Inflexible Interpretations of Ambiguous Social Situations: A Novel Predictor of Suicidal Ideation and the Beliefs That Inspire It
Bibliographic record
Abstract
Suicidal ideation has been linked to a bias toward interpreting ambiguous information in consistently less positive or more negative manners ( positive/negative interpretation bias), implying that information-processing biases might distort beliefs thought to inspire suicidal ideation (e.g., those regarding burdensomeness). Therefore, in the present study, we examined whether suicidal ideation and beliefs highlighted in theories of suicide are related to positive/negative interpretation bias and/or a bias against revising negative interpretations in response to evidence against them ( negative interpretation inflexibility). Data were collected in three waves, each 1 week apart. Network analyses and structural equation models provided evidence that negative interpretation bias (cross-sectionally) and negative interpretation inflexibility (cross-sectionally and over time) were related to suicidal ideation and that the latter relationship was mediated by perceived burdensomeness. By identifying this mediation pathway in the present study, we provide a potential mechanism by which perceptions of burdensomeness, a key risk factor for suicidality, might arise and/or persist.
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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 | 0.002 | 0.013 |
| 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 | 0.001 |
| 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".