Dynamic associations between interpersonal needs and suicidal ideation in a sample of individuals with eating disorders
Bibliographic record
Abstract
BACKGROUND: Over half of individuals with eating disorders experience suicidal ideation at some point in their lives, yet few longitudinal studies have examined predictors of ideation in this at-risk group. Moreover, prospective research has focused on relatively distal or trait-level factors that are informative for distinguishing who is most at risk but not when. Little is known about more proximal or state-level risk factors that fluctuate within an individual, which is critical for determining when a person is most likely to engage in suicidal behaviors. METHODS: Women (N = 97) receiving treatment for their eating disorder completed questionnaires weekly to assess suicidal ideation and interpersonal constructs (i.e. perceived burdensomeness, thwarted belongingness) theorized to be proximal predictors of suicidal desire. Longitudinal multilevel models were conducted to examine both within- and between-person predictors of suicidal ideation across 12 weeks of treatment. RESULTS: Statistically significant within-person effects for burdensomeness (β = 0.06; p < 0.001) indicate that when individuals have greater feelings of burdensomeness compared to their own average, they also experience higher suicidal ideation. We did not find any significant influence of thwarted belongingness or the interaction between burdensomeness and belongingness on suicidal ideation. CONCLUSIONS: This study was the first to examine dynamic associations between interpersonal constructs and suicidal ideation in individuals with eating disorders. Results are only partially consistent with the Interpersonal Theory of Suicide and suggest that short-term changes in burdensomeness may impact suicidal behavior in individuals with eating disorders.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".