Determinants of loneliness among older adults: A systematic review based on recent longitudinal studies
Bibliographic record
Abstract
AIMS: To synthesize studies examining the determinants of loneliness among older adults based on recent longitudinal observational studies. METHODS: PRISMA guidelines were followed (PROSPERO ID CRD420251006752). In mid-March 2025, four established databases were searched and an additional hand search was performed. Observational longitudinal studies investigating the determinants of loneliness amongst older adults were included published from June 2018 ongoing. We extracted main characteristics and evaluated study quality. RESULTS: Overall, 47 studies were finally included in this review. There is mainly mixed/inconclusive evidence regarding the link between socioeconomic determinants of loneliness, whereas spousal loss was mainly associated with higher loneliness. Regarding support and volunteering determinants, there is cautious evidence showing that volunteering may be beneficial for preventing loneliness. Regarding mental health/psychological factors, most studies showed a bidirectional relation of depressive symptoms and meaning/purpose in life with loneliness. Regarding health-related factors, poor self-rated health was often associated with higher loneliness. There is also some evidence for the link between sensory impairment and higher loneliness, whilst other health-related factors such as functional impairments were not consistently associated with loneliness. CONCLUSIONS: Our systematic review identified some risk factors of loneliness among older adults, including spousal loss, unfavorable mental health, absence of meaning in life, poor self-rated health, and sensory impairment. Furthermore, volunteering may help to avoid loneliness. Thus, efforts to support individuals experiencing spousal loss, avoid poor mental and self-rated health, enhance the meaning in life, maintain sensory abilities, and encourage volunteering may help prevent loneliness in old age.
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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 | 0.015 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| 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".