Codesigning simulations and analyzing the process to ascertain principles of authentic and meaningful research engagement in childhood disability research
Bibliographic record
Abstract
BACKGROUND: Including youth with disabilities and their families as partners in childhood disability research is imperative but can be challenging to do in an authentic and meaningful way. Simulation allows individuals to learn in a controlled environment and provides an opportunity to try new approaches. The objectives of the research study were to (1) codesign a suite of simulations and facilitation resources and understand how stakeholders engaged in the codesign process; and (2) describe the principles of authentic and meaningful research engagement as identified by stakeholders. METHODS: Interdisciplinary stakeholder groups, including youth with disabilities, parents, researchers, and trainees, codesigned simulation training videos by developing shared storylines about challenges with research engagement that were then performed and digitally recorded with standardized patient actors. Two forms of data were collected: (1) observations via field notes and video recordings were analyzed to understand the codesign process; and (2) interviews were analyzed to understand principles of authentic and meaningful engagement. RESULTS: Four simulation training videos were developed, and topics included: (1) forming a project team; (2) identifying project objectives and priorities; (3) reviewing results; and (4) navigating concerns about knowledge translation. Thirteen participants participated in the simulation codesign; nine of whom consented to be observed in the codesign process and seven who completed follow up interviews. We identified two themes about authentic and meaningful engagement in research: (1) whether the invitation to engage on a project was authentic and meaningful or was extended to 'tick a box'; and (2) whether there were authentic and meaningful opportunities to contribute (e.g., valued contributions aligned with people's lived experience, skills, and interests) or if they only served as a 'rubber stamp'. Communication and expectations tied the 'tick box' and 'rubber stamp' themes together and underlie whether engagement was authentic and meaningful. CONCLUSIONS: For research engagement to be authentic and meaningful, researchers and families need to set clear expectations, build rapport, have tangible supports, use clear communication, and build time and space to work together. Future work will explore the utility of the simulations and whether they improve knowledge and attitudes about authentic and meaningful engagement in research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.095 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".