Adherence to mask wearing and social distancing and use of lateral flow tests during the COVID19 pandemic in England and Wales based on the Virus Watch community cohort study

Adherence to mask wearing and social distancing and use of lateral flow tests during the COVID19 pandemic in England and Wales based on the Virus Watch community cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Adherence to mask wearing and social distancing and use of lateral flow tests during the COVID19 pandemic in England and Wales based on the Virus Watch community cohort study Vivi Antonopoulou, Madeline Ong, Carly Meyer, Sarah Beale, Fabiana Lorencatto, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6369060/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Jan, 2026 Read the published version in Discover Public Health → Version 1 posted 12 You are reading this latest preprint version Abstract Background Personal protective behaviours (PPBs) played a crucial role in limiting infection spread during the COVID-19 pandemic, yet adherence varied across communities. Understanding the factors influencing adherence is important, as PPBs will remain critical in future pandemics. Using behavioural science, we investigated the influences on adherence to PPBs, focusing on face mask wearing, social distancing, and lateral flow testing (LFT). Methods Two online surveys were conducted in July and August 2021 in England and Wales ( N = 20,488 (survey 1) and N = 26,613 (survey 2)). Survey questions were informed by the Capability, Opportunity, Motivation model of Behaviour (COM-B). Multivariate models examined associations between behavioural influences and adherence to PPBs. Results Most respondents reported wearing a face mask in public indoor places (88.5%) and maintaining a 1+ metre distance (86.8%) all or most of the time. After two doses of COVID-19 vaccine, adherence declined with 48.3% reporting meeting friends or family and 38.3% visiting indoor places more frequently. Motivation, Opportunity and Capability factors were significantly associated with increased odds of wearing a face mask and social distancing (p < 0.05). Among those using LFTs (68% of the sample), 50.4% engaged in routine testing, while 55.3% of non-users cited a perceived lack of necessity for testing. Routine testing was significantly associated with accurate interpretation of test results. Conclusions Despite reduced restrictions and high vaccination rates, overall adherence to PPBs remained high. Behavioural influences played a significant role in PPB use. These findings can inform tailored public health interventions and support future community-level emergency preparedness. personal protective behaviors public health interventions pandemic rapid lateral flow tests lateral flow device (LFD) behavioral science Background Throughout the COVID-19 pandemic, governments worldwide implemented various public health and social measures to control the spread of the virus, especially before the development of vaccines [ 1 , 2 ]. These measures included travel bans, lockdowns (school, non-essential shop, and workplace closures), restrictions on social interactions, isolation and quarantine protocols, social distancing guidelines, mandatory mask-wearing, and cancellation of public events. In countries with testing capabilities, population-wide testing and contact tracing were also implemented [ 3 ]. However, it has been widely recognised that the introduction of such measures alone is not enough to limit disease transmission. Behaviours such as compliance with public health guidance, adherence to restrictions, and the adoption of personal protective measures (PPBs) (e.g., hand washing and use of face masks) are crucial factors for the successful prevention of infectious diseases across communities [ 4 – 9 ]. Even after the development of effective vaccines [ 10 – 13 ], with new strains of the virus, waning immunity, and a proportion of the population remaining unvaccinated for COVID-19, PPBs continued to be valuable in managing the spread of the disease [ 10 , 13 , 14 ]. However, as vaccination was promoted as the most effective public health intervention to control the virus and return to normalcy, there were concerns that adherence to preventive behaviours might decline after vaccination due to a false sense of reduced infection risk [ 15 , 16 ]. Previous studies on vaccine rollouts for other diseases (e.g. Lyme disease, influenza) indicated reduced adherence [ 17 , 18 ], and early evidence from COVID-19 antibody testing studies also suggested lower intention to engage in protective behaviours among individuals with antibodies [ 19 – 21 ]. Studies conducted during the early stages of the COVID-19 pandemic yielded mixed results with some studies suggesting a decrease in PPB use (e.g. [ 22 – 26 ], while others indicated a consistent use of PPBs regardless of vaccination status [ 15 , 27 ]. Mask wearing and social distancing are important PPBs to mitigate COVID-19 infection, particularly as mask wearing and social distancing are the most visible and hence socially impactful [ 28 – 30 ]. A number of international studies examining adoption of mask wearing and social distancing during the COVID-19 pandemic indicated that PPB use can vary depending on the specific behaviour, country, and time ([ 31 , 32 ]. Evidence regarding sociodemographic factors influencing mask wearing and social distancing including age [ 33 – 37 ], gender [ 34 , 38 – 42 ], level of education [ 43 ], employment and income [ 44 ], ethnicity [ 34 , 35 , 39 ], and perceived susceptibility to the disease [ 43 ] was mixed and varied across contexts. In a similar vein, an evidence review of interventions to increase PPBs for respiratory viruses, including COVID-19, found unclear results for interventions targeting face mask use and highlighted the lack of evidence about intervention effectiveness for the majority of PPBs [ 45 ]. Self-testing using a rapid Lateral Flow Test (LFTs) (also known as rapid diagnostic test (RDT)) was also a preventative measure that contributed to the management of the COVID-19 virus and was a cost-effective alternative to Polymerase Chain Reaction (PCR) testing [ 46 , 47 ]. LFTs were initially introduced as a form of asymptomatic screening and not recommended for use when symptomatic, and while this guidance later changed, LFTs were still primarily about preventing the spread of the virus by rapidly identifying those individuals who were carrying high levels of the virus so they may self-isolate, rather than for monitoring one’s own health [ 48 ]. The evidence-base for the uptake of LFT is still limited, but early evidence pointed to low uptake among the public in UK-based studies, although some improvement was found over time [ 49 – 51 ]. Moreover, the coexistence of both PCR and LFT options for the general public led to considerable confusion regarding the appropriate test for different situations [ 50 , 51 ]. As we are now transitioning out of the acute phase of the COVID-19 pandemic, we need to better understand the evidence from the COVID-19 pandemic to plan for future epidemics/pandemics, particularly as adoption of personal protective measures (PPBs) to protect oneself and others in our communities will undoubtedly be a critical part of any public health response. Using behavioural science theories and frameworks can be very helpful for guiding investigation of the factors influencing the enactment (or maintenance) of PPBs and for designing effective public health interventions [ 52 ]. An example of an integrated model of behaviour change which is widely used to conceptualise possible influences on behaviour is the COM-B model [ 53 ]. The COM-B model states that to enact a behaviour one needs to have the Capability (psychological or physical), Opportunity (social or physical) and Motivation (the reflective and automatic processes that direct behaviour) to perform the Behaviour [ 54 ]. One major benefit of the COM-B is that it is mapped to the Behaviour Change Wheel, enabling systematic progression from identifying influences to generating suggestions for interventions [ 53 ]. Therefore, we sought to identify and classify behavioural influences on mask-wearing, social distancing and lateral flow testing during the COVID-19 pandemic with a view to generate recommendations that can inform public health interventions for future epidemics and pandemics. Aims of the current study In this context, the present study aimed to assess a) changes to use of wearing of face masks and social distancing, following vaccination compared to baseline, and b) the factors associated with use of face masks and social distancing, and the uptake of lateral flow testing, using a behavioural science approach. Specifically, this study addressed the following research questions (RQs): RQ1a. To what extent did participants adhere to wearing face masks and observing social distancing rules? RQ1b. Was there a change in reported use of mask wearing and/or social distancing post-vaccination? RQ1c. Which influences (capability, opportunity, and motivational factors) are associated with wearing of face masks post-vaccination? RQ 1d. Which influences (capability, opportunity, and motivational factors) are associated with social distancing post-vaccination? RQ2a. To what extent did participants use LFT and what were the reasons for using LFT? RQ2b. Were there any differences in understanding the test result between those who routinely test and those who test opportunistically? RQ2c. Which influences (capability, opportunity, and motivational factors) are associated with lack of (LF) testing? Methods Design This is a cross-sectional study nested within the prospective Virus Watch community cohort study which comprised over 50,000 participants from households across England and Wales. The Virus Watch study was run by University College London (UCL) in conjunction with NHS and was aiming to investigate transmission of COVID-19 in relation to population movement and behaviours and to provide evidence on which public health approaches are most likely to be effective in reducing transmission of the virus [ 55 ]. Virus Watch included weekly online surveys regarding infection symptoms, COVID-19 testing, and vaccinations, as well as monthly surveys on psychosocial and clinical topics beyond the scope of the weekly surveys and tailored to the phase of the pandemic. Data for this study were collected in two one-off surveys with households sampled from the Royal Mail post office address file and through social media advertising. Data on face mask wearing and social distancing were collected from a survey conducted in July 2021 (survey 1). Data on lateral flow testing were collected from a survey carried out in August 2021 (survey 2). In addition, survey 2 included a screening question about use of LFT and directed participants in two branches based on their responses. If they had used LFT, they were asked questions about routine and non-routine use and their understanding of the test result. If they had never taken a LFT, they were asked about the reasons for never having self-tested using a LFT along with COM-B questions. Data for both surveys were collected using REDCap electronic data capture tools hosted on University College London (UCL) Data Safe Haven. Sample For representativeness, the sample was stratified by age, gender, ethnicity and geographical regions across England and Wales (for more information on the Virus Watch recruitment strategy see [ 56 ]). Entire households were recruited, and the lead householder was asked to complete two online surveys. Mask wearing and social distancing (Survey 1): Participants were included if they had received one or two doses of a COVID-19 vaccine at the point of data collection. By the time of the data collection for this study, the vaccine had been offered to all individuals in the first nine priority groups in the UK which included residents of care homes for older adults and their carers, those 50 years old and older, and clinically extremely vulnerable individuals. The UK government anticipated that by the end of July 2021, all 18–49 year-old people from the general population would have been offered a vaccine. At the time of the survey, 69,932,565 doses had been administered, with 38,890,375 individuals having received at least one dose [ 57 ]. LFT (Survey 2): We included responses from people who had and had not done LFT previously. At the time of data collection, lateral flow devices were available to everyone in England for symptomatic or for regular asymptomatic testing at no cost to the individual [ 58 ]. Materials and Measures Survey 1 RQ1. Mask wearing and social distancing measures a) Frequency of mask wearing and social distancing measures b) Changes in frequency of mask wearing and social distancing Frequency of mask wearing and social distancing was measured with the statements ‘ I wear a face covering in public, indoor places ’ and ‘ I keep a 1 + metre distance from people I don’t live with ’. Response options were measured on a 5-point Likert Scale and ranged from ‘Never’ to ‘All of the time’. Changes in frequency of mask wearing and social distancing after receiving the vaccine were measured with statements such as ‘ Have you changed any of the following as a result of having had one/two doses of the vaccine - Visiting public indoor places (e.g., restaurant, café, cinema) with people you don’t live with ’. Responses were measured on a 3-point Likert scale (‘More frequently’, ‘No change’, ‘Less frequently’). (See Table S1 in the Supplementary Material file) c) Influences on Mask wearing and social distancing measures - COM-B factors Influences on mask wearing and social distancing behaviours were measured with agreement to statements structured around the COM-B domains, for example “ The elderly and vulnerable are protected from Covid-19 now that vaccination is available ” (reflective motivation statement). Responses were measured on a 5-point Likert scale from ‘Strongly disagree’ to ‘Strongly agree’. (See Table S2) Survey 2 RQ2. LFT measures a) Frequency of testing Participants were initially asked two screening questions to assess use of LFT. The first screening question assessed whether they had ever done a test (‘Have you ever done a lateral flow test? with response options ‘Yes/No/Don’t know’); the second question asked about frequency of use (‘Do you routinely have lateral flow tests? Response options included Yes/No/Don’t know’).’ Based on reported frequency of LFT (regular, non-regular testing, never used), participants were directed to either answer questions related to the reported use and understanding of a test result, or to indicate the reasons for never having done a test. b) Reasons for testing and understanding of a test result Non-regular testing . Of those who reported having done LFT, those who reported non-regular testing were asked to indicate on which of the following occasions they did a test (option of multiple response): a) Before visiting friends or relatives, b) To get into a venue, c) When I’m feeling poorly, d) Because I have symptoms that might be Covid-19, e) Because I’m required to for work/education, f) So that I can travel, g) Because someone told me to, h) Because I’ve been in contact with someone I think might have Covid-19, i) Other [free text] This group of participants was also asked questions related to their understanding of the LFT result. Regular testing . Participants who reported regular testing were only asked questions related to their understanding of the LFT result. Understanding of a positive/negative LFT result (for participants indicating regular as well as for participants indicating non-regular testing) was measured with agreement to statements such as ‘If you get a positive result from a lateral flow test, it means: I’m infected with COVID-19 ’ on a 5-point Likert scale (from ‘Definitely not’ to ‘Definitely’). (See Table S3) c) Influences on testing - COM-B factors Participants who reported never having done a LFT test were asked to indicate their level of agreement with statements citing possible reasons for never having done an LFT. These statements were structured around the COM-B model including capability, opportunity, and motivational factors, for example, ‘ I don’t want to have to report my test result’ (reflective motivation). The response options were measured on a 5-point Likert scale ranging from ‘Strongly disagree’ to ‘Strongly agree’. (See Table S4) Statistical Analysis For frequency of use, frequency responses for wearing face masks, social distancing, and lateral flow testing were analysed and reported as percentages. Logistic regression models were used to identify those COM-B factors associated with mask wearing and social distancing (maintaining a 1 + metre distance) among those fully vaccinated controlling for age, ethnic group, income, gender, and health status (assessed by having received an NHS risk letter). Subscale factors (capability, opportunity, and motivational factors) were used in the model. Cronbach’s alpha for each subscale was calculated to assess the internal consistency of the sub-scales (see Table S5). Univariate associations were examined to screen for variables to include in the model (p < 0.1). Multicollinearity between predictor variables were checked using the Variance Inflation Factor (VIF) (see Table S6). Frequencies of reported reasons for testing and interpretations of LFT results were analysed and reported as percentages. The reasons for never having done LFT were also analysed and reported as percentages and mean scores. A chi-square test was performed to measure the differences in interpretations of LFT results among those who do and do not routinely test. Results Participant Characteristics The sociodemographic characteristics of the respondents for both surveys are presented in Table 1 . In survey 1 (July 2021), a total of 20,488 responses on social distancing and wearing a face mask were included in the final sample.1 In survey 2 (August 2021), a total of 26,613 responses on LFT were included in the final sample. In both surveys, 56% of participants were female and 60 years old and older. The majority of participants belonged to White ethnic groups. Table 1 Baseline participant characteristics for survey 1 (N = 20,488) and survey 2 (N = 26,613) Participants (Survey 1: mask wearing and social distancing) Participants (Survey 2: Lateral Flow Testing*) Overall After one dose After two doses Overall Used an LFT Never used LFT Age in years % (n) % (n) % (n) % (n) % (n) % (n) <30 2.5 (519) 59.3 (118) 2.0 (401) 3.6 (952) 4.4 (802) 1.8 (150) 30–39 2.4 (493) 5.0 (10) 2.4 (483) 4.1 (1084) 5.1 (931) 1.8 (153) 40–49 4.1 (848) 11.1 (22) 4.1 (826) 7.2 (1925) 8.9 (1623) 3.5 (302) 50–59 15.3 (3127) 7.0 (14) 15.3 (3113) 16.3 (4372) 18.8 (3432) 11.0 (940) 60+ 75.7 (15501) 17.6 (35) 76.2 (15466) 68.9 (18431) 62.7 (11422) 81.9 (7009) Number of people in the household Mean (SD) 1.9 (0.6) 2.6 (1.1) 1.8 (0.6) 2.0 (0.8) 2.0 (0.9) 2.0 (0.7) Gender at birth % (n) Male 43.2 (8803) 48.5 (96) 43.1 (8707) 43.2 (11500) 40.9 (7393) 48.3 (4103) Female 56.6 (11536) 51.5 (102) 56.6 (11434) 56.5 (15036) 58.9 (10666) 51.5 (4370) Intersex 0.1 (30) 0 (0) 0.1 (30) 0.1 (34) 0.1 (26) 0.1 (8) Prefer not to say 0.1 (16) 0 (0) 0.1 (16) 0.1 (21) 0.1 (10) 0.1 (11) Ethnic Group % (n) White-English/Welsh/Scottish/Northern Irish/British 91.7 (18653) 85.3 (168) 91.8 (18485) 90.0 (23887) 89.9 (16245) 90.2 (7642) Any other white background 5 (1012) 8.6 (17) 4.9 (995) 5.5 (1474) 5.8 (1053) 5.0 (421) Mixed/ multiple ethnic groups 0.8 (167) 1.5 (3) 0.8 (164) 1.0 (252) 1.0 (181) 0.8 (71) Asian/Asian British background 1.7 (348) 4.0 (8) 1.9 (340) 2.4 (625) 2.1 (383) 2.8 (242) Black British/African/Caribbean/Any other Black background 0.4 (72) 0 (0) 0.1 (72) 0.6 (167) 0.7 (115) 0.6 (52) Any other ethnic group 0.3 (66) 0 (0) 0.4 (66) 0.4 (99) 0.4 (70) 0.4 (29) Prefer not to say 0.1 (26) 0.5 (1) 0.1 (25) 0.1 (35) 0.1 (20) 0.2 (15) Received an NHS risk letter % (n) Yes 13.6 (2574) 9.0 (15) 13.6 (2559) 13.0 (3205) 12.9 (2155) 13.4 (1050) No 86.4 (16391) 91.0 (152) 86.4 (16239) 87.0 (21428) 87.1 (14614) 86.6 (6814) Combined Household Income % (n) 0–9,999 5.9 (1117) 9.9 (18) 5.8 (1099) 5.4 (1331) 5.1 (863) 5.9 (468) 10,000–24,999 28.2 (5362) 15.9 (29) 28.3 (5333) 26.5 (6552) 24.9 (4187) 29.8 (2365) 25,000–49,999 37.3 (7076) 33.5 (61) 37.3 (7015) 35.7 (8826) 34.4 (5782) 38.3 (3044) 50,000–74,999 12.7 (2421) 18.7 (34) 12.7 (2387) 14.3 (3537) 15.4 (2590) 11.9 (947) 75,000–99,999 5.0 (942) 8.2 (15) 4.9 (927) 5.9 (1470) 6.7 (1134) 4.2 (336) 100,000-124,999 2.3 (440) 3.3 (6) 2.3 (434) 3.1 (762) 3.6 (601) 2.0 (161) 125,000-149,999 0.6 (122) 4.4 (8) 0.6 (114) 0.9 (234) 1.2 (196) 0.5 (38) 150,000-174,999 0.5 (99) 0.5 (1) 0.5 (98) 0.7 (173) 0.9 (145) 0.4 (28) 175,000-199,999 0.3 (60) 0.5 (1) 0.3 (59) 0.4 (93) 0.5 (78) 0.2 (15) 200,000 or more 0.5 (91) 1.6 (3) 0.5 (88) 0.8 (192) 1.0 (167) 0.3 (25) Prefer not to say 6.7 (1264) 3.3 (6) 6.7 (1258) 6.4 (1582) 6.4 (1068) 6.5 (514) *NB: Lateral Flow Testing (LFT) [insert Table 1 here] Survey 1 RQ1a. Frequency of mask wearing and social distancing Of 20,488 participants who received one or two doses of the COVID-19 vaccine, 99% (20289) completed two doses. The majority of the respondents reported that they would wear a face mask in public indoor places (88.5%) and maintain a 1 + metre distance (86.8%) all or most of the time, as shown in Table 2 . Table 2 Reported levels of use of protective behaviour among participants with two doses of COVID-19 vaccine. Response options I wear a face mask in public indoor places (n = 20,135) % (n) I keep a 1 + metre distance from people I don’t live with (n = 20,057) % (n) Never 1.1 (218) 0.5 (91) Rarely 2.1 (413) 2.0 (400) Sometimes 8.4 (1685) 10.7 (2147) Most of the time 31.7 (6375) 49.2 (9870) All of the time 56.8 (11444) 37.6 (7549) [insert Table 2 here] RQ1b. Changes in reported frequency of mask wearing and social distancing post-vaccination Although the majority of participants reported no change following vaccination for wearing a face mask, social distancing, visiting public indoor and outdoor places and using public transport, there was still a proportion of participants reporting changes in their behaviour. Specifically, 48.3% participants reported meeting with friends or family more frequently, while 38.3% participants reported increasing the frequency of visiting indoor places and 27.8% increasing the frequency of visiting outdoor places. Conversely, 14.5% reported wearing a face mask less frequently and 16.1% reported maintaining social distance less frequently (see Table 3 ). Table 3 Changes in mask wearing and social distancing after two doses of COVID-19 vaccine Less frequently % (n) More frequently % (n) No change % (n) Wearing a face mask in public indoor spaces (n = 20,127) 14.5 (2912) 3.0 (606) 82.5 (16609) Maintaining a 1m + distance from people you don’t live with (n = 20,020) 16.1 (3231) 5.1 (1027) 78.7 (15762) Meeting friends or family you don’t live with, either at your home or their home (n = 20,035) 3.7 (748) 48.3 (9681) 47.9 (9606) Visiting public indoor places (e.g. restaurant, café, cinema) with people you don’t live with (n = 19,784) 5.7 (1123) 38.3 (7584) 56.0 (11077) Visiting public outdoor places (e.g. parks) with people you don’t live with (n = 19568) 3.9 (761) 27.8 (5431) 68.4 (13376) Using public transport (n = 17,990) 5.8 (1037) 14.3 (2566) 80.0 (14387) [insert Table 3 here] Women were more likely than men to wear masks all or most of the time (OR 1.43 [1.28, 1.59], p < 0.001) and keep a 1 + metre distance from others all or most of the time (OR 1.16 [1.05, 1.30], p < 0.01). Being white decreased the odds of keeping a 1 + metre distance from others all or most of the time (OR 0.73 [0.54, 0.98], p < 0.05). Participants older than 40 years were more likely than those younger than 30 years to keep a 1 + metre distance from others all or most of the time, and these odds were higher as age increased (40–49 years: OR 1.68 [1.15, 2.46], p > 0.01; 50–59 years: OR 1.77 [1.28, 2.46], p < 0.001; 60 + years: OR 2.13 [1.56, 2.91], p 50,000GBP compared to < 25,000 were less likely to keep a 1 + metre distance from others all or most of the time (OR 0.73 [0.64, 0.84], p < 0.001). Participants who received an NHS risk letter were more likely to keep a 1 + metre distance from others all or most of the time (OR 1.78 [1.49, 2.12], p < 0.001). RQ 1c. COM-B influences on mask wearing and social distancing post-vaccination Overall, results from the logistic regression models indicated that all COM-B predictor variables significantly contributed to wearing a face mask in public indoor spaces (model 1) and keeping a 1 + metre distance all or most of the time (model 2), as shown in Table 8 . For both models, the Hosmer and Lemeshow goodness of fit test was not significant (p < 0.001) indicating they were correctly specified. Additionally, the Cox and Snell was 0.092 and 0.100 for models 1 and 2, respectively; and the Nagelkerke R squared was 0.179 and 0.186 for models 1 and 2, respectively indicating that approx. 20% of the variance was accounted for in each of the models. Specifically: Mask wearing The estimated adjusted odds ratio for the COM-B domain of automatic motivation showed an increase of 2.20 times for mask wearing for every unit of increase in participants’ reported agreement score (aOR = 2.20, 95% CI 2.02–2.39); for social opportunity an increase of 1.7 times the odds (aOR = 1.70, 95% CI 1.61–1.79); and for psychological capability an increase of 1.3 times the odds (aOR = 1.31, 95% CI 1.23–1.39). In contrast, the estimated odds ratio for reflective motivation showed a decrease in the odds of about 0.6 times (aOR = 0.58, 95% CI 0.53–0.63) for mask wearing for every unit of increase in participants’ reported agreement score. Essentially this findings suggests that people who had higher scores on reflective motivation, indicating they thought they could no longer catch or pass on COVID-19 post-vaccination, were at decreased odds of wearing a face mask. Social distancing The estimated odds ratio for the COM-B domain of automatic motivation for social distancing showed an increase of 2.5 times for every unit of increase in participants’ reported agreement score (aOR = 2.46, 95% CI 2.27–2.67),; for social opportunity an increase of 1.8 times the odds (aOR = 1.77, 95% CI 1.68–1.87); and for psychological capability an increase of 1.3 times the odds (aOR = 1.29, 95% CI 1.22–1.37). In contrast, the estimated odds ratio for reflective motivation showed a decrease in the odds of 0.7 times (aOR = 0.74, 95% CI 0.683, 0.81). A high reflective motivation score for these items would suggest thinking that one can no longer catch or pass on COVID-19 post-vaccination or that the risks of COVID-19 are exaggerated. All results for both mask wearing and social distancing per COM-B domain are presented in Table 4 . Table 4 Multivariable logistic regression results for face mask wearing and social distancing (survey 1) among those with two doses of COVID-19 vaccine (n = 18,873) Wearing of face mask in public indoor spaces Keeping a 1 + metre distance from others Always/Most of the time OR (95% CI) Always/Most of the time OR (95% CI) Reflective motivation 0.58*** (0.53, 0.63) 0.74*** (0.683, 0.81) Automatic motivation 2.20*** (2.02, 2.39) 2.46*** (2.27, 2.67) Social opportunity 1.70*** (1.61, 1.79) 1.77*** (1.68, 1.87) Psychological capability 1.31*** (1.23, 1.39) 1.29*** (1.22, 1.37) Age 30–39 (vs < 30) 1.54 (0.97, 2.46) 1.19 (0.80, 1.76) 40–49 (vs < 30) 0.74 (0.50, 1.11) 1.68** (1.15, 2.46) 50–59 (vs < 30) 1.04 (0.73, 1.50) 1.77*** (1.28, 2.46) 60+ ( 50,000 (vs. 0–24,999) 1.11 (0.97, 1.28) 0.73*** (0.64, 0.84) Gender Male (vs. Female) 0.70*** (0.63, 0.78) 0.856** (0.77, 0.95) Received an NHS risk letter (vs. Did not receive an NHS risk letter) 1.07 (0.91, 1.25) 1.78*** (1.49, 2.12) * p < 0.05, ** p < 0.01, *** p < 0.001 Reference category: Sometimes/Rarely/Never Wearing of face mask Cox and Snell 0.092, Nagelkerke 0.179, Hosmer and Lemeshow p < 0.001 Keeping a 1 + metre distance Cox and Snell 0.100, Nagelkerke 0.186, Hosmer and Lemeshow p < 0.001 [insert Table 4 here] Survey 2 RQ2a. Frequency of lateral flow testing Of 26,613 respondents, 32.1% had never done an LFT. Of the 67.9% who had done an LFT, 50.4% tested routinely, while the remaining 49.6% tested non-routinely. RQ2b. Non-routine testing: Reasons for testing and understanding the test result Among those who tested non-routinely, the most frequently reported reason or occasion for testing was before visiting friends and family (40.2%). In contrast, the least cited reasons for testing included personal health or illness-related issues—16.7% when feeling poorly, 12.9% because of having been in contact with someone who might have COVID-19, and 10.8% because of having symptoms that might be COVID-19. An even smaller minority tested for other reasons such as travel and getting into venues (see Table 5 ). Table 5 Reasons for testing among those who do not routinely take a LFT (n = 8,953) Yes % (n) No % (n) Before visiting friends or relatives 40.2 (3602) 59.8 (5351) To get into a venue 4.9 (443) 95.1 (8510) When I’m feeling poorly 16.7 (1491) 83.3 (7462) Because I have symptoms that might be Covid-19 10.8 (968) 89.2 (7985) Because I’m required to for work/education 7.4 (664) 92.6 (8289) So that I can travel 6.5 (585) 93.5 (8368) Because someone told me to 9.2 (825) 90.8 (8128) Because I’ve been in contact with someone I think might have Covid-19 12.9 (1156) 87.1 (7797) Had other reasons 18.8 (1684) [insert Table 5 here] Most people thought that a positive test meant they probably had COVID-19 (76.2%) with only a minority thinking a positive test definitely indicated COVID-19 infection (20.4%). The majority thought that a positive test meant they could definitely or probably infect others (97.3%). RQ2c. Routine testing. Those who tested routinely were more likely to think that a positive test needed to be followed up with a PCR test than those who did not test routinely (90.7% vs. 81.3%). The majority thought that if they tested positive they definitely needed to self-isolate (80.3%) and most thought that their household contacts would need to self-isolate (61.6%). Those who regularly tested were more likely than those who did not regularly test to think that positive tests needed to be reported (92.6% vs. 81.1%). A summary of these results as well significant differences in the interpretation of LFT results between those who routinely and do not routinely test are shown in Table 6 . Table 6 Differences in interpretation of LFT results among those who routinely and do not routinely take a LFT Definitely don’t have COVID-19 % (n) Probably don’t have COVID-19 % (n) May still have COVID-19 % (n) Don’t know % (n) Chi-square (c 2 ) Sig. Overall Routinely have LFT (n = 9059) 7.1 (635) 71.5 (6368) 20.6 (1830) 0.8 (68) c 2 (3) = 154.556, p < .001 Do not routinely have LFT (n = 8901) 6.1 (549) 79.3 (7181) 14.2 (1288) 0.5 (41) Definitely not % (n) Probably not % (n) Don’t know % (n) Probably % (n) Definitely % (n) Do you think you could have a negative test result today from a lateral flow test but a positive test result tomorrow? Routinely have LFT (n = 9066) 1.1 (98) 4.7 (425) 7.9 (716) 36.5 (3309) 49.8 (4518) c 2 (4) = 59.861, p < .001 Do not routinely have LFT (n = 8898) 1.4 (122) 5.6 (494) 9.9 (882) 38.5 (3423) 44.7 (3977) If you get a negative result from a lateral flow test, it means: It’s safe to mix with people from outside your household Routinely have LFT (n = 8990) 5.3 (475) 7.1 (637) 2.4 (218) 67.8 (6098) 17.4 (1562) c 2 (4) = 73.905, p < .001 Do not routinely have LFT (n = 8110) 4.2 (369) 8.8 (776) 3.8 (334) 68.5 (6031) 14.8 (1300) I need to get a PCR test Routinely have LFT (n = 8549) 43.4 (3706) 46.3 (3960) 2.8 (240) 2.1 (179) 5.4 (464) c 2 (4) = 517.788, p < .001 Do not routinely have LFT (n = 8297) 31.3 (2600) 50.2 (4168) 7.4 (615) 5.1 (422) 5.9 (492) I need to report my test result Routinely have LFT (n = 8819) 11.0 (969) 7.5 (660) 3.6 (321) 8.3 (733) 69.6 (6136) c 2 (4) = 517.788, p < .001 Do not routinely have LFT (n = 8489) 19.5 (1657) 14.9 (1261) 8.4 (713) 10.5 (888) 46.8 (3970) If I test positive on LFT: I’m infected with Covid-19 Routinely have LFT (n = 8709) 0.6 (52) 0.6 (49) 1.7 (152) 76.2 (6640) 19.9 (1816) c 2 (4) = 15.045, p = .005 Do not routinely have LFT (n = 8487) 0.8 (67) 0.8 (72) 2.3 (194) 76.1 (6456) 20.0 (1698) I might infect others Routinely have LFT (n = 8680) 0.5 (41) 0.3 (27) 1.5 (131) 59.0 (5122) 38.7 (3359) c 2 (4) = 16.921, p = .002 Do not routinely have LFT (n = 8427) 0.7 (58) 0.6 (48) 1.8 (149) 60.2 (5073) 36.8 (3099) I need to get a PCR test Routinely have LFT (n = 8821) 0.8 (71) 0.8 (71) 2.3 (204) 5.4 (475) 90.7 (8000) c 2 (4) = 327.444, p < .001 Do not routinely have LFT (n = 8389) 1.2 (97) 1.8 (147) 5.4 (455) 10.4 (873) 81.3 (6817) I need to self-isolate Routinely have LFT (n = 8823) 0.8 (71) 0.6 (50) 1.5 (129) 13.6 (1200) 83.6 (7373) c 2 (4) = 122.234, p < .001 Do not routinely have LFT (n = 8495) 0.9 (74) 1.0 (86) 2.3 (194) 18.8 (1597) 77.0 (6544) Others who live with me will need to self-isolate Routinely have LFT (n = 8641) 2.3 (196) 5.3 (461) 6.0 (516) 21.0 (1817) 65.4 (5651) c 2 (4) = 114.960, p < .001 Do not routinely have LFT (n = 8262) 2.7 (224) 6.5 (539) 8.4 (693) 24.8 (2045) 57.6 (4761) I need to report my test result Routinely have LFT (n = 8821) 0.8 (70) 0.6 (54) 1.9 (167) 4.1 (364) 92.6 (8166) c 2 (4) = 517.788, p < .001 Do not routinely have LFT (n = 8456) 1.8 (152) 2.1 (181) 6.2 (521) 8.8 (744) 81.1 (6858) [insert Table 6 here] Overall, only a small minority of participants thought that a negative LFT test meant that they definitely did not have COVID-19 (6.6%) with 92.8% thinking they ‘probably did not have COVID-19’ or ‘may still have COVID-19’. Most people thought that a negative LFT result today could definitely or probably turn positive the next day (84.8%). The great majority thought that a negative test meant it is probably safe to mix with people from outside their households (70.9%). Those who tested routinely were more likely to think that they do not need to follow up a negative test with a PCR test than those who did not test routinely (43.4% vs. 31.3%). Those who tested routinely were also more likely to think that they needed to report their negative test result compared to those who did not test routinely (69.6% vs 46.8%). RQ2d. Non-testing: Influences on testing – COM-B factors Table 7 depicts the reasons reported by those who have never taken an LFT categorised into capability, opportunity, and motivational factors. Participants’ responses indicated that the highest level of agreement (mean M = 4.3, SD = 0.97) was obtained for the statement 'I have not needed to test’ (Social opportunity). Table 7 Mean and SDs of reasons for never having taken a LFT Mean (SD) Answered Definitely % (n) Answered Probably % (n) Answered Don’t know % (n) Answered Probably not % (n) Answered Definitely not % (n) Capability Factor I don’t know where to get tested or where to get a hold of tests (n = 6351) 2.02 (1.153) 4.1 (262) 8.9 (564) 16.2 (1030) 26.7 (1695) 44.1 (2801) Opportunity Factor (social) I have not needed to (n = 8294) 4.33 (0.966) 55.3 (4588) 31.9 (2642) 7.9 (653) 0.7 (57) 4.3 (354) Opportunity Factor (physical) I can’t afford to self-isolate for practical or financial reasons (n = 6261) 1.64 (0.916) 1.7 (108) 2.6 (163) 12.3 (767) 24.6 (1538) 58.9 (3685) Motivation Factors (reflective) Cronbach’s Alpha = 0.815 I don’t believe it is accurate (n = 6325) 2.41 (1.022) 3.3 (207) 8.3 (528) 36.7 (2324) 29.7 (1876) 22.0 (1390) I don’t want to have to report my test result (n = 6253) 1.78 (0.955) 1.4 (87) 2.4 (148) 19.4 (1215) 27.0 (1686) 49.8 (3117) I don’t want to or am unable to self-isolate (n = 6271) 1.74 (0.955) 1.5 (92) 3.7 (233) 16.1 (1011) 25.0 (1570) 53.7 (3365) I don’t believe in testing (n = 6263) 1.49 (0.835) 1.7 (104) 0.7 (45) 10.3 (644) 19.4 (1218) 67.9 (4252) I don’t think Covid-19 poses a risk to me (n = 6281) 1.57 (0.914) 1.8 (113) 2.8 (176) 10.3 (646) 20.9 (1310) 64.3 (4036) I’m vaccinated so I can’t catch Covid-19 (n = 6356) 1.70 (0.902) 1.5 (93) 2.5 (156) 14.0 (889) 28.4 (1805) 53.7 (3413) Motivation Factors (automatic) It is unpleasant or uncomfortable (n = 6312) 2.69 (1.080) 4.5 (283) 15.6 (985) 43.0 (2712) 18.4 (1160) 18.6 (1172) It’s a hassle (n = 6290) 2.36 1.058) 2.2(137) 10.0 (628) 37.4 (2352) 22.5 (1415) 27.9 (1758) *Responses: Definitely, Probably, Don’t know, Probably not, Definitely not [insert Table 7 here] Conversely, participants’ low mean scores for the statements which were categorised as ‘reflective motivation’ statements, which mostly conveyed negative meanings (e.g. ‘I don’t think Covid-19 poses a risk to me’), indicated that participants did not agree with these statements. The lowest mean score (denoting a disagreement) was found for the statement ‘I don’t believe in testing’ (M = 1.49, SD = 0.84) signifying that the majority of participants did believe in testing, despite never having done a LFT. Discussion The results of our study indicate that a significant portion of fully vaccinated individuals maintained high adherence to wearing face masks in public indoor spaces (88.5% of the sample) and practicing social distancing (keeping at least 1 meter from others) (86.8% of the sample) most of the time. At the time of the data collection, there was no legal requirement in England and Wales to wear a face mask or maintain social distancing, with only general government advice that people should continue to wear a face mask and maintain a social distance considering the risks of close contact with others, particularly those who were clinically extremely vulnerable or not yet fully vaccinated [ 59 ]. It is noteworthy that while some participants reported minor changes in the frequency of mask-wearing and social distancing after vaccination, the majority reported no change in these behaviors. In contrast, a substantial portion of respondents (32.1% of the sample) had never used a lateral flow test (LFT), a percentage that appears considerably high, especially considering that the study was conducted during the peak of the pandemic when LFTs were widely available and often free or low-cost for asymptomatic testing. However, among those who had used LFTs, half of them (50.4%) reported testing regularly. High level of adherence for face mask wearing is consistent with other UK studies which were conducted at later stages of the pandemic documenting that the overall levels of adherence were relatively high throughout the pandemic until the government mandate ended. A cross-sectional study investigating adherence to PPBs, including face mask wearing over the course of the pandemic, found that engagement with protective behaviours increased at the start of the pandemic and remained high throughout and that the greatest variations in behaviour reflected changes to Government guidance [ 50 ]. Similarly, another study found that adherence to PPBs ranged between 50–95%, with higher adherence during the period of stricter government measures and with the highest level of adherence for wearing masks indoors [ 60 ]. The reported level of adherence to social distancing in this study is notably higher compared to findings in other studies, where adherence rates ranged from as low as 31% [ 61 ] to 70% [ 60 ]. Conversely, in a separate study, non-adherence, whether intentional or unintentional, was reported at a much higher rate of 92.8% [ 62 ], though we noted the smaller sample size of that particular study and that follow up analyses showed that the odds of not adhering to rules increased if a participant was not identified as highly vulnerable to COVID-19 [ 43 ]. In comparison, the majority of participants in this study were aged 60 years and above and had received two doses of the vaccine indicating a specific demographic represented in this research. The variation in age distribution between those who received one versus two doses of the vaccine can be attributed to the initial vaccination campaign's emphasis on prioritising older adults due to elevated risk of infection and severe illness. This likely contributed to a heightened awareness of health precautions among older adults during the COVID-19 pandemic. This is also in line with other studies in the UK which show that being less vulnerable and less worried about COVID-19 increased the odds of non-adherence to social distancing and isolation. [ 43 , 63 ] This, to a degree, also reflects the effectiveness of COVID-19 risk communication targeted at the vulnerable population, particularly the older population. In relation to changes in reported compliance for mask wearing and social distancing, our finding that the majority reported no change in behaviour is in line with the findings in the COVID-19 Social Study which comprised of 70,000 adults in the UK and did not yield any significant differences in compliance with COVID-19 measures between those who were vaccinated and those non-vaccinated [ 15 , 64 ]. A smaller study in the UK also shows similar findings of no significant differences in decrease of PBBs among the fully, partially, and non-vaccinated [ 65 ]. Identified influences on face mask wearing and social distancing post-vaccination After adjusting for age, sex, income, ethnicity, and receipt of NHS risk letter, capability, opportunity, and motivation factors were associated with higher compliance to mask wearing and social distancing [ 66 ]. In relation to automatic motivation which was the strongest predictor for both mask wearing and social distancing, this finding is in line with other studies which reveal that automatic motivation factors such as habit and fear are associated with increased compliance to protective behaviours [ 35 , 67 ]. Associations between these PPBs and social opportunity factors have also been previously documented. In several studies, adherence to social distancing decreased when one had less control over others’ distancing or when coming in contact with others was unavoidable [ 43 , 68 ]. Another study in the US showed that the perceived social norm was a predictor of mask wearing behaviour. [ 35 ] Finally, capability factors such as having access to COVID-19 information and being knowledgeable about the threat of COVID-19 have also been shown to increase the likelihood of adherence to public health measures [ 69 ]. The reflective motivation factor assessed risk perception post vaccination in this study - specifically, agreement with the statement that COVID-19 poses low to no risk after vaccination - signifying that participants did not think that the risk of infection was lower post vaccination. This finding is consistent with existing evidence showing that perceived high risk to COVID-19 promotes vaccine uptake as a means of protection and risk aversion [ 64 , 70 , 71 ], and it is therefore, possible that the same risk aversion could promote PPBs irrespective of vaccination status [ 72 ]. Conversely, being less worried about COVID-19 decreases the likelihood of compliance to PPBs [ 63 ]. In a similar vein, other reflective motivation factors such as self-efficacy and action planning have been shown to increase compliance to PPBs [ 68 , 73 , 74 ]. Identified influences on LFT Of the 67.9% who had done an LFT, participants reported primarily using LFTs only before social gatherings with friends and family. They rarely tested themselves in response to any symptoms that may be COVID-19 or after potential exposure to COVID-19 and a very small proportion of our participants responded that they tested for work-related purposes or to travel. In contrast, in a study conducted in two English local authority areas, 60% of participants reported getting tested primarily for work-related reasons [ 48 ]. This finding may be explained by the government’s advice at the time of the survey to take a PCR test for those experiencing symptoms. Furthermore, this finding highlights the importance of social relations and the sense of social responsibility towards others, which are fundamental human needs, especially during times of isolation. This is particularly relevant in the context of meeting friends and family from different households, which showed the most significant increase after vaccination in our study. This also emphasises the complex interplay between public health guidance, testing behaviours and the need to maintain social connections during these challenging times [ 75 ]. In the context of interpreting test results, the key difference between individuals who test regularly being more inclined to report a positive test and self-isolate than those who do not test regularly, can be attributed to differences in their overall understanding of the disease and risk attitudes of each group. While there is a lack of specific studies exploring the association between COVID-19 testing behaviors and risk attitudes, existing research indicates that being risk-averse can serve a protective function. Risk-averse individuals tend to engage in more proactive health information seeking and a perception of utility of public health measures, such as adhering to lockdown protocols [ 70 ]. Those in the habit of routine testing may exhibit a higher risk aversion, leading them to be more cautious and therefore, reporting a positive result and isolating promptly, thereby reducing the risk of spreading the virus to others. Conversely, individuals with a higher tolerance for risk might adopt a more relaxed approach even in the event of a positive test result, assuming that transmission might not necessarily occur. This leniency could result from their willingness to accept a certain level of risk or uncertainty in their daily activities. Among individuals who have never taken an LFT, the highest mean (agreement) score pertained to the social opportunity factor that they did not need to test indicating a perceived lack of need for testing. This finding coupled with high disagreement scores for negative statements about the utility and accuracy of testing (reflective motivation) suggest a likely absence of conditions such as work requirements, social interactions or contact with infected individuals that would necessitate the use of LFT rather than negative beliefs about the value of testing. Alternatively, this could also be attributed to a limited understanding about when to take the LFT test (psychological capability). This finding aligns with other research, where limited face-to-face interactions with others emerged as a common justification for not testing [ 76 ]. Moreover, another study revealed that a prevalent reason for not engaging in LFTs, despite the recommended bi-weekly testing, was the belief that testing was only necessary after exposure to someone with COVID-19 [ 44 ]. Policy implications While the COVID-19 is no longer classified as a public health emergency of international concern [ 77 ], the findings of this study can be useful for future pandemic preparedness and critical response strategies. It is noteworthy that the findings of our study suggest that at a time when there were few restrictions in the UK, many participants reported still wearing a face mask and keeping the recommended distance. This indicates that adherence to these behaviours was mostly a personal decision, rather than merely a response to official guidance, to protect themselves and others around them [ 78 ]. This is supported by studies conducted during the COVID-19 and influenza (e.g. H1N1 in 2009) pandemics which show that greater sense of social responsibility and the belief in protecting others promoted compliance to protective behaviours [ 79 – 81 ]. Similarly, LFTs which enable access to testing beyond healthcare settings were reportedly used by the majority of our participants. However, our results suggest that there was still a significant proportion of our participants (about a third of our sample) who had never used an LFT at a time when the pandemic was still ongoing and when LFTs were widely available - although not free for most people apart from those meeting eligibility criteria (i.e. being clinically vulnerable and working as a key worker). Based on our findings, health communications and messaging campaigns in the UK are recommended to focus on shared responsibility and social consciousness principles since the population appears to relate and respond well to these [ 82 ]. Importantly, given that the LFTs could also play an important part in the detection of other infectious diseases of epidemic potential and antimicrobial resistance [ 46 ], public health planning should also focus on increasing social opportunity by addressing systemic factors that influence LFT uptake for COVID-19 and other infectious respiratory diseases. It is important, however, to consider the ethical implications of any interventions especially in light of substantial evidence pointing to intervention-induced inequalities during the pandemic [ 83 ]. Failing to address these ethical considerations may exacerbate existing disparities and disproportionately impact vulnerable populations, emphasising the need for a conscientious and equitable approach in implementing intervention strategies to ensure fair outcomes across diverse communities [ 84 , 85 ]. Recommendations for intervention design To generate recommendations for interventions to increase the uptake of mask wearing, social distancing, and LFT, we consulted the BCW matrix for intervention strategies that are likely to be effective in addressing the different types of behavioural influences. The BCW is a published matrix that pairs the COM-B to BCW interventions and policy options for intervention implementation [ 53 , 86 ]. Factors found to be significantly associated with the target behaviours were mapped to Intervention Types (ITs) and then onto relevant policy options using the BCW matrix and generated descriptions as to how these could potentially be operationalised and delivered using frequently used Behaviour Change Techniques taxonomy BCTTv1 [ 87 ]. Significant influences for mask wearing and social distancing were found to be associated with capability, social opportunity and motivation, with (automatic) motivation having the highest odds for uptake of mask wearing and social distancing. These factors could be targeted with a wide range of interventions such as education and persuasion, delivered via policy options such as communication, regulation, or environmental and social planning in a way that resonates with the community's values and concerns. For example, a tailored public health messaging campaign could include a series of posters or digital graphics conveying persuasive messages about the benefits of face masks or social distancing in protecting both oneself and others and encourage regular mask wearing and social distancing as a habit in public spaces. For testing, the primary COM-B domain underpinning lack of testing was social opportunity followed by psychological capability. Factors related to social opportunity can be targeted through interventions using modelling, environmental restructuring, and enablement. For example, public health (government or community) campaigns should aim to convey the importance of testing as a community-wide responsibility to curb the virus and can encourage regular testing through video advertisements featuring prominent public figures and/or healthcare professionals. A list of other potential intervention strategies and policy options as well as examples of how these could be delivered, in the form of behavior change techniques, are shown in Table 8 . Table 8 COM-B influences mapped to proposed interventions using the Behaviour Change Wheel Behaviour COM-B factors Intervention types Policy options Example Behaviour Change Techniques Examples of how these could be designed and delivered Mask wearing/ Social distancing/ Testing Psychological Capability Education Enablement Persuasion Communications/marketing Guidelines - Information about social and environmental consequences - Information on health consequences - Salience of consequences - Action planning - Credible source -Raise awareness about the importance of minimising risk/stop virus transmission through the use of PPBs -Raise awareness of importance of testing following contact with someone who had Covid-19 -Provide details of where to locate scientifically robust evidence about the benefits of mask wearing, social distancing and testing - Community support, targeted media campaigns, apps, and websites to assist households, especially those with vulnerable people to establish new living arrangements and routines and to remember the guidance Mask wearing/ Social distancing/ Testing Reflective Motivation Education Persuasion Modelling Enablement Communications/marketing Guidelines - Pros and cons - Credible source - Framing /reframing - Information about health consequences - Address misleading informational sources about mask wearing, social distancing and testing accuracy (e.g., social media) -Provide testimonials from medical experts about the importance of mask wearing, social distancing and testing -Targeted ads and comms campaigns about the significance of testing and likely unwanted consequences before meeting vulnerable individuals Mask wearing/ Social distancing Automatic Motivation Persuasion Modelling Incentivisation/ Coercion Communications/marketing Service provision Fiscal measures - Habit formation -Information about consequences - Anticipated regret, - Social support (Emotional) - Salience of consequences - Prompt rehearsal and repetition of mask wearing and social distancing in public spaces (context) so that the context elicits the behaviour (e.g. prompt individuals before taking public transport, or offer free masks) so that it becomes a habit -Testimonials from individuals at high risk about their experiences/fears -Create an expectation of a fine if not adhering to government guidance Testing/ Mask wearing/ Social distancing Social Opportunity Persuasion Modelling Environmental restructuring Enablement Service provision Guidelines Regulation Environmental/ social planning - Credible source - Social support (Practical) - Social comparison - Workplaces (all public-facing industries) should provide testing programmes for their workers to increase uptake/make it an expectation - Make it a pre-requisite for admission in certain settings like public transport, public places and healthcare settings - Offer masks or LFTs in a variety of designated locations in the community (e.g. schools, hospitals) - Community champions to model behaviour (e.g. testing, mask wearing) - Community support, clear messaging and promotion of strong social identity and shared responsibility [insert Table 8 here] Strengths and Limitations Strengths of the study include the large sample size and the use of a theoretically-informed behavioural science framework to structure the questionnaire items and interpret the data. This allows for a systematic analysis and identification of influences on the behaviours of interest and to generate recommendations for future public health interventions. However, despite the large sample size, non-white ethnic groups were under-represented in this study and most participants were older adults (60+). It is also likely that participants may have been more self-aware of adherence to PPBs and responses may have been influenced by a degree of social-desirability bias. These limitations may have led to an overreporting of PPBs compared to the general population. Conclusions The findings of this study show that, overall, there is a high level of adherence to mask wearing and social distancing, despite fewer restrictions and high rates of vaccination. However, there is still a proportion of people (about 10%) who do not use these protective measures and a higher proportion of people who had never used the LFT (about 30%) to check themselves. After two doses of the vaccine, people reported visited friends and relatives more frequently compared to other activities and visiting family and friends was also the most reported reason for testing. Therefore, targeted interventions and public health initiatives fostering a sense of social responsibility and promoting safe social interactions can be effective in managing new COVID-19 variants and new viruses in future public health emergencies. Declarations Ethics approval and consent to participate All methods were carried out in accordance with relevant guidelines and regulations. The Virus Watch Study was approved by the Hampstead NHS Health Research Authority Ethics Committee (Ethics approval number 20/HRA/2320). Informed consent was obtained from all participants involved in the study. Clinical trial number : not applicable Consent to Publish declaration : not applicable Competing interests The authors declare no competing interests. Availability of data and materials – All materials used are included in the Appendices andthe data presented in this study are available upon reasonable request from the corresponding author. Funding – This study has received funding from the following funders: UKRI Medical Research Council Grant: MC_PC 19070 & MR/V028375/1 Department of Health & Social Care, UK European Commission Horizon Health 2021 Grant: 101046314 Authors' contributions – Conceptualisation, SM, FL, SB, RA, AH, CM, VA; Design, SM, FL, SB, AH, RA, CM, VA, Funding acquisition, SM, FL, SB, RA, AH; Methodology, SM, FL, SB, AH, RA, CM, VA; Data curation, MO; Formal analysis, MO, CM, VA; Investigation and Interpretation, MO, VA, CM; Writing – original draft, OM, VA; Writing – review & editing, VA, OM, CM, FL, SM, SB, AH, RA. All authors have approved the submitted version of the study References World Health Organization. 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Characteristics and motivations of individuals participating in COVID-19 community testing in two English local authority areas. BMC Public Health. 2022;22(1):588. Smith LE, et al. Who is engaging with lateral flow testing for COVID-19 in the UK? The COVID-19 Rapid Survey of Adherence to Interventions and Responses (CORSAIR) study. BMJ Open. 2022;12(2):e058060. Smith LE, et al. Adherence to protective measures among healthcare workers in the UK: a cross-sectional study. Emerg Med J. 2022;39(2):100–5. Smith LE, et al. How has the emergence of the Omicron SARS-CoV-2 variant of concern influenced worry, perceived risk and behaviour in the UK? A series of cross-sectional surveys. BMJ Open. 2022;12(8):e061203. Bavel J, et al. Using social and behavioural science to support COVID-19 pandemic response. Nat Hum Behav. 2020;4(5):460–71. Michie S, van Stralen MM, West R. The behaviour change wheel: A new method for characterising and designing behaviour change interventions. Implement Sci. 2011;6(1):42. Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011;6:42. Andrew H, et al. Risk factors, symptom reporting, healthcare-seeking behaviour and adherence to public health guidance: protocol for Virus Watch, a prospective community cohort study. BMJ Open. 2021;11(6):e048042. Byrne T, et al. Cohort Profile: Virus Watch-understanding community incidence, symptom profiles and transmission of COVID-19 in relation to population movement and behaviour. Int J Epidemiol. 2023;52(5):e263–72. NHS. COVID-19 Vaccination Statistics: Week ending Sunday 25th July 2021. NHS; 2021. NHS. Weekly statistics for rapid asymptomatic testing (England): 19 August to 25 August 2021 . 2021. Goverment U. COVID-19 Response - Spring 2021. Spring; 2021. Kale D, et al. Patterns and predictors of adherence to health-protective measures during COVID-19 pandemic in the UK: cross-sectional and longitudinal findings from the HEBECO study. BMC Public Health. 2022;22(1):2347. Norman P, Wilding S, Conner M. Reasoned action approach and compliance with recommended behaviours to prevent the transmission of the SARS-CoV-2 virus in the UK. Br J Health Psychol. 2020;25(4):1006–19. Eraso Y, Hills S. Intentional and unintentional non-adherence to social distancing measures during COVID-19: A mixed-methods analysis. PLoS ONE. 2021;16(8):e0256495. Smith LE, et al. Factors associated with adherence to self-isolation and lockdown measures in the UK: a cross-sectional survey. Public Health. 2020;187:41–52. Brewer NT, et al. Risk compensation and vaccination: can getting vaccinated cause people to engage in risky behaviors? Ann Behav Med. 2007;34(1):95–9. Desrichard O, Moussaoui L, Ofosu N. Reduction of Precautionary Behaviour following Vaccination against COVID-19: A Test on a British Cohort. Vaccines (Basel), 2022. 10(6). Pedersen MJ, Favero N. Social Distancing during the COVID-19 Pandemic: Who Are the Present and Future Noncompliers? Public Adm Rev. 2020;80(5):805–14. Hagger MS, et al. Predicting Social Distancing Intention and Behavior During the COVID-19 Pandemic: An Integrated Social Cognition Model. Ann Behav Med. 2020;54(10):713–27. Coroiu A, et al. Barriers and facilitators of adherence to social distancing recommendations during COVID-19 among a large international sample of adults. PLoS ONE. 2020;15(10):e0239795. Moran C, et al. Predictors of attitudes and adherence to COVID-19 public health guidelines in Western countries: a rapid review of the emerging literature. J Public Health (Oxf). 2021;43(4):739–53. Petrocchi S et al. The interplay between risk and protective factors during the initial height of the COVID-19 crisis in Italy: The role of risk aversion and intolerance of ambiguity on distress. Curr Psychol, 2021: pp. 1–12. Hudson A, Montelpare WJ. Predictors of Vaccine Hesitancy: Implications for COVID-19 Public Health Messaging. Int J Environ Res Public Health, 2021. 18(15). Hamilton K, et al. Application of the Health Action Process Approach to Social Distancing Behavior During COVID-19. Appl Psychol Health Well Being. 2020;12(4):1244–69. Seale H, et al. COVID-19 is rapidly changing: Examining public perceptions and behaviors in response to this evolving pandemic. PLoS ONE. 2020;15(6):e0235112. Hamilton K, Hagger MS. The Vaccination Concerns in COVID-19 Scale (VaCCS): Development and validation. PLoS ONE. 2022;17(3):e0264784. Long E et al. COVID-19 pandemic and its impact on social relationships and health. J Epidemiol Community Health, 2021. Mathers J, et al. Exploration of the uptake of asymptomatic COVID-19 lateral flow testing in Birmingham, UK: survey and qualitative research. BMJ Open. 2022;12(4):e056606. (WHO). W.H.O., WHO chief declares end to COVID-19 as a global health emergency , https://news.un.org/en/story/2023/05/1136367 . May 2023. Jalloh MF et al. Behaviour adoption approaches during public health emergencies: implications for the COVID-19 pandemic and beyond. BMJ Glob Health, 2021. 6(1). Warnock-Parkes E, Thew GR, Clark DM. Belief in Protecting Others and Social Perceptions of Face Mask Wearing Were Associated With Frequent Mask Use in the Early Stages of the COVID Pandemic in the UK. Front Psychol. 2021;12:680552. Davis MD, et al. Beyond resistance: social factors in the general public response to pandemic influenza. BMC Public Health. 2015;15:436. Grimani A, et al. Effect of prosocial public health messages for population behaviour change in relation to respiratory infections: a systematic review protocol. BMJ Open. 2021;11(1):e044763. Grimani A, Antonopoulou V, Meader N, Bonell C, Michie S, Kelly MP, Vlaev I. Motivational effectiveness of prosocial public-health messaging interventions to reduce the risk of respiratory infections: A systematic review and network meta-analysis [Manuscript under review]. 2023. Paremoer L, et al. Covid-19 pandemic and the social determinants of health. BMJ. 2021;372:n129. Green MA, et al. Evaluating social and spatial inequalities of large scale rapid lateral flow SARS-CoV-2 antigen testing in COVID-19 management: An observational study of Liverpool, UK (November 2020 to January 2021). Lancet Reg Health Eur. 2021;6:100107. Watson D, et al. How do we engage people in testing for COVID-19? A rapid qualitative evaluation of a testing programme in schools, GP surgeries and a university. BMC Public Health. 2022;22(1):305. Michie S, et al. Reducing SARS-CoV-2 transmission in the UK: A behavioural science approach to identifying options for increasing adherence to social distancing and shielding vulnerable people. Br J Health Psychol. 2020;25(4):945–56. Michie S. Implementation science: understanding behaviour change and maintenance . BMC Health Serv Res. 2014;14(Suppl 2):O9. 10.1186/1472-6963-14-S2-O9 . eCollection 2014. Additional Declarations No competing interests reported. Supplementary Files VirusWatchSupplementaryMaterial.docx Cite Share Download PDF Status: Published Journal Publication published 17 Jan, 2026 Read the published version in Discover Public Health → Version 1 posted Editorial decision: Revision requested 13 Oct, 2025 Reviews received at journal 06 Oct, 2025 Reviewers agreed at journal 03 Oct, 2025 Reviews received at journal 20 Aug, 2025 Reviewers agreed at journal 22 Jul, 2025 Reviews received at journal 02 Jun, 2025 Reviewers agreed at journal 27 May, 2025 Reviewers agreed at journal 23 May, 2025 Reviewers invited by journal 23 May, 2025 Editor assigned by journal 11 May, 2025 Submission checks completed at journal 07 May, 2025 First submitted to journal 07 May, 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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These measures included travel bans, lockdowns (school, non-essential shop, and workplace closures), restrictions on social interactions, isolation and quarantine protocols, social distancing guidelines, mandatory mask-wearing, and cancellation of public events. In countries with testing capabilities, population-wide testing and contact tracing were also implemented [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, it has been widely recognised that the introduction of such measures alone is not enough to limit disease transmission. Behaviours such as compliance with public health guidance, adherence to restrictions, and the adoption of personal protective measures (PPBs) (e.g., hand washing and use of face masks) are crucial factors for the successful prevention of infectious diseases across communities [\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEven after the development of effective vaccines [\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], with new strains of the virus, waning immunity, and a proportion of the population remaining unvaccinated for COVID-19, PPBs continued to be valuable in managing the spread of the disease [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, as vaccination was promoted as the most effective public health intervention to control the virus and return to normalcy, there were concerns that adherence to preventive behaviours might decline after vaccination due to a false sense of reduced infection risk [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Previous studies on vaccine rollouts for other diseases (e.g. Lyme disease, influenza) indicated reduced adherence [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and early evidence from COVID-19 antibody testing studies also suggested lower intention to engage in protective behaviours among individuals with antibodies [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Studies conducted during the early stages of the COVID-19 pandemic yielded mixed results with some studies suggesting a decrease in PPB use (e.g. [\u003cspan additionalcitationids=\"CR23 CR24 CR25\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], while others indicated a consistent use of PPBs regardless of vaccination status [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMask wearing and social distancing are important PPBs to mitigate COVID-19 infection, particularly as mask wearing and social distancing are the most visible and hence socially impactful [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. A number of international studies examining adoption of mask wearing and social distancing during the COVID-19 pandemic indicated that PPB use can vary depending on the specific behaviour, country, and time ([\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Evidence regarding sociodemographic factors influencing mask wearing and social distancing including age [\u003cspan additionalcitationids=\"CR34 CR35 CR36\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], gender [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan additionalcitationids=\"CR39 CR40 CR41\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], level of education [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], employment and income [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], ethnicity [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], and perceived susceptibility to the disease [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] was mixed and varied across contexts. In a similar vein, an evidence review of interventions to increase PPBs for respiratory viruses, including COVID-19, found unclear results for interventions targeting face mask use and highlighted the lack of evidence about intervention effectiveness for the majority of PPBs [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSelf-testing using a rapid Lateral Flow Test (LFTs) (also known as rapid diagnostic test (RDT)) was also a preventative measure that contributed to the management of the COVID-19 virus and was a cost-effective alternative to Polymerase Chain Reaction (PCR) testing [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. LFTs were initially introduced as a form of asymptomatic screening and not recommended for use when symptomatic, and while this guidance later changed, LFTs were still primarily about preventing the spread of the virus by rapidly identifying those individuals who were carrying high levels of the virus so they may self-isolate, rather than for monitoring one\u0026rsquo;s own health [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The evidence-base for the uptake of LFT is still limited, but early evidence pointed to low uptake among the public in UK-based studies, although some improvement was found over time [\u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Moreover, the coexistence of both PCR and LFT options for the general public led to considerable confusion regarding the appropriate test for different situations [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs we are now transitioning out of the acute phase of the COVID-19 pandemic, we need to better understand the evidence from the COVID-19 pandemic to plan for future epidemics/pandemics, particularly as adoption of personal protective measures (PPBs) to protect oneself and others in our communities will undoubtedly be a critical part of any public health response. Using behavioural science theories and frameworks can be very helpful for guiding investigation of the factors influencing the enactment (or maintenance) of PPBs and for designing effective public health interventions [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. An example of an integrated model of behaviour change which is widely used to conceptualise possible influences on behaviour is the COM-B model [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The COM-B model states that to enact a behaviour one needs to have the Capability (psychological or physical), Opportunity (social or physical) and Motivation (the reflective and automatic processes that direct behaviour) to perform the Behaviour [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. One major benefit of the COM-B is that it is mapped to the Behaviour Change Wheel, enabling systematic progression from identifying influences to generating suggestions for interventions [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Therefore, we sought to identify and classify behavioural influences on mask-wearing, social distancing and lateral flow testing during the COVID-19 pandemic with a view to generate recommendations that can inform public health interventions for future epidemics and pandemics.\u003c/p\u003e\n\u003ch3\u003eAims of the current study\u003c/h3\u003e\n\u003cp\u003eIn this context, the present study aimed to assess a) changes to use of wearing of face masks and social distancing, following vaccination compared to baseline, and b) the factors associated with use of face masks and social distancing, and the uptake of lateral flow testing, using a behavioural science approach. Specifically, this study addressed the following research questions (RQs):\u003c/p\u003e \u003cp\u003eRQ1a. To what extent did participants adhere to wearing face masks and observing social distancing rules?\u003c/p\u003e \u003cp\u003eRQ1b. Was there a change in reported use of mask wearing and/or social distancing post-vaccination?\u003c/p\u003e \u003cp\u003eRQ1c. Which influences (capability, opportunity, and motivational factors) are associated with wearing of face masks post-vaccination?\u003c/p\u003e \u003cp\u003eRQ 1d. Which influences (capability, opportunity, and motivational factors) are associated with social distancing post-vaccination?\u003c/p\u003e \u003cp\u003eRQ2a. To what extent did participants use LFT and what were the reasons for using LFT?\u003c/p\u003e \u003cp\u003eRQ2b. Were there any differences in understanding the test result between those who routinely test and those who test opportunistically?\u003c/p\u003e \u003cp\u003eRQ2c. Which influences (capability, opportunity, and motivational factors) are associated with lack of (LF) testing?\u003c/p\u003e "},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eDesign\u003c/h2\u003e \u003cp\u003eThis is a cross-sectional study nested within the prospective Virus Watch community cohort study which comprised over 50,000 participants from households across England and Wales. The Virus Watch study was run by University College London (UCL) in conjunction with NHS and was aiming to investigate transmission of COVID-19 in relation to population movement and behaviours and to provide evidence on which public health approaches are most likely to be effective in reducing transmission of the virus [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Virus Watch included weekly online surveys regarding infection symptoms, COVID-19 testing, and vaccinations, as well as monthly surveys on psychosocial and clinical topics beyond the scope of the weekly surveys and tailored to the phase of the pandemic.\u003c/p\u003e \u003cp\u003eData for this study were collected in two one-off surveys with households sampled from the Royal Mail post office address file and through social media advertising. Data on face mask wearing and social distancing were collected from a survey conducted in July 2021 (survey 1). Data on lateral flow testing were collected from a survey carried out in August 2021 (survey 2). In addition, survey 2 included a screening question about use of LFT and directed participants in two branches based on their responses. If they had used LFT, they were asked questions about routine and non-routine use and their understanding of the test result. If they had never taken a LFT, they were asked about the reasons for never having self-tested using a LFT along with COM-B questions. Data for both surveys were collected using REDCap electronic data capture tools hosted on University College London (UCL) Data Safe Haven.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eSample\u003c/h3\u003e\n\u003cp\u003eFor representativeness, the sample was stratified by age, gender, ethnicity and geographical regions across England and Wales (for more information on the Virus Watch recruitment strategy see [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]). Entire households were recruited, and the lead householder was asked to complete two online surveys.\u003c/p\u003e \u003cp\u003eMask wearing and social distancing (Survey 1): Participants were included if they had received one or two doses of a COVID-19 vaccine at the point of data collection. By the time of the data collection for this study, the vaccine had been offered to all individuals in the first nine priority groups in the UK which included residents of care homes for older adults and their carers, those 50 years old and older, and clinically extremely vulnerable individuals. The UK government anticipated that by the end of July 2021, all 18\u0026ndash;49 year-old people from the general population would have been offered a vaccine. At the time of the survey, 69,932,565 doses had been administered, with 38,890,375 individuals having received at least one dose [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLFT (Survey 2): We included responses from people who had and had not done LFT previously. At the time of data collection, lateral flow devices were available to everyone in England for symptomatic or for regular asymptomatic testing at no cost to the individual [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eMaterials and Measures\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSurvey 1\u003c/h2\u003e \u003cp\u003e \u003cem\u003eRQ1. Mask wearing and social distancing measures\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ea) Frequency of mask wearing and social distancing measures\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eb)\u003c/em\u003e Changes in frequency of mask wearing and social distancing\u003c/p\u003e \u003cp\u003eFrequency of mask wearing and social distancing was measured with the statements \u0026lsquo;\u003cem\u003eI wear a face covering in public, indoor places\u003c/em\u003e\u0026rsquo; and \u0026lsquo;\u003cem\u003eI keep a 1\u0026thinsp;+\u0026thinsp;metre distance from people I don\u0026rsquo;t live with\u003c/em\u003e\u0026rsquo;. Response options were measured on a 5-point Likert Scale and ranged from \u0026lsquo;Never\u0026rsquo; to \u0026lsquo;All of the time\u0026rsquo;. Changes in frequency of mask wearing and social distancing after receiving the vaccine were measured with statements such as \u0026lsquo;\u003cem\u003eHave you changed any of the following as a result of having had one/two doses of the vaccine - Visiting public indoor places (e.g., restaurant, caf\u0026eacute;, cinema) with people you don\u0026rsquo;t live with\u003c/em\u003e\u0026rsquo;. Responses were measured on a 3-point Likert scale (\u0026lsquo;More frequently\u0026rsquo;, \u0026lsquo;No change\u0026rsquo;, \u0026lsquo;Less frequently\u0026rsquo;). (See Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e in the Supplementary Material file)\u003c/p\u003e \u003cp\u003e \u003cem\u003ec) Influences on Mask wearing and social distancing measures\u003c/em\u003e \u003cb\u003e-\u003c/b\u003e \u003cem\u003eCOM-B factors\u003c/em\u003e\u003c/p\u003e \u003cp\u003eInfluences on mask wearing and social distancing behaviours were measured with agreement to statements structured around the COM-B domains, for example \u0026ldquo;\u003cem\u003eThe elderly and vulnerable are protected from Covid-19 now that vaccination is available\u003c/em\u003e\u0026rdquo; (reflective motivation statement). Responses were measured on a 5-point Likert scale from \u0026lsquo;Strongly disagree\u0026rsquo; to \u0026lsquo;Strongly agree\u0026rsquo;. (See Table S2)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSurvey 2\u003c/h2\u003e \u003cp\u003e \u003cem\u003eRQ2. LFT measures\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ea) Frequency of testing\u003c/h3\u003e\n\u003cp\u003eParticipants were initially asked two screening questions to assess use of LFT. The first screening question assessed whether they had ever done a test (\u0026lsquo;Have you ever done a lateral flow test? with response options \u0026lsquo;Yes/No/Don\u0026rsquo;t know\u0026rsquo;); the second question asked about frequency of use (\u0026lsquo;Do you routinely have lateral flow tests? Response options included Yes/No/Don\u0026rsquo;t know\u0026rsquo;).\u0026rsquo; Based on reported frequency of LFT (regular, non-regular testing, never used), participants were directed to either answer questions related to the reported use and understanding of a test result, or to indicate the reasons for never having done a test.\u003c/p\u003e\n\u003ch3\u003eb) Reasons for testing and understanding of a test result\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eNon-regular testing\u003c/em\u003e. Of those who reported having done LFT, those who reported non-regular testing were asked to indicate on which of the following occasions they did a test (option of multiple response): a) Before visiting friends or relatives, b) To get into a venue, c) When I\u0026rsquo;m feeling poorly, d) Because I have symptoms that might be Covid-19, e) Because I\u0026rsquo;m required to for work/education, f) So that I can travel, g) Because someone told me to, h) Because I\u0026rsquo;ve been in contact with someone I think might have Covid-19, i) Other [free text]\u003c/p\u003e \u003cp\u003e This group of participants was also asked questions related to their understanding of the LFT result.\u003c/p\u003e \u003cp\u003e \u003cem\u003eRegular testing\u003c/em\u003e. Participants who reported regular testing were only asked questions related to their understanding of the LFT result.\u003c/p\u003e \u003cp\u003eUnderstanding of a positive/negative LFT result (for participants indicating regular as well as for participants indicating non-regular testing) was measured with agreement to statements such as \u003cem\u003e\u0026lsquo;If you get a positive result from a lateral flow test, it means: I\u0026rsquo;m infected with COVID-19\u003c/em\u003e\u0026rsquo; on a 5-point Likert scale (from \u0026lsquo;Definitely not\u0026rsquo; to \u0026lsquo;Definitely\u0026rsquo;). (See Table S3)\u003c/p\u003e \u003cp\u003ec) \u003cem\u003eInfluences on testing - COM-B factors\u003c/em\u003e\u003c/p\u003e \u003cp\u003eParticipants who reported never having done a LFT test were asked to indicate their level of agreement with statements citing possible reasons for never having done an LFT. These statements were structured around the COM-B model including capability, opportunity, and motivational factors, for example, \u0026lsquo;\u003cem\u003eI don\u0026rsquo;t want to have to report my test result\u0026rsquo;\u003c/em\u003e (reflective motivation). The response options were measured on a 5-point Likert scale ranging from \u0026lsquo;Strongly disagree\u0026rsquo; to \u0026lsquo;Strongly agree\u0026rsquo;. (See Table S4)\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFor frequency of use, frequency responses for wearing face masks, social distancing, and lateral flow testing were analysed and reported as percentages. Logistic regression models were used to identify those COM-B factors associated with mask wearing and social distancing (maintaining a 1\u0026thinsp;+\u0026thinsp;metre distance) among those fully vaccinated controlling for age, ethnic group, income, gender, and health status (assessed by having received an NHS risk letter). Subscale factors (capability, opportunity, and motivational factors) were used in the model. Cronbach\u0026rsquo;s alpha for each subscale was calculated to assess the internal consistency of the sub-scales (see Table S5). Univariate associations were examined to screen for variables to include in the model (p\u0026thinsp;\u0026lt;\u0026thinsp;0.1). Multicollinearity between predictor variables were checked using the Variance Inflation Factor (VIF) (see Table S6). Frequencies of reported reasons for testing and interpretations of LFT results were analysed and reported as percentages. The reasons for never having done LFT were also analysed and reported as percentages and mean scores. A chi-square test was performed to measure the differences in interpretations of LFT results among those who do and do not routinely test.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eParticipant Characteristics\u003c/h2\u003e \u003cp\u003eThe sociodemographic characteristics of the respondents for both surveys are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In survey 1 (July 2021), a total of 20,488 responses on social distancing and wearing a face mask were included in the final sample.1 In survey 2 (August 2021), a total of 26,613 responses on LFT were included in the final sample. In both surveys, 56% of participants were female and 60 years old and older. The majority of participants belonged to White ethnic groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e Baseline participant characteristics for survey 1 (N\u0026thinsp;=\u0026thinsp;20,488) and survey 2 (N\u0026thinsp;=\u0026thinsp;26,613)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eParticipants (Survey 1: mask wearing and social distancing)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eParticipants (Survey 2: Lateral Flow Testing*)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAfter one dose\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAfter two doses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUsed an LFT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNever used LFT\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge in years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5 (519)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.3 (118)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0 (401)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.6 (952)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.4 (802)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.8 (150)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.4 (493)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4 (483)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.1 (1084)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.1 (931)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.8 (153)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.1 (848)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.1 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.1 (826)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.2 (1925)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.9 (1623)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.5 (302)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.3 (3127)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.0 (14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.3 (3113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.3 (4372)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.8 (3432)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.0 (940)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.7 (15501)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.6 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.2 (15466)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e68.9 (18431)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e62.7 (11422)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e81.9 (7009)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of people in the household\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.9 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.6 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.8 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.0 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.0 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.0 (0.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender at birth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e% (n)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.2 (8803)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.5 (96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.1 (8707)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.2 (11500)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40.9 (7393)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e48.3 (4103)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.6 (11536)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.5 (102)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.6 (11434)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.5 (15036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.9 (10666)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e51.5 (4370)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntersex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1 (34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1 (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1 (8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1 (16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1 (16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1 (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1 (11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnic Group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e% (n)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite-English/Welsh/Scottish/Northern Irish/British\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.7 (18653)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.3 (168)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91.8 (18485)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.0 (23887)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e89.9 (16245)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e90.2 (7642)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny other white background\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (1012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.6 (17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.9 (995)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.5 (1474)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.8 (1053)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.0 (421)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed/ multiple ethnic groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8 (167)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8 (164)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.0 (252)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.0 (181)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.8 (71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian/Asian British background\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.7 (348)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9 (340)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.4 (625)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.1 (383)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.8 (242)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack British/African/Caribbean/Any other Black background\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.6 (167)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.7 (115)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.6 (52)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny other ethnic group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3 (66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4 (66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.4 (99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4 (70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.4 (29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1 (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2 (15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReceived an NHS risk letter\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e% (n)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.6 (2574)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.0 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.6 (2559)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.0 (3205)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.9 (2155)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.4 (1050)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.4 (16391)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.0 (152)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.4 (16239)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87.0 (21428)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e87.1 (14614)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e86.6 (6814)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCombined Household Income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e% (n)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;9,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.9 (1117)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.9 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.8 (1099)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.4 (1331)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.1 (863)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.9 (468)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10,000\u0026ndash;24,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.2 (5362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.9 (29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.3 (5333)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.5 (6552)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.9 (4187)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e29.8 (2365)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25,000\u0026ndash;49,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.3 (7076)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.5 (61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.3 (7015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35.7 (8826)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34.4 (5782)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e38.3 (3044)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50,000\u0026ndash;74,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.7 (2421)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.7 (34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.7 (2387)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.3 (3537)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.4 (2590)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.9 (947)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75,000\u0026ndash;99,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.0 (942)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.2 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.9 (927)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.9 (1470)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.7 (1134)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.2 (336)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100,000-124,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.3 (440)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.3 (434)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.1 (762)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.6 (601)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.0 (161)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e125,000-149,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6 (122)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.4 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6 (114)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.9 (234)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.2 (196)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.5 (38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e150,000-174,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 (99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5 (98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.7 (173)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9 (145)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.4 (28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e175,000-199,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3 (60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3 (59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.4 (93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5 (78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2 (15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200,000 or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 (91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.6 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5 (88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8 (192)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.0 (167)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.3 (25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.7 (1264)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.7 (1258)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.4 (1582)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.4 (1068)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.5 (514)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*NB: Lateral Flow Testing (LFT)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSurvey 1\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003eRQ1a. Frequency of mask wearing and social distancing\u003c/h2\u003e \u003cp\u003eOf 20,488 participants who received one or two doses of the COVID-19 vaccine, 99% (20289) completed two doses. The majority of the respondents reported that they would wear a face mask in public indoor places (88.5%) and maintain a 1\u0026thinsp;+\u0026thinsp;metre distance (86.8%) all or most of the time, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eReported levels of use of protective behaviour among participants with two doses of COVID-19 vaccine.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponse options\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI wear a face mask in public indoor places (n\u0026thinsp;=\u0026thinsp;20,135)\u003c/p\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eI keep a 1\u0026thinsp;+\u0026thinsp;metre distance from people I don\u0026rsquo;t live with (n\u0026thinsp;=\u0026thinsp;20,057)\u003c/p\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.1 (218)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5 (91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRarely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.1 (413)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.0 (400)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSometimes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.4 (1685)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.7 (2147)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMost of the time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.7 (6375)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.2 (9870)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll of the time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.8 (11444)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.6 (7549)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e here]\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003eRQ1b. Changes in reported frequency of mask wearing and social distancing post-vaccination\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eAlthough the majority of participants reported no change following vaccination for wearing a face mask, social distancing, visiting public indoor and outdoor places and using public transport, there was still a proportion of participants reporting changes in their behaviour. Specifically, 48.3% participants reported meeting with friends or family more frequently, while 38.3% participants reported increasing the frequency of visiting indoor places and 27.8% increasing the frequency of visiting outdoor places. Conversely, 14.5% reported wearing a face mask less frequently and 16.1% reported maintaining social distance less frequently (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges in mask wearing and social distancing after two doses of COVID-19 vaccine\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess frequently\u003c/p\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMore frequently\u003c/p\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo change\u003c/p\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWearing a face mask in public indoor spaces (n\u0026thinsp;=\u0026thinsp;20,127)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.5 (2912)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.0 (606)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82.5 (16609)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaintaining a 1m\u0026thinsp;+\u0026thinsp;distance from people you don\u0026rsquo;t live with (n\u0026thinsp;=\u0026thinsp;20,020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.1 (3231)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.1 (1027)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.7 (15762)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeeting friends or family you don\u0026rsquo;t live with, either at your home or their home (n\u0026thinsp;=\u0026thinsp;20,035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.7 (748)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.3 (9681)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.9 (9606)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisiting public indoor places (e.g. restaurant, caf\u0026eacute;, cinema) with people you don\u0026rsquo;t live with (n\u0026thinsp;=\u0026thinsp;19,784)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.7 (1123)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.3 (7584)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.0 (11077)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisiting public outdoor places (e.g. parks) with people you don\u0026rsquo;t live with (n\u0026thinsp;=\u0026thinsp;19568)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.9 (761)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.8 (5431)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e68.4 (13376)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUsing public transport (n\u0026thinsp;=\u0026thinsp;17,990)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.8 (1037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.3 (2566)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80.0 (14387)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e here]\u003c/p\u003e \u003cp\u003eWomen were more likely than men to wear masks all or most of the time (OR 1.43 [1.28, 1.59], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and keep a 1\u0026thinsp;+\u0026thinsp;metre distance from others all or most of the time (OR 1.16 [1.05, 1.30], p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Being white decreased the odds of keeping a 1\u0026thinsp;+\u0026thinsp;metre distance from others all or most of the time (OR 0.73 [0.54, 0.98], p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Participants older than 40 years were more likely than those younger than 30 years to keep a 1\u0026thinsp;+\u0026thinsp;metre distance from others all or most of the time, and these odds were higher as age increased (40\u0026ndash;49 years: OR 1.68 [1.15, 2.46], p\u0026thinsp;\u0026gt;\u0026thinsp;0.01; 50\u0026ndash;59 years: OR 1.77 [1.28, 2.46], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; 60\u0026thinsp;+\u0026thinsp;years: OR 2.13 [1.56, 2.91], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Those with an income\u0026thinsp;\u0026gt;\u0026thinsp;50,000GBP compared to \u0026lt;\u0026thinsp;25,000 were less likely to keep a 1\u0026thinsp;+\u0026thinsp;metre distance from others all or most of the time (OR 0.73 [0.64, 0.84], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Participants who received an NHS risk letter were more likely to keep a 1\u0026thinsp;+\u0026thinsp;metre distance from others all or most of the time (OR 1.78 [1.49, 2.12], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eRQ 1c. COM-B influences on mask wearing and social distancing post-vaccination\u003c/h2\u003e \u003cp\u003eOverall, results from the logistic regression models indicated that all COM-B predictor variables significantly contributed to wearing a face mask in public indoor spaces (model 1) and keeping a 1\u0026thinsp;+\u0026thinsp;metre distance all or most of the time (model 2), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e8\u003c/span\u003e. For both models, the Hosmer and Lemeshow goodness of fit test was not significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) indicating they were correctly specified. Additionally, the Cox and Snell was 0.092 and 0.100 for models 1 and 2, respectively; and the Nagelkerke R squared was 0.179 and 0.186 for models 1 and 2, respectively indicating that approx. 20% of the variance was accounted for in each of the models. Specifically:\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eMask wearing\u003c/h2\u003e \u003cp\u003eThe estimated adjusted odds ratio for the COM-B domain of automatic motivation showed an increase of 2.20 times for mask wearing for every unit of increase in participants\u0026rsquo; reported agreement score (aOR\u0026thinsp;=\u0026thinsp;2.20, 95% CI 2.02\u0026ndash;2.39); for social opportunity an increase of 1.7 times the odds (aOR\u0026thinsp;=\u0026thinsp;1.70, 95% CI 1.61\u0026ndash;1.79); and for psychological capability an increase of 1.3 times the odds (aOR\u0026thinsp;=\u0026thinsp;1.31, 95% CI 1.23\u0026ndash;1.39). In contrast, the estimated odds ratio for reflective motivation showed a decrease in the odds of about 0.6 times (aOR\u0026thinsp;=\u0026thinsp;0.58, 95% CI 0.53\u0026ndash;0.63) for mask wearing for every unit of increase in participants\u0026rsquo; reported agreement score. Essentially this findings suggests that people who had higher scores on reflective motivation, indicating they thought they could no longer catch or pass on COVID-19 post-vaccination, were at decreased odds of wearing a face mask.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eSocial distancing\u003c/h2\u003e \u003cp\u003eThe estimated odds ratio for the COM-B domain of automatic motivation for social distancing showed an increase of 2.5 times for every unit of increase in participants\u0026rsquo; reported agreement score (aOR\u0026thinsp;=\u0026thinsp;2.46, 95% CI 2.27\u0026ndash;2.67),; for social opportunity an increase of 1.8 times the odds (aOR\u0026thinsp;=\u0026thinsp;1.77, 95% CI 1.68\u0026ndash;1.87); and for psychological capability an increase of 1.3 times the odds (aOR\u0026thinsp;=\u0026thinsp;1.29, 95% CI 1.22\u0026ndash;1.37). In contrast, the estimated odds ratio for reflective motivation showed a decrease in the odds of 0.7 times (aOR\u0026thinsp;=\u0026thinsp;0.74, 95% CI 0.683, 0.81). A high reflective motivation score for these items would suggest thinking that one can no longer catch or pass on COVID-19 post-vaccination or that the risks of COVID-19 are exaggerated.\u003c/p\u003e \u003cp\u003eAll results for both mask wearing and social distancing per COM-B domain are presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable logistic regression results for face mask wearing and social distancing (survey 1) among those with two doses of COVID-19 vaccine (n\u0026thinsp;=\u0026thinsp;18,873)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWearing of face mask in\u003c/p\u003e \u003cp\u003epublic indoor spaces\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKeeping a 1\u0026thinsp;+\u0026thinsp;metre distance from others\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlways/Most of the time\u003c/p\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAlways/Most of the time\u003c/p\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eReflective motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58*** (0.53, 0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.74*** (0.683, 0.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAutomatic motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.20*** (2.02, 2.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.46*** (2.27, 2.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSocial opportunity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.70*** (1.61, 1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.77*** (1.68, 1.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003ePsychological capability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.31*** (1.23, 1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.29*** (1.22, 1.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u0026ndash;39 (vs\u0026thinsp;\u0026lt;\u0026thinsp;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.54 (0.97, 2.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.19 (0.80, 1.76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u0026ndash;49 (vs\u0026thinsp;\u0026lt;\u0026thinsp;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74 (0.50, 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.68** (1.15, 2.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u0026ndash;59 (vs\u0026thinsp;\u0026lt;\u0026thinsp;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04 (0.73, 1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.77*** (1.28, 2.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60+ (\u0026lt;\u0026thinsp;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.48* (1.05, 2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.13*** (1.56, 2.91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEthnic Group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWhite (vs. Non-White)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14 (0.87, 1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.73* (0.54, 0.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCombined Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25,000\u0026ndash;49,999 (vs. 0\u0026ndash;24,999)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.15* (1.02, 1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.01 (0.90, 1.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;50,000 (vs. 0\u0026ndash;24,999)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11 (0.97, 1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.73*** (0.64, 0.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale (vs. Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70*** (0.63, 0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.856** (0.77, 0.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eReceived an NHS risk letter\u003c/p\u003e \u003cp\u003e(vs. Did not receive an NHS risk letter)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07 (0.91, 1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.78*** (1.49, 2.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e*\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e**\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003csup\u003e***\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eReference category: Sometimes/Rarely/Never\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eWearing of face mask Cox and Snell 0.092, Nagelkerke 0.179, Hosmer and Lemeshow p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eKeeping a 1\u0026thinsp;+\u0026thinsp;metre distance Cox and Snell 0.100, Nagelkerke 0.186, Hosmer and Lemeshow p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e here]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eSurvey 2\u003c/h2\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003eRQ2a. Frequency of lateral flow testing\u003c/h2\u003e \u003cp\u003eOf 26,613 respondents, 32.1% had never done an LFT. Of the 67.9% who had done an LFT, 50.4% tested routinely, while the remaining 49.6% tested non-routinely.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eRQ2b. Non-routine testing: Reasons for testing and understanding the test result\u003c/h2\u003e \u003cp\u003eAmong those who tested non-routinely, the most frequently reported reason or occasion for testing was before visiting friends and family (40.2%). In contrast, the least cited reasons for testing included personal health or illness-related issues\u0026mdash;16.7% when feeling poorly, 12.9% because of having been in contact with someone who might have COVID-19, and 10.8% because of having symptoms that might be COVID-19. An even smaller minority tested for other reasons such as travel and getting into venues (see Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eReasons for testing among those who do not routinely take a LFT (n\u0026thinsp;=\u0026thinsp;8,953)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003e\u003cem\u003e% (n)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBefore visiting friends or relatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.2 (3602)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.8 (5351)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTo get into a venue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.9 (443)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.1 (8510)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhen I\u0026rsquo;m feeling poorly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.7 (1491)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.3 (7462)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBecause I have symptoms that might be Covid-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.8 (968)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.2 (7985)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBecause I\u0026rsquo;m required to for work/education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.4 (664)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.6 (8289)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSo that I can travel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.5 (585)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.5 (8368)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBecause someone told me to\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.2 (825)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.8 (8128)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBecause I\u0026rsquo;ve been in contact with someone I think might have Covid-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.9 (1156)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.1 (7797)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHad other reasons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.8 (1684)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e here]\u003c/p\u003e \u003cp\u003eMost people thought that a positive test meant they probably had COVID-19 (76.2%) with only a minority thinking a positive test definitely indicated COVID-19 infection (20.4%). The majority thought that a positive test meant they could definitely or probably infect others (97.3%).\u003c/p\u003e \u003cp\u003e \u003cem\u003eRQ2c. Routine testing.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThose who tested routinely were more likely to think that a positive test needed to be followed up with a PCR test than those who did not test routinely (90.7% vs. 81.3%). The majority thought that if they tested positive they definitely needed to self-isolate (80.3%) and most thought that their household contacts would need to self-isolate (61.6%). Those who regularly tested were more likely than those who did not regularly test to think that positive tests needed to be reported (92.6% vs. 81.1%). A summary of these results as well significant differences in the interpretation of LFT results between those who routinely and do not routinely test are shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in interpretation of LFT results among those who routinely and do not routinely take a LFT\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDefinitely don\u0026rsquo;t have COVID-19\u003c/p\u003e \u003cp\u003e% (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProbably don\u0026rsquo;t have COVID-19\u003c/p\u003e \u003cp\u003e% (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMay still have COVID-19\u003c/p\u003e \u003cp\u003e% (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e \u003cp\u003e% (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eChi-square (c\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoutinely have LFT (n\u0026thinsp;=\u0026thinsp;9059)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.1 (635)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.5 (6368)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.6 (1830)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8 (68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ec\u003csup\u003e2\u003c/sup\u003e(3)\u0026thinsp;=\u0026thinsp;154.556, p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo not routinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8901)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.1 (549)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79.3 (7181)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.2 (1288)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5 (41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eDefinitely not\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e% (n)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eProbably not\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e% (n)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eDon\u0026rsquo;t know\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e% (n)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eProbably\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e% (n)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eDefinitely\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e% (n)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo you think you could have a negative test result today from a lateral flow test but a positive test result tomorrow?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoutinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;9066)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1 (98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.7 (425)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.9 (716)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.5 (3309)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e49.8 (4518)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ec\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;59.861, p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo not routinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8898)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 (122)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.6 (494)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.9 (882)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.5 (3423)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.7 (3977)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIf you get a negative result from a lateral flow test,\u003c/p\u003e \u003cp\u003eit means:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIt\u0026rsquo;s safe to mix with people from outside your household\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoutinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8990)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.3 (475)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.1 (637)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.4 (218)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67.8 (6098)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.4 (1562)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ec\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;73.905, p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo not routinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2 (369)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.8 (776)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.8 (334)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68.5 (6031)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.8 (1300)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI need to get a PCR test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoutinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8549)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.4 (3706)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.3 (3960)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.8 (240)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.1 (179)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.4 (464)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ec\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;517.788, p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo not routinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8297)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.3 (2600)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.2 (4168)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.4 (615)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.1 (422)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.9 (492)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI need to report my test result\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoutinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8819)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.0 (969)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.5 (660)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.6 (321)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.3 (733)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e69.6 (6136)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ec\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;517.788, p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo not routinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8489)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.5 (1657)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.9 (1261)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.4 (713)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.5 (888)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.8 (3970)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIf I test positive on LFT:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eI\u0026rsquo;m infected with Covid-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoutinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8709)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6 (52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6 (49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7 (152)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.2 (6640)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.9 (1816)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ec\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;15.045, p\u0026thinsp;=\u0026thinsp;.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo not routinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8487)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3 (194)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.1 (6456)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.0 (1698)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eI might infect others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoutinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8680)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 (41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3 (27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5 (131)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59.0 (5122)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38.7 (3359)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ec\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;16.921, p\u0026thinsp;=\u0026thinsp;.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo not routinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8427)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7 (58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6 (48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.8 (149)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.2 (5073)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.8 (3099)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eI need to get a PCR test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoutinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8821)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8 (71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3 (204)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.4 (475)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90.7 (8000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ec\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;327.444, p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo not routinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8389)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2 (97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.8 (147)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.4 (455)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.4 (873)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.3 (6817)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eI need to self-isolate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoutinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8823)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5 (129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.6 (1200)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.6 (7373)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ec\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;122.234, p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo not routinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8495)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0 (86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3 (194)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.8 (1597)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e77.0 (6544)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOthers who live with me will need to self-isolate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoutinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8641)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3 (196)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.3 (461)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.0 (516)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.0 (1817)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e65.4 (5651)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ec\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;114.960, p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo not routinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8262)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7 (224)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.5 (539)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.4 (693)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.8 (2045)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57.6 (4761)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eI need to report my test result\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoutinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8821)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6 (54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.9 (167)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.1 (364)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e92.6 (8166)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ec\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;517.788, p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDo not routinely have LFT\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8456)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8 (152)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1 (181)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.2 (521)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.8 (744)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.1 (6858)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e6\u003c/span\u003e here]\u003c/p\u003e \u003cp\u003eOverall, only a small minority of participants thought that a negative LFT test meant that they definitely did not have COVID-19 (6.6%) with 92.8% thinking they \u0026lsquo;probably did not have COVID-19\u0026rsquo; or \u0026lsquo;may still have COVID-19\u0026rsquo;. Most people thought that a negative LFT result today could definitely or probably turn positive the next day (84.8%). The great majority thought that a negative test meant it is probably safe to mix with people from outside their households (70.9%). Those who tested routinely were more likely to think that they do not need to follow up a negative test with a PCR test than those who did not test routinely (43.4% vs. 31.3%). Those who tested routinely were also more likely to think that they needed to report their negative test result compared to those who did not test routinely (69.6% vs 46.8%).\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eRQ2d. Non-testing: Influences on testing \u0026ndash; COM-B factors\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e7\u003c/span\u003e depicts the reasons reported by those who have never taken an LFT categorised into capability, opportunity, and motivational factors. Participants\u0026rsquo; responses indicated that the highest level of agreement (mean M\u0026thinsp;=\u0026thinsp;4.3, SD\u0026thinsp;=\u0026thinsp;0.97) was obtained for the statement 'I have not needed to test\u0026rsquo; (Social opportunity).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean and SDs of reasons for never having taken a LFT\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnswered Definitely\u003c/p\u003e \u003cp\u003e% (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAnswered Probably\u003c/p\u003e \u003cp\u003e% (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAnswered Don\u0026rsquo;t know\u003c/p\u003e \u003cp\u003e% (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAnswered Probably not\u003c/p\u003e \u003cp\u003e% (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAnswered Definitely not\u003c/p\u003e \u003cp\u003e% (n)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCapability Factor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI don\u0026rsquo;t know where to get tested or where to get a hold of tests\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6351)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.02 (1.153)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.1 (262)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.9 (564)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.2 (1030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.7 (1695)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.1 (2801)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOpportunity Factor (social)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI have not needed to\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;8294)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.33 (0.966)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.3 (4588)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.9 (2642)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.9 (653)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7 (57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.3 (354)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOpportunity Factor (physical)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI can\u0026rsquo;t afford to self-isolate for practical or financial reasons\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6261)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.64 (0.916)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.7 (108)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.6 (163)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.3 (767)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.6 (1538)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e58.9 (3685)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMotivation Factors (reflective)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCronbach\u0026rsquo;s Alpha\u0026thinsp;=\u0026thinsp;0.815\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI don\u0026rsquo;t believe it is accurate\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6325)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.41 (1.022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3 (207)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.3 (528)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.7 (2324)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.7 (1876)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.0 (1390)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI don\u0026rsquo;t want to have to report my test result\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6253)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.78 (0.955)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 (87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4 (148)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.4 (1215)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.0 (1686)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e49.8 (3117)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI don\u0026rsquo;t want to or am unable to self-isolate\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6271)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.74 (0.955)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 (92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.7 (233)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.1 (1011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.0 (1570)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53.7 (3365)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI don\u0026rsquo;t believe in testing\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6263)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.49 (0.835)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.7 (104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7 (45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.3 (644)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.4 (1218)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e67.9 (4252)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI don\u0026rsquo;t think Covid-19 poses a risk to me\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6281)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.57 (0.914)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8 (113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.8 (176)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.3 (646)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.9 (1310)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64.3 (4036)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u0026rsquo;m vaccinated so I can\u0026rsquo;t catch Covid-19\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6356)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.70 (0.902)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 (93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5 (156)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.0 (889)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.4 (1805)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53.7 (3413)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMotivation Factors (automatic)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIt is unpleasant or uncomfortable\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.69 (1.080)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5 (283)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.6 (985)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.0 (2712)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.4 (1160)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.6 (1172)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIt\u0026rsquo;s a hassle\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6290)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.36 1.058)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2(137)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.0 (628)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.4 (2352)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.5 (1415)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.9 (1758)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003e*Responses: Definitely, Probably, Don\u0026rsquo;t know, Probably not, Definitely not\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e7\u003c/span\u003e here]\u003c/p\u003e \u003cp\u003eConversely, participants\u0026rsquo; low mean scores for the statements which were categorised as \u0026lsquo;reflective motivation\u0026rsquo; statements, which mostly conveyed negative meanings (e.g. \u0026lsquo;I don\u0026rsquo;t think Covid-19 poses a risk to me\u0026rsquo;), indicated that participants did not agree with these statements. The lowest mean score (denoting a disagreement) was found for the statement \u0026lsquo;I don\u0026rsquo;t believe in testing\u0026rsquo; (M\u0026thinsp;=\u0026thinsp;1.49, SD\u0026thinsp;=\u0026thinsp;0.84) signifying that the majority of participants did believe in testing, despite never having done a LFT.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results of our study indicate that a significant portion of fully vaccinated individuals maintained high adherence to wearing face masks in public indoor spaces (88.5% of the sample) and practicing social distancing (keeping at least 1 meter from others) (86.8% of the sample) most of the time. At the time of the data collection, there was no legal requirement in England and Wales to wear a face mask or maintain social distancing, with only general government advice that people should continue to wear a face mask and maintain a social distance considering the risks of close contact with others, particularly those who were clinically extremely vulnerable or not yet fully vaccinated [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. It is noteworthy that while some participants reported minor changes in the frequency of mask-wearing and social distancing after vaccination, the majority reported no change in these behaviors. In contrast, a substantial portion of respondents (32.1% of the sample) had never used a lateral flow test (LFT), a percentage that appears considerably high, especially considering that the study was conducted during the peak of the pandemic when LFTs were widely available and often free or low-cost for asymptomatic testing. However, among those who had used LFTs, half of them (50.4%) reported testing regularly.\u003c/p\u003e \u003cp\u003eHigh level of adherence for face mask wearing is consistent with other UK studies which were conducted at later stages of the pandemic documenting that the overall levels of adherence were relatively high throughout the pandemic until the government mandate ended. A cross-sectional study investigating adherence to PPBs, including face mask wearing over the course of the pandemic, found that engagement with protective behaviours increased at the start of the pandemic and remained high throughout and that the greatest variations in behaviour reflected changes to Government guidance [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Similarly, another study found that adherence to PPBs ranged between 50\u0026ndash;95%, with higher adherence during the period of stricter government measures and with the highest level of adherence for wearing masks indoors [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe reported level of adherence to social distancing in this study is notably higher compared to findings in other studies, where adherence rates ranged from as low as 31% [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] to 70% [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Conversely, in a separate study, non-adherence, whether intentional or unintentional, was reported at a much higher rate of 92.8% [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], though we noted the smaller sample size of that particular study and that follow up analyses showed that the odds of not adhering to rules increased if a participant was not identified as highly vulnerable to COVID-19 [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In comparison, the majority of participants in this study were aged 60 years and above and had received two doses of the vaccine indicating a specific demographic represented in this research. The variation in age distribution between those who received one versus two doses of the vaccine can be attributed to the initial vaccination campaign's emphasis on prioritising older adults due to elevated risk of infection and severe illness. This likely contributed to a heightened awareness of health precautions among older adults during the COVID-19 pandemic. This is also in line with other studies in the UK which show that being less vulnerable and less worried about COVID-19 increased the odds of non-adherence to social distancing and isolation. [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] This, to a degree, also reflects the effectiveness of COVID-19 risk communication targeted at the vulnerable population, particularly the older population.\u003c/p\u003e \u003cp\u003eIn relation to changes in reported compliance for mask wearing and social distancing, our finding that the majority reported no change in behaviour is in line with the findings in the COVID-19 Social Study which comprised of 70,000 adults in the UK and did not yield any significant differences in compliance with COVID-19 measures between those who were vaccinated and those non-vaccinated [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. A smaller study in the UK also shows similar findings of no significant differences in decrease of PBBs among the fully, partially, and non-vaccinated [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003eIdentified influences on face mask wearing and social distancing post-vaccination\u003c/h2\u003e \u003cp\u003eAfter adjusting for age, sex, income, ethnicity, and receipt of NHS risk letter, capability, opportunity, and motivation factors were associated with higher compliance to mask wearing and social distancing [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. In relation to automatic motivation which was the strongest predictor for both mask wearing and social distancing, this finding is in line with other studies which reveal that automatic motivation factors such as habit and fear are associated with increased compliance to protective behaviours [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Associations between these PPBs and social opportunity factors have also been previously documented. In several studies, adherence to social distancing decreased when one had less control over others\u0026rsquo; distancing or when coming in contact with others was unavoidable [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Another study in the US showed that the perceived social norm was a predictor of mask wearing behaviour. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] Finally, capability factors such as having access to COVID-19 information and being knowledgeable about the threat of COVID-19 have also been shown to increase the likelihood of adherence to public health measures [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe reflective motivation factor assessed risk perception post vaccination in this study - specifically, agreement with the statement that COVID-19 poses low to no risk after vaccination - signifying that participants did not think that the risk of infection was lower post vaccination. This finding is consistent with existing evidence showing that perceived high risk to COVID-19 promotes vaccine uptake as a means of protection and risk aversion [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e], and it is therefore, possible that the same risk aversion could promote PPBs irrespective of vaccination status [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Conversely, being less worried about COVID-19 decreases the likelihood of compliance to PPBs [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. In a similar vein, other reflective motivation factors such as self-efficacy and action planning have been shown to increase compliance to PPBs [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003eIdentified influences on LFT\u003c/h2\u003e \u003cp\u003eOf the 67.9% who had done an LFT, participants reported primarily using LFTs only before social gatherings with friends and family. They rarely tested themselves in response to any symptoms that may be COVID-19 or after potential exposure to COVID-19 and a very small proportion of our participants responded that they tested for work-related purposes or to travel. In contrast, in a study conducted in two English local authority areas, 60% of participants reported getting tested primarily for work-related reasons [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. This finding may be explained by the government\u0026rsquo;s advice at the time of the survey to take a PCR test for those experiencing symptoms. Furthermore, this finding highlights the importance of social relations and the sense of social responsibility towards others, which are fundamental human needs, especially during times of isolation. This is particularly relevant in the context of meeting friends and family from different households, which showed the most significant increase after vaccination in our study. This also emphasises the complex interplay between public health guidance, testing behaviours and the need to maintain social connections during these challenging times [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the context of interpreting test results, the key difference between individuals who test regularly being more inclined to report a positive test and self-isolate than those who do not test regularly, can be attributed to differences in their overall understanding of the disease and risk attitudes of each group. While there is a lack of specific studies exploring the association between COVID-19 testing behaviors and risk attitudes, existing research indicates that being risk-averse can serve a protective function. Risk-averse individuals tend to engage in more proactive health information seeking and a perception of utility of public health measures, such as adhering to lockdown protocols [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. Those in the habit of routine testing may exhibit a higher risk aversion, leading them to be more cautious and therefore, reporting a positive result and isolating promptly, thereby reducing the risk of spreading the virus to others. Conversely, individuals with a higher tolerance for risk might adopt a more relaxed approach even in the event of a positive test result, assuming that transmission might not necessarily occur. This leniency could result from their willingness to accept a certain level of risk or uncertainty in their daily activities.\u003c/p\u003e \u003cp\u003eAmong individuals who have never taken an LFT, the highest mean (agreement) score pertained to the social opportunity factor that they did not need to test indicating a perceived lack of need for testing. This finding coupled with high disagreement scores for negative statements about the utility and accuracy of testing (reflective motivation) suggest a likely absence of conditions such as work requirements, social interactions or contact with infected individuals that would necessitate the use of LFT rather than negative beliefs about the value of testing. Alternatively, this could also be attributed to a limited understanding about when to take the LFT test (psychological capability). This finding aligns with other research, where limited face-to-face interactions with others emerged as a common justification for not testing [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. Moreover, another study revealed that a prevalent reason for not engaging in LFTs, despite the recommended bi-weekly testing, was the belief that testing was only necessary after exposure to someone with COVID-19 [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003ePolicy implications\u003c/h2\u003e \u003cp\u003eWhile the COVID-19 is no longer classified as a public health emergency of international concern [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e], the findings of this study can be useful for future pandemic preparedness and critical response strategies. It is noteworthy that the findings of our study suggest that at a time when there were few restrictions in the UK, many participants reported still wearing a face mask and keeping the recommended distance. This indicates that adherence to these behaviours was mostly a personal decision, rather than merely a response to official guidance, to protect themselves and others around them [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. This is supported by studies conducted during the COVID-19 and influenza (e.g. H1N1 in 2009) pandemics which show that greater sense of social responsibility and the belief in protecting others promoted compliance to protective behaviours [\u003cspan additionalcitationids=\"CR80\" citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Similarly, LFTs which enable access to testing beyond healthcare settings were reportedly used by the majority of our participants. However, our results suggest that there was still a significant proportion of our participants (about a third of our sample) who had never used an LFT at a time when the pandemic was still ongoing and when LFTs were widely available - although not free for most people apart from those meeting eligibility criteria (i.e. being clinically vulnerable and working as a key worker).\u003c/p\u003e \u003cp\u003eBased on our findings, health communications and messaging campaigns in the UK are recommended to focus on shared responsibility and social consciousness principles since the population appears to relate and respond well to these [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. Importantly, given that the LFTs could also play an important part in the detection of other infectious diseases of epidemic potential and antimicrobial resistance [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], public health planning should also focus on increasing social opportunity by addressing systemic factors that influence LFT uptake for COVID-19 and other infectious respiratory diseases. It is important, however, to consider the ethical implications of any interventions especially in light of substantial evidence pointing to intervention-induced inequalities during the pandemic [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. Failing to address these ethical considerations may exacerbate existing disparities and disproportionately impact vulnerable populations, emphasising the need for a conscientious and equitable approach in implementing intervention strategies to ensure fair outcomes across diverse communities [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eRecommendations for intervention design\u003c/h2\u003e \u003cp\u003eTo generate recommendations for interventions to increase the uptake of mask wearing, social distancing, and LFT, we consulted the BCW matrix for intervention strategies that are likely to be effective in addressing the different types of behavioural influences. The BCW is a published matrix that pairs the COM-B to BCW interventions and policy options for intervention implementation [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. Factors found to be significantly associated with the target behaviours were mapped to Intervention Types (ITs) and then onto relevant policy options using the BCW matrix and generated descriptions as to how these could potentially be operationalised and delivered using frequently used Behaviour Change Techniques taxonomy BCTTv1 [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSignificant influences for mask wearing and social distancing were found to be associated with capability, social opportunity and motivation, with (automatic) motivation having the highest odds for uptake of mask wearing and social distancing. These factors could be targeted with a wide range of interventions such as education and persuasion, delivered via policy options such as communication, regulation, or environmental and social planning in a way that resonates with the community's values and concerns. For example, a tailored public health messaging campaign could include a series of posters or digital graphics conveying persuasive messages about the benefits of face masks or social distancing in protecting both oneself and others and encourage regular mask wearing and social distancing as a habit in public spaces. For testing, the primary COM-B domain underpinning lack of testing was social opportunity followed by psychological capability. Factors related to social opportunity can be targeted through interventions using modelling, environmental restructuring, and enablement. For example, public health (government or community) campaigns should aim to convey the importance of testing as a community-wide responsibility to curb the virus and can encourage regular testing through video advertisements featuring prominent public figures and/or healthcare professionals. A list of other potential intervention strategies and policy options as well as examples of how these could be delivered, in the form of behavior change techniques, are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCOM-B influences mapped to proposed interventions using the Behaviour Change Wheel\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBehaviour\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCOM-B factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eIntervention\u003c/p\u003e \u003cp\u003etypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003ePolicy options\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eExample Behaviour Change Techniques\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eExamples of how these could be designed and delivered\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMask wearing/\u003c/p\u003e \u003cp\u003eSocial distancing/\u003c/p\u003e \u003cp\u003eTesting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ePsychological\u003c/p\u003e \u003cp\u003eCapability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003cp\u003eEnablement\u003c/p\u003e \u003cp\u003ePersuasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eCommunications/marketing\u003c/p\u003e \u003cp\u003eGuidelines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e- Information about social and environmental consequences\u003c/p\u003e \u003cp\u003e- Information on health consequences\u003c/p\u003e \u003cp\u003e- Salience of consequences\u003c/p\u003e \u003cp\u003e- Action planning\u003c/p\u003e \u003cp\u003e- Credible source\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e-Raise awareness about the importance of minimising risk/stop virus transmission through the use of PPBs\u003c/p\u003e \u003cp\u003e-Raise awareness of importance of testing following contact with someone who had Covid-19\u003c/p\u003e\u003cp\u003e-Provide details of where to locate scientifically robust evidence about the benefits of mask wearing, social distancing and testing\u003c/p\u003e \u003cp\u003e- Community support, targeted media campaigns, apps, and websites to assist households, especially those with vulnerable people to establish new living arrangements and routines and to remember the guidance\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMask wearing/\u003c/p\u003e \u003cp\u003eSocial distancing/\u003c/p\u003e \u003cp\u003eTesting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eReflective\u003c/p\u003e \u003cp\u003eMotivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003cp\u003ePersuasion\u003c/p\u003e \u003cp\u003eModelling\u003c/p\u003e \u003cp\u003eEnablement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eCommunications/marketing\u003c/p\u003e \u003cp\u003eGuidelines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e- Pros and cons\u003c/p\u003e \u003cp\u003e- Credible source\u003c/p\u003e \u003cp\u003e- Framing /reframing\u003c/p\u003e \u003cp\u003e- Information about health consequences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e- Address misleading informational sources about mask wearing, social distancing and testing accuracy (e.g., social media)\u003c/p\u003e \u003cp\u003e-Provide testimonials from medical experts about the importance of mask wearing, social distancing and testing\u003c/p\u003e \u003cp\u003e-Targeted ads and comms campaigns about the significance of testing and likely unwanted consequences before meeting vulnerable individuals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMask wearing/\u003c/p\u003e \u003cp\u003eSocial distancing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eAutomatic Motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003ePersuasion\u003c/p\u003e \u003cp\u003eModelling\u003c/p\u003e \u003cp\u003eIncentivisation/\u003c/p\u003e \u003cp\u003eCoercion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eCommunications/marketing\u003c/p\u003e \u003cp\u003eService provision\u003c/p\u003e \u003cp\u003eFiscal measures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e- Habit formation\u003c/p\u003e \u003cp\u003e-Information about consequences\u003c/p\u003e \u003cp\u003e- Anticipated regret,\u003c/p\u003e \u003cp\u003e- Social support (Emotional)\u003c/p\u003e \u003cp\u003e- Salience of consequences\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e- Prompt rehearsal and repetition of mask wearing and social distancing in public spaces (context) so that the context elicits the behaviour (e.g. prompt individuals before taking public transport, or offer free masks) so that it becomes a habit\u003c/p\u003e \u003cp\u003e-Testimonials from individuals at high risk about their experiences/fears\u003c/p\u003e \u003cp\u003e-Create an expectation of a fine if not adhering to government guidance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTesting/\u003c/p\u003e \u003cp\u003eMask wearing/\u003c/p\u003e \u003cp\u003eSocial distancing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eSocial\u003c/p\u003e \u003cp\u003eOpportunity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003ePersuasion\u003c/p\u003e \u003cp\u003eModelling\u003c/p\u003e \u003cp\u003eEnvironmental restructuring\u003c/p\u003e \u003cp\u003eEnablement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eService provision\u003c/p\u003e \u003cp\u003eGuidelines\u003c/p\u003e \u003cp\u003eRegulation\u003c/p\u003e \u003cp\u003eEnvironmental/\u003c/p\u003e \u003cp\u003esocial planning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e- Credible source\u003c/p\u003e \u003cp\u003e- Social support (Practical)\u003c/p\u003e \u003cp\u003e- Social comparison\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e- Workplaces (all public-facing industries) should provide testing programmes for their workers to increase uptake/make it an expectation\u003c/p\u003e \u003cp\u003e- Make it a pre-requisite for admission in certain settings like public transport, public places and healthcare settings\u003c/p\u003e \u003cp\u003e- Offer masks or LFTs in a variety of designated locations in the community (e.g. schools, hospitals)\u003c/p\u003e \u003cp\u003e- Community champions to model behaviour (e.g. testing, mask wearing)\u003c/p\u003e\u003cp\u003e- Community support, clear messaging and promotion of strong social identity and shared responsibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c13\" namest=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cp\u003e[insert Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e8\u003c/span\u003e here]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eStrengths of the study include the large sample size and the use of a theoretically-informed behavioural science framework to structure the questionnaire items and interpret the data. This allows for a systematic analysis and identification of influences on the behaviours of interest and to generate recommendations for future public health interventions. However, despite the large sample size, non-white ethnic groups were under-represented in this study and most participants were older adults (60+). It is also likely that participants may have been more self-aware of adherence to PPBs and responses may have been influenced by a degree of social-desirability bias. These limitations may have led to an overreporting of PPBs compared to the general population.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe findings of this study show that, overall, there is a high level of adherence to mask wearing and social distancing, despite fewer restrictions and high rates of vaccination. However, there is still a proportion of people (about 10%) who do not use these protective measures and a higher proportion of people who had never used the LFT (about 30%) to check themselves. After two doses of the vaccine, people reported visited friends and relatives more frequently compared to other activities and visiting family and friends was also the most reported reason for testing. Therefore, targeted interventions and public health initiatives fostering a sense of social responsibility and promoting safe social interactions can be effective in managing new COVID-19 variants and new viruses in future public health emergencies.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll methods were carried out in accordance with relevant guidelines and regulations. The Virus Watch Study was approved by the Hampstead NHS Health Research Authority Ethics Committee (Ethics approval number 20/HRA/2320). Informed consent was obtained from all participants involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e: not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish declaration\u003c/strong\u003e: not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials –\u0026nbsp;\u003c/strong\u003eAll materials used are included in the Appendices andthe data presented in this study are available upon reasonable request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding –\u0026nbsp;\u003c/strong\u003eThis study has received funding from the following funders:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eUKRI Medical Research Council Grant: MC_PC 19070 \u0026amp; MR/V028375/1\u003c/li\u003e\n \u003cli\u003eDepartment of Health \u0026amp; Social Care, UK\u003c/li\u003e\n \u003cli\u003eEuropean Commission Horizon Health 2021 Grant: 101046314\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e – Conceptualisation, SM, FL, SB, RA, AH, CM, VA; Design, SM, FL, SB, AH, RA, CM, VA, Funding acquisition, SM, FL, SB, RA, AH; Methodology, SM, FL, SB, AH, RA, CM, VA; Data curation, MO; Formal analysis, MO, CM, VA; Investigation and Interpretation, MO, VA, CM; Writing – original draft, OM, VA; Writing – review \u0026amp; editing, VA, OM, CM, FL, SM, SB, AH, RA. All authors have approved the submitted version of the study\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. Considerations for implementing and adjusting public health and social measures in the context of COVID-19: interim guidance 14 June 2021. World Health Organization; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Overview of public health and social measures in the context of COVID-19: interim guidance, 18 May 2020. World Health Organization; 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMercer TR, Salit M. Testing at scale during the COVID-19 pandemic. Nat Rev Genet. 2021;22(7):415\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWest R, et al. Applying principles of behaviour change to reduce SARS-CoV-2 transmission. 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Vaccines (Basel), 2022. 10(6).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePedersen MJ, Favero N. Social Distancing during the COVID-19 Pandemic: Who Are the Present and Future Noncompliers? Public Adm Rev. 2020;80(5):805\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHagger MS, et al. Predicting Social Distancing Intention and Behavior During the COVID-19 Pandemic: An Integrated Social Cognition Model. Ann Behav Med. 2020;54(10):713\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoroiu A, et al. Barriers and facilitators of adherence to social distancing recommendations during COVID-19 among a large international sample of adults. PLoS ONE. 2020;15(10):e0239795.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoran C, et al. Predictors of attitudes and adherence to COVID-19 public health guidelines in Western countries: a rapid review of the emerging literature. J Public Health (Oxf). 2021;43(4):739\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetrocchi S et al. The interplay between risk and protective factors during the initial height of the COVID-19 crisis in Italy: The role of risk aversion and intolerance of ambiguity on distress. Curr Psychol, 2021: pp. 1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHudson A, Montelpare WJ. Predictors of Vaccine Hesitancy: Implications for COVID-19 Public Health Messaging. Int J Environ Res Public Health, 2021. 18(15).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHamilton K, et al. Application of the Health Action Process Approach to Social Distancing Behavior During COVID-19. Appl Psychol Health Well Being. 2020;12(4):1244\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeale H, et al. 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W.H.O., \u003cem\u003eWHO chief declares end to COVID-19 as a global health emergency\u003c/em\u003e, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://news.un.org/en/story/2023/05/1136367\u003c/span\u003e\u003cspan address=\"https://news.un.org/en/story/2023/05/1136367\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. May 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJalloh MF et al. Behaviour adoption approaches during public health emergencies: implications for the COVID-19 pandemic and beyond. BMJ Glob Health, 2021. 6(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWarnock-Parkes E, Thew GR, Clark DM. Belief in Protecting Others and Social Perceptions of Face Mask Wearing Were Associated With Frequent Mask Use in the Early Stages of the COVID Pandemic in the UK. Front Psychol. 2021;12:680552.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavis MD, et al. 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BMC Health Serv Res. 2014;14(Suppl 2):O9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1472-6963-14-S2-O9\u003c/span\u003e\u003cspan address=\"10.1186/1472-6963-14-S2-O9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. eCollection 2014.\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"personal protective behaviors, public health interventions, pandemic, rapid lateral flow tests, lateral flow device (LFD), behavioral science","lastPublishedDoi":"10.21203/rs.3.rs-6369060/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6369060/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePersonal protective behaviours (PPBs) played a crucial role in limiting infection spread during the COVID-19 pandemic, yet adherence varied across communities. Understanding the factors influencing adherence is important, as PPBs will remain critical in future pandemics. Using behavioural science, we investigated the influences on adherence to PPBs, focusing on face mask wearing, social distancing, and lateral flow testing (LFT).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo online surveys were conducted in July and August 2021 in England and Wales (\u003cem\u003eN\u003c/em\u003e = 20,488 (survey 1) and \u003cem\u003eN \u003c/em\u003e= 26,613 (survey 2)). Survey questions were informed by the Capability, Opportunity, Motivation model of Behaviour (COM-B). Multivariate models examined associations between behavioural influences and adherence to PPBs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMost respondents reported wearing a face mask in public indoor places (88.5%) and maintaining a 1+ metre distance (86.8%) all or most of the time. After two doses of COVID-19 vaccine, adherence declined with 48.3% reporting meeting friends or family and 38.3% visiting indoor places more frequently. Motivation, Opportunity and Capability factors were significantly associated with increased odds of wearing a face mask and social distancing (p \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003eAmong those using LFTs (68% of the sample), 50.4% engaged in routine testing, while 55.3% of non-users cited a perceived lack of necessity for testing. Routine testing was significantly associated with accurate interpretation of test results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite reduced restrictions and high vaccination rates, overall adherence to PPBs remained high. Behavioural influences played a significant role in PPB use. These findings can inform tailored public health interventions and support future community-level emergency preparedness.\u003c/p\u003e","manuscriptTitle":"Adherence to mask wearing and social distancing and use of lateral flow tests during the COVID19 pandemic in England and Wales based on the Virus Watch community cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-28 10:36:04","doi":"10.21203/rs.3.rs-6369060/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-13T07:27:01+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-07T02:28:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"137092670371845048476046751381816987972","date":"2025-10-03T10:17:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-20T16:52:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"254817762938773853276533651053055963031","date":"2025-07-22T07:50:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-02T15:15:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"201746939210054893200720906180070489164","date":"2025-05-27T08:26:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"210957203486075964336827987783438668450","date":"2025-05-23T13:15:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-23T12:11:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-11T13:38:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-07T11:03:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2025-05-07T11:02:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"31ce9269-395b-4f0b-8a3c-96f9df981124","owner":[],"postedDate":"May 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-19T17:02:40+00:00","versionOfRecord":{"articleIdentity":"rs-6369060","link":"https://doi.org/10.1186/s12982-026-01375-6","journal":{"identity":"discover-public-health","isVorOnly":false,"title":"Discover Public Health"},"publishedOn":"2026-01-17 16:28:32","publishedOnDateReadable":"January 17th, 2026"},"versionCreatedAt":"2025-05-28 10:36:04","video":"","vorDoi":"10.1186/s12982-026-01375-6","vorDoiUrl":"https://doi.org/10.1186/s12982-026-01375-6","workflowStages":[]},"version":"v1","identity":"rs-6369060","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6369060","identity":"rs-6369060","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}