Development of a New Care Pathway for Depression and Anxiety in Adult‐Onset Isolated Dystonia
Bibliographic record
Abstract
Background: Recently, we identified barriers and facilitators to the screening and treatment of depressive and anxiety symptoms in adult-onset isolated dystonia (AOID). These symptoms are common, functionally impairing, and often underdetected and undertreated. Objectives: To develop a care pathway for mood symptoms in AOID. Methods: We used a multistep modified Delphi approach to seek consensus among healthcare professionals with experience of AOID on the screening, diagnosis, and treatment of mood symptoms. A combination of face-to-face meetings and online surveys was performed from 2019 to 2020. We created the survey and then reviewed with stakeholders before 2 rounds of Delphi surveys, all of which was finally reviewed in a consensus meeting. A purposive sample of 41 expert stakeholders from 4 Canadian provinces, including neurologists, nurses, psychiatrists, psychologists, and family physicians, was identified by the research team. Results: The Delphi process led to consensus on 12 statements that operationalized a pathway of care to screen for and manage depression and anxiety in people with AOID. Key actions of the pathway included yearly screening with self-rated instruments, multidisciplinary involvement in management involving local networks of providers coordinated by movement disorders neurologists, and access to educational resources. The Delphi panel indicated the 2 core steps as the documentation of the most recent screening outcome and the documentation of a management plan for patients who were positive at the last screening. Conclusions: This new care pathway represents a potentially useful intervention that can be used to build an integrated model of care for AOID.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".