Appetite 86 (2015) 54–60

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Research report

Following family or friends. Social norms in adolescent healthy eating☆ Susanne Pedersen, Alice Grønhøj, John Thøgersen * MAPP, Department of Business Administration, Business and Social Sciences, Aarhus University, Bartholins Allé 10, 8000 Aarhus C, Denmark

A R T I C L E

I N F O

Article history: Received 28 March 2014 Received in revised form 25 July 2014 Accepted 27 July 2014 Available online 1 August 2014 Keywords: Adolescent diet Social influence Parenting Social cognitive theory Structural equation modelling

A B S T R A C T

It is commonly believed that during adolescence children become increasingly influenced by peers at the expense of parents. To test the strength of this tendency with regards to healthy eating (fruit and vegetable intake), a survey was completed by 757 adolescent–parent dyads. Our theoretical framework builds on social cognitive theory and the focus theory of normative conduct, and data are analysed by means of confirmatory factor analysis and structural equation modelling. The study reveals that when it comes to adolescents’ fruit and vegetable intake, parents remain the main influencer, with what they do (descriptive norms) being more important than what they say (injunctive norms). The study contributes to a more comprehensive understanding of what influences adolescent healthy eating, including the social influence of parents and friends, while also taking adolescent self-efficacy and outcome expectations into account. No previous studies have included all these factors in the same analysis. The study has a number of important implications: (1) healthy eating interventions should aim at strengthening self-efficacy and positive outcome expectations among adolescents, (2) the family context should be included when implementing healthy eating interventions and (3) parents’ awareness of their influence on their children’s healthy eating should be reinforced. © 2014 Elsevier Ltd. All rights reserved.

Introduction Eating practices established in childhood are often carried into adulthood (Lake et al., 2004). Hence, it is important to establish healthy eating practices early in childhood and to support them during adolescence (WHO, 2000). Especially, eating sufficient quantities of fruit and vegetables contributes to the prevention of chronic diseases and the avoidance of obesity in general (WHO, 2003). Children most often eat in a social context. They are strongly influenced by parents’ attitudes and behaviour, and as primary socialisation agents (John, 1999), parents are gatekeepers of their children’s healthy eating (Birch & Fisher, 1998). As the child grows older, secondary socialisation agents such as friends, school and media influence behaviour as well (Chan, Prendergast, Grønhøj, &

☆ Acknowledgements: This study is part of the research project “Step by step changes of children’s preferences towards healthier food”, which was funded by the Danish Ministry of Science, Technology and Innovation, grant no. 09/061357. The authors would like to thank student assistants Jacob Heiss Rosendahl, Astrid Refsgaard, Ken Jørgensen and Christina Bæklund for their work in relation to the data collection and Birgitte Steffensen for proofreading the manuscript. We are also grateful for constructive comments on a previous version of the manuscript from C. Peter Herman and two anonymous reviewers. * Corresponding author. E-mail address: [email protected] (J. Thøgersen).

http://dx.doi.org/10.1016/j.appet.2014.07.030 0195-6663/© 2014 Elsevier Ltd. All rights reserved.

Bech-Larsen, 2010). Parental influence is believed to decline or at least change as the child moves into adolescence (Gitelson & McDermott, 2006). Among the many routes to healthy eating, special attention has been devoted to increasing the intake of fruit and vegetables – and hopefully replacing unhealthy food. Although we acknowledge that the latter cannot be taken for granted, and that reducing unhealthy eating is an important topic in its own right, this study’s point of departure is the fact that most adolescents do not eat the recommended amount of fruit and vegetables (Rasmussen et al., 2006; WHO, 2004) and there is a need for a better understanding why. Specifically, there is a lack of research on the relative importance of adolescents’ personal motivation and the social influence of parents and friends on adolescents’ healthy eating. Therefore, the purpose of this study is to determine the social influence of parents and friends on adolescents’ healthy eating, specifically fruit and vegetable intake, while also taking into account adolescents’ personal motivation to eat fruit and vegetables. A range of motives for food intake has been identified by previous research (e.g., Herman, Roth, & Polivy, 2003). Bandura’s (1986) Social Cognitive Theory (SCT) is a popular framework for studying people’s motivation to change behaviour (in our case, increasing fruit and vegetable intake). Many previous studies have confirmed the importance of the key motivation constructs proposed by SCT, namely self-efficacy and outcome expectations,

S. Pedersen et al./Appetite 86 (2015) 54–60

for healthy eating (e.g. Fitzgerald, Heary, Kelly, Nixon, & Shevlin, 2013; Geller & Dzewaltowski, 2010). Self-efficacy is the belief “that one has the power to produce desired changes by one’s actions” (Bandura, 2004, p. 144). Relevant outcome expectations regarding an anticipated behaviour are classified into three types: physical, social and self-evaluative (Bandura, 1977). Further, SCT suggests that a person’s behaviour is not the product of personal motivation alone, but also learned through observing the behaviour of others and influenced by perceived social pressure. The individual’s self-efficacy, outcome expectations and social influence (i.e., perceived social norms) together lead to behavioural goals or intentions, which together with facilitating and/or impeding contextual factors lead to behaviour. A common definition of social norms is “rules and standards that are understood by members of a group and that guide and/or constrain social behaviour without the force of laws” (Cialdini & Trost, 1998, p. 152). Cialdini and colleagues distinguish between descriptive and injunctive norms (Cialdini, Kallgren, & Reno, 1991; Cialdini, Reno, & Kallgren, 1990). Descriptive norms refer to what is commonly done, whereas injunctive norms refer to commonly held perceptions of do’s and don’ts. In the context of SCT, it is not so much other people’s objective behaviour or expectations as the individual’s subjective perception of these realities that are assumed to influence behaviour (Thøgersen, 2008). Healthy eating (Fitzgerald et al., 2013) and specifically fruit and vegetable consumption among adolescents have been found to increase with self-efficacy (Rasmussen et al., 2006; Young, Fors, Fasha, & Hayes, 2004) and with positive outcome expectations (Resnicow et al., 1997). As regards social influence on children’s healthy eating, the importance of parents is widely recognised (Lau, Quadrel, & Hartman, 1990) and parental influence in childhood seems to have long-term effects (Bauer, Laska, Fulkerson, & Neumark-Sztainer, 2010; Lake et al., 2004). Not surprisingly, given children’s daily exposure to parents’ attitudes and behaviour, parental intake (Rasmussen et al., 2006) and adolescents’ perception of parents’ intake of fruit and vegetables (Kristjánsdóttir, De Bourdeaudhuij, Klepp, & Thorsdóttir, 2009; Young et al., 2004) are also positively correlated with adolescents’ intake. Adolescents and their parents usually live together and share the fruit and vegetables that are available in the home and also a more general context and culture of eating, preparing and planning food intake. SCT refers to this shared context, which may account for some of the similarity in behaviour between adolescents and their parents, as (facilitating or impeding) socio-structural factors (Bandura, 1986). Previous research has also found correlations between adolescents’ and their friends’ eating behaviour (Bruening et al., 2012) suggesting that friends influence each other (Ball, Jeffery, Abbott, McNaughton, & Crawford, 2010; Salvy, de la Haye, Bowker, & Hermans, 2012) and/or conform to common norms (Stead, McDermott, MacKintosh, & Adamson, 2011). It has also been found that friends influence healthy eating negatively (Fitzgerald et al., 2013) by sometimes encouraging adolescents to consume unhealthy foods (Croll, Neumark-Sztainer, & Story, 2001). Others have found that friends restrict each other’s intake of unhealthy foods (Howland, Hunger, & Mann, 2012) and that friends’ negative influence can be counteracted by the adolescent’s impression management concerns (Salvy et al., 2012). It is not always clear from the literature whether friends actually influence each other or whether they become friends based on behavioural similarities (see for instance Bruening et al., 2012). In this paper, the importance for adolescents’ fruit and vegetable intake of both parents’ and friends’ descriptive and injunctive norms as well as adolescents’ own self-efficacy and outcome expectations is investigated. On the basis of the literature, we expect that all of these variables will influence adolescents’ intake of fruit and vegetables and that family norms will influence adolescents’

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healthy eating more than their own self-efficacy and outcome expectations. Specifically, we hypothesise that: Hypothesis 1a. Adolescents’ intake of fruit and vegetables depends on their self-efficacy and outcome expectations as well as on the dominant family norms as reflected in parental behaviour. Hypothesis 1b. Adolescents’ intake of fruit and vegetables depends more on the dominant family norms than on their own self-efficacy and outcome expectations. According to SCT and empirical research (Baker, Whisman, & Brownell, 2000; McClain, Chappuis, Nguyen-Rodriguez, Yaroch, & Spruijt-Metz, 2009) it is the perception of others’ behaviour more than others’ actual behaviour that influences a person’s behaviour. Hence, we expect that adolescents’ behaviour will be more strongly related to their subjective perception of their parents’ behaviour than to their parents’ actual behaviour, and even more so when parent’s actual behaviour is measured imperfectly by parental self-report. Hypothesis 2. Adolescents’ intake of fruit and vegetables depends more on how they perceive their parents’ behaviour than their parents’ actual behaviour, as measured by parental self-report. Since adolescents consume most meals in the family, parents are expected to be more influential than friends when it comes to adolescents’ eating. Hence, we hypothesise that: Hypothesis 3. Adolescents’ intake of fruit and vegetables is influenced more by the dominant norms in their own family than by the norms that they perceive as dominant among their friends. A recent study among adolescents (16 to 19 years old) found that descriptive norms, but not injunctive norms of peers in school were associated with their own fruit and vegetable intake (Lally, Bartle, & Wardle, 2011). Hence, we hypothesise that descriptive norms influence adolescents’ healthy eating more than injunctive norms. Hypothesis 4. Adolescents’ intake of fruit and vegetables depends more on what their parents and peers do (i.e., descriptive norms) than on what they say (i.e., injunctive norms).

Methods Participants and procedure A sample of 1321 adolescents and 795 parents was recruited from 17 schools in the Central Denmark Region in September 2010.1 The sample contained a total of 757 adolescent–parent dyads, which were identified by a unique ID number. In the adolescent–parent dyads sample, there were 347 boys/410 girls and 634 mothers/113 fathers (see Table 1). Hence, girls are slightly and mothers heavily overrepresented in the sample. Participation was voluntary and no compensation was offered. The questionnaire was thoroughly pre-tested. A school gave access to four children (age 11) who filled in the questionnaire and afterwards wording and scales were discussed with the first author. Following adjustments, four new pupils from the same school went through the same pre-test. A third pre-test was conducted with 30 pupils (ages 10–16), who filled in the questionnaire; subsequently, frequencies and scale reliability were checked. The adaptations and

1 The Step-by-Step Project also contained an intervention study aiming at increasing fruit and vegetable intake among school children (Pedersen, S., Grønhøj, A., Bech-Larsen, T., & Thøgersen, J. (2014). Texting your way to healthier eating? Effects of a feedback-intervention using text messaging to increase adolescents’ fruit and vegetable intake. (manuscript in preparation)).

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S. Pedersen et al./Appetite 86 (2015) 54–60

Table 1 Background information.

Number of participants Gender and class level No. of male/female

Parent

Adolescent

757

757

113/634 (10 missing)

347/410

No. of 5th/9th graders No. of boys/girls in 5th grade No. of boys/girls in 9th grade Mean age Standard deviation 5th graders 9th graders Parents’ educational level 7th–10th grade High school or similar Vocational education Short further education (up to 2 years) College degree completed (2–4 years) Graduate school (Masters, Doctorate or equivalent, 4 years or more) Monthly household income before tax Less than 8,000 DKK/1441$ 8000–14,999 DKK/1441–2702$ 15,000–29,999 DKK/2702–5404$ 30,000–49,999 DKK/5404–9007$ 50,000–69,999 DKK/9007–12,609$ 70,000 DKK or more/12,609$ or more

42.7 5.241

translations of existing scales from English into Danish included back translations and group discussions (Brislin, 1970). For the final data collection, adolescents completed a questionnaire at school under supervision of a research assistant while parents completed it at home. Measures

453/304 209/244 138/166 12.5 1.978 10.89 14.83

Adolescents and parents answered the same questions about behaviours, self-efficacy and outcome expectations related to fruit and vegetable consumption. The adolescents were also asked about their perception of parents’ and friends’ behaviour and attitudes in relation to fruit and vegetable consumption (see Table 2). Except where other scales are mentioned below, a 5-point Likert scale ranging from 1 = totally disagree to 5 = totally agree was used. Children (ages 6–18) have been found to prefer the Likert scale over other scales (van Laerhoven, van der Zaag-Loonen, & Derkx, 2004) and to be unable to grasp more than five response options (Chambers & Johnston, 2002; Streiner & Norman, 2008). Self-reported measures of behaviour were used because observing real-life behaviour of large samples of people is prohibitively costly and would also be extremely difficult in practice. Selfreporting is error-prone because respondents might be unable or unwilling to accurately report their own behaviour (Thøgersen, 2008). To make it easier to accurately report one’s behaviour, the

8.9% 7.3% 28.0% 11.0% 34.8% 10.0%

0.7% 3.1% 13.6% 28.8% 35.7% 18.0%

Table 2 Overview over key variables. Study variables

Adolescents Valid

Missing

Parents Mean

Behaviour “Thinking of an ordinary week, how often do you eat”: . . .fruit as a part of your breakfast 1300 188 2.64 . . .fruit as a part of your lunch 1293 195 4.11 . . .fruit as a part of your dinner 1287 201 2.64 . . .fruit in between meals 1299 189 5.03 . . .vegetables as part of your breakfast 1302 186 1.40 . . .vegetables as part of your lunch 1302 186 3.55 . . .vegetables as part of your dinner 1297 191 5.41 . . .vegetables in between meals 1295 193 2.87 Self-efficacy “How sure are you that you can eat more fruit and vegetables”: . . .every day 1305 183 3.26 . . .when coming home from school/work 1296 192 3.17 . . .when watching TV or DVD 1300 188 2.97 . . .when sitting at the computer 1298 190 2.75 . . .when your friends are around 1298 190 2.91 . . .when you are bored 1295 193 3.22 . . .when you are in a bad mood 1297 191 2.52 . . .when junk food is around 1293 195 2.63 . . .when you are busy 1302 186 2.69 Outcome expectations “Please answer what will happen if you eat more fruit and vegetables”: I will be in better shape if I eat more fruit and vegetables 1289 199 3.73 I will like myself better if I eat more fruit and vegetables 1290 198 3.69 I will get more energy if I eat more fruit and vegetables 1288 200 4.09 I will lose weight if I eat more fruit and vegetables 1288 200 3.43 I will be better looking if I eat more fruit and vegetables 1287 201 3.43 If I eat more fruit and vegetables, so will the rest of my family 1294 194 2.74 My family will be pleased if I eat more fruit and vegetables 1295 193 342 Descriptive norms “Please think about how people you know eat”: My mum eats a lot of fruit and vegetables 1182 306 3.94 My dad eats a lot of fruit and vegetables 1148 340 3.33 My friends eat a lot of fruit and vegetables 945 543 3.35 Injunctive norms “Please answer what people you know think you should do”: My friends think I should eat more fruit and vegetables 819 669 2.25 My father thinks I should eat more fruit and vegetables 1035 453 2.87 My mother thinks I should eat more fruit and vegetables 1114 374 3.23 * A “Don’t know” option was added to the scale.

Min.

Max.

Valid

Missing

Mean

Min.

Max.

1 1 1 1 1 1 1 1

8 8 8 8 8 8 8 8

779 774 756 785 773 775 779 776

709 714 732 703 715 713 709 712

3.25 3.97 2.19 5.77 1.32 4.95 6.46 3.30

1 1 1 1 1 1 1 1

8 8 8 8 8 8 8 8

1 1 1 1 1 1 1 1 1

5 5 5 5 5 5 5 5 5

777 780 778 777 778 776 776 778 778

711 708 710 711 710 712 712 710 710

3.48 3.54 3.22 2.95 3.04 3.04 2.74 2.87 2.86

1 1 1 1 1 1 1 1 1

5 5 5 5 5 5 5 5 5

1 1 1 1 1 1 1

5 5 5 5 5 5 5

775 778 774 775 776 775 775

713 710 714 713 712 713 713

3.56 3.78 4.05 3.75 3.68 3.47 2.43

1 1 1 1 1 1 1

5 5 5 5 5 5 5

1 1 1

5* 5* 5*

– – –

– – –

– – –

– – –

– – –

1 1 1

5* 5* 5*

– – –

– – –

– – –

– –

– – –

S. Pedersen et al./Appetite 86 (2015) 54–60

individual behaviour items were made as specific as possible. Respondents reported their behaviour on an 8-point scale from “never” (coded as 1) to “seven times a week” (coded as 8) for each of eight items: “Thinking of an ordinary week, how often do you eat fruit/ vegetables as a part of your breakfast/as part of your lunch/as part of your dinner/in-between meals?” Notice that we asked for the frequency of consumption rather than specific portion sizes, which we hoped decreased the risk of impression management (i.e., exaggerating how much they live up to the official guidelines). Further, we checked the validity of the self-reported behaviour by also asking parents and children to report their child’s/parents’ behaviour. The correlation between parents’ self-reported fruit and vegetable intake and adolescents’ report of their behaviour is significant and positive (r = .33) and the correlation between adolescents’ self-reported fruit and vegetable intake and their parent’s report of their behaviour is even stronger (r = .46). It seems reasonable to assume that the difference between these two correlations reflects the fact that parents are able to report their children’s behaviour with greater certainty than vice versa. Be that as it may, according to Cohen (1988), a correlation of .30/.50 is considered moderate/strong, meaning that the obtained correlations support the validity of the self-reported behaviour measures. The adolescent’s perception of others’ behaviour (a descriptive norm) was measured by three items: “My mum/dad/friends eat(s) a lot of fruit and vegetables”. The adolescent’s perception of others’ attitudes (injunctive norm) was measured by the following items: “My mum/dad/friends think(s) I should eat more fruit and vegetables”. For these items, a “don’t know” option was added to the scale. The items regarding parents’ behaviour and attitudes are assumed to capture adolescents’ perception of the dominant family norms. It is likely that some adolescents live in a context where their two parents differ in opinions and behaviour. However, a Cronbach’s alpha of .85 suggests a rather coherent injunctive family norm (mum/ dad thinks. . .). Cronbach alpha for the descriptive family norm (mum/ dad does. . .) is only .53, which suggests that this norm is not equally coherent, but it is still reasonable to assume that it exists. The respondent’s self-efficacy with regard to eating fruit and vegetables was measured using nine items adapted from Perry, De Ayala, Lebow, and Hayden’s (2008) Physical Activity and Healthy Food and Efficacy Scale for Children (PAHFE). The question was “How sure are you that you can eat more fruit and vegetables . . .?” with items focused on the situational context such as: “. . . when watching TV or DVD” or “. . . when you are busy”. The possible responses were “Not sure at all” (1), “Not too sure” (2), “Sure” (3), “Very sure” (4), “Completely sure” (5). Cronbach’s alpha was .86 for children and .92 for parents.

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The respondent’s outcome expectations (Bandura, 1986) were measured by asking the respondent to evaluate seven possible outcomes of eating fruit and vegetables such as: “I will like myself better if I eat more fruit and vegetables” or “I will lose weight if I eat more fruit and vegetables”. Cronbach’s alpha was .81 for children and .82 for parents. Results The analyses were conducted by means of structural equation modelling (SEM) using AMOS 21 (Arbuckle, 2007). In SEM, the measurement model is a confirmatory factor analysis (CFA) model and the theoretical constructs are latent factors extracted from the manifest variables (Bagozzi, 1994). The key results from both the CFA and the SEM are presented below in three steps. Step 1 In Step 1 the effects of self-efficacy and outcome expectations on adolescents’ behaviour were analysed while also including parents’ self-efficacy, outcome expectations and behaviour in the analysis. The bivariate correlations between the latent constructs based on CFA are shown in Table 3. The fit indices show that the CFA model fits the data well. The correlation matrix shows that all other latent variables correlate significantly with adolescent behaviour, with adolescent self-efficacy, parent behaviour and adolescent outcome expectations being the strongest predictors. The correlations reported in Table 3 are consistent with Hypothesis 1a, but some of them are inconsistent with Hypothesis 1b. However, a multivariate analysis is necessary to properly test the hypotheses. This analysis was conducted by means of SEM using all other variables included in the CFA as predictors of adolescent behaviour, as is also shown in Table 3. The SEM identifies the same variables as the strongest predictors of adolescents’ behaviour as the CFA. This means that Hypothesis 1a is supported. However, since adolescent selfefficacy is a stronger predictor of adolescents’ healthy eating than is parent behaviour, Hypothesis 1b is not supported. Step 2 In Step 2, the behavioural impact of dominant family norms as perceived by the adolescent were investigated while also including the adolescent’s self-efficacy, outcome expectations and parents’ (self-reported) behaviour. Since normative influence is assumed to be mediated through the actor’s perceptions and interpretations (Grønhøj & Thøgersen, 2012), adolescents’ perception of their

Table 3 The impact of adolescents’ and parents’ self-efficacy and outcome expectations and parents’ behaviour on adolescent behaviour.

Correlations between latent variablesb Adolescent behaviour Adolescent self-efficacy Adolescent outcome expectations Parent behaviour Parent self-efficacy Parent outcome expectations Structural modela Adolescent behaviour Parent behaviour

Adolescent behaviour

Adolescent self-efficacy

Adolescent outcome expectations

Parent behaviour

1.00 .57*** .37*** .41*** .16*** .12*

1.00 .28*** .18*** .18*** .06

1.00 .09 .10* .22***

1.00 .37*** .20***

0.47***

0.23**

0.35***

Parent self-efficacy

Parent outcome expectations

1.00 .14**

1.00

−0.07 0.35***

−0.01 0.15**

Ra

0.45 0.16

Standardised solution, only the structural model. Fit indices: Chi square = 342.117, 159 d.f., p < .001; CFI = .96; RMSEA = .039 (90% confidence interval: .033–.045). Based on CFA. The rest of the AMOS output from both analyses can be acquired from the first author. Fit indices: Chi square = 335.637; 157 d.f., p < .001; CFI = .96; RMSEA = .039 (90% confidence interval: .033–.045). *p < .05, **p < .01, ***p < .001. a

b

58

S. Pedersen et al./Appetite 86 (2015) 54–60

Table 4 The impact of adolescents’ perception of parents’ behaviour, parents’ self-reported behaviour and adolescent’s self-efficacy and outcome expectations on adolescent behaviour.

Correlations between latent variablesb Adolescent behaviour Adolescent self-efficacy Adolescent outcome expectations Adolescent perception of parent behaviour Parent behaviour Structural modela Adolescent behaviour Adolescent perception of parent behaviour

Adolescent behaviour

Adolescent self-efficacy

Adolescent outcome expectations

Adolescent perception of parent behaviour

Parent behaviour

1.00 .57*** .37*** .32*** .40***

1.00 .28*** .27*** .18***

1.00 .19** .09

1.00 .33***

1.00

.46***

.22***

.09

.31*** .29**

Ra

0.43 0.09

Standardised solutions, only the structural model. Fit indices: Chi square = 307.058, 99 d.f., p < .001; CFI = .93; RMSEA = .053 (90% confidence interval: .046–.059). Based on CFA. The rest of the AMOS output from both analyses can be acquired from the first author. Fit indices: Chi square = 260.776; 95 d.f., p < .001; CFI = .94; RMSEA = .048 (90% confidence interval: .041–.055). **p < .01, ***p < .001. a

b

Table 5 The impact of descriptive and injunctive norms regarding family and friends and adolescents’ own self-efficacy and outcome expectations on adolescent behaviour.

Correlations between latent variablesb Adolescent behaviour Adolescent self-efficacy Adolescent outcome expectations Descriptive norms, parents Injunctive norms, parents Descriptive norms, friends Injunctive norms, friends Structural modela Adolescent behaviour

Adolescent outcome expectations

Descriptive norms, parents

Injunctive norms, parents

Descriptive norms, friends

Injunctive norms, friends

1.00 .27*** .24*** −.31*** .27*** −.14*

1.00 .21*** .09 .21*** .09

1.00 .01 .12* −.13*

1.00 −.07 .66***

1.00 .13*

1.00

.39***

.26***

.02

−.10

Adolescent behaviour

Adolescent self-efficacy

1.00 .56*** .37*** .30*** −.32*** .20*** −.25***

.14**

−.16

Ra

0.44

Standardised solutions, only the structural model. Fit indices: Chi square = 171.768, 60 d.f., p < .001; CFI = .95; RMSEA = .050 (90% confidence interval: .041–.058). b Based on CFA. The rest of the AMOS output for both analyses can be acquired from the first author. Fit indices: Chi square = 171.843, 61 d.f., p < .001; CFI = .95; RMSEA = .049 (90% confidence interval: .040–.058). *p < .05, **p < .01, ***p < .001. a

parents’ behaviour was expected to be more predictive of adolescent behaviour than was parents’ self-reported behaviour. Table 4 shows the correlations between the latent constructs based on CFA. Again, the fit indices show that the CFA model fits the data well. Adolescents’ behaviour correlates significantly with their perception of parent behaviour, but contrary to our expectations and Hypothesis 2, the correlation is weaker than with parent’s self-reported behaviour. Table 4 also presents the results of a SEM using all other variables included in the CFA as predictors of adolescent behaviour. According to this analysis, adolescents’ perception of parent behaviour is not a significant predictor when these other variables are included, which means that Hypothesis 2 is not supported. Step 3 In Step 3, the impact of family and friends’ norms on adolescent behaviour were compared while distinguishing between descriptive (perceived behaviour) and injunctive (perceived attitude) norms. Since it was impossible to obtain measures of selfreported behaviour from friends, we only compared adolescents’ perceptions of parents’ and friends’ behaviour in Step 3, despite this measure being more weakly correlated with adolescent behaviour than parents’ self-reported behaviour in Step 2. Bivariate correlations between the latent constructs based on CFA are shown in Table 5. The fit indices show that the CFA model fits the data well. The correlation matrix shows that all other latent variables correlate significantly with adolescents’ behaviour, with adolescent selfefficacy, outcome expectations and the descriptive norms of parents as the strongest predictors. As predicted, the descriptive norms of parents correlate more strongly with adolescent behaviour than do

the descriptive norms of friends. Surprisingly, injunctive norms of both parents and friends correlate negatively and significantly with adolescent behaviour. Still, the correlations are consistent with Hypotheses 3 and 4. Table 5 also presents the results of the SEM using all other variables included in the CFA as predictors of adolescent behaviour. When including the other predictors, the descriptive norms of friends and the injunctive norms of both parents and friends are not significant. With parents influencing adolescents more than friends, Hypothesis 3 is supported. Hypothesis 4 is also supported since only the descriptive norm (of parents) predicts adolescent behaviour. The finding that adolescents are less influenced by friends than by parents when it comes to healthy eating is bolstered by a simple analysis of adolescents’ ability to answer questions about their mother/father/friends’ healthy eating behaviour and expectations regarding the adolescent’s behaviour (descriptive and injunctive norms, respectively). For these items, a “don’t know”2 response option was offered, and a substantially larger number of adolescents chose this option in response to questions about their friends’ expectations and behaviour: 37.9% and 28.3% respectively, compared to fathers (19% and 10%) and mothers (12.7% and 8.4%). This suggests that adolescents are more uncertain about their friends’ expectations and behaviour than their parents’, probably because

2 Due to the large proportion of “don’t know” responses, models with “don’t know” coded as missing or as “either or” were compared, but without substantially different results. This indicates that it is rather random whether the adolescent chooses to answer “either or” or “don’t know”. Therefore the models with “don’t know” coded as “missing” were chosen.

S. Pedersen et al./Appetite 86 (2015) 54–60

adolescents (irrespective of age group) are more exposed to parents’ healthy eating behaviour than to that of friends.

Discussion The aim of this research was to compare the social influence of parents and friends on adolescents’ healthy eating, focusing on fruit and vegetable intake, while distinguishing between descriptive and injunctive norms and also including adolescent self-efficacy and outcome expectations regarding fruit and vegetable intake. Previous studies have not included all these factors in the same analysis. Consumer socialisation theory suggests that the grip of parents gradually loosens in adolescence with friends taking over (John, 1999). However, this study does not confirm this for healthy eating. The results presented here show that parents continue to be the main influence on adolescents’ healthy eating behaviour whereas friends seem to have virtually no influence, although this might partly depend on how we defined ‘healthy eating’ (as fruit and vegetable intake rather than, e.g., cutting down on unhealthy food). Further, this study shows that descriptive norms (what parents do) are more important than injunctive norms (what parents say) when it comes to healthy eating – the sort of eating that parents would be expected to encourage. We found a surprising negative correlation between injunctive norms and behaviour. We cannot say with certainty, but one might speculate that this is due to others thinking that one should eat more fruit and vegetables only in cases where one does not already eat a lot.3 Fitzgerald et al. (2013) found that peer support for healthy eating and self-efficacy were significantly stronger for boys than for girls. The fact that in every surveyed age group of Danish adolescents, significantly more girls than boys eat fruit and vegetables every day (Sundhedsstyrelsen, 2008) also suggests gender differences. However, the present study did not find significant differences regarding selfefficacy, outcome expectations, social norms or behaviour between genders, nor between age groups.4 As with all other studies, this one has its limitations. First of all, this is a cross-sectional study conducted in one country at a single point in time. Both the cultural context and changes over time are important aspects of socialisation processes, so future research should include both cross-cultural and longitudinal studies. As has been pointed out by de Castro (1999), genetics and heredity are further factors that might account for parent–child similarities in food intake, in addition to socialisation and social influence. However, the present study has no basis for saying anything about the importance of these factors. Another limitation is the measurement of behaviour (which could in principle be observed) by selfreport, which may be inaccurate. As was mentioned in the methods section, respondents may be unable or unwilling to accurately report their own behaviour (Thøgersen, 2008). In the methods section we also reported a number of measures that we took to reduce the errors in self-reports; significant, positive and quite strong correlations between self-reported behaviour and reports by the respondent’s parent or child support the validity of the self-report measures. On the basis of SCT and previous findings (e.g. Baker et al., 2000), it was expected that adolescent behaviour would be more strongly related to their perception of parents’ behaviour than to parents’ self-reported behaviour. There could be several reasons why this was not what we found. One of these is the fact that the construct reliability of adolescents’ perception of parents’ behaviour (also

3 4

We are grateful to an anonymous reviewer for suggesting this interpretation. The analyses can be acquired from the first author.

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referred to as descriptive family norms) is weaker than that of all other predictor variables. The weak reliability might have led to its relationship with other variables being attenuated. Another reason might be that some unaccounted for “third variable” increases the correlation between parent and child self-reported behaviour, over and above the effects of social influence. For example, it is possible that the strong correlation between children’s and parents’ eating behaviour is partly due to genetic factors (de Castro, 1999). Perhaps even more obviously, the correlation between the two self-reported behaviours might partly be due to a shared family context containing shared socio-structural factors that either facilitate or impede fruit and vegetable intake for all family members. For instance, previous studies have found that availability at home is an important predictor of fruit and vegetable intake (Kristjánsdóttir et al., 2009; Neumark-Sztainer, Wall, Perry, & Story, 2003; Young et al., 2004). Hence, future research on this topic should both aim for a more reliable measure of descriptive family norms, as perceived by the children, and develop ways to measure how facilitating or impeding the family context is for the analysed behaviour. And until this unexpected finding has been replicated in other studies, it would be prudent not to draw any practical implications from it. The latter reservation is relevant for other results of this study that await support from other studies as well. However, many results of this study are in line with much contemporary research in related areas, which increases their face validity. For example, the observed impact of self-efficacy and outcome expectations on adolescents supports previous research recommending that healthy eating interventions targeted at adolescents should aim at strengthening their self-efficacy and clearly emphasise positive outcomes. Also, the observed strength of parental influence compared to that of friends suggests that the family context should be included when conducting healthy eating interventions and that parents – as gatekeepers – should be made aware of their role model influence with regard to healthy eating. It is important to stress, however, that we are not implying, for example, that school interventions should be de-emphasised. The present study is mute about the effectiveness of such interventions. The stronger effect of descriptive than injunctive norms shows that it is not enough for parents to preach healthy eating; they have to demonstrate it with their own good example. In sum, active parent involvement is recommended when conducting healthy eating interventions among adolescents (see also Pedersen, Grønhøj, & Bech-Larsen, 2012). According to this study, friends’ attitudes and behaviour do not influence adolescents’ fruit and vegetable intake, which conflicts with previous research findings, for example, that adolescents conform to a common eating norm thereby creating a group feeling (Stead et al., 2011). It is a limitation of this study that the adolescents were asked questions about their “friends” in general, which demands that they aggregate over several persons with perhaps very different attitudes and behaviour. This might explain why the adolescents in this study found it difficult to answer questions about their friends’ attitudes and behaviour. However, this difficulty might also be due to eating fruits and vegetables not being an identity-defining priority among adolescents. If this finding can be replicated in other studies, it suggests that healthy eating interventions targeting groups of friends should not necessarily rely on friends influencing each other, but perhaps instead aim to create a group feeling about healthy eating. In conclusion, this study has produced new knowledge about the role of important predictors on healthy eating among adolescents: self-efficacy, outcome expectations and not least descriptive and injunctive norms of parents and friends. Future research should build on these findings by exploring how interventions can build up self-efficacy and favourable outcome expectations while also including parents as positive models as a means to increase healthy eating among adolescents.

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