Associations between loneliness and outcomes of Common Mental Disorders (CMDs): A systematic review of longitudinal studies
Bibliographic record
Abstract
Abstract Background Loneliness has been increasingly associated with poor mental health outcomes, yet its prognostic role in people with Common Mental Disorders (CMDs) remains unclear. This systematic review aimed to examine whether loneliness is longitudinally associated with mental health outcomes in individuals with CMDs, regardless of treatment status. Methods We searched PsycINFO, MEDLINE, Embase and CINAHL from inception to May 2024 for longitudinal studies examining associations between baseline loneliness and CMD outcomes at follow-up. Eligible studies included adults aged 16+ with CMDs. Study quality was assessed using the Newcastle-Ottawa Scale, and certainty of evidence was evaluated using GRADE. Due to heterogeneity in population and outcomes, a narrative synthesis was conducted. The protocol was registered with PROSPERO (registration number: CRD42023410401). Results Seventeen studies met the inclusion criteria. Most included studies investigated depression-related outcomes (n=13), with fewer addressing suicidal ideation (n=5), anxiety (n=2), and mixed CMD outcomes (n=1). Several studies contributed data to more than one outcome category. We found that high baseline loneliness was consistently associated with poorer depression-related outcomes at follow-up in people with CMDs. This association was observed across clinical, community, and treatment settings. In contrast, evidence for suicidal ideation and anxiety outcomes was limited and mixed, with inconsistent associations and lower study quality. Only two studies examined treatment outcomes, with mixed findings on whether loneliness influenced intervention response. Overall, the GRADE certainty of evidence was high for depression, low for suicidal ideation, and very low for anxiety and mixed CMD outcomes. Conclusions Loneliness appears to be a consistent prognostic factor for poor depression outcomes in people with CMDs, highlighting its potential relevance for assessment and intervention. However, its role in anxiety, suicidality, and treatment response remains unclear. Further high-quality longitudinal research is needed to clarify whether—and under what conditions—loneliness affects broader CMD outcomes and treatment effectiveness.
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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 | 0.019 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.011 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".