Association between loneliness and suicidality among general populations and persons with depressive and bipolar disorders: A systematic review
Bibliographic record
Abstract
BACKGROUND: Loneliness and suicidality are interrelated phenomena. Several studies suggest that they often co-exist, but the magnitude is unclear. This systematic review aims to analyze this association in general population samples of varying age groups and persons with depressive and bipolar disorders. METHODS: Search terms in this review included words related to loneliness and suicidality among general populations and depressive and bipolar disorders. Databases included PubMed, PsychINFO, and Web of Science. The search occurred up until May 27, 2024. Screening and data extraction were performed independently. Studies were categorized by age group or clinical diagnosis. Quality assessments were conducted using NIH tools. RESULTS: Fifty-six studies met eligibility criteria: 52 involved general population samples and 4 involved patients with depressive or bipolar disorders. In healthy adults aged 18 to 64, loneliness mainly showed a moderate positive correlation with suicidality (r = 0.26 to 0.59), while correlations in older adults (aged 65+) (r = 0.498) and in adolescents aged 13-17 were weaker. In depressive and bipolar disorders, correlations ranged from weak to moderate (r = -0.06 to 0.40), with associations stronger in unadjusted models (UOR = 2.8 to 7.07). Furthermore, some studies suggested that depressive symptoms mediate the association between loneliness and suicidality. CONCLUSION: A moderate and positive association was observed between loneliness and suicidality in healthy adults and patients with depressive disorders. However, the role of bipolar disorders in the association remains unclear. Practitioners should routinely evaluate persons living with depressive or bipolar disorders for loneliness as part of a comprehensive assessment.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".