Describing a Clinical Group Coding Method for Identifying Competencies in an Allied Health Single Session
Bibliographic record
Abstract
Shelley L Craig,1 Lauren B McInroy,2 Andrew D Eaton3 1Factor-Inwentash Faculty of Social Work (FIFSW) at the University of Toronto, Toronto, ON M5S1V4, Canada; 2College of Social Work at the Ohio State University, Columbus, OH 43210, USA; 3FIFSW at the University of Toronto, Toronto, ON M5S1V4, CanadaCorrespondence: Shelley L CraigFactor-Inwentash Faculty of Social Work (FIFSW) at the University of Toronto, Toronto, ON M5S1V4, CanadaTel +1416-978-8847Fax +1416-978-7072Email shelley.craig@utoronto.caIntroduction: Competencies that integrate research findings and practice expertise are necessary to maintain comprehensive evidence-based practice for allied health professions, such as social work. The context of modern multidisciplinary healthcare, especially in acute or emergency settings, means that an individual clinician may only have a single session with a patient. Maximizing the benefit of single sessions requires advanced competence that extends beyond diagnostics and biomedical treatments to the impact of social systems on health outcomes; multi-level advocacy for reduction of existing health disparities and equity in access to health and mental health services; and “working knowledge” of non-pharmacological treatments.Methods: This study employed a practice-based research methodology whereby health social workers group coded 32 simulation videos, drawn from an advanced social work practice course, to develop a practice-based competency framework that incorporates these advanced skills. Constructivist grounded theory was employed through a cyclical coding process of viewing video data, identifying and discussing skills and competencies, and summarizing/synthesizing the discussions for critical reflection.Results: The resulting Clinician Group Coding Method utilized systematic and collaborative group coding of practice simulation videos by three clinicians and two researchers to identify relevant competencies for a single session. Emphasis was placed on the progressive phases of single-session patient interactions (eg, joining, working, ending), a practice format that frequently occurs in social work and other allied health professions. These phases include themes of preparing, agenda setting and refining, addressing context, providing education, planning the next steps, and encouraging success.Discussion: The group coding process allowed for immediate discussions and clarifications, supporting the clinicians to synthesize their experiences toward shared understandings of “best practices” in single-session healthcare contexts. This approach facilitated the understanding of critical actions that allied health clinicians could undertake to improve single-session interactions. This practice-based competency framework may have significant utility for multidisciplinary healthcare education and practice.Keywords: simulation, practice-based research, competence, allied health, group coding, education
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 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 | 0.044 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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".