J Community Health DOI 10.1007/s10900-013-9817-3
ORIGINAL PAPER
Key Beliefs Related to Decisions for Physical Activity Engagement Among First-in-Family Students Transitioning to University Eloise Cowie • Kyra Hamilton
Ó Springer Science+Business Media New York 2013
Abstract The current study investigated key beliefs related to decisions for physical activity (PA) engagement among first-in-family (FIF) students transitioning to university. FIF students (n = 157) completed an online questionnaire assessing standard theory of planned behaviour constructs and belief-based items. One week later, participants completed a follow-up questionnaire assessing self-reported PA during the previous week. Results identified a range of behavioural, normative, and control beliefs that were significantly correlated with both PA intention and behaviour. Various key beliefs were also identified in relation to FIF students’ decisions to be regularly physically active, with behavioural beliefs such as ‘‘take up too much time’’, normative beliefs including ‘‘friends outside of university’’, and control beliefs such as ‘‘cost’’, identified. Finally, frequencies of those who strongly or fully accepted these beliefs were analysed, demonstrating that typically, a large number of FIF students did not hold the beliefs, and as such, these are relevant to target in resultant interventions. The current study effectively highlights a number of key beliefs that can be targeted in programs aimed at encouraging FIF students’ PA. Further, the study addresses a gap in the literature of targeting FIF students, a cohort at risk for inactivity, and utilises a sound theoretical framework to identify the unique set of beliefs guiding decisions for PA for this at-risk community group. Keywords Physical activity University students Theory of planned behaviour Beliefs Intervention
E. Cowie K. Hamilton (&) School of Applied Psychology, Griffith University, 176 Messines Ridge Road, Mt Gravatt, QLD 4122, Australia e-mail: [email protected]
Introduction Regular physical activity (PA) is recommended as key to an individual’s wellbeing, with Australian guidelines suggesting 30 min of moderate intensity PA on most, if not all days, in order to maintain and enhance health [1]. However, despite numerous benefits associated with regular PA, including improved cognitive functioning [2], approximately half of those aged 18–24 years do not meet appropriate standards [3]. Associated with this reduced engagement in PA may be life transitions experienced by those in this age group, in particular, commencing university [4]. Research has documented that a large proportion of students transitioning to university engage in insufficient levels of PA, with approximately one-third of previously active students becoming inactive during this transition [4]. Students who are first-in-family (FIF) to attend university, that is, students whom neither parent attended university [5], may experience greater challenges when transitioning to university, for example, limited knowledge of the university system, unrealistic expectations, and ongoing external responsibilities [6]. Alongside the general barriers to PA experienced by transitioning students, including limited social support, low motivation, and increased workload [7], these amplified challenges may put the FIF student community at greater risk for inactivity. However, no research has investigated the mechanisms guiding decision making processes for this at-risk cohort, and as such, little can be done to effectively address this decline, despite evidence indicating that tailored interventions are the most efficacious [8]. The Theory of Planned Behaviour The theory of planned behaviour (TPB) [9] is a well-validated model, applied to the prediction of specific behaviours,
123
J Community Health
including PA. The TPB can also be utilised to identify key targets for tailored interventions. The theory posits that behaviour is formulated by an individual’s intention to perform a specific behaviour, with intention comprised of attitude (positive/negative evaluations), subjective norm (social approval/disapproval), and perceived behavioural control (PBC; ease/difficulty of performing a behaviour, also predicts behaviour alongside intention). Importantly, the TPB posits that attitude, subjective norm, and PBC are underpinned by behavioural (costs/benefits), normative (pressure to conform to important others’ approval/disapproval), and control beliefs (encouraging/preventative factors). These beliefs reflect the deeper cognitions that determine intention, and subsequently, behaviour [9]. The salience of these beliefs is the main factor determining their influence, with individuals tending to utilise only a small number of principal beliefs to inform their intentions and behaviour [9, 10]. Despite key beliefs being essential to the TPB, there is a lack of empirical research addressing beliefs related to PA for specific cohorts and communities. It may be assumed that similar underlying beliefs exist for the same target behaviour. However, research has indicated the importance of identifying data related to beliefs for specific cohorts [11]. The identification of these beliefs informs the complex decision-making processes that underlie PA and provides insight into the relevant individuals and groups who influence decisions for PA for at-risk communities [11]. The current research will address this gap by identifying underlying beliefs regarding PA for FIF students transitioning to university. Research has identified key beliefs in relation to PA among various other population groups. A recent study investigating the key beliefs of mothers and fathers of young children identified numerous behavioural, normative, and control beliefs significantly correlated with parents’ PA intentions and behaviour [12]. Behavioural beliefs such as ‘‘interfering with other commitments’’ identified in this population group may also be relevant among transitioning FIF students who have numerous competing demands. Other studies have identified specific sets of beliefs underlying decisions for PA; however, common beliefs are often identified. Behavioural beliefs are often centred on the benefits of health and fitness, and costs of fatigue and muscle soreness; normative social pressure from important individuals and/or community groups is predominantly from family or friends; and control beliefs surround preventative factors such as weather, lack of time or motivation, and cost [13, 14]. A systematic review of the literature relating to TPB beliefs and PA has also identified the most salient behavioural, normative, and control beliefs across a range of studies [15]. Frequently obtained behavioural beliefs surrounded concepts of PA improving both physical and psychological health; normative beliefs demonstrated that family were the group to have the strongest social influence; and control beliefs
123
identified physical limitations as the largest preventative factor for PA [15]. Despite this substantive investigation, it is uncertain as to whether these beliefs would generalise to a specific group, such as FIF students, as various individuals and community groups share different cognitions and attitudes towards PA [15]. As such, interventions formulated from generic research may not accurately reflect the processes experienced by this specific university community group [15]. It is necessary therefore, to further investigate the beliefs held by FIF students in the hope that key beliefs elicited can help improve PA for this cohort. The Present Study The current study aims to investigate the key beliefs underlying the decision to engage in regular PA during the transition to university for FIF students. The study adopts a TPB belief-based approach to identify key behavioural, normative, and control beliefs underlying FIF students’ PA intentions and behaviour. First, correlations between behavioural, normative, and control beliefs, and intention and behaviour will be explored. Second, the key beliefs that significantly predict intentions and behaviour will be investigated. Finally, the relative amount of students who fully and strongly accept each of the key beliefs identified will be examined in order to determine the utility of each belief for subsequent interventions.
Methods Participants Participants were 157 [females = 126 (80.3 %), males = 31 (19.7 %)] undergraduate FIF university students, ranging in age from 17 to 54 years (M = 19.44, SD = 4.74). The majority of participants (n = 137, 87.2 %) had completed high school within 3 years of commencing university, and were from an English-speaking background (n = 127, 80.9 %). Several inclusion criteria were required: participants were to be aged 17 years and over, FIF to attend university, and commencing a university degree for the first time that semester. Participants were excluded if they identified having a physical disability perceived to interfere with doing regular PA, as inability to be physically active could potentially affect responses. Design and Procedure The study used a prospective cross-sectional design with two stages of data collection occurring 1 week apart. The university human research ethics committee approved the study (Reference #: PSY/35/13/HREC). Prior to data
J Community Health
collection for the main study, a pilot study was conducted on a representative sample in order to elicit behavioural, normative, and control beliefs as per recommendations made by Fishbein and Ajzen [16]. A sample of 14 university students (3 male, 11 female), aged between 18 and 35 years (M = 21.57, SD = 5.37) were recruited for the pilot. Content analysis was performed on the responses, and frequently occurring beliefs were used to form the belief-based TPB measures in the main questionnaire. The participants for the main study were recruited using convenience sampling from a first year cohort of psychology students. Standard TPB items identified by Ajzen [9] were included (e.g. intention), as well as measures assessing the underlying beliefs of the TPB constructs (behavioural, normative, and control beliefs). One week after completion of the main questionnaire, participants were contacted by email or text message to complete the follow-up questionnaire. In this stage, participants were assessed on their self-reported PA during the previous week. Participants received course credit as an incentive to participate in both the pilot and the main study. Measures Target Behaviour Regular PA was the target behaviour. Based on the Australian Government Department of Health and Aging [1] definition, it was operationalised as: At least 30 minutes of at least moderate-intensity PA on most, if not all days. This can be built up during the day of a variety of activities at least 10 minutes in length, or done in one session. It involves activities that make you breathe much harder than normal. Pilot Study A pilot study was conducted to identify frequently occurring salient beliefs, later used as the belief-based TPB measures in the main questionnaire. Due to the large number of beliefs elicited within the pilot study, a 30 % frequency cut off was used to select behavioural, normative, and control beliefs [17]. To elicit salient beliefs, participants were required to list the advantages and disadvantages of doing regular PA. This informed the behavioural beliefs measure, including nine elicited beliefs (e.g. ‘‘make me fitter’’, ‘‘increase the risk of me sustaining pain and/or injury’’). Participants were also requested to list, in the order of importance, any individuals or groups who would approve or disapprove of their doing regular PA. The eight most commonly identified individuals or groups (e.g. ‘‘friends at university’’, ‘‘parents’’, ‘‘health care professionals’’) were used as a measure of normative beliefs.
Participants were requested to identify factors or circumstances that might discourage or encourage them to perform regular PA. The seven most commonly reported factors (e.g. ‘‘study commitments’’, ‘‘laziness’’, ‘‘inconvenience’’) informed the control beliefs measure. Main Questionnaire The main questionnaire was formulated of items measuring belief-based TPB constructs related to performing regular PA. The majority of the items were positively worded, with some reverse-scaled items included to reduce response bias. Items were scored on a 7-point Likert scale. Intention Intention was measured using four items assessing the strength of intention to perform PA [e.g. 1 (I do not intend) to 7 (intend) to do regular PA in the next week]. Behavioural Beliefs Behavioural beliefs were measured by assessing the beliefs elicited from the pilot study. Participants were requested to rate how likely the costs (e.g. ‘‘take up too much time’’, ‘‘make me feel tired’’) and benefits (‘‘make me fitter’’, ‘‘improve my physical health’’) would result if they did regular PA in the next week. Responses ranged from 1 (extremely unlikely) to 7 (extremely likely). Normative Beliefs Normative beliefs were measured using the normative beliefs pertaining to eight socially relevant individuals or community groups (e.g. ‘‘friends at university’’, ‘‘parents’’, ‘‘health care professionals’’) obtained in the pilot study. Participants were asked to rate how likely these individuals or community groups were to think they should do regular PA in the next week, with responses ranging from 1 (extremely unlikely) to 7 (extremely likely). Control Beliefs Control beliefs were assessed by the seven control beliefs elicited from the pilot study. Participants were asked to rate how likely internal and external factors (e.g. ‘‘study commitments’’, ‘‘laziness’’, ‘‘cost’’) were to prevent or discourage them from doing regular PA, scored from 1 (extremely unlikely) to 7 (extremely likely). Follow up Questionnaire One week following the completion of the main questionnaire, participants were contacted to complete a followup questionnaire assessing their engagement in regular PA. Participants were requested to indicate the extent to which they had done regular PA of a moderate intensity for at least 30 min in the previous week (e.g. ‘‘In the last week, to what extent did you do regular PA?’’), rated from 1 (not at all) to 7 (very often).
123
J Community Health Table 1 Means, standard deviations, and bivariate correlations of behavioural, normative, and control beliefs related to PA for first-in-family students First-in-family student beliefs
M (SD) Total (n = 157)
Intention (r) Total (n = 157)
Behaviour (r) Total (n = 85)
Behavioural beliefs Make me fitter
5.93 (1.05)
.29**
Improve my physical health Take up too much time
5.92 (1.08) 4.22 (1.49)
.31** -.28**
.15 .12 -.23*
Make me feel tired
4.40 (1.56)
-.23**
-.21
Interfere with my other commitments
4.43 (1.55)
-.25**
-.09 -.06
Make me look good
5.37 (1.40)
.19*
Give me the opportunity to socialise
4.07 (1.73)
.27**
Increase the risk of me sustaining pain and/or injury
3.74 (1.55)
Improve my mental health
5.41 (1.36)
-.16* .33**
.13 -.17 .21
Normative beliefs Friends at university
4.41 (1.57)
.23**
.06
Friends outside of university
4.81 (1.52)
.34**
-.01
Parents
5.14 (1.59)
.21**
-.15 -.16
Other family members (e.g. siblings)
4.84 (1.57)
.32**
Boyfriend/girlfriend/partner/spouse
4.75 (1.67)
.26**
Health care professionals
5.04 (1.80)
.03
-.23*
Fitness trainer/coach Fitness/sports role models
5.19 (1.75) 5.12 (1.79)
.12 .15
-.12 -.06
.09
Control beliefs Study commitments
5.34 (1.38)
-.20*
-.24*
Not enough time
4.89 (1.51)
-.23**
-.39**
Laziness
4.91 (1.70)
-.44**
-.45**
Bad weather
3.84 (1.80)
-.23**
-.45**
Lack of motivation
4.84 (1.68)
-.38**
-.52**
Inconvenience
4.25 (1.66)
-.39**
-.39**
Cost
3.06 (1.86)
-.29**
-.47**
** p \ .01; * p \ .05
Results Key Beliefs Analysis: Intentions and Behaviour In eliciting the key beliefs that underpin the intentions and behaviour of FIF students to engage in regular PA, guidelines set out by Von Haeften et al. [18] were adhered to, in order to obtain specific targets for interventions. Initially, Pearson Product-Moment Correlations were conducted for each belief set (i.e. behavioural, normative, and control beliefs) to identify the beliefs significantly correlated with intention and PA behaviour. To identify key beliefs, the beliefs that were significantly correlated within each set (i.e. behavioural, normative, and control beliefs) were then entered into subsequent stepwise multiple regressions, with intention and PA as dependent variables,
123
respectively. Finally, in order to identify key beliefs relevant to intervention, guidelines by Hornik and Woolf [19] were adopted. Beliefs were analysed to elicit the percentage of FIF students who strongly or fully accepted the belief. Means, standard deviations, and bivariate correlations of behavioural, normative, and control beliefs related to PA intentions and behaviour for FIF students are displayed in Table 1. For the behavioural beliefs, all nine beliefs were significantly correlated with intention, and one belief (‘‘take up too much time’’) was significantly correlated with behaviour. Multiple regression analyses (see Table 2) revealed four behavioural beliefs as key beliefs related to intention, namely ‘‘improve my mental health’’, ‘‘take up too much time’’, ‘‘give me the opportunity to socialise’’, and ‘‘make me fitter’’. One key
J Community Health Table 2 Stepwise multiple regression for analysis of behavioural, normative, and control beliefs predicting intention and behaviour b
R2
df
F
.27
4, 145
13.12**
% strongly accept the beliefa
% fully accept the beliefb
Both (%)
Students’ intentions Behavioural beliefs Improve my mental health
35
21.7
56.7
-.27**
12.1
3.8
15.9
Give me the opportunity to socialise
.19*
18.5
6.4
24.9
Make me fitter
.19*
43.3
31.2
74.5
24.2
12.1
36.3
Take up too much time
Normative beliefs Friends outside of university
.22**
.12
1, 150
19.45**
.46
2, 148
20.09**
.34**
Control beliefs Laziness
-.37**
7.6
4.5
12.1
Cost
-.19*
18.5
28.7
47.2
12.1
3.8
15.9
25.5
24.2
49.7 12.1
Students’ behaviour Behavioural beliefs Take up too much time Normative beliefs Health care professionals
.05
1, 81
4.58*
.05
1, 82
4.47*
.41
3, 77
17.52**
-.23* -.23*
Control beliefs Lack of motivation
-.31**
8.3
3.8
Cost
-.34**
18.5
28.7
47.2
Not enough time
-.20*
8.3
1.9
10.2
** p \ .01; * p \ .05 a
Scale measured on a 7-point scale (1 = extremely unlikely, 7 = extremely likely), with a score of six indicating strongly accepting the belief for positively worded items, and a score of two indicating strongly accepting the belief for negatively worded items b
Scale measured on a 7-point scale (1 = extremely unlikely, 7 = extremely likely), with a score of seven indicating fully accepting the belief for positively worded items, and a score of one indicating fully accepting the belief for negatively worded items
belief (‘‘take up too much time’’) was related to behaviour. For the normative beliefs, five beliefs were significantly correlated with intention, namely ‘‘friends at university’’, ‘‘friends outside of university’’, ‘‘parents’’, ‘‘other family members (e.g. siblings)’’, and ‘‘boyfriend/girlfriend/partner/spouse’’. One belief (‘‘health care professionals’’) was significantly correlated with behaviour. One key belief was elicited from the multiple regression for intention (‘‘friends outside of university’’), and one key belief was elicited for behaviour (‘‘health care professionals’’), however, this belief has a negative beta. For the control beliefs, all beliefs were significantly correlated with both intention and behaviour, thus were all entered into the multiple regressions. Two key beliefs were elicited in relation to intention, namely, ‘‘laziness’’ and ‘‘cost’’, and three key beliefs were elicited in relation to behaviour, namely, ‘‘lack of motivation’’, ‘‘cost’’, and ‘‘not enough time’’. As demonstrated in Table 2, the majority of participants did not fully or strongly accept the behavioural, normative, and control beliefs for intentions or behaviour.
Discussion The aim of the study was to identify key salient beliefs underlying the decision to engage in regular PA during the transition to university for FIF students. This addresses the scant research within the TPB literature related to the identification of key beliefs, particularly for specific at-risk community groups [15]. First, results demonstrated that a large number of behavioural, normative, and control beliefs were significantly correlated with PA intention and behaviour. Second, a number of key beliefs were identified as significant predictors of intention and/or behaviour. Finally, frequencies of FIF students who fully or strongly hold key beliefs were obtained. Such results are congruent with previous TPB belief-based research [12–15]. The information obtained is pivotal to the formulation of effective targeted interventions to encourage PA engagement amongst this at-risk community. For the behavioural beliefs analyses, a number of positive outcomes arose, including ‘‘improve my mental health’’, ‘‘give me the opportunity to socialise’’, and ‘‘make me fitter’’, as well as the negative outcome of ‘‘take up too
123
J Community Health
much time’’. Beliefs obtained are similar to those from previous studies, with a focus on health and fitness. In contrast however, the current study did not identify weight control or weight loss as a key behavioural belief [12–14]. Thus, interventions should not focus on this as an important element, but rather, the positive health benefits of fitness and improved mental health. When reviewing the percentage of students who strongly or fully accepted these beliefs, approximately half or less fit into these categories (except for ‘‘make me fitter’’). This is important as such beliefs can be encouraged in order to increase PA engagement for FIF students. It is evident that the influence of competing demands during the transition to university plays a significant role in PA decision-making, as perception of the time available to engage in PA is salient to the formation of both intentions and behaviour. The identification of ‘‘take up too much time’’ highlights the demands placed on university students and the subsequent influence on behaviour. Thus, activities perceived to be time consuming may be particularly salient for this community group whose time management becomes increasingly important when managing university studies [20]. Further, it is relevant due to the low percentage of students who strongly or fully accepted this belief. As such, it is relevant to targeted interventions, where encouraging perceptions of self-efficacy related to time management may result in increased PA engagement for this transitioning community group. In relation to normative beliefs, social pressure from ‘‘friends outside of university’’ was identified as the key belief for PA intention, in relation to FIF students’ perceptions of who would think that they should do regular PA. However, less than half of the participants strongly or fully accepted this belief. This differs from the systematic review identifying family as the most important individual or community group to exert social pressure influencing ones motivation to engage in PA [15]. As such, it may be relevant to incite norms of social support and encouragement between a FIF student and their friends outside of university, rather than focusing on family. The supportive community that transitioning students surround themselves with, particularly their friends external to university, may be influential to students’ decisions to be physically active. Whilst literature emphasises the importance of becoming connected with peers at university for academic adjustment [21], the current research suggests that maintaining relationships with friends outside of university is also relevant to ensuring holistic wellbeing throughout the transition. For behaviour, the normative belief that arose as key was the influence from health care professionals; however, this was a negative predictor. This indicates that despite FIF students’ belief that a health care professional would think that they should do regular PA, this does not predict
123
increased PA behaviour. This may be due to the pressure placed on students from various sources such as university staff, bosses, parents, and friends to fulfil various commitments. The added pressure of a health care professional encouraging a student to remain physically active during this transition may have the opposite effect, whereby the pressure demotivates them to be active. Further research is required to understand how social pressures truly function for transitioning university students, and the effect that this has on PA behaviour. Control beliefs also arose in relation to both PA intention and behaviour. Two key beliefs were elicited in relation to intention, namely ‘‘laziness’’ and ‘‘cost’’, suggesting that when formulating intentions, motivational and cost related factors are salient. This is similar to beliefs obtained in previous research [12–15]. However, FIF students did not identify health issues or weather as preventative factors, as is commonly identified in other belief research [12– 15]. This may indicate either that these factors are not relevant to FIF students’ decisions for regular PA, or that other factors are more salient. The identification of ‘‘cost’’ may be particularly salient to transitioning students as they are in a period of financial stress, where the predominant costs that they face are university related. As such, students may feel that they are unable to afford PA related expenses, such as joining a gym. Importantly, less than half of the participants strongly or fully accepted the belief that these factors would not prevent them from doing regular PA. Therefore, these are important targets for intervention. In relation to behaviour, similar factors are key, for example ‘‘lack of motivation’’, ‘‘cost’’, and ‘‘not enough time’’. Therefore, it can be argued that competing demands faced by FIF students during the transition to university may reduce their engagement in regular PA. Specifically, for FIF students, their time allocation and motivations may now focus on university studies, and as such, students may feel that there is little time or motivation remaining to focus on PA. Notably, a very low percentage believed that laziness and lack of motivation would not prevent them from engaging in regular PA, and are important factors to address when formulating proactive interventions for this cohort. According to Ajzen’s TPB, in order to formulate an effective intervention, beliefs should be elicited from the target population, as these underlying beliefs function differently for varying at-risk community groups [9]. Stemming from the beliefs identified in the current study, interventions can focus on the way that these beliefs function specifically for FIF students transitioning to university. Positive behavioural beliefs, such as the ability of PA to ‘‘improve my mental health’’ and ‘‘make me fitter’’ can be encouraged by providing education about self-care within orientation events for transitioning students.
J Community Health
Students could be informed about the positive benefits of PA for both physical and mental health, particularly focusing on the cognitive benefits [2]. In addition, attention could be given to the need to maintain relationships with friends outside of university, and engaging in fun activities with friends that are physically active. This would target the behavioural belief of ‘‘give me the opportunity to socialise’’ whilst incorporating the social influence from friends outside of university. When addressing the salience of time and motivation, students could be encouraged to plan for PA as part of their everyday life. For example, students could be encouraged to include small amounts of PA into their study timetable, possibly as a study break. As mentioned earlier, PA improves cognitive abilities and so, by including it in everyday activities, students may feel better equipped for university studies. When addressing the control belief of cost, students could be encouraged to consider forms of PA that are not costly, for example, walking around campus, or riding a bike to university. All of these intervention strategies can be addressed and implemented by a supportive university community who understands the benefits of maintaining regular PA during the transition to university for students’ overall wellbeing. The current study has various strengths. First, to the authors’ knowledge, the study was the first to address the role of underlying key beliefs for FIF students in relation to their engagement in regular PA, important for the formulation of effective and targeted interventions to encourage regular PA among this at-risk community group. Despite this strength, an important limitation of the current study is the use of self-report measures to obtain PA data. Selfreport is problematic as it is susceptible to social desirability bias. However, a recent study investigating the use of web-based self-report (as used in the current study) in relation to PA, demonstrated that social desirability was not related to self-reported PA, nor was it moderated by demographic variables [22]. Despite this, it would be beneficial to source data from more objective sources, such as electronic monitors or externally based assessments from friends or family, in order to increase accuracy of results, and gain a deeper understanding of the influence of beliefs on actual PA behaviour. In addition, the crosssectional nature of the research limits the understanding of the long-term function of beliefs and their effect on PA behaviour. Influences may change throughout the course of a FIF student’s studies as the student adjusts to university and becomes acquainted with the system. As such, future research would benefit from investigating the belief patterns in relation to PA behaviour throughout the university career. In summary, the current study identified behavioural, normative, and control beliefs related to PA in FIF students
transitioning to university, with underlying key beliefs predicting intention and behaviour. The information provided from this analysis can be applied to the construction of intervention programs, with the intention of addressing barriers to PA experienced by FIF students, as well as promoting engagement in regular PA during the transition to university. Awareness of the empirically established benefits of engaging in regular PA, in addition to the insufficient level of PA engaged in by a large number of university aged individuals, as well as demonstrated declines in regular PA upon transitioning to university shown throughout the literature, exhibits the importance of identifying the factors and underlying beliefs that predict engagement in regular PA. By identifying these, opportunities arise to develop effective intervention strategies to target beliefs related to PA decisions, with the hope of preventing declines in PA and increase wellbeing among FIF university students.
References 1. Australian Government Department of Health and Aging. (2005). An active way to better health: National physical activity guidelines for adults. Canberra, ACT: Commonwealth of Australia. 2. Guiney, H., & Machado, L. (2013). Benefits of regular aerobic exercise for executive functioning in healthy populations. Psychonomic Bulletin Review, 20(10), 73–86. doi:10.3759/s13423012-0345-4. 3. Australian Bureau of Statistics. (2013). Australian Health Survey: Physical Activity, 2011–2012, (no. 4364.0.55.004). Canberra, ACT: Australian Bureau of Statistics. 4. Bray, S., & Born, H. (2004). Transition to university and vigorous physical activity: Implications for health and psychological wellbeing. Journal of American College Health, 52(4), 181–188. http://search.proquest.com.libraryproxy.griffith.edu.au/docview/ 213030921?accountid=14543. 5. Talebi, M., Matheson, K., & Anisman, H. (2013). Does being first in family matter? The role of identity in the stigma of seeking help among first and non-first in family university students. The International Journal of the First Year in Higher Education, 4(1), 47–58. doi:10.5204/intjfyhe.v4i1.137. 6. Luzeckyj, A., King, S., Scutter, S., & Brinkworth, R. (2011). The significance of being first: A consideration of cultural capital in relation to ‘‘first in family’’ student’s choices of university and program. A practise report. The International Journal of the First Year in Higher Education, 2(2), 91–96. doi:10.5204/intfyhe.v2i2.89. 7. Gyurcsik, N., Bray, S., & Brittain, D. (2004). Coping with barriers to vigorous physical activity during transition to university. Family Community Health, 27(2), 130–142. http://ovidsp.tx.ovid. com.libraryproxy.griffith.edu.au/. 8. Muller-Riemenschneider, F., Reinhold, T., Nocon, M., & Willich, S. (2008). Long-term effectiveness of interventions promoting physical activity: A systematic review. Preventative Medicine, 47(4), 354–368. doi:10.1016/j.ypmed.2008.07.006. 9. Ajzen, I. (1991). The theory of planned behaviour. Organizational Behaviour and Human Decision Processes, 50(2), 179–211. doi:10.1016/0749-5978(91)90020-T. 10. Van de Plight, J., & De Vries, N. (1998). Belief importance in expectancy-value models of attitudes. Journal of Applied Social
123
J Community Health
11.
12.
13.
14.
15.
16.
Psychology, 28(15), 1339–1354. doi:10.1111/j.1559-1816.1998. tb01680.x. Hamilton, K., & White, K. (2010). Understanding parental physical activity: Meanings, habits, and social role influence. Psychology of Sport and Exercise, 11(4), 275–285. doi:10.1016/j. psychsport2010.02.006. Hamilton, K., & White, K. (2011). Identifying key belief-based targets for promoting physical activity among mothers and fathers with young children. Journal of Science and Medicine in Sport, 14(2), 135–142. doi:10.1016/j.jsams.2010.07.004. White, K., Terry, D., Troup, C., & Rempel, L. (2007). Behavioural, normative, and control beliefs underlying low-fat dietary and regular physical activity behaviours for adults diagnosed with type 2 diabetes and/or cardiovascular disease. Psychology, Health and Medicine, 12(4), 485–494. doi:10.1080/13548500601089932. Conn, V., Tripp-Reimer, T., & Maas, M. (2003). Older women and exercise: Theory of planned behaviour beliefs. Public Health Nursing, 20(2), 153–163. doi:10.1046/j.1525-1446.2003.20209.x. Downs, D., & Hausenblas, H. (2005). Elicitation studies and the theory of planned behaviour: A systematic review of exercise beliefs. Psychology of Sport and Exercise, 6(1), 1–31. doi:10. 1016/j.psychsport.2003.08.001. Fishbein, M., & Ajzen, I. (1975). Beliefs, attitude, intention and behaviour: An introduction to theory and research. Reading, MA: Addison-Wesley.
123
17. Hamilton, K., & White, K. (2010). Identifying parents’ perceptions about physical activity: A qualitative exploration of salient behavioural, normative, and control beliefs among mothers and fathers of young children. Journal of Health Psychology, 15(8), 1157–1169. doi:10.1177/1359105310364176. 18. von Haeften, I., Fishbein, M., Kasprzyk, D., & Montano, D. (2001). Analyzing data to obtain information to design targeted interventions. Psychology, Health and Medicine, 6(2), 151–164. doi:10.1080/13548500125076. 19. Hornik, R., & Woolf, K. (1999). Using cross-sectional surveys to plan message strategies. Social Marketing Quarterly, 5(1), 34–41. doi:10.1080/15245004.1999.9961044. 20. MacCann, C., Fogarty, G., & Roberts, R. (2011). Strategies for success in education: Time management is more important for part-time than full-time community college students. Learning and Individual Differences, 22(5), 618–623. doi:10.1016/j.lindif. 2011.09.015. 21. Ward, L., Siegel, M., & Davenport, Z. (2012). First-generation college students: Understanding and improving the experience from recruitment to commencement. http://www.eblib.com. 22. Crutzen, R., & Goritz, A. (2011). Does social desirability compromise self-reports of physical activity in web-based research? The International Journal of Behavioural Nutrition and Physical Activity, 8(31), 31–35. doi:10.1186/1479-5868-8-31.
ORIGINAL PAPER
Key Beliefs Related to Decisions for Physical Activity Engagement Among First-in-Family Students Transitioning to University Eloise Cowie • Kyra Hamilton
Ó Springer Science+Business Media New York 2013
Abstract The current study investigated key beliefs related to decisions for physical activity (PA) engagement among first-in-family (FIF) students transitioning to university. FIF students (n = 157) completed an online questionnaire assessing standard theory of planned behaviour constructs and belief-based items. One week later, participants completed a follow-up questionnaire assessing self-reported PA during the previous week. Results identified a range of behavioural, normative, and control beliefs that were significantly correlated with both PA intention and behaviour. Various key beliefs were also identified in relation to FIF students’ decisions to be regularly physically active, with behavioural beliefs such as ‘‘take up too much time’’, normative beliefs including ‘‘friends outside of university’’, and control beliefs such as ‘‘cost’’, identified. Finally, frequencies of those who strongly or fully accepted these beliefs were analysed, demonstrating that typically, a large number of FIF students did not hold the beliefs, and as such, these are relevant to target in resultant interventions. The current study effectively highlights a number of key beliefs that can be targeted in programs aimed at encouraging FIF students’ PA. Further, the study addresses a gap in the literature of targeting FIF students, a cohort at risk for inactivity, and utilises a sound theoretical framework to identify the unique set of beliefs guiding decisions for PA for this at-risk community group. Keywords Physical activity University students Theory of planned behaviour Beliefs Intervention
E. Cowie K. Hamilton (&) School of Applied Psychology, Griffith University, 176 Messines Ridge Road, Mt Gravatt, QLD 4122, Australia e-mail: [email protected]
Introduction Regular physical activity (PA) is recommended as key to an individual’s wellbeing, with Australian guidelines suggesting 30 min of moderate intensity PA on most, if not all days, in order to maintain and enhance health [1]. However, despite numerous benefits associated with regular PA, including improved cognitive functioning [2], approximately half of those aged 18–24 years do not meet appropriate standards [3]. Associated with this reduced engagement in PA may be life transitions experienced by those in this age group, in particular, commencing university [4]. Research has documented that a large proportion of students transitioning to university engage in insufficient levels of PA, with approximately one-third of previously active students becoming inactive during this transition [4]. Students who are first-in-family (FIF) to attend university, that is, students whom neither parent attended university [5], may experience greater challenges when transitioning to university, for example, limited knowledge of the university system, unrealistic expectations, and ongoing external responsibilities [6]. Alongside the general barriers to PA experienced by transitioning students, including limited social support, low motivation, and increased workload [7], these amplified challenges may put the FIF student community at greater risk for inactivity. However, no research has investigated the mechanisms guiding decision making processes for this at-risk cohort, and as such, little can be done to effectively address this decline, despite evidence indicating that tailored interventions are the most efficacious [8]. The Theory of Planned Behaviour The theory of planned behaviour (TPB) [9] is a well-validated model, applied to the prediction of specific behaviours,
123
J Community Health
including PA. The TPB can also be utilised to identify key targets for tailored interventions. The theory posits that behaviour is formulated by an individual’s intention to perform a specific behaviour, with intention comprised of attitude (positive/negative evaluations), subjective norm (social approval/disapproval), and perceived behavioural control (PBC; ease/difficulty of performing a behaviour, also predicts behaviour alongside intention). Importantly, the TPB posits that attitude, subjective norm, and PBC are underpinned by behavioural (costs/benefits), normative (pressure to conform to important others’ approval/disapproval), and control beliefs (encouraging/preventative factors). These beliefs reflect the deeper cognitions that determine intention, and subsequently, behaviour [9]. The salience of these beliefs is the main factor determining their influence, with individuals tending to utilise only a small number of principal beliefs to inform their intentions and behaviour [9, 10]. Despite key beliefs being essential to the TPB, there is a lack of empirical research addressing beliefs related to PA for specific cohorts and communities. It may be assumed that similar underlying beliefs exist for the same target behaviour. However, research has indicated the importance of identifying data related to beliefs for specific cohorts [11]. The identification of these beliefs informs the complex decision-making processes that underlie PA and provides insight into the relevant individuals and groups who influence decisions for PA for at-risk communities [11]. The current research will address this gap by identifying underlying beliefs regarding PA for FIF students transitioning to university. Research has identified key beliefs in relation to PA among various other population groups. A recent study investigating the key beliefs of mothers and fathers of young children identified numerous behavioural, normative, and control beliefs significantly correlated with parents’ PA intentions and behaviour [12]. Behavioural beliefs such as ‘‘interfering with other commitments’’ identified in this population group may also be relevant among transitioning FIF students who have numerous competing demands. Other studies have identified specific sets of beliefs underlying decisions for PA; however, common beliefs are often identified. Behavioural beliefs are often centred on the benefits of health and fitness, and costs of fatigue and muscle soreness; normative social pressure from important individuals and/or community groups is predominantly from family or friends; and control beliefs surround preventative factors such as weather, lack of time or motivation, and cost [13, 14]. A systematic review of the literature relating to TPB beliefs and PA has also identified the most salient behavioural, normative, and control beliefs across a range of studies [15]. Frequently obtained behavioural beliefs surrounded concepts of PA improving both physical and psychological health; normative beliefs demonstrated that family were the group to have the strongest social influence; and control beliefs
123
identified physical limitations as the largest preventative factor for PA [15]. Despite this substantive investigation, it is uncertain as to whether these beliefs would generalise to a specific group, such as FIF students, as various individuals and community groups share different cognitions and attitudes towards PA [15]. As such, interventions formulated from generic research may not accurately reflect the processes experienced by this specific university community group [15]. It is necessary therefore, to further investigate the beliefs held by FIF students in the hope that key beliefs elicited can help improve PA for this cohort. The Present Study The current study aims to investigate the key beliefs underlying the decision to engage in regular PA during the transition to university for FIF students. The study adopts a TPB belief-based approach to identify key behavioural, normative, and control beliefs underlying FIF students’ PA intentions and behaviour. First, correlations between behavioural, normative, and control beliefs, and intention and behaviour will be explored. Second, the key beliefs that significantly predict intentions and behaviour will be investigated. Finally, the relative amount of students who fully and strongly accept each of the key beliefs identified will be examined in order to determine the utility of each belief for subsequent interventions.
Methods Participants Participants were 157 [females = 126 (80.3 %), males = 31 (19.7 %)] undergraduate FIF university students, ranging in age from 17 to 54 years (M = 19.44, SD = 4.74). The majority of participants (n = 137, 87.2 %) had completed high school within 3 years of commencing university, and were from an English-speaking background (n = 127, 80.9 %). Several inclusion criteria were required: participants were to be aged 17 years and over, FIF to attend university, and commencing a university degree for the first time that semester. Participants were excluded if they identified having a physical disability perceived to interfere with doing regular PA, as inability to be physically active could potentially affect responses. Design and Procedure The study used a prospective cross-sectional design with two stages of data collection occurring 1 week apart. The university human research ethics committee approved the study (Reference #: PSY/35/13/HREC). Prior to data
J Community Health
collection for the main study, a pilot study was conducted on a representative sample in order to elicit behavioural, normative, and control beliefs as per recommendations made by Fishbein and Ajzen [16]. A sample of 14 university students (3 male, 11 female), aged between 18 and 35 years (M = 21.57, SD = 5.37) were recruited for the pilot. Content analysis was performed on the responses, and frequently occurring beliefs were used to form the belief-based TPB measures in the main questionnaire. The participants for the main study were recruited using convenience sampling from a first year cohort of psychology students. Standard TPB items identified by Ajzen [9] were included (e.g. intention), as well as measures assessing the underlying beliefs of the TPB constructs (behavioural, normative, and control beliefs). One week after completion of the main questionnaire, participants were contacted by email or text message to complete the follow-up questionnaire. In this stage, participants were assessed on their self-reported PA during the previous week. Participants received course credit as an incentive to participate in both the pilot and the main study. Measures Target Behaviour Regular PA was the target behaviour. Based on the Australian Government Department of Health and Aging [1] definition, it was operationalised as: At least 30 minutes of at least moderate-intensity PA on most, if not all days. This can be built up during the day of a variety of activities at least 10 minutes in length, or done in one session. It involves activities that make you breathe much harder than normal. Pilot Study A pilot study was conducted to identify frequently occurring salient beliefs, later used as the belief-based TPB measures in the main questionnaire. Due to the large number of beliefs elicited within the pilot study, a 30 % frequency cut off was used to select behavioural, normative, and control beliefs [17]. To elicit salient beliefs, participants were required to list the advantages and disadvantages of doing regular PA. This informed the behavioural beliefs measure, including nine elicited beliefs (e.g. ‘‘make me fitter’’, ‘‘increase the risk of me sustaining pain and/or injury’’). Participants were also requested to list, in the order of importance, any individuals or groups who would approve or disapprove of their doing regular PA. The eight most commonly identified individuals or groups (e.g. ‘‘friends at university’’, ‘‘parents’’, ‘‘health care professionals’’) were used as a measure of normative beliefs.
Participants were requested to identify factors or circumstances that might discourage or encourage them to perform regular PA. The seven most commonly reported factors (e.g. ‘‘study commitments’’, ‘‘laziness’’, ‘‘inconvenience’’) informed the control beliefs measure. Main Questionnaire The main questionnaire was formulated of items measuring belief-based TPB constructs related to performing regular PA. The majority of the items were positively worded, with some reverse-scaled items included to reduce response bias. Items were scored on a 7-point Likert scale. Intention Intention was measured using four items assessing the strength of intention to perform PA [e.g. 1 (I do not intend) to 7 (intend) to do regular PA in the next week]. Behavioural Beliefs Behavioural beliefs were measured by assessing the beliefs elicited from the pilot study. Participants were requested to rate how likely the costs (e.g. ‘‘take up too much time’’, ‘‘make me feel tired’’) and benefits (‘‘make me fitter’’, ‘‘improve my physical health’’) would result if they did regular PA in the next week. Responses ranged from 1 (extremely unlikely) to 7 (extremely likely). Normative Beliefs Normative beliefs were measured using the normative beliefs pertaining to eight socially relevant individuals or community groups (e.g. ‘‘friends at university’’, ‘‘parents’’, ‘‘health care professionals’’) obtained in the pilot study. Participants were asked to rate how likely these individuals or community groups were to think they should do regular PA in the next week, with responses ranging from 1 (extremely unlikely) to 7 (extremely likely). Control Beliefs Control beliefs were assessed by the seven control beliefs elicited from the pilot study. Participants were asked to rate how likely internal and external factors (e.g. ‘‘study commitments’’, ‘‘laziness’’, ‘‘cost’’) were to prevent or discourage them from doing regular PA, scored from 1 (extremely unlikely) to 7 (extremely likely). Follow up Questionnaire One week following the completion of the main questionnaire, participants were contacted to complete a followup questionnaire assessing their engagement in regular PA. Participants were requested to indicate the extent to which they had done regular PA of a moderate intensity for at least 30 min in the previous week (e.g. ‘‘In the last week, to what extent did you do regular PA?’’), rated from 1 (not at all) to 7 (very often).
123
J Community Health Table 1 Means, standard deviations, and bivariate correlations of behavioural, normative, and control beliefs related to PA for first-in-family students First-in-family student beliefs
M (SD) Total (n = 157)
Intention (r) Total (n = 157)
Behaviour (r) Total (n = 85)
Behavioural beliefs Make me fitter
5.93 (1.05)
.29**
Improve my physical health Take up too much time
5.92 (1.08) 4.22 (1.49)
.31** -.28**
.15 .12 -.23*
Make me feel tired
4.40 (1.56)
-.23**
-.21
Interfere with my other commitments
4.43 (1.55)
-.25**
-.09 -.06
Make me look good
5.37 (1.40)
.19*
Give me the opportunity to socialise
4.07 (1.73)
.27**
Increase the risk of me sustaining pain and/or injury
3.74 (1.55)
Improve my mental health
5.41 (1.36)
-.16* .33**
.13 -.17 .21
Normative beliefs Friends at university
4.41 (1.57)
.23**
.06
Friends outside of university
4.81 (1.52)
.34**
-.01
Parents
5.14 (1.59)
.21**
-.15 -.16
Other family members (e.g. siblings)
4.84 (1.57)
.32**
Boyfriend/girlfriend/partner/spouse
4.75 (1.67)
.26**
Health care professionals
5.04 (1.80)
.03
-.23*
Fitness trainer/coach Fitness/sports role models
5.19 (1.75) 5.12 (1.79)
.12 .15
-.12 -.06
.09
Control beliefs Study commitments
5.34 (1.38)
-.20*
-.24*
Not enough time
4.89 (1.51)
-.23**
-.39**
Laziness
4.91 (1.70)
-.44**
-.45**
Bad weather
3.84 (1.80)
-.23**
-.45**
Lack of motivation
4.84 (1.68)
-.38**
-.52**
Inconvenience
4.25 (1.66)
-.39**
-.39**
Cost
3.06 (1.86)
-.29**
-.47**
** p \ .01; * p \ .05
Results Key Beliefs Analysis: Intentions and Behaviour In eliciting the key beliefs that underpin the intentions and behaviour of FIF students to engage in regular PA, guidelines set out by Von Haeften et al. [18] were adhered to, in order to obtain specific targets for interventions. Initially, Pearson Product-Moment Correlations were conducted for each belief set (i.e. behavioural, normative, and control beliefs) to identify the beliefs significantly correlated with intention and PA behaviour. To identify key beliefs, the beliefs that were significantly correlated within each set (i.e. behavioural, normative, and control beliefs) were then entered into subsequent stepwise multiple regressions, with intention and PA as dependent variables,
123
respectively. Finally, in order to identify key beliefs relevant to intervention, guidelines by Hornik and Woolf [19] were adopted. Beliefs were analysed to elicit the percentage of FIF students who strongly or fully accepted the belief. Means, standard deviations, and bivariate correlations of behavioural, normative, and control beliefs related to PA intentions and behaviour for FIF students are displayed in Table 1. For the behavioural beliefs, all nine beliefs were significantly correlated with intention, and one belief (‘‘take up too much time’’) was significantly correlated with behaviour. Multiple regression analyses (see Table 2) revealed four behavioural beliefs as key beliefs related to intention, namely ‘‘improve my mental health’’, ‘‘take up too much time’’, ‘‘give me the opportunity to socialise’’, and ‘‘make me fitter’’. One key
J Community Health Table 2 Stepwise multiple regression for analysis of behavioural, normative, and control beliefs predicting intention and behaviour b
R2
df
F
.27
4, 145
13.12**
% strongly accept the beliefa
% fully accept the beliefb
Both (%)
Students’ intentions Behavioural beliefs Improve my mental health
35
21.7
56.7
-.27**
12.1
3.8
15.9
Give me the opportunity to socialise
.19*
18.5
6.4
24.9
Make me fitter
.19*
43.3
31.2
74.5
24.2
12.1
36.3
Take up too much time
Normative beliefs Friends outside of university
.22**
.12
1, 150
19.45**
.46
2, 148
20.09**
.34**
Control beliefs Laziness
-.37**
7.6
4.5
12.1
Cost
-.19*
18.5
28.7
47.2
12.1
3.8
15.9
25.5
24.2
49.7 12.1
Students’ behaviour Behavioural beliefs Take up too much time Normative beliefs Health care professionals
.05
1, 81
4.58*
.05
1, 82
4.47*
.41
3, 77
17.52**
-.23* -.23*
Control beliefs Lack of motivation
-.31**
8.3
3.8
Cost
-.34**
18.5
28.7
47.2
Not enough time
-.20*
8.3
1.9
10.2
** p \ .01; * p \ .05 a
Scale measured on a 7-point scale (1 = extremely unlikely, 7 = extremely likely), with a score of six indicating strongly accepting the belief for positively worded items, and a score of two indicating strongly accepting the belief for negatively worded items b
Scale measured on a 7-point scale (1 = extremely unlikely, 7 = extremely likely), with a score of seven indicating fully accepting the belief for positively worded items, and a score of one indicating fully accepting the belief for negatively worded items
belief (‘‘take up too much time’’) was related to behaviour. For the normative beliefs, five beliefs were significantly correlated with intention, namely ‘‘friends at university’’, ‘‘friends outside of university’’, ‘‘parents’’, ‘‘other family members (e.g. siblings)’’, and ‘‘boyfriend/girlfriend/partner/spouse’’. One belief (‘‘health care professionals’’) was significantly correlated with behaviour. One key belief was elicited from the multiple regression for intention (‘‘friends outside of university’’), and one key belief was elicited for behaviour (‘‘health care professionals’’), however, this belief has a negative beta. For the control beliefs, all beliefs were significantly correlated with both intention and behaviour, thus were all entered into the multiple regressions. Two key beliefs were elicited in relation to intention, namely, ‘‘laziness’’ and ‘‘cost’’, and three key beliefs were elicited in relation to behaviour, namely, ‘‘lack of motivation’’, ‘‘cost’’, and ‘‘not enough time’’. As demonstrated in Table 2, the majority of participants did not fully or strongly accept the behavioural, normative, and control beliefs for intentions or behaviour.
Discussion The aim of the study was to identify key salient beliefs underlying the decision to engage in regular PA during the transition to university for FIF students. This addresses the scant research within the TPB literature related to the identification of key beliefs, particularly for specific at-risk community groups [15]. First, results demonstrated that a large number of behavioural, normative, and control beliefs were significantly correlated with PA intention and behaviour. Second, a number of key beliefs were identified as significant predictors of intention and/or behaviour. Finally, frequencies of FIF students who fully or strongly hold key beliefs were obtained. Such results are congruent with previous TPB belief-based research [12–15]. The information obtained is pivotal to the formulation of effective targeted interventions to encourage PA engagement amongst this at-risk community. For the behavioural beliefs analyses, a number of positive outcomes arose, including ‘‘improve my mental health’’, ‘‘give me the opportunity to socialise’’, and ‘‘make me fitter’’, as well as the negative outcome of ‘‘take up too
123
J Community Health
much time’’. Beliefs obtained are similar to those from previous studies, with a focus on health and fitness. In contrast however, the current study did not identify weight control or weight loss as a key behavioural belief [12–14]. Thus, interventions should not focus on this as an important element, but rather, the positive health benefits of fitness and improved mental health. When reviewing the percentage of students who strongly or fully accepted these beliefs, approximately half or less fit into these categories (except for ‘‘make me fitter’’). This is important as such beliefs can be encouraged in order to increase PA engagement for FIF students. It is evident that the influence of competing demands during the transition to university plays a significant role in PA decision-making, as perception of the time available to engage in PA is salient to the formation of both intentions and behaviour. The identification of ‘‘take up too much time’’ highlights the demands placed on university students and the subsequent influence on behaviour. Thus, activities perceived to be time consuming may be particularly salient for this community group whose time management becomes increasingly important when managing university studies [20]. Further, it is relevant due to the low percentage of students who strongly or fully accepted this belief. As such, it is relevant to targeted interventions, where encouraging perceptions of self-efficacy related to time management may result in increased PA engagement for this transitioning community group. In relation to normative beliefs, social pressure from ‘‘friends outside of university’’ was identified as the key belief for PA intention, in relation to FIF students’ perceptions of who would think that they should do regular PA. However, less than half of the participants strongly or fully accepted this belief. This differs from the systematic review identifying family as the most important individual or community group to exert social pressure influencing ones motivation to engage in PA [15]. As such, it may be relevant to incite norms of social support and encouragement between a FIF student and their friends outside of university, rather than focusing on family. The supportive community that transitioning students surround themselves with, particularly their friends external to university, may be influential to students’ decisions to be physically active. Whilst literature emphasises the importance of becoming connected with peers at university for academic adjustment [21], the current research suggests that maintaining relationships with friends outside of university is also relevant to ensuring holistic wellbeing throughout the transition. For behaviour, the normative belief that arose as key was the influence from health care professionals; however, this was a negative predictor. This indicates that despite FIF students’ belief that a health care professional would think that they should do regular PA, this does not predict
123
increased PA behaviour. This may be due to the pressure placed on students from various sources such as university staff, bosses, parents, and friends to fulfil various commitments. The added pressure of a health care professional encouraging a student to remain physically active during this transition may have the opposite effect, whereby the pressure demotivates them to be active. Further research is required to understand how social pressures truly function for transitioning university students, and the effect that this has on PA behaviour. Control beliefs also arose in relation to both PA intention and behaviour. Two key beliefs were elicited in relation to intention, namely ‘‘laziness’’ and ‘‘cost’’, suggesting that when formulating intentions, motivational and cost related factors are salient. This is similar to beliefs obtained in previous research [12–15]. However, FIF students did not identify health issues or weather as preventative factors, as is commonly identified in other belief research [12– 15]. This may indicate either that these factors are not relevant to FIF students’ decisions for regular PA, or that other factors are more salient. The identification of ‘‘cost’’ may be particularly salient to transitioning students as they are in a period of financial stress, where the predominant costs that they face are university related. As such, students may feel that they are unable to afford PA related expenses, such as joining a gym. Importantly, less than half of the participants strongly or fully accepted the belief that these factors would not prevent them from doing regular PA. Therefore, these are important targets for intervention. In relation to behaviour, similar factors are key, for example ‘‘lack of motivation’’, ‘‘cost’’, and ‘‘not enough time’’. Therefore, it can be argued that competing demands faced by FIF students during the transition to university may reduce their engagement in regular PA. Specifically, for FIF students, their time allocation and motivations may now focus on university studies, and as such, students may feel that there is little time or motivation remaining to focus on PA. Notably, a very low percentage believed that laziness and lack of motivation would not prevent them from engaging in regular PA, and are important factors to address when formulating proactive interventions for this cohort. According to Ajzen’s TPB, in order to formulate an effective intervention, beliefs should be elicited from the target population, as these underlying beliefs function differently for varying at-risk community groups [9]. Stemming from the beliefs identified in the current study, interventions can focus on the way that these beliefs function specifically for FIF students transitioning to university. Positive behavioural beliefs, such as the ability of PA to ‘‘improve my mental health’’ and ‘‘make me fitter’’ can be encouraged by providing education about self-care within orientation events for transitioning students.
J Community Health
Students could be informed about the positive benefits of PA for both physical and mental health, particularly focusing on the cognitive benefits [2]. In addition, attention could be given to the need to maintain relationships with friends outside of university, and engaging in fun activities with friends that are physically active. This would target the behavioural belief of ‘‘give me the opportunity to socialise’’ whilst incorporating the social influence from friends outside of university. When addressing the salience of time and motivation, students could be encouraged to plan for PA as part of their everyday life. For example, students could be encouraged to include small amounts of PA into their study timetable, possibly as a study break. As mentioned earlier, PA improves cognitive abilities and so, by including it in everyday activities, students may feel better equipped for university studies. When addressing the control belief of cost, students could be encouraged to consider forms of PA that are not costly, for example, walking around campus, or riding a bike to university. All of these intervention strategies can be addressed and implemented by a supportive university community who understands the benefits of maintaining regular PA during the transition to university for students’ overall wellbeing. The current study has various strengths. First, to the authors’ knowledge, the study was the first to address the role of underlying key beliefs for FIF students in relation to their engagement in regular PA, important for the formulation of effective and targeted interventions to encourage regular PA among this at-risk community group. Despite this strength, an important limitation of the current study is the use of self-report measures to obtain PA data. Selfreport is problematic as it is susceptible to social desirability bias. However, a recent study investigating the use of web-based self-report (as used in the current study) in relation to PA, demonstrated that social desirability was not related to self-reported PA, nor was it moderated by demographic variables [22]. Despite this, it would be beneficial to source data from more objective sources, such as electronic monitors or externally based assessments from friends or family, in order to increase accuracy of results, and gain a deeper understanding of the influence of beliefs on actual PA behaviour. In addition, the crosssectional nature of the research limits the understanding of the long-term function of beliefs and their effect on PA behaviour. Influences may change throughout the course of a FIF student’s studies as the student adjusts to university and becomes acquainted with the system. As such, future research would benefit from investigating the belief patterns in relation to PA behaviour throughout the university career. In summary, the current study identified behavioural, normative, and control beliefs related to PA in FIF students
transitioning to university, with underlying key beliefs predicting intention and behaviour. The information provided from this analysis can be applied to the construction of intervention programs, with the intention of addressing barriers to PA experienced by FIF students, as well as promoting engagement in regular PA during the transition to university. Awareness of the empirically established benefits of engaging in regular PA, in addition to the insufficient level of PA engaged in by a large number of university aged individuals, as well as demonstrated declines in regular PA upon transitioning to university shown throughout the literature, exhibits the importance of identifying the factors and underlying beliefs that predict engagement in regular PA. By identifying these, opportunities arise to develop effective intervention strategies to target beliefs related to PA decisions, with the hope of preventing declines in PA and increase wellbeing among FIF university students.
References 1. Australian Government Department of Health and Aging. (2005). An active way to better health: National physical activity guidelines for adults. Canberra, ACT: Commonwealth of Australia. 2. Guiney, H., & Machado, L. (2013). Benefits of regular aerobic exercise for executive functioning in healthy populations. Psychonomic Bulletin Review, 20(10), 73–86. doi:10.3759/s13423012-0345-4. 3. Australian Bureau of Statistics. (2013). Australian Health Survey: Physical Activity, 2011–2012, (no. 4364.0.55.004). Canberra, ACT: Australian Bureau of Statistics. 4. Bray, S., & Born, H. (2004). Transition to university and vigorous physical activity: Implications for health and psychological wellbeing. Journal of American College Health, 52(4), 181–188. http://search.proquest.com.libraryproxy.griffith.edu.au/docview/ 213030921?accountid=14543. 5. Talebi, M., Matheson, K., & Anisman, H. (2013). Does being first in family matter? The role of identity in the stigma of seeking help among first and non-first in family university students. The International Journal of the First Year in Higher Education, 4(1), 47–58. doi:10.5204/intjfyhe.v4i1.137. 6. Luzeckyj, A., King, S., Scutter, S., & Brinkworth, R. (2011). The significance of being first: A consideration of cultural capital in relation to ‘‘first in family’’ student’s choices of university and program. A practise report. The International Journal of the First Year in Higher Education, 2(2), 91–96. doi:10.5204/intfyhe.v2i2.89. 7. Gyurcsik, N., Bray, S., & Brittain, D. (2004). Coping with barriers to vigorous physical activity during transition to university. Family Community Health, 27(2), 130–142. http://ovidsp.tx.ovid. com.libraryproxy.griffith.edu.au/. 8. Muller-Riemenschneider, F., Reinhold, T., Nocon, M., & Willich, S. (2008). Long-term effectiveness of interventions promoting physical activity: A systematic review. Preventative Medicine, 47(4), 354–368. doi:10.1016/j.ypmed.2008.07.006. 9. Ajzen, I. (1991). The theory of planned behaviour. Organizational Behaviour and Human Decision Processes, 50(2), 179–211. doi:10.1016/0749-5978(91)90020-T. 10. Van de Plight, J., & De Vries, N. (1998). Belief importance in expectancy-value models of attitudes. Journal of Applied Social
123
J Community Health
11.
12.
13.
14.
15.
16.
Psychology, 28(15), 1339–1354. doi:10.1111/j.1559-1816.1998. tb01680.x. Hamilton, K., & White, K. (2010). Understanding parental physical activity: Meanings, habits, and social role influence. Psychology of Sport and Exercise, 11(4), 275–285. doi:10.1016/j. psychsport2010.02.006. Hamilton, K., & White, K. (2011). Identifying key belief-based targets for promoting physical activity among mothers and fathers with young children. Journal of Science and Medicine in Sport, 14(2), 135–142. doi:10.1016/j.jsams.2010.07.004. White, K., Terry, D., Troup, C., & Rempel, L. (2007). Behavioural, normative, and control beliefs underlying low-fat dietary and regular physical activity behaviours for adults diagnosed with type 2 diabetes and/or cardiovascular disease. Psychology, Health and Medicine, 12(4), 485–494. doi:10.1080/13548500601089932. Conn, V., Tripp-Reimer, T., & Maas, M. (2003). Older women and exercise: Theory of planned behaviour beliefs. Public Health Nursing, 20(2), 153–163. doi:10.1046/j.1525-1446.2003.20209.x. Downs, D., & Hausenblas, H. (2005). Elicitation studies and the theory of planned behaviour: A systematic review of exercise beliefs. Psychology of Sport and Exercise, 6(1), 1–31. doi:10. 1016/j.psychsport.2003.08.001. Fishbein, M., & Ajzen, I. (1975). Beliefs, attitude, intention and behaviour: An introduction to theory and research. Reading, MA: Addison-Wesley.
123
17. Hamilton, K., & White, K. (2010). Identifying parents’ perceptions about physical activity: A qualitative exploration of salient behavioural, normative, and control beliefs among mothers and fathers of young children. Journal of Health Psychology, 15(8), 1157–1169. doi:10.1177/1359105310364176. 18. von Haeften, I., Fishbein, M., Kasprzyk, D., & Montano, D. (2001). Analyzing data to obtain information to design targeted interventions. Psychology, Health and Medicine, 6(2), 151–164. doi:10.1080/13548500125076. 19. Hornik, R., & Woolf, K. (1999). Using cross-sectional surveys to plan message strategies. Social Marketing Quarterly, 5(1), 34–41. doi:10.1080/15245004.1999.9961044. 20. MacCann, C., Fogarty, G., & Roberts, R. (2011). Strategies for success in education: Time management is more important for part-time than full-time community college students. Learning and Individual Differences, 22(5), 618–623. doi:10.1016/j.lindif. 2011.09.015. 21. Ward, L., Siegel, M., & Davenport, Z. (2012). First-generation college students: Understanding and improving the experience from recruitment to commencement. http://www.eblib.com. 22. Crutzen, R., & Goritz, A. (2011). Does social desirability compromise self-reports of physical activity in web-based research? The International Journal of Behavioural Nutrition and Physical Activity, 8(31), 31–35. doi:10.1186/1479-5868-8-31.
