Does patient and public involvement influence the development of competency frameworks for the health professions? A systematic review
Bibliographic record
Abstract
Competency frameworks typically describe the perceived knowledge, skills, attitudes and other characteristics required for a health professional to practice safely and effectively. Patient and public involvement in the development of competency frameworks is uncommon despite delivery of person-centered care being a defining feature of a competent health professional. This systematic review aimed to determine how patients and the public are involved in the development of competency frameworks for health professions, and whether their involvement influenced the outcome of the competency frameworks. Studies were identified from six electronic databases (MEDLINE, CINAHL, PsycINFO, EMBASE, Web of Science and ERIC). The database search yielded a total of 8,222 citations, and 43 articles were included for data extraction. Most studies were from the United Kingdom (27%) and developed through multidisciplinary collaborations involving two or more professions (40%). There was a large variation in the number of patients and members of the public recruited (range 1-1,398); recruitment sources included patients and carers with the clinical condition of interest (30%) or established consumer representative groups (22%). Common stages for involving patients and the public were in generation of competency statements (57%) or reviewing the draft competency framework (57%). Only ten studies (27%) took a collaborative approach to the engagement of patients and public in competency framework development. The main ways in which involvement influenced the competency framework were validation of health professional-derived competency statements, provision of desirable behaviors and attitudes and generation of additional competency statements. Overall, there was a lack of reporting regarding the details and outcome of patient and public involvement. Further research is required to optimize approaches to patient and public involvement in competency framework development including guidance regarding who, how, when and for what purposes they should be engaged and the requirements for reporting. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier: CRD42020203117.
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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 | 0.033 | 0.145 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".