{
  "abstract": "Background\n\nSocial distancing was a cornerstone of the COVID-19 pandemic response, yet evidence on factors associated with adherence remains fragmented and context-specific. We conducted a global meta-analysis to quantify the associations between key individual-level determinants and adherence to social distancing measures.Methods\n\nWe systematically searched six electronic databases from inception to August 20, 2025 to identify studies reporting associations between individual-level determinants and adherence to social distancing measures. Effect estimates were transformed into Pearson's correlation coefficients (r) and pooled using random-effects meta-analysis. Subgroup analyses and meta-regression were conducted to examine regional and temporal variation.Results\n\nOf 10,804 records identified, 58 cross‑sectional studies comprising 545,640 participants were included, and fourteen determinants of adherence to social distancing were assessed. Higher educational attainment (r = 0.09), female sex (r = 0.08), being married (r = 0.08), older age (r = 0.06), higher income (r = 0.07), and greater perceived risk and severity of COVID-19 (r = 0.10) were positively associated with adherence, whereas more conservative political ideology was negatively associated (r = -0.12). No significant associations were observed for perceived government response, comorbidity, place of residence, knowledge and awareness, smoking, employment status, or essential worker status. The magnitude and statistical significance of several associations varied across World Health Organization regions, with the European region showing the highest number of determinants significantly associated with adherence, whereas the African and Eastern Mediterranean regions exhibited the fewest.Conclusion\n\nAdherence to social distancing during COVID-19 was associated with a set of demographic, socioeconomic, psychological, and political factors, with substantial regional heterogeneity. These findings underscore the importance of accounting for contextual and structural differences when interpreting behavioural evidence and designing public health responses to future disease outbreaks.",
  "abstract_shown": true,
  "affiliations": [
    "Agent-Based Modelling Laboratory, Centre of Excellence in AI for Public Health Advancement, York University, Toronto, ON, M3J 1P3, Canada.",
    "Laboratory for Industrial and Applied Mathematics, Centre of Excellence in AI for Public Health Advancement, York University, Toronto, ON, M3J 1P3, Canada.",
    "National Laboratory for Health Security, University of Szeged, Szeged, 6720, Hungary.",
    "Agent-Based Modelling Laboratory, Centre of Excellence in AI for Public Health Advancement, York University, Toronto, ON, M3J 1P3, Canada. moghadas@yorku.ca."
  ],
  "article_type": "systematic review",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Dewan Md Sumsuzzman"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Congjie Shi"
    },
    {
      "affs": [
        2
      ],
      "name": "Gergely Röst"
    },
    {
      "affs": [
        1
      ],
      "name": "Jianhong Wu"
    },
    {
      "affs": [
        3
      ],
      "name": "Seyed M Moghadas",
      "orcid": "0000-0003-4414-0227"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1nj9ckttnv6na.bib",
  "cited_by": 0,
  "doi": "10.1186/s12889-026-28873-1",
  "fulltext_url": "https://europepmc.org/articles/PMC13726038",
  "id": "1nj9ckttnv6na",
  "issns": [
    "1471-2458"
  ],
  "landing_url": "https://europepmc.org/article/MED/42972331",
  "language": "eng",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Systematic Review"
    ],
    [
      "openalex",
      "3312|COVID-19 Prevention and Impact"
    ]
  ],
  "openalex": "W7172555870",
  "pdf_url": "https://europepmc.org/articles/PMC13726038?pdf=render",
  "pmcid": "PMC13726038",
  "pmid": "42972331",
  "published": "2026-08-05",
  "publisher": "BMC",
  "ris": "https://research.draconitic.com/paper/1nj9ckttnv6na.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T15:20:49Z",
      "native_id": "MED:42972331",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42972331"
    },
    {
      "first_seen": "2026-11-05T12:22:27Z",
      "native_id": "PMC13726038",
      "source": "pmc",
      "url": "https://doi.org/10.1186/s12889-026-28873-1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "issn:1471-2458",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Associations between individual-level factors and adherence to social distancing measures during the COVID-19 pandemic: a global meta-analysis.",
  "title_text": "Associations between individual-level factors and adherence to social distancing measures during the COVID-19 pandemic: a global meta-analysis.",
  "type": "peer-reviewed",
  "updated_at": "2026-11-06T12:22:05Z",
  "url": "https://research.draconitic.com/paper/1nj9ckttnv6na",
  "venue": "BMC public health",
  "versions": []
}