Enhancing patient-oriented research training: participant perceptions of an online course
Bibliographic record
Abstract
Patient-oriented research is now widely regarded as key to improving health systems and patient outcomes. This shift toward meaningful patient involvement in health research has sparked a growing interest in patient-oriented research training across Canada. Yet some barriers to participation, including distance and scheduling constraints, may impede the provision of in-person patient-oriented research training. Virtual course delivery options may help surmount those barriers, as well as offer unique pedagogical advantages. To help increase patient-oriented research training uptake, the research team adapted the Canadian Institutes of Health Research’s (CIHR) Strategy for Patient-Oriented Research’s Foundations for Patient-Oriented Research course to a virtual format. The course consists of three modules, which focus respectively on patient-oriented research, health research methods, and teamwork skills. The current evaluation of this virtual delivery examines how a diverse set of participants received the online course. Course participants from a variety of professional backgrounds, including researchers, patients, clinicians, and policy decision-makers, were recruited from across Canada to participate in the adapted course. Participant and facilitator feedback was solicited via online surveys that were distributed shortly after the delivery of each module. Over the span of the current project, the online course was delivered seven times across Canada. A total of 189 learners and 12 facilitators participated in the course. We received 89 completed feedback surveys in total. These included a total of 78 responses from learners, with 22 on Module 1, 32 on Module 2, and 24 on Module 3, in addition to 11 responses from facilitators. Overall, participants and facilitators were very satisfied with the course, indicating a successful adaptation from traditional to online delivery. Survey respondents were especially pleased with the course’s co-learning elements, which exposed them to fresh perspectives and real patient voices, as well as ample opportunity for discussion. Some participants offered recommendations for minor course revisions. Future iterations of the course will reflect participant and facilitator feedback to enhance accessibility via minor changes to course format (e.g., shorter live sessions), content (e.g., more concrete examples), and workload (e.g., reduced pre-work requirements). Sustainable and effective health care depends on health research that includes active partnerships across diverse populations. These collaborative relationships are fostered by strong capacity in patient-oriented research, which in turn hinges on widely accessible training opportunities. This online course overcomes common barriers to face-to-face training and offers the accessible, inclusive training environment required for sustained progress in patient-oriented research. In the past, patients were only involved in health research as study subjects and were excluded from membership on the research team. Today, it is the norm to involve patients and other non-researchers, such as clinicians and policy makers, as full, active partners in health research projects. This approach is called patient-oriented research, and is regarded as essential for good health care. In 2016, the Canadian Institutes of Health Research (CIHR) developed a course in patient-oriented research that helps people develop the skills they need to work together on a team with researchers, patients, caregivers, care providers, policy makers, and others. However, logistical challenges such as travel distance and scheduling conflicts may create barriers to in-person participation. Our research team adapted CIHR’s course in patient-oriented research for online delivery, which can help overcome these challenges and provide additional educational benefits. We delivered the online course seven times to diverse groups of participants from across Canada, including researchers, patients, clinicians, and policy makers. A total of 189 participants completed at least one of the three course modules. In this article, we examine the results of 89 completed feedback surveys (78 from learners and 11 from facilitators). Overall, the feedback was very positive, with participants appreciating the opportunity to learn from real patient experiences in an inclusive environment. We also received suggestions for improvement, such as reducing pre-work and using more concrete examples, which will be incorporated into future versions of the course. This evaluation shows that this course was successfully adapted for online delivery and offers a valuable opportunity for building skills in patient-oriented research.
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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 | 0.020 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".