The effects of meditation on individuals facing loneliness: a scoping review
Bibliographic record
Abstract
BACKGROUND: Meditation is defined as a mind and body practice focused on interactions between the brain, mind, body, and behaviour, containing four key elements: a quiet location with little distractions, a comfortable posture, a focus of attention, and an open attitude. We sought to review the benefits of meditation on the alleviation of loneliness. METHODS: A scoping review was conducted based on Arksey and O'Malley's five-stage framework. Eligibility criteria included primary studies of any type that investigated the effects of meditation on loneliness. Search strategies were developed and conducted on MEDLINE, EMBASE, AMED, and CINAHL. The National Center for Complementary and Integrative Health, and American Psychological Association websites were also searched. Articles meeting the inclusion criteria were critically reviewed using a descriptive-analytical narrative method. RESULTS: Thirteen studies met our inclusion criteria and were published between 2012 and 2020 across 10 countries. Eleven studies reported improvements in relation to loneliness. Of the remaining two studies (15%), one mentioned the alleviation of loneliness, but only looked primarily at social closeness in lonely individuals. The other study found a correlation between loneliness and nuclear factor (NF)-κB levels, which was the measured outcome; however, the direct effects of meditation on loneliness were unclear. Three main themes emerged from our analysis, as follows: 1) positive results across all studies, 2) relatively small randomized control trials conducted over the last decade, and 3) lack of diverse demographic information. CONCLUSIONS: While a small number of studies exist at this intersection, given all included studies indicated positive findings, the effects of meditation in alleviating loneliness are promising. Future research should be directed at understanding how meditation mitigates loneliness and how this intervention can impact practice for healthcare professionals.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".