Investigating and evaluating evidence of the behavioural determinants of adherence to social distancing measures – A protocol for a scoping review of COVID-19 research [version 1; peer review: 2 approved]

Background: The WHO has declared the outbreak of coronavirus disease 2019 (COVID-19) as a pandemic. With no vaccine currently available, using behavioural measures to reduce the spread of the virus within the population is an important tool in mitigating the effects of this pandemic. As such, social distancing measures are being implemented globally and have proven an effective tool in slowing the large-scale spread of the virus. Aim: 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. Methods: A scoping review will be conducted in accordance with guidelines for best practice. Literature searches will be conducted using online databases and grey literature sources. Databases will include Medline, Web of Science, Embase and PsycInfo, alongside relevant pre-print servers. Grey literature will be searched on Google Scholar. Screening, data extraction and quality appraisal will be conducted independently by two members of the research team, with any discrepancies resolved by consensus discussion and an additional team member if needed. Quality appraisal will be conducted using the Cochrane’s ROBINS-I tool, the Cochrane Risk of Bias tool, and the JBI Critical Appraisal Checklist where appropriate. Results will be analysed by mapping findings onto the Theoretical Domains Framework and visualising characteristics of the included studies using EviAtlas. This Open Peer Review


Introduction
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). 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.

Protocol
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 methodol-  Studies must focus on human participants, but no further exclusions on the basis of participant characteristics will be made. Included studies must be 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. Included studies must have collected or plan to collect 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)).

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.

Stage 3: Study selection
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.

Stage 4: Charting the data
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: • 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 in duplicate. 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: , 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.
Step 6: Consultation with stakeholders 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.

Dissemination
To facilitate rapid dissemination, the results of this review will be reported in a pre-print which will be uploaded to PsyArXiv. This report will also be submitted to a peer-reviewed journal.

Discussion
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. 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.

Data Availability
Underlying data No underlying data are associated with this article. The focus of this review is on quantitative research, but in this emerging crisis qualitative inquiry is equally valuable for identifying determinants (e.g. Williams et al. 1 ). It would be useful to state why qualitative studies are excluded, or perhaps include them as well? If the authors prefer to focus only on quantitative information, mentioning this in the abstract will be useful for readers.

3.
The term used for determinants is "behavioral determinants". Are there 'non-behavioral determinants' in this context which would be excluded? The term "behavioral determinants" is used in public health to denote the impact of behaviour on health outcomes (as opposed to social, environmental, etc.), but in the context of studying determinants of a behaviour (distancing) can we talk about non-behavioral or is it just intended as 'all determinants of this behaviour'? Would for example socio-demographic characteristics be excluded if they appear as IVs in a regression model with distancing as DV? Perhaps other distinctions to consider in the review would be between modifiable-non modifiable, and individualenvironmental (and in the environment there could be different actors and behaviours facilitating social distancing). These would inform intervention by recommending modifiable determinants and identifying which actors it could target.

4.
Following on the previous point, presence of interactions between determinants and background characteristics could be useful to code to guide tailoring of interventions.

5.
In this topic, grey literature is likely to be very important. The Appendix with grey literature searches includes only 'distancing' as search term, while for the other sources it has already been expanded to other keywords (isolation, quarantine, etc.). It would be useful to use these other terms here as well. Moreover, from own experience with Google Scholar, title only searches might miss important contributions. It would perhaps be useful to compare with 'allintext' for relevance of entries. 6.
The abbreviations RQ1, RQ2, etc., in "Stage 5: Collating, summarising, and reporting of results" refer to the research questions presented in Stage 1. Please add abbreviation where it first appears in the text.

Yes
Are the datasets clearly presented in a useable and accessible format? Yes