Psychache, Hopelessness, and Suicidal Ideation and Behaviors: A Cross-Sectional Study from China
Bibliographic record
Abstract
This study explored the relationship between variables emphasized in the theory’s first step of the three-step theory (3ST)—psychache, hopelessness, and their interaction—to suicide-related variables (i.e., lifetime suicidal ideation and attempt, past-year suicidal ideation, communication of suicidal thoughts, and self-reported future suicide attempt likelihood). Chinese undergraduate students (N = 11,399; mean age = 20.69 ± 1.35) from seven provinces participated in this cross-sectional survey. They answered the Suicidal Behaviors Questionnaire-Revised, Psychache Scale, and Beck Hopelessness Scale. Bivariate and multivariate analyses were used to examine the association between psychache, hopelessness, and hopelessness × psychache interaction on the outcome variables. Bivariate analyses showed that psychache and hopelessness were correlated with suicidal ideation and behaviors. In multiple regression models, the interaction between psychache and hopelessness was significantly associated with past-year suicidal ideation and self-report chances of a future suicide attempt, p < 0.001, though effect sizes for the interaction term were small. The results are broadly consistent with the 3ST’s proposition of how the combination of pain and hopelessness is related to various suicide-related variables. The low prevalence of suicide-related communication should inform future suicide prevention measures by encouraging help-seeking. Psychache as a correlate of the self-reported likelihood of a future attempt could be further investigated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".