Key factors for promoting protective behaviours in future pandemics: An umbrella review

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Understanding the factors that enable or hinder these behaviours is essential for improving preparedness and response in future health crises. This umbrella review aimed to synthesize evidence on determinants of protective behaviours during pandemics and provide recommendations for policy and practice. Methods: Following PRISMA 2020 guidelines, we conducted an umbrella review on peer reviewed literature reviews and meta-analyses published between 2020 and 2025. Searches in Epistemonikos, MEDLINE, and Scopus (last update June 2025) targeted reviews on “protective behaviours” and “COVID-19”. Eligibility criteria followed the Population–Concept–Context framework: general population, multifactorial determinants of protective behaviours, and pandemic contexts. Data extraction was performed in a table which included review characteristics, behavioural domains (general compliance, medical interventions, conversation promotion, information handling, hygiene, physical distancing, and other behaviours), and factor valence. Quality appraisal used the Joanna Briggs Institute checklist. Results: From 86 records identified, 11 met inclusion criteria, covering COVID-19 and other diseases. (e.g., H1N1, SARS, MERS, Ebola). Quality scores averaged 8.8/10. Protective behaviours were influenced by three categories of factors: (1) sociodemographic (age, gender, education, socio-economic status), (2) personal (perceptions, beliefs, trust in authorities and science, political orientation), and social and environmental factors (access to protective materials, social norms, community support, health education and communication, policies). Enabling factors included trust in credible sources, perceived effectiveness of measures, and multimodal communication. Barriers comprised misinformation, conspiracy beliefs, and resource inaccessibility. Some factors (e.g., age, gender, education) showed inconsistent effects across behaviours. Findings underscore the need for culturally sensitive messaging, transparent communication, and targeted interventions for vulnerable populations. Conclusions: This umbrella review synthesizes multi-level determinants enabling or hindering protective behaviours during pandemics. It provides evidence-based guidance for policymakers to design targeted interventions through trusted communication channels, culturally appropriate messaging, and addressing the specific needs of different demographic groups. The findings underscore the importance of consistent, positive messaging for pandemic preparedness and response. Registration: PROSPERO registration number: CRD42023467236. Funding: Brussels-Capital Region – Innoviris. COVID-19 disease outbreaks pandemic epidemic public health protective behaviours enabling factors barriers review Figures Figure 1 Figure 2 Text box 1. Contributions to the literature • Synthesizes evidence from 11 reviews across seven behavioural domains, offering a comprehensive overview of factors influencing protective behaviours during pandemics. • Identifies multi-level determinants (sociodemographic, psychological, and social/environmental) and categorizes them as enabling, hindering, or neutral, supporting targeted interventions. • Highlights inconsistencies and potential effect modifiers, providing insights into heterogeneity and guiding context-sensitive policy design. • Offers actionable recommendations for policymakers, emphasizing trust-building, culturally appropriate communication, and equitable resource distribution. • Addresses gaps in previous literature by integrating findings from diverse pandemics and proposing directions for future research on behavioural determinants. Introduction The COVID-19 pandemic of 2020 highlighted the vulnerabilities of a globally interconnected society to various crises (1). The pandemic underscored the limitations of biomedical interventions, and the need to have social and behavioural strategies alongside them. As was also the case for previous outbreaks, measures to curb the pandemic such as physical distancing, mask-wearing, and vaccination necessitated behavioural adjustments from both citizens and health professionals, and called for community cooperation and supportive collective actions (2-4), especially as scepticism regarding health system efficacy and perceptions of unjust or unnecessary measures intensified individuals’ reactance against preventive behaviour. Therefore, effective management of a health crisis requires a careful integration of communication, information dissemination, and individual support. Experience with previous epidemics illustrates the dual necessity of health and social management in epidemic control (5). This involves six strategic components: virus transmission control, maintaining healthcare quality, preventive measures in various environments, managing imported cases, risk reduction in vulnerable settings, and promoting community responsibility through sanitary practices. Of these, promoting protective behaviours during a pandemic is vital for public health. The significance of protective behaviours has been well-established in scientific research, not least during COVID-19. To promote individual protective behaviours, authorities typically use a mix of information and sensibilisation, and legislative approaches. Analysing the psychological and social factors that influence these behaviours can enhance intervention effectiveness (5-9). Protective behaviours are shaped by cognitive, emotional, and social influences. Public health messaging must clearly convey disease risks and preventive benefits. Although studies on protective behaviour adoption during epidemics yield inconsistent results due to different methodologies used, several reviews have consolidated insights on the factors that affect the adoption of protective behaviour (10-12). Of these, a high perceived risk of infection combined with trust in information sources appears to be of crucial influence (8, 9, 13). This paper aims to synthesize findings on actionable policy recommendations during pandemics by presenting an umbrella review compiling the results from various studies into an accessible format (14, 15). By summarizing evidence on facilitators and barriers to protective behaviours, it can enhance the understanding of the subject and guide government interventions during future public health crises. The purpose of this umbrella review is to answer the following question: “What factors enabled or hindered protective behaviours during COVID-19 and infectious diseases outbreaks?” Methods Search strategy An umbrella review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines (16) was conducted on published literature reviews and meta-analyses regarding protective behaviours and COVID-19. The Epistemonikos, MEDLINE, and Scopus databases were consulted using “COVID-19” and “protective behaviours” as search terms, accommodating for variations in American and British English. Filters were applied to identify (systematic) reviews and meta-analyses (for queries, see Supplementary File 1). The search occurred in November 2023 and was updated in June 2025. Framework and eligibility criteria The “Population-Concept-Context” framework (17) and eligibility criteria are presented in Table 1. Table 1 Population-Concept-Context framework and Eligibility criteria Population General population globally • Included: Humans from all age groups • Excluded: Clinical populations Concept Multifactorial determinants of protective behaviours adoption during infectious disease outbreaks • Scope: Facilitators, barriers, and ineffective factors of protective behaviours against Covid-19 or other infectious diseases considered in reviews related to COVID-19 • Types: All factor categories (e.g., psychological, social, environmental, economic, cultural, interventions) • Behaviours: Protective behaviours (including behaviours perceived as protective, without scientific consensus, such as hoarding) and adherence to recommendations, and specific measures (e.g., mask wearing, physical distancing, hand hygiene) Context Covid-19 pandemic and other infectious diseases • Temporal: Throughout pandemic phases (no distinction between early/later stages) • Geographic: Global scope Inclusion criteria Peer reviewed review studies or meta-analyses • Language: English, French, Dutch Exclusion criteria Grey literature, conference outputs, books, preprints, theses (i.e., not peer reviewed) Research without causal relationship with protective behaviours, intentions or attitudes towards protective behaviours, or retroactive effects of protective behaviours (e.g., the influence of mask wearing on distancing) Selection and Synthesis Procedure The selection and screening of the reviews followed the PRISMA 2020 guidelines(16). Figure 1 presents the selection process. Titles and abstracts of all search results were screened independently by two researchers (AC and SR). Disagreements about inclusion were discussed to reach a consensus. Studies meeting the inclusion criteria were read by one of the researchers (AC or SR), leading to the extraction of the following data: type of pandemics or epidemics; population/sample description; methods; theoretical framework; objective of the review; enabling, hindering and ineffective factors; and protective behaviours. Quality assessment was performed by one researcher (AC) and SciSpace (18) with Joanna Briggs Institute critical appraisal checklist for systematic reviews and research syntheses (19). Influencing factors were sorted by categories of protective behaviours to summarize what enables, hinders or has no impact on the following types of behaviour: general protective behaviours and compliance, medical interventions, promoting conversation, handling information and misinformation, hygiene and prevention of spreading infection, physical distancing, and “other behaviours”. The latter encompasses non-evidence-based strategies adopted by portions of the population (e.g., herding). Consideration of Effect Modifiers and Heterogeneity No quantitative heterogeneity analysis was performed because this umbrella review synthesizes findings from systematic reviews rather than primary studies. However, potential effect modifiers and sources of variability were considered qualitatively during data synthesis. These included sociodemographic characteristics (e.g., age, gender, education, socioeconomic status), psychological factors (e.g., trust in authorities and science, perceived susceptibility and severity, beliefs), and contextual elements (e.g., cultural norms, resource availability, policy enforcement). Differences in pandemic context (COVID-19 vs. H1N1 vs. Ebola), population type (general population vs. healthcare workers vs. refugees), and methodological diversity across reviews (e.g., scoping vs. systematic vs. rapid reviews) were also noted as reasons for heterogeneity in reported effects. Protocol and Registration This umbrella review followed the PRISMA 2020 checklists, available in Supplementary File 2. The research protocol is registered on PROSPERO, the international prospective register of systematic reviews of the National Institute for Health Research (registration number: CRD42023467236; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023467236). RESULT Overview of the search results The search yielded 23 references from Epistemonikos, 32 from Medline, and 31 from Scopus (Figure 1). Following the removal of 35 duplicates, 51 records were screened based on titles and abstracts. Of these, 31 articles were excluded for reasons including irrelevance (n=15), lack of methodological reporting (n=13), non-selected languages (n=2), and not being peer-reviewed (n=1). The eligibility assessment of the remaining 20 studies and 1 study derived from a study protocol led to the exclusion of 10 additional papers, with 6 not qualifying as reviews (i.e., no proper methodology) and 4 being outside the review's scope. Consequently, 11 reviews were deemed suitable for data extraction. Variability in reported effects likely reflects differences in populations, cultural contexts, and methodological approaches. Description of selected reviews The data from the selected reviews and the quality assessment are detailed in Supplementary File 3. The eleven reviews, published from 2020 to 2025, encompass various types: rapid scoping (20), systematic (21-24), integrative (25), rapid (26, 27), rapid evidence review (28), scoping (29), and integrative rapid narrative (30). The number of articles in these studies ranges from 13 to 78, with a mean of 44.09. In addition to COVID-19, other diseases examined include H1N1 (20, 22, 24, 27, 28, 30), influenza (20, 24, 25, 27, 28), SARS (22, 28, 30), MERS (22, 27, 30), Ebola (22), HIV, hepatitis, Zika (27), tuberculosis, pertussis (24), other respiratory viruses (28), and hypothetical pandemics (30). One study (25) specifically addresses seasonal influenza to offer recommendations for COVID-19. Quality of the reviews is satisfactory with a mean score of 8.8/10 (min=7/10, max=10/10). The methodologies of the studies are articulated in all reviews, with ten of them specifying the countries from which data were collected, spread across the following continents: Africa (20, 22, 24), Asia (20-24, 28-30), Europe (20, 22-24, 26, 30), North America (20, 22-24, 26, 28, 30), Oceania (20, 22-24, 26, 28, 30), and South America (23, 24). Four reviews incorporate theoretical frameworks, including health behaviour change models (25), health belief model (24), behaviour change wheel (24, 29, 30), the Capability-Opportunity-Motivation-Behaviour framework (29) and the theoretical domain framework (30). Information is collated on communication styles (20, 21, 27), compliance (24-26, 29, 30), trust and belief systems (22, 23), and interventions to curb pandemics and epidemics (28). The quality of the studies was assessed in four reviews (23, 25, 28, 29) and three reported risk bias (23, 24, 28). Table 2 presents the enabling and hindering factors influencing protective behaviour as well as neutral factors, categorized into the seven groups of behaviour mentioned above. The subsequent sections elaborate on the influence of the factors regrouped into three categories (Figure 2) on the relevant protective behaviours. Sociodemographic factors Age Older individuals exhibit enhanced compliance and adoption of protective behaviours such as hygiene and transmission prevention, while younger adults demonstrate lower compliance with distancing directives. However, one study indicated negligible age-related impacts on compliance, particularly concerning mask-wearing (26). Sex or gender Female individuals show higher compliance and adoption of protective behaviours such as hygiene, transmission prevention, and distancing measures (26, 30), whereas males are less likely to wear masks (30). Similar to age, some findings suggest minimal effects of sex or gender on compliance and protective behaviour adoption, specifically regarding mask use and distancing (27, 30). Socio-economic and health status Higher socio-economic status, contrary to financial and food insecurity, and larger household size correlate with greater compliance and adoption of protective behaviours (24, 26). Factors such as marital status and financial concerns facilitate compliance with distancing directives; however, other studies indicate minimal or no effect of socio-economic status on compliance. Furthermore, employment and health status do not influence how well people follow protective behaviours overall. Similarly, employment and household status do not affect hygiene practices, and socio-economic status does not impact mask usage. Additionally, race, ethnicity, household structure, socio-economic status, employment, or health status do not affect compliance with distancing guidelines (26). Level of education Educational attainment does not influence overall compliance or hygiene practices (26, 28) but is positively associated with mask-wearing and respiratory etiquette (30). One review suggested that higher education fosters compliance with distancing rules (30), while another deemed it non-influential on such behaviours (26). Knowledge and experience foster vaccination, while inadequate information or fake news hinders it (24, 25), particularly among minority and migrant populations (20). Knowledge also improves general compliance (24, 29) although some studies do not show any effect (26). Awareness of public health guidelines does not necessarily translate to compliance with protective behaviours (26), and vaccine education alone does not guarantee uptake (25). Personal factors Trust Trust can pertain to various entities, including authorities, science, medicine, healthcare staff and agencies, and media. Trust in authorities and healthcare staff correlates with general compliance, despite some studies indicating no effect (20, 22, 26, 29). Trust may mitigate misinformation, enables knowledge (20, 22) and fosters compliance with directives, though its impact on the latter is contested. A deficit in trust is linked to hoarding behaviours (20). Trust in science and medicine encourages compliance and willingness to engage with health services (20, 22) but does not influence compliance with distancing measures (26). Trust in COVID-19 vaccines enhances vaccination rates, while mistrust diminishes them (24, 25). Trust in media may encourage herding behaviour. Conversely, trust in others does not affect compliance or protective behaviour adoption (26). Perceptions Perceived effectiveness of guidelines enhances compliance (26). The perception of COVID-19 as a threat presents mixed findings, with some studies identifying it as enabling and others asserting no significant impact on compliance (26, 29). Perceived threat levels of COVID-19 do not affect hygiene practices or compliance with distancing directives (26). Perceptions of susceptibility, severity, and health are related to compliance with general protective behaviours, distancing, and hygiene practices, although misinformation regarding fatality rates does not impact mask-wearing (24, 30). Vulnerability perceptions and professional duty enhance vaccination willingness (25). Acceptance of school closures is challenging for those who view them as ineffective and believe their children are at low risk (30). Beliefs Conspiracy beliefs hinder various protective behaviours, including compliance, despite some studies finding no effect (23, 26). These beliefs negatively impact vaccination rates, mask-wearing, and hygiene practices, although some studies report no effect. Furthermore, conspiracy beliefs may promote alternative protective actions such as hoarding, discrimination, and pseudo-scientific practices involving alternative remedies (23). Religious, personal or medical beliefs also reduce general adherence to recommendations (24, 29) Political preferences Political conservatism impedes general compliance and politics do not influence mask wearing or respect for distancing directives (26). Other personal factors Habits and past behaviours (previous vaccination) promote vaccination (25) and hand and general hygiene (30). Compliance with guidelines (26) and positive attitude towards isolation (29) correlates with the adoption of protective behaviours. Anxiety promotes cough or sneeze cover, and disgust generates hand and general hygiene (30). Social or physical environment Access to protective materials Provision of and access to resources, hygiene materials, sanitizers and masks, is essential for general adherence to recommendations, hand and general hygiene, and sanitizer use (25, 28, 29); however, one study indicated that specific provision of mask with use instructions and sanitizer may have no or a hindering impact on hygiene practices (28). Health education and communication Educational interventions (e.g., hygiene education, media campaigns, training sessions, posters, etc.) generally promote testing (29), hand and general hygiene (26, 28), mask-wearing, use of sanitizers, cough and sneeze cover (28) testing, and conversation promotion (27). However, few interventions report no or negative effects (27, 28). Multimodal communication and access to traditional media enhance compliance (20, 21, 24, 26, 29), while moralistic messaging enables acceptance of school closures but does not impact compliance with distancing (26). Health policies Recommendations from authorities and legislation/obligation with monitoring enable general compliance and vaccine uptake (24, 29). Financial support enhances adherence, vaccination, and treatment (24, 25). Social determinants Social pressure or influencers, and peer communication may affect general compliance in both ways (29) but improve compliance with hygiene practices, conversation promotion, and quarantine compliance (27, 30). Socio-cultural and community norms reduce global adherence, distancing measures, and testing propensity (29), while ethnicity and anti-vaccination groups reduced vaccination rate (24). The sense of collective responsibility encourages general compliance, vaccination, and distancing (25, 29). Social support improves adherence to measures and treatment (24). Discussion Main findings of this study This investigation identified key strategies to promote protective behaviours during pandemics. These include targeting non-compliant populations, enhancing trust in authorities and scientific evidence, addressing conspiracy theories, disseminating tailored information and educational resources, and ensuring access to hygiene materials. This study synthesized findings from eleven reviews that examined seven distinct protective behaviours: overall compliance with protective measures, medical interventions (including vaccination, testing, and treatment), conversation promotion, information acquisition, (hand) hygiene, physical distancing, and “others”. These behaviours are influenced by three categories of factors. Socio-demographic factors (i.e., age, sex or gender, socio-economic and health status, and level of education) are not directly amendable by policies but must be acknowledged to identify hesitant populations for intervention. Psychological factors (i.e., trust, perceptions, beliefs, political inclinations, and other personal elements) constitute the individual variables that could be targeted through communication campaigns and policies. The social or physical environment (i.e., accessibility to protective materials, health education and communication, health policies, and social determinants) encompasses overarching contextual elements that can also be enhanced for improved compliance. The reviews emphasized the importance of transparent, timely communication and health education. Effective messaging should integrate risk alerts with actionable advice, clarify evolving recommendations, and offer alternatives to risky behaviours. Rapid dissemination of new information and correction of earlier messages are also crucial (26, 31, 32). What is already known on this topic The COVID-19 pandemic highlighted the vital role of protective behaviours—such as mask-wearing, hand hygiene, physical distancing, and isolation—in limiting disease transmission (33). Evidence from previous pandemics (H1N1, SARS, MERS, Ebola) has consistently demonstrated that successful adoption of protective behaviours depends on multiple interconnected factors spanning individual, social, and structural levels. Theoretical frameworks including the Health Belief Model, Theory of Planned Behaviour, Capability-Opportunity-Motivation-Behaviour models, and Social Cognitive Theory have identified risk perception, self-efficacy, social norms, and outcome expectations as key determinants. Prior research has also shown that beyond knowledge, factors like social cohesion, trust in public authorities, and perceived government competence are essential for effective crisis response. Communication strategies, information source credibility, and message framing significantly influence behaviour adoption across diverse populations. However, existing reviews have typically focused on single behaviours or specific populations, and studies yield inconsistent results due to methodological variations and cultural differences. A comprehensive understanding of the enabling and inhibiting factors across different behavioural domains remained fragmented, limiting the development of unified, evidence-based frameworks for pandemic preparedness and targeted policy guidance across diverse health crisis contexts. What this study adds This study consolidates insights from existing reviews into a unified framework, offering a broad synthesis of protective and obstructive factors across multiple behaviours. It provides actionable guidance for policymakers by identifying behavioural targets and intervention strategies grounded in behavioural science and public health. This research has implications for policy and public health. First, the multi-level framework encompassing demographics, individual and social factors, education, communication, perceptions, beliefs, and misinformation enables targeted resource allocation and intervention design for maximum population impact while addressing root causes of behaviour resistance. Second, the identification of common facilitators across behaviours (trust, risk perception, social norms, self-efficacy) provides evidence for integrated rather than siloed policy approaches, improving cost-effectiveness and reducing intervention fatigue. Third, the synthesis reveals critical considerations for health equity, as demographic factors, socioeconomic status, and misinformation disproportionately affect vulnerable populations, demanding culturally sensitive, linguistically appropriate, and inclusive intervention strategies that address structural barriers. Fourth, the findings underscore ethical tensions between individual autonomy and collective responsibility, requiring careful balance in policy implementation while respecting human rights and democratic principles. Fifth, the communication and education findings highlight the need for transparent, timely, and scientifically accurate public health messaging that builds rather than erodes public trust. The study also outlines future directions, such as investing in healthcare infrastructure, enhancing surveillance and diagnostics, and fostering international cooperation. The study underscores the importance of combining communication, regulation, incentives, and social influence to promote compliance and resilience in future pandemics. Limitations of this study This review is limited to peer-reviewed literature in English, French, and Dutch, excluding grey literature and studies on pandemics other than COVID-19, although some of the selected reviews included grey literature and other infectious diseases. Several of the reviews (22, 23, 25, 27) noted the poor quality of the primary studies they included and the lack of comparative, experimental, or longitudinal designs. Inconsistencies must also be acknowledged (see factors in grey tint in Table 2); they may be due to different definitions of the factors across included studies and methodological limitations (e.g., cross-sectional designs, convenience sampling, lack of sound statistical analyses). The discrepancies may indicate that factors are interconnected and that they should be considered as systems, potentially with network analyses, instead of separately. These gaps highlight the need for more robust research. Observed heterogeneity may be explained by differences in sociodemographic profiles, trust levels, cultural norms, and resource availability. Methodological diversity and pandemic context further contribute to variability. Additionally, while this review offers strategic insights, it cannot fully account for the dynamic and context-specific nature of public health crises. Future research should explore how to strengthen trust in institutions and mobilize social capital to enhance societal resilience. Despite these limitations, the findings can inform emergency preparedness plans, including simulations, resource distribution, and coordination with local authorities (14, 15, 28, 30), and support prevention strategies that empower individuals and communities to navigate uncertainty (5-8). Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials Any data that could not be found in the supplementary files can be obtained upon reasonable request to the corresponding author. Competing interests The authors report no competing interests. Funding This work was supported by the Brussels-Capital Region - Innoviris. Author’s contributions Study Design: SR Data Collection: AC, SR Data Analysis: AC, SR, CG Manuscript Drafting: AC, MVH, SVdB Figure and table: AC Supplementary Material: AC, SR Manuscript Revision: All the authors Acknowledgements We would like to thank Dr Nathan Nguyen for his valuable contribution to the development of the research queries. AC, SR and Dr Nathan Nguyen were funded by the Brussels-Capital Region - Innoviris on the Pandorix project. References Corbin JH, Oyene UE, Manoncourt E, Onya H, Kwamboka M, Amuyunzu-Nyamongo M, et al. A health promotion approach to emergency management: effective community engagement strategies from five cases. Health Promot Int. 2021;36(Supplement1):i24–38. 10.1093/heapro/daab152 . Atlas R, Rubin C, Maloy S, Daszak P, Colwell R, Hyde B. One health—attaining optimal health for people, animals, and the environment. Microbe. 2010;5(9):383–9. Bish A, Michie S. 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BMC Infect Dis. 2020;20(1):607. 10.1186/s12879-020-05340-9 . Osterholm MT. Preparing for the next pandemic. In: Cockerham WC, Cockerham GB, editors. The Covid-19 Reader. Routledge; 2020. pp. 11–20. Alami H, Lehoux P, Fleet R, Fortin J-P, Liu J, Attieh R, et al. How can health systems better prepare for the next pandemic? Lessons learned from the management of COVID-19 in Quebec (Canada). Front Public Health. 2021;9:671833. Balisi S, Madisa M. COVID-19 preventative measures: Lessons for public health policy. Open J Social Sci. 2021;9(7):1–14. Table 2 Table 2 is available in the Supplementary Files section. Additional Declarations Competing interest reported. Stephan Van den Broucke is member of the editorial board of Archive of Public Health. Supplementary Files ManuscriptAoPHTable2.docx SupplementaryFile1SearchStrategyHighlightedchanges.docx SupplementaryFile2PRISMAChecklist.docx SupplementaryFile3DataExtractedandCriticalAppraisal.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 14 Feb, 2026 Reviews received at journal 20 Jan, 2026 Reviews received at journal 18 Jan, 2026 Reviews received at journal 16 Jan, 2026 Reviewers agreed at journal 05 Jan, 2026 Reviewers agreed at journal 05 Jan, 2026 Reviewers agreed at journal 03 Jan, 2026 Reviewers invited by journal 03 Jan, 2026 Editor assigned by journal 23 Dec, 2025 Submission checks completed at journal 23 Dec, 2025 First submitted to journal 19 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8405099","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":569654422,"identity":"3cef93ef-d937-4893-a127-eb50f817f398","order_by":0,"name":"Aurélien 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2","display":"","copyAsset":false,"role":"figure","size":4241812,"visible":true,"origin":"","legend":"\u003cp\u003eClassification of the factors related to protective behaviours.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote.\u003c/em\u003e Icons were retrieved from the Flaticon database accessible at www.flaticon.com.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8405099/v1/74d2faa9d8b4e10a84fc21e1.png"},{"id":99805292,"identity":"2750da10-2f8c-434e-abec-7ff7363c3f96","added_by":"auto","created_at":"2026-01-08 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Stephan Van den Broucke is member of the editorial board of Archive of Public Health.","formattedTitle":"Key factors for promoting protective behaviours in future pandemics: An umbrella review","fulltext":[{"header":"Text box 1. Contributions to the literature","content":"\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026bull; Synthesizes evidence from 11 reviews across seven behavioural domains, offering a comprehensive overview of factors influencing protective behaviours during pandemics.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026bull; Identifies multi-level determinants (sociodemographic, psychological, and social/environmental) and categorizes them as enabling, hindering, or neutral, supporting targeted interventions.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026bull; Highlights inconsistencies and potential effect modifiers, providing insights into heterogeneity and guiding context-sensitive policy design.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026bull; Offers actionable recommendations for policymakers, emphasizing trust-building, culturally appropriate communication, and equitable resource distribution.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026bull; Addresses gaps in previous literature by integrating findings from diverse pandemics and proposing directions for future research on behavioural determinants.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe COVID-19 pandemic of 2020 highlighted the vulnerabilities of a globally interconnected society to various crises (1). The pandemic underscored the limitations of biomedical interventions, and the need to have social and behavioural strategies alongside them. As was also the case for previous outbreaks, measures to curb the pandemic such as physical distancing, mask-wearing, and vaccination necessitated behavioural adjustments from both citizens and health professionals, and called for community cooperation and supportive collective actions (2-4), especially as scepticism regarding health system efficacy and perceptions of unjust or unnecessary measures intensified individuals\u0026rsquo; reactance against preventive behaviour. Therefore, effective management of a health crisis requires a careful integration of communication, information dissemination, and individual support.\u003c/p\u003e\n\u003cp\u003eExperience with previous epidemics illustrates the dual necessity of health and social management in epidemic control (5). This involves six strategic components: virus transmission control, maintaining healthcare quality, preventive measures in various environments, managing imported cases, risk reduction in vulnerable settings, and promoting community responsibility through sanitary practices. Of these, promoting protective behaviours during a pandemic is vital for public health. The significance of protective behaviours has been well-established in scientific research, not least during COVID-19. To promote individual protective behaviours, authorities typically use a mix of information and sensibilisation, and legislative approaches. Analysing the psychological and social factors that influence these behaviours can enhance intervention effectiveness (5-9). Protective behaviours are shaped by cognitive, emotional, and social influences. Public health messaging must clearly convey disease risks and preventive benefits. Although studies on protective behaviour adoption during epidemics yield inconsistent results due to different methodologies used, several reviews have consolidated insights on the factors that affect the adoption of protective behaviour (10-12). Of these, a high perceived risk of infection combined with trust in information sources appears to be of crucial influence (8, 9, 13).\u003c/p\u003e\n\u003cp\u003eThis paper aims to synthesize findings on actionable policy recommendations during pandemics by presenting an umbrella review compiling the results from various studies into an accessible format (14, 15). By summarizing evidence on facilitators and barriers to protective behaviours, it can enhance the understanding of the subject and guide government interventions during future public health crises. The purpose of this umbrella review is to answer the following question: \u0026ldquo;What factors enabled or hindered protective behaviours during COVID-19 and infectious diseases outbreaks?\u0026rdquo;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cu\u003eSearch\u0026nbsp;\u003c/u\u003e\u003cu\u003estrategy\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eAn umbrella review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines (16) was conducted on published literature reviews and meta-analyses regarding protective behaviours and COVID-19. The Epistemonikos, MEDLINE, and Scopus databases were consulted using \u0026ldquo;COVID-19\u0026rdquo; and \u0026ldquo;protective behaviours\u0026rdquo; as search terms, accommodating for variations in American and British English. Filters were applied to identify (systematic) reviews and meta-analyses (for queries, see Supplementary File 1). The search occurred in November 2023 and was updated in June 2025.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFramework and eligibility criteria\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe \u0026ldquo;Population-Concept-Context\u0026rdquo; framework (17) and eligibility criteria are presented in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Population-Concept-Context framework and Eligibility criteria\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003ePopulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 903px;\"\u003e\n \u003cp\u003eGeneral population globally\u003cbr\u003e\u0026nbsp;\u0026bull; Included: Humans from all age groups\u003cbr\u003e\u0026nbsp;\u0026bull; Excluded: Clinical populations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eConcept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 903px;\"\u003e\n \u003cp\u003eMultifactorial determinants of protective behaviours adoption during infectious disease outbreaks\u003cbr\u003e\u0026nbsp;\u0026bull; Scope: Facilitators, barriers, and ineffective factors of protective behaviours against Covid-19 or other infectious diseases considered in reviews related to COVID-19\u003cbr\u003e\u0026nbsp;\u0026bull; Types: All factor categories (e.g., psychological, social, environmental, economic, cultural, interventions)\u003cbr\u003e\u0026nbsp;\u0026bull; Behaviours: Protective behaviours (including behaviours perceived as protective, without scientific consensus, such as hoarding) and adherence to recommendations, and specific measures (e.g., mask wearing, physical distancing, hand hygiene)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eContext\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 903px;\"\u003e\n \u003cp\u003eCovid-19 pandemic and other infectious diseases\u003cbr\u003e\u0026nbsp;\u0026bull; Temporal: Throughout pandemic phases (no distinction between early/later stages)\u003cbr\u003e\u0026nbsp;\u0026bull; Geographic: Global scope\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eInclusion criteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 903px;\"\u003e\n \u003cp\u003ePeer reviewed review studies or meta-analyses\u003cbr\u003e\u0026nbsp;\u0026bull; Language: English, French, Dutch\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eExclusion criteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 903px;\"\u003e\n \u003cp\u003eGrey literature, conference outputs, books, preprints, theses (i.e., not peer reviewed)\u003cbr\u003e\u0026nbsp;Research without causal relationship with protective behaviours, intentions or attitudes towards protective behaviours, or retroactive effects of protective behaviours (e.g., the influence of mask wearing on distancing)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cu\u003eSelection and Synthesis Procedure\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe selection and screening of the reviews followed the PRISMA 2020 guidelines(16). Figure 1 presents the selection process. Titles and abstracts of all search results were screened independently by two researchers (AC and SR). Disagreements about inclusion were discussed to reach a consensus. Studies meeting the inclusion criteria were read by one of the researchers (AC or SR), leading to the extraction of the following data: type of pandemics or epidemics; population/sample description; methods; theoretical framework; objective of the review; enabling, hindering and ineffective factors; and protective behaviours. Quality assessment was performed by one researcher (AC) and SciSpace (18) with Joanna Briggs Institute critical appraisal checklist for systematic reviews and research syntheses (19). Influencing factors were sorted by categories of protective behaviours to summarize what enables, hinders or has no impact on the following types of behaviour: general protective behaviours and compliance, medical interventions, promoting conversation, handling information and misinformation, hygiene and prevention of spreading infection, physical distancing, and \u0026ldquo;other behaviours\u0026rdquo;. The latter encompasses non-evidence-based strategies adopted by portions of the population (e.g., herding).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConsideration of Effect Modifiers and Heterogeneity\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eNo quantitative heterogeneity analysis was performed because this umbrella review synthesizes findings from systematic reviews rather than primary studies. However, potential effect modifiers and sources of variability were considered qualitatively during data synthesis. These included sociodemographic characteristics (e.g., age, gender, education, socioeconomic status), psychological factors (e.g., trust in authorities and science, perceived susceptibility and severity, beliefs), and contextual elements (e.g., cultural norms, resource availability, policy enforcement). Differences in pandemic context (COVID-19 vs. H1N1 vs. Ebola), population type (general population vs. healthcare workers vs. refugees), and methodological diversity across reviews (e.g., scoping vs. systematic vs. rapid reviews) were also noted as reasons for heterogeneity in reported effects.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eProtocol and Registration\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis umbrella review followed the PRISMA 2020 checklists, available in Supplementary File 2. The research protocol is registered on PROSPERO, the international prospective register of systematic reviews of the National Institute for Health Research (registration number: CRD42023467236; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023467236).\u003c/p\u003e"},{"header":"RESULT","content":"\u003cp\u003e\u003cu\u003eOverview of\u0026nbsp;\u003c/u\u003e\u003cu\u003ethe\u0026nbsp;\u003c/u\u003e\u003cu\u003esearch results\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe search yielded 23 references from Epistemonikos, 32 from Medline, and 31 from Scopus (Figure 1). Following the removal of 35 duplicates, 51 records were screened based on titles and abstracts. Of these, 31 articles were excluded for reasons including irrelevance (n=15), lack of methodological reporting (n=13), non-selected languages (n=2), and not being peer-reviewed (n=1). The eligibility assessment of the remaining 20 studies and 1 study derived from a study protocol led to the exclusion of 10 additional papers, with 6 not qualifying as reviews (i.e., no proper methodology) and 4 being outside the review\u0026apos;s scope. Consequently, 11 reviews were deemed suitable for data extraction. Variability in reported effects likely reflects differences in populations, cultural contexts, and methodological approaches.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eDescription of selected reviews\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe data from the selected reviews and the quality assessment are detailed in Supplementary File 3. The eleven reviews, published from 2020 to 2025, encompass various types: rapid scoping (20), systematic (21-24), integrative (25), rapid (26, 27), rapid evidence review (28), scoping (29), and integrative rapid narrative (30). The number of articles in these studies ranges from 13 to 78, with a mean of 44.09. In addition to COVID-19, other diseases examined include H1N1 (20, 22, 24, 27, 28, 30), influenza (20, 24, 25, 27, 28), SARS (22, 28, 30), MERS (22, 27, 30), Ebola (22), HIV, hepatitis, Zika (27), tuberculosis, pertussis (24), other respiratory viruses (28), and hypothetical pandemics (30). One study (25) specifically addresses seasonal influenza to offer recommendations for COVID-19. Quality of the reviews is satisfactory with a mean score of 8.8/10 (min=7/10, max=10/10).\u003c/p\u003e\n\u003cp\u003eThe methodologies of the studies are articulated in all reviews, with ten of them specifying the countries from which data were collected, spread across the following continents: Africa (20, 22, 24), Asia (20-24, 28-30), Europe (20, 22-24, 26, 30), North America (20, 22-24, 26, 28, 30), Oceania (20, 22-24, 26, 28, 30), and South America (23, 24). Four reviews incorporate theoretical frameworks, including health behaviour change models (25), health belief model (24), behaviour change wheel (24, 29, 30), the Capability-Opportunity-Motivation-Behaviour framework (29) and the theoretical domain framework (30). Information is collated on communication styles (20, 21, 27), compliance (24-26, 29, 30), trust and belief systems (22, 23), and interventions to curb pandemics and epidemics (28). The quality of the studies was assessed in four reviews (23, 25, 28, 29) and three reported risk bias (23, 24, 28).\u003c/p\u003e\n\u003cp\u003eTable 2 presents the enabling and hindering factors influencing protective behaviour as well as neutral factors, categorized into the seven groups of behaviour mentioned above. The subsequent sections elaborate on the influence of the factors regrouped into three categories (Figure 2) on the relevant protective behaviours.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eSociodemographic factors\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOlder individuals exhibit enhanced compliance and adoption of protective behaviours such as hygiene and transmission prevention, while younger adults demonstrate lower compliance with distancing directives. However, one study indicated negligible age-related impacts on compliance, particularly concerning mask-wearing (26).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSex or gender\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFemale individuals show higher compliance and adoption of protective behaviours such as hygiene, transmission prevention, and distancing measures (26, 30), whereas males are less likely to wear masks (30). Similar to age, some findings suggest minimal effects of sex or gender on compliance and protective behaviour adoption, specifically regarding mask use and distancing (27, 30).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSocio-economic and health status\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHigher socio-economic status, contrary to financial and food insecurity, and larger household size correlate with greater compliance and adoption of protective behaviours (24, 26). Factors such as marital status and financial concerns facilitate compliance with distancing directives; however, other studies indicate minimal or no effect of socio-economic status on compliance. Furthermore, employment and health status do not influence how well people follow protective behaviours overall. Similarly, employment and household status do not affect hygiene practices, and socio-economic status does not impact mask usage. Additionally, race, ethnicity, household structure, socio-economic status, employment, or health status do not affect compliance with distancing guidelines (26).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLevel of education\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEducational attainment does not influence overall compliance or hygiene practices (26, 28) but is positively associated with mask-wearing and respiratory etiquette (30). One review suggested that higher education fosters compliance with distancing rules (30), while another deemed it non-influential on such behaviours (26). Knowledge and experience foster vaccination, while inadequate information or fake news hinders it (24, 25), particularly among minority and migrant populations (20). Knowledge also improves general compliance (24, 29) although some studies do not show any effect (26). Awareness of public health guidelines does not necessarily translate to compliance with protective behaviours (26), and vaccine education alone does not guarantee uptake (25).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003ePersonal factors\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTrust\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTrust can pertain to various entities, including authorities, science, medicine, healthcare staff and agencies, and media. Trust in \u003cem\u003eauthorities\u003c/em\u003e and \u003cem\u003ehealthcare staff\u003c/em\u003e correlates with general compliance, despite some studies indicating no effect (20, 22, 26, 29). Trust may mitigate misinformation, enables knowledge (20, 22) and fosters compliance with directives, though its impact on the latter is contested. A deficit in trust is linked to hoarding behaviours (20). Trust in \u003cem\u003escience and medicine\u003c/em\u003e encourages compliance and willingness to engage with health services (20, 22) but does not influence compliance with distancing measures (26). Trust in COVID-19 \u003cem\u003evaccines\u003c/em\u003e enhances vaccination rates, while mistrust diminishes them (24, 25). Trust in \u003cem\u003emedia\u003c/em\u003e may encourage herding behaviour. Conversely, trust in \u003cem\u003eothers\u003c/em\u003e does not affect compliance or protective behaviour adoption (26).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePerceptions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePerceived effectiveness of guidelines enhances compliance (26). The perception of COVID-19 as a threat presents mixed findings, with some studies identifying it as enabling and others asserting no significant impact on compliance (26, 29). Perceived threat levels of COVID-19 do not affect hygiene practices or compliance with distancing directives (26).\u003c/p\u003e\n\u003cp\u003ePerceptions of susceptibility, severity, and health are related to compliance with general protective behaviours, distancing, and hygiene practices, although misinformation regarding fatality rates does not impact mask-wearing (24, 30). Vulnerability perceptions and professional duty enhance vaccination willingness (25). Acceptance of school closures is challenging for those who view them as ineffective and believe their children are at low risk (30).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBeliefs\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eConspiracy beliefs hinder various protective behaviours, including compliance, despite some studies finding no effect (23, 26). These beliefs negatively impact vaccination rates, mask-wearing, and hygiene practices, although some studies report no effect. Furthermore, conspiracy beliefs may promote alternative protective actions such as hoarding, discrimination, and pseudo-scientific practices involving alternative remedies (23). Religious, personal or medical beliefs also reduce general adherence to recommendations (24, 29)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePolitical preferences\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePolitical conservatism impedes general compliance and politics do not influence mask wearing or respect for distancing directives (26).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOther personal factors\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHabits and past behaviours (previous vaccination) promote vaccination (25) and hand and general hygiene (30). Compliance with guidelines (26) and positive attitude towards isolation (29) correlates with the adoption of protective behaviours. Anxiety promotes cough or sneeze cover, and disgust generates hand and general hygiene (30).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eSocial or physical environment\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAccess to protective materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eProvision of and access to resources, hygiene materials, sanitizers and masks, is essential for general adherence to recommendations, hand and general hygiene, and sanitizer use (25, 28, 29); however, one study indicated that specific provision of mask with use instructions and sanitizer may have no or a hindering impact on hygiene practices (28).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHealth education and communication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEducational interventions (e.g., hygiene education, media campaigns, training sessions, posters, etc.) generally promote testing (29), hand and general hygiene (26, 28), mask-wearing, use of sanitizers, cough and sneeze cover (28) testing, and conversation promotion (27). However, few interventions report no or negative effects (27, 28).\u003c/p\u003e\n\u003cp\u003eMultimodal communication and access to traditional media enhance compliance (20, 21, 24, 26, 29), while moralistic messaging enables acceptance of school closures but does not impact compliance with distancing (26).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHealth policies\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRecommendations from authorities and legislation/obligation with monitoring enable general compliance and vaccine uptake (24, 29). Financial support enhances adherence, vaccination, and treatment (24, 25).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSocial determinants\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSocial pressure or influencers, and peer communication may affect general compliance in both ways (29) but improve compliance with hygiene practices, conversation promotion, and quarantine compliance (27, 30). Socio-cultural and community norms reduce global adherence, distancing measures, and testing propensity (29), while ethnicity and anti-vaccination groups reduced vaccination rate (24). The sense of collective responsibility encourages general compliance, vaccination, and distancing (25, 29). Social support improves adherence to measures and treatment (24).\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cu\u003eMain findings of this study\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis investigation identified key strategies to promote protective behaviours during pandemics. These include targeting non-compliant populations, enhancing trust in authorities and scientific evidence, addressing conspiracy theories, disseminating tailored information and educational resources, and ensuring access to hygiene materials. This study synthesized findings from eleven reviews that examined seven distinct protective behaviours: overall compliance with protective measures, medical interventions (including vaccination, testing, and treatment), conversation promotion, information acquisition, (hand) hygiene, physical distancing, and \u0026ldquo;others\u0026rdquo;. These behaviours are influenced by three categories of factors. \u003cem\u003eSocio-demographic factors\u003c/em\u003e (i.e., age, sex or gender, socio-economic and health status, and level of education) are not directly amendable by policies but must be acknowledged to identify hesitant populations for intervention. \u003cem\u003ePsychological factors\u003c/em\u003e (i.e., trust, perceptions, beliefs, political inclinations, and other personal elements) constitute the individual variables that could be targeted through communication campaigns and policies. The \u003cem\u003esocial or physical environment\u003c/em\u003e (i.e., accessibility to protective materials, health education and communication, health policies, and social determinants) encompasses overarching contextual elements that can also be enhanced for improved compliance.\u003c/p\u003e\n\u003cp\u003eThe reviews emphasized the importance of transparent, timely communication and health education. Effective messaging should integrate risk alerts with actionable advice, clarify evolving recommendations, and offer alternatives to risky behaviours. Rapid dissemination of new information and correction of earlier messages are also crucial (26, 31, 32).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eWhat is already known on this topic\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe COVID-19 pandemic highlighted the vital role of protective behaviours\u0026mdash;such as mask-wearing, hand hygiene, physical distancing, and isolation\u0026mdash;in limiting disease transmission (33). Evidence from previous pandemics (H1N1, SARS, MERS, Ebola) has consistently demonstrated that successful adoption of protective behaviours depends on multiple interconnected factors spanning individual, social, and structural levels. Theoretical frameworks including the Health Belief Model, Theory of Planned Behaviour, Capability-Opportunity-Motivation-Behaviour models, and Social Cognitive Theory have identified risk perception, self-efficacy, social norms, and outcome expectations as key determinants. Prior research has also shown that beyond knowledge, factors like social cohesion, trust in public authorities, and perceived government competence are essential for effective crisis response. Communication strategies, information source credibility, and message framing significantly influence behaviour adoption across diverse populations. However, existing reviews have typically focused on single behaviours or specific populations, and studies yield inconsistent results due to methodological variations and cultural differences. A comprehensive understanding of the enabling and inhibiting factors across different behavioural domains remained fragmented, limiting the development of unified, evidence-based frameworks for pandemic preparedness and targeted policy guidance across diverse health crisis contexts.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eWhat this study adds\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis study consolidates insights from existing reviews into a unified framework, offering a broad synthesis of protective and obstructive factors across multiple behaviours. It provides actionable guidance for policymakers by identifying behavioural targets and intervention strategies grounded in behavioural science and public health. This research has implications for policy and public health. First, the multi-level framework encompassing demographics, individual and social factors, education, communication, perceptions, beliefs, and misinformation enables targeted resource allocation and intervention design for maximum population impact while addressing root causes of behaviour resistance. Second, the identification of common facilitators across behaviours (trust, risk perception, social norms, self-efficacy) provides evidence for integrated rather than siloed policy approaches, improving cost-effectiveness and reducing intervention fatigue. Third, the synthesis reveals critical considerations for health equity, as demographic factors, socioeconomic status, and misinformation disproportionately affect vulnerable populations, demanding culturally sensitive, linguistically appropriate, and inclusive intervention strategies that address structural barriers. Fourth, the findings underscore ethical tensions between individual autonomy and collective responsibility, requiring careful balance in policy implementation while respecting human rights and democratic principles. Fifth, the communication and education findings highlight the need for transparent, timely, and scientifically accurate public health messaging that builds rather than erodes public trust. The study also outlines future directions, such as investing in healthcare infrastructure, enhancing surveillance and diagnostics, and fostering international cooperation. The study underscores the importance of combining communication, regulation, incentives, and social influence to promote compliance and resilience in future pandemics.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eLimitations of this study\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis review is limited to peer-reviewed literature in English, French, and Dutch, excluding grey literature and studies on pandemics other than COVID-19, although some of the selected reviews included grey literature and other infectious diseases. Several of the reviews (22, 23, 25, 27) noted the poor quality of the primary studies they included and the lack of comparative, experimental, or longitudinal designs. Inconsistencies must also be acknowledged (see factors in grey tint in Table 2); they may be due to different definitions of the factors across included studies and methodological limitations (e.g., cross-sectional designs, convenience sampling, lack of sound statistical analyses). The discrepancies may indicate that factors are interconnected and that they should be considered as systems, potentially with network analyses, instead of separately.\u0026nbsp;These gaps highlight the need for more robust research.\u003c/p\u003e\n\u003cp\u003eObserved heterogeneity may be explained by differences in sociodemographic profiles, trust levels, cultural norms, and resource availability. Methodological diversity and pandemic context further contribute to variability.\u003c/p\u003e\n\u003cp\u003eAdditionally, while this review offers strategic insights, it cannot fully account for the dynamic and context-specific nature of public health crises. Future research should explore how to strengthen trust in institutions and mobilize social capital to enhance societal resilience.\u003c/p\u003e\n\u003cp\u003eDespite these limitations, the findings can inform emergency preparedness plans, including simulations, resource distribution, and coordination with local authorities\u0026nbsp;(14, 15, 28, 30), and support prevention strategies that empower individuals and communities to navigate uncertainty (5-8).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eEthics approval and consent to participate\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNot applicable\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConsent for publication\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNot applicable\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAvailability of data and materials\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAny data that could not be found in the\u0026nbsp;\u003c/em\u003e\u003cem\u003esupplementary files\u003c/em\u003e\u003cem\u003e\u0026nbsp;can be obtained upon reasonable request to the corresponding author.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eCompeting interests\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors report no competing interests.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFunding\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Brussels-Capital Region - Innoviris.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAuthor\u0026rsquo;s contributions\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStudy Design: SR\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData Collection: AC, SR\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData Analysis: AC, SR, CG\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eManuscript Drafting: AC, MVH, SVdB\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFigure and table: AC\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSupplementary Material: AC, SR\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eManuscript Revision: All the authors\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAcknowledgements\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWe would like to thank Dr Nathan Nguyen for his valuable contribution to the development of the research queries.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAC, SR and Dr Nathan Nguyen were funded by\u0026nbsp;\u003c/em\u003ethe Brussels-Capital Region - Innoviris\u003cem\u003e\u0026nbsp;on the Pandorix project.\u003c/em\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCorbin JH, Oyene UE, Manoncourt E, Onya H, Kwamboka M, Amuyunzu-Nyamongo M, et al. 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Front Public Health. 2021;9:671833.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBalisi S, Madisa M. COVID-19 preventative measures: Lessons for public health policy. Open J Social Sci. 2021;9(7):1\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Table 2","content":"\u003cp\u003eTable 2 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aoph","sideBox":"Learn more about [Archives of Public Health](http://archpublichealth.biomedcentral.com/)","snPcode":"13690","submissionUrl":"https://submission.nature.com/new-submission/13690/3","title":"Archives of Public Health","twitterHandle":"@Archpubhealth","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, disease outbreaks, pandemic, epidemic, public health, protective behaviours, enabling factors, barriers, review","lastPublishedDoi":"10.21203/rs.3.rs-8405099/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8405099/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The COVID-19 pandemic highlighted the critical importance of protective behaviours—such as mask-wearing, hand hygiene, and physical distancing—in managing health crises. Understanding the factors that enable or hinder these behaviours is essential for improving preparedness and response in future health crises. This umbrella review aimed to synthesize evidence on determinants of protective behaviours during pandemics and provide recommendations for policy and practice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Following PRISMA 2020 guidelines, we conducted an umbrella review on peer reviewed literature reviews and meta-analyses published between 2020 and 2025. Searches in Epistemonikos, MEDLINE, and Scopus (last update June 2025) targeted reviews on “protective behaviours” and “COVID-19”. Eligibility criteria followed the Population–Concept–Context framework: general population, multifactorial determinants of protective behaviours, and pandemic contexts. Data extraction was performed in a table which included review characteristics, behavioural domains (general compliance, medical interventions, conversation promotion, information handling, hygiene, physical distancing, and other behaviours), and factor valence. Quality appraisal used the Joanna Briggs Institute checklist.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e From 86 records identified, 11 met inclusion criteria, covering COVID-19 and other diseases. (e.g., H1N1, SARS, MERS, Ebola). Quality scores averaged 8.8/10. Protective behaviours were influenced by three categories of factors: (1) sociodemographic (age, gender, education, socio-economic status), (2) personal (perceptions, beliefs, trust in authorities and science, political orientation), and social and environmental factors (access to protective materials, social norms, community support, health education and communication, policies). Enabling factors included trust in credible sources, perceived effectiveness of measures, and multimodal communication. Barriers comprised misinformation, conspiracy beliefs, and resource inaccessibility. Some factors (e.g., age, gender, education) showed inconsistent effects across behaviours. Findings underscore the need for culturally sensitive messaging, transparent communication, and targeted interventions for vulnerable populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e This umbrella review synthesizes multi-level determinants enabling or hindering protective behaviours during pandemics. It provides evidence-based guidance for policymakers to design targeted interventions through trusted communication channels, culturally appropriate messaging, and addressing the specific needs of different demographic groups. The findings underscore the importance of consistent, positive messaging for pandemic preparedness and response.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegistration:\u003c/strong\u003e PROSPERO registration number: CRD42023467236.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e Brussels-Capital Region – Innoviris.\u003c/p\u003e","manuscriptTitle":"Key factors for promoting protective behaviours in future pandemics: An umbrella review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-07 11:13:47","doi":"10.21203/rs.3.rs-8405099/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-14T20:31:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-20T06:51:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-19T04:38:59+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-16T15:10:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214879434754270059980275475927784794461","date":"2026-01-05T15:02:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"317259163517130617639704239347093097811","date":"2026-01-05T09:11:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"204995188703321917332270898129291589528","date":"2026-01-03T15:15:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-03T14:04:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-24T02:00:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-24T01:59:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Public Health","date":"2025-12-19T13:01:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aoph","sideBox":"Learn more about [Archives of Public Health](http://archpublichealth.biomedcentral.com/)","snPcode":"13690","submissionUrl":"https://submission.nature.com/new-submission/13690/3","title":"Archives of Public Health","twitterHandle":"@Archpubhealth","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ed6b5372-2336-44ba-9549-32c9321fd507","owner":[],"postedDate":"January 7th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-02T09:24:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-07 11:13:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8405099","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8405099","identity":"rs-8405099","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}