Patient-Oriented Research Competencies in Health (PORCH) for patients, healthcare providers, decision-makers and researchers: protocol of a scoping review
Bibliographic record
Abstract
BACKGROUND: Patient-Oriented Research (POR) is a Canadian initiative for health research that refers to research processes informed by full and active patient involvement in all aspects of the research. Ideally, POR results in a wide dissemination of the research findings and the uptake of such findings in both clinical practice and health policy. The Canadian Institute for Health Research (CIHR) identifies four stakeholder groups that are involved in POR who are envisioned to take on a collaborative role in enacting this approach to research. Those stakeholder groups are patients, researchers, health care providers and healthcare decision-makers. To achieve collaboration among stakeholders in POR, tools, resources, education/training and capacity building are required for each stakeholder group engaged in this work. Therefore, this review focuses on understanding and articulating competencies needed by participants to engage in POR. The aim is to summarize existing knowledge on discrete POR competencies for the four stakeholder groups; to support collaboration among them for uptake and strengthening of POR; and to inform policy, education and future research. Accordingly, our research question is 'What are the POR core competencies needed by patients, researchers, healthcare providers, and decision-makers?' The main objectives are to (1) systematically explore the academic and grey literature on competencies needed for these stakeholder groups to engage in POR; (2) map the eligible publications and research gaps in this area; (3) gain knowledge to support collaboration among stakeholders; and (4) provide recommendations for further research to use competencies that emerge in developing stakeholder groups' readiness to conduct POR. METHODS/DESIGN: We will use a methodologically rigorous scoping review approach including formulation of the research question and development of the protocol; screening and identification of the literature; selection of relevant studies; data extraction; and collation, summary and report of the results. Our eligibility criteria include elements of population (patients, researchers, healthcare providers and decision-makers); concept (competencies: knowledge, skills, attitudes; and POR); context (level of involvement in research, settings, funding sources); study design (sample, stakeholder group, methodology, grey literature, theoretical framework); outcomes (primary: relevant to decision-making/policy and practice; and secondary: relevant to education and research); language (English, French); and timing (1990-2017). Registration with PROSPERO is not eligible for scoping reviews; so, it has not been registered. DISCUSSION: Research on core competencies required to enact POR is in its infancy. In this review, we can articulate what is known and thought about competencies (knowledge, skills and attitudes) needed by individuals on POR research teams and ultimately provide knowledge that could impact research, practice, education and policy. Identification of competencies can contribute to design of healthcare professionals' basic and ongoing educational programmes, patient training in research, and professional development activities for health care providers and decision-makers. In addition, knowledge of core competencies can permit individuals to evaluate their own readiness to enter POR research teams.
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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 | 0.155 | 0.175 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.009 | 0.013 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.055 | 0.013 |
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".