‘Bring Your Own Device’: Considering potential risks to student health

Abstract

Background and context:

Schools in Australia and internationally are increasingly adopting a Bring Your Own Device (BYOD) approach to teaching and learning.

The review:

While discussion of a BYOD approach has taken place, there is a dearth of consideration of the potential impact of BYOD policy on student health. Implementation of a BYOD policy may have implications for increased sedentary behaviour, as well as spinal and postural health. Increased use of devices at home to complete homework may also have implications for sleep duration, which in turn may impact upon a range of physical and cognitive issues. BYOD implementation may also increase student vulnerability to cyberbullying. These and other health issues are discussed.

Recommendations:

Schools may find it helpful to adopt a risk analysis approach informed by social cognitive theory, with an emphasis on the provision of knowledge and the fostering of self-efficacy in order to safeguard against potential health risks. As this issue has significance for researchers in both health promotion and education, an interdisciplinary approach should be taken.

Keywords

Health education school health promotion healthy schools safe schools

Introduction

A Bring Your Own Device (BYOD) approach to the use of information and communication technology (ICT) is becoming increasingly popular in schools internationally and in Australia (Foo, 2013), with suggestions that Australian schools have finally met the anticipated ‘tipping point’ (Newhouse, 2014) where 1:1 device access is increasingly the norm. A BYOD approach is also known as Bring Your Own Technology (BYOT) and is often discussed within the broader context of mobile learning (m-learning). M-learning refers to the delivery of learning experiences to learners wherever required, as facilitated by the use of mobile devices such as tablets and laptops. Under a BYOD approach, students are expected to bring in an electronic device with wireless capability, usually a laptop computer or tablet, which is within the defined specifications of their school.

The Australian national government provided substantial funding in 2008 towards equipping students with laptops, although this is now no longer the case. In 2008, the national government funded what it termed a Digital Education Revolution, which aimed to supply every student in Years 9–12 with a computer before 2012. Since this funding programme ended, schools have needed to decide if they wished to continue providing high levels of access to computers to their students, and if so, how best to maintain this. A BYOD approach offers an attractive alternative, as it is generally parent-funded, rather than dependent on government funds and school support.

A BYOD approach is responsive to the need for students to achieve competence in digital literacy in readiness for success in academic, vocational and social demands of life in the digital age, a concern both locally and internationally. In 2013, the first international comparative study into secondary students’ digital literacy, the International Computer and Information Literacy Study, was undertaken in order to inform understandings of students’ ‘ability to use computers to investigate, create and communicate in order to participate effectively at home, at school, in the workplace and in society’ (Fraillon et al., 2013: 17). The study found that Australian students demonstrated comparably high levels of digital literacy (De Bortoli et al., 2014).

In order to comply with the expectations of the new Australian Curriculum, access to ICT in the school setting is essential, and this can be facilitated through a BYOD approach. Not only is ICT capability identified as one of the key General Capabilities in the Australian Curriculum, it is also features in the content descriptions of specific subjects. For example, within the Literacy strand and Creating Texts sub-strand in English, Year 9 students (usually aged 13 or 14) are required to ‘Use a range of software, including word processing programmes, flexibly and imaginatively to publish texts’ (Australian Curriculum Assessment and Reporting Authority [ACARA], n.d.-a). The positioning of ICT in the curriculum is such that it is ‘therefore no longer optional for teachers to integrate digital texts in the classroom’, and ‘it is of course convenient and appropriate to work with such texts not only on desktop or laptop computers, but on mobile handheld devices’ (Oakley et al., 2012: 8).

Implications for student health

Lost in the push towards increased technological immersion at schools is consideration of the impact of BYOD policy on students’ physical and mental health and, to date, the potential health implications of introducing a BYOD policy in schools have been peripheral to discussion about implementation. This may be due to the fact that they have yet to be adequately addressed in research. While the use of media can have important positive effects, evidence clearly suggests that use of devices can ‘contribute substantially to many different risks and health problems’ (Strasburger et al., 2013: 958). BYOD is likely to result in significantly increased screen use, and unless students respond to increased screen-time in school by reducing screen-time at home, overall screen-time may increase markedly.

Current screen-time recommendations in Australia were developed in recognition of the range of negative health effects of viewing screen media. Screen-time here ‘refers to the amount of time children spent watching television including videos and digital versatile disc (DVDs), playing computer games on a games console or on personal computers, and using computers for other purposes’ (Commonwealth Scientific and Industrial Research Organisation [CSIRO], 2008). Australian guidelines recommend, ‘that children aged 2–18 years should not spend more than two hours per day using electronic media for entertainment’ (Commonwealth Department of Health and Ageing [CDHA], 2004). Only one-third of young Australians aged 9–16 years were meeting this guideline in 2007(CSIRO, 2008); by 2010 more than half of primary schools students and three-quarters of secondary school students exceeded the 2-hour limit (Hardy, 2011). The 2-hour guideline has been retained in subsequent iterations of the recommendations (Australian Government Department of Health [AGDH], 2014).

What makes it problematic to apply these guidelines to the educational context is that screen-time for educational purposes is excluded from the 2-hour guidelines, which deal specifically with screen-time ‘for entertainment’ (CSIRO, 2008: 31). Excluding educational screen-time from the guidelines can position it as peripheral to health promotion concerns. Furthermore, this exclusion can lead to the perception that even extensive screen-time for educational purposes holds no health risks, therefore reducing the likelihood that schools will attempt to regulate screen-time for educational purposes. While the 2007 CSIRO data on screen-time usage found that ‘during the school day, about 5–10% of adolescents were engaged in screen-time, mainly using computers during classes’ (p. 33), as BYOD is increasingly implemented, it can be anticipated that this percentage will rise dramatically. Research into the impact that this increase will have on student health should ideally be undertaken prior to widespread implementation of BYOD, however this tipping point may have already been surpassed. Introducing BYOD in a school may also increase the amount of time spent on devices during recreational periods at lunch and recess.

Although this paper focuses on secondary schools, many of the issues raised have currency for primary schools also, if there is increasing interest in BYOD in this context into the future. While in some areas of the USA, BYOD programmes have been implemented first in the lower grades and then extended upwards (Quillen, 2011), the aforementioned Digital Education Revolution provided devices to higher grades (pp. 9–12), thus at present, these concerns may have more relevance in the secondary school context. Research suggests that younger children meet the recommended screen guidelines ‘more often than older children’ (CSIRO, 2008: 31), and that screen-time steadily increases during childhood, peaking between the ages of 13–14 at ‘over 4 hours per day for boys and 3.5 hours per day for girls’ (p. 32).

A BYOD policy is likely to lead to a significant workplace change for students, which is likely to have similar effects on movement to those caused by the widespread adoption of computers in the workplace 30 years ago:

Until that time, office work had involved a range of activities including typing, filing, reading, and writing. Each activity was adequately varied in the requirements of posture and vision, posing a natural ‘break’ from the previous activity. The introduction of computers, however, has combined these tasks to where most can be performed without moving from the desktop, thereby improving quality, production, and efficiency. (Blehm et al., 2005: 253)

Introduction of a BYOD policy in the school is also likely to lead to a loss of natural ‘breaks’, subsequent increasing in sedentary behaviour. While the extent to which BYOD increases sedentary time at school has not been explored in the research, it can be surmised that introduction of BYOD may increase sedentary time, and that this is an area warranting future investigation, particularly as ‘workplace sitting time’ has been identified as a key area for ‘future population surveillance of sedentary behaviour’ (Tremblay et al., 2010: 735). While the implementation of increased device use in schools makes the school environment more workplace-like, at school students may not commonly be inducted into workplace safety strategies around sedentary behaviour and lengthy computer or device use, which are commonly part of induction practices in contemporary office environments, in order to ensure compliance with occupational health and safety policy. For example, the Australian government agency responsible for workplace safety, Comcare (2008), has produced a guide outlining health and safety in the office, which emphasises that ‘repetitive tasks such as using a keyboard and mouse should be performed for short periods’ and ‘best interspersed with other tasks requiring different postures and movements’ (p. 14).

Sedentary time itself is associated with significant health risk. A Canadian study exploring the relationship between screen-time and the likelihood of metabolic syndrome, which is characterised by biological and physiological symptoms which generally precede the development of type 2 diabetes and cardiovascular disease, found that high screen-time was significantly associated with increased likelihood of metabolic syndrome ‘independent of physical activity, diet and other important covariates’ (Mark and Janssen, 2008: 159). Similarly, a US study of 54,863 children aged 6–17 found that the greater use of computers was associated with being overweight or obese (Russ et al., 2009). These findings were supported by a substantial longitudinal study in the USA which found that screen-time in adolescence ‘independently and significantly predicted incident obesity in early adulthood’ (Boone et al., 2007).

Even in the unlikely event that future research finds that increasing screen-time through implementation of BYOD does not increase amount of sedentary time, high use of devices has been found to pose additional health risks. Emerging research suggests that touch-screen tablets may impact the posture of heavy tablet users, in addition to ‘discomfort in a number of body areas, especially the neck and wrists’ (Stawarz and Benedyk, 2013: 1), with the British Chiropractic Association’s (2014) research into this area finding that ‘40% of 11 to 16 year olds in the UK have experienced back or neck pain’ with 15% of this pain being perceived as the result of ‘using a laptop, tablet or computer’. A large (N = 31,022) study of adolescents in Denmark, Sweden, Norway, Finland, Iceland and Greenland found that computer use was a contributing factor to complaints of backache and headache in young people (Torsheim et al., 2010). Further research is needed in this area.

Extended screen-time has also been related to the occurrence of a number of ocular health issues, with ‘eye-related symptoms’ deemed ‘the most frequently occurring health problems’ resulting from heavy screen use in the adult workplace (Blehm et al., 2005: 254). These symptoms, which include ‘eyestrain, tired eyes, irritation, redness, blurred vision, and double vision’ are collectively known as Computer Vision Syndrome (CVS) (p. 253). CVS is thought to be primarily caused by near and long work at the computer (Yan et al., 2008: 2032), and although it has not been investigated in the context of BYOD in secondary school, a strong association has been found between school students’ prolonged computer use and low vision (Bener et al., 2010). While more research is needed in this area, it is suggested that children take a ‘brief eye-focusing break every 20 minutes to prevent eyestrain’, ideally combined with standing and movement (Young, 2009: 365).

BYOD use at school is likely to contribute to increased device use at home, at least for homework purposes. Night time use of devices has been found to be significantly associated with ‘shortened sleep duration, excess body weight, poorer diet quality, and lower physical activity levels’ (Chahal, et al., 2013: 42). These findings have been consistently supported in the research, such as in a large (N = 3,427) study of Australian children, which found a bidirectional relationship between sleep duration and children’s media use (Magee et al., 2014). Sleep deprivation is a health issue as it is associated with increased risk of obesity and diabetes (Knutson et al., 2007), as well as negative cognitive issues including tiredness, difficulty concentrating and irritability, which can ‘mimic attention deficiency hyperactivity disorder’ (Dahl, 1996: 44). Therefore, any impact of BYOD at school on home device use also warrants further investigation.

While research in the area of mental health effects of sustained screen-time is mounting, there has been controversy around whether Internet addiction¹ is a mental health issue in its own right, or symptomatic of other mental health issues (American Psychiatric Association [APA], 2013a, 2013b; Pies, 2009). Studies have explored the relationship between Internet addiction and depression, finding that Internet addiction rates in some populations are very high, with nearly one-third of adolescents in a non-clinical sample of Korean adolescents classified as experiencing Internet addiction, and with Internet addiction significantly associated with both obsessive compulsive and depressive symptoms (Ha et al., 2007). A Chinese study looking at a sample of over 5,000 students in junior high found that high screen-time and related insufficient physical activity led to increased risk of depressive and anxiety symptoms (Cao et al., 2011).

Adopting a BYOD policy could also provide increased opportunities for students to engage in cyberbullying, which is associated with even higher rates of depressive symptoms than ‘traditional’ bullying as well as anxiety and other psychosomatic symptoms (Campbell et al., 2012; Perren, et al., 2010). This form of bullying has a high rate of prevalence in Australia, with the period of transition from primary school to high school being a particularly high-risk period (Price and Dalgleish, 2010). While as previously noted, cybersafety has received consideration when implementing BYOD, there is little research indicating that the impact of BYOD on occurrence of cyberbullying has also received adequate consideration. While much of cyberbullying may currently be conducted using mobile phones for phone call, text message and instant message bullying (Smith et al., 2008), phone use is currently controlled or ‘excluded’ in most secondary schools. In such circumstances, implementing BYOD may allow students a potential alternative avenue for bullying in an environment where phone use is banned or controlled, facilitating student access to a device with which they can make calls, send texts and instant messages during school hours, lifting this exclusion. The implications of these increased opportunities for engaging in cyberbullying through implementation of BYOD need to be explored.

Using a risk analysis approach

The benefits of digital literacy for current and future generations are significant. This paper does not argue for a regression to past practices, or the rejection of new devices. What it does suggest is that the health implications of increasing device use need to be considered, and mitigated where possible. While waiting for future research to address the potentially significant impact of BYOD on student health across a range of areas, some of which were explored previously, schools could ideally adopt a risk analysis approach to safeguard student health.

While the principles of risk management originate in manufacturing industries, they have been subsequently applied to health care to offer a basis for management of clinical risk (Dickson, 1995). When applied to the context of health promotion, social cognitive theory places understanding of risks and benefits as ‘core determinants’ for effectively translating knowledge into optimal health practice. These ‘core determinants’ include the following:

… knowledge of health risks and benefits of different health practices, perceived self-efficacy that one can exercise control over one’s health habits, outcome expectations about the expected costs and benefits for different health habits, the health goals people set for themselves and the concrete plans and strategies for realising them, and the perceived facilitators and social and structural impediments to the changes they seek. (Bandura, 2004: 144)

Applying social cognitive theory in this context can be particularly appropriate as by implementing BYOD, schools act as an influential social agent. While this process is hindered by the lack of research specific to the health risks of BYOD implementation, schools could experimentally extrapolate the health risks of increased screen-time for the purposes of identifying potential risks, as well as monitoring and mitigating potential associated risks to student health. Knowledge and self-efficacy can be particularly pertinent in this context, and will therefore be explored in some detail.

Knowledge

Without sound knowledge of the health risks of increased screen-time, the desire to moderate screen-time may not be present. There should be an evaluation of levels of awareness of suggested screen-time limitations in schools and homes. Understanding of the risks of sustained screen-time must be present in all stakeholders: students, teachers and parents. Schools should inform parents about the importance of monitoring their child’s screen use. This becomes increasingly complicated when the majority of homework is required to be performed on a device, and it may be just as difficult for parents to ascertain if homework is being done at home, as it is for teachers to determine if schoolwork is being done in class. In consequence, parents may be reticent to attempt to exert boundaries over device use. The level of surveillance required to monitor students may be unacceptable and unrealistic in consideration of other demands on parents’ time, but even if this is impracticable, parents should be aware of how to assess whether their children are exhibiting dependent behaviours. Even though understanding of Internet dependency is still at the formative rather than the established level, credible and accessible health promoting resources are already available to support parents in this area such as on the Better Health Channel (2011), which are inclusive of parental diagnostic criteria.

Schools should gather knowledge about young people’s screen use within their own community in order to make informed decisions. For example, some consideration should be given to quantifying the amount of screen-time exposure before and after BYOD implementation in their students to determine if screen-time levels are exceeding limits set by advising bodies. The American Academy of Paediatrics suggests that health professionals working with schools should ‘work collaboratively with parent-teacher associations to encourage parental guidance in limiting or monitoring age-appropriate screen times’ (Strasburger et al., 2013: 960).

Not all activities should be completed on devices, especially those that would have previously involved movement. If collaborative activities where students would stand in a group, negotiating their roles, are replaced with remote, stationary collaboration, whereby students no longer work face-to-face, there may be implications for the development of interpersonal skills as well as sedentary behaviour. If teachers are aware of the potential risks of screen-time for such diverse areas of potential health impact as sedentary behaviour, CVS, spinal and postural health, increased home screen use resulting in sleep disorders, Internet addiction and increased capacity for cyberbullying, they can actively counter some of these issues through in-class activities which should be supported by broader school policies. Once reducing the potential health risk of increased screen-time resultant from BYOD implementation is broadly understood and subject to due consideration pre- and post-implementation, teachers can act to ensure that the benefits of BYOD are not overshadowed by the increase of health risks, by adapting pedagogy to ensure that students still move around and interact face-to-face in their classrooms, and that students and their parents are knowledgeable about the potential risks.

Perceived self-efficacy

A key role of social relations in health promotion is to increase the sense of self-efficacy in the recipient group. In this case, this might involve engaging the students in a degree of self-regulation of screen-time and also personal monitoring for ill effects. While this approach aligns with the social cognitive model, it is also reflective of productive pedagogy as outlined by Lingard et al. (2003), in that increasing student efficacy relates to ‘self-regulation’, which is one of the 20 productive pedagogies these researchers identify (p. 411). A Risk Analysis Approach is reflective of best practice in teaching strategies, and fostering student self-regulation and self-efficacy can become part of the educational plan.

Indeed, the concept of the critical, self-reflective consumer aligns well with curricular requirements in the Health and Physical Education subject in the Australian Curriculum. For example, the Years 9 to 10 Content Descriptions (ACARA, n.d.-b) state that students should be able to ‘propose, practise and evaluate responses in situations where external influences may impact on their ability to make healthy and safe choices’. As the BYOD policy is an external influence that may lead to negative impacts on student health through the likelihood of increased screen-time, developing self-efficacy in this area can align with the curriculum. Critical consumption is also explored in the English subject area, and thus there is scope for cross-curricular exploration of this issue.

It could be contended that parents and schools also need to develop a sense of efficacy in their capacity to exert a positive influence on students. While qualitative research currently suggests that many parents do not perceive screen-time as a problem (Hardy, 2011), research also suggests that restrictive guidance of screen-time can reduce screen-time (Van den Bulck and Van den Bergh, 2000). Parents may lack confidence restricting their children’s access to Internet technology as they may view their children as more knowledgeable about the medium than themselves (Bittman and Sipthorp, 2011). They may thus hold a relatively ambivalent position compounded by a sense of inefficacy through a comparative lack of knowledge (Livingstone, 2007).

Conclusion

This paper has been written to trigger interdisciplinary discussion and research on the implementation of BYOD policies in schools, both in Australia and internationally, attempting to engage researchers in health promotion with an issue arising in the education realm. It seeks to encourage researchers, leaders and teachers in education to consider viewing BYOD implementation through a health lens, in addition to the education-specific material and ideological considerations that are currently explored.

While schools have increasingly embraced technology in recent times, with some research indicating resultant benefits for student digital literacy, motivation and assessment scores, the introduction of BYOD may signal significant changes to school cultures that are only being understood through implementation. It is concerning that little consideration appears to have been given to the potential impacts of BYOD policy on student health, particularly due to increasing understandings of the impacts of physical and mental health issues that emerge from high levels of screen-time in young people. Research exploring the impact of BYOD implementation is overdue as the pace of implementation is growing despite the lack of evidence based and empirically informed strategies to mitigate potential risks.

Schools need to take responsibility for ensuring that their introduction of a BYOD policy does not contribute to negative implications for students’ physical and mental health.

Despite the paucity of research in this area specific to the impact of BYOD policy on student health, schools are nonetheless encouraged to be active in identifying, monitoring and mitigating potential associated risks to student health, as the risks of excessive screen-time are well-established in other areas as aforementioned. A Risk Analysis Approach that fosters knowledge and self-efficacy is presented as one possible avenue for safeguarding against the potentially negative health consequences resultant from BYOD.

What is clear is that more research is urgently needed in this area, as technological advancement rapidly outpaces relevant research output. First, data are needed to confirm what may be felt as obvious: does BYOD policy increase student screen-time? While studies of students in the USA and Australia who have a BYOD (or 1:1 laptop) policy suggest that these students engage in more than 3 hours of computer time per day (Harris and Straker, 2000; Sommerich et al., 2007), without knowing their engagement levels prior to exposure to these programmes, it is impossible to ascertain the impact of BYOD on student screen- time. If this foundational supposition is resolved, and an increase in screen-time is confirmed, some of the additional myriad questions to be posed include the following:

To what extent has screen-time increased?

Do the Australian Guidelines need to be adjusted to be inclusive of screen-time for educational purposes (in school and at home)?

Has shifting to a BYOD policy impacted student health across a range of health dimensions?

Does BYOD lead to potential health benefits? For example, has the potential mobility of BYOD led to students moving into everyday environments (where students may be less likely to be stationary)?

Does spending greater time on screen in school lead to greater time being spent on screen for entertainment or educative purposes at home?

Does implementation of BYOD lead to increased screen-time during school-based recreational periods such as lunch and recess?

Does engagement with diverse screen types impact differently on student health?

The BYOD movement is acquiring considerable momentum. It is important that a sense of urgency in implementation does not expose young people to unmitigated and unmonitored health risks, and this can only be ensured when our knowledge of these potential risks is better appreciated in the context of implementation. Schools are expected to play a key role in supporting both parental and student education for the mitigation of known issues around screen-time such as problematic levels of video gaming at home. Schools must also provide a model for screen use that is both responsible, and responsive, to the potentially competing interests of student health and ICT skills development.

Footnotes

Funding

The author(s) received no financial support for the research, authorship and/or publication of this article.

Notes

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