Study protocol: A cross-sectional survey of clinicians to identify barriers to clinical practice guideline implementation in the assessment and treatment of persistent tic disorders
Bibliographic record
Abstract
INTRODUCTION: Eight members of the International Parkinson's Disease and Movement Disorders Society Tic and Tourette Syndrome Study Group formed a subcommittee to discuss further barriers to practice guideline implementation. Based on expert opinion and literature review, the consensus was that practice variations continue to be quite broad and that many barriers in different clinical settings might negatively influence the adoption of the American Academy of Neurology and the European Society for the Study of Tourette Syndrome published guidelines. OBJECTIVES: 1) To identify how clinical practices diverge from the existing American Academy of Neurology and European Society for the Study of Tourette Syndrome guidelines, and 2) to identify categories of barriers leading to these clinical care gaps. METHODS AND ANALYSIS: This article presents the methodology of a planned cross-sectional survey amongst healthcare professionals routinely involved in the clinical care of patients with persistent tic disorders, aimed at 1) identifying how practices diverge from the published guidelines; and 2) identifying categories of barriers leading to these clinical care gaps. Purposeful sampling methods are used to identify and recruit critical persistent tic disorders stakeholders. The analysis will use descriptive statistics.
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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 | 0.050 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".