Screening for Bipolar I Disorder and the Rapid Mood Screener
Bibliographic record
Abstract
Effective screening for bipolar I disorder can lead to enhanced assessment, improved diagnosis, and better patient outcomes. The Rapid Mood Screener (RMS), a new bipolar I disorder screening tool, was evaluated in a nationwide survey of health care providers (HCPs). Eligible HCPs were asked to describe their opinions/current use of screening tools, assess the RMS, and evaluate the RMS versus the Mood Disorder Questionnaire (MDQ). Results were stratified by primary care and psychiatric specialty. Findings were reported using descriptive statistics; statistical significance was reported at the 95% confidence level. < .05); 76% reported that they would screen new patients with depressive symptoms, and 68% indicated they would rescreen patients with a depression diagnosis. Most HCPs (84%) said the RMS would have a positive impact on their practice, with 46% saying they would screen more patients for bipolar disorder. In our survey, the RMS was favorably evaluated by HCPs. A large percentage of respondents preferred the RMS over the MDQ and indicated that it would likely have a positive impact on clinicians' screening behavior.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 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".