In-person interventions to reduce social isolation and loneliness: An evidence and gap map
Bibliographic record
Abstract
Background There is a growing body of research indicating that social isolation and loneliness can occur in all age groups, and they have been shown to be linked to increased mortality and poorer health outcomes. Hence the need for research on interventions aiming to alleviate social isolation and loneliness. Objectives To map available evidence on the effects of in-person interventions aimed at mitigating social isolation and/or loneliness across all age groups and settings.Search methods The following databases were searched from inception up to February 2022 with no language restrictions: Ovid MEDLINE, Embase, EBM Reviews – Cochrane Central Register of Controlled Trials, APA PsycInfo via Ovid, CINAHL via EBSCO, EBSCO (all databases except CINAHL), Global Index Medicus, ProQuest (all databases), ProQuest ERIC, Web of Science, Korean Citation Index, Russian Science Citation Index, and SciELO Citation Index via Clarivate, and Elsevier Scopus.Selection criteria Titles, abstracts and full texts of potentially eligible articles identified were screened independently by two reviewers for inclusion following the outlined eligibility criteria. Data collection and analysis We developed and pilot tested a data extraction code set in Eppi-Reviewer. Data was individually extracted and coded. Main results A total of 513 articles were included in this evidence and gap map (421 primary studies and 92 systematic reviews) which assessed the effectiveness of in-person interventions on the reduction of social isolation and loneliness. Most (68%) of the reviews were classified as critically low quality, while less than 5% were classified as high or moderate quality. The evidence is unevenly distributed with most reviews looking at interpersonal delivery and community-based delivery interventions, especially interventions for changing cognition led by a health professional and group activities, respectively. Loneliness, wellbeing, and depression/anxiety were the most assessed outcomes. Most research was conducted in high-income countries, concentrated in the United States, United Kingdom, and Australia, with none from low-income countries. Major gaps were identified in societal level and community-based delivery interventions that address policies and community structures, respectively. Less than 5% of included reviews assessed process indicators or implementation outcomes. Similar trends of findings were found in primary studies. All age groups were represented although more reviews and primary studies focused on older adults ≥ 60 years (60%) than young people ≤ 24 years (34%). Two thirds described how at-risk populations were identified and even fewer assessed differences in effect across PROGRESS-Plus factors for populations experiencing inequities.Authors’ conclusions There is growing evidence that social isolation and loneliness are public health concerns. This evidence and gap map shows the available evidence, at the time of the search, on the effectiveness of in-person interventions at reducing social isolation and loneliness across all ages and settings. Despite a large body of research, with much of it published in more recent years, it is unevenly distributed. Most of the systematic reviews are of critically low quality indicating the need for high quality research. This map can guide funders and researchers to consider the areas in which the evidence is lacking and to address these gaps as future research priorities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.053 | 0.191 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.026 | 0.023 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".