Adherence to COVID-19 PrecautionaryMeasures: Applying the Health Belief Model andGeneralised Social Beliefs to a ProbabilityCommunity SampleKwok Kit Tong† , Juliet Honglei Chen† , Eilo Wing-yat Yuand Anise M. S. Wu*University of Macau, Macao, ChinaBackground: In the face of the global pandemic of coronavirus disease-2019(COVID-19), people’s adherence to precautionary behavioral measures (e.g.social distancing) largely influences the effectiveness of those measures incontaining the spread of the coronavirus. The present study aims at testingthe applicability of the health belief model (HBM) and generalised socialbeliefs (i.e. social axioms) to explore strategies for promoting adherence toCOVID-19 precautionary measures. Methods: We conducted a telephone surveywith a two-step stratified random sampling method and obtained a probability sam-ple of 616 adults in Macao, China (18–87 years old; 60.9% women) in April2020. Results: Our participants showed stronger adherence to some COVID-19precautionary measures (e.g. face mask wearing; 96.4%) but not others (e.g. socialdistancing; 42.3%). Their adherence to those measures was found to be signifi-cantly associated with four HBM factors and two social axioms, after controllingfor gender, age, and years of education. Conclusions: The HBM and the gener-alised social beliefs of social cynicism and reward for application can be applied tounderstanding adherence to precautionary measures against COVID-19. Strategiesbased on beliefs were proposed to facilitate the promotion of precautionarymeasures.Keywords: adherence, COVID-19, health belief model, precautionary measure,social axioms, social beliefs*Address for correspondence: Anise M. S. Wu, Department of Psychology, Faculty of SocialSciences, University of Macau, Avenida da Universidade, Taipa, Macao, China. Email: anise-wu@um.edu.mo†These authors contributed equally to this work.APPLIED PSYCHOLOGY: HEALTH AND WELL-BEING, 2020doi:10.1111/aphw.12230© 2020 International Association of Applied Psychologybs_bs_banner

INTRODUCTIONCoronavirus disease 2019 (COVID-19) was first discovered in Wuhan, China inDecember 2019 and it was declared a pandemic by the World Health Organiza-tion in March 2020, spreading to more than 200 territories across the globe. Tocontrol the infection, various behavioral precautions such as social distancingand personal hygiene practices have been recommended by governments. Thesesocial and behavioral containment measures are considered to be effective insuppressing the exponential growth in COVID-19 cases (Maier & Brockmann,2020). Nevertheless, individual differences have been observed regarding behav-ioral adherence to precautionary measures (Abraham & Sheeran, 2005; Harper,Satchell, Fido, & Latzman, 2020). Understanding such individual differences atthe intrapersonal level is essential for controlling COVID-19 transmission, espe-cially in the absence of vaccination (Betsch, 2020). In this study, we aimed toexplore how two intrapersonal-level factors (i.e. specific COVID-19 beliefs andgeneralised social beliefs) are associated with an individual’s behavioral adher-ence to COVID-19 precautionary measures.Intrapersonal factors are centered on major health behavior models with a focuson a variety of elements, such as health beliefs and disease-related fear or anxiety(Abraham& Sheeran, 2005; Harper et al., 2020). Due to the rapid spread of the virusand a dearth of verified research, current knowledge on the influence of intrapersonalfactors on alleviating the COVID-19 pandemic is sparse. We made reference to theprevention strategies for the human immunodeficiency virus (HIV) epidemic andfound the health belief model (HBM) promising for containing the coronavirus onthe intrapersonal level, as evidenced by its successful application to enhancing HIVprecautionary behaviors, including condom use (Abraham, Sheeran, Spears, &Abrams, 1992; Zhao et al., 2012), sexual partner numbers and selection (Lin,Simoni, & Zemon, 2005; Lux & Petosa, 1994), and HIV voluntary testing and coun-seling (Buldeo &Gilbert, 2015; N€othling&Kagee, 2013).The HBM is a value-expectancy theory addressing the desire to avoid diseaseand the belief that a health-related action can prevent it. Its components includeperceived susceptibility (i.e. belief about the risk of getting a disease), perceivedseverity (i.e. belief about the seriousness of the consequences resulted from get-ting the disease), perceived benefit (i.e. belief in the efficacy of the advisedactions to reduce the risk or seriousness of the disease threat), perceived barrier(i.e. belief about the tangible and psychological costs of the advised actions),and cue-to-action (i.e. the intensity of the cue that triggers the advised actions;Rosenstock, 1974). In addition to the HIV intervention, the HBM has been foundto be suitable for designing and/or evaluating various health interventions in acommunity setting such as accident prevention (Cao, Chen, & Wang, 2014),influenza vaccination (Wu, Lau, Ma, & Lau, 2015), addiction control (Mantler,2013; Tong, Chen, & Wu, 2019), and fertility control (Eisen, Zellman, &McAlister, 1992). Seeing the potential utility of applying the HBM to preventing2 TONG ET AL.© 2020 International Association of Applied Psychology

COVID-19, some researchers have already offered medical staff HBM-basedsuggestions to mitigate the impacts of this unprecedented health challenge (Car-ico, Sheppard, & Thomas, 2020; Mukhtar, 2020).Nevertheless, the applicability of the HBM to different COVID-19 precaution-ary behaviors has not been empirically established. The weights and relation-ships among HBM factors may vary with target behaviors (Abraham & Sheeran,2005). Past studies have also shown that some HBM factors may be morepromising than others in HBM-based interventions (Jones, Smith, & Llewellyn,2014; LaBrosse & Albrecht, 2013). Testing the applicability of the HBM hasgreat practical significance because it can inform governments and relevantdepartments of proper intervention strategies (Tola et al., 2016). Therefore, thefirst aim of the study was to evaluate the applicability of the HBM to adherenceto COVID-19 precautionary measures.While the HBM deals with specific beliefs related to the target disease/behav-ior, the role of generalised beliefs about the social world (i.e. social axioms) mayalso influence one’s adherence to precautionary measures. A group of cross-cul-tural psychologists has identified five social axioms (i.e. social cynicism, rewardfor application, social complexity, fate control, and religiosity), which are uni-versal generalised beliefs about oneself and the social and physical environ-ments, or the spiritual world, across more than 40 societies (Bond, Leung, Au,Tong, & Chemonges-Nielson, 2004a; Bond, Leung, Au, Tong, de Carrasquel,et al., 2004b). These generalised beliefs help explain different types of humanbehaviors in different cultures (Bond et al., 2004a; Leung & Bond, 2009), notonly providing guidance to human actions, including health and safety behaviors(Dinca & Iliescu, 2009; Leung & Bond, 2009), but also contributing to under-standing laypeople’s nomological network of clinical models through predictingperceived causes and cures of psychiatric symptoms (Chen & Bond, 2012).Additionally, social axioms are found to make unique contributions over per-sonal characteristics in behaviors involving interactive processes (e.g. self-ex-pressive behaviors conducted in privacy and anonymity; Kurman, 2011), whichmay be relevant to many COVID-19 precautionary behaviors. Unfortunately, theroles of social axioms in illness-preventive behaviors are not established due to alack of empirical studies. The second aim of the study was to evaluate whethersocial axioms influence adherence to COVID-19 precautionary measures.Given that the social axioms are orthogonal, the five generalised beliefs canbe used either in full or in part (Bond et al., 2004b; Zhou, Leung, & Bond,2009). In this study, we particularly focus on the roles of social cynicism (i.e.negative views of human nature, biases against some social groups, and mistrustin social institutions) and reward for application (i.e. beliefs that the investmentof effort and resources will bring positive outcomes; Bond, Leung, Au, Tong, deCarrasquel, et al., 2004b). These two social axioms were suggested to be relatedto the self-regulatory process (Hui & Bond, 2010), while reward for applicationwas also related to active coping and adjustment (Safdar, Lewis, & Daneshpour,ADHERENCE TO COVID-19 PRECAUTIONARY MEASURES 3© 2020 International Association of Applied Psychology

2006). Although no empirical study has yet tested the relationship betweensocial axioms and precautionary behaviors against a pandemic, we expect socialcynicism to have a negative association with adherence to COVID-19 precau-tionary behaviors because a higher level of social cynicism has been found to beassociated with a lower level of self-regulation and a higher tendency to distrustauthorities that provide health guidance (Hui & Bond, 2010; Singelis, Hubbard,Her, & An, 2003). On the other hand, reward for application is expected to havea positive association with adherence to COVID-19 precautionary measuresbecause stronger beliefs in positive outcomes were associated with effort, bettercoping, and the tendency to try harder after unsuccessful experiences (Singeliset al., 2003).In summary, the current study aimed at evaluating the applicability of specificHBM beliefs and generalised beliefs (i.e. social axioms) to understanding thegeneral public’s adherence to COVID-19 precautionary measures in Macao,China. Macao has the highest population density in the world, with a populationof around 696,100 (Direcc
~ao dos Servic
os de Estatıstica e Censos, 2020) in alandmass of 32.9 square kilometers. By the end of May 2020, the total numberof confirmed COVID-19 cases in Macao was 45, with zero mortality (Centro deControlo e Prevenc
~ao da Doenc
a, 2020a). To the best of our knowledge, noempirical study has tested the roles of all five HBM factors together with socialaxioms concerning precautionary behaviors against a pandemic, not to mentionwith a probability community sample. The findings of the present study mayshed light on formulating promotional strategies to enhance behavioral adher-ence to COVID-19 precautionary measures.METHODSRespondents and ProceduresA telephone survey, with two-step stratified random sampling, was designed toacquire a representative sample of the local adult Chinese. The first step was arandom selection of units of households from the latest residential phonebook ofMacao, which was followed by the second step, a random selection of one eligi-ble respondent within the chosen household based on the last-birthday rule—thehousehold member who most recently had his or her birthday was selected(Gaziano, 2008). The inclusion rule was both genders, local adult residents(18 years old or above), and with the ability to understand and speak Cantoneseor Mandarin Chinese. Each chosen respondent was invited to voluntarily partici-pate in the telephone survey with a briefing by trained research assistants on thenature of the study and their rights upon participation. Formal interviews for sur-vey data collection, without monetary incentives, were only conducted with4 TONG ET AL.© 2020 International Association of Applied Psychology

those who gave their oral consent to participate. Prior ethical approval for thisstudy was obtained from the affiliated university of the first author(s).A probability sample of 616 local Chinese adults in Macao (39.1% men, 95%CI [35.2%, 43.0%]; 60.9% women, 95% CI [57.0%, 64.8%]) was solicitedthrough the telephone survey conducted in April 2020. Each interview lasted foran average of 16.52 min. The cooperation rate, the percentage of all cases inter-viewed versus all eligible respondents ever contacted, was 89.9 per cent accord-ing to the calculation method proposed by the American Association for PublicOpinion Research (2016). The average age of the respondents was 41.70 yearsold (SD = 16.28; range = 18 to 87 years) and most of them had received educa-tion at the junior (12.8%), senior (25.6%), or tertiary (51.9%) level. About 63.0per cent of the respondents had a full- or part- time job and the remainder werestudents (13.3%), retired (12.7%), homemakers (7.0%), unemployed (3.2%), orothers (0.8%).MEASURESAdherence to COVID-19 Precautionary MeasuresIn line with the advice of the World Health Organization (2020) and the Macaogovernment (Centro de Controlo e Prevenc
~ao da Doenc
a, 2020b), our studyassessed six major COVID-19 precautionary behaviors, namely proper handwashing (i.e. use solid or liquid soap to wash hands), face mask wearing (i.e.wear a face mask in public places), social distancing (i.e. keep a one-meter dis-tance from others in public places), avoiding touching one’s eyes, nose, andmouth (i.e. avoid touching nose, mouth, and eyes before proper handwashing;hereinafter avoiding touching face), proper toilet flushing (i.e. use the toilet lidto cover the toilet seat before flushing—a government recommendation based onearly COVID-19 advice from Hong Kong; Centro de Coremaker de Contingên-cia do Novo Tipo de Coronavırus, 2020), and carrying hand sanitiser whengoing out (hereinafter carrying hand sanitiser). Respondents were prompted toreport their past-week adherence to each of the COVID-19 precautionary mea-sures (e.g. “How often did you wear a face mask in public places last week?”).All questions were rated on a 5-point Likert scale from 1 = never to 5 = always.HBM Factors of COVID-19HBM items were adapted from past HBM studies on Chinese populations (Tonget al., 2019; Wang, Wu, & Lau, 2016).(1) Perceived Susceptibility to COVID-19 (Susceptibility for short) wasassessed by a single item: “I am very likely to have COVID-19”; (2) PerceivedSeverity of COVID-19 (Severity for short) was assessed by six items (e.g. “TheADHERENCE TO COVID-19 PRECAUTIONARY MEASURES 5© 2020 International Association of Applied Psychology

consequences of COVID-19 would be severe or even fatal for me”), with aCronbach’s alpha of .79; (3) Perceived Benefit of Adherence to COVID-19Precautionary Measures (Benefit for short) involved three items (e.g. “Adher-ence to COVID-19 precautionary measures recommended by the governmentreduces the chances of having COVID-19”) and displayed a Cronbach’s alpha of.89; (4) Perceived Barrier for Adherence to COVID-19 Precautionary Measures(Barrier for short) contained six items (e.g. “Adherence to COVID-19 precau-tionary measures recommended by the government disrupts your daily life”),with a Cronbach’s alpha of .74; and (5) Cue-to-action for Adherence to COVID-19 Precautionary Measures (Cue-to-action for short) was composed of eightitems and focused on external cues (e.g. “How often do you receive informationfrom public media about COVID-19 precautionary measures recommended bythe government?”), with a Cronbach’s alpha of .68.All of the constructs adopted a 5-point Likert scale from 1 = stronglydisagree to 5 = strongly agree, except that a 5-point Likert scale of frequencywas designed for cue-to-action (1 = never, 5 = always). A scale score was com-puted for each construct by averaging the scores of all the items involved in thescore. A higher scale score represented a higher level of the correspondingfactor.Social AxiomsSocial cynicism and reward for application were assessed by two eight-item sub-scales of the Social Axioms Survey (Leung et al., 2012) on a 5-point Likert scale(1 = strongly disbelieve, 5 = strongly believe). Social cynicism evaluates towhat extent respondents believe human nature and the social world will producenegative consequences (e.g. “People create hurdles to prevent others from suc-ceeding.”). Reward for application entails the belief that positive outcomes canbe achieved as a result of people’s use of effort, knowledge, careful planning,and other resources (e.g. “One will succeed if he/she really tries.”). A higher sub-scale score represented a higher level of the corresponding social axiom con-struct. The internal reliability of social cynicism and reward for application was.79 and .88, respectively.Demographic VariablesDemographic items included gender, age, educational attainment (six levels fromno formal education to tertiary level and each level was converted to years ofeducation for analysis), and work status (six categories of employed [full- orpart-time], unemployed, retired, student, homemaker, and others). Respondentsalso responded to whether they had ever had COVID-19.6 TONG ET AL.© 2020 International Association of Applied Psychology

Statistical AnalysisWe first conducted preliminary analyses in SPSS 25.0 to explore the extent ofadherence to each of the precautionary measures in order to identify the preva-lence of strong adherence across various precautionary measures. Second, asso-ciations among adherence, HBM factors, and social axioms were examined withPearson’s r for bivariate correlation in SPSS 25.0 and then with one multivariateregression that included the adherence to all six types of precautionary measuresaltogether to test the hypothesised multivariate association in Mplus 7.3. Thedemographic effects of gender, age, and years of education were controlled forin the multivariate regression. Because none of the respondents reported experi-ence of the COVID-19 infection, this indicator showed no variance and hencehas not been included in the analysis. The missing values were handled by arobust form of Full Information Maximum Likelihood, maximum likelihood esti-mation with robust standard errors (MLR), which also does not assume multi-variate normality; however, the cases with missing values at X-position wereexcluded from the model by default of MLR.RESULTSPreliminary AnalysesNone of the respondents reported experience of having COVID-19. The respon-dents’ adherence to each of the COVID-19 precautionary measures was consid-ered as strong if a practice frequency of “often” (4 points on the 5-point scale) orabove was reported. Most respondents showed strong adherence to face maskwearing and proper handwashing (96.4% and 79.1%, respectively), while overhalf often engaged in proper toilet flushing (72.6%), avoiding touching the face(63.6%), and carrying hand sanitiser (59.8%). However, only 42.3 per centreported strong adherence to social distancing.Associations among Adherence, HBM Factors, andSocial AxiomsTable 1 demonstrates the bivariate associations among adherence to COVID-19precautionary measures, HBM factors, and two social axioms. Following theguideline of Cohen (1988), a bivariate Pearson’s r < .10, the small effect size,was not further interpreted, while a significance level of .01 provides a morestringent result than that of a significance level of .05. For HBM factors, per-ceived benefit displayed a positive association with adherence to proper hand-washing, face mask wearing, and social distancing (r = .12 to .15, p < .01),while perceived barrier showed a negative association with adherence to properADHERENCE TO COVID-19 PRECAUTIONARY MEASURES 7© 2020 International Association of Applied Psychology

TABLE1BivariateCorrelationsamongAdherence,HBMFactors,andSocialAxioms(N=616)12345678910111213Adherence1.Properhandwashing12.Facemaskwearing.23***13.Socialdistancing
.01.11**14.Avoidingtouchingface.10*.22***.0315.Propertoiletflushing.17***.16***.15***.13**16.Carryinghandsanitiser.18***12**.12**.07.30***1HBMfactors7.Susceptibility
.02
.04.01
.03.06.00118.Severity.06.07
.03.04.18***.01.24***19.Benefit.14**.15***.12**.09†.09†.09†
.12**.16***110.Barrier
.10*
.11**.02
.18***
.09†
.09†.26***.11**
.11**111.Cue-to-action.07.07.11**
.03.08†.17***.09†.20***.22***.10*1Socialaxioms12.Socialcynicism
.14***
.20***
.04
.19***
.08†
.11**.26***.06
.14**.26***
.08113.Rewardforapplication.05.12**.12**.06.15***.16***
.10*.07.21***
13**.06
.021M(SD)4.01(0.91)4.83(0.51)3.30(1.13)3.73(1.07)3.91(1.24)3.53(1.38)2.55(1.29)3.80(0.68)4.33(0.57)2.60(0.71)3.44(0.62)2.85,(0.68)3.86(0.64)Note:*p<.05;**p<.01;***p<.001.†p<.05butrvaluedoesnotreachasmalleffectsize(lowerthan0.10).8 TONG ET AL.© 2020 International Association of Applied Psychology

TABLE2MultivariateRegressionofAdherenceinRelationtotheHBMandSocialAxiomsConstructs(N=575)1.Properhandwashing2.Facemaskwearing3.Socialdistancingb[95%CI]pb[95%CI]pb[95%CI]PSusceptibility0.03[
0.068,0.126].560.02[
0.053,0.086].640.03[
0.061,0.118].54Severity0.02[
0.072,0.114].660.06[
0.040,0.158].24
0.07[
0.172,0.023].13Benefit0.11[0.022,0.202].020.08[0.015,0.154].020.09[0.001,0.182].047Barrier
0.08[
0.160,0.007].07
0.04[
0.120,0.035].280.05[
0.051,0.142].35Cue
to-action0.05[
0.045,0.145].300.02[
0.073,0.103].740.10[0.006,0.202].04Socialcynicism
0.10[
0.190,
0.005].04
0.17[
0.252,
0.080]<.001
0.03[
0.127,0.068].56Rewardforapplication0.01[
0.090,0.116].800.11[
0.007,0.220].070.11[0.014,0.210].03Gender0.07[
0.014,0.148].11
0.02[
0.093,0.060].68
0.02[
0.104,0.059].59Age
0.04[
0.150,0.063].42
0.04[
0.133,0.066].510.04[
0.068,0.147].47Yearsofeducation
0.003[
0.110,0.105].96
0.05[
0.150,0.051].340.03[
0.072,0.136].54R2=0.049,p=.01R2=0.065,p=.005R2=0.045,p=.024.Avoidingtouchingface5.Propertoiletflushing6.Carryinghandsanitiserb[95%CI]pb[95%CI]pb[95%CI]PSusceptibility0.03[
0.067,0.121].570.07[
0.19,0.154].130.06[
0.035,0.145].23Severity0.08[
0.007,0.169].070.13[0.034,0.226].01
0.04[
0.128,0.057].45Benefit0.03[
0.056,0.112].510.05[0.042,0.136].300.04[
0.054,0.132].41Barrier
0.11[
0.200,
0.029].01
0.09[
0.169,
0.001].048
0.06[
0.154,0.030].19Cue-to-action
0.05[
0.145,0.042].280.02[
0.081,0.115].730.13[0.032,0.229].01Socialcynicism
0.18[
0.265,
0.100]<.001
0.06[
0.156,0.036].22
0.07[
0.158,0.021].13Rewardforapplication0.001[
0.090,0.091].990.12[0.030,0.215].010.15[0.064,0.242].001Gender0.06[
0.016,0.143].120.10[0.019,0.179].020.14[0.058,0.214].001Age0.08[
0.035,0.186].18
0.04[
0.143,0.060].42
0.12[
0.227,
0.010].03ADHERENCE TO COVID-19 PRECAUTIONARY MEASURES 9© 2020 International Association of Applied Psychology

TABLE2(CONTINUED)1.Properhandwashing2.Facemaskwearing3.Socialdistancingb[95%CI]pb[95%CI]pb[95%CI]PYearsofeducation
0.02[
0.118,0.079].700.003[
0.092,0.098].94
0.01[
0.105,0.091].89R2=0.076,p=.001R2=0.074,p=.001R2=0.093,p<.001Note:Themissingvalueswerehandledbymaximumlikelihoodestimationwithrobuststandarderrors(MLR)inthemodelwhile41caseswithmissingvaluesatX-positionwereexcludedfromtheanalysisbydefaultofMLR.HBM,HealthBeliefModel.10 TONG ET AL.© 2020 International Association of Applied Psychology

handwashing, face mask wearing, avoiding touching face (r =
.10 to
.18,p < .05 to < .001). Cue-to-action was positively associated with two precaution-ary behaviors, including social distancing and carrying hand sanitiser (r = .11and .17, p < .01 and < .001); whereas perceived severity was positively associ-ated with proper toilet flushing (r = .18, p < .001). For two social axioms, socialcynicism was negatively associated with proper handwashing, face mask wear-ing, avoiding touching face, and carrying hand sanitiser (r =
.11 to
.20,p < .01 to < .001); in contrast, reward for application was positively associatedwith face mask wearing, social distancing, proper toilet flushing, and carryinghand sanitiser (r = .12 to .16, p < .01 to < .001).The multivariate associations between adherence to COVID-19 precautionarymeasures and HBM/social beliefs were further explored with the multivariateregression analysis, in which gender, age, and years of education were controlledfor (see Table 2). Except for perceived susceptibility showing a non-significantassociation with all six precautionary behaviors, the other four HBM factors andtwo social axioms all demonstrated significant associations with adherence to atleast one precautionary measure and in the expected directions. Specifically, per-ceived benefit was positively associated with proper handwashing, face maskwearing, and social distancing (b = 0.08 to 0.11, p < .05), while perceived bar-rier was negatively associated with avoiding touching face as well as proper toi-let flushing (b =
0.09 to
0.11, p < .05). Cue-to-action was positivelyassociated with carrying hand sanitiser and social distancing (b = 0.10 to 0.13,p < .05), whereas perceived severity was positively associated with proper toiletflushing (b = 0.13, p = .01). As for the two social axioms, social cynicism wasnegatively associated with proper handwashing, avoiding touching face, and facemask wearing (b =
0.10 to
0.18, p < .05), while reward for application waspositively associated with proper toilet flushing, carrying hand sanitiser, andsocial distancing (b = 0.11 to 0.12, p < .05).DISCUSSIONThe present study examined residents’ adherence to six types of COVID-19 pre-cautionary measures in Macao, where none of these measures were enforced bylaw and no penalty was imposed for noncompliance. Among the six precaution-ary measures, we found that face mask wearing in public places was most likelyto be adhered to (i.e. 96.4% often or always), followed by proper handwashing(i.e. 79.1% often or always). The findings were consistent with similar studies inEast Asia (e.g. Lee & You, 2020) demonstrating that people showed strongadherence to personal hygiene measures. A plausible underlying mechanismmay lie in Asian health beliefs regarding these personal hygiene practices. Wadaet al. (2012) argued that face mask wearing in public places was common insome Asian countries, especially during influenza seasons, because peoplebelieve that it helps prevent respiratory infections; in addition, they also showedADHERENCE TO COVID-19 PRECAUTIONARY MEASURES 11© 2020 International Association of Applied Psychology

that face mask wearing was associated with other positive health behaviors, suchas handwashing. Their arguments were consistent with our findings that per-ceived benefit was positively related to these COVID-19 precautionary mea-sures. Nevertheless, one should note that social cynicism was negatively relatedto proper hand washing and face mask wearing in the present study; it may sug-gest that people who had a negative world view and mistrust in social institutionswere less likely to follow the precautionary measures recommended by authori-ties. Further study may investigate whether the social cynics were more receptiveto misinformation or conspiracy theories against practices proposed by theauthorities.Social distancing, protecting people from virus-carrying droplets, is anothermajor preventive measure advocated by the World Health Organization (2020).Unfortunately, our sample showed poor adherence to it (i.e. 42.3%) despite itsimportance. Practicing social distancing requires effort and resources to over-come the inconvenience or social norms against it, which is particularly difficultfor young people (Andrews, Foulkes, & Blakemore, 2020). There were limitedempirical evidence testing factors that may influence adherence to social distanc-ing. Our findings addressed this missing link and suggested that strategies of pro-viding more resources through more exposure to cue-to-action (e.g. posters orgovernment broadcasts) may promote adherence to social distancing. Addition-ally, we identified that those who believed that positive outcomes would followan investment of effort and resources were more likely to adhere to social dis-tancing. Future research may also consider including other potential factors ofadherence to social distancing in addition to the HBM constructs and socialaxioms. For example, Andrews et al. (2020) proposed a social norm favoringsocial distancing, a community-level factor, that can be a promising element toenhance one’s adherence to social distancing, especially for young people.Based on our findings, adherence to different types of precautionary measureswas correlated with four HBM factors (i.e. perceived severity, perceived benefit,perceived barrier, and cue-to-action) and two generalised beliefs (i.e. social cyni-cism and reward for application) to different extents. Similar to the findings ofJones et al. (2014), the HBM as a whole may improve adherence, but the specificHBM factors that work best may vary across behaviors. Consistent with our find-ings concerning perceived severity, Harper et al. (2020) reported a correlationbetween risk perception and COVID-19-related behavioral variations. Interven-tions, targeting perceived severity, typically involve providing information onrisk factors and the health consequences (e.g. Jones, Jones, & Katz, 1988; Kelly,Zyzanski, & Alemagno, 1991). Weinstein and Klein (1995) argued that people,particularly in the younger age groups, may be too optimistic and thus wouldundermine the effectiveness of the intervention. The solution proposed by Wein-stein (1983) was simple; that is, to reduce excessive optimism by providing addi-tional information (e.g. figures on mortality) to their peers because information12 TONG ET AL.© 2020 International Association of Applied Psychology

linking the enactment of behaviors and specific facts about disease transmissionmay provide a realistic appraisal of risky behaviors.Perceived benefit, with positive valence, and perceived barrier, with negativevalence, were both related to COVID-19 precautionary behaviors in this study.Consistent with what McCaul and Wold proposed (2002), our findings suggestthat perceived benefit and perceived barrier may contribute to adherence to thesebehaviors during the pandemic, and thus a better understanding of these two fac-tors can be a requisite for related interventions to work. Previous studies havesuggested that tailored messages can be effective in promoting the perceivedbenefit of health behaviors in specific target groups (e.g. McCaul & Wold, 2002;Nansel et al., 2002). Given that COVID-19 is highly infectious, precautionarybehaviors not only are beneficial to oneself but also can contribute to the com-munity health as a whole. Therefore, the perception of “benefits to others” mayalso be promoted in related health campaigns. In addition, future campaigns areadvised to take into account whether sufficient and consistent information isbeing provided to change the perception of barriers and inform the public of pre-cautionary behaviors. Special attention should be paid to common barriers tohealth behaviors, such as side effects, inconvenience, cost, and peer pressure(Jones et al., 2014). For example, wearing a face mask may be considered as vio-lating peer norms at the beginning of the pandemic, which may be overcome byallowing specific groups, such as young people, to take part in creating theirown promotion campaigns.As hypothesised, cue-to-action was found to be positively associated withadherence to COVID-19 precautionary measures in our study. Although Noar,Benac, and Harris’s (2007) review pointed out the general effectiveness ofHBM-based interventions for health promotions, intervention studies based oncue-to-action were relatively rare (Jones et al., 2014) and some past findingsmay not be effective in the digital era when traditional media plays a less impor-tant role, especially among young people. Further cue-to-action study concerningpandemic/epidemic prevention could focus on personalised reminders (e.g.mobile health) and workshops directed toward groups with specific needs (Caoet al., 2014; Odeny et al., 2014), such as older adults.Generally speaking, the present study supported that the HBM can be appliedto understanding individual differences in adherence to COVID-19 precautionarymeasures. Since the HBM assumes that people’s behaviors are influenced by per-ceived reality, changes in their subjective health beliefs (i.e. related to the diseaseand corresponding preventive behaviors) via multiple means (e.g. evaluativeassessment, protocol provision, and education) are the core theme of HBM-basedintervention (Jones et al., 1988). Our findings have lent extra empirical supportto the role of beliefs, as intrapersonal factors, on COVID-19 precautionarybehaviors. In line with Noar et al.’s (2007) assertion that HBM-based interven-tions were generally effective for health promotions based on their review study,our findings also offered insight for the promotion of precautionary measures viaADHERENCE TO COVID-19 PRECAUTIONARY MEASURES 13© 2020 International Association of Applied Psychology

HBM-based interventions in the COVID-19 pandemic and other possible pan-demics in the future, especially in the absence of any effective vaccines (Betsch,2020; Eaton & Kalichman, 2020). However, the relatively small effect sizes ofthe HBM factors imply that interventions based purely on the intrapersonal level(e.g. HBM factors) alone may be insufficient to substantially influence the adher-ence to precautionary measures. Further studies may consider the social-ecologi-cal model (McLeroy, Bibeau, Steckler & Glanz, 1988) that incorporates not onlyintrapersonal-level factors like HBM but also factors at the interpersonal level(e.g. social stigma), the community level (e.g. social norms) and the societallevel (e.g. community mobilisation) when designing effective interventions.The generalised belief, also known as social axioms, of reward for applicationand social cynicism were also found to be associated with COVID-19 precau-tionary behaviors in the present study. The mechanism linking social axioms andhealth behavior is not well documented. While some studies have suggested thattheir influences on behaviors may be indirect (Liem, Hidayat, & Soemarno,2009), other studies have shown that they have direct effects on behaviors (Bondet al., 2004a; Dinca & Iliescu, 2009; Kurman, 2011). Reward for application pro-motes effort exertion and favorable attitudinal reactions to striving (Zhou et al.,2009) and we also found its direct effect on practicing COVID-19 precautionarybehaviors. On the other hand, social cynicism had a negative relation with pre-cautionary behaviors, implying that a negative view toward authority or societyhas an undesirable influence on adherence to the precautionary measures pro-posed by the government. In fact, concerning COVID-19 responses or policies,there was distrust in government, misinformation perpetuated by vaccine acti-vists, or even conspiracy beliefs referring to the pandemic as a hoax (Limayeet al., 2020). Interventions aimed at reducing social cynicism may take time towork but it may be useful to prepare people for facing potential future pandemicsor accepting clinically approved vaccines. Some researchers have proposed thepotential relevance of social axioms to clinical interventions, such as sensitivityto individual beliefs (Lam, Bond, Chen, & Wu, 2010), but there is no empiricaltest of health interventions based on social axioms by far, and thus furtherresearch is warranted. In addition, other dimensions of social axioms may alsobe promising for future investigations. For instance, religiosity may have a nega-tive association with the adoption of precautionary behaviors because some ofthe recommended precautionary behaviors may be inconsistent with religiouspractices (Muhtada, 2020).There are a few limitations of this study. First, the present investigation onlyconsidered a limited number of intrapersonal factors based on the HBM andsocial axioms, while factors such as personality may also contribute to ourunderstanding. In addition, a more comprehensive picture of pandemic preven-tion can be further extended to the interpersonal, community, and societal levels.Indicators of exposure to COVID-19 (e.g. COVID-19 infection experience),behavioral factors (e.g. previous hygiene habits), and socioeconomic status are14 TONG ET AL.© 2020 International Association of Applied Psychology

worth being controlled for, especially in regions with more infections. Second,given the cross-sectional design of the present study, it is not feasible to trace theinfluences of beliefs on precautionary behaviors over time, nor to make any cau-sal inferences. A longitudinal or experimental study that explores the relationshipof different HBM factors or social axioms with adherence to COVID-19 precau-tionary measures will further improve our understanding of the effectiveness ofinterventions based on these beliefs. Given the varying impacts of differentHBM factors and social axioms across precautionary practices, it is premature toconclude what works best for interventions, and thus future investigation isneeded. The small effect size of HBM factors observed in our study may also befound in regions with few COVID-19 cases and low death rates (e.g. Taiwanand Japan), plausibly accompanied by a discovery of the limited role of suscepti-bility and severity, similar to our findings. In regions with more COVID-19cases and higher death rates, the importance of different HBM factors maychange and a cross-cultural study is required for further exploration. Third, theremay be self-report biases (e.g. social desirability) and systematic sampling errors(e.g. failure to reach all the eligible participants of the target population) in thisself-report survey, so readers are advised to take account of such limitations.Last but not least, it remains unknown how cultural factors would influenceCOVID-19 precautionary behaviors. Some researchers have proposed investigat-ing different cultural dimensions, such as tightness or looseness of social norms,to understand COVID-19-related responses (Bavel et al., 2020). Although theHBM and social axioms are assumed to be valid across cultures, the weightingof each factor is not; such information can be valuable in tailoring country-speci-fic prevention strategies.In summary, the present study examined adherence to different COVID-19precautionary measures among Chinese adults in a probability community sam-ple and provided support for the hypothesised relations among HBM factors,social axioms, and adherence to COVID-19 precautionary measures. To the bestof our knowledge, this is the first attempt to test whether the five HBM factorstogether with social axioms are related to precautionary behaviors against a pan-demic. Based on the results, we have discussed the potential applications ofspecific health beliefs and generalised beliefs to improving the design ofCOVID-19 precautionary promotion.REFERENCESAbraham, C., & Sheeran, P. (2005). The health belief model. In M. Conner & P. Normal(Eds.), Predicting health behavior (2nd edn., pp. 28–80). Philadelphia, PA: OpenUniversity Press.Abraham, C., Sheeran, P., Spears, R., & Abrams, D. (1992). Health beliefs and promotionof HIV-preventive intentions among teenagers: A Scottish perspective. HealthPsychology, 11(6), 363–370.ADHERENCE TO COVID-19 PRECAUTIONARY MEASURES 15© 2020 International Association of Applied Psychology

American Association for Public Opinion Research (2016). Standard definitions: Finaldispositions of case codes and outcome rates for surveys, 9th edition. AAPOR.Andrews, J.L., Foulkes, L., & Blakemore, S.-J. (2020). Peer influence in adolescence:Public-health implications for COVID-19. Trends in Cognitive Sciences, 24(8), 585–587.Bavel, J.J.V., Baicker, K., Boggio, P.S., Capraro, V., Cichocka, A., Cikara, M., . . .Willer, R. (2020). Using social and behavioural science to support COVID-19 pan-demic response. Nature Human Behaviour, 4(5), 460–471.Betsch, C. (2020). How behavioural science data helps mitigate the COVID-19 crisis.Nature Human Behaviour, 4(5), 438.Bond, M.H., Leung, K., Au, A., Tong, K.-K., & Chemonges-Nielson, Z. (2004a). Com-bining social axioms with values in predicting social behaviours. European Journal ofPersonality, 18(3), 177–191.Bond, M.H., Leung, K., Au, A., Tong, K.-K., de Carrasquel, S.R., Murakami, F., . . .Lewis, J.R. (2004b). Culture-level dimensions of social axioms and their correlatesacross 41 cultures. Journal of Cross-Cultural Psychology, 35(5), 548–570.Buldeo, P., & Gilbert, L. (2015). Exploring the health belief model and first-year students’responses to HIV/AIDS and VCT at a South African university. African Journal ofAIDS Research, 14(3), 209–218.Cao, Z.-J., Chen, Y., & Wang, S.-M. (2014). Health belief model based evaluation ofschool health education programme for injury prevention among high school studentsin the community context. BMC Public Health, 14(1), 26.Carico, R.R., Sheppard, J., & Thomas, C.B. (2020). Community pharmacists and commu-nication in the time of COVID-19: Applying the health belief model. Research inSocial and Administrative Pharmacy. https://doi.org/10.1016/j.sapharm.2020.03.017Centro de Controlo e Prevenc
~ao da Doenc
a (2020a). Pagina Electronica Especial ContraEpidemias Confluência. Retrieved from: https://www.ssm.gov.mo/apps1/PreventCOVID-19/pt.aspx#clg17458.Centro de Controlo e Prevenc
~ao da Doenc
a (2020b). Pagina Electronica Especial ContraEpidemias Educac
~ao em Saude. Retrieved from: https://www.ssm.gov.mo/apps1/PreventCOVID-19/en.aspx#clg17668.Coordenac
~ao and de Contingência do Novo Tipo de Coronavırus (2020). Tipo de Coro-navırus apela a manutenc
~ao dos canais de drenagem em habitac
~oes. Retrieved from:https://www.gov.mo/pt/noticias/221753/.Chen, S.X., & Bond, M.H. (2012). Lay beliefs about psychological and social problemsamong adolescents: Motivational and cognitive antecedents. Journal of Applied SocialPsychology, 42, 170–194.Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd edn.).Hillsdale, NJ: Erlbaum Associates.Dinca, M., & Iliescu, D. (2009). Linking social axioms with behavioral indicators andpersonality in Romania. In K. Leung & M.H. Bond (Eds.), Psychological aspects ofsocial axioms: Understanding global belief systems (pp. 145–162). New York:Springer.Direcc
~ao dos Servic
os de Estatıstica e Censos (2020). Estimativas da populac
~ao.Retrieved from: https://www.dsec.gov.mo/ts/#!/step2/PredefinedReport/pt-PT/1.16 TONG ET AL.© 2020 International Association of Applied Psychology

Eaton, L.A., & Kalichman, S.C. (2020). Social and behavioral health responses toCOVID-19: Lessons learned from four decades of an HIV pandemic. Journal ofBehavioral Medicine, 43(3), 341–345.Eisen, M., Zellman, G.L., & McAlister, A.L. (1992). A health belief model-social learningtheory approach to adolescents’ fertility control: Findings from a controlled field trial.Health Education Quarterly, 19(2), 249–262.Gaziano, C. (2008). Last-birthday selection. In P.J. Lavrakas (Ed.), Encyclopedia ofsurvey research methods, Vol. 1 (pp. 417–418). Thousand Oaks, CA: SAGEPublications.Harper, C.A., Satchell, L.P., Fido, D., & Latzman, R.D. (2020). Functional fear predictspublic health compliance in the COVID-19 pandemic. International Journal of MentalHealth and Addiction. https://doi.org/10.1007/s11469-020-00281-5Hui, C.-M., & Bond, M.H. (2010). Relationship between social axioms and subjectivewell-being: The role of self-regulation. Journal of Psychology in Chinese Societies,11, 1–24.Jones, C.J., Smith, H., & Llewellyn, C. (2014). Evaluating the effectiveness of healthbelief model interventions in improving adherence: A systematic review. HealthPsychology Review, 8(3), 253–269.Jones, S.L., Jones, P.K., & Katz, J. (1988). Health belief model intervention to increasecompliance with emergency department patients. Medical Care, 26(12), 1172–1184.Kelly, R.B., Zyzanski, S.J., & Alemagno, S.A. (1991). Prediction of motivation andbehavior change following health promotion: Role of health beliefs, social support,and self-efficacy. Social Science & Medicine, 32(3), 311–320.Kurman, J. (2011). What I do and what I think they would do: Social axioms and beha-viour. European Journal of Personality, 25(6), 410–423.LaBrosse, L., & Albrecht, J.A. (2013). Pilot intervention with adolescents to increaseknowledge and consumption of folate-rich foods based on the Health Belief Model.International Journal of Consumer Studies, 37(3), 271–278.Lam, B.C.P., Bond, M.H., Chen, S.X., & Wu, W.C.H. (2010). Worldviews and individualvulnerability to suicide: The role of social axioms. European Journal of Personality,24(7), 602–622.Lee, M., & You, M. (2020). Psychological and behavioral responses in South Korea dur-ing the early stages of Coronavirus Disease 2019 (COVID-19). International Journalof Environmental Research and Public Health, 17(9), 2977.Leung, K., & Bond, M.H. (Eds.) (2009). Psychological aspects of social axioms. NewYork: Springer.Leung, K., Lam, B.C.P., Bond, M.H., Conway, L.G., Gornick, L.J., Amponsah, B., . . .Zhou, F. (2012). Developing and evaluating the Social Axioms Survey in eleven coun-tries: Its relationship with the five-factor model of personality. Journal of Cross-Cultural Psychology, 43(5), 833–857.Liem, A.D., Hidayat, S.S., & Soemarno, S. (2009). Do general beliefs predict specificbehavioral intentions in Indonesia? The role of social axioms within the theory ofplanned behavior. In K. Leung & M.H. Bond (Eds.), Psychological aspects of socialaxioms. International and Cultural Psychology (pp. 217–238). New York: Springer.ADHERENCE TO COVID-19 PRECAUTIONARY MEASURES 17© 2020 International Association of Applied Psychology

Limaye, R.J., Sauer, M., Ali, J., Bernstein, J., Wahl, B., Barnhill, A., & Labrique, A.(2020). Building trust while influencing online COVID-19 content in the social mediaworld. The Lancet Digital Health, 2(6), e277–e278.Lin, P., Simoni, J.M., & Zemon, V. (2005). The health belief model, sexual behaviors,and HIV risk among Taiwanese immigrants. AIDS Education and Prevention, 17(5),469–483.Lux, K.M., & Petosa, R. (1994). Using the health belief model to predict safer sex inten-tions of incarcerated youth. Health Education Quarterly, 21(4), 487–497.Maier, B.F., & Brockmann, D. (2020). Effective containment explains subexponentialgrowth in recent confirmed COVID-19 cases in China. Science, 368(6492), 742–746.Mantler, T. (2013). A systematic review of smoking youths’ perceptions of addiction andhealth risks associated with smoking: Utilizing the framework of the health beliefmodel. Addiction Research & Theory, 21(4), 306–317.McCaul, K.D., & Wold, K.S. (2002). The effects of mailed reminders and tailored mes-sages on mammography screening. Journal of Community Health, 27(3), 181–190.McLeroy, K.R., Bibeau, D., Steckler, A., & Glanz, K. (1988). An ecological perspectiveon health promotion programs. Health Education & Behavior, 15(4), 351–377.Muhtada, D. (2020). Religion and COVID-19 mitigation. The Jakarta Post. Retrievedfrom: https://www.thejakartapost.com/academia/2020/03/26/religion-and-covid-19-mitigation.html.Mukhtar, S. (2020). Mental health and emotional impact of COVID-19: Applying HealthBelief Model for medical staff to general public of Pakistan. Brain, Behavior, andImmunity, S0889–1591(0820), 30463.Nansel, T.R., Weaver, N., Donlin, M., Jacobsen, H., Kreuter, M.W., & Simons-Morton,B. (2002). Baby, be safe: The effect of tailored communications for pediatric injuryprevention provided in a primary care setting. Patient Education and Counseling, 46(3), 175–190.Noar, S.M., Benac, C.N., & Harris, M.S. (2007). Does tailoring matter? Meta-analyticreview of tailored print health behavior change interventions. Psychological Bulletin,133(4), 673–693.N€othling, J., & Kagee, A. (2013). Acceptability of routine HIV counselling and testingamong a sample of South African students: Testing the Health Belief Model. AfricanJournal of AIDS Research, 12(3), 141–150.Odeny, T.A., Newman, M., Bukusi, E.A., McClelland, R.S., Cohen, C.R., & Camlin,C.S. (2014). Developing content for a mHealth intervention to promote postpartumretention in prevention of mother-to-child HIV transmission programs and early infantdiagnosis of HIV: A qualitative study. PLoS One, 9(9), e106383.Rosenstock, I.M. (1974). Historical origins of the health belief model. Health EducationMonographs, 2(4), 328–335.Safdar, S., Lewis, J.R., & Daneshpour, M. (2006). Social axioms in Iran and Canada:Intercultural contact, coping and adjustment. Asian Journal of Social Psychology, 9(2), 123–131.Singelis, T.M., Hubbard, C., Her, P., & An, S. (2003). Convergent validation of the SocialAxioms Survey. Personality and Individual Differences, 34(2), 269–282.Tola, H.H., Shojaeizadeh, D., Tol, A., Garmaroudi, G., Yekaninejad, M.S., Kebede, A.,. . . Klinkenberg, E. (2016). Psychological and educational intervention to improve18 TONG ET AL.© 2020 International Association of Applied Psychology

tuberculosis treatment adherence in Ethiopia based on health belief model: A clusterrandomized control trial. PLoS One, 11(5), e0155147.Tong, K.-K., Chen, J.H., & Wu, A.M.S. (2019). Application of health belief model topractice of responsible gambling. Journal of Gambling Studies, 35(3), 1047–1062.Wada, K., Oka-Ezoe, K., & Smith, D.R. (2012). Wearing face masks in public during theinfluenza season may reflect other positive hygiene practices in Japan. BMC PublicHealth, 12(1), 1065.Wang, Y., Wu, A.M.S., & Lau, J.T.F. (2016). The health belief model and number ofpeers with internet addiction as inter-related factors of Internet addiction among sec-ondary school students in Hong Kong. BMC Public Health, 16(1), 272.Weinstein, N.D. (1983). Reducing unrealistic optimism about illness susceptibility.Health Psychology, 2(1), 11–20.Weinstein, N.D., & Klein, W.M. (1995). Resistance of personal risk perceptions to debi-asing interventions. Health Psychology, 14(2), 132–140.World Health Organization (2020). Coronavirus disease (COVID-19) advice for the pub-lic. Retrieved from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/advice-for-public.Wu, A.M.S., Lau, J.T.F., Ma, Y.L., & Lau, M.M.C. (2015). Prevalence and associatedfactors of seasonal influenza vaccination among 24- to 59-month-old children in HongKong. Vaccine, 33(30), 3556–3561.Zhao, J., Song, F., Ren, S., Wang, Y., Wang, L., Liu, W., . . . Sun, Y. (2012). Predictorsof condom use behaviors based on the Health Belief Model (HBM) among female sexworkers: A cross-sectional study in Hubei Province, China. PLoS ONE, 7(11),e49542.Zhou, F., Leung, K., & Bond, M.H. (2009). Social axioms and achievement across cul-tures: The influence of reward for application and fate control. Learning andIndividual Differences, 19(3), 366–371.ADHERENCE TO COVID-19 PRECAUTIONARY MEASURES 19© 2020 International Association of Applied Psychology