Share this article on:

The Ubiquity of the Screen: An Overview of the Risks and Benefits of Screen Time in Our Modern World

LeBlanc, Allana G.1; Gunnell, Katie E.2; Prince, Stephanie A.1; Saunders, Travis J.3; Barnes, Joel D.2; Chaput, Jean-Philippe2

Translational Journal of the American College of Sports Medicine: 1 September 2017 - Volume 2 - Issue 17 - p 104–113
doi: 10.1249/TJX.0000000000000039
Review Article

ABSTRACT: Sedentary behavior, and specifically screen-based sedentary behavior, has been a focus for health researchers, engineers, telecommunications companies, gamers, and the media for many years. In recent years, research in this area has proliferated at an exponential rate. On one side, arguments have been made that screen time is harmful to the healthy growth and development of children and youth. On the other side, modern technology has far surpassed any prediction of success and become a fixture of daily living, making life easier and providing opportunities never thought possible. Regardless, screens have become omnipresent in our society, and it is important to understand the risks and the benefits associated with their use. Excessive time spent in various sedentary behaviors can coexists in a lifestyle that includes sufficient levels of moderate- to vigorous-intensity physical activity, but research has shown that for optimal health benefits, individuals should be both physically active and limit their sedentary behaviors (especially screen time). This narrative review provides a brief history of research on sedentary behavior in the context of screen time, the evolution of screens and screen time, highlights the risks and benefits of screen-based sedentary behavior, and provides experimental evidence for reductions in habitual screen time.

1Division of Prevention and Rehabilitation, University of Ottawa Heart Institute, Ottawa, Ontario, CANADA; 2Healthy Active Living and Obesity Research Group, Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, CANADA; and 3Department of Applied Human Sciences, Faculty of Science, University of Prince Edward Island, Charlottetown, PEI, CANADA

Address for correspondence: Jean-Philippe Chaput, Ph.D., Healthy Active Living and Obesity Research Group, Children's Hospital of Eastern Ontario Research Institute, 401 Smyth Road, Ottawa, Ontario, Canada K1H 8L1 (E-mail: jpchaput@cheo.on.ca).

Back to Top | Article Outline

INTRODUCTION

Screens are ubiquitous in today's world. Technology continues to evolve at a very rapid rate, challenging behavioral and physiology researchers. Researchers have attempted to respond to this evolution, and in recent years, we have seen an exponential growth in the number of scientific publications related to sedentary behavior and screen time (Fig. 1). However, advances in technology may hamper these efforts. In fact, by the time scientists evaluate the psychometric properties of tools for measuring screen time, technology may have already evolved, rendering their efforts outdated, or no longer applicable to the current technology landscape (e.g., a newer version of an existing device or popular devices becoming obsolete). For example, most self-report questionnaires focus primarily on television and computer time, as opposed to the smartphones and tablets that make up an increasingly large proportion of discretionary screen time. Further, researchers often ignore the issue of multitasking (i.e., using multiple screens simultaneously), which precludes accurate estimates of an individual's “total” screen time. Moreover, evolving definitions of the term “sedentary behavior” and the use of proxy measurement tools have often been used to draw conclusions about the health effects of sedentariness, making it difficult to ascertain the true magnitude of the relationship between sedentary time, physiology, and health (60).

Emerging evidence indicates that the negative health effects of specific modalities of sedentary behavior (e.g., screen time) may be worse than others (e.g., reading) (13). Given the rapid rise in screen-based sedentary behavior, and the importance of technology in day-to-day life, screen time will be the focus of this review. Other operational definitions can be found in Table 1 and will be referenced throughout this work. Further elaboration on the term sedentary behavior, and the importance of screen time, is presented in the following section.

The objective of this narrative review is to discuss the evolving definition of sedentary behavior, highlight the risks and benefits of screen time in today's society, provide an overview of interventions aimed at reducing sedentary and screen time, and list key future research directions. Through this review, we aim to provide a dynamic discussion centered on multiple recent systematic reviews, meta-analyses, and primary studies. It is hoped that this contribution will inform researchers, practitioners, and policy makers about the current state of evidence from the sedentary behavior field to spur future innovative research and facilitate its translation into clinical and community settings.

Back to Top | Article Outline

CURRENT DEFINITION OF SEDENTARY BEHAVIOR

In recent years, sedentary physiology has become a distinct field of study from exercise physiology (89); however, there are still widespread misunderstandings on how to define sedentary behavior (see Table 1 for definitions used in this article). In 2012, the Sedentary Behavior Research Network (SBRN) proposed a standardized definition of the term “sedentary behavior” that has become commonplace in the scientific literature (75). Sedentary behavior is defined as “any waking behavior characterized by an energy expenditure ≤1.5 metabolic equivalents while in a sitting or reclining posture” (excluding sleep) (75). In 2017, SBRN extended their list of consensus definitions for scientists interested in sedentary behavior research (85). Common sedentary behaviors include TV viewing, passive video game playing, computer use, driving or riding in a car, and reading while sitting.

Although the SBRN definition for sedentary behavior has been adopted by many researchers, other definitions persist. For example, in contrast to the SBRN definition, the U.S. National Library of Medicine MeSH descriptor defines “sedentary lifestyle” as a “usual level of physical activity that is less than 30 min of moderate-intensity activity on most days of the week” (93). The SBRN definition of sedentary behavior is used throughout this work. Researchers and health care providers working in the field are encouraged to use the SBRN definition of sedentary behavior to minimize confusion and to ensure that future research efforts are conceptualizing and operationalizing sedentary behaviors in a consistent manner.

Messages about sedentary behavior can be conveyed in a similar fashion to messages about physical activity. Similar to the commonly used frequency, intensity, time, and type principle to prescribe physical activity, sedentary behavior is prescribed using the sedentary behavior frequency, interruptions, time, and type principle (89) and in accordance with sedentary behavior guidelines (e.g., no more than 2 h of discretional screen time per day in children and youth) (91). Discretionary screen time is generally used for sedentary behavior recommendations (as opposed to total sedentary time) because it is the component of sedentary time most strongly and consistently associated with adverse health outcomes (86). Evidence from screen time research will be the focus of this review, but evidence from sedentary behavior research will be used throughout to support our discussion.

Time spent engaged in sedentary behavior can be objectively measured (e.g., accelerometers and inclinometers) or through subjective evaluations (e.g., self- or proxy-reported questionnaires). However, objective measures are not able to provide information on different modalities of (e.g., watching TV, reading, and car driving) or contexts (e.g., work, home, and school) of sedentary behavior and may miss some important associations. Screen time is usually measured via subjective evaluations but very few have undergone any formal psychometric testing, especially for use among large, population-based cohorts. Future work should assess these questionnaires, especially in light of emerging technology and viewing habits.

Back to Top | Article Outline

CURRENT SCREEN TIME GUIDELINES AROUND THE WORLD

Public health guidelines are useful to help educate members of the general public on minimal and optimal levels of various movement behaviors to achieve health benefits. Physical activity guidelines have been around for many years and are relatively consistent around the world (i.e., at least 60 min of moderate- to vigorous-intensity physical activity (MVPA) per day for children and youth [88] and at least 150 min of MVPA per week for adults and older adults [92]). Guidelines for sedentary behavior, or specifically screen time, are relatively new. Currently, specific sedentary behavior guidelines only exist for children <18 yr of age and generally focus on screen time. These guidelines recommend that time spent sedentary be minimized and time spent in discretional screen time be limited to no more than 2 h·d−1 (for children and youth) (88), no more than 1 h·d−1 (preschoolers and toddlers), and no screen time at all for children younger than 2 yr (90).

Guidance on sedentary behavior for adults and older adults is less clear. Some guidelines (e.g., the World Health Organization, the United States, and Australia) have incorporated recommendations for sedentary behavior and screen time into their physical activity guidelines with an overarching message to break up and/or reduce sedentary time (4). In 2016, the United Kingdom launched the first workplace sedentary behavior guidelines (11). They recommend that office-based workers progress to accumulating 4 h·d−1 of standing time during working hours through a combination of activity breaks, the use of sit–stand desks, and by incorporating standing-based tasks (11). To date, there are no guidelines for discretionary screen time for adults, or older adults. However, there is limited evidence to suggest that increases in screen time are associated with additional health benefits, and there should be no reason to believe that adults cannot follow the screen time guidelines for children and youth until age-specific guidelines are developed.

Back to Top | Article Outline

EVOLUTION OF SCREENS

The history of screen-based technology might be better understood as histories because screen developments over the past 100+ yr have involved antecedent technologies with rich histories of their own and included various groups of practitioners who have seen unrealized potential in screens and made efforts to innovate accordingly (49,51,58). Despite the historical complexity of screens, understanding their evolution is important given the profound influence they have on modern life. Everything from work, education, and leisure, to our interpersonal relationships, are now affected and often predicated on by screens (49).

Although mechanical precursors to the television date as far back as the 17th century (e.g., magic lanterns) (49), it was the discovery of selenium's photoconductivity in 1873 (80) that gave rise to ideas of instantly transmitting moving images and to international efforts to develop the television (49). The first demonstrations of the electronic television followed several decades later in the 1920s (49). Mass adoption of this new screen-based technology occurred rapidly in American society after World War 2 with the proportion of households having a television nearing 90% in less than 15 yr from the initial entrance of commercial televisions into consumer markets (0.5% in 1946, 55% in 1956, 87% in 1960, and 97% in 1974) (70). By 2001, the average number of televisions in the typical American household was 2.4 (70).

Early in the post–World War 2 era, other screen-based technology cropped up in prototypical and/or operational forms, including the electronic computer (1946), the tablet computer (1957), and the first video game (1958) (70,95,96). Computing hardware evolved from mainframes to minicomputers to microcomputers (97) so that by the late 1970s and early 1980s, personal computers were available to consumers (70). As with television, the adoption of personal computers by American consumers was swift. The proportion of households with 3- to 17-yr-olds and a personal computer nearly tripled between 1989 (approximately 25%) and 2003 (75%) (70). It would be remiss to pass over the development of the Internet (invented in 1969) and the World Wide Web (invented in 1989), the latter being a way of sharing information over the Internet (98). Without these, the rate of mass uptake of personal computers would doubtless be less than what is seen today.

Smartphones followed an evolutionary trajectory similar to that of the television and the personal computer (i.e., early invention, lag of a decade or more before market entry and consumer appeal, and rapid mass adoption thereafter). The first prototype of the IBM Simon debuted in 1992, and there was an initial lag before products were introduced to market. It was only when the first iPhone was unveiled in 2007 that smartphone ownership started to grow at exponential rates (79). In Canada, for example, ownership increased by 38% (55% in 2014 vs 76% in 2016) in the last 2 yr alone (79). Recent poll research reveals that a high proportion of Americans (72%) and Canadians (76%) now own smartphones and similar ownership rates are seen in many other countries around the world (e.g., South Korea [88%], Australia [77%], and Israel [74%]), although there is less uptake in some lower-income countries (e.g., Ethiopia and Uganda) (38,79). Currently, 92% of U.S. adults own either a cell phone or a smartphone (3) and almost half (46.5%) of U.S. households do not own a landline telephone (42). Further, 90% of Americans report that they “frequently” have their smartphone with them (42).

Over the past decade, ownership of cell phones, smartphones, and tablets have increased exponentially, whereas home computer and game console ownership have hit a plateau (Fig. 2). This is perhaps because users are moving away from unifunction devices to more portable, multifunction devices. For example, current smartphones can act as a camera, a telephone, a TV, a day planner, and most recently, as your wallet. As mentioned, developed nations tend to have higher proportion of screen ownership, whereas underdeveloped and developing countries are quickly catching up. In recent years, developing countries have witnessed an exponential growth in screen and technology ownership (e.g., cell phone, smartphone, and Internet). For example, the proportion of Internet and smartphone use rose from 45% in 2013 to 54% in 2015, with emerging countries such as Malaysia, China, and Brazil contributing to the increase (63).

Many other forms of screen-based technology make up the current landscape including active video games, smartwatches, and augmented reality video games (Fig. 3). As this figure makes clear, there have been many developments in screen technology during the past 100 yrs. Once these innovations rise to prominence, they either decline into obsolescence or become ubiquitous (49). As the mass adoption data reveal, screens have mostly followed the latter course. Rather than older technology being displaced by what is newer, screens are being paired and used concurrently (70).

Back to Top | Article Outline

PREVALENCE OF SEDENTARY BEHAVIOR AND SCREEN USE AROUND THE WORLD

Objectively measured sedentary behavior data from the National Health and Nutrition Examination Survey in the U.S. show that boys 6–19 yr of age accumulate 6.0–7.9 h of daily sedentary behavior (with the oldest children being the most sedentary); girls are slightly more sedentary accumulating 6.1–8.1 h daily (again with the oldest being the most sedentary) (59). In a recent study looking at 9–11 yr olds in 12 countries around the world, an average of 54.5% of children exceeded current screen time guidelines of no more than 2 h of discretionary screen time per day (48). A recent comparison of 38 countries from around the world found a widespread problem of excessive screen time among children and youth with children from high-income countries more likely to exceed screen time guidelines compared with those from lower-income and developing countries (87). Data from the Health Behavior in School-aged Children study of youth from 42 countries in Europe and North America showed that the large majority of youth (62% of 13 yr olds, and 63% of 15 yr olds) exceeded screen time guidelines (39).

There is a similar trend for high levels of sedentary behavior among adults. Data from the National Health and Nutrition Examination Survey show that men and women accumulate approximately 8–9 h of sedentary time per day (50). This is common for adults around the world with the large majority of office-based employment done while sitting at a desk. The advent of sit–stand workstations, treadmill desks, and other adaptations to incorporate physical activity into the workplace will continue to be an interesting area of study in the coming years. Although there is some evidence to suggest that older adults engage in more TV viewing that their younger counterparts (78), the fact remains that many individuals require the use of screens (i.e., computers, tablets, and/or smartphones) to be used throughout the day.

Back to Top | Article Outline

RISKS AND BENEFITS ASSOCIATED WITH SCREEN TIME

As outlined in Figure 3, screens have been a pervasive element of our sociocultural makeup for the last half century. With such widespread use, it is essential that we understand both the risks and the benefits associated with screen use. The following section provides an overview of research outlining both the risks and the benefits associated with screen time and overall health, including physical, biological, and mental health.

Back to Top | Article Outline

Risks Associated with Screen Time

With the widespread use of accelerometers, we are beginning to understand the detrimental effects of prolonged uninterrupted bouts of sedentary time on acute and chronic health conditions. In adults, long bouts of sitting time have been associated with acute and chronic ill-health (e.g., increased risk of obesity and heart disease), regardless of the mode or domain of sedentary behavior (37,67). In children, limiting sedentary behavior, and specifically screen time, is associated with more optimal measures of body composition, fitness, self-esteem, self-worth, prosocial behavior, and academic achievement (13,86). However, previous reviews have been informed primarily by proxy report (i.e., self-report, teacher report, or parental report) recalls of screen-based behaviors. Currently, the relationship between sedentary behavior and health seems to be at least partially mitigated by how sedentary behavior is measured, defined, and categorized. For example, more recent studies using accelerometer data to quantify total sedentary time and markers of cardiometabolic health have been less conclusive. Evidence from both clinical and population-based studies have shown that in children, long bouts of sitting time are not associated with acute elevations in cardiometabolic health risk (72,73), body mass index (BMI), or waist circumference (19). These equivocal findings in children support the notion that screen-based sedentary time is the most worrisome subset of sedentary behavior, at least in children and youth.

Evidence among adult populations is less divisive and shows that total sedentary behavior, and not just screen time, is associated with adverse health. The American Heart Association science advisory recently summarized the existing evidence about total sedentary behavior as a risk factor for cardiovascular morbidity and mortality in adults (100). They reported that prospective evidence is accumulating rapidly on sedentary behavior as a risk factor for cardiovascular disease and diabetes mellitus morbidity and for all-cause mortality. However, they also mentioned that the degree to which this is independent of the effects of physical activity needs further clarity.

Interestingly, a recent meta-analysis showed that high levels of MVPA (i.e., 60–75 min·d−1) seemed to eliminate the increased risk of death associated with high sitting time (i.e., >8 h daily) in adults (26). However, this high activity level only attenuates but does not eliminate the increased risk associated with high TV viewing time (i.e., ≥5 h or more a day). This was the first meta-analysis to use a harmonized approach to directly compare mortality between people with different levels of sitting time and physical activity. Examining the joint effects of these two behaviors is important because most people engage in both behaviors every day, so the effects of both should be considered in public health guidelines. These findings suggest that if long periods of sitting time each day are unavoidable (e.g., for work or transport), it is important to be physically active to compensate for this unhealthy behavior. These findings also suggest that specific modalities of sedentary behavior, including both occupational and discretionary screen time, should be examined to understand the health effects among adults. These relationships could also inform the development of physical activity and screen time guidelines for this population. For example, the amount of MVPA needed for optimal health could be dependent on the amount of screen time or sitting time a person engages in on a daily basis.

A recent synthesis of systematic reviews reported numerous negative relationships between screen time and health indicators (24). Specifically, in children and adolescents, they reported that there is strong evidence for a negative relationship between TV viewing, screen time, and obesity. Moderate evidence was found for the relationship between TV viewing, screen time, and higher blood pressure; higher total cholesterol; lower self-esteem; social behavior problems; lower physical fitness; and poorer academic achievement. In adults, they reported strong evidence for a relationship between TV viewing, screen time, and all-cause mortality; fatal and nonfatal cardiovascular disease; type 2 diabetes; and metabolic syndrome. Their overview, on the basis of the best available systematic reviews, showed that sedentary behavior is an important determinant of health (24); however, it also further highlighted that the relationship is complex and depends on many factors including the type of sedentary behavior (sitting only vs screen time) and the age-group studied (children vs adults). In general, stronger associations with adverse health outcomes are found with increased TV viewing as the type of sedentary behavior and more so in adults compared with children.

In addition to adverse effects of screen time on physical health, psychosocial health indicators can also be affected by high levels of screen time. For instance, a recent systematic review on screen-based sedentary behavior and mental health indicators in children and adolescents reported strong evidence for the association between high duration of screen time and indicators of mental health, including hyperactivity/inattention problems, internalizing problems, and lower psychological well-being and perceived quality of life (81). Similarly, a systematic review that focused on adolescent girls found that higher levels of screen time were associated with depression and poor social support (21).

The observation that adverse health effects are more consistently associated with high levels of screen time than nonscreen sedentary behavior suggests that certain characteristics of screens should not be overlooked. For example, messages emanating from screens, such as advertisements for unhealthy foods, are important factors to take into consideration (16). This can be coupled with more mindless eating in front of the screen device (distracting activity) and therefore overconsumption of food. Another important difference between screen time and nonscreen sedentary time is the fact that screen exposure increases sleep disturbances (29). For example, the blue light of screens has been shown to suppress melatonin secretion, which may delay sleep onset (99). Many individuals are using screen devices within the hour before trying to fall asleep or using cell phones in bed, which interferes with the ability to fall asleep throughout the night (1). Given that lack of sleep is a contributor to obesity and other health hazards (14,15), it is important to acknowledge the unique health effects of screen time that are independent from those of nonscreen sedentary behavior.

Overall, there is a large body of evidence (although largely observational in nature) linking higher screen time with adverse psychological and physical health. These findings are certainly a cause for concern given that screen time is ubiquitous in modern societies, with many individuals exceeding public health screen time recommendations. This reality is especially important to document and study as new technologies emerge that integrate screen time into a more traditional physical activity environment.

Back to Top | Article Outline

Benefits Associated with Screen Time

Alongside the evolution of screens, the ways in which people use and interact with screens has changed over time. Screen time is no longer restricted to watching TV programming on a TV or passively playing a video game. Today, it is not uncommon for individuals to watch TV while using a tablet and/or their smartphone at the same time (40). Gamers can immerse themselves in video games that allow for in game self-direction, discovery, mastery, and social connection (e.g., in massively multiplayer online games) (33,69). Recognizing the complex interactions with screens, researchers have begun to explore the cognitive, social, motivational, and behavioral effects of certain types and contexts of screen time (7,22,23,54,69).

Emerging research is showing some interesting results on the content of screen-based programming. A recent meta-analysis showed that the relationship between video games and information processing was moderated in part by game type (64). Another recent review showed that playing shooting-based games is associated with benefits related to visual processing, attention, and spatial processing (i.e., mental rotation abilities) (33,34). In addition, most types of video games have favorable associations with problem solving and creativity (33). Educational TV programs can also help to broaden children's knowledge by influencing their racial attitudes and imaginativeness (82). Researchers have also shown that the context in which youth use the Internet can affect mental health outcomes differently. For example, in youth who perceived that their friendship qualities were low, using the Internet to communicate was related to less depression and less internalizing problems whereas using the Internet for noncommunication such as surfing was related to detrimental effects on depression and social anxiety (76). Finally, researchers have found evidence for a U-shaped association between screen time and depression such that very low (e.g., <1 h·d−1) and higher Internet (e.g., >2 h·d−1) use was detrimental for depression scores whereas regular (e.g., <2 h·d−1) amounts of Internet use appeared to have no problematic effect (6).

With Internet usage a mainstay in society, it is not surprising that people are using it to connect with others from around the world. The American Academy of Pediatrics recently released a consensus statement that noted that screen time can be used to enhance social support and connection, community participation, and civic engagement (22). Moreover, social media can be used to harness health communication and can be useful for people who are looking for tailored health information (e.g., disease-specific information and information about sexuality) or who are seeking welcoming communities and social support (22,23,45,55,56). In fact, the majority (68%) of U.S. adults report that they get their news from social media sites such as Facebook, Reddit, or Twitter (31).

With the large majority of people around the world engaged in social media (35), it holds the potential to enhance and broaden opportunities to affiliate with people, enhance peer relationships, and to explore opportunities of self-disclosure (77). This also seems to hold true for video games (28). The social benefits of video games can include building social skills, working cooperatively to achieve an in-game goal, engaging in moral decision making, prosocial behaviors, and civic engagement (30,33,69).

The motivational quality of screen time has been proposed as a moderator of the relationship between screen time and mental health indicators (32,69). For example, researchers have shown that a higher duration of playing video games in adults was only related to lower well-being when the players were obsessively passionate about the video game. By contrast, a higher duration of playing video games in people who were low on obsessive passion had higher levels of postplay energy (68). Furthermore, video games that allow players to feel competent or efficacious, compete socially with or against friends in an interactive format, or allow for in game self-direction of behaviors have been related to higher in game enjoyment and preferences for playing in the future (71).

Although traditional active video games (i.e., played indoors on stationary gaming consoles) are not currently recommended as a means of meeting physical activity guidelines, evidence suggests that they can acutely increase energy expenditure above resting when compared with playing passive video games (17,47). In addition, in a systematic review on various health behaviors, researchers found promise for the beneficial effects of video games on outcomes related to psychological therapy, physical therapy, and, to a lesser extent, disease self-management (65). Finally, preliminary evidence indicates that newer forms of active video games, such as the augmented reality games such as Pokémon Go, hold potential for enhancing physical activity, although research in this area is still in its infancy and long-term engagement questionable (46). With the advent of new technologies, including virtual reality gaming and the popularity of gamification, there is potential for screen time to play a prominent role in facilitating behavior change.

Collectively, research evidence highlights some potential cognitive, social, motivational, and health behavioral benefits associated with certain types or contexts of screen time. Nevertheless, these potential beneficial effects of screen time on health must be weighed alongside the known potential harmful effects of accruing longer time spent sedentary while using a screen. Current evidence seems to suggest there are more deleterious effects of excessive screen time than potential benefits. However, determining if the benefits of screen time balance out, or counteract the negative effects of screen time, is a question that will undoubtedly garner future research attention in the near future.

Back to Top | Article Outline

INTERVENTIONS AIMED AT REDUCING SCREEN TIME AND SEDENTARY TIME: EFFECT ON ENERGY EXPENDITURE AND HEALTH

The available evidence suggests that interventions that successfully reduce screen-based behaviors also result in lowered BMI among children with excess weight, although the clinical significance of this reduction may be limited. For example, a randomized intervention by Epstein et al. (27) used a digital screen-limiting device to cut TV and computer time in half among children 4–7 yr of age with a BMI higher than the 75th percentile. They reported an 18-h·wk−1 reduction in screen time over a 2-yr period, which was accompanied by a 0.24-unit decrease in BMI z-score (27). Of note, they also reported a significant reduction in caloric intake of roughly 300 kcal·d−1 in the intervention group, without any significant change in physical activity levels (27). These findings are supported by a systematic review and meta-analysis by Tremblay et al. (86), which examined randomized controlled trials (RCTs) that aimed to reduce screen time in school-age children and youth. They reported that, on average, these interventions resulted in a −0.89-kg·m−2 reduction in BMI in the intervention group compared with the control group (86). A recent meta-analysis by Azevedo et al. (5) concluded that sedentary behavior interventions targeting children with overweight or obesity resulted in a mean reduction of 0.49 kg·m−2, although an average reduction of just 0.029 kg·m−2 was observed among mixed weight populations. Taken together, these results suggest that interventions which successfully reduce screen time are likely to result in modest changes in body weight for children who are overweight or obese. Although the clinical significance of these changes at the level of the individual may be small, they may nonetheless have an important effect at the population level (5). Further, the above-mentioned findings should be interpreted with caution, as Azevedo et al. (5) noted a risk of publication bias in the published literature, including a more frequent observation of significant findings among studies with a high risk of bias.

Although the above-mentioned findings are promising, a meta-analysis by Wahi et al. (94) found that, on average, interventions targeting screen time in the pediatric population result in just a 0.90-h reduction in weekly screen time. Thus, although reductions in screen time may reduce adiposity, few interventions have been shown to successfully reduce screen time in children. More research on this topic is clearly needed if screen time interventions are to have maximal health benefits. A systematic review by Schmidt et al. (74) provides a promising start and suggests that effective interventions would benefit from setting a specific target for reduced screen time, and using screen time limiting devices, provide feedback or counseling, and include high levels of parental involvement. Interventions also appear more likely to succeed when targeting children who are younger than 6 yr (94) and/or with overweight or obesity (5,74).

A limited number of interventions have also focused on sitting per se as opposed to screen time (8,9). These interventions have tended to focus on the classroom setting, with outcomes focusing on energy expenditure, and results that may not be clinically significant. For example, Benden et al. (9) examined the effect of sit–stand desks in 374 students in grades 2 to 4. They reported that sit–stand desks resulted in an additional 4.8–9.6 kcal·h−1 expended, or approximately 60 kcal per school day. Thus, while statistically significant, these differences are unlikely to affect adiposity or weight control. To our knowledge, no studies have looked at other potential health benefits of sit–stand desks in school-age children.

In contrast to the literature in children and youth, the majority of interventions among adult populations have targeted prolonged sitting in the workplace, with very few interventions targeting discretionary screen time (66). Workplace interventions have largely focused on two mechanisms. The first involves the use of active workstations (e.g., treadmill desk and desk pedal system) to increase energy expenditure while maintaining productivity and reducing interruptions to the work day. The second focuses on breaking up prolonged sitting with either stationary standing (e.g., sit–stand desks) or with movement (e.g., prompting software to get up and move for a few minutes or do a form of exercise).

Evidence has also shown that sedentary-focused interventions result in an average reduction of 42 to 91 min·d−1 in sedentary time (53,66). Chu et al. (18) in a recent systematic review of workplace interventions aimed at reducing sedentary time among white-collar workers found that workplace interventions resulted in an average reduction of ~40 min per 8-h workday. Multicomponent interventions (e.g., sit–stand workstation + behavioral interventions) resulted in the largest reduction of workplace sitting (−89 min per 8-h workday), followed by environmental (e.g., sit–stand workstations, active workstations; −73 min per 8-h workday) and educational/behavioral interventions (e.g., motivational interviewing, information on behavioral consequences, goal setting, action planning, and self-monitoring; −16 min per 8-h workday) (18).

Workplace-based interventions aimed at reducing prolonged sitting show promise for significantly increasing energy expenditure (10,61), although the meaningfulness of these increases and the reality of employees achieving enough standing time to garner clinically meaningful increases poses a challenge. Workplace sedentary interventions have largely been found to have conflicting evidence with respect to metabolic and physiologic outcomes (20). Important to note, however, is that there is a large heterogeneity in the literature with respect to study design, intensity, duration, and intervention focus. Individual interventions have resulted in significant decreases of mean arterial pressure, lowered blood glucose, reduced waist circumference, reduced body weight, lowered low-density lipoprotein cholesterol, lowered total cholesterol, and increases in high-density lipoprotein cholesterol (2,12,36,41,44,57,83).

Fewer interventions have targeted the reduction of sedentary time among adults outside of the workplace. Otten et al. (57), in an RCT of overweight and obese adults, investigated the effects of using an electronic TV lock-out system to reduce TV viewing by 50% for 3 wk. The intervention group significantly increased their energy expenditure by ~200 kcal·d−1. Although not significantly different than the control group, the intervention group also achieved a reduction in energy intake and BMI (57). Although this RCT shows promise with respect to energy balance regulation, the reality of having people agree to an ongoing lockout system for their TV remains questionable. Further, without specific TV, or discretionary screen time guidelines for adults, it is difficult to ascertain what the benchmark should be set at.

Smartphone apps or wearable technologies are promising intervention methodologies for the future. Although this work is in its infancy, studies have shown they have the capacity to reduce sedentary time. Pellegrini et al. (62) developed a smartphone application (NEAT!) that provided participants with noise or vibration prompts upon 20 min of consecutive sitting time. Their pilot study (N = 7) found that participants decreased their sedentary time. Thomsen et al. (84) combined motivational counseling with individual SMS reminders to reduce sedentary time and found that the intervention group decreased sitting time, whereas the control group increased it. Similarly, Kendzor et al. (43) used a mobile phone intervention that provided prompts during self-reported sitting bouts to reduce sitting time and information on the consequences of sedentary behavior. The intervention resulted in significantly fewer minutes of daily sedentary time (B = −22.09, P = 0.045) and significantly greater minutes spent active (B = 23.01, P = 0.04). Ultimately, future work is needed to identify how best to use new technologies to reduce sedentary behavior and the potential health benefits of such interventions (52).

Back to Top | Article Outline

FUTURE RESEARCH DIRECTIONS

Scientists, health care providers, and policy makers wishing to translate sedentary behavior research and implement new findings into clinical and community settings will likely be busy in the near future. This is certainly an exciting and rapidly evolving area of research. Although many questions remain unanswered and much needs to be done, it is clear that there is a need to promote the “Sit Less, Move More” strategy (25). The following list is not intended to be comprehensive but highlights important research avenues that need to be addressed in the near future.

* Stronger evidence (i.e., randomized trials and longitudinal studies) is needed to inform specific recommendations on sedentary behavior (across modes and domains), including on dose–response relationships with various health outcomes, and underlying physiological mechanisms.

* Unobtrusive, and low-burden, yet objective measures of different sedentary modalities (e.g., screen time) and posture are needed (e.g., life logging, wearable cameras, inclinometers) to provide better estimates of sedentary time and its associations with outcomes. These measures also need to be valid, reliable, and feasible.

* Studies and tools need to adapt to the modern reality with sedentary multitasking (i.e., engaging in multiple screen time behaviors simultaneously, and the different types of electronic devices and contexts). These tools also need to be flexible to allow for incorporation of new technologies as they emerge and low-burden to participants.

* Compositional data analyses combined with 24-h objective monitoring of movement/nonmovement behaviors can provide insights into the collective health implications and interactions of lifestyle behaviors.

* Studies need to determine whether smartphones and tablets have the same health effects as traditional forms of screen time such as television or video games. This also includes understanding use of smartphone and tablets while engaging in other more beneficial activities (e.g., watching TV programming while running on the treadmill).

* The effectiveness of novel sedentary behavior reduction interventions need to be tested in different domains (e.g., occupational/educational, leisure/discretional, transportation, household) and to determine whether the behavior changes and affects on health achieved are sustainable over time before they can be scaled up for population-wide adoption. Studies targeting high-risk populations (e.g., individuals with preexisting cardiovascular disease or diabetes) should be prioritized, as high-risk individuals can benefit the most from sedentary behavior reduction.

* Compensatory adjustments of sedentary behavior reduction interventions need to be monitored to better understand the net result on health (e.g., breaking up sitting time may result in more siting time and/or unhealthy eating behaviors in another time during the day).

* Population health researchers need to work with technology companies and private companies to use new technologies to decrease habitual sedentary time and increase physical activity, with or without the addition of screen-based devices (e.g., free-to-play location-based augmented reality games).

* Future studies should assess both the biological/physiological effect of sedentary behavior and/or the screen time but also the psychosocial and cognitive effects to gain a holistic understanding of the risks and benefits.

Back to Top | Article Outline

CONCLUSION

Screen-based technology is rapidly changing, and it is imperative that researchers recognize and keep pace with the shifts in trends and use of screen-based entertainment devices and how this affects daily movement behaviors. It is also important to acknowledge that screen-based and sedentary behaviors have become a fixture in daily life and understand how to exploit this ever-presence to maximize health benefits. Future work would benefit from longitudinal and experimental examination of how to change sedentary behaviors across domains (e.g., occupational/education, transportation, leisure, household), how these changes translate to improvements in physical and psychosocial outcomes, and how these changes can be sustained.

SPW has received an equipment award from Pal Technologies Ltd. TJS has received research support from Stepscount and Ergotron. All other authors declare no conflict of interest and do not have any financial disclosures.

The views and conclusions of this review do not constitute endorsement by the American College of Sports Medicine.

Back to Top | Article Outline

REFERENCES

1. Adams SK, Daly JF, Williford DN. Adolescent sleep and cellular phone use: recent trends and implications for research. Health Serv Insights. 2013;3(6):99–103.
2. Alkhajah TA, Reeves MM, Eakin EG, Winkler EA, Owen N, Healy GN. Sit–stand workstations: a pilot intervention to reduce office sitting time. Am J Prev Med. 2012;43(3):298–303.
3. Anderson M. Technology Device Ownership: 2015. Pew Research Center; 2015. Available from: http://www.pewinternet.org/2015/10/29/technology-device-ownership-2015/
4. Australia physical activity and sedentary behaviour guidelines. Australian Government Department of Health and Ageing. Available from: http://www.health.gov.au
5. Azevedo LB, Ling J, Soos I, Robalino S, Ells L. The effectiveness of sedentary behaviour interventions for reducing body mass index in children and adolescents: systematic review and meta-analysis. Obes Rev. 2016;17(7):623–35.
6. Bélanger RE, Akre C, Berchtold A, Michaud PA. A U-shaped association between intensity of Internet use and adolescent health. Pediatrics. 2011;127(2):e330–5.
7. Bell V, Bishop DV, Przybylski AK. The debate over digital technology and young people. BMJ. 2015;351:h3064.
8. Benden ME, Blake JJ, Wendel ML, Huber JC Jr. The impact of stand-biased desks in classrooms on calorie expenditure in children. Am J Public Health. 2011;101(8):1433–6.
9. Benden ME, Zhao H, Jeffrey CE, Wendel ML, Blake JJ. The evaluation of the impact of a stand-biased desk on energy expenditure and physical activity for elementary school students. Int J Environ Res Public Health. 2014;11(9):9361–75.
10. Ben-Ner A, Hamann DJ, Koepp G, Manohar CU, Levine J. Treadmill workstations: the effects of walking while working on physical activity and work performance. PLoS One. 2014;9(2):e88620.
11. Buckley JP, Hedge A, Yates T, et al. The sedentary office: a growing case for change towards better health and productivity. Expert statement commissioned by Public Health England and the Active Working Community Interest Company. Br J Sports Med. 2015;49(21):1353.
12. Carr LJ, Karvinen K, Peavler M, Smith R, Cangelosi K. Multicomponent intervention to reduce daily sedentary time: a randomised controlled trial. BMJ Open. 2013;3(10):e003261.
13. Carson V, Hunter S, Kuzik N, et al. Systematic review of sedentary behaviour and health indicators in school-aged children and youth: an update. Appl Physiol Nutr Metab. 2016;41(6 (Suppl. 3):S240–65.
14. Chaput JP. Is sleep deprivation a contributor to obesity in children? Eat Weight Disord. 2016;21(1):5–11.
15. Chaput JP, Dutil C. Lack of sleep as a contributor to obesity in adolescents: impacts on eating and activity behaviors. Int J Behav Nutr Phys Act. 2016;13:103.
16. Chaput JP, Klingenberg L, Astrup A, Sjödin AM. Modern sedentary activities promote overconsumption of food in our current obesogenic environment. Obes Rev. 2011;12(5):e12–20.
17. Chaput JP, LeBlanc AG, McFarlane A, et al. Active Healthy Kids Canada's position on active video games for children and youth. Paediatr Child Health. 2013;18(10):529–32.
18. Chu AH, Ng SH, Tan CS, Win AM, Koh D, Müller-Riemenschneider F. A systematic review and meta-analysis of workplace intervention strategies to reduce sedentary time in white-collar workers. Obes Rev. 2016;17(5):467–81.
19. Colley RC, Garriguet D, Janssen I, et al. The association between accelerometer-measured patterns of sedentary time and health risk in children and youth: results from the Canadian Health Measures Survey. BMC Public Health. 2013;13:200.
20. Commissaris DA, Huysmans MA, Mathiassen SE, Srinivasan D, Koppes LL, Hendriksen IJ. Interventions to reduce sedentary behavior and increase physical activity during productive work: a systematic review. Scand J Work Environ Health. 2016;42(3):181–91.
21. Costigan SA, Barnett L, Plotnikoff RC, Lubans DR. The health indicators associated with screen-based sedentary behavior among adolescent girls: a systematic review. J Adolesc Health. 2013;52(4):382–92.
22. Council on Communications and Media. Media and young minds. American Academy of Pediatrics. Pediatrics. 2016:e20162591.
23. Council on Communications and Media. Media use in school-aged children and adolescents. American Academy of Pediatrics. Pediatrics. 2016:e20162592.
24. de Rezende LF, Rodrigues Lopes M, Rey-López JP, Matsudo VK, Luiz Odo C. Sedentary behavior and health outcomes: an overview of systematic reviews. PLoS One. 2014;9(8):e105620.
25. Dunstan DW, Howard B, Healy GN, Owen N. Too much sitting—a health hazard. Diabetes Res Clin Pract. 2012;97(3):368–76.
26. Ekelund U, Steene-Johannessen J, Brown WJ, et al. Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than 1 million men and women. Lancet. 2016;388(10051):1302–10.
27. Epstein LH, Roemmich JN, Robinson JL, et al. A randomized trial of the effects of reducing television viewing and computer use on body mass index in young children. Arch Pediatr Adolesc Med. 2008;162(3):239–45.
28. Ferguson CJ, Olson CK. Friends, fun, frustration and fantasy: child motivations for video game play. Motiv Emot. 2013;37(1):154–64.
29. Fonken LK, Nelson RJ. The effects of light at night on circadian clocks and metabolism. Endocr Rev. 2014;35(4):648–70.
30. Gentile DA, Anderson CA, Yukawa S, et al. The effects of prosocial video games on prosocial behaviors: international evidence from correlational, longitudinal, and experimental studies. Pers Soc Psychol Bull. 2009;35(6):752–63.
31. Gottfried J, Shearer E. News Use Across Social Media Platforms 2016. Pew Research Center; 2016. Available from: http://www.journalism.org/2016/05/26/news-use-across-social-media-platforms-2016/
32. Granic I. The promise of applied video games for the prevention of anxiety and depression in youth. ISSDB Bulletin, 2016.
33. Granic I, Lobel A, Engels CM. The benefits of playing video games. Am Psychol. 2014;69(1):66–78.
34. Green CS, Bavelier D. Learning, attentional control, and action video games. Curr Biol. 2012;22(6):R197–206.
35. Greenwood S, Perrin A, Duggan M. Social Media Update 2016. Pew Research Center; 2016. Available from: http://www.pewinternet.org/2016/11/11/social-media-update-2016/
36. Healy GN, Eakin EG, LaMontagne AD, et al. Reducing sitting time in office workers: short-term efficacy of a multicomponent intervention. Prev Med. 2013;57(1):43–8.
37. Healy GN, Matthews CE, Dunstan DW, Winkler EA, Owen N. Sedentary time and cardio-metabolic biomarkers in US adults: NHANES 2003–06. Eur Heart J. 2011;32(5):590–7.
38. How many people own smartphones around the world. Bus Insid. 2016. Available from: www.businessinsider.com/how-many-people-own-smartphones-around-the-world-2016-2
39. Inchley J, Currie D, Young TK, et al. Growing Up Unequal: Gender and Socioeconomic Differences in Young People's Health and Well-being. Copenhagen: WHO Regional Office for Europe: World Health Organization; 2016.
40. Jago R, Sebire SJ, Gorely T, Cillero IH, Biddle SJ. “I'm on it 24/7 at the moment”: a qualitative examination of multi-screen viewing behaviours among UK 10–11 year olds. Int J Behav Nutr Phys Act. 2011;8:85.
41. John D, Thompson DL, Raynor H, Bielak K, Rider B, Bassett DR. Treadmill workstations: a worksite physical activity intervention in overweight and obese office workers. J Phys Act Health. 2011;8(8):1034–43.
42. Keeter S, McGeeney K. Pew Research Will Call More Cellphones in 2015. Pew Research Center; 2015. Available from: http://www.pewresearch.org/fact-tank/2015/01/07/pew-research-will-call-more-cellphones-in-2015/
43. Kendzor DE, Shuval K, Gabriel KP, et al. Impact of a mobile phone intervention to reduce sedentary behavior in a community sample of adults: a quasi-experimental evaluation. J Med Internet Res. 2016;18(1):e19.
44. Koepp GA, Manohar CU, McCrady-Spitzer SK, et al. Treadmill desks: a 1-year prospective trial. Obesity. 2013;21(4):705–11.
45. Krueger EA, Young SD. Twitter: a novel tool for studying the health and social needs of transgender communities [Internet]. JMIR Ment Health. 2015;2(2).
46. LeBlanc AG, Chaput JP. Pokémon Go: a game changer for the physical inactivity crisis? Prev Med. 2016; epub ahead of print DOI:10.1016/j.ypmed.2016.11.012.
47. LeBlanc AG, Chaput JP, McFarlane A, et al. Active video games and health indicators in children and youth: a systematic review. PLoS One. 2013;8(6):e65351.
48. LeBlanc AG, Katzmarzyk PT, Barreira TV, et al. Correlates of total sedentary time and screen time in 9–11 year-old children around the world: the international study of childhood obesity, lifestyle and the environment. PLoS ONE. 2015;10(6):e0129622.
49. Magoun AB. Television: The Life Story of a Technology. Greenwood Publishing Group; 2007.
50. Maher CA, Mire E, Harrington DM, Staiano AE, Katzmarzyk PT. The independent and combined associations of physical activity and sedentary behavior with obesity in adults: NHANES 2003–06. Obesity. 2013;21(12):E730–7.
51. Mahoney MS. The histories of computing(s). Interdiscip Sci Rev. 2005;30(2):119–35.
52. Manini TM, Carr LJ, King CA, Marshall S, Robinson TN, Rejeski WJ. Interventions to reduce sedentary behavior. Med Sci Sports Exerc. 2015;47(6):1306–10.
53. Martin A, Fitzsimons C, Jepson R, et al. Interventions with potential to reduce sedentary time in adults: systematic review and meta-analysis. Br J Sports Med. 2015;49(16):1056–63.
54. McCarthy C. Pediatricians and television: it's time to rethink our messaging and our efforts. Pediatrics. 2013;131(3):589–90.
55. Moorhead SA, Hazlett DE, Harrison L, Carroll JK, Irwin A, Hoving C. A new dimension of health care: systematic review of the uses, benefits, and limitations of social media for health communication. J Med Internet Res. 2013;15(4):e85.
56. Naslund JA, Aschbrenner KA, Marsch LA, Bartels SJ. The future of mental health care: peer-to-peer support and social media. Epidemiol Psychiatr Sci. 2016;25(2):113–22.
57. Otten JJ, Jones KE, Littenberg B, Harvey-Berino J. Effects of television viewing reduction on energy intake and expenditure in overweight and obese adults: a randomized controlled trial. Arch Intern Med. 2009;169(22):2109–15.
58. Parikka J. History of Computers. Baltimore: John Hopkins University Press; 2013.
59. Pate RR, Mitchell JA, Byun W, Dowda M. Sedentary behaviour in youth. Br J Sports Med. 2011;45(11):906–13.
60. Pate RR, O'Neill JR, Lobelo F. The evolving definition of “sedentary.” Exerc Sport Sci Rev. 2008;36(4):173–8.
61. Pedersen SJ, Cooley PD, Mainsbridge C. An e-health intervention designed to increase workday energy expenditure by reducing prolonged occupational sitting habits. Work. 2014;49(2):289–95.
62. Pellegrini CA, Hoffman SA, Daly ER, Murillo M, Iakovlev G, Spring B. Acceptability of smartphone technology to interrupt sedentary time in adults with diabetes. Transl Behav Med. 2015;5(3):307–14.
63. Poushter J. Smartphone ownership and internet usage continues to climb in emerging economies [Internet]. Pew Res Cent Glob Attitudes Proj. 2016. Available from: http://www.pewglobal.org/2016/02/22/smartphone-ownership-and-internet-usage-continues-to-climb-in-emerging-economies/
64. Powers KL, Brooks PJ, Aldrich NJ, Palladino MA, Alfieri L. Effects of video-game play on information processing: a meta-analytic investigation. Psychon Bull Rev. 2013;20(6):1055–79.
65. Primack BA, Carroll MV, McNamara M, et al. Role of video games in improving health-related outcomes: a systematic review. Am J Prev Med. 2012;42(6):630–8.
66. Prince SA, Saunders TJ, Gresty K, Reid RD. A comparison of the effectiveness of physical activity and sedentary behaviour interventions in reducing sedentary time in adults: a systematic review and meta-analysis of controlled trials. Obes Rev. 2014;15(11):905–19.
67. Proper KI, Singh AS, van Mechelen W, Chinapaw MJ. Sedentary behaviors and health outcomes among adults: a systematic review of prospective studies. Am J Prev Med. 2011;40(2):174–82.
68. Przybylski AK, Weinstein N, Ryan RM, Rigby CS. Having to versus wanting to play: background and consequences of harmonious versus obsessive engagement in video games. Cyberpsychol Behav. 2009;12(5):485–92.
69. Rigby CS, Ryan RM. Time well-spent? Motivation for entertainment media and its eudaimonic aspects through the lens of sel-determination theory. In: Reinecke L, Oliver MB, editors. The Routledge Handbook of Media Use and Well-being. New York (NY): Routledge; 2017. pp. 34–48.
70. Roberts DF, Foehr UG. Trends in media use. Future Child. 2008;18(1):11–37.
71. Ryan RM, Rigby CS, Przybylski A. The motivational pull of video games: a self-determination theory approach. Motiv Emot. 2006;30(4):344–60.
72. Saunders TJ, Chaput JP, Goldfield GS, et al. Prolonged sitting and markers of cardiometabolic disease risk in children and youth: a randomized crossover study. Metabolism. 2013;62(10):1423–8.
73. Saunders TJ, Chaput JP, Tremblay MS. Sedentary behaviour as an emerging risk factor for cardiometabolic diseases in children and youth. Can J Diabetes. 2014;38(1):53–61.
74. Schmidt ME, Haines J, O'Brien A, et al. Systematic review of effective strategies for reducing screen time among young children. Obesity. 2012;20(7):1338–54.
75. Sedentary Behaviour Research Network. Letter to the editor: standardized use of the terms “sedentary” and “sedentary behaviours.” Appl Physiol Nutr Metab. 2012;37(3):540–2.
76. Selfhout MH, Branje SJ, Delsing M, ter Bogt TF, Meeus WH. Different types of Internet use, depression, and social anxiety: the role of perceived friendship quality. J Adolesc. 2009;32(4):819–33.
77. Spies Shapiro LA, Margolin G. Growing up wired: social networking sites and adolescent psychosocial development. Clin Child Fam Psychol Rev. 2014;17(1):1–18.
78. Shields M, Tremblay MS. Screen time among Canadian adults: a profile. Health Rep. 2008;19(2):31–43.
79. Smartphone behavior in Canada and the implications for marketers in 2016 [Internet]. Available from: catalyst.ca/2016-canadian-smartphone-behaviour
80. Smith W. Effect of light on selenium during the passage of an electric current. Nature. 1873;7:303.
81. Suchert V, Hanewinkel R, Isensee B. Sedentary behavior and indicators of mental health in school-aged children and adolescents: a systematic review. Prev Med. 2015;76:48–57.
82. Thakkar RR, Garrison MM, Christakis DA. A systematic review for the effects of television viewing by infants and preschoolers. Pediatrics. 2006;118(5):2025–31.
83. Thompson WG, Koepp GA, Levine JA. Increasing physician activity with treadmill desks. Work. 2014;48(1):47–51.
84. Thomsen T, Aadahl M, Hetland ML, Beyer N, Loeppenthin K, Esbensen BA. FRI0595-HPR reduction of sedentary behaviour in patients with rheumatoid arthritis. A randomized feasibility study. Ann Rheum Dis. 2014;73(Suppl 2):1210.
85. Tremblay MS, Aubert S, Barnes JD, et al. Sedentary behavior research network (SBRN)—terminology consensus project process and outcome. Int J Behav Nutr Phys Act. 2017;14:75.
86. Tremblay MS, LeBlanc AG, Kho ME, et al. Systematic review of sedentary behaviour and health indicators in school-aged children and youth. Int J Behav Nutr Phys Act. 2011;8:98.
87. Tremblay MS, Barnes JD, González SA, et al. Global Matrix 2.0: report card grades on the physical activity of children and youth comparing 38 countries. J Phys Act Health. 2016;13(11 Suppl 2):S343–66.
88. Tremblay MS, Carson V, Chaput JP, et al. Canadian 24-hour movement guidelines for children and youth: an integration of physical activity, sedentary behaviour, and sleep. Appl Physiol Nutr Metab. 2016;41(6 Suppl 3):S311–27.
89. Tremblay MS, Colley RC, Saunders TJ, Healy GN, Owen N. Physiological and health implications of a sedentary lifestyle. Appl Physiol Nutr Metab. 2010;35(6):725–40.
90. Tremblay MS, LeBlanc AG, Carson V, et al. Canadian sedentary behaviour guidelines for the early years (aged 0–4 years). Appl Physiol Nutr Metab. 2012;37(2):370–91.
91. Tremblay MS, LeBlanc AG, Janssen I, et al. Canadian sedentary behaviour guidelines for children and youth. Appl Physiol Nutr Metab. 2011;36(1):59–64.
92. Tremblay MS, Warburton DE, Janssen I, et al. New Canadian physical activity guidelines. Appl Physiol Nutr Metab. 2011;36(1):36–46.
93. U.S. National Library of Medicine. Sedentary Lifestyle: MeSH Descriptor Data 2017 [Internet]. 2010. Available from: https://meshb.nlm.nih.gov/#/record/ui?ui=D057185
94. Wahi G, Parkin PC, Beyene J, Uleryk EM, Birken CS. Effectiveness of interventions aimed at reducing screen time in children: a systematic review and meta-analysis of randomized controlled trials. Arch Pediatr Adolesc Med. 2011;165(11):979–86.
95. Wikepedia contributors. History of tablet computers [Internet]. Wikipedia Free Encycl. Available from: en.wikipedia.org/w/index.php?title=History_of_tablet_computers&oldid=755303903
96. Wikipedia contributors. ENIAC [Internet]. Wikipedia Free Encycl. Available from: en.wikipedia.org/w/index.php?title=ENIAC&oldid=754672151
97. Wikipedia contributors. History of computing hardware (1960s–present) [Internet]. Wikipedia Free Encycl. Available from: en.wikipedia.org/w/index.php?title=History_of_computing_hardware_(1960s%E2%80%93present)&oldid=752978062
98. Wikipedia contributors. World Wide Web [Internet]. Wikipedia Free Encycl. Available from: en.wikipedia.org/w/index.php?title=World_Wide_Web&oldid=750309338
99. Wood B, Rea MS, Plitnick B, Figueiro MG. Light level and duration of exposure determine the impact of self-luminous tablets on melatonin suppression. Appl Ergon. 2013;44(2):237–40.
100. Young DR, Alhassan S, Camhi SM, et al. Sedentary behavior and cardiovascular morbidity and mortality: a science advisory from the American Heart Association. Circulation. 2016;134(13):e262–79.
© 2017 American College of Sports Medicine