The Influence of Personality Disorder Symptoms on Treatment Outcomes in Bipolar Disorder: A Secondary Analysis of a Randomised Controlled Trial: L’influence des symptômes du trouble de la personnalité sur les résultats du traitement dans le trouble bipolaire : Une analyse secondaire d’un essai randomisé contrôlé
Bibliographic record
Abstract
OBJECTIVES: Many people who are diagnosed with bipolar disorder also have comorbid personality disorder. Few studies have explored how personality disorder may influence pharmacological treatment outcomes. The aim of this study was to conduct a secondary analysis of data from a clinical trial of adjunctive nutraceutical treatments for bipolar depression, to determine whether maladaptive personality traits influence treatment outcomes. METHODS: = 29) above threshold personality disorder symptoms (personality disorder). Outcome measures included: The Montgomery Åsberg Depression Rating Scale, Clinical Global Impressions and Improvement Severity Scales, Patient Global Impressions-Improvement scale, Bipolar Depression Rating Scale, Range of Impaired Functioning Tool, Social and Occupational Functioning Assessment Scale and Quality of Life and Enjoyment Scale (Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form). Generalised estimated equations examined the two-way interactions of personality disorder by time or treatment and investigated personality disorder as a non-specified predictor of outcomes. RESULTS: Over time, the Patient Global Impressions-Improvement scores were significantly higher in those in the personality disorder group. No other significant differences in the two-way interactions of personality disorder by treatment group or personality disorder by time were found. Personality disorder was a significant but non-specific predictor of poorer outcomes on the Bipolar Depression Rating Scale, Range of Impaired Functioning Tool, and Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form, regardless of time or treatment group. CONCLUSIONS: This study highlights the potential impact of maladaptive personality traits on treatment outcomes and suggests that the presence of comorbid personality disorder may confer additional burden and compromise treatment outcomes. This warrants further investigation as does the corroboration of these exploratory findings. This is important because understanding the impact of comorbid personality disorder on bipolar disorder may enable the development of effective psychological and pharmacotherapeutic options for personalised treatments.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".