School travel in Europe 1
Title: Psychosocial factors related to children’s active school travel: A comparison of two European
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regions
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McMinn, D.1 ‡*, Rowe, D. A.2 ‡, Murtagh, S.2‡, Nelson, M.3‡, Čuk, I.4‡, Atiković, A.5‡, Peček, M.6‡,
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Breslin, G.7‡, Murtagh, E. M.8‡, & Murphy, M. H.7‡
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1
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2nd Floor Health Sciences Building, Foresterhill Campus, Ashgrove Road, Aberdeen, Scotland, AB25
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2ZD. 01224 438101,
[email protected]
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2
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[email protected],
[email protected]
Rowett Institute of Nutrition and Health, School of Medicine and Dentistry, University of Aberdeen,
School of Psychological Sciences and Health, University of Strathclyde, Glasgow, Scotland,
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School of Culture and Lifestyle, University of Derby, Buxton, England,
[email protected]
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Faculty of Sport, University of Ljubljana, Ljubljana, Slovenia,
[email protected]
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Faculty of Physical Education and Sport, University of Tuzla, Tuzla, Bosnia and Herzegovina,
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[email protected]
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Faculty of Education, University of Ljubljana, Ljubljana, Slovenia,
[email protected]
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Ulster Sports Academy, University of Ulster, Newtonabbey, Northern Ireland,
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[email protected],
[email protected]
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Ireland,
[email protected]
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* Corresponding author (graduate student at time of data collection)
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Data collection in the Republic of Ireland was supported by a grant from the Mary Immaculate
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College Research Seed Funding Scheme: Grant Number 100404
Department of Arts Education & Physical Education, University of Limerick, Limerick, Republic of
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School travel in Europe 23 24
Introduction In childhood, regular physical activity forms an important foundation for future health status and
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helps to establish positive health-related behaviours that track into adulthood (Kelder et al, 1994).
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Additionally, there are several benefits of physical activity for children including reductions in
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systolic blood pressure (Leary et al., 2008), improvements in bone mineral density (McKay et al.,
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2000), improved cardio-respiratory functioning (Farpour-Lambert et al., 2009), and benefits to
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psychological wellbeing (Biddle & Mutrie, 2008; Breslin, et al 2012). Furthermore, regular physical
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activity in childhood and adulthood may confer other long-term benefits such as protection against
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many non-communicable diseases like hypertension, type 2 diabetes, cardiovascular disease, and
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several cancers (Schoenborn & Stommel, 2011).
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A large proportion of children in Western societies do not meet the daily physical activity (Ness
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et al., 2007) recommendation of 60 minutes of moderate to vigorous intensity physical activity per
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day, and are therefore at risk of forfeiting these many health benefits. For the future health of
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children, it is important to identify settings in which physical activity can be increased, and to gain a
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better understanding of factors that promote or inhibit engagement in physical activity (e.g.,
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environmental, social, psychosocial, and political factors).
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The school commute has been identified as an important opportunity for increasing physical
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activity (Tudor-Locke, Ainsworth, & Popkin, 2001). In a typical week, home-school and school-home
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commutes provide at least 10 distinct time periods during which children can engage in health-
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enhancing activity (by walking or cycling). Unfortunately, in most developed countries many children
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travel to school using inactive modes (Davison, Werder, & Lawson, 2008), and the prevalence of
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active travel is in decline (Central Statistics Office, 2006; McDonald, 2007; van der Ploeg et al., 2008).
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The decline in active travel and increased use of motorised modes are likely due to increased car
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ownership, perceptions of danger on the route to and from school, and changing family dynamics
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School travel in Europe 47
related to parental working patterns (Centers for Disease Control and Prevention, 2005; Faulkner et
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al., 2010).
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A better knowledge of the correlates that may influence children’s school travel decisions is
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important for designing effective and sustainable active travel interventions and to inform school
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travel policy. Previous studies in this area have focused primarily on the physical and social
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environment and demographic variables associated with active commuting (Kerr et al., 2006;
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Timperio et al., 2006). Findings from these studies suggest that the primary factors that influence
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active school travel are the distance from home to school (Nelson et al., 2008; Sirard & Slater, 2008),
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socio-economic deprivation (Ewing, et al., 2004), ethnicity (Evenson, et al., 2003), car ownership
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(Carlin, et al., 1997; Grize, et al., 2010), population density, urbanisation (Fulton, et al., 2005), and
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perceptions of road and traffic danger (Braza, et al., 2004; Bringolf-Isler, et al., 2008).
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Findings from these studies are helpful; however they do not shed light on the psychosocial
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factors that may influence school travel. Variables such as self-efficacy (De Bourdeaudhuij et al.,
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2005), pro-social characteristics (Brodersen et al., 2005), positive outcome expectations (Heitzler et
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al., 2006), and physical self-perceptions (Crocker, Eklund, & Kowalski, 2000) have been associated
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with general physical activity levels in children. It is logical, therefore, to propose that psychosocial
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variables may similarly be related to school travel behaviors. Only a few studies have been
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conducted to investigate the role of such variables in school travel behavior. Mendoza et al. (2010)
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found that parents‘ self-efficacy for allowing their child to actively commute to school was positively
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related to the percent of weekly trips made by active modes. Martin et al. (2007) found that parental
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perceptions of barriers were significantly associated with active school travel. Finally, Murtagh et al.
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(2012) demonstrated that TPB variables (attitude, subjective norm, and perceived behavioral
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control) explain 41% of the variance in active commuting intention and 10% of the variance in
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objectively measured behavior in Scottish school children.
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School travel in Europe 71
Most school travel studies have been conducted in North America, Australia, and New Zealand.
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It is not clear, therefore, whether the factors associated with active school travel are different in
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other countries. This is particularly relevant in Europe, where health behavior inequalities have been
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identified between regions. For example, it has been reported that there are clear and consistent
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patterns of inequality along a North West to South East geographic axis with respect to some key
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health outcomes, health behaviors, and risk behaviors (World Health Organisation, 2008).
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Specifically, higher levels of satisfaction and lower levels of health complaints have been observed
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among boys and girls in Northern and Western Europe compared with children from Southern and
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Eastern Europe. A combination of social, political, and cultural influences likely contributes to these
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patterns in health inequalities. However, in addition to these generally accepted factors, inequalities
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may, in part, be explained by differences in psychosocial factors associated with given health
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behaviors. The aim of the present study therefore, was to determine whether the health behavior of
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walking to school differs between two European regions, and to investigate differences in
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psychosocial constructs which may act as antecedents of walking to school.
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Methods Sample
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Participants were from Scotland (n = 165, from 5 schools, mean age 8.7 yrs), Northern Ireland (n
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= 340, from 5 schools, mean age 10.1 yrs), the Republic of Ireland (n = 136, from 7 schools, mean age
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8.7 yrs), Slovenia (n = 232, from 3 schools, mean age 8.7 yrs), and Bosnia and Herzegovina (n = 390,
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from 3 schools, mean age 9.6 yrs). Participants from these five countries were divided into two
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groups, representing North West Europe (Scotland, Ireland, and Northern Ireland, n = 641) and
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South East Europe (Slovenia and Bosnia and Herzegovina, n = 622). The rationale for grouping the
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countries in such a way was based on evidence indicating inequalities in health behaviors between
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North Western Europe and South Eastern Europe (World Health Organisation, 2008). Ethical
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approval was granted by the University of (Blinded) Ethics Committee to collect data in Scotland, the
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School travel in Europe 96
Republic of Ireland, and Northern Ireland. The University of (Blinded) granted ethical approval to
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collect data in Slovenia and Bosnia and Herzegovina. Informed consent was obtained from all
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participants prior to data collection.
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Theoretical framework
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The TPB (Ajzen, 1985, 1987) was used as the guiding psychological model to understand
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commuting behavior. The TPB was designed to predict and explain human behavior in specific
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contexts (Ajzen, 1991); in relation to the present study this is school commuting behavior. According
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to this theory, behavior is primarily influenced by the proximal determinant of behaviour i.e.,
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intentions. Intentions have been defined as “indications of how hard people are willing to try, of
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how much of an effort they are planning to exert, in order to perform the behavior” (Ajzen, 1991, p.
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181). Consequently, the greater the intention, the more likely the behavior will be performed. In
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turn, intention is influenced by three factors: attitude, subjective-norm, and perceived behavioral
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control. Attitude can be viewed as a person’s positive or negative evaluation of participating in the
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commuting behavior. Subjective-norm refers to the social pressure to perform or not perform the
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behavior. Finally, perceived behavioral control relates to an individual’s perception of the ease or
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difficulty of actively commuting.
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The TPB has been used successfully to predict changes in children’s physical activity (Hagger
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et al., 2001; Rhodes, Macdonald, & McKay, 2006), and has been used to predict objectively
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measured active commuting in a sample of Scottish school children (Murtagh et al., 2012).
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Travel Questionnaire
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A previously validated child travel questionnaire (McMinn et al., 2011) was used to obtain
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information on age, gender, travel mode, travel companion(s), feelings about living in the local area,
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and commuting behavior in relation to the four TPB constructs (intention, attitude, subjective norm,
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and perceived behavioral control).
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School travel in Europe 120
Travel mode was established via a self-report questionnaire item that was formatted to
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reflect the five ‘stages of change’ related to walking to school (i.e., pre-contemplation,
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contemplation, action, maintenance, and relapse, Prochaska & Di Clemente, 1983). Participants who
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categorised themselves as being in the action or maintenance stages were classified as walkers,
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while participants in the pre-contemplation, contemplation, or relapse stages were classified as non-
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walkers.
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To establish whether children travelled alone or with companions, they were asked: ‘On a
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normal day, who do you usually travel to school with?’. Possible check-box responses included: An
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Adult, An Adult and Other Children, On my own, Friends, and Brother/Sister. Responses were re-
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coded to reflect two possible options (i.e., alone or with travel companions).
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Regarding feelings about living in their local area, children were asked, ‘How do you feel
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about living in your local area?’. Participants responded using a three-point Likert-scale (unhappy,
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undecided, happy).
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All TPB constructs were measured using a 4-point Likert-scale (Disagree in a big way,
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Disagree, Agree, Agree in a big way). Intention to actively commute was measured using the
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following items: ‘I plan to walk to school every day’ and ‘I intend to walk to school every day’. The
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mean score of these items represented participants’ intention. Attitude towards walking to school
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was measured using the following four items: ‘Walking to school every day would be fun’, ‘Walking
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to school every day would be enjoyable’, ‘Walking to school every day would be good for me’, and
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‘Walking to school every day would be important for me’. The first two items relate to the affective
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(e.g., enjoyable/not enjoyable) component of attitude, and the second two items are concerned
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with the instrumental (e.g., beneficial/harmful) component (Ajzen & Driver, 1991). The mean score
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of these items represented participants’ attitude. Six items were used to measure subjective norm.
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Three of these measured the injunctive component of subjective norm (i.e., whether one believes
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the social network/people surrounding them wants them to perform the behavior). These were: ‘My 6
School travel in Europe 145
family wants me to walk to school every day’, ‘My friends want me to walk to school every day’, and
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‘My teachers want me to walk to school every day’. Three items measured the descriptive
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component (i.e., whether one’s social network performs the behavior): ‘My family will walk to
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school or work every day’, ‘My friends will walk to school every day’, and ‘My teachers will walk to
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school every day’. As with the other constructs, the mean of these items served as the measure of
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subjective norm. Finally, the following three items were used to measure perceived behavioral
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control: ‘I could walk to school every day if I wanted to’, ‘I have the time to walk to school every day
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if I wanted to’, and ‘I live in a place which allows me to walk to school every day if I wanted to’. The
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mean of these three items was used as the final measure of perceived behavioral control.
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Questionnaires were translated into the relevant languages for children in Slovenia and
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Bosnia and Herzegovina by individuals fluent in both English and the native language.
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Protocol
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Questionnaires were completed by each child in the classroom setting, taking approximately
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one hour. A researcher was present to answer queries related to questionnaire wording. Data were
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collected between August 2009 and December 2011.
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Data processing and Analysis
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Data were analysed using the Statistical Package for the Social Sciences (version 19.0.0; IBM
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Corp., Armonk, NY). Range checks were conducted to identify outliers. Outlying data points (i.e.,
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responses to questionnaire items that were beyond the possible range of scores) were deemed to be
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caused by inputting error and were deleted. Only three such data points were found. Missing data
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for the TPB variables were replaced using an Individual Information Centred (IIC) approach (Kang et
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al., 2009). The following percentages of missing TPB data were replaced for each country: Scotland =
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1.3%; Northern Ireland = 7.5%; Republic of Ireland = 10.4%; Slovenia = 21.2%; and Bosnia and
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Herzegovina = 0.1%.
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Descriptive statistics were calculated for age, gender, travel mode and companion, and
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feelings about the local area. These results were stratified by country and by region. The predictive
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value of the TPB variables in relation to commuting behavior have been previously demonstrated
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(Murtagh et al, 2012). Therefore, instead of investigating the predictive value of TPB variables on
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commuting behavior in each country, a one-way MANOVA was used to investigate differences in TPB
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variables between the two European regions (i.e., North West and South East). Relevant
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assumptions for MANOVA were satisfied, including normally distributed dependent variables
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(skewness and kurtosis values
