Academic performance and adolescent smoking in 6 European cities: the role of friendship ties

Abstract

Poor academic performance is a known risk factor for adolescent smoking, yet the association remains unclear, as the role of social ties has been rarely examined. Our study aims to investigate the role of friendship ties in this association. In a sample of 11,015 adolescents, aged 14 to17, in 50 schools within six European cities (SILNE-survey, 2013), we used multilevel models to analyse the mediating effect of the composition of friendship ties and school types on the association between academic performance and smoking. Results show smoking was more prevalent in adolescents with lower academic performance than with higher. This association was stronger in non-vocational schools than in vocational. Adolescents tended to have friendship ties with someone sharing the same smoking status and academic performance. Finally, friendship networks are patterned both on smoking and academic performance. This suggests the educational environment contributes to future socio-economic inequalities in smoking among young people.

Keywords:

• Daily smoking
• academic performance
• adolescents
• schools
• friendship ties

Introduction

Among adolescents, poor academic performance is associated with a greater risk of smoking initiation, more frequent smoking, a higher number of cigarettes smoked, and fewer attempts to quit smoking (Go, Tucker, Green, Pollard, & Kennedy, 2012; Hu, Lin, & Keeler, 1998; Karp, O'loughlin, Paradis, Hanley, & Difranza, 2005; Kinnunen et al., 2016; Kuntz & Lampert, 2013; Mercken, Snijders, Steglich, & de Vries, 2009). High smoking rates among poor academic performing adolescents have been observed in cross-sectional studies and in longitudinal studies of smoking onset, and across high income countries (Bradley & Greene, 2013; Hu et al., 1998; Karp et al., 2005; Kinnunen et al., 2016; Mercken, Snijders, Steglich, & de Vries, 2009; Schnohr, Kreiner, Rasmussen, Due, & Diderichsen, 2009). Academic performance in part is strongly related to socio-economic opportunities later in life (Lorant et al., 2016). The prevention of smoking in poorly performing adolescents is therefore crucial in order to decrease smoking inequalities in adults. However, there is a lack of understanding why adolescents who perform poorly in school are so much more likely to start smoking.

Some previous studies have suggested that poor academic performers are more often smokers due to confounding factors, such as low family socio-economic background (Ali & Dwyer, 2009) and a higher prevalence of smoking among family members (Go et al., 2012; Mercken, Snijders, Steglich, Vartiainen, & de Vries, 2009; Simons-Morton, Hartos, & Haynie, 2004). Other studies have suggested that the association between academic performance and smoking results from marginalization of poor performing students. Adolescents who perform less well may feel marginalized by teachers and by their better-performing peers (Elstad, 2010). They are less likely to receive social, emotional, and academic support from others. This makes them more likely to cluster together and engage in deviant behaviour, such as violation of school rules and smoking, as a way to create a social identity (Chen & Hsiao, 2009).

Clustering of poor performing students may for a large part be expressed in friendship ties, but the role of such ties has not been extensively studied in the existing literature (Lorant et al., 2015, 2016). Adolescents not only tend to create and maintain friendship ties with other adolescents at a similar level of academic performance (Huang, Soto, Fujimoto, & Valente, 2014; Kobus, 2003; Lomi, Snijders, Steglich, & Torló, 2011; Mercken, Snijders, Steglich, & de Vries, 2009; Schaefer, Haas, & Bishop, 2012; Woolf, Potts, Patel, & MCManus, 2012), but also with others with a similar smoking status (Mercken, Snijders, Steglich, & de Vries, 2009, Go et al., 2012; Schaefer et al., 2012; Seo & Huang, 2012; DeLay, Laursen, Kiuru, Salmela-Aro, & Nurmi, 2013). Based on Dimaggio’s theory of social network-induced inequality, adolescents’ social ties to students with similar smoking behaviour and similar level of performance contribute to the association between academic performance and smoking. This, in turn, could increase early socio-economic smoking inequalities (DiMaggio & Garip, 2012).

This kind of clustering may also be affected by school type, as some schools track students solely according to their academic performance (van de Werfhorst, 2011; Rathmann et al., 2016). School types, school options (e.g. sport, sciences, arts, etc.), and classroom assignments serve as a primary filter for peer influence because they facilitate physical and social proximity among adolescents who share similar characteristics, including smoking (Go et al., 2012; Mercken et al., 2009; Seo & Huang, 2012) and academic performance (Huang et al., 2014; Kobus, 2003; Lomi et al., 2011; Mercken, Snijders, Steglich, & de Vries, 2009; Schaefer et al., 2012; Woolf et al., 2012). School type, which is imposed by the educational system, influences the composition of friendship ties among students. Adolescents with higher academic performance are more likely to be attend schools that have a greater academic focus and are more oriented towards university degrees, while adolescents with lower academic performance may attend schools with a vocational orientation (Huisman, van de Werfhorst, & Monshouwer, 2012; Van de Werfhorst & Mijs, 2010). Tracking of students according to their academic performance may promote inequalities not only with regard to academic performance and aspirations (Buchmann & Dalton, 2002) but also to smoking (Doku, Koivusilta, Rainio, & Rimpelä, 2010; Rathmann et al., 2016). Richter (2007) showed that students in vocational-orientation schools have a four times higher risk of smoking than students who are enrolled in schools with the highest (university) educational orientation (Richter & Leppin, 2007). We therefore expected that the link between smoking and low academic performance would vary according to school type.

The aim of this study was to test to what extent the association between academic performance and adolescent smoking is explained by the patterning of adolescents’ social relationships based on smoking and academic performance. We addressed three specific questions:

1. What is the association between academic performance and smoking among adolescents in Europe?

2. Does the composition of social ties explain the association between academic performance and smoking?

3. Does the association between academic performance and smoking vary according to school type?

Methods

This study used data from the 2013 ‘SILNE’ survey (‘Tackling Smoking Inequalities: Learning from Natural Experiments’). SILNE is a school-based social network survey of adolescents in two grades corresponding to 14–17 year-olds and was conducted in six European cities (Namur, Belgium; Tampere, Finland; Hanover, Germany; Latina, Italy; Amersfoort, Netherlands; and Coimbra, Portugal). In each city an average of 8 schools and 1800 adolescents were recruited. A total of 163 schools were contacted and 50 agreed to participate. A total of 13,870 adolescents registered in these schools were invited to fill in a written questionnaire about their social relationships in school, health behaviours, and sociodemographic characteristics. A total of 11,015 adolescents (participation rate of 79.4%) participated, yielding 57,094 collected ties between those adolescents. In each city, ethical approval was obtained from national or local organizations. A detailed description of the design and concepts of the SILNE study has been published elsewhere (Lorant et al., 2015).

Measures

Daily smoking was defined as reporting having smoked at least 1 cigarette per day in the last 30 days. All other respondents were considered non(-daily) smokers.

Adolescent academic performance was based on the student’s self-reported marks during the previous year: ‘Which of the following best describes your marks during the past year?’. This variable included five initial values based on each country’s academic performance assessment system. These values were grouped into three tertile categories: low, average and high.

Adolescents were asked to nominate up to 5 friends (also referred to ‘alters’) within the two grades. Respondents answered the question, ‘who are your best and closest friends?’ (Lorant et al., 2015). To identify their peers, adolescents were handed a student directory which contained the names of all students enrolled in the two grades, alphabetically for each class and grade. One code was assigned to each name and respondents were asked to use the codes. In Finland, the names of adolescents had to be written on the questionnaire and the researchers coded them afterwards (name-generator approach).

Relationships established between adolescents in relation to smoking behaviour and academic performance were described at the individual level: (1) the proportion of friendship ties to low academic achievers of the total number of friendship nominations (the number of outgoing ties that a student has) and (2) the proportion of friendship ties to daily smokers of the total number of friendship nominations. In the main analysis, the indices were computed for reciprocal friendship ties. In a sensitivity analysis non-reciprocal friendship ties were also included. Reciprocal friendships are generally considered as involving more trust and social capital than non-reciprocal friendships (Rivera, Soderstrom, & Uzzi, 2010).

To capture the composition of institutional social ties imposed by the educational system, we categorized the students in vocational vs. non-vocational school types. The non-vocational school type is defined as the university-preparatory track and the vocational school type is defined as that of students who enter the labour market after secondary school and before the age of 20. As Finland does not have tracking in the included age-range, we created a ‘no-tracking’ category for that country. Supplementary Table 1 describes the allocation of the different tracks per school type and per country (Huisman et al., 2012; Moor et al., 2014).

Table 1. Sample characteristics and distribution of daily smoking and academic performance, SILNE, 2013, overall percentage and chi-square test (n = 9876).

Covariates	%	N	Daily smoker (%)	χ^2	P value	Low academic performer (%)	χ^2	P value
Gender
Male	49.7	5071	14.3	10.3	0.001	20.6	41.5	<.001
Female	50.3	5132	12.1			15.7
Age group
12–14	27.1	2770	5.7	417.3	<.001	12.8	205.8	<.001
15	38.3	3903	10.3			15.1
16+	34.6	3530	22.3			25.7
Cities
Namur (BE)	17.8	1818	19.2	166.0	<.001	23.3	298.1	0.004
Hanover (DE)	20.2	2064	9.5			18.8
Amersfoort (NL)	25.4	2594	9.0			10.7
Latina (IT)	7.3	740	21.1			7.8
Coimbra (PT)	16.8	1709	15.4			19.3
Tampere (FI)	12.5	1278	11.7			29.1
School types
Non-vocational	56.1	5668	7.7	407.9	<.001	14.2	166.8	<.001
Vocational	31.2	3153	23.2			20.6
‘No tracking’^a	12.7	1278	11.7			29.1
Mother’s education
Low	15.9	1625	17.0	67.2	<.001	22.4	120.3	<.001
Medium	32.6	3328	15.0			19.9
High	32.8	3343	9.7			12.4
Other/unknown	18.7	1906	12.9			21.4
Father’s education
Low	18.6	1902	17.5	84.5	<.001	23.3	151.0	<.001
Medium	28.6	2919	14.6			19.1
High	31.1	3176	9.1			11.7
Other/unknown	21.6	2207	13.6			21.7
Academic performance
Low performance	18.7	1849	23.1	271.0	<.001
Average performance	43.2	4264	13.6
High performance	38.1	3763	7.2
Total			13.2%			18.7%

^a “No tracking” = Finland.

Covariates included the number of smokers among family members in the household, socio-economic status, age, and sex. Socio-economic status was defined by the parental educational level. Parental education was classified into low, middle, high, and unknown, according to the education system of each country (Lorant et al., 2015).

Data analysis

After excluding 1,139 observations due to missing data, we were left with 9,876 full records.

We first tabulated smoking status and academic performance by socio-demographic groups. We then described the composition of friendship ties according to the adolescent’s own smoking status and academic performance level. We used multilevel logistic regression models (random intercept) to quantify the association between academic performance and smoking. Mediation of the association by the composition of friendship ties was tested. In Model 1, we regressed the academic performance variable on daily smoking. In Model 2, we added 3 indices of the composition of friendship ties: the composition of institutional social ties imposed by the educational system (school types), friendship ties with daily smokers, and friendship ties with low-performing peers. In Model 3, we controlled Model 2 for gender, age, parents’ education, and the number of smokers among family members. Statistical analyses were carried out with SAS 9.3. As participation differed slightly between schools, we weighted the data by the inverse of the participation rate.

Results

Table 1 describes the sample and the distribution of daily smoking and of academic performance. Older adolescents, students attending vocational schools, and students from lower socio-economic backgrounds were more likely to be smokers and to have low academic performance. Daily smoking was more frequent among students with lower academic performance than among students with high academic performance (23.1 vs. 7.2%, χ² = 271, p < 0.001).

Table 2 describes the composition of adolescents’ friendships ties according to their own academic performance and smoking status. Each cell is the average percentage of reciprocal ties to smokers (or to low performers) as a proportion of the total number of reciprocal ties. Adolescents had more friendship ties to adolescents with a similar smoking status and with a similar academic performance. The percentage of smoking alters was higher among daily smokers (from 40 to 54%) than among non(-daily) smokers (from 5 to 11%), independent of their academic performance. This association was stronger among high performers (ratio = 8.1) than among low performers (ratio = 4.71). It also varied according to the academic performance. The percentage of daily-smoking friends was higher among lower performers than among higher performers (ratio = 1.34).

Table 2. Friendship reciprocal ties with smokers and with low academic performers by smoking status and academic performance of ego: average percentage of the number of ties and ratio, SILNE international Survey 2013 (n = 11,021).

		Friendship alters in % of total No. of ties
Smoking status of ego	Composition of friendship ties	Low academic performance	Average academic performance	High academic performance	Ratio low/high
Daily smokers	Friendship ties with daily smokers	53.7%	43.0%	39.9%	1.34
	Friendship ties with low performers	45.3%	24.6%	15.8%	2.86
Non-daily-smokers	Friendship ties with daily smokers	11.4%	7.9%	4.9%	2.32
	Friendship ties with low performers	31.0%	16.1%	9.1%	3.40
Ratio*		4.71	5.44	8.14

* Ratio of friendship ties with daily smokers among daily smokers / friendship ties with daily smokers among non-daily-smokers.

Table 2 also shows that the percentage of ties to daily smokers increased as academic performance decreased, both among smokers and non-smokers. A similar pattern was observed for friendship ties to students with low academic performance. Among lower performers, between 45% and 31% of reciprocal friends were low performers, as against 16 to 9% among high performers.

Supplementary Table 2 shows a replication of Table 2 with all ties (reciprocal and non-reciprocal). The same pattern was found, but with less pronounced differences, suggesting that the strength of ties fosters the association between ego-smoking and alters’ smoking status.

Table 3 presents the association between daily smoking and academic performance by school types. In all countries there was a dose-response association between academic performance and daily smoking: the lower the academic performance, the higher the prevalence of daily smoking. Students in vocational school type have a higher prevalence of daily smoking than those in non-vocational school types. Overall, the risk of smoking among low-performing adolescents compared to high performers was higher for adolescents in ‘no-tracking’ schools and the non-vocational type of school than for the vocational type of school.

Table 3. Association of daily smoking with academic performance per school type: percentage and OR, SILNE international study of adolescent health, 2013.

	Daily smokers (%) per school type
Academic performance	‘No-tracking’^b	Non-vocational	Vocational
Low performance	25.6%	16.5%	29.4%
Average performance	7.8%	8.2%	23.4%
High performance	1.6%	3.9%	18.0%
Total	11.1%	7.5%	23.1%
OR (95%CI)^a	21.90 (9.74–49,23)	3.25 (2.43–4.36)	1.72 (1.35–2.20)

^a OR = Odds ratio of low performers vs. high performers, adjusted for age and sex with 95% Confidence Interval (CI). All the P-values are under 0.001.

^b ‘No-tracking’ = Tampere (Finland).

Table 4 presents the multilevel logistic regression models. In Model 1, low academic performance (OR 3.86, 95% CI 3.28–4.55) was associated with daily smoking. In Model 2, shows that the higher the percentage of friendship ties to daily smokers, the higher the odds of daily smoking (OR = 16.53, 95% CI: 13.36–20.45). A higher percentage of friendship ties with low-performing peers was also associated with higher odds of daily smoking (OR = 1.89, 95% CI: 1.50–2.39). The association between low compared to high academic performance and daily smoking decreased from 3.86 (Model 1) to 2.26 (Model 2). This means that a part of the association between academic performance and daily smoking was attributed by the composition of friendship ties. Moreover, adolescents enrolled in vocational schools compared with those in non-vocational schools were more likely to smoke (OR = 2.28, 95% CI: 1.87–2.76). Model 3 included confounders sex, age, parental education, and the number of family members who are smokers. The risk of daily smoking for low performers decreased slightly between Model 2 and Model 3 (from OR 2.26 to OR 1.99), which suggests that family background and adolescent characteristics slightly confound the association between adolescents’ own performance and daily smoking. Friendship ties and school type remained strongly related to smoking, independent of family background and adolescent characteristics.

Table 4. Risk of daily smoking according to academic performance, school type, and composition of friendship ties. Odds ratio from the logistic regression, SILNE international survey of adolescents, 2013.

Covariates	Model 1 OR (95%CI)	Model 2 OR (95%CI)	Model 3 OR (95%CI)
Academic performance (ref = High)
Average	2.02 (1.74–2.35)***	1.65 (1.36–2.01)***	1.55 (1.27–1.90)***
Low	3.86 (3.28–4.55)***	2.26 (1.81–2.84)***	1.99 (1.58–2.52)***
Friendship ties with daily smokers (%)		16.53 (13.36–20.45)***	13.69 (11.00–17.03)***
Friendship ties with low performers (%)		1.89 (1.50–2.39)***	1.76 (1.39–2.23)***
School type (ref = non-vocational)
‘No-tracking’		0.96 (0.69–1.34)	1.13 (0.80–1.60)
Vocational		2.28 (1.87–2.76)***	1.79 (1.46–2.20)***
Age			1.43 (1.32–1.56)***
Sex (Ref=female)
Male			0.98 (0.83–1.15)
Parents’ education (ref = high and middle)
Low level			1.02 (0.85–1.22)
Smoking family members			1.48 (1.40–1.56)***

Notes: Model 1 regressed the academic performance variable on daily smoking.

Model 2 added 3 indices of friendship-ties composition and random intercept at the city level.

Model 3 controlled Model 2 by gender, age, parents’ education, the number of smokers among family members, and random intercept at the city level.

*** = P-value under 0.001.

‘No-tracking’ = Tampere (Finland).

Discussion

Main findings

The origin of the association between smoking and poor academic performance in adolescents has remained unclear so far. Using an original international social-network study across six countries, we investigated the role of social ties in this association, looking at both the individual level and the dyad level. We found that friendship ties were homophilous both in relation to smoking and in relation to academic performance. Adolescents who are daily smokers have more friends who are smokers than non-smokers and low-performing adolescents have more ties to other low-performing adolescents. Adolescents enrolled in vocational schools are more likely to smoke than their counterparts in non-vocational or non-tracking schools. This composition of friendship ties and school type partly explains the association between smoking and academic performance. Although smoking is more prevalent in vocational schools than in non-vocational schools, low academic performance is more strongly associated with daily smoking in vocational schools than in non-vocational schools and particularly strongly in non-tracking schools.

Consistency and interpretation

Adolescents tended to have social ties with those who had the same smoking status and academic performance level. This is consistent with previous studies on both smoking (Mercken, Snijders, Steglich, & de Vries, 2009; Schaefer et al., 2012; Seo & Huang, 2012) and academic performance (Huang et al., 2014; Kobus, 2003; Lomi et al., 2011; Mercken, Snijders, Steglich, & de Vries, 2009; Schaefer et al., 2012; Woolf et al., 2012). Our study shows that friendship networks are patterned on both characteristics simultaneously. This means that poorly performing adolescents who smoke have a double social jeopardy: they have more friends who both perform poorly and also smoke. Social homophily on these two individual characteristics provide the backbone for health behaviour inequality in a school context. One possible explanation may be that smoking and low academic performance are signals of low social status, which may trigger greater social inclusiveness. Horn’s study (2006), cited by Killen, showed that adolescents who identified with low-status peer-group members were socially more cohesive than their high-status-group peers. This social cohesion, on one hand, reinforces the social identity of a group, but, on the other hand, also has consequences for health, well-being at school, emotional engagement, and academic performance (Killen, Rutland, & Jampol, 2009; Ladd, 2009). Our finding that reciprocal ties were more associated with the same smoking behaviour and the same level of performance than non-reciprocal ties makes clear the role of social cohesion (Fujimoto & Valente, 2012).

This may be related to the stronger association of academic performance and smoking in non-vocational schools (or in schools with no tracking) than in vocational schools. Within non-vocational schools, students who perform worse are less likely to receive social, emotional, and academic support from others and are thus more likely to cluster together and to engage in deviant behaviour such as violation of school rules and smoking (Chen & Hsiao, 2009). The association between smoking and academic performance may be weaker in vocational schools than in non-vocational schools because, there, low academic performance and smoking are more prevalent and thus socially less salient.

Potential limitations

Our study has some limitations. First, the differences between countries’ educational systems and grading systems are likely to affect the overall association between smoking and academic performance. In addition, the validity of the association between academic performance and smoking relies on the validity of academic performance, which was self-reported: it is possible that the social desirability of higher academic performance may lower the true association.

Second, our cross-sectional design cannot ascertain the direction of the association between smoking and academic performance and cannot disentangle causal effects from selection effects in the friendship network: adolescents may have similar friends in terms of smoking (or academic performance) either because they were influenced by their friends’ smoking status or because they selected them according to their own smoking status (Mercken, Snijders, Steglich, & de Vries, 2009).

Conclusions

Smoking rates are higher among adolescents with poor academic performance than among those with high academic performance. This association was to a considerable extent explained by homophily of friendship ties to smokers and to poor performers. This suggests that the educational environment contributes to socio-economic inequalities in smoking in young people. Further studies are needed to ascertain whether reducing the clustering of poor performers, e.g. class formation, could reduce this association (Valente, 2012).

Authors’ contribution

POR conceived the research question, participated in the data collection, performed the data analysis, and drafted the manuscript. AK contributed to the survey design and coordinated the study. POR, MK, KR, IM, JK, AR, JP, BF, and MR carried out the study in each European city and contributed to the manuscript. AK, MK, KR, IM, JK, AR, and JP helped draft the manuscript. VL designed the survey, supervised the data collection, assisted in the study’s conception, and contributed to the manuscript. All authors read and approved the final manuscript.

Disclosure statement

The authors report no conflicts of interest in relation to this study.

Funding

This study is part of the project ‘Tackling socio-economic inequalities in smoking: learning from natural experiments by time trend analyses and cross-national comparisons’ – SILNE, which is funded by the European Commission, Directorate General for Research and Innovation, under FP7 Health 2011 programme, with grant agreement number No. 278273. This study is also part of the SILNE-R project, which is supported by the European Union’s Horizon 2020 research and innovation programme, under grant agreement 635056.

Ethics approval

In each country, ethical approval from local or national ethical committees was requested and obtained. In addition, in some countries, permission to conduct the survey was requested from educational authorities. School principals, parents, and adolescents received leaflets, information letters, and parental consent letters, according to each country’s regulations. Informed consent was obtained from all individual participants included in the study.

Italy

Name of the committee: Ethics committee, Azienda Unità Sanitaria Locale Frosinone, Italy

Approval’s reference number: 862, approved on 13/11/2012

Netherlands

Name of the committee: Medical Ethical Committee of the AMC Approval’s reference number: W12_256#12.17.0290

Finland

Name of the committee: Ethics Committee of the Tampere region Favourable Statement reference number: 10/2012 

Germany

Name of the committee: Ethics committee, Medical Faculty, Martin-Luther-University Halle-Wittenberg, GermanyApproval’s reference number: 2012–112, approved on 13/12/2012.

Belgium

Name of the committee: Commission d’Éthique Biomédicale

Approval’s reference number: 2012/09OCT/461

Portugal

Name of the committee: General Directorate for Education

(Direção Geral da Educação)

Approval’s reference number: Ref number 0338600001, approved on 02/11/2012

Keypoints

• Smoking was more prevalent in poorly performing adolescents than in high-performing adolescents.

• This association was stronger in no-tracking school and in non-vocational schools than in vocational schools.

• This suggests that the educational environment contributes to socio-economic inequalities in smoking in young people.

• The friendship network is patterned both on smoking and on academic performance.

• Further studies are needed to ascertain whether reducing the clustering of poor performers, e.g. class formation, could reduce this association.

Notes on contributors

Pierre-Olivier Robert (MSc) is a researcher, teaching assistant and PhD student and Vincent Lorant (PhD) is professor at the Institute of Health and Society at the Université Catholique de Louvain (Belgium).

Mirte AG Kuipers (PhD) is a postdoctoral researcher and Anton E Kunst (PhD) is head of the Department of Public Health at the University of Amsterdam (The Netherlands).

Irene Moor (PhD) and Katharina Rathmann (PhD) are research associates and Matthias Richter (PhD) is professor at the Institute of Medical Sociology at Martin Luther University Halle (Germany) .

Jaana M Kinnunen (MHS) is researcher and Arja Rimpelä (PhD) is professor at the School of Health Sciences at University of Tampere (Finland).

Julian Perelman (PhD) is assistant professor at the Escola Nacional de Saúde Pública and Centro de Investigação em Saúde Pública, Universidade NOVA de Lisboa (Portugal).

Bruno Federico (PhD) is associate professor at Department of Human Sciences, Society and Health, University of Cassino and Southern Lazio (Italy).

All authors are part of the European project SILNE (http://silne-r.ensp.org/) aiming to enhance the effectiveness of programs and strategies to prevent smoking by adolescents in 7 European countries.

Supplemental data

The supplemental data for this article is available online at https://doi.org/10.1080/02673843.2018.1475288.

Acknowledgements

We are grateful to the schools for their participation, to the educational authorities for their support, to A. Ninane for managing data security and blinding, to M. Berdii for the web-platform management, to Francis Grogna for helping with the SILNE website, to V. S. Rojas for the survey management, to L. Thibaut for data collection in Belgium and for her help in the design of SILNE questionnaires, to S. Raisamo for her helpful advice on the design of the student questionnaire, to D. Favresse and R. Felder-Puig, respectively HBSC Belgium and HBSC Europe, for advice on using HBSC instruments, to L. Bekaert for his help with the leaflet design, and to J. Vandermeersch for helping us to test the Web-based platform.