DEVELOPING SKILLS FOR DEVELOPMENTAL DISABILITIES PRE-CLINICAL ELECTIVE: DIFFERENT SETTING AND POPULATION PRODUCES CONSISTENT IMPROVEMENT IN STUDENT CONFIDENCE
Bibliographic record
Abstract
Abstract BACKGROUND Medical students feel they are inadequately trained in caring for patients with developmental disabilities (PWDD) (Troller et al. 2016; Salvador-Carulla et al., 2015). Consequently, PWDD may not receive timely, empathetic care from their future clinicians (Sahin and Akyol, 2010). We developed a preclinical elective, “Developing Skills with Developmental Disabilities” (DSDD), to improve student knowledge, skills, and attitudes toward paediatric PWDD. The first cohorts worked with pre-schoolers; DSDD was effective in improving student confidence working with PWDD (Penner et al. 2017). The current project compared the efficacy of DSDD using a hospital-based day-school for elementary-aged children, to previous cohorts. OBJECTIVES Our goal was to determine if changing the population being observed and the setting in which they are being observed could reproduce improvement in student confidence as seen in past cohorts. DESIGN/METHODS The DSDD module was an elective offered to preclinical medical students for credit. Students were given 6 hours of didactics on child development, assistive technologies, and breaking bad news. Students also participated in 6 clinical hours at the Glenrose Rehabilitation Hospital, where they observed school-aged PWDD in a classroom and interacted with an interdisciplinary team. Students also interviewed children’s families during medical intakes. Students completed pre- and post-elective surveys administered on a 5-point Likert scale. Questions pertained to students’ self-perceived comfort and knowledge regarding PWDD. Scores pre- and post-elective were compared using t-test analysis. This data was compared to data collected from previous cohorts, which used the same survey. RESULTS 24 students registered for DSDD, and 21 surveys were able to be analysed. Statistically significant (p<0.01) increases were present in 9/10 self-reported scores, with the statistically insignificant score pertaining to confidence using positive reinforcement. There was no significant difference in pre- and post-elective score improvement when comparing this cohort with past cohorts, across all scores. The critical components of DSDD were maintained across setting changes with significant (p<0.01) increases in students’ self-reported confidence and knowledge in working with PWDD. CONCLUSION This elective demonstrates effectiveness in different settings and ages. The general structure and principles of this elective may be applied by Paediatricians to improve medical education. Examples include having students attend developmental programmes they might provide support for, using a short set of parent interview questions and/or a child observation to improve developmental teaching, and allocating time for interaction with other allied health professionals to better understand their roles in the management of paediatric PWDD.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".