An exploratory study on the teaching of evidence-based decision making
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: There is no clear guideline on how to teach students evidence-based decision making (EBDM), so this study aimed to assess the impact of an educational intervention on students’ EBDM skills. Methods: This was an explorative mixed-method study of 12 undergraduate occupational therapy students and their teacher. The teaching was aimed at increasing self-efficacy and cognitive skills in EBDM. Semi-structured interviews were conducted to gather the students’ perceived learning benefits. Before and after the intervention, a self-efficacy questionnaire, a critical thinking test, and scored generic cognitive skills in an argument were used as measures of learning achievements. Content analysis was applied to analyze the interview data. To analyze the quantitative data, the Wilcoxon signed rank test was applied. Results: Following the five teaching sessions, the participants’ experienced (a) an understanding of the value and challenges in individually tailored EBDM, (b) the ability to sort and select information, (c) being more cautious in reasoning and reaching conclusions, and (d) better interaction with clients. These categories were supported by significant increases in measures of self-efficacy and cognitive skills used in EBDM. Active, guided education and working with real clients were reported as powerful stimuli for learning. Conclusion: Critical thinking exercises used in authentic health professional evidence-based decisions are promising methods for promoting EBDM.
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.
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 | 0.013 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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 it