Parent Perceptions of Trainees in Pediatric Care: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Clinical experience and progressive autonomy are essential components of medical education and must be balanced with patient comfort. While previous studies have suggested that most patients accept trainee involvement in their care, few studies have focused specifically on the views of parents of pediatric patients or examined groups who may not report acceptance. OBJECTIVE: This study aims to understand parental profiles of resident and medical student involvement in pediatric care and to use latent class analysis (LCA) methodology to identify classes of responses associated with parent demographic characteristics. METHODS: We used data from a national cross-sectional web-based survey of 3000 parents. The survey used a 5-point Likert scale to assess 8 measures of parent perceptions of residents and medical students. We included participants who indicated prior experience with residents or medical students. We compared responses about resident involvement in pediatric care with responses about student involvement, used LCA to identify latent classes of parent responses, and compared demographic features between the latent classes. RESULTS: Of the 3000 parents who completed the survey, 1543 met the inclusion criteria for our study. Participants reported higher mean scores for residents than for medical students for perceived quality of care, comfort with autonomously performing an examination, and comfort with autonomously giving medical advice. LCA identified 3 latent classes of parent responses: Trainee-Hesitant, Trainee-Neutral, and Trainee-Supportive. Compared with the Trainee-Supportive and Trainee-Neutral classes, the Trainee-Hesitant class had significantly more members reporting age <30 years, household income < US $50,000, no college degree, and lesser desire to receive future care at a teaching hospital (all P<.05). CONCLUSIONS: Parents may prefer greater clinical autonomy for residents than medical students. Importantly, views associated with the Trainee-Hesitant class may be held disproportionately by members of historically and currently socially marginalized demographic groups. Future studies should investigate underlying reasons for trainee hesitancy in these groups, including the possibility of mistrust in medicine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".