Developing a Taxonomy of Communication Techniques and Aids Used By Healthcare Providers During Patient Consultations: Protocol for a Systematic Review
Bibliographic record
Abstract
BACKGROUND: Currently, there is no available standardized taxonomy of defined communication techniques and aids used by healthcare providers during patient consultations. It is challenging to identify communication techniques that contribute to effective healthcare provider and patient consultations and to replicate communication interventions in research. OBJECTIVE: The aim of this paper is to describe a protocol for the development and pilot of a taxonomy of communication techniques and aids used by healthcare providers during patient consultations. METHODS: A systematic review will be completed to identify eligible studies. Extracted techniques and aids will be organized into a preliminary taxonomy by a multidisciplinary team. The preliminary taxonomy will be piloted by two groups: research assistants trained in taxonomy application and healthcare providers and healthcare professional students not trained in taxonomy use. The pilot will use custom developed video footage of health provider and patient interactions. Interrater validity and interview feedback will be used to inform a Delphi panel of multidisciplinary healthcare providers and patient experts when they convene to finalize the preliminary taxonomy. RESULTS: This study was funded in November 2017 by the Monash University Interdisciplinary Research Seed Funding Scheme. Data collection commenced in March 2018, and data analysis is in progress. We expect the results to be published in 2021. CONCLUSIONS: This is the first known attempt to develop a defined and standardized taxonomy of communication techniques and aids used by healthcare providers in patient consultations. The findings will be used to inform future research by providing a detailed taxonomy of healthcare providers' communication techniques and standardized definitions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/16801.
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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 | 0.124 | 0.171 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.044 | 0.008 |
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".