Cognitions in bipolar affective disorder and unipolar depression: imagining suicide
Bibliographic record
Abstract
OBJECTIVE: Bipolar disorder has the highest rate of suicide of all the psychiatric disorders. In unipolar depression, individuals report vivid, affect-laden images of suicide or the aftermath of death (flashforwards to suicide) during suicidal ideation but this phenomenon has not been explored in bipolar disorder. Therefore the authors investigated and compared imagery and verbal thoughts related to past suicidality in individuals with bipolar disorder (n = 20) and unipolar depression (n = 20). METHODS: The study used a quasi-experimental comparative design. The Structured Clinical Interview for DSM-IV was used to confirm diagnoses. Quantitative and qualitative data were gathered through questionnaire measures (e.g., mood and trait imagery use). Individual interviews assessed suicidal cognitions in the form of (i) mental images and (ii) verbal thoughts. RESULTS: All participants reported imagining flashforwards to suicide. Both groups reported greater preoccupation with these suicide-related images than with verbal thoughts about suicide. However, compared to the unipolar group, the bipolar group were significantly more preoccupied with flashforward imagery, rated this imagery as more compelling, and were more than twice as likely to report that the images made them want to take action to complete suicide. In addition, the bipolar group reported a greater trait propensity to use mental imagery in general. CONCLUSIONS: Suicidal ideation needs to be better characterized, and mental imagery of suicide has been a neglected but potentially critical feature of suicidal ideation, particularly in bipolar disorder. Our findings suggest that flashforward imagery warrants further investigation for formal universal clinical assessment procedures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".