Variability and predictors of negative mood intensity in patients with borderline personality disorder and recurrent suicidal behavior: Multilevel analyses applied to experience sampling methodology.
Bibliographic record
Abstract
Variability in mood swings is a characteristic of borderline personality disorder (BPD) and is associated with suicidal behavior. This study investigated patterns of mood variability and whether such patterns could be predicted from demographic and suicide-related psychological risk factors. Eighty-two adults with BPD and histories of recurrent suicidal behavior were recruited from 3 outpatient psychiatric programs in Canada. Experience sampling methodology (ESM) was used to assess negative mood intensity ratings on a visual analogue scale, 6 random times daily, for 21 days. Three-level models estimated variability between times (52.8%), days (22.2%), and patients (25.1%) and supported a quadratic pattern of daily mood variability. Depression scores predicted variability between patients' initial rating of the day. Average daily mood patterns depended on levels of hopelessness, suicide ideation, and sexual abuse history. Patients reporting moderate to severe sexual abuse and elevated suicide ideation were characterized by worsening moods from early morning up through evening, with little or no relief; patients reporting mild sexual abuse and low suicide ideation reported improved mood throughout the day. These patterns, if replicated in larger ESM studies, may potentially assist the clinician in determining which patients require close monitoring.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".