Is the 4-factor model of symptomology equivalent across bipolar disorder subtypes?
Bibliographic record
Abstract
Abstract Background Research with the BDSx (Bipolar Disorder Symptom Scale) suggests a 4-factor structure of responses: two depression (cognitive, somatic) and two hypo/mania factors (elation/loss of insight, affrontive symptoms). The two depression and two hypo/mania factors are correlated; and affrontive symptoms of hypo/mania (e.g., furious, disgusted, argumentative) are positively correlated with both depression factors suggesting pathways for mixed symptom presentation. This grouping of affrontive symptoms of hypo/mania organically emerged in exploratory research and has subsequently been supported in confirmatory analyses between samples and over time. The BDSx has been clinically validated with BD outpatients. Results Over 19 days, we recruited an international sample of 784 adults with BD using micro-targeted, social media advertising (M = 44.48 years, range 18–82). All participants indicated that they had BD (subtype, if known) and had been diagnosed with BD (month, year). This sample size was sufficient to confirm the 4-factor model across subtypes and compare the three (BD I, BD II, BD NOS). Responses to 19 of 20 BDSx items were psychometrically consistent across BD subtypes. Only responses to the ‘hopeless’ item were significantly higher for those with BD II. Conclusions When comparing models, it appears that affrontive symptoms are significantly and uniformly associated with hypo/mania and both depression factors across subtypes. In contrast to BD diagnostic criteria, this suggests that affrontive symptoms are central to the clinical presentation of hypo/mania and mixed symptomology across BD subtypes.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".