Coping styles in prodromes of bipolar mania
Bibliographic record
Abstract
OBJECTIVES: Psychological studies have identified that different coping strategies affect outcome in bipolar disorder (BD), with the possibility of preventing mania by effective coping with prodromes. This study seeks to examine coping mechanisms using a recently developed scale to clarify the relationship of coping styles to clinical and demographic characteristics, and to identify coping differences between bipolar I and II subjects. METHODS: The Coping Inventory for Prodromes of Mania (CIPM) was completed by 203 bipolar patients, along with other diagnostic and clinical measures. The CIPM is organized into four factors of coping including: stimulation reduction (SR), problem-oriented coping (PR), seeking professional help (SPH), denial and blame (DB). CIPM psychometric properties and its relationship to demographic and clinical factors, dysfunctional attitudes, and mood symptoms were examined. Coping profiles were generated by BD subtype (I versus II). RESULTS: The CIPM displayed psychometric properties consistent with the single previous study with this instrument. Neither demographic/clinical characteristics nor mood symptoms showed any particular relationship with the CIPM. Clear differences in coping also emerged between BD I and BD II subjects. BD I tended to use a wider range of coping strategies and scored highly on the SPH factor as compared to BD II subjects. BD II participants preferred to use DB and PR, but were less likely to use SPH and SR. CONCLUSIONS: The CIPM appears to be a valid measure of coping. Coping style preferences appear to differ according to bipolar subtype.
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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 | 0.000 | 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".