The Diagnostic clinical Interview for Drug Withdrawal 1 (DID-W1) – New Symptoms of Selective Serotonin Reuptake Inhibitors (SSRI) or Serotonin Norepinephrine Reuptake Inhibitors (SNRI): inter-rater reliability
Bibliographic record
Abstract
Aim: A wide range of clinical phenomena have been reported with dose reduction or drug discontinuation of Selective Serotonin Reuptake Inhibitors (SSRIs) or Serotonin Norepinephrine Reuptake Inhibitors (SNRIs). In 2015, a new classification of SRIs/SNRIs withdrawal (i.e., new withdrawal symptoms, rebound symptoms withdrawal, persistent post-withdrawal disorders) was outlined on the basis of the literature and clinical observations. A semistructured clinical interview, the Diagnostic clinical Interview for Drug Withdrawal 1 - New Symptoms of SSRI and SNRI (DID-W1), was developed for identifying and differentiating such syndromes. Its inter-rater reliability has been tested. Methods: Seventeen consecutive outpatients with a history of SSRI or SNRI dose reduction or discontinuation were assessed independently by 2 clinicians at different times during the same day. Percent agreement, Cohen’s kappa, and the squared correlation coefficient were used to measure inter-rater reliability. Results: The percent agreement for the whole interview was 97.06%, the Cohen’s kappa 0.85 (95% CI of 0.61-1.08), the squared correlation coefficient 0.72. Discussion and conclusions: The kappa values indicated excellent inter-rater agreement. Validity evaluation and comparison with other instruments need to be performed. The DID-W1 may help diagnosing the clinical phenomena related to SSRI and SNRI discontinuation, their differentiation from relapse, and the potential iatrogenic origin of psychiatric symptoms in clinical practice.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".