Perspectives on neurological patient registries: a literature review and focus group study
Bibliographic record
Abstract
BACKGROUND: Patient registries represent a well-established methodology for prospective data collection with a wide array of applications for clinical research and health care administration. An examination and synthesis of registry stakeholder perspectives has not been previously reported in the literature. METHODS: To inform the development of future neurological registries we examined stakeholder perspectives about such registries through a literature review followed by 3 focus groups comprised of a total of 15 neurological patients and 12 caregivers. RESULTS: (1) LITERATURE REVIEW: We identified 6,435 abstracts after duplicates were removed. Of these, 410 articles underwent full text review with 24 deemed relevant to perspectives about neurological and non-neurological registries and were included in the final synthesis. From a patient perspective the literature supports altruism, responsible use of data and advancement of research, among others, as motivating factors for participating in a patient registry. Barriers to participation included concerns about privacy and participant burden (i.e. extra clinic visits and associated costs). (2) Focus groups: The focus groups identified factors that would encourage participation such as: having a clear purpose; low participant burden; and being well-managed among others. CONCLUSIONS: We report the first examination and synthesis of stakeholder perspectives on registries broadly with a specific focus on neurological patient registries. The findings of the broad literature review were congruent with the neurological patient and caregiver focus groups. We report common themes across the literature and the focus groups performed. Stakeholder perspectives need to be considered when designing and operating patient registries. Emphasizing factors that promote participation and mitigating barriers may enhance patient recruitment.
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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 | 0.118 | 0.193 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.037 | 0.029 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 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".