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LLM - Digital Humanities 16

ERROR: type should be string, got "https://doi.org/10.17269/s41997-021-00501-y\nCanadian Journal of Public Health (2021) 112:363–375 https://doi.org/10.17269/s41997-021-00501-y\nCanadian Journal of Public Health (2021) 112:363–375 SPECIAL SECTION ON COVID-19: QUANTITATIVE RESEARCH Abstract Objectives The effectiveness of public health interventions for mitigation of the COVID-19 pandemic depends on individual\nattitudes, compliance, and the level of support available to allow for compliance with these measures. The aim of this study was to\ndescribe attitudes and behaviours towards the Canadian COVID-19 public health response, and identify risk-modifying behav-\niours based on socio-demographic characteristics. g p\nMethods A cross-sectional online survey was administered in May 2020 to members of a paid panel representative of the\nCanadian population by age, gender, official language, and region of residence. A total of 4981 respondents provided responses\nfor indicators of self-reported risk perceptions, attitudes, and behaviours towards COVID-19 public health measures. Results More than 90% of respondents reported confidence in the ability to comply with a variety of public health measures. However, only 51% reported preparedness for illness in terms of expectation to work if sick or access to paid sick days. Risk\nperceptions, attitudes, and behaviours varied by demographic variables. Men, younger age groups, and those in the paid\nworkforce were less likely to consider public health measures to be effective, and had less confidence in their ability to comply. Approximately 80% of respondents reported that parents provided childcare and 52% reported that parents in the workforce\nprovided childcare while schools were closed. Methods A cross-sectional online survey was administered in May 2020 to members of a paid panel representative of the\nCanadian population by age, gender, official language, and region of residence. A total of 4981 respondents provided responses\nfor indicators of self-reported risk perceptions, attitudes, and behaviours towards COVID-19 public health measures. Results More than 90% of respondents reported confidence in the ability to comply with a variety of public health measures. However, only 51% reported preparedness for illness in terms of expectation to work if sick or access to paid sick days. Risk\ni\ni d\nd b h\ni\ni d b\nd\nhi\ni bl\nM\nd h\ni\nh\nid Methods A cross-sectional online survey was administered in May 2020 to members of a paid panel representative of the\nCanadian population by age, gender, official language, and region of residence. A total of 4981 respondents provided responses\nfor indicators of self-reported risk perceptions, attitudes, and behaviours towards COVID-19 public health measures. Abstract p\np\np\np\nResults More than 90% of respondents reported confidence in the ability to comply with a variety of public health measures. However, only 51% reported preparedness for illness in terms of expectation to work if sick or access to paid sick days. Risk\nperceptions, attitudes, and behaviours varied by demographic variables. Men, younger age groups, and those in the paid\nworkforce were less likely to consider public health measures to be effective, and had less confidence in their ability to comply. Approximately 80% of respondents reported that parents provided childcare and 52% reported that parents in the workforce\nprovided childcare while schools were closed. Conclusion Policies to help address issues of public adherence include targeted messaging for men and younger age groups,\nsocial supports for those who need to self-isolate, changes in workplace policies to discourage presenteeism, and provincially co-\nordinated masking and safe school policies. Socio-demographic disparities in knowledge, practices, and ability\nto comply with COVID-19 public health measures in Canada Amy L. Greer1,3 Received: 7 September 2020 /Accepted: 22 February 2021\n# The Author(s) 2021\n/ Published online: 24 March 2021 * Amy L. Greer\nagreer@uoguelph.ca; https://www.mathepilab.org * Amy L. Greer\nagreer@uoguelph.ca; https://www.mathepilab.org\n1\nDepartment of Population Medicine, University of Guelph,\nGuelph, Canada\n2\nMunk School of Global Affairs & Public Policy, University of\nToronto, Toronto, Canada\n3\nDalla Lana School of Public Health, University of Toronto,\nToronto, Canada 1\nDepartment of Population Medicine, University of Guelph,\nGuelph, Canada 2\nMunk School of Global Affairs & Public Policy, University of\nToronto, Toronto, Canada Résumé\nObj\nif 364 Can J Public Health (2021) 112:363–375 Résultats Plus de 90 % des répondants se sont dits certains de leur capacité de respecter de nombreuses mesures de santé\npublique. Par contre, 51 % seulement ont dit être préparés à respecter ces mesures s’ils attrapaient la maladie, c’est-à-dire pouvoir\ns’absenter du travail ou avoir droit à des congés de maladie payés. Les perceptions du risque, les attitudes et les comportements\nvariaient selon les caractéristiques démographiques. Les hommes, les jeunes et les personnes ayant un emploi rémunéré étaient\nmoins susceptibles de trouver les mesures de santé publique efficaces et moins sûrs de leur capacité de les respecter. Environ\n80 % des répondants ont indiqué que la garde des enfants était assurée par les parents, et 52 % ont indiqué que la garde des enfants\nquand les écoles étaient fermées était assurée par des parents ayant un emploi. Résultats Plus de 90 % des répondants se sont dits certains de leur capacité de respecter de nombreuses mesures de santé\npublique. Par contre, 51 % seulement ont dit être préparés à respecter ces mesures s’ils attrapaient la maladie, c’est-à-dire pouvoir\ns’absenter du travail ou avoir droit à des congés de maladie payés. Les perceptions du risque, les attitudes et les comportements\nvariaient selon les caractéristiques démographiques. Les hommes, les jeunes et les personnes ayant un emploi rémunéré étaient\nmoins susceptibles de trouver les mesures de santé publique efficaces et moins sûrs de leur capacité de les respecter. Environ\n80 % des répondants ont indiqué que la garde des enfants était assurée par les parents, et 52 % ont indiqué que la garde des enfants\nquand les écoles étaient fermées était assurée par des parents ayant un emploi. Conclusion Des messages ciblant les hommes et les jeunes, des soutiens sociaux aux personnes ayant besoin de\ns’isoler, des changements dans les politiques en milieu de travail pour dissuader le présentéisme, ainsi que des\npolitiques de port du masque et de sécurité à l’école coordonnées à l’échelle provinciale sont des mesures suscep-\ntibles d’atténuer les problèmes d’adhésion du public. Keywords COVID-19 . Attitude . Behaviour . Risk perception . Survey Keywords COVID-19 . Attitude . Behaviour . Risk perception . Survey Mots-clés COVID-19 . attitude . comportement . perception du risque . enquête Introduction public health measures. Thus, the objectives of this study are\nto (1) describe attitudes and behaviours towards the Canadian\nCOVID-19 public health response in May 2020, and\n(2) identify risk-modifying behaviours and resources to com-\nply with public health measures based on socio-demographic\nand household characteristics. This paper presents an initial\ndescriptive portrait of attitudes and perceptions among\nCanadians in the early stage of the pandemic to provide in-\nsights into improvements of programs and policies. The current coronavirus (COVID-19) pandemic represents a\nunique challenge for public health and health care systems. In\nthe absence of effective medical treatment options or a safe\nand effective vaccine, public health agencies have relied on\nnon-pharmaceutical interventions (NPIs) to mitigate transmis-\nsion of the virus. Physical distancing interventions act to re-\nduce the person-to-person contact rate in a population thereby\nreducing the likelihood of disease transmission. All Canadian\nprovinces and territories have instituted aggressive physical\ndistancing measures in response to the COVID-19 pandemic,\nincluding school closures, remote work, cancellation of mass\ngatherings, and the closure of all non-essential businesses. Résumé\nObj\nif Objectifs L’efficacité des mesures d’intervention en santé publique pour atténuer la pandémie de COVID-19 dépend des attitudes\nindividuelles, de la conformité, ainsi que du niveau d’aide disponible pour que les mesures soient respectées. Notre étude visait à\ndécrire les attitudes et les comportements à l’égard de la riposte de la santé publique canadienne à la COVID-19 et à cerner les\ncomportements modificateurs du risque d’après les caractéristiques sociodémographiques. Méthode Un sondage en ligne transversal a été administré en mai 2020 aux membres d’un comité rémunéré représentatif de\nl’âge, du sexe, des langues officielles et des régions de résidence de la population canadienne. En tout, 4 981 personnes ont fourni\ndes réponses à des questions indicatrices de leurs perceptions du risque, de leurs attitudes et de leurs comportements autodéclarés\nà l’égard des mesures de santé publique liées à la COVID-19. Objectifs L’efficacité des mesures d’intervention en santé publique pour atténuer la pandémie de COVID-19 dépend des attitudes\nindividuelles, de la conformité, ainsi que du niveau d’aide disponible pour que les mesures soient respectées. Notre étude visait à\ndécrire les attitudes et les comportements à l’égard de la riposte de la santé publique canadienne à la COVID-19 et à cerner les\ncomportements modificateurs du risque d’après les caractéristiques sociodémographiques. Objectifs L’efficacité des mesures d’intervention en santé publique pour atténuer la pandémie de COVID-19 dépend des attitudes\nindividuelles, de la conformité, ainsi que du niveau d’aide disponible pour que les mesures soient respectées. Notre étude visait à\ndécrire les attitudes et les comportements à l’égard de la riposte de la santé publique canadienne à la COVID-19 et à cerner les\ncomportements modificateurs du risque d’après les caractéristiques sociodémographiques. Méthode Un sondage en ligne transversal a été administré en mai 2020 aux membres d’un comité rémunéré représentatif de\nl’âge, du sexe, des langues officielles et des régions de résidence de la population canadienne. En tout, 4 981 personnes ont fourni Méthode Un sondage en ligne transversal a été administré en mai 2020 aux membres d’un comité rémunéré représentatif de\nl’âge, du sexe, des langues officielles et des régions de résidence de la population canadienne. En tout, 4 981 personnes ont fourni\ndes réponses à des questions indicatrices de leurs perceptions du risque, de leurs attitudes et de leurs comportements autodéclarés\nà l’égard des mesures de santé publique liées à la COVID-19. Data collection 2020) and posed questions about perceived risk Can J Public Health (2021) 112:363–375 365 of COVID-19 infection, as well as attitudes and behaviours\nregarding COVID-19 public health measures. Participants\nprovided information about their age, gender, province of res-\nidence, education level, employment status, household com-\nposition, household income, and the general size of their lo-\ncation of residence with options ranging from large city to\nrural. Participants were also asked whether they would be\nconsidered a priority risk group to receive the seasonal influ-\nenza vaccine as outlined by the Public Health Agency of\nCanada. The conditions meeting this criterion included chron-\nic respiratory disease, chronic heart disease, chronic kidney\ndisease, chronic liver disease, chronic neurological disease,\ndiabetes (all types), cancer, immunosuppression, dysfunction\nof the spleen, and/or BMI > 40 (National Advisory Committee\non Immunization (NACI) 2019). about attitudes toward COVID-19 public health measures. Chi-\nsquare analyses of individual contingency tables were conducted\nto further explore these data by respondent demographics and\nhousehold characteristics. The Bonferroni correction was applied\nfor each of the indicators of attitudes toward and ability to com-\nply with public health measures to account for multiple compar-\nisons within each measure. Therefore, a relationship was consid-\nered significant if the p-value was less than the corrected value\n(0.05/19 = 0.0026). Pairwise post hoc analyses with a Bonferroni\ncorrection were conducted for multi-level demographic and\nhousehold variables which showed significance in the chi-\nsquare analyses. q\ny\nLogistic regression models were developed to identify fac-\ntors associated with (1) mask use in the 24 hours prior to\nsurvey completion, (2) reporting direct contact with individ-\nuals outside of the respondent’s immediate household in the\n7 days prior to survey completion, and (3) reporting confi-\ndence in the ability to self-isolate with mild symptoms of\nCOVID-19. Univariable models were first assessed using a\nliberal p-value of less than 0.3 to determine eligibility for\ninclusion in the multivariable models. Variables included in\nthe initial full model for mask use included age, gender, risk\ngroup status, size of geographic region of residence, house-\nhold income, education level, employment status, household\ncomposition, and household size, as well as two indicators of\nperceived risk of COVID-19 to self and one indicator of\nperceived risk of transmission to others. Data collection Human behaviour is the main driver of respiratory disease\ntransmission and in the absence of a vaccine or other pharma-\nceutical interventions, mitigation requires large-scale behav-\niour change. As such, the effectiveness of public health inter-\nventions depends on the level of individual compliance and\nability to comply. Perceived risk due to COVID-19 and atti-\ntudes toward these measures have a large impact on the\nwillingness of people to make the behaviour changes\nnecessary for public health measures to be effective\n(Qazi et al. 2020). Perhaps more importantly, the ability\nto comply with public health measures such as self-\nisolation is dependent on an individual’s social and fi-\nnancial resources (Atchison et al. 2021). The study protocol was approved by the University of Guelph\nResearch Ethics Board (protocol #20-04-011) and the\nUniversity of Toronto Research Ethics Board (protocol\n#38251). The research company, Dynata, was contracted to\nconduct an electronic survey of Canadian adults between\nMay 7 and May 19, 2020. Participants were recruited from a\npanel of survey respondents and paid a nominal amount for\ncompleting the survey. Panelists who logged into their Dynata\naccount during the study period were directed to the survey if\nthey fit the quotas being targeted. Respondents provided in-\nformed consent after reading the study information by choos-\ning to continue to the survey questions. Representativeness of\nthe survey sample population was ensured by setting quotas\non age, gender, official language (English and French), and\nregion of residence (i.e., Atlantic, Quebec, Ontario, and West)\nbased on 2016 Canadian Census data (Statistics Canada\n2016a). Respondents could complete the survey in English\nor French. Enrollment into the survey within each stratum\nwas on a first-come, first-served basis. It is imperative that evidence be used to drive decision-\nmaking in order to provide the messaging and supports nec-\nessary to minimize transmission. It is important to identify\ngroups who are less likely to perceive COVID-19 as a risk,\nto perceive that public health measures are effective, and to\nhave the resources to comply, and more likely to engage in\nbehaviours associated with transmission of COVID-19. This\ninformation can be used to target messaging, develop policies,\nand provide supports to encourage uptake of the necessary The survey instrument was adapted from previous work\n(Jarvis et al. Data collection The initial full model\nassessing factors associated with engaging in an activity with\nnon-household contacts included respondents’ perceived ef-\nfectiveness of reducing contacts to mitigate transmission in\naddition to all variables included in the model described\nabove for mask use. The initial full model for confidence in\nthe ability to self-isolate included demographic characteristics\nand indicators of perceived risk as above in addition to work-\nplace indicators such as access to paid sick leave, expectation\nto work while sick, and the ability to work remotely. Household characteristics such as household size, whether\nthe household included children or a single parent, and\nwhether the household had access to a 14-day stockpile of\nsupplies were also included in the initial model. Further\ndetails of this regression model are located in the\nSupplementary Materials. COVID-19 risk perceptions were assessed by 3 statements\nand each response was recorded using a 6-level Likert scale\nranging from strongly agree to strongly disagree, and unsure. Perceived effectiveness of public health interventions to con-\ntrol COVID-19 was assessed by 8 questions, the responses to\nwhich were recorded using a 5-level Likert scale ranging from\nvery effective to not at all effective, and unsure. Respondents’\nconfidence that they could comply with various public health\nmeasures related to COVID-19 was assessed by 7 items and\nresponses were recorded using a 5-level Likert scale ranging\nfrom very confident to not at all confident, and unsure. Ability\nto comply with public health measures due to external influ-\nences was assessed using a 5-item Likert scale, ranging from\nstrongly agree to strongly disagree. Participants were also asked about their use of face masks. Adults living with children under the age of 15 years were\nasked to provide information about childcare provision during\nschool and daycare closures. The complete survey is provided\nin the Supplementary Materials. Results A total of 9120 survey responses were received between\nMay 7 and May 19, 2020. Survey responses were excluded\nfrom analysis if the survey was completed in less than\none third of the estimated completion time (n = 137), if the\nrespondent reported their age as less than 18 years (n = 23), or\nif the survey was discontinued prior to completion for any\nreason, including exceeding the age, gender, or province\nquotas (n = 3960). Responses with duplicated entries for gen-\nder, age, postal code, date, and contact names were considered\nduplicate responses and removed from the dataset (n = 19). Respondents who completed the entire survey and were not\nscreened out for any reason were included in the final sample,\nresulting in 4981 high-quality survey responses. Predictors of mask use The proportion of respondents who wore a mask in the 24\nhours prior to survey completion was 32.5% (95% CI, 31.2–\n33.8) for an average duration of 96.6 (SD 412.4) minutes. Respondents from Ontario (where physical distancing mea-\nsures were still in place at the time of the survey) reported the\nhighest level of mask use while those from Prince Edward\nIsland (where physical distancing recommendations were be-\nginning to relax at the time of the survey) reported the lowest\nmask use (Fig. 2a). The most common locations to wear a Data analysis Demographic characteristics of survey respondents were com-\npared with those from the 2016 Canadian Census in order to\nensure that the sample population was generally representative\nof the Canadian population. Attitudes towards the effectiveness of COVID-19 measures\nand confidence in individuals’ ability to comply with such mea-\nsures were aggregated to provide binary measures of agreement\n(strongly or somewhat); confidence (very or fairly); and per-\nceived effectiveness of measures (very or fairly); with the other\ncategory comprised of neutral responses, non-agreement, or un-\ncertainty. For a question regarding expectations of coworkers\nwith respect to working while ill, the responses “somewhat dis-\nagree” and “strongly disagree” were combined to form “dis-\nagree”, while all other responses were combined. The proportion\nof respondents who agreed, were confident, or thought each\nmeasure was effective was calculated for each of the questions pp\ny\nA backward elimination procedure was used to evaluate\nvariables for inclusion in the final multivariable regression\nmodels. Confounding was assessed by examining the vari-\nables in the model for changes once the potentially confound-\ning variable was excluded from the model. Once the final\nmodel was identified, all two-way multiplicative interaction\nterms involving age group with the other predictor variables\nwere assessed. Age group was of interest because it was sig-\nnificantly associated with most measures of perceived effec-\ntiveness and ability to comply with public health measures. Multicollinearity was assessed for each model using the Can J Public Health (2021) 112:363–375 366 variance inflation factor. All data were analyzed using\nRStudio Version 1.2.5033 (RStudio Team 2019). them to work if sick (Table 1). Fewer respondents in the youn-\ngest age group (18–29 years) reported having access to paid sick\nleave compared with those in the 30–39 years age group, and\nthose aged 30–59 years were more likely to have access to paid\nsick leave compared with respondents aged 60–69 years\n(Table 1). Demographics also predicted confidence in access to\na 14-day supply of food, and ability to find childcare (Table 1). Perceived effectiveness and confidence in the ability\nto comply with public health measures At least 87% of respondents considered each of the public\nhealth measures described to be effective in reducing the\ntransmission of COVID-19, with women and older indi-\nviduals expressing greater faith in public health mea-\nsures (Table 2). Those in the paid workforce were less\nlikely to agree that each of the public health measures\nis effective except school closures, where there was no\ndifference between groups. A detailed description of the respondent population is in-\ncluded in the Supplementary Materials (Table S1). For the\n4981 surveys, the proportion of respondents living in each\nprovince, the male to female ratio, and the proportion of re-\nspondents in each age category were comparable to the 2016\nCanadian Census of the population (data shown in Table S1,\nSupplementary Materials). More than 90% of respondents reported that they were\nconfident in their ability to comply with each of the five public\nhealth measures (Table 3), with greater confidence on most\nmeasures in women and older individuals. Lower-income in-\ndividuals were less confident in their ability to avoid public\ntransportation. Less confidence was seen in the paid work-\nforce, compared with those who were unemployed, retired,\nor working within the home. Childcare Table 1 describes respondents’ level of perceived risk in\nMay 2020 as well as indicators of preparedness in the event\nof illness. Overall, 61.5% of respondents agreed that COVID-\n19 would be a serious illness for them, 21.5% agreed that they\nare likely to catch the virus, and 71.5% agreed that they are\nlikely to transmit the virus if they do not follow public health\nadvice. Perceived risk of serious illness due to COVID-19\nincreased with increasing age beyond 50 years; however, per-\nceived risk of contracting the virus was highest in the 30–39\nyear age group and decreased with increasing age thereafter. Individuals who self-identified as being in a risk group were\nmore likely to agree that they are likely to catch the virus and\nexperience serious illness compared with other individuals,\nwhile those living with children under the age of 18 years or\nthose in the paid workforce were less likely to agree that\nCOVID-19 would be a serious illness for them compared with\nhouseholds containing no children or those not in the paid\nworkforce, respectively. Risk perception was also associated\nwith gender (Table 1). Respondents with household members who were 14 years of\nage or younger were asked about childcare provision when\nschools and daycares were closed due to the pandemic (n =\n930). More than 80% of respondents reported that a parent\nprovided childcare for their children during this time\n(Fig. 1a). Only 12.2% (95% CI, 10.1–14.3) of those requiring\nchildcare used providers who were not part of their household. Of the parents providing childcare, parents in the workforce\nprovided the greatest proportion of childcare duties (52%)\n(Fig. 1b). The wording of the questionnaire did not allow for\nan analysis of childcare by gender. Perceived preparedness A higher proportion of older individuals, those not in a risk\ngroup, and women reported that co-workers would not expect Can J Public Health (2021) 112:363–375 367 Table 1\nIndicators of perceived risk and preparedness in the event of illness stratified by socio-demographic characteristics. Values are reported as % (95% confidence interval), and those in bold font\nwere statistically significant between subgroups (p < 0.0026). Cells denoted by “-” signify that statistics were not run because the survey question was not relevant for one of the groups. Perceived preparedness Letters in superscript\nindicate levels at which pairwise comparisons were statistically significant with Bonferroni correction (p < 0.05)\nPerceived risk\nPreparedness in the event of illness\nLikely to contract\nCOVID-19 (n = 4981)\nLikely to be a serious\nillness for self (n = 4981)\nLikely to transmit to\nothers (n = 4981)\nMy co-workers would\nnot expect me to\nwork if ill (n = 2698)\nI would still get\npaid (n = 2698)\nI have enough food/supplies\nto last for 14 days (n = 4981)\nSomeone else would be\nable to look after my\nchildren (n = 930)\nOverall\n21.5% (20.4–22.7)\n61.5% (60.1–62.8)\n71.5% (70.3–72.8)\n50.9% (49.0–52.7)\n51.1% (49.2–53.0)\n70.8% (69.6–72.1)\n59.6% (56.4–62.7)\nGender\nWomen\n20.8% (19.3–22.4)\n61.0% (59.1–62.9)\n74.5% (72.8–76.2)\n55.7% (52.9–58.4)\n48.7% (45.9–51.5)\n72.9% (71.2–74.7)\n53.2% (48.7–57.6)\nMen\n22.1% (20.5–23.8)\n61.9% (60.0–63.8)\n68.4% (66.5–70.2)\n46.8% (44.2–49.3)\n53.3% (50.7–55.9)\n68.8% (66.9–70.6)\n66.2% (61.9–70.6)\nAge group\n18–29 yearsa\n25.7% d–f (22.7–28.8)\n45.1% c–f (41.6–48.6)\n70.9% (67.8–74.1)\n40.0% c, d (35.6–44.3)\n48.2% b (43.8–52.7)\n62.5% c–f (59.1–65.9)\n54.4% b, c, e (46.0–62.7)\n30–39 yearsb\n32.2% c–f (29.2–35.2)\n51.6% d–f (48.4–54.8)\n71.4% (68.6–74.3)\n43.3% c, d (39.8–46.8)\n55.3% a, e (51.7–58.8) 65.6% e, f (62.5–68.6)\n56.7% a, e (51.6–61.9)\n40–49 yearsc\n24.3% b, e, f (21.4–27.3) 54.9% a, d–f (51.4–58.3)\n70.3% (67.2–73.5)\n52.4% a, b (48.5–56.2)\n54.1% e (50.2–58.0)\n66.5% a, e, f (63.2–69.7)\n60.7% a, d, e (55.3–66.1)\n50–59 yearsd\n18.4% a, b (15.8–21.0)\n62.6% a-c, e, f (59.4–65.9)\n71.3% (68.3–74.4)\n63.4% a,b, e (59.4–67.4) 50.9% e (46.7–55.1)\n71.6% a, e, f (68.5–74.6)\n77.8% c, e (69.2–86.4)\n60–69 yearse\n13.4% a–c (11.3–15.6)\n72.9% a–c, d, f (70.1–75.7)\n70.6% (67.8–73.5)\n62.0% (55.9–68.2)\n41.4% b–d (35.1–47.6) 77.8% a–d (75.2–80.4)\n35.0% a, b, d (14.1–55.9)\n70+ yearsf\n13.8% a–c (11.1–16.5)\n85.3% a–d (82.5–88.0)\n75.6% (72.2–78.9)\n-\n-\n82.5% a–d (79.5–85.4)\n-\nRisk group\nYes\n29.8% (27.6–32.0)\n86.1% (84.4–87.7)\n74.0% (71.9–76.2)\n44.0% (40.3–47.6)\n52.7% (49.1–56.4)\n73.6% (71.5–75.8)\n63.4% (57.5–69.3)\nNo\n17.5% (16.2–18.8)\n49.6% (47.9–51.3)\n70.3% (68.8–71.9)\n53.4% (51.2–55.6)\n50.5% (48.3–52.7)\n69.4% (67.9–71.0)\n58.1% (54.4–61.9)\nHousehold children\nYes\n29.0% (26.4–31.7)\n55.8% (52.8–58.7)\n71.0% (68.3–73.6)\n48.3% (45.0–51.7)\n53.4% (50.1–56.8)\n66.1% (63.4–68.9)\n-\nNo\n19.3% (18.1–20.6)\n63.1% (61.6–64.7)\n71.7% (70.3–73.1)\n52.0% (50.0–54.3)\n50.0% (47.7–52.3)\n72.2% (70.8–73.6)\n-\nHousehold income\n$0–$60,000g\n21.8% (20.0–23.7)\n64.8% h (62.6–66.9)\n70.3% (68.3–72.4)\n51.0% (47.4–54.6)\n40.0% h, i (36.4–43.5)\n68.0% (65.9–70.1)\n49.3% h, i (42.8–55.8)\n$60,001–$110,000h\n22.9% (20.8–25.0)\n58.5% g (56.0–60.9)\n73.0% (70.8–75.2)\n51.6% (48.5–54.7)\n55.0% g, i (51.9–58.1)\n73.5% (71.3–75.6)\n62.2% g, i (57.2–67.2)\n> $110,000i\n22.4% (19.8–24.9)\n60.5% (57.5–63.4)\n73.1% (70.4–75.9)\n48.2% (44.7–51.7)\n57.8% g, h (54.3–61.3) 71.6% (68.8–74.3)\n65.1% g, h (59.6–70.7)\nDon’t know/prefer\nnot to answer\n14.5% (11.4–17.5)\n60.6% (56.3–64.8)\n68.4% (64.3–72.4)\n57.0% (50.1–63.9)\n47.0% (40.1–53.9)\n71.3% (67.4–75.2)\n56.5% (44.1–68.8)\nEmployment status\nPaid workforce\n26.2% (24.6–27.9)\n56.3% (54.4–58.1)\n70.6% (68.9–72.3)\n-\n-\n68.7% (66.9–70.4)\n61.5% (57.9–65.1)\nNot in paidworkforce 16.0% (14.5–17.5)\n67.6% (65.7–69.5)\n72.6% (70.8–74.5)\n-\n-\n73.3% (71.5–75.1)\n53.1% (46.4–59.8)\nLevel of education\nSecondary or lessj\n18.7% (16.5–20.9)\n61.7% (59.0–64.5)\n71.1% (68.5–73.6)\n53.6% (48.9–58.2)\n40.3% k, l (35.7–44.9)\n71.4% (68.8–74.0)\n50.3% (42.3–58.4)\nCollege/trades or\nother qualificationk\n21.7% (19.9–23.6)\n62.1% (59.9–64.3)\n70.0% (67.9–72.1)\n51.5% (48.4–54.6)\n50.7% j, l (47.6–53.8)\n71.4% (69.3–73.4)\n58.2% (53.0–63.4)\nUniversity degreel\n23.1% (21.2–25.0)\n60.6% (58.4–62.9)\n73.4% (71.4–75.4)\n49.5% (46.7–52.2)\n55.1% j (52.4–57.9)\n69.9% (67.8–72.0)\n63.8% (59.3–68.4)\nCan J Public Health (2021) 112:363 375 Can J Public Health (2021) 112:363–375 368 Table 2\nPerceived effectiveness of six different public health measures stratified by socio-demographic characteristics. Perceived preparedness Values are reported as % (95% confidence interval), and those in bold font were\nstatistically significant between subgroups (p < 0.0026) (n = 4981). Perceived preparedness However, there are\ndifferences in these indicators based on socio-demographic\nvariables and context. If our collective priority is to maintain\nan open economy, we need to ensure that individuals are able\nto comply with public health measures that prevent and con-\ntrol transmission of the virus. The results from this study have\nidentified a number of areas in which policies could help ad-\ndress issues of public adherence. mask were in supermarkets or other stores, anywhere\noutside the home, and walking on the street (Fig. 2b);\n42.7% (95% CI, 35.3–50.1) of mask-wearing transit-\nusers had worn a mask on transit in the past 24 hours. Factors associated with mask use are shown in Table 4;\nmask use was increased in households with more than one\nadult, with children, or with multiple generations; and in\nindividuals with university-level education, or reporting\nthat they would be at risk of serious illness with COVID-\n19 or at increased risk of developing COVID-19. Of the\nvariables assessed for interaction with age group, the\nonly interaction detected was between age and high-\nrisk conditions with younger (< 30 years), high-risk in-\ndividuals more likely to have reported mask use com-\npared with 40–49-year-old respondents who were not in\na risk group. p\nWhile confidence in the ability to comply with various\npublic health measures was high, younger age groups, those\nin the paid workforce, and, in some cases, those with lower\nincome were less likely to report confidence in the ability to\ncomply. Individuals need to feel supported in complying\nwith public health measures. Our findings of reduced confi-\ndence in ability to comply with public health measures are\nconsistent with other research demonstrating that those with\na low income (Wolf et al. 2020) and those in younger age\ngroups (Cvetković et al. 2020) are less prepared in the event\nof illness. Compliance in the event of self-isolation or quar-\nantine is at least partially dependent on preparedness and\nhaving the means to self-isolate; there is a need to develop\nsupports for those who need to self-isolate but may not have\nthe means to do so. Presenteeism risk (attending work while\nsick) was gendered, with more men than women anticipating\nthat co-workers would expect them to continue to work\nwhile sick; however, responses did not differentiate between\nemployer and co-workers. Perceived preparedness Letters in superscript indicate levels at which pairwise comparisons were statistically significant with Bonferroni correction (p < 0.05)\nPublic health measures\nReduce contacts\nSelf-isolate for\n14 days with severe\nrespiratory symptoms\nAvoid crowds\nStay home for 14 days when\nhousehold member has severe\nrespiratory symptoms\nSchool closures\nBusiness closures\nOverall\n93.7% (93.0–94.3)\n93.1% (92.4–93.8)\n94.0% (93.3–94.6)\n90.6% (89.8–91.4)\n87.2% (86.2–88.1)\n91.4% (90.6–92.2)\nGender\nWomen\n95.3% (94.4–96.1)\n94.9% (94.0–95.7)\n95.8% (95.0–96.6)\n92.5% (91.5–93.5)\n89.6% (88.5–90.8)\n93.4% (92.4–94.4)\nMen\n92.0% (91.0–93.1)\n91.3% (90.2–92.4)\n92.1% (91.1–93.2)\n88.8% (87.5–90.0)\n84.7% (83.2–86.1)\n89.4% (88.1–90.6)\nAge group\n18–29 yearsa\n90.4% c–f (88.3–92.5)\n89.9% e, f (87.8–92.0)\n89.8% d–f (87.7–91.9)\n86.2% d–f (83.8–88.6)\n85.8% (83.3–88.2)\n87.1% e, f (84.7–89.4)\n30–39 yearsb\n92.0% e, f (90.2–93.7)\n91.2% e, f (89.4–93.0)\n91.4% d–f (89.7–93.2)\n88.2% e, f (86.2–90.3)\n86.7% (84.6–88.9)\n88.9% e, f (86.9–90.9)\n40–49 yearsc\n91.3% a, e, f (89.3–93.2)\n92.5% (90.7–94.3)\n92.3% e, f (90.4–94.1)\n90.9% (88.9–92.9)\n85.8% (83.4–88.2)\n90.8% e, f (88.8–92.8)\n50–59 yearsd\n94.8% a, f (93.3–96.3)\n93.9% (92.3–95.5)\n95.4% a, b (94.0–96.8)\n92.2% a (90.4–94.0)\n88.1% (85.9–90.3)\n91.4% e, f (89.5–93.3)\n60–69 yearse\n95.9% a–c (94.7–97.2)\n95.4% a, b (94.1–96.7)\n97.1% a–c (96.1–98.2)\n92.7% a, b (91.1–94.4)\n88.2% (86.2–90.3)\n95.0% a–d (93.6–96.4)\n70+ yearsf\n98.1% a –d (97.1–99.2)\n95.8% a, b (94.2–97.3)\n98.1% a–c (97.1–99.2)\n93.9% a, b (92.0–95.8)\n88.4% (85.9–90.9)\n95.8% a–d (94.2–97.3)\nRisk group\nYes\n95.3% (94.2–96.3)\n93.4% (92.2–94.6)\n94.1% (92.9–95.2)\n90.3% (88.8–91.7)\n88.8% (87.2–90.3)\n92.8% (91.6–94.1)\nNo\n92.9% (92.0–93.8)\n92.9% (92.1–93.8)\n93.9% (93.1–94.7)\n90.8% (89.8–91.8)\n86.4% (85.2–87.6)\n90.7% (89.7–91.7)\nHousehold children\nYes\n92.6% (91.1–94.1)\n93.1% (91.6–94.5)\n93.1% (91.6–94.5)\n90.4% (88.7–92.1)\n87.6% (85.7–89.5)\n90.2% (88.4–91.9)\nNo\n94.0% (93.2–94.7)\n93.1% (92.3–93.9)\n94.2% (93.5–95.0)\n90.7% (89.8–91.6)\n87.0% (86.0–88.1)\n91.8% (90.9–92.7)\nHousehold income\n$0–$60,000\n93.2% (92.0–94.3)\n92.9% (91.7–94.1)\n94.3% (93.3–95.4)\n90.2% (88.9–91.6)\n87.8% (86.3–89.2)\n91.6% (90.3–92.8)\n$60,001–$110,000\n94.9% (93.8–96.0)\n94.8% (93.7–95.9)\n94.9% (93.8–96.0)\n92.4% (91.1–93.8)\n88.2% (86.6–89.8)\n93.1% (91.9–94.4)\n> $110,000\n92.5% (90.9–94.1)\n91.5% (89.8–93.2)\n92.0% (90.3–93.7)\n89.4% (87.5–91.2)\n85.1% (82.9–87.2)\n88.7% (86.7–90.6)\nDon’t know/prefer\nnot to answer\n94.0% (91.9–96.0)\n91.6% (89.2–94.0)\n93.8% (91.7–95.9)\n89.1% (86.4–91.8)\n86.1% (83.1–89.1)\n91.0% (88.5–93.5)\nEmployment status\nPaid workforce\n92.6% (91.6–93.5)\n92.2% (91.2–93.2)\n92.6% (91.6–93.6)\n89.3% (88.2–90.5)\n86.6% (85.3–87.9)\n89.4% (88.2–90.6)\nNot in paid workforce\n95.0% (94.1–95.9)\n94.1% (93.2–95.1)\n95.6% (94.7–96.4)\n92.2% (91.1–93.3)\n87.9% (86.5–89.2)\n93.8% (92.8–94.8)\nLevel of education\nSecondary or less\n93.0% (91.5–94.4)\n92.7% (91.2–94.2)\n93.8% (92.4–95.2)\n90.9% (89.2–92.5)\n88.1% (86.3–89.9)\n91.4% (89.8–93.0)\nCollege/trades\nor other qualification\n93.7% (92.6–94.8)\n93.5% (92.4–94.6)\n93.8% (92.8–94.9)\n90.2% (88.9–91.5)\n86.3% (84.7–87.8)\n90.5% (89.2–91.8)\nUniversity degree\n94.0% (93.0–95.1)\n92.9% (91.8–94.1)\n94.2% (93.1–95.2)\n90.9% (89.6–92.2)\n87.5% (86.0–89.0)\n92.3% (91.1–93.5)\n368\nCan J Public Health (2021) 112:363 Can J Public Health (2021) 112:363–375 369 to comply with such measures was high. Perceived preparedness More individuals with less edu-\ncation or income were at risk of not being paid if they took sick\nleave. Presenteeism has been shown to be prevalent among oc-\ncupations with high contact rates, including the care, welfare, and\neducation sectors (Aronsson et al. 2000). Determinants of\npresenteeism include job insecurity, workplace performance in-\ndicators that include attendance rates, and limited entitlement to\npaid sick leave (Kinman 2019). Investigators in Israel demon-\nstrated that paid sick time increases compliance with stay-home-\nwhen-sick policies from 57% with no compensation to almost\n100% when compensation was assumed (Bodas and Peleg\n2020). These findings highlight the need for a shift in workplace\nculture toward discouraging presenteeism and ensuring paid sick\ntime. Direct contact with non-household members The proportion of respondents who had engaged in an activity\nwith non-household contacts in the 7 days prior to survey\ncompletion was 24.4% (95% CI, 23.2–25.6) (Fig. 3a). More\nnon-household contact was reported for provinces which were\nmore advanced in the de-escalation of physical distancing\n(e.g., PEI) at the time of survey completion; however, in prov-\ninces where physical distancing was still in place during the\nsurvey period (e.g., ON), approximately 20% of respondents\nwere reporting non-household contacts in May 2020. Of the\nrespondents who reported non-household contacts, 62% re-\nported that this occurred once or twice in a 7-day period while\nalmost 23% reported having non-household contacts more\nthan 3 days out of the 7-day period prior to survey completion\n(Fig. 3b). Individuals in the youngest age group and those who\nreported an annual household income greater than $110,000\nwere more likely to have participated in an activity with\nsomeone outside their household (Table 5) compared\nwith older respondents and those earning less than\n$60,000, respectively. Perceived risk of serious illness\nwas associated with less interaction with individuals\noutside the household. Our finding that a majority of respondents with dependent\nchildren were responsible for childcare at the same time as\nmaintaining employment when schools and daycares were\nclosed due to the pandemic highlights the need for provincial-\nly co-ordinated plans with evidence-based infection preven-\ntion and control (IPAC) procedures for safe school function-\ning. There is mounting evidence that children are more sus-\nceptible and can transmit infection more readily than original-\nly thought, potentially contributing substantially to communi-\nty transmission (Hyde 2020). Recognition of transmission\namong children could lead to prolonged school closures in\nprovinces heavily impacted by the pandemic. Statistics\nCanada estimates that there are more than 10 million families Details of the regression model identifying factors associ-\nated with confidence in the ability to self-isolate with mild\nsymptoms of COVID-19 are located in Table S2 of the\nSupplementary Materials. Discussion At the time of data collection, Canadian provinces were in\nvarious stages of reopening the economy. Overall, the major-\nity of participants reported risk perceptions and attitudes about\nthe effectiveness of public health measures that are\nwell aligned with scientific evidence and the reported ability Table 3\nConfidence in the ability to comply with five different public health measures stratified by socio-demographic characteristics. Values are reported as % (95% confidence interval), and those in\nbold font were statistically significant between subgroups (p < 0.0026) (n = 4981). Discussion 1 a Respondents with children 14 years of age or younger (n = 930)\nreported on which individuals looked after the children in their household\nduring school and daycare closures due to the pandemic. b Respondents\nwho reported that parents provided childcare during school and daycare\nclosures (n = 769) also identified the employment circumstances of the\nparent who provided the childcare. The category “Parent in the\nWorkforce” includes those working remotely, those working part-time,\nthose who took leave from their job, and those who were unemployed due\nto COVID-19 but otherwise have been working parent who provided the childcare. The category “Parent in the\nWorkforce” includes those working remotely, those working part-time,\nthose who took leave from their job, and those who were unemployed due\nto COVID-19 but otherwise have been working Fig. 1 a Respondents with children 14 years of age or younger (n = 930)\nreported on which individuals looked after the children in their household\nduring school and daycare closures due to the pandemic. b Respondents\nwho reported that parents provided childcare during school and daycare\nclosures (n = 769) also identified the employment circumstances of the Fig. 1 a Respondents with children 14 years of age or younger (n = 930)\nreported on which individuals looked after the children in their household\nduring school and daycare closures due to the pandemic. b Respondents\nwho reported that parents provided childcare during school and daycare\nclosures (n = 769) also identified the employment circumstances of the parent who provided the childcare. The category “Parent in the\nWorkforce” includes those working remotely, those working part-time,\nthose who took leave from their job, and those who were unemployed due\nto COVID-19 but otherwise have been working parent who provided the childcare. The category “Parent in the\nWorkforce” includes those working remotely, those working part-time,\nthose who took leave from their job, and those who were unemployed due\nto COVID-19 but otherwise have been working parent who provided the childcare. The category “Parent in the\nWorkforce” includes those working remotely, those working part-time,\nthose who took leave from their job, and those who were unemployed due\nto COVID-19 but otherwise have been working An indication that public health messaging has been\nsuccessful in many cases, we found that both the per-\nceived ability to comply with public health measures\nand perceived effectiveness of such measures were very\nhigh. Discussion Letters in superscript indicate levels at which pairwise comparisons were statistically significant with Bonferroni\ncorrection (p < 0.05)\nPublic health measures\nReduce contacts\nSelf-isolate for 14 days\nwith severe respiratory\nsymptoms\nAvoid crowds\nStay home for 14 days\nwhen household member\nhas severe respiratory symptoms\nAvoid public transportation\nOverall\n93.7% (93.0–94.4)\n93.0% (92.3–93.7)\n93.3% (92.6–94.0)\n91.0% (90.2–91.7)\n90.9% (90.0–91.7)\nGender\nWomen\n94.6% (93.7–95.5)\n94.9% (94.1–95.8)\n94.7% (93.8–95.6)\n92.7% (91.6–93.7)\n92.9% (91.9–93.9)\nMen\n92.8% (91.8–93.9)\n91.1% (90.0–92.2)\n91.9% (90.8–92.9)\n89.3% (88.1–90.5)\n88.8% (87.6–90.1)\nAge group\n18–29 years a\n90.1% c–f (88.1–92.2)\n87.7% c–f (85.4–90.0)\n88.1.% c–f (85.8–90.4)\n85.6% c–f (83.2–88.1)\n85.3% c–f (82.8–87.8)\n30–39 years b\n92.6% e (90.9–94.3)\n90.6% e, f (88.7–92.5)\n89.2% c–f (87.2–91.2)\n87.5% c–f (85.4–89.6)\n86.8% c–f (84.7–89.0)\n40–49 years c\n92.0% a, e, f (90.1–93.9)\n92.1% a, e, f (90.3–94.0)\n91.8% a, c–f (89.9–93.7)\n89.7% a, c–f (87.5–91.8)\n89.4% a, b, e, f (87.3–91.5)\n50–59 years d\n94.3% a (92.8–95.9)\n94.2% a (92.7–95.8)\n95.6% a (94.3–97.0)\n93.9% a (92.3–95.5)\n92.1% a, b, f (90.3–93.9)\n60–69 years e\n96.7% a–c (95.6–97.8)\n96.4% a–c (95.3–97.6)\n97.2% a (96.2–98.3)\n94.2% a (92.7–95.6)\n95.0% a–c (93.6–96.4)\n70+ years f\n96.1% a, c (94.6–97.6)\n97.2% a–c (95.9–98.5)\n98.4% a (97.5–99.4)\n95.3% a (93.7–97.0)\n97.3% a–c (96.1–98.6)\nRisk group\nYes\n95.1% (94.0–96.1)\n92.8% (91.5–94.0)\n94.3% (93.1–95.4)\n91.0% (89.6–92.4)\n91.4% (90.1–92.8)\nNo\n93.0% (92.2–93.9)\n93.1% (92.2–94.0)\n92.8% (92.0–93.7)\n90.9% (90.0–91.9)\n90.6% (89.6–91.6)\nHousehold children\nYes\n92.6% (91.1–94.1)\n91.6% (90.0–93.3)\n91.7% (90.1–93.3)\n90.0% (88.2–91.7)\n89.2% (87.4–91.0)\nNo\n94.0% (93.2–94.7)\n93.4% (92.6–94.2)\n93.8% (93.0–94.5)\n91.2% (90.3–92.1)\n91.3% (90.5–92.2)\nHousehold income\n$0–$60,000 g\n93.2% (92.0–94.3)\n92.6% (91.4–93.8)\n93.3% (92.1–94.4)\n90.2% (88.8–91.5)\n89.3% h (87.9–90.7)\n$60,001–$110,000 h\n94.7% (93.6–95.8)\n94.5% (93.4–95.7)\n94.0% (92.8–95.1)\n92.0% (90.7–93.3)\n93.0% g (91.7–94.2)\n> $110,000\n93.8% (92.3–95.2)\n91.7% (90.0–93.4)\n92.7% (91.1–94.3)\n90.4% (88.6–92.2)\n90.8% (89.1–92.6)\nDon’t know/prefer\nnot to answer\n92.2% (89.9–94.5)\n92.4% (90.1–94.7)\n92.6% (90.3–94.9)\n91.6% (89.2–94.0)\n90.2% (87.7–92.8)\nEmployment status\nPaid workforce\n92.4% (91.4–93.4)\n91.4% (90.3–92.4)\n91.1% (90.1–92.2)\n88.9% (87.7–90.1)\n88.9% (87.7–90.1)\nNot in paid workforce\n95.2% (94.3–96.1)\n94.9% (94.0–95.8)\n95.8% (95.0–96.7)\n93.4% (92.4–94.4)\n93.2% (92.1–94.2)\nLevel of education\nSecondary or less\n92.7% (91.2–94.2)\n92.5% (91.0–94.0)\n93.1% (91.7–94.6)\n90.1% (88.4–91.8)\n90.4% (88.7–92.0)\nCollege/trades or\nother qualification\n93.6% (92.5–94.7)\n93.6% (92.5–94.7)\n93.7% (92.6–94.8)\n92.2% (91.0–93.4)\n91.5% (90.2–92.7)\nUniversity degree\n94.4% (93.4–95.4)\n92.8% (91.6–94.0)\n93.0% (91.8–94.1)\n90.2% (88.9–91.6)\n90.5% (89.2–91.9)\n370\nCan J Public Health (2021) 112:363–375 Can J Public Health (2021) 112:363–375 370 Can J Public Health (2021) 112:363–375 371 Fig. Discussion However, both indicators varied by age and gender, with children living in Canada (Statistics Canada 2020) and\nalmost 70% of families with dependent children have two\nemployed parents (Statistics Canada 2016b). Investing in ro-\nbust IPAC procedures for schools will allow schools to remain\nopen and parents to maintain employment. Fig. 2 Respondents were asked if they had worn a face mask in the 24 hours prior to survey completion. a represents reported mask use by province of\nresidence. b identifies the location(s) of mask use for respondents who reported wearing a mask in the previous 24 hours (n = 1617) Fig. 2 Respondents were asked if they had worn a face mask in the 24 hours prior to survey completion. a represents reported mask use by province of\nresidence. b identifies the location(s) of mask use for respondents who reported wearing a mask in the previous 24 hours (n = 1617) Fig. 2 Respondents were asked if they had worn a face mask in the 24 hours prior to survey completion. a represents reported mask use by province of\nresidence. b identifies the location(s) of mask use for respondents who reported wearing a mask in the previous 24 hours (n = 1617) 372 Can J Public Health (2021) 112:363–375 emphasizing the need for additional targeted messaging. in younger individuals was associated with poor compli-\nTable 4\nResults of a multivariable logistic regression analysis assessing factors associated with mask use in the 24 hours prior to survey completion. Discussion Values are reported as adjusted odds ratios (95% confidence interval) and those in bold font were statistically significant (p < 0.05) (n = 4981)\nVariable\nAdjusted OR (95% CI)\np Wald’s test\np (L-R test)\nHousehold composition\n0.005\nSingle person living alone (referent)\nAdults only living together\n1.32 (1.13–1.55)\n< 0.001\nFamily with children\n1.24 (1.01–1.52)\n0.04\n>2 generations living together\n1.71 (1.12–2.63)\n0.01\nGrandparents living with their grandchildren only\n1.16 (0.28–4.72)\n0.84\nAge category\n1\n18–29 years\n1.61 (1.23–2.10)\n< 0.001\n30–39 years\n1.21 (0.95–1.56)\n0.13\n40–49 years (referent)\n-\n-\n50–59 years\n1.22 (0.93–1.60)\n0.15\n60–69 years\n1.44 (1.08–1.92)\n0.01\nOver 70 years\n1.39 (0.98–1.99)\n0.07\nRespondent risk group\n1\nRespondent is in a high-risk group\n1.51 (1.06–2.15)\n0.02\nSize of the geographic region of residence\n< 0.001\nLarge city (referent)\nMedium-sized city\n0.74 (0.64–0.85)\n< 0.001\nLarge town\n0.61 (0.48–0.76)\n< 0.001\nSmall town\n0.53 (0.43–0.66)\n< 0.001\nRural place\n0.38 (0.29–0.50)\n< 0.001\nEducation level of respondent\n0.02\nSecondary or less (referent)\nCollege/trade/other qualification\n1.00 (0.85–1.18)\n1.0\nUniversity (bachelor degree or higher)\n1.21 (1.02–1.43)\n0.03\nEmployment status of respondent\n< 0.001\nUnemployed, student, retired, work within home (referent)\nEmployed FT, PT, self-employed\n1.32 (1.13–1.54)\n< 0.001\nPerceived risk of contracting the virus\n< 0.001\nLikely to contact the virus\n1.31 (1.12–1.52)\n< 0.001\nPerceived risk of serious illness due to COVID-19\n< 0.001\nCOVID-19 would be a serious illness for respondent\n1.61 (1.39–1.85)\n< 0.001\nInteraction between age category and respondent risk group\n< 0.001\n18–29 years in a risk group\n1.75 (1.06–2.90)\n0.03\n30–39 years in a risk group\n1.57 (0.98–2.53)\n0.06\n40–49 years, not high risk (referent)\n-\n-\n50–59 years in a risk group\n0.87 (0.54–1.39)\n0.56\n60–69 years in a risk group\n0.72 (0.46–1.13)\n0.15\nOver 70 years in a risk group\n0.89 (0.54–1.46)\n0.64 Table 4\nResults of a multivariable logistic regression analysis assessing factors associated with mask use in the 24 hours prior to survey completion. Values are reported as adjusted odds ratios (95% confidence interval) and those in bold font were statistically significant (p < 0.05) (n = 4981)\nVariable\nAdjusted OR (95% CI)\np Wald’s test\np (L-R test) Table 4\nResults of a multivariable logistic regression analysis assessing factors associated with mask use in the 24 hours prior to survey completion. Table 5 Results of a\nmultivariable logistic regression\nanalysis assessing factors\nassociated with engaging in an\nactivity with non-household con-\ntacts in the 7 days prior to survey\ncompletion. Values are reported\nas adjusted odds ratios (95%\nconfidence interval) and those in\nbold font are statistically signifi-\ncant (p < 0.05) (n = 4981) Discussion Values are reported as adjusted odds ratios (95% confidence interval) and those in bold font were statistically significant (p < 0.05) (n = 4981) in younger individuals was associated with poor compli-\nance with public health measures and is consistent with a\ngrowing body of evidence demonstrating that male gender\nand younger age groups engage in more COVID-19 risk\nbehaviours (Alsan et al. 2020; Seale et al. 2020). Younger\nadults tend to have larger contact networks than older in younger individuals was associated with poor compli-\nance with public health measures and is consistent with a\ngrowing body of evidence demonstrating that male gender\nand younger age groups engage in more COVID-19 risk\nbehaviours (Alsan et al. 2020; Seale et al. 2020). Younger\nadults tend to have larger contact networks than older emphasizing the need for additional targeted messaging. The finding that perceived risk of serious illness increased\nwith age group is consistent with past research (Bruine de\nBruin 2020; He et al. 2020) and is in line with empiric\nestimates of illness risk in older individuals (Public\nHealth Agency of Canada 2020). Perceived lack of risk Can J Public Health (2021) 112:363–375 373 Fig. 3 a Proportion of respondents reporting contact with non-household\nmembers in the 7 days prior to survey completion. More non-household\ncontacts were reported for provinces which were more advanced in the\nde-escalation of physical distancing (e.g., PEI) at the time of survey\ncompletion; however, in provinces where physical distancing was still\nin place during the survey period (e.g., ON), approximately 20% of re-\nspondents were reporting non-household contacts in May 2020. b The\nnumber of days in the past week respondents engaged in an activity with a\nnon-household contact, for those reporting such activity (n = 1216) in place during the survey period (e.g., ON), approximately 20% of re-\nspondents were reporting non-household contacts in May 2020. b The\nnumber of days in the past week respondents engaged in an activity with a\nnon-household contact, for those reporting such activity (n = 1216) Fig. 3 a Proportion of respondents reporting contact with non-household\nmembers in the 7 days prior to survey completion. More non-household\ncontacts were reported for provinces which were more advanced in the\nde-escalation of physical distancing (e.g., PEI) at the time of survey\ncompletion; however, in provinces where physical distancing was still Fig. Discussion 3 a Proportion of respondents reporting contact with non-household\nmembers in the 7 days prior to survey completion. More non-household\ncontacts were reported for provinces which were more advanced in the\nde-escalation of physical distancing (e.g., PEI) at the time of survey\ncompletion; however, in provinces where physical distancing was still Fig. 3 a Proportion of respondents reporting contact with non-household\nmembers in the 7 days prior to survey completion. More non-household\ncontacts were reported for provinces which were more advanced in the\nde-escalation of physical distancing (e.g., PEI) at the time of survey\ncompletion; however, in provinces where physical distancing was still Fig. 3 a Proportion of respondents reporting contact with non-household\nmembers in the 7 days prior to survey completion. More non-household\ncontacts were reported for provinces which were more advanced in the\nde-escalation of physical distancing (e.g., PEI) at the time of survey\ncompletion; however, in provinces where physical distancing was still in place during the survey period (e.g., ON), approximately 20% of re-\nspondents were reporting non-household contacts in May 2020. b The\nnumber of days in the past week respondents engaged in an activity with a\nnon-household contact, for those reporting such activity (n = 1216) The evidence for the efficacy of non-medical masks\nfor COVID-19 prevention continues to grow (Fisman\net al. 2020; Konda et al. 2020; Lyu and Wehby 2020;\nRodriguez-Palacios et al. 2020). While the survey ques-\ntion for mask use was not restricted to people who had\nleft their household in the previous 24 hours, fewer than adults (Mossong et al. 2008) which likely partially ex-\nplains these results. Recent increases in cases of\nCOVID-19 in adolescents and young adults have been\nattributed to greater mixing among this age group com-\nbined with lower adherence to physical distancing mea-\nsures (Goldstein and Lipsitch 2020). Supplementary Information The online version contains supplementary\nmaterial available at https://doi.org/10.17269/s41997-021-00501-y. Supplementary Information The online version contains supplementary\nmaterial available at https://doi.org/10.17269/s41997-021-00501-y. Acknowledgments We thank J. Lau for support in programming the\nsurvey. Author contributions All the authors contributed to the study conception\nand design. Survey design and data collection were performed by GB,\nAG, PL, and EM. Data analysis was conducted by GB. The first draft of\nthe manuscript was written by GB and all the authors commented on\nprevious versions of the manuscript. All the authors read and approved\nthe final manuscript. Data availability Aggregated data are available upon request from the\ncorresponding author. Data availability Aggregated data are available upon request from the\ncorresponding author. Data availability Aggregated data are available upon request from the\ncorresponding author. Code availability Code is available upon request from the corresponding\nauthor. Code availability Code is available upon request from the corresponding\nauthor. Declarations The funders had no role in study design, data collec-\ntion and analysis, decision to publish or preparation of the manuscript. Declarations The funders had no role in study design, data collec-\ntion and analysis, decision to publish or preparation of the manuscript. Ethics approval\nThe study protocol was approved by the University of\nGuelph Research Ethics Board (protocol #20-04-011) and the University\nof Toronto Research Ethics Board (protocol #38251). Ethics approval\nThe study protocol was approved by the University of\nGuelph Research Ethics Board (protocol #20-04-011) and the University\nof Toronto Research Ethics Board (protocol #38251). Consent to participate\nInformed consent was obtained from all individ-\nual participants included in the study. Consent for publication\nInformed consent was obtained from all indi-\nvidual participants included in the study. Discussion Variable\nAdjusted OR (95% CI)\np Wald’s test\np (L-R test)\nAge category\n< 0.001\n18–29 years\n1.74 (1.39–2.18)\n< 0.001\n30–39 years\n1.18 (0.95–1.48)\n0.14\n40–49 years (referent)\n-\n-\n50–59 years\n0.98 (0.78–1.24)\n0.88\n60–69 years\n1.22 (0.97–1.52)\n0.09\nOver 70 years\n0.90 (0.69–1.18)\n0.46\nHousehold income of respondent\n< 0.001\n$0–$60,000 (referent)\n-\n$60,001–$110,000\n1.09 (0.93–1.28)\n0.29\n> $110,000\n1.49 (1.25–1.78)\n< 0.001\nUnsure/prefer not to answer\n1.03 (0.82–1.30)\n0.80\nPerceived risk of COVID as a serious illness to self\n0.006\nNo (referent)\nYes\n0.83 (0.72–0.95)\n0.006 Adjusted OR (95% CI)\np Wald’s test\np (L-R test) Adjusted OR (95% CI)\np Wald’s test\np (L-R test) 374 Can J Public Health (2021) 112:363–375 for in-person learning, and to discourage presenteeism. Taken\ntogether, such measures are likely to mitigate the impact of the\nCOVID-19 pandemic in Canada. one third of respondents reported wearing a face mask\nin the 24 hours prior to survey completion. Mask use\nwas associated with household composition and the\nstrongest association was belonging to a household with\nmore than two generations living together, likely\nreflecting concern for the safety of older individuals in\nhouseholds. Increased mask use in the youngest age\ngroup may reflect younger individuals working in essen-\ntial service jobs at the time of the survey (e.g., grocery\nstores). As with other preventive measures, compliance\nwith masks was more likely in individuals with greater\nself-perceived risk. Limitations Funding GB and AG are supported by the Canada Research Chairs pro-\ngram. DF and AT are supported by the Canadian Institutes of Health\nResearch (CIHR). ZP is supported by the Natural Sciences and\nEngineering Research Council (NSERC). EM and PL are supported by\nHeritage Canada and the Social Sciences and Humanities Research\nCouncil (SSHRC). Funding to support data collection was provided by\nthe Public Health Agency of Canada (PHAC), The National\nCollaborating Centre for Infectious Diseases (NCCID), and the\nUniversity of Guelph. While every effort was made to ensure representativeness of\nthe study population, we note several potential biases, includ-\ning non-representativeness of the sample (a risk with any sur-\nvey), the online nature of the survey, which limits participa-\ntion to those who use the Internet, and self-report which intro-\nduces the potential for recall, response, and social desirability\nbiases. The large sample size means that statistical signifi-\ncance is seen with small absolute differences. The results are\nconsistent with the large body of research on risk attitudes and\nbehaviours and, on their own, would add little new knowledge\nto the literature. However, governments and public health of-\nficials have asked Canadians to comply with extraordinary\nmeasures. The value of this study lies in its assessment of\nthe ability to comply with these extraordinary measures during\na pandemic given a variety of socio-demographic characteris-\ntics. Finally, knowledge about COVID-19 and recommended\nbehaviours is changing rapidly. These data were collected in\nMay 2020 during a time in which provinces were in different\nphases of public health de-escalation and indoor masking or-\nders were not widespread, so these data are best interpreted as\na snapshot in time. References Mossong, J., Hens, N., Jit, M., Beutels, P., Auranen, K., Mikolajczyk, R.,\net al. (2008). Social contacts and mixing patterns relevant to the\nspread of infectious diseases. PLOS Medicine, 5(3), e74. https://\ndoi.org/10.1371/journal.pmed.0050074. Alsan, M., Stantcheva, S., Yang, D., & Cutler, D. (2020). 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Conclusion Conflict of interest\nThe authors declare no competing interests. Conflict of interest\nThe authors declare no competing interests. The results of this study highlight the need for the develop-\nment of enhanced messaging and financial supports in order to\nfurther support improved compliance with public health mea-\nsures. Work is needed to identify strategies and develop tools\nfor targeted messaging to groups who are more likely to en-\ngage in risk behaviours, and social support is needed for lower\nincome individuals to enable periods of self-isolation and\nchildcare should they become ill, to permit schools to be open Open Access This article is licensed under a Creative Commons\nAttribution 4.0 International License, which permits use, sharing, adap-\ntation, distribution and reproduction in any medium or format, as long as\nyou give appropriate credit to the original author(s) and the source, pro-\nvide a link to the Creative Commons licence, and indicate if changes were\nmade. The images or other third party material in this article are included\nin the article's Creative Commons licence, unless indicated otherwise in a\ncredit line to the material. 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