The Structured Communication Adolescent Guide (SCAG)
Bibliographic record
Abstract
Abstract Introduction The Structured Communication Adolescent Guide (SCAG) has been developed as a teaching, learning, and assessment tool for medical students to obtain feedback from adolescents, both in standardized patient (SP) encounters and real patient examinations. The goal is to improve feedback to learners on their adolescent interviewing Methods The SCAG can be used in a teaching session, for practice by medical students, and in assessment. The time to complete an adolescent interview, depending on the learner and how experienced they are, can take approximately 30-40 minutes (without examination). The written feedback using the SCAG takes the adolescents 5-7 minutes to complete. Verbal feedback given by a SP may also take an additional 5 minutes. Results The SCAG has been used at Dalhousie University for over 7 years, University of Calgary for 3 years, and Queen's University and the University of British Columbia began adopting the SCAG in 2007-2008. The SCAG has been validated and is reliable to be used with untrained adolescents. Therefore, medical schools that are unable to offer an SP program can use the SCAG with a lecture or tutorial after which the students can use the SCAG independently with patients. Discussion The SCAG is considered generalizable as it has been successfully adopted by a number of schools for undergraduate teaching both nationally and internationally with minimal modifications. The SCAG has been shown to be a reliable and valid tool when used by trained adolescent SPs to assess medical student and resident interviewing abilities. The SCAG has also been shown to be reliable with untrained adolescents within a school-based pilot study. More research is needed regarding how the SCAG could be used in family practice, perhaps with trained SPs who are coming in undercover, and/or with the general adolescent patient population that the family practitioners see.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.049 | 0.023 |
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".