What can we learn from pandemic educational methods?: military general practice trainees’ attitudes to feedback from recorded consultations
Bibliographic record
Abstract
BACKGROUND: Recorded consultations are a useful tool for developing consultation skills for general practice speciality trainees (GPSTs). Historical barriers to utility include a lack of recording equipment and trainee discomfort. Widespread use of online communication platforms during the pandemic led to the introduction of the Recorded Consultation Assessment (RCA), prompting an exploration of its impact on GPSTs' attitudes and acceptability of using recorded consultations for feedback. AIM: This sequential explanatory mixed methods study explored attitudes of military GPSTs towards using recorded consultations for feedback to develop consultation skills, and identify factors influencing GPST attitudes. METHODS: Participants of this study completed a questionnaire, followed by a representative sample focus group. Descriptive statistics were used to analyse quantitative data, reflexive thematic analysis was employed for qualitative data. Triangulation was conducted using a meta-matrix. RESULTS: Results indicated agreement among respondents on the usefulness of recorded consultations for developing consultation skills, particularly communication skills. Perceived trainer attitudes significantly influence the GPST utility of this tool. The RCA positively impacted attitudes, providing familiarity, free access to easy-to-use online recording platforms, simplified consenting procedures, secure data storage, and improved feedback quality from trainers. CONCLUSION: Pre-pandemic studies cited equipment access and consent procedures as barriers to utilising recording as a method of feedback. The pandemic and RCA introduced online resources and imperative to utilise this method, resulting in largely positive GPST learning experiences. As we move away from the RCA it is important to retain institutional memory of the benefits gained from feedback using recorded methods.
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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 | 0.053 | 0.195 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| 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 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".