-person collection from parents/caregivers (≥18 years old) in the waiting room of an academic pediatric primary care clinic, targeted social media promotion, and professional listservs for health care professionals in pediatrics. Statistical analysis included chi-square tests of independence between categorical variables. RESULTS: In total, 125 health care professionals and 126 caregivers completed the survey. Of those surveyed, 81% (101/125) of health care professionals and 55% (69/126) of parents/caregivers listened to podcasts (P<.001). Health care professionals and parents/caregivers listed the same top 3 quality indicators for medical podcasts. Podcast listeners were more likely to have higher incomes and use professional websites for information. The survey elicited a variety of reasons for podcast nonengagement. CONCLUSIONS: Health care professionals appear to be more engaged in medical education podcasts than parents/caregivers. However, similar factors were valued when evaluating the quality of a pediatric podcast: accuracy, transparency, and credibility. Professional websites may be one avenue to increase podcast uptake. More needs to be done to explore the use of podcasts and digital media for medical information.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".