Keywords
COVID-19, coronavirus, social distancing, physical distancing, pandemic
This article is included in the Coronavirus (COVID-19) collection.
COVID-19, coronavirus, social distancing, physical distancing, pandemic
This update version responds to both reviewer comments and some necessary but minor deviations from the method set out in version 1 of this paper. These deviations will be noted in our results paper too. The changes are as follows:
* There is now reference to other evidence synthesis work in relation to social distancing and it is noted that these studies focus on the effectiveness of social distancing measures whereas our scoping review focuses on potential behavioural determinants of adherence to social distancing measures.
* We have added the "RQ" abbreviation where the research questions are first presented.
* We clarified what we mean by the term "behavioural determinant" and clarified that as an independent variable it could be observed or manipulated.
* Though data extraction has not taken place yet, it is clear that we do not have the resources to independently extract the data in duplicate. Therefore, in a deviation from the first version, we are now planning to have the data extracted by one reviewer and checked by another.
* There was a contradiction in the first version of the protocol where in the eligbility section it was simultaneously stated that only reports of primary quantitative data would be included, and that reports of plans for studies that would collect primary quantitative data would be included too. This was a mistake - we did not intend to include, and have not included, study plans in the scoping review and this has been corrected in the new version of this protocol.
* We fixed a typo that one of the reviewers kindly pointed out.
See the authors' detailed response to the review by Emma Norris
See the authors' detailed response to the review by Luiza Siqueira do Prado and Alexandra L. Dima
Coronavirus disease 2019 (COVID-19) has had a devastating effect globally since it was first identified in China in December 2019 (Johns Hopkins University, 2020). While several vaccines against SARS-COV-2, the virus which causes COVID-19, are in development, there are none currently available (WHO, 2020). The lack of a vaccine means that behavioural strategies for reducing the transmission of COVID-19 are vital to the global pandemic response (Michie et al., 2020). Some refer to these strategies collectively as a “behavioural vaccine” (Speight et al., 2020).
Societal and community-level strategies for controlling the pandemic including various levels of lockdown and quarantine focus on preventing physical contact between people through public health recommendations, environmental restructuring or legal mandates (Perkins & Espana, 2020). These and other activities that prevent or reduce the frequency and closeness of contact between people as a means of interrupting disease transmission are often collectively referred to as social distancing measures (Kinlaw & Levine, 2007). Individual-level preventative strategies include effective handwashing, properly disinfecting surfaces, coughing and sneezing into a tissue, wearing protective masks, avoiding touching one’s face and keeping a physical distance from others – which is also often referred to as social distancing, though many now refer to this behaviour as physical distancing (West et al., 2020).
While understanding and developing interventions for handwashing, mask-wearing and cough and sneeze etiquette have been the focus of research in psychology previously and in relation to other infectious diseases, less is known about how to effectively encourage behaviours related to social distancing and research in the context of COVID-19 is obviously just emerging (Berry & Fournier, 2014; Jefferson et al., 2007; Lunn et al., 2020; Luong Thanh et al., 2016). Adherence to measures which increase social distance is vital to the success of exit strategies of countries that underwent lockdown and efforts to end the COVID-19 pandemic (Gilbert et al., 2020). Social distancing measures have been shown to reduce the spread of COVID-19 (Courtemanche et al., 2020). Recent evidence syntheses have focused on the efficacy of social distancing measures (Chu et al., 2020; Mahtani et al., 2020; Regmi & Lwin, 2020). One found observational support for keeping a distance of at least 1m, with the chances of COVID-19 transmission decreasing with distance (Chu et al., 2020). Another found support from systematic reviews for self-isolation of ill and exposed individuals, and strategies for reducing people’s social contacts and mobility (Mahtani et al., 2020). Our scoping review will focus on the determinants that potentially increase adherence to social distancing measures, which may inform the development of behavioural interventions to increase adherence to these measures, and thereby increase their effectiveness. Understanding how people successfully adhere to these measures will also be vital to the control of future pandemics.
Behavioural interventions aimed at ensuring high levels of adherence to social distancing guidelines (and other preventative behaviours) have been described as “urgently needed” (Glasziou et al., 2020). However, as of April 2020, only a handful of studies had been registered to test behavioural interventions for preventing COVID-19 transmission – and none focused on increasing adherence to social distancing measures (Hoffmann & Glasziou, 2020). It is crucial that behavioural interventions that can reduce the transmission of COVID-19 are rapidly developed, tested, optimised and implemented in a systematic and evidence-based manner.
A vital step in developing behavioural interventions, regardless of the development framework being employed, is collating the relevant evidence regarding the potential determinants of the behaviour that needs to be changed (O’Cathain et al., 2019a). It is therefore crucial to facilitate the development and testing of such interventions by mapping and evaluating the research on the behavioural determinants of adherence to social distancing measures. The Theoretical Domains Framework is a useful tool for mapping the determinants of behaviours and linking them to specific intervention functions (Michie et al., 2005). It summarises 128 constructs derived from 33 theories of health behaviour into 14 domains. Thus, it provides a method for collating and summarising research on determinants of health behaviours such as adherence to social distancing measures.
Emerging areas of research are often described using scoping review methods as they allow for a broader focus than systematic reviews and present results in descriptive formats that highlight what kinds of evidence exist, where there are evidence gaps, and the quality of the existing evidence (Nyanchoka et al., 2019). Scoping reviews are also specifically indicated when there is a need to clarify the key constructs and operational definitions employed in an area of research, to examine the ways in which research in an emerging area is being conducted and to identify the factors associated with a specific concept (Munn et al., 2018).
The COVID-19 pandemic has caused an exponential increase in research on ways of tackling this crisis and concerns have been raised about the level of research waste that this has produced (Glasziou et al., 2020). Given that there are also concerns about the readiness of psychology as a discipline to contribute to policymaking in emergencies (IJzerman et al., 2020), it is imperative that we consider this growth in research carefully and evaluate the quality of its products – particularly in new areas such as social distancing in research on COVID-19. This scoping review will focus on answering key questions about the state of the evidence on the behavioural determinants of adherence to social distancing measures in research on COVID-19.
This scoping review will be carried out in accordance with guidance from the Joanna Briggs Institute, which builds on previous guidance on best practice in scoping review methodology (Arksey & O’Malley, 2005; Levac et al., 2010; Peters et al., 2019) and reported in accordance with PRISMA-ScR guidance (Tricco et al., 2018). This protocol is structured according to the steps suggested by Arksey & O’Malley (2005). Any deviations from this protocol will be tracked on the review’s Open Science Framework project; the protocol is pre-registered at https://doi.org/10.17605/OSF.IO/TMKUX.
We aim to address the following research questions (RQ) relating to social distancing in research on COVID-19:
RQ1. In what ways have social distancing measures been defined and how has adherence to these measures been operationalised in research on their behavioural determinants conducted in research on COVID-19?
RQ2. What behavioural determinants of adherence to social distancing measures have been studied in research on COVID-19?
RQ3. How do the behavioural determinants of adherence to social distancing measures that have been studied in research on COVID-19 map onto the Theoretical Domains Framework (TDF; Cane et al., 2012)?
RQ4. What is the quality of the evidence from the included studies in this scoping review?
RQ5. What study designs have been used to study the behavioural determinants of adherence to social distancing measures in research on COVID-19?
RQ6. Where has this research taken place?
RQ7. What gaps exist in the literature that need to be addressed in future research on social distancing measures?
Eligibility criteria. Studies must focus on human participants, but no further exclusions on the basis of participant characteristics will be made. Included studies must measure adherence to social distancing measures (i.e. quarantine, lockdown, and physical distancing) and include potential behavioural determinants of adherence to these measures as independent variables (i.e. as either an observed or manipulated variable). By behavioural determinants, we mean any intrapersonal, interpersonal, community, societal or cultural influences on behaviour as commonly represented by ecological models of health (Golden & Earp, 2012). Included studies must have collected primary data using quantitative designs. The included studies must have specifically been conducted in relation to COVID-19 (see Table 1). There will be no restriction on languages. We will use Google Translate to aid in the screening and data extraction of sources that are not reported in English as there is evidence that this is an effective approach (Jackson et al., 2019). A definitions and elaboration document has been developed based on these criteria to aid screening (see Extended data (Noone et al., 2020)).
Information sources. We will identify potentially relevant published literature by searching Medline, PsycInfo, Embase, and Web of Science Core Collection, as this combination of databases has been recommended for adequate and efficient search coverage (Bramer et al., 2017). We will also identify potentially relevant pre-prints by searching PsyArXiv, medRxiv, SocArxiv and Preprints.org. We will search ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform to identify any potentially relevant trials. Grey literature will be searched for using Google Scholar, according to the guidance from Haddaway & colleagues (2015), which suggests using the title-only search option and screening the first 1000 records.
Search strategy. The Medline search strategy for the review was developed with assistance from a research support librarian and includes terms related to COVID-19 and social distancing measures. The searches will be restricted to 2020 to ensure that only sources relevant to the COVID-19 pandemic are identified. The Peer Review of Electronic Search Strategies checklist (McGowan et al., 2016) was applied to this strategy by an independent information specialist. Once the suggested adjustments were applied, the search strategy was translated to the other databases using the Polyglot Search Translator (Clark et al., 2020). Separate search strategies were developed for each pre-print server and Google Scholar. We will use the medrxivr app to search medRxiv (McGuinness, 2020). For each of the other sources, we will use the native search interface. The full search strategy is documented in the Extended data (Noone et al., 2020).
Reference management. Search results from Medline, PsycInfo, Embase, and Web of Science will be exported to .ris files and then imported to Zotero. Search results from both trial registries, each pre-print server and Google Scholar will be imported to Zotero using the Zotero Connector. Specific folders for each literature source will be created in the Zotero Group library for this project, which is available at https://bit.ly/BDSDA_Library. All search results will be exported to a single .ris file so that deduplication can be conducted using the DeDuplicator tool within the Systematic Review Accelerator suite (Rathbone et al., 2015). The deduplicated library will then be exported for screening.
Screening will be conducted within Covidence (Covidence, 2019). The screening process will be piloted initially – 25 titles and abstracts will be selected at random and the entire research team will screen these using the predefined eligibility criteria and definitions/elaboration document. If any discrepancies are identified, these will be discussed within the team and modifications will be made to the eligibility criteria and the definitions and elaboration document. Screening will then begin once an agreement rate of 75% or greater is reached based on the screening of a further 25 titles and abstracts. The screening process will involve two reviewers screening each title and abstract, with conflicts resolved by consensus or a third reviewer. Full texts will also be screened in duplicate with conflicts resolved by consensus or a third reviewer.
The research team will design a data charting tool, as set out by the PRISMA-ScR Checklist (Tricco et al., 2018), to which the following information will be extracted by two members of the research team:
Author(s)
Year of publication
Country of origin (i.e. where the study was conducted)
Funding
Aims/purpose
Time of data collection
Context (e.g., description of local COVID-19 impact at time of data collection, description of relevant public health policies in place; if available in the study report)
Population
Sample size
Study design
Pre-registration (if any)
Specific theory (if any)
Intervention type, comparator and details of these (e.g., duration of the intervention; if applicable).
Outcomes and details of these (e.g., how measured)
Key findings that relate to the scoping review question/s.
The data charting tool will be independently piloted by two reviewers who will conduct full data extraction on five sources chosen to cover the diversity of different study types included.
Any discrepancies that arise will be discussed by the full team before proceeding with the data extraction process. As per the iterative nature of scoping reviews, it is expected that this tool may be adjusted during this process to ensure accurate representation of all data sources. Data from each included source will be extracted by one reviewer and checked by another. All data extracted will be compiled into a summary spreadsheet.
Quality assessment. We will use the following quality appraisal tools for studies included in the review: the Cochrane Risk of Bias Tool (Sterne et al., 2019) for randomised controlled trials, the Cochrane ROBINS-I Tool (Sterne et al., 2016) for quasi-experimental studies, and the Joanna Briggs Institute Critical Appraisal Checklist (Moola et al., 2020) for analytical cross-sectional research.
To visually represent study selection and reasons for exclusion at full text review, a PRISMA flow diagram will be presented. The diversity of definitions of social distancing measures and the operationalisations of adherence to these measures will be recorded in a table (RQ1). A table of study characteristics will summarise the aim, design and results (if available) of each study (RQ2). A framework analysis using the TDF (Cane et al., 2012) will be used to summarise and report the types of evidence available regarding the behavioural determinants of adherence to social distancing measures that have been studied in research on COVID-19. Two reviewers will independently judge which domains of the TDF are most applicable to each behavioural determinant of adherence to social distancing measures reported in the included studies. Additional headings will be employed should the framework not be sufficient in representing the data (RQ3). While there is little consensus on the exact definition of what constitutes an evidence gap map (Miake-Lye et al., 2016), for the purpose of this review, we aim to produce a visual depiction of current research and any gaps in the literature, alongside an assessment of study quality (RQ4). This will be presented using a bubble plot, whereby the colour of and size of each bubble will represent research type and research quality. A heat map will present counts of the different research designs used in the included studies (RQ5). A geographical map will be produced to visualise the volume of included studies carried out in different countries (RQ6). Knowledge gaps will be represented through the development of an evidence gap map (RQ7). We will also produce a timeline of the studies based on the reported time of data collection. The visualisations described above will be produced using EviAtlas, an open science tool for mapping and graphing study characteristics (Haddaway et al., 2019). Clusters and heat maps of frequently occurring terms in the included studies will be visualised using VOSviewer (van Eck & Waltman, 2010). Strengths and limitations to the review will be discussed, alongside future recommendations for research.
We consider the primary stakeholders in this study to be the researchers developing work in this area, in particular those who develop behavioural interventions. We will invite open consultation and seek comments on this article. We will disseminate this invitation through relevant professional societies (e.g. the International Society for Behavioural Medicine, the European Health Psychology Society, the Asian Congress of Health Psychology), social media networks and mailing lists. We will summarise all feedback received and record any changes in the study that are made as a result.
Developing interventions that effectively increase adherence to social distancing measures is vital to the success of efforts to tackle the COVID-19 pandemic and will contribute to preparedness for future pandemics. This scoping review will systematically collate and describe the available evidence regarding the behavioural determinants of adherence to social distancing measures. It will also highlight gaps in this area of research. This may reduce research waste by making it easier to avoid the unnecessary duplication of work and instead contribute to cumulative research on this topic.
Ideally, the results of this study will facilitate the systematic development of behavioural interventions to increase adherence to social distancing measures based on behavioural evidence and theory using established approaches such as Intervention Mapping (Bartholomew Eldredge, 2016) and the Behaviour Change Wheel (O’Cathain et al., 2019b; Michie et al., 2014). These interventions should then be tested within methodological frameworks that can rapidly and efficiently identify the optimal set of components that the interventions should contain. The Multiphase Optimisation Strategy (Collins et al., 2011) and the Agile Science process (Hekler et al., 2016) are two such frameworks that make intelligent use of innovative research designs such as fractional factorial experiments, microrandomised trials and sequential multiple assignment randomised trials.
To facilitate this work, this review will produce an accessible summary of how social distancing measures are defined and how adherence to these measures has been operationalised in research conducted on COVID-19. It will also identify the behavioural determinants that have been studied in relation to adherence to social distancing measures and map them to the TDF. Finally, it will analyse and visualise key characteristics of the included studies.
Open Science Framework: Investigating and evaluating evidence of the behavioural determinants of adherence to social distancing measures – A scoping review of COVID-19 research. https://doi.org/10.17605/OSF.IO/TMKUX (Noone et al., 2020).
This project contains the following extended data:
Cochrane ROB Tool.pdf (Risk of bias tool to be used).
Codebook.docx
Data Extraction Form.xlsx (Blank data extraction form).
Eligibility Criteria.docx
EMBASE.docx (Search strategy for EMBASE).
JBI Critical Appraisal.pdf (JBI Critical Appraisal check
MEDLINE.docx (Search strategy for MEDLINE).
Pre-print, Grey Lit and Registry Search Strategies.docx (Search strategies for pre-prints, grey literature and registries).
PRESS 2015 checklist for search strategies.docx
PSYCINFO.docx (Search strategy for PSYCINFO).
ROBINS-I Tool.pdf (Blank ROBINS-I assessment tool).
Web of Science.docx (Search strategy for Web of Science).
Extended data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).
Is the rationale for, and objectives of, the study clearly described?
Yes
Is the study design appropriate for the research question?
Yes
Are sufficient details of the methods provided to allow replication by others?
Yes
Are the datasets clearly presented in a useable and accessible format?
Yes
References
1. Williams S, Armitage C, Tampe T, Dienes K: Public perceptions and experiences of social distancing and social isolation during the COVID-19 pandemic: a UK-based focus group study. BMJ Open. 2020; 10 (7). Publisher Full TextCompeting Interests: We know the group and appreciate their work. We participate in several networking initiatives together. We do not feel this affected our ability to review impartially.
Reviewer Expertise: Behaviour change, health psychology, public health, health services research.
Is the rationale for, and objectives of, the study clearly described?
Yes
Is the study design appropriate for the research question?
Yes
Are sufficient details of the methods provided to allow replication by others?
Yes
Are the datasets clearly presented in a useable and accessible format?
Yes
References
1. Chu D, Akl E, Duda S, Solo K, et al.: Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis. The Lancet. 2020; 395 (10242): 1973-1987 Publisher Full TextCompeting Interests: Non-financial competing interests: I am Co-Chair of the European Health Psychology Society's Open Science SIG with Elaine Toomey.
Reviewer Expertise: Behaviour change, health psychology, evidence synthesis, open science.
Alongside their report, reviewers assign a status to the article:
Invited Reviewers | ||
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Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list:
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