Clinical Dimensions Associated With Psychological Pain in Suicidal Patients
Bibliographic record
Abstract
Objective: Psychological pain is a transdiagnostic factor in mental health and a key clinical dimension to understand suicide in patients with mood disorders. However, less is known about the clinical characteristics that predict high psychological pain. The aim of this study was to fill this gap in a sample of patients with mood disorders. Methods: Inpatients admitted for a major depressive episode, according to DSM-IV criteria, from 2010 to 2017 were divided into 3 groups: 178 recent suicide attempters (within the last 7 days), 101 past suicide attempters (lifetime history of suicide attempt), and 93 nonattempters (no lifetime history of suicidal act). At inclusion, current psychopathology, medication, personality traits (impulsivity, anxiety, hopelessness), and childhood trauma were assessed. At inclusion and at 1-year follow-up, depressive symptomatology and current and maximal (within the 15 last days) psychological and physical pain were assessed. Results: At baseline, maximal psychological pain was higher in recent than in past suicide attempters (odds ratio = 1.18 ) and nonattempters (OR = 1.32 ). In the multivariate model, depression severity (OR = 1.11 ) and worst physical pain (OR = 2.53 ) predicted high psychological pain, whereas bipolar disorder (OR = 0.54 ) predicted low psychological pain. During the follow-up, the change in maximal psychological pain was predicted by changes in depressive symptomatology (β = 0.46, P < .001) and maximal physical pain (β = 0.42, P < .003). Finally, among depressive symptoms, guilt, lack of initiative, and loss of appetite better explained maximal psychological pain, both at inclusion and at 1 year (all P < .050). Conclusions: Psychological pain is associated with a recent suicidal act and depressive severity. Due to the strong link between psychological pain and physical pain, future studies should investigate whether psychotropic drugs with analgesic effects protect from psychological pain and therefore from suicide.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".