Top 10 Research Themes for Dystonia in Cerebral Palsy
Bibliographic record
Abstract
Dystonia in cerebral palsy (DCP) is a common, debilitating, but understudied condition. The CP community (people with CP and caregivers) is uniquely equipped to help determine the research questions that best address their needs. We developed a community-driven DCP research agenda using the well-established James Lind Alliance methodology. CP community members, researchers, and clinicians were recruited through multiple advocacy, research, and professional organizations. To ensure shared baseline knowledge, participants watched webinars outlining our current knowledge on DCP prepared by a Steering Group of field experts (cprn.org/research-cp-dystonia-edition). Participants next submitted their remaining uncertainties about DCP. These were vetted by the Steering Group and consolidated to eliminate redundancy to generate a list of unique uncertainties, which were then prioritized by the participants. The top-prioritized uncertainties were aggregated into themes through iterative consensus-building discussions within the Steering Group. 166 webinar viewers generated 67 unique uncertainties. 29 uncertainties (17 generated by community members) were prioritized higher than their randomly matched pairs. These were coalesced into the following top 10 DCP research themes: (1) develop new treatments; (2) assess rehabilitation, psychological, and environmental management approaches; (3) compare effectiveness of current treatments; (4) improve diagnosis and severity assessments; (5) assess the effect of mixed tone (spasticity and dystonia) in outcomes and approaches; (6) assess predictors of treatment responsiveness; (7) identify pathophysiologic mechanisms; (8) characterize the natural history; (9) determine the best treatments for pain; and (10) increase family awareness. This community-driven research agenda reflects the concerns most important to the community, both in perception and in practice. We therefore encourage future DCP research to center around these themes. Furthermore, noting that community members (not clinicians or researchers) generated the majority of top-prioritized uncertainties, our results highlight the important contributions community members can make to research agendas, even beyond DCP.
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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 | 0.062 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".