Fluctuations in unmet interpersonal needs and emotional pain among adolescents with and without depression: A daily diary study
Bibliographic record
Abstract
Introduction: Emotional pain and unmet interpersonal needs, i.e., thwarted belongingness and perceived burdensomeness, are associated with increased risk for suicidality. This study examined their daily occurrence and variability among adolescents at both lower and higher risk for suicidality, and whether unmet interpersonal needs predicted daily emotional pain. Method: Fifty-five adolescents with and without major depressive disorder (MDD) completed 10 consecutive daily diaries assessing feelings of burdensomeness, loneliness (as a proxy for thwarted belongingness), and emotional pain. Descriptive analyses examined the occurrence, severity, and variability in these daily experiences. Within-person associations of daily unmet interpersonal needs with emotional pain were examined using multilevel modeling. Results: Adolescents with MDD reported greater occurrence, severity, and variability in day-to-day loneliness, burdensomeness, and emotional pain, compared to adolescents without MDD. Daily unmet interpersonal needs independently and interactively predicted daily emotional pain across both groups, such that greater emotional pain was experienced on days when participants reported greater loneliness and burdensomeness than usual for them. Conclusions: Although adolescents with MDD present with more unmet interpersonal needs and emotional pain, the within-person associations between daily unmet interpersonal needs and emotional pain are similar between adolescents with and without MDD. Daily fluctuations in unmet interpersonal needs and emotional pain over time may represent a potential mechanism via which increasing risk for suicidal ideation is accrued longitudinally.
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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 | 0.004 |
| 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 | 0.001 | 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".