Characteristics of people with bipolar disorder I with and without auditory verbal hallucinations
Bibliographic record
Abstract
BACKGROUND: Approximately half of people with bipolar disorder type I (BD-I) report the presence of psychotic symptoms at least at some point during their illness. Previous data suggest that more than 20% of people with BD-I report the presence of auditory verbal hallucinations (AVHs), or "voice-hearing" in particular. While work in other disorders with psychotic features (e.g., schizophrenia) indicates that the presence vs. absence of AVHs is associated with poorer clinical outcomes, little is known about their effects on clinical and socioeconomic features in BD-I. METHODS: We investigated whether people with BD-I (N = 119) with AVHs (n = 36) and without AVHs (n = 83) in their lifetime differ in terms of demographic features and clinical measures. Relations with AVHs and other positive symptoms were explored. RESULTS: People with BD-I and AVHs vs. without AVHs had higher manic and positive symptom scores (i.e., higher scores on the hallucinations, delusions, and bizarre behavior subscales). Further, a greater proportion of those with vs. without AVHs reported lower subjective socioeconomic status and tended to have higher rates of unemployment, thus, speaking to the longer-term consequences of AVH presence. CONCLUSION: Our findings suggest that people with BD-I with AVHs exhibit more severe psychotic features and manic symptoms compared to those without. This might be associated with more socioeconomic hardship. More in-depth characterization of people with BD-I with/without AVHs is needed to fully understand this subgroup's unique challenges and needs. LIMITATIONS: The modest sample size of the AVH group and a study population with low racial diversity/representation may limit generalizability.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".