Assessing the influence of researcher–partner involvement on the process and outcomes of participatory research in autism spectrum disorder and neurodevelopmental disorders: A scoping review
Bibliographic record
Abstract
Participatory research aims to increase the relevance and broaden the implementation of health research by involving those affected by the outcomes of health studies. Few studies within the field of neurodevelopmental disorders, particularly autism spectrum disorders, have involved autistic individuals as partners. This study sought to identify and characterize published participatory research partnerships between researchers and individuals with autism spectrum disorder or other neurodevelopmental disorders and examine the influence of participatory research partnerships on the research process and reported study outcomes. A search of databases and review of gray literature identified seven studies that described participatory research partnerships between academic researchers and individuals with autism spectrum disorder or other neurodevelopmental disorders. A comparative analysis of the studies revealed two key themes: (1) variations in the participatory research design and (2) limitations during the reporting of the depth of the partner's involvement. Both themes potentially limit the application and generalizability of the findings. The results of the review are discussed in relation to the use of evaluative frameworks for such participatory research studies to determine the potential benefits of participatory research partnerships within the neurodevelopmental and autism spectrum disorder populations.
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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 | 0.136 | 0.269 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".