Possible Contribution of Meaning in Life in Patients With Chronic Pain and Suicidal Ideation: Observational Study
Bibliographic record
Abstract
BACKGROUND: Chronic pain is associated with an elevated risk of suicidal ideation (SI). OBJECTIVE: We aimed to examine if the presence or the search for Meaning in Life (MiL) are associated with less SI and explore whether MiL profiles emerge in our cohort. These profiles can be described as high presence-high search, high presence-low search, low presence-low search, and low presence-high search. METHODS: In this observational study, we recruited 70 patients who were referred to the Multidisciplinary Pain Center of the Geneva University Hospitals and who answered positively to question 9 on the Beck Depression Inventory, 2nd Edition, investigating SI. Patients who agreed to participate in the study were further investigated; they participated in a structured diagnostic interview to screen for psychiatric diagnoses. During this interview, they completed the Meaning in Life Questionnaire and the semistructured Scale for Suicide Ideation (SSI) to assess the characteristics and severity of SI. RESULTS: There was a statistically significant correlation between the presence of MiL subscale and the SSI. These 2 scales had a negative and statistically highly significant correlation (R=-.667; P<.001). The results also showed a negative and statistically highly significant correlation between the score of the search for MiL and the SSI (R=-.456; P<.001). The results thus pointed to the presence of MiL as a potential protective factor against the severity of SI, while the search for MiL is also a possible resiliency factor, although to a lesser extent. The profile low presence-low search grouped the vast majority (47%) of the patients; in these patients, the mean SSI score was 14.36 (SD 5.86), much higher compared with that of the other subgroups. CONCLUSIONS: This study's results point to MiL as a concept of interest regarding devising psychotherapeutic interventions for chronic pain patients in order to reduce the suicidal risk and more accurately determine patients' suffering.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".