Prioritizing ADHD Research and Policy in Canada: Methodological Approaches and Researcher Perspectives
Bibliographic record
Abstract
Priority Setting (PS) processes are essential tools for guiding research efforts toward the most impactful and relevant questions in specific fields. This paper compares and contrasts two widely applied PS methodologies: the James Lind Alliance Priority Setting Protocol (JLA Protocol) and the Delphi Methodology. This paper identifies distinctions between the two approaches, including differences in advisory structures, stakeholder involvement, consensus-building techniques, and dissemination practices. The JLA Protocol emphasizes inclusivity and transparency, producing a concise top 10 list of research priorities, while the Delphi Methodology adapts to varied contexts, relying on statistical measures for consensus without a predefined priority limit. This analysis provides researchers with a comprehensive framework to select the most appropriate PS method, considering study objectives, resource availability, and ethical imperatives. By advancing understanding of PS methodologies, this research contributes to enhancing the alignment of research agendas with stakeholder needs. ADHD can pose significant public health challenges in Canada, with rising diagnoses underscoring gaps in diagnostic reliability, treatment access, and social support. This study employed a multi-wave Delphi approach to identify ADHD research priorities among 45 Canadian researchers, addressing knowledge transmission, diagnostic challenges, treatment options, and social challenges. Participants from multiple stakeholder groups were initially surveyed and, following rigorous data cleaning, 45 researchers completed Wave Three. Participants rated 55 priority items across seven thematic categories, with consensus defined as ≥90% rating an item as high or critical priority. Key findings revealed unanimous consensus on access to well-trained healthcare providers, strong support for educational awareness, access to funded ADHD services socio-emotional functioning research, and including people with lived experience in ADHD research. These priorities are in alignment with the Canadian context, contrast the study by Jacobson et al., (2016) and build on prior studies (i.e., Gaynes et al., 2012; Stephens et al., 2025) by incorporating psychosocial and cultural dimensions. Despite limitations, such as sample diversity, the findings offer actionable insights for policy, emphasizing professional training, gender-sensitive diagnostics, and culturally tailored interventions. Collaborative platforms can translate these priorities into practice, reducing the research-to-policy lag. Future research should diversify stakeholder perspectives and refine methodologies to enhance equity in ADHD support across Canada.
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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 | 0.257 | 0.274 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.016 | 0.027 |
| Science and technology studies | 0.037 | 0.022 |
| Scholarly communication | 0.026 | 0.007 |
| Open science | 0.007 | 0.017 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".