Change in emotion-based narrative as a potential mechanism of change in a brief treatment for borderline personality disorder
Bibliographic record
Abstract
Background: The move from inconsistent and problematic autobiographical narrative to a more coherent and reality-based narrative construction of the Self has been discussed as potential mechanism of change in psychotherapies for personality disorders. So far, little empirical evidence exists that demonstrates in a time-dependent design the role of narrative construction in the treatment of borderline personality disorder, in particular when it comes to understanding the integration of body-related information from the affective system with the autobiographical narrative. The present study aims at demonstrating change in emotion-based narrative markers over brief psychiatric treatment and to assess the impact of these changes on subsequent symptom change. Methods: A total of N = 57 clients with borderline personality disorder were assessed at three timepoint over the course of four months of brief psychiatric treatment, within the context of a secondary process-outcome analysis of a randomized controlled trial. Symptom change was assessed using the OQ-45.2 and emotion-narrative change was assessed using the Narrative-Emotion Process Coding System to code client’s in-session speech in terms of problem, transition and change markers. Results: All three emotion-based marker categories evidenced significant changes in the assumed direction. The reduction in problem emotion-based narrative markers (e.g., empty story telling) between session 1 and 5 into the treatment predicted the symptom reduction assessed between session 5 and 10. Conclusions: Emotion-based narrative construction may be a suitable method to study the pathway of change toward a more coherent and reality-based narrative construction of the Self-in-interaction-with-the-Other. Reduction of emotion-based problem-marker may be a promising candidate for a mechanism of change in treatments for personality disorders which should be tested in a time-dependent controlled design.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 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 teacher head, 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".