An educational game for teaching clinical practice guidelines to Internal Medicine residents: development, feasibility and acceptability
Bibliographic record
Abstract
BACKGROUND: Adherence to Clinical Practice Guidelines (CPGs) remains suboptimal among internal medicine trainees. Educational games are of growing interest and have the potential to improve adherence to CPGs. The objectives of this study were to develop an educational game to teach CPGs in Internal Medicine residency programs and to evaluate its feasibility and acceptability. METHODS: We developed the Guide-O-Game(c) in the format of a TV game show with questions based on recommendations of CPGs. The development of the Guide-O-Game(c) consisted of the creation of a multimedia interactive tool, the development of recommendation-based questions, and the definition of the game's rules. We evaluated its feasibility through pilot testing and its acceptability through a qualitative process. RESULTS: The multimedia interactive tool uses a Macromedia Flash web application and consists of a manager interface and a user interface. The user interface allows the choice of two game styles. We created so far 16 sets of questions relating to 9 CPGs. The pilot testing proved that the game was feasible. The qualitative evaluation showed that residents considered the game to be acceptable. CONCLUSION: We developed an educational game to teach CPGs to Internal Medicine residents that is both feasible and acceptable. Future work should evaluate its impact on educational outcomes.
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 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 | 0.006 | 0.086 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".