Reliability of <scp>DNMSQuest</scp> as a Screening Tool for Mood Disorders in Cervical Dystonia
Bibliographic record
Abstract
BACKGROUND: The high prevalence of mood disorders in cervical dystonia, often unaddressed in botulinum toxin clinics, is a major factor in impaired quality of life. There is a clear need for a brief screening method for identifying these disorders; the Dystonia non-motor symptoms questionnaire (DNMSQuest) has been proposed as such. OBJECTIVE: We aimed to assess the practical utility of the DNMSQuest and compare it with validated rating scales for anxiety, depression and quality of life. METHODS: In 88 patients with cervical dystonia, we compared results from the DNMSQuest with mood rating scales [Beck Anxiety Inventory (BAI), Beck Depression Index (BDI-II) and Hospital Anxiety and Depression Scale (HADS)], quality of life measures [European Quality of Life (EQOL) and European Quality of Life Visual Analogue Scale (EQOLVAS)] and with assessments of dystonia severity [Cervical Dystonia Impact Profile-58 (CDIP58) and Toronto Western Rating Scale for Spasmodic Torticollis (TWSTRS)]. RESULTS: Using a cut off score on the DNMSQuest of 5, we noted that DNMSQuest had a sensitivity of 85% for detecting anxiety and depression using the BAI and BDI-II, and 76% and 78% for anxiety and depression respectively using the HADS. The DNMSQuest correlated strongly with BAI (ρ = 0.715), BDI-II (ρ = 0.658), HADS-Anxiety (ρ = 0.616), HADS-Depression (ρ = 0.706), EQOL (ρ = 0.653) and CDIP-58 (ρ = 0.665). CONCLUSION: The DNMSQuest is a brief, sensitive and non-specific instrument for identifying patients that warrant further review for anxiety and depression and can easily be implemented in a neurologist-run botulinum toxin clinic.
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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 | 0.002 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".