Prevailing research on individuals’ compliance with public health related behaviours during the COVID-19 pandemic tends to study composite measures of multiple types of behaviours, without distinguishing between different types of behaviours. However, measures taken by governments involve adjustments concerning a range of different daily behaviours. In this study, we seek to explain students’ public health related compliance behaviours during the COVID-19 pandemic by examining the underlying components of such behaviours. Subsequently, we investigate how these components relate to individual attitudes towards public health measures, descriptive norms among friends and family, and key demographics. We surveyed 7,403 university students in ten countries regarding these behaviours. Principal Components Analysis reveals that compliance related to hygiene (hand washing, coughing behaviours) is uniformly distinct from compliance related to social distancing behaviours. Regression analyses predicting Social Distancing and Hygiene lead to differences in explained variance and type of predictors. Our study shows that treating public health compliance as a sole construct obfuscates the dimensionality of compliance behaviours, which risks poorer prediction of individuals’ compliance behaviours and problems in generating valid public health recommendations. Affecting these distinct behaviours may require different types of interventions.
Compliance with public health measures set by authorities during the COVID-19 pandemic consists of two clearly distinct components: Social Distancing and Hygiene. There is significant variability among students in Social Distancing and Hygiene across countries. Attitudes towards regulations and descriptive norms are predictive of both behaviours, but are more strongly related to Social Distancing. Treating public health compliance as a simple construct obfuscates the dimensionality of compliance.
To dampen the spread of COVID-19
Yet, most studies focus solely on composite measures assessing compliance with multiple types of behaviours (
In sum, studies that focus on public health compliance as being a sole and coherent construct may obfuscate the potential dimensionality of COVID-19 compliance, and as a result lead to undertheorized models with poor prediction of individuals’ compliance, and unvalidated public health recommendations. To address this, we examine the extent to which compliance with key public health measures correlates with compliance with other measures in a large cross-national study of university students’ self-reported perception of and self-reported compliance regarding COVID-19 recommendations and restrictions. The importance of cross-national studies was highlighted in a recent review on how social and behavioural science can support COVID-19 pandemic response (
In research unrelated to pandemics, compliance or non-adherence behaviours have been studied in connection to medical recommendations for the chronically ill (for a review, see
The goal of COVID-19 recommendations is to bring about and maintain a change in individual behaviours that will make people less likely to get infected and infect others. For this to happen, an underlying assumption is that people will perceive these recommendations as appropriate and have favourable attitudes towards following them. Recent studies on attitudes towards COVID-19 recommendations also suggest overall high agreement and adherence with public health guidelines (
In addition to an individual's attitude towards specific behaviours, another central factor in psychological theories of health behaviours is the role of behavioural norms in individuals' social context. Norms are powerful shapers of behaviour (
We examine the extent to which compliance with key public health measures correlates with compliance with other measures, and if these behaviours differ across and within student populations in distinct countries. We use Principal Components Analysis (PCA) to examine underlying components of compliance behaviour. Moreover, using the international setting of the dataset we examine how the different compliance components acquired in step one vary across countries. Finally, we study whether a set of individual attitudes towards public health measures, descriptive norms among friends and family, and key demographics are differently related to the compliance components unearthed using multiple regression analysis.
We surveyed 7,403 students from late April to the beginning of May 2020 (week 17 through 19) at twelve universities in ten countries: Belgium, Colombia, France, Germany, India, Ireland, Italy, the Netherlands, Portugal, Spain and Sweden. We used an online survey based on the Qualtrics software, approved in advance by the Internal Review Board of the Erasmus University Rotterdam.
At the time of data collection, all countries had initiated various recommendations and restrictions regarding health-related behaviour. Eight of the countries were in complete lockdown (India, Colombia, Spain, Italy, Portugal, Ireland, Belgium, France), meaning that inhabitants could only go outside if movements could be justified. However, specific regulations differed across countries. Measures were least strict in Sweden, followed by the Netherlands. For an overview of regulations applicable across countries at the time of data collection see
Students have been shown to be a key group for studies on compliance behaviours for several reasons: with former general lockdown measures across the world having been relaxed, infection levels have started to rise in late summer of 2020 and in Europe as well as the United States, new cases are mostly found among the younger generation and have been linked to student gatherings and parties (
The survey could be completed in English, Dutch, French or Spanish. Translations were made by a native speaker, reviewed by another native speaker and if necessary adapted after consultation between both translators. A pre-test was conducted with Dutch students
Descriptive sample statistics are presented as
In this section we describe all measures used for analyses. Descriptive statistics for all variables and the anticipated outcome variables of the PCA are presented as
Compliance was measured using nine items revolving around different behaviours related to the recommendations and restrictions by governments. The behaviours investigated are listed in
Item | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ||
---|---|---|---|---|---|---|---|---|---|---|
1. I avoided touching my face | 3.17 | 1.26 | ||||||||
2. I coughed and sneezed into my elbow and/or used a handkerchief | 4.46 | .84 | .27 | |||||||
3. I washed my hands more often and longer | 4.23 | .86 | .31 | .25 | ||||||
4. When not at home I kept the advised distance between myself and others | 4.36 | .87 | .19 | .18 | .15 | |||||
5. I did not meet with others unless it was strictly necessary | 4.13 | 1.07 | .11 | .03 | .04 | .31 | ||||
6. I only went outside if it was strictly necessary | 3.91 | 1.17 | .15 | .07 | .03 | .28 | .59 | |||
7. I did not shake hands | 4.76 | .62 | .09 | .13 | .11 | .33 | .25 | .21 | ||
8. I did not visit others/have not had visitors | 3.82 | 1.27 | .13 | .08 | .05 | .27 | .63 | .51 | .22 | |
9. I have not visited elderly people or people who are vulnerable for health reasons | 4.56 | .92 | .08 | .11 | .05 | .11 | .18 | .17 | .13 | .29 |
Pearson’s correlations of the compliance items are presented for the full dataset in
Students report complying most with ‘not shaking hands’ and least with ‘avoiding touching their face’. Most variation was present for ‘visiting others/having visitors’, indicating that students differ most in their agreement with performing this behaviour. The least variation was found for ‘not shaking hands’, meaning that students answered relatively uniformly for this question.
Attitudes to public health measures is captured by two individual items revolving around the extent to which students report taking measures seriously and how they feel about the amount of measures taken in their country. ‘Taking Measures Seriously’ was captured by the following question: ‘
The descriptive norm was captured using one item on the degree to which friends and family of students have complied with the measures. The question that had to be answered was as follows: ‘
The following demographic variables were included: age (continuous), gender (0 = male, 1 = female) and relationship status (0 = not in a relationship, 1 = in a relationship).
To study the dimensionality of compliance we investigate how the nine compliance behaviours relate to each other and whether it is possible to create composite measures of students’ public-health related behaviour. We use PCA to identify orthogonal components explaining most of the variance in the data by reducing dimensions of the original set of items, while preserving as much information as possible. Parallel Analysis is used to determine the number of components that should be retained (
After obtaining the components of compliance by creating item-average scores, we examine how they correlate and how they vary across countries by studying descriptive statistics (mean and standard deviations).
Finally, we predict each compliance component using multiple regression analyses and the predictors described. The models include country dummies to control for country differences, a method recommended when the number of countries in a sample is low (< 50) (
The Kaiser-Mayer-Olkin measure verified the sampling adequacy for the PCA, KMO = .756 (
Item | Component 1 | Component 2 |
---|---|---|
Social Distancing | Hygiene | |
1. I avoided touching my face | .37 | |
2. I coughed and sneezed into my elbow and/or used a handkerchief | .30 | |
3. I washed my hands more often and longer | .26 | |
4. When not at home I kept the advised distance between myself and others | .17 | |
5. I did not meet with others unless it was strictly necessary | -.35 | |
6. I only went outside if it was strictly necessary | -.29 | |
7. I did not shake hands | .10 | |
8. I did not visit others/have not had visitors | -.30 | |
9. I have not visited elderly people or people who are vulnerable for health reasons | -.03 |
Looking at the items that cluster on the same components in
We also conducted PCAs on the separate country samples. In eight out of ten countries, parallel analysis confirms that two factors should be retained. In two countries, the parallel analysis indicates that one component should be retained: Spain and Ireland. Looking closely at these country sub-group samples, our interpretation is that the one-factor structure arises in the Spanish sample due to Spanish students indicating high compliance on both social distancing and hygiene items, meaning that all items load highly (> .40) on the first component. For Ireland, the interpretation is less clear since all items except avoiding ‘touching one’s face’ and ‘washing hands’ load highly (> .40) on the first component. These two hygiene-related items load highly on the second component, which seems to hint at a two-factor structure. The somewhat divergent pattern in the Irish sub-sample may be caused by the relatively small sample size of Irish students (
To check whether compliance behaviours can be understood as a similar two-dimensional construct across countries, we compared item loadings on the first two principal components of each country with the pattern of loadings extracted for the whole sample. This is done by following the procedure advised by researchers dealing with evaluation of degree of cross-cultural replication (
Country | Component 1 |
Component 2 |
---|---|---|
Belgium | 1.00 | 1.00 |
Colombia | 0.98 | 0.99 |
Spain | 0.76 | 0.43 |
France | 1.00 | 0.96 |
India | 0.98 | 0.99 |
Ireland | 0.97 | 0.90 |
Italy | 0.99 | 0.99 |
Netherlands | 0.99 | 0.99 |
Portugal | 0.98 | 0.98 |
Sweden | 0.99 | 0.99 |
The structure was equal for all countries (> .95, good similarity), except for the second component in the Irish sample (> .85, fair similarity), and the loadings of both components in the Spanish sample (< .85, no similarity) (
Using the outcomes of the PCA, composite continuous scores can be created by taking the average of the items that belong to each component. By doing so we created two composite measures of different types of compliance: Social Distancing (Item 4-9) and Hygiene (Item 1-3). Internal consistency of items included in the Social Distancing construct was good (α = .73) while internal consistency of the Hygiene construct was weaker (α = .52). This lower reliability likely results from the small number of items related to Hygiene included in the survey.
Relating the item-average composite measures of Social Distancing and Hygiene to each other strongly supports that these are two distinct behaviours that are only weakly correlated (
Using the measures of students’ average compliance with Social Distancing and Hygiene obtained from the PCA, we examine how these behaviours vary between students in different countries. Finally, we calculate how much of the variation in compliance is dependent on the country that the student lives in.
To compare the extent to which students comply with measures in each country we compare the average scores of Social Distancing and Hygiene among all students in a country in
Country | Social Distancing |
Hygiene |
||
---|---|---|---|---|
Belgium | 4.31 | 0.61 | 3.84 | 0.74 |
Colombia | 4.41 | 0.59 | 4.06 | 0.71 |
Spain | 4.61 | 0.53 | 4.24 | 0.71 |
France | 4.27 | 0.69 | 4.09 | 0.69 |
India | 4.47 | 0.54 | 4.10 | 0.72 |
Ireland | 4.33 | 0.65 | 4.10 | 0.56 |
Italy | 4.50 | 0.51 | 3.87 | 0.78 |
Netherlands | 3.80 | 0.69 | 4.00 | 0.66 |
Portugal | 4.44 | 0.57 | 4.10 | 0.65 |
Sweden | 3.65 | 0.72 | 4.15 | 0.59 |
Total | 4.26 | 0.66 | 3.96 | 0.72 |
We calculated the intraclass correlation coefficient (ICC) to gauge the variance in students’ self-reported behaviour that can be attributed to the different country clusters, as opposed to variation between individual students regardless of country of residence
Dependent Variable | Social Distancing |
Hygiene |
||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Model 1 |
Model 2 |
Model 3 |
Model 4 |
|||||||||
Age | 0.11 | 0.00 | < .001 | 0.09 | 0.00 | < .001 | 0.11 | 0.00 | < .001 | 0.10 | 0.00 | < .001 |
Gender (1 = female) | 0.05 | 0.01 | < .001 | 0.04 | 0.01 | < .001 | 0.11 | 0.02 | < .001 | 0.10 | 0.02 | < .001 |
Relationship (1 = yes) | -0.04 | 0.01 | < .001 | -0.05 | 0.01 | < .001 | 0.09 | 0.02 | < .001 | 0.10 | 0.02 | < .001 |
Taking Measures Seriously | 0.26 | 0.01 | < .001 | 0.24 | 0.01 | < .001 | 0.17 | 0.01 | < .001 | 0.13 | 0.01 | < .001 |
Too Few Measures (dummy) | 0.12 | 0.01 | < .001 | 0.11 | 0.01 | < .001 | 0.07 | 0.02 | < .001 | 0.05 | 0.02 | < .001 |
Too Many Measures (dummy) | -0.02 | 0.02 | 0.047 | -0.02 | 0.02 | 0.062 | -0.02 | 0.02 | 0.203 | -0.01 | 0.03 | 0.305 |
Descriptive Norm | 0.15 | 0.01 | < .001 | 0.14 | 0.01 | < .001 | 0.08 | 0.01 | < .001 | 0.06 | 0.01 | < .001 |
Social Distancing | 0.15 | 0.01 | < .001 | |||||||||
Hygiene | 0.13 | 0.01 | < .001 | |||||||||
Adjusted |
0.273 | 0.287 | 0.116 | 0.134 | ||||||||
7217 | 7201 | 7221 | 7201 |
We find ‘Taking measures seriously’ to be positively related to both Social Distancing (
We also find that students reporting higher descriptive social norms in one’s environment (having friends and family more strictly following the measures) are more likely to comply with Social Distancing (
Regarding the control variables, we find students’ Age to be positively related to both Social Distancing (
By adding Hygiene and Social Distancing as control variables in Models 2 and 4 of
We used a continuous measure of compliance with multiple behaviours and showed that compliance with public health measures set by authorities during the COVID-19 pandemic consists of two clearly distinct components: Social Distancing and Hygiene. Despite the differences in the restrictive measures and prevalence of COVID-19 among the ten studied countries, our findings point towards high commonalities in regard to the dimensionality of compliance. The two types of behaviours are only weakly correlated with each other, and differently predicted by individual attitudes towards public health measures, descriptive norms among friends and family, and key demographics. In other words: Social Distancing does not necessarily go hand in hand with Hygiene. This means that one cannot simply rank students as ‘more or less compliant with COVID-19 measures’ (e.g.,
The contributions of this study are multiple. First, we show that Social Distancing and Hygiene are two distinct types of behaviours during the COVID-19 pandemic, and potentially also during other infectious diseases. With this finding we hope to inspire future research to study the behaviours separately and develop stronger predictive models for each behaviour. Assuming that compliance is unidimensional and/or mostly composed of behaviours related to “social” distancing is wrong and can result in a missed opportunity to correctly identify possibly different antecedents of these different behavioural dimensions. Our findings show that compliance with public health measures is best viewed as a multidimensional construct and this directly implies that both dimensions should be taken into account to design effective strategies, and when investigating, theorizing and modelling compliance (and pandemic related outcomes) (e.g.,
Second, we show that attitudes towards public policy and descriptive norms are more predictive of Social Distancing than for Hygiene. Given that Hygiene related behaviours are less salient (less visible) than behaviours related with Social Distancing, more routinized (automatic), and less problematized and discussed in the media, it is not surprising that they were shown to be less strongly connected with attitudes and norms. It is highly possible that thinking about the recommendations and restrictions related to COVID-19 is dominated by behaviours related with “social” distancing, and therefore reported attitudes and descriptive norms are more closely related with these behaviours than with Hygiene. Social distancing behaviours are more easily (and correctly) observable. In contrast,
Third, our study is based on a rather large sample compared to existing samples previously conducted on compliance during the COVID-19 pandemic. We found a stable distinction between Social Distancing and Hygiene both in the overall sample as well as when examining the specific country-samples. It should be mentioned that for two countries (Ireland and Spain) one component emerged from the PCA, indicating that Social Distancing and Hygiene are more related for students in these countries. This is likely explained by high levels of both Social Distancing and Hygiene in Spain and by a relatively small sample size (
Results of our study should be interpreted acknowledging the timing of data collection. The end of April 2020 was still in the early phase of the COVID-19 pandemic. Public health behaviours related to Hygiene and Social Distancing may change over time, while we implicitly model Social Distancing and Hygiene in this study as stable traits. We recognize that in reality these are dynamic behaviours, showing even daily fluctuations. Future research should investigate the temporal stability of both dimensions, using not only self-reported behaviours - which are likely affected by social desirability to a certain degree - but also measures of actual behaviours. Such an approach would also reduce the common method bias of a single survey being used to measure all variables of interest self-reported by the participants at the same point in time (
A strength of this study comes from the fact that we collected data on samples of students in ten different countries at a simultaneous relevant point in time. Yet, we were not able to avoid self-selection bias, which probably led to low compliance students being underrepresented. While we assume that their underrepresentation did not affect the findings about the dimensionality of compliance in any substantial degree, it is possible that due to the range restriction in our dependent variable the investigated predictor variables could have been compromised. Future data collection efforts should try to secure the participation of students such that those who are not complying highly are incentivised to participate.
We identified two distinct dimensions of compliance and investigated them using attitudes and descriptive norm variables. We hope that future research will build on our findings and use more elaborate models of behaviours of interest distinguishing between Social Distancing and Hygiene. A logical step would be to validate key constructs from central theories of health behaviours such as perceived behavioural control as in the Theory of Planned Behavior (
For this article, a dataset is freely available (
Supplementary Material 1 gives an overview of the COVID-19 regulations across countries at the time data was collected. Supplementary Material 2 presents descriptive statistics for the full sample. Supplementary Material 3 shows means, standard deviations and correlations for all variables part of the regression analyses. Supplementary Material 4 consists of component matrices of principal component analyses that were conducted using country samples. Supplementary Material 5 consists of the results of One-Way ANOVA’s testing the mean differences in compliance between countries. Finally, research data that was used for the study and a codebook explaining all variables in this data are part of the Supplementary Materials (for access see
Roy Thurik, Jinia Mukerjee and Olivier Torrès are members of LabEx Entreprendre of the Université de Montpellier (Montpellier Management, MOMA) funded by the French government (LabEx Entreprendre, ANR-10-Labex-11-01) as well as of the public research centre Montpellier Research in Management (EA 4557, Université de Montpellier).
In the paper and in our student survey we refer to ‘COVID-19’ and ‘COVID-19 health recommendations and restrictions’ as synonymous with the SARS-CoV-2 virus for the sake of simplicity and readability.
By social distancing behaviours we refer to “a constellation of behaviours that decrease close physical contact among non-household members” (
When we refer to students from a specific country in this paper, we mean students studying in that country, e.g., with Dutch students we refer to students that study in the Netherlands.
It should be noted that Social distancing has and can be used interchangeably with Physical Distancing. In our paper we refer to Social Distancing, because of its extensive use in literature and media and to avoid confusion that physical distancing only refers to "keeping the advised distance between self and others".
We note that ICC estimates may be unreliable due to the low number of countries in our sample (
The same models estimated without international students were all but identical, except for the coefficient ‘Too Many Measures’ in Model 2 (
While multilevel analysis is unreliable with only 10 countries included (
The authors have declared that no competing interests exist.
The authors have no support to report.