Introduction

At the time of writing, COVID-19 has held the world in its grasp for more than three years. With over 761 million cases and over 6.8 million deaths (World Health Organization 2023a), governments all over the world have taken measures to prevent the Coronavirus from spreading, such as social or physical distancing measures. Overall, adults show a high level of self-reported compliance to COVID-19 mitigation measures globally (Van Rooij et al. 2020; Wang et al. 2021). However, youths are known to show less compliance with public health measures, and social distancing measures in particular (Barari et al. 2020; Cohen et al. 2020; Park et al. 2020). Less is known about what motivated youth (defined here as 16 to 25 years old) to comply or not to comply with social distancing measures during the COVID-19 pandemic. Research is needed to better understand what makes youth comply (or not), and how governments can stimulate them to comply to reduce the spread of the Coronavirus. Reducing the spread of the Coronavirus is essential to protect those who are vulnerable or whose health is at risk.

There is limited empirical evidence about the factors that play a role in affecting compliance with behavioral measures in pandemics, especially for youth aged 16 to 25 years. The Health Belief Model (HBM) offers a starting point, describing factors that can initially induce people to adopt preventive health behavior. This is a widely used conceptual framework to explain changes to health-related behaviors and to inform interventions to change health behaviors. The HBM was developed in the 1950s to explain why people hardly participated in programs to prevent and detect diseases and was inspired by Cognitive Theory (Champion and Skinner 2008; Skinner et al. 2015).

The HBM consists of several constructs that predict whether and why someone will take action to prevent, detect, or control illness. These include perceived threat, perceived benefits, perceived barriers to engage in a behavior, self-efficacy, and cues to action (e.g., advice from others). The HBM can be applied to behaviors that reduce the risk of contracting an infectious disease (such as COVID-19). The first construct, ‘perceived threat’, is a combination of perceived susceptibility (the belief of how likely it is to become infected) and perceived severity (the belief about how serious contracting a disease is). The second construct, ‘perceived benefits’, can be explained as a belief about the positive outcomes or advantages of a recommended action to reduce the threat of a disease. This includes outcome efficacy, which refers to the belief about to what extent a particular behavior leads to a certain outcome. The third construct, ‘perceived barriers’, are beliefs about how possible obstacles to taking action can hinder engagement in health behavior. The fourth construct, ‘self-efficacy’, refers to the belief that one can successfully execute health behavior. Lastly, the construct ‘cues to action’ can be explained as internal or external cues that can trigger health behavior.

Perceived threat, benefits, barriers, and self-efficacy all concern health beliefs that may affect health behavior. These beliefs are influenced by sociodemographic (e.g., age, gender, ethnicity, education) and socioeconomic (e.g., insurance status) factors (Skinner et al. 2015). Cues to action may have a direct effect on health behavior or an indirect effect by influencing health beliefs (Skinner et al. 2015). A study by Clark et al. (2020) shows that outcome benefits (e.g., believing that following preventive measures helps to prevent the spread of the Coronavirus) are important for compliance to COVID-19 measures for (young) adults.

The mitigation measures that were put in place all over the world to prevent further transmission of COVID-19 (e.g., social distancing) applied for a substantial amount of time. These long-term mitigation measures can be seen as a chronic or maintenance stage of a crisis (Abdalla et al. 2021). The constantly changing mitigation measures (e.g., curfew) that are not long-term, but are only in place for a shorter period of time can be seen as an acute stage (Abdalla et al. 2021). The two stages are not separate, but exist next to each other. New additions to the acute mitigation stage may occur because of changing circumstances, such as an increase in infection rates, new virus variants, or a change in preventive measures, whereas the maintenance stage (in which measures as social distancing are maintained) remains for a longer period of time. Therefore, it would be useful to examine the maintenance of behavior change in addition to the HBM construct (Kwasnicka et al. 2016).

The maintenance of behavior change can be defined as “the continuous performance of a behavior following an initial intentional change at a level that significantly differs from the baseline performance in the intended direction” (Kwasnicka et al. 2016, p. 280). Theoretical explanations for the maintenance of behavior change in relation to health-related behaviors include maintenance motives, self-regulation, habits, resources, and contextual (environment and social) influences. These factors are related to each other (Kwasnicka et al. 2016).

The first factor, ‘maintenance motives’, can be explained as motives that enable regular gratification of new behavior. Examples of such motives are those focused on behavior enjoyment, the satisfaction with behavior outcomes, or the congruence of new behavior with someone’s identity, beliefs and values. ‘Self-regulation’ refers to a person’s efforts to monitor and regulate their new health behavior while simultaneously inhibiting dominant and automatic behavior, urges, emotions, or desires that may threaten the newly adopted behavior. The factor ‘habits’ refers to automatically triggered actions performed without conscious awareness. Habits develop after a period of successfully self-regulating new behavior. The fourth factor, ‘resources’, includes physical and psychological assets that can be relied on during the process of behavioral regulation. When resources are limited or depleted (e.g., due to mental health issues), this can hinder one’s self-regulatory capacities. Lastly, the factor ‘environmental and social influences’ can be explained as features of the social and environmental context of action which can either facilitate or hinder the maintenance of new behavior over time (e.g., social support, social identity, social norms, environmental changes) (Kwasnicka et al. 2016).

With respect to the latter two factors, several studies have been performed during the COVID-19 pandemic. Although youth have lower risk of serious COVID-19 illness compared to adults (older people and those with underlying medical conditions are more likely to develop serious illness) (World Health Organization, 2023b), the pandemic is taking a toll on youth mental health (Courtney et al. 2020, Khan et al. 2020). There have been multiple reports of increased mental health challenges for youth during the ongoing COVID-19 pandemic (such as depression, anxiety, suicide, and stress) (Loades et al. 2020; Moreira et al. 2020; O’Connor et al. 2021). The negative effect of the COVID-19 pandemic on mental health seems to be stronger for (older) youth than for adults (O’Connor et al. 2021; Samji et al. 2022).

While youth have mostly reported negative effects of the COVID-19 pandemic on their mental health, some have also reported positive outcomes (e.g., greater appreciation of the things they had taken for granted) (Cleofas 2021). While negative effects on mental health are in themselves worrying outcomes, it is possible that worse mental health might influence compliance with social distancing measures as well. An individual’s effort to actively control behavior (self-regulation) depends on their personal resources as well as other factors. Someone’s self-regulatory capacity is, for example, limited when their personal resources are limited or depleted due to stress or tiredness (Kwasnicka et al. 2016). Mental health is one example of a personal resource. This suggests that a decrease in personal resources (e.g., worse mental health) may lead to less compliance. This was found in a study by Koning et al. (2021), which found that youth with fewer mental health symptoms showed better compliance with social distancing measures. This is in line with results of Nivette et al. (2021), who found that youth with ‘anti-social potential’ were less compliant. In contrast, a different study found that anxiety towards COVID-19 resulted in more compliance with preventive measures (Harper et al. 2020). These results suggest that there might be a difference between internalizing and externalizing symptoms in terms of effects on compliance with preventive COVID-19 (i.e., pandemic) measures.

Other factors, such as the environmental and social context, may influence both conscious as well as automatic behavior, by either facilitating or hindering behavior change maintenance (Kwasnicka et al. 2016). An example of a social context factor can be found in natural mentoring. A natural mentor may be a non-parent relative, neighbor, teacher, (adult) friend, or someone from a religious community, who is a confidant and advocate for youth (Van Dam et al. 2018). They can provide support, give advice, or be a role model for youth (Spencer et al. 2016). Having access to a natural mentor might help youth comply with the preventive measures, because their natural mentor complies him- or herself (role model) or because their natural mentor advises youth to comply (norm setting). In line with the theory on maintenance of behavioral change, Koning et al. (2021) found that having a natural mentor might have a positive effect on compliance with social distancing measures. Additionally, support from a natural mentor can help overcome the difficulties of the COVID-19 pandemic, and help to ensure better or good mental wellbeing (Hagler and Rhodes 2018).

Current study

Knowledge on which factors might contribute to better youth compliance with preventive measures can inform government interventions to increase compliance among this specific target group, and so might contribute to less spreading of the Coronavirus and fewer COVID-19 infections. The current explorative interview study will combine the above-described behavioral models (HBM and maintenance of behavior change) to obtain a more complete view of the factors affecting youth compliance with the preventive COVID-19 social distancing measures in the Netherlands, and to consider whether the models are sufficient or might need to be expanded. The aim of this qualitative interview study is to explore which factors enable or encourage youth to comply with the preventive COVID-19 social distancing measures, more specifically the 1.5 meter social distancing rule. Various factors within the behavioral models will be explored, in particular mental health issues and natural mentorship.

In sum, the following research question is addressed: Which factors influence the compliance of youth with social distancing measures in the Netherlands? The sub-questions are: How well do youth comply with the 1.5 meter social distancing rule? Which factors from the behavioral models play a part in the compliance of youth with this rule? How do youth mental health issues and natural mentorship influence youth compliance with the 1.5 meter rule?

Methods

Sample

The sample consisted of 35 youth that were between 16 and 25 years old (M = 19.6, SD = 2.86) and who lived in the Netherlands. Participants were included from every state of the Netherlands. Eighteen youth were male, seventeen were female. Of those 35 participants, 31 were Dutch, one was Syrian, one was Somalian, one was Sudanese, and one was Gambian. Twenty-eight participants followed or finished vocational education and seven participants followed or finished academic education. Of the 35 participants, 18 lived with their parents, three lived alone, three lived together with their partner, four lived in student housing, four lived in an assisted living facility, two were homeless, and one participant lived in a mother-child institution.

Procedure

This interview study was approved by the ethics committee of the faculty of Social and Behavioral Sciences of the University of Amsterdam (2020-CDE-12362). The participants were recruited through purposive sampling. The youth had to be between 16 and 25 years old. To achieve a heterogenous sample, we aimed to include both youth from vocational and academic education, and to have an even distribution of sex. To include other valuable data, urban and disadvantaged youth were also included, as they usually do not participate in studies. This was done in a collaboration between the National Institute of Public Health and Environment (RIVM) (access to a large pool of youth from the Netherlands) and the University of Amsterdam (access to urban and disadvantaged youth) to achieve a representational sample. The aim was to include 35 participants, 20 participants by the RIVM and 15 participants by the University of Amsterdam. The participants were interviewed between May 30th 2020 and June 10th 2020, during the COVID-19 crisis. From June 1st 2020 the government of the Netherlands announced that restaurants, cafés, cinemas, secondary schools, museums, and other cultural institutions could re-open again (with a maximum of 30 persons) after a lockdown of two months. The 1.5 meter rule was still in place during the period of the interviews, as were other preventive measures. The 1.5 meter rule applied to all youth, and they had to keep distance between each other as well. See Appendix 1 for all COVID-19 measures stated by the Dutch government during the period the interviews took place.

Due to the COVID-19 measures, most interviews were conducted through video calls or regular phone calls. Four interviews were conducted face-to-face because the problematic background of these youth warranted personal contact. The interviews were conducted by a team of 11 interviewers from the RIVM and the University of Amsterdam, because all interviews had to take place between a short time frame to ensure that the COVID-19 measures were the same for all participants. Interviewers used a semi-structured topic list with all relevant topics and were instructed on how to conduct the interview (Appendix 2). At the start of each interview, informed consent was asked from each participant. After obtaining permission, the interviews and informed consent were recorded. The average duration of an interview was 43 minutes (range = 21-90 minutes). Two interviews were conducted in English, because these participants did not speak Dutch sufficiently. The rest of the interviews were conducted in Dutch. The interviews were transcribed verbatim.

Instruments

The semi-structured interview format consisted of three main interview topics: compliance with the 1.5 meter rule, perceived mental health issues and natural mentoring. In addition, the topic list included some demographic questions (age, gender, education, housing situation, and ethnicity) and the question whether the youth, or someone in their environment, is or were/was infected with COVID-19. See Appendix 2 for the complete topic list and Appendix 3 for the operationalization of the theory constructs.

COVID-19 Measure: 1.5 meter rule

Participants were asked what they thought about social distancing and how well they complied with it. Social distancing is one of the main COVID 19-measures, and in the Netherlands known as the ‘1.5 meter distance rule’. We explored to what degree they complied with this rule and what their reasons were to comply or not comply. Question examples are: “Why and when can you keep 1.5 meter distance and why and when are you unable to comply to 1.5 meter social distance?”.

Perceived mental health issues

The participants were asked to what degree the COVID-19 pandemic and the COVID-19 measures influenced how they were feeling and what emotions they felt. If they were feeling negative emotions, they were asked how those emotions influenced complying with the social distancing measures. For instance, when they were feeling alone, they were asked if their loneliness influenced how well they complied with the social distancing measures. A question example is: “How does the COVID-19 pandemic and the COVID-19 measures influence how you are feeling?”.

Natural mentoring

To get an idea whether natural mentorship influenced the compliance to the 1.5 meter measure, participants were asked whether they had a natural mentor (e.g., someone other than their parents that they could go to for advice and support), whether or not they had contact with a mentor during the COVID-19 pandemic, and whether or not they discussed the COVID-19 measures with a mentor. A question example is: “How do the conversations you have with your natural mentor influence your compliance with the measures?”.

Coding and analysis

We used reflexive thematic analysis (TA) to code the data (Braun and Clarke 2006; Braun and Clarke 2020). Reflexive TA can be seen as an umbrella term for various approaches. This allowed us to create codes beforehand, based on theory, but also allowed for additional codes based on the data from the interviews themselves (inductive coding) (Boeije 2005; Braun and Clarke 2020). First, we used the theoretical frameworks from the ‘prevention behavior framework COVID-19Footnote 1’ that is used by the Behavioral Corona Unit of the National Institute for Public Health and the Environment, which is based on the HBM and the theory of maintenance of behavior change, to create codes for compliance with the 1.5 meter rule (deductive coding). To add some nuance to those factors, subfactors were created during the coding (inductive coding). This resulted in 23 factors in total. All the factors and their operationalization for both compliance as well as non-compliance can be found in Appendix 4a. For example, the factor ‘cue to action’ has been operationalized in five subfactors, among others ‘knowing someone with COVID-19’, ‘a fine’, and ‘the government rules’, which specify the direction of the belief. During coding, a subfactor of the factor risk perception was added about trusting others (mostly family and friends) not to have the virus, which is slightly different than perceived susceptibility and perceived severity and therefore relevant to mention as a separate (sub)factor.

The topic about perceived mental health issues consisted of four broader codes about internalizing issues (e.g., anxiety), externalizing issues (e.g., anger), positive outcomes (e.g., more time for hobbies), and other negative outcomes (e.g., sleeping problems) and subcodes of the specific health issues (see Appendix 4b).

The topic about natural mentoring consisted of codes about who was the natural mentor (kin/non-kin and adult/non-adult), whether the interviewed youth spoke about COVID-19 and the measures with their natural mentor, to what degree this influenced their compliance to the preventive measures, and how the youth experienced support from (contact with) their natural mentor.

The transcripts were coded and analyzed using the software MAXQDA 2020 (VERBI software 2019). The first four authors started with coding the transcripts in two groups, which both consisted of two authors. The first group coded the compliance to the 1.5 meter rule and the factors mentioned by respondents for compliance, the other group coded perceived mental health issues and natural mentoring. To increase trustworthiness and credibility, five transcripts were coded by all coders. These were discussed and compared. When sufficient inter-rater-reliability was achieved, the rest of the transcripts were coded. Coders remained in contact with each other to discuss difficult codes. Dividing the participants in the three groups was also done by all the coders in consultation.

After the transcripts were coded, the codes were analyzed and potential relations between topics were noted following the criteria of thematic analysis and using analytical tools such as a code matrix (Braun and Clarke 2006). Based on the analysis of the question to what extent respondents comply with the 1.5 meter rule, we distinguished three groups of participants: 1) participants that were almost always compliant with the 1.5 meter rule, 2) almost never compliant with the 1.5 meter rule, and 3) sometimes compliant and sometimes not compliant with the 1.5 meter rule. Depending on the compliance group, each participant was assigned factors for compliance and/or factors for non-compliance. The three compliance groups, including factors for each participant, were used for further analysis of mental health and natural mentorship. The results are presented for each compliance group separately.

Results

Twenty-one participants stated that they always complied with the 1.5 meter rule or at least most of the time (i.e., the mainly compliant group), 12 stated complying with the 1.5 meter rule sometimes (i.e., the sometimes compliant group), and two indicated that they did not comply with the 1.5 meter rule at all (i.e., the non-compliant group). The demographics of the participants (age and sex) appeared to have no relation to their compliance with the 1.5 meter rule, according to the code matrix. For each of the three groups of participants we have described what factors for compliance and non-compliance seem most important, what mental health issues are reported by the participants, and to what extent a natural mentor is involved with the participants. These participant groups are presented in Table 1.

Table 1 Demographics and the frequencies of the most mentioned codes per group
Full size table

Group 1: Compliant most of the time

Seventeen of the 21 participants in the mainly compliant group stated that they complied with the 1.5 meter rule always or most of the time and specified why they follow this measure. The other four participants did not state any specific reason as of why they complied. This might be due to the fact that most interviews were conducted by phone, which might have hindered digging deeper. The most mentioned factor for complying with the 1.5 meter rule was motivation, more specifically feeling of solidarity with or feeling responsible for others, such as people with fragile health.

“I keep 1.5 meter distance, because I am aware of the fact that there is a greater chance of getting infected or infecting someone else with COVID-19 when you do not comply to this distance rule. As long as there is scientific evidence, you should follow it. And while the virus is still around, everyone should take their responsibility to avoid getting infected.” -Male, 25 years old

The second most mentioned reason was that they could follow the 1.5 meter rule because the physical environment facilitated keeping sufficient social distance from others. Regarding this, participants named supermarkets, shops, public spaces, and just being outside or on the street as examples of physical spaces where it is possible to keep a distance of 1.5 meter. The third most mentioned reason was that following the 1.5 meter rule has become a habit.

More than half of the participants mentioned at least two reasons for why they followed the 1.5 meter rule. Four different combinations of reasons for compliance were detected. First, compliance is fostered when youth are motivated to comply because they feel responsible for others and when the 1.5 meter rule has become a habit. Second, compliance is fostered when youth are motivated out of a feeling of responsibility for others and because the government says they have to comply or because of the risk of getting a fine in case of non-compliance (cue to action). Third, being motivated out of feeling responsible for others was often mentioned with a physical environment in which it is easy to keep 1.5 meter distance from others because there is sufficient space to do so. The fourth and final combination of reasons is being motivated out of a feeling of responsibility for others as well as considering the high risk of getting infected or infecting others with the Coronavirus (risk perception). This analysis suggests that being motivated to comply, and specifically feeling responsible for or solidarity with others, is particularly important for compliance with the 1.5 meter rule. Two participants mentioned motivation as their only reason for compliance, whereas the other participants stated another reason besides being motivated.

Regarding perceived mental health issues, most participants who stated that they always comply with the 1.5 meter rule experienced internalizing mental health issues. They mentioned anxiety, loss of motivation (e.g., for school) or loneliness. A few participants of this group mentioned externalizing mental health issues, such as anger. Some participants experienced other issues, like sleeping problems. Lastly, positive outcomes, such as having more time for sports or hobbies were also described by almost half of the participants. However, according to the code matrix, no explicit association between perceived mental health issues and following the 1.5 meter rule was found for the this group of youth who comply most of the time.

Regarding natural mentoring, most participants of the compliant group had a natural mentor to which most participants spoke about COVID-19 and the preventive measures. Additionally, half of the participants felt support from their natural mentor. Five participants had no natural mentor but mentioned that their parents or partner was their ‘natural mentor’. Half of the participants who spoke with their mentor about COVID-19 and the measures also mentioned that they followed the 1.5 meter rule because they were feeling responsible/solidarity towards others.

“I have spoken with my mother’s friend, who is like a second mother to me about the COVID-19 measures. Her father is 90 years old, and she has to be very cautious with who she is in contact with. She wants to reduce the infection risk as much as possible to avoid infecting her father. This raised awareness in me, to follow the 1.5 meter rule.” -female, 19 years old

Group 2: Sometimes compliant with the 1.5 meter rule

The most mentioned reason for compliance of the participants of this group was that they were motivated due to their solidarity with others. The second most stated reason was that they complied because the physical environment made it possible to keep 1.5 meter distance from others (e.g., outside on the street). The third and fourth most brought up reasons are: the risk of getting infected or infecting others is considered high (risk perception), believing other people might be infected with the virus/be contagious (risk perception). Eleven participants mentioned two or more reasons for their compliance. The combination that occurred the most was feeling solidarity with others (motivation) and the physical environment facilitating enough space to keep 1.5 meter distance. Another combination was the risk of getting infected or infecting others (risk perception) and the physical environment facilitating enough space to keep 1.5 meter distance.

The participants also articulated reasons as for why they do not always comply with the 1.5 meter rule. The most mentioned reason was that the physical environment does not facilitate enough space to keep 1.5 meter distance (e.g. in the supermarket). The second most stated reason is that the participant trusts others to not have the virus (risk perception), and therefore they do not keep a distance of 1.5 meter. Other often mentioned reasons were: having close contact with others was considered more important than the risk of getting infected (social barriers) and keeping distance is not the norm of the social group (social environment). The situation in which participants say they do not comply with the 1.5 meter rule, was often with family and/or friends. Four participants mentioned only one reason for their non-compliance and the rest two or more reasons. The most occurring combinations were: the participant trusts the other person to not have the virus and the physical environment does not facilitate enough space to keep 1.5 distance, and the participant trusts the other to not have the virus (risk perception) and they feel having close contact with others is more important than the risk of getting infected with the virus (social barriers).

The analysis showed that trusting others to not have the virus (risk perception) seems to be an important reason for non-compliance (particularly in situations with family and/or friends) and that the physical environment and ‘social barriers’ also seem to play a role in non-compliance. The combination of physical environment and risk perception occurs for both compliance (‘others may have the virus’) and non-compliance (‘trusting others to not have the virus’). Lastly, physical environment is also mentioned as a reason for both compliance and non-compliance.

“I can keep 1.5 meter distance at places like a tram stop, because I am waiting in one spot. But, when I have to board the tram or on the stairs at a train station I cannot keep 1.5 meter distance, because it is too busy and people are running to catch their train or tram” -female, 17 years old

Regarding perceived mental health issues, most participants of this group experienced internalizing mental health issues, with more than half of them mentioning anxiety (n = 6). Some participants of this group experienced externalizing mental health issues (e.g., anger) and four participants mentioned other issues (e.g., boredom). Almost half of the participants of this group described they experienced positive outcomes as well, such as feeling happy. All six participants who mentioned anxiety (e.g., fear of getting infected with COVID-19) said they followed the 1.5 meter rule because they felt responsible for others.

“If I get infected it is my own fault, but I would hate it if I would infect my mother or father. So I am afraid to get infected, because I do not want to infect others.” - male, 20 years old

Regarding natural mentoring, most participants in this group had a natural mentor, of which almost all of them spoke about COVID-19 and the measures with their natural mentor. Some participants felt support from their natural mentor. Four participants did not have a natural mentor, but mentioned their parents or their partner. Four of the seven participants who spoke with their mentor about COVID-19 and the measures also mentioned they followed the 1.5 meter measure because they were feeling responsible/solidarity for/with others.

Group 3: Non-compliant with the 1.5 meter rule

Two participants did not adhere to the 1.5 meter rule. When they were asked why they did not comply, they both said that they did not believe COVID-19 was real or posed a real threat.

“COVID-19 exists, but it is just like the flu. It has been blown up to exercise control over people. The 1.5 meter distance is everywhere, even in the law. This is just a plan to gain more control over people.” - female, 17 years old

Therefore, they did not perceive any threat (risk perception) and they also did not believe that the 1.5 meter rule would have any effect (response efficacy). One of them experienced mental health issues. No associations between perceived mental health issues and following the 1.5 meter rule were found. Both participants did not have a natural mentor.

Discussion

The purpose of this study was to examine which factors have played a role in how well youth in the Netherlands have complied with social distancing measures during the COVID-19 crisis. Our results show that most youth did comply with the 1.5 meter rule or at least tried to comply as much as they managed to. This is not in line with other studies, which have found that youth generally show less compliance than adults (Barari et al. 2020; Park et al. 2020). Additionally, Dutch media reported that youth did not comply well with the social distancing measures (e.g., Hart van Nederland 2020). Lastly, in Lisbon, non-complying youth were even considered as the main reason for the government to impose additional preventive measures (BNR Webredactie 2020). Besides this contract in results, it is noteworthy to point out that other preventive measures than social distancing might show different degrees of compliance (see Bacque Dion et al. 2021; Nivette et al. 2021; Zur Raffar et al. 2021). A limitation of these studies was that they asked youth whether they did or not comply; there was no specific category for ‘sometimes compliant’. Our study shows that this extra category of ‘sometimes compliant’ is a good addition, as compliance seems to be a construct of gradual differences instead of dichotomy. Compliance seems to depend on various factors. For the respondents in the sometimes compliant group, compliance with the 1.5 meter rule depends on their location (e.g., supermarket or work) or the people around them (e.g., friends or strangers). Compliance is therefore context-dependent and this should also be taken into account in future research.

Why did most youth in our sample comply with the social distancing measures? Most of the youth stated that they complied because of their solidarity with others (factor motivation). This seems to be the most important reason for compliance with social distancing measures. This is in line with a study that found that almost half of an adult sample complied with social distancing measures because they felt solidarity with others or felt responsible for others (e.g., people with vulnerable health) (Liekefett and Becker 2021). A qualitative study found that protection of loved ones or social responsibility were commonly mentioned as reasons for compliance among adults (Wang et al. 2021). A study in Slovenia showed that youth and adults complied with COVID-19 preventive measures to protect vulnerable social groups (Mihelič et al. 2021). Given these findings about the importance of social solidarity, also identified by Mishra and Rath (2020), in addition to social distancing measures governments should foster social solidarity by communicating about its importance. This promotion of solidarity happened in the Netherlands with messages such as “Alleen samen krijgen we Corona onder controle”. This might enhance feelings of solidarity or a collective conscience, which in our study was an important reason for compliance. Lastly, it is notable, that even though youth have low perceived susceptibility (low health risk) in relation to COVID-19, they still show maintenance motives and perceived benefits (e.g., not infecting others) and comply with the social distancing measures.

Another frequently mentioned reason for both compliance and non-compliance with social distancing measures was whether the physical environment made it possible to keep a distance of 1.5 meter from other persons. The physical environment was therefore an important facilitator of compliance. Another important reason for youth to comply was the perceived risk of becoming infected or infecting others. Thus, if people perceive the risk of becoming infected or infecting others as high, this may enable compliance. This can be seen as a form of personal self-protection from the perceived threat of a virus (Brug et al. 2009; Liekefett and Becker 2021; Rubin et al. 2009). However, risk perception may also hinder compliance when the perceived risk of infection is low. This was the case when the participants in this study trusted others not to have the virus, which happened in particular in situations with family and/or friends.

This study found that youth frequently reported multiple reasons for their compliance (e.g., motivation and habit). This means that compliance to social distancing measures is a complex mechanism, which might depend on multiple factors. This is possible, since both the HBM and the theory of maintenance of behavior change distinguish factors that can exist alongside each other (Kwasnicka et al. 2016; Skinner et al. 2015).

The most frequently mentioned reasons for compliance, which were ‘solidarity with others’ and ‘feeling responsible for others’, stem from the ‘maintenance motives’ of the behavior change maintenance model (Kwasnicka et al. 2016). The definition of ‘maintenance motives’ is broad and therefore these specific reasons have not been widely researched in other health behavior studies (e.g., about dieting). Studies about dieting or quitting smoking tend to focus on satisfaction with behavior outcomes (e.g., I am motivated because I feel healthier and I am slim) (Kwasnicka et al. 2019). There is one study that showed similar reasons for vaccination willingness for travelling adults. Travelers felt that it was their and everyone’s responsibility to get vaccinated before they travelled to protect others (Suess et al. 2022). Future research should investigate whether the specific reasons ‘feeling solidarity with others’ and ‘feeling responsible for others’ also exist in relation to other health behaviors, such as quitting smoking.

We also explored whether perceived mental health issues among youth influenced their compliance. We did not find explicit evidence for this relationship but did find that the youth who were experiencing anxiety issues also mentioned that they complied with the social distancing measures, because they felt solidarity with others or felt responsible for others. In other words, they might have been afraid of becoming infected with the Coronavirus because that would mean that they could also infect others with more vulnerable health. This would explain why they felt anxiety, which might have led to even greater compliance, due to their fear of infecting others. This is in line with the study by Harper et al. (2020) who found that anxiety about COVID-19 led to more compliance. However, in this study we did not specifically ask for anxiety of the Coronavirus, but anxiety issues as a whole. Future research should pay attention to these more specific anxieties.

It is notable, however, that a lot of youth in our sample were experiencing mental health issues. This is in line with numerous studies that show that youth experienced more mental health complaints during the COVID-19 pandemic, and specifically due to social distancing measures (Rauschenberg et al. 2021; Samji et al. 2022; Xie et al. 2020). However, we could not find a relationship between mental health issues and compliance in our study. The effect of mental health problems on compliance needs to be examined in future research, using bigger samples and, for instance, validated questionnaires to measure mental health.

More positively, youth did not only mention mental health complaints during the COVID-19 pandemic, but also stated various positive outcomes (e.g., more time for hobbies). This is in line with other studies that also found positive outcomes during the COVID-19 pandemic (e.g., increased creativity, increased social connectedness or support) (Dvorsky et al. 2020; Gijzen et al. 2020; Mercier et al. 2021; Penner et al. 2021; Suhail et al. 2021; Tull et al. 2020). In the current study we did not find a relationship between compliance and positive outcomes. If positive outcomes can, for instance, increase mental health, that could subsequently increase compliance. Further research to examine these links between positive outcomes, mental health and compliance is therefore worth doing.

Finally, and again more positively, this study did find that most of the interviewed youth seemed to have a natural mentor, and some of the participants also mentioned that their mentor supported them during the COVID-19 pandemic, and that they could talk with their mentor about the COVID-19 measures. These findings indicate that having a natural mentor helped with compliance to the social distancing measures, since the non-compliant group did not have natural mentors. This is supported by the theory behind natural mentoring, which assumes that a natural mentor can function as a role model or a person of guidance (Spencer et al. 2016). However, our study just offers an indication. Future research needs to examine the effect of a natural mentor on compliance using bigger samples (including both compliant and non-compliant youth).

Limitations and strengths

This study has several limitations. First, we used multiple interviewers, which might have influenced the quality and consistency of some interviews. This was necessary because the interviews had to be conducted in a limited timeframe. Second, the data we collected are based on the participants’ own perception, which will have influenced the data. Because of social desirability, for example, the participants might have reported better compliance than how well they actually complied. For future research this can be averted by using unbiased forms of measuring compliance, such as camera images (see Hoeben et al. 2021). The final limitation of the study is that the relationships between mental health issues and compliance could not be explicitly examined, due to the insufficient information obtained from the questions asked.

However, this study also has notable strengths. The first is that it had a diverse and sufficiently large sample (Boddy 2016). We collected a sample which consisted of 35 youth with various backgrounds, housing situations, education levels, and ages ranging from 16 to 25. Another strength of the study is that it collected information in a short period of time, which meant the same ‘COVID-19 conditions’ applied for each participant. This is a strength, certainly in a worldwide pandemic in which the situation and preventive measures changed all the time.

Implications and future research

A practical implication of the results of this study is that governments all over the world should address and/or keep addressing the motivations of youth to comply with social distancing measures. According to this study, they could address motivation as the willingness of youth to show solidarity with and responsibility for others. The government in the Netherlands already seeks to address motivation, as seen in the central slogan “Alleen samen krijgen we Corona onder controle” [Only together do we get COVID-19 under control], which also appears in government communication guidelines (Nationaal Kernteam Crisiscommunication (NKC) 2021). Governments should also praise youth for their compliance and emphasize that the COVID-19 pandemic could also have positive outcomes as well, such as more time for hobbies. Another important task for governments is to keep an eye on the mental health of youth and support youth in recognizing that there may also be positive outcomes (e.g., more time for hobbies). Lastly, we advise that youth are stimulated to have regular contact with their natural mentor and talk with them about the measures. Natural mentors, on the other hand, need to look after the youth and support them as much as they can, and governments can facilitate this by communicating how important these social support figures are.

Future research should investigate whether the specific reasons for compliance found in the current study (solidarity and responsibility) are also identified in other and larger samples, such as among adults, with other preventive measures than the social distancing measure and with other health behavior (e.g., quitting smoking). Future research could also pay attention to the youth compliance over time, since our study only measured compliance over a short period of time at a certain moment in the COVID-19 pandemic. It could be that during another period of this or a future pandemic, reasons for compliance might shift. Future research could also include less biased information about compliance, such as the use of video images referred to above (see Hoeben et al. 2021). The current study did include non-compliant youth, but this was a small sub-sample. Future research should examine non-compliant youth better with a larger sample, to understand their reasons for non-compliance.

Our current study could not investigate the effects of mental health on compliance specifically, so future research could focus on that relationship and might even use validated questionnaires to measure mental health problems. Our results showed evidence of a possible relationship between anxiety and compliance. Additional research is needed to further examine this relationship, with also focusing on the kind of anxiety that is experienced (e.g., fear of getting infected with the Coronavirus). Lastly, future research should examine the relationship that was found in the current study between natural mentorship and compliance in a bigger sample.

Conclusion

This study offers insight as to why youth comply with social distancing measures in the Netherlands. Youth seemed to comply well with the social distancing measures, even though they have a low health risk, with the most important factor being ‘motivation’ (feeling solidarity with others and feeling responsible for others). Most youth mentioned multiple reasons for their compliance, which indicates that compliance is a complex mechanism. We suggest that the specific reasons for compliance found in our study are examined for other health behaviors as well (e.g., quitting smoking) Nevertheless, while youth seem to comply well, this does not mean they do not experience mental health issues, which may be related to COVID-19 pandemic, or the preventive measures that have an impact on social lives. We found that many youths experienced mental health issues, but also reported positive outcomes (e.g., more time for hobbies). Lastly, we found evidence that having a natural mentor could have a positive effect on compliance with the social distancing measures.