THE SMART PHONE LIFECYCLE
The difference in smartphone use between adolescents
and emerging adults
University of Amsterdam Graduate school of Communication
Master Thesis
Name: Kirsten Hamelink Student number: 10458573
Master program: Research Master Communication Science Supervisor: Monique Timmers
Abstract
This study examined whether there is a difference in smartphone usage amongst adolescents and emerging adults. It was analysed whether there is a difference in their motivations for using their smartphone and whether they differ in their smartphone self-regulating abilities. Besides that, adolescents’ and emerging adults’ habitual- and normative smartphone
behaviour was studied, as well whether their smartphone usage is influenced by saturation. The central research question was ‘to what extent do adolescents and emerging adults differ
in their smartphone usage? Do age, motivations, self-regulating behaviour and lifecycle contribute to changing smartphone usage?’. Two studies have been completed. The first
study indicated by means of a survey (N = 90) that there was no difference in smartphone usage between both age groups. Motivational smartphone usage shows no difference between both age groups. Except for sought autonomy where adolescents indicate using their
smartphone more often for autonomy than emerging adults. For both habitual-, normative smartphone behaviour and smartphone saturation, there was no difference found between the smartphone usage of adolescents and emerging adults. There was, however, a difference found in gender when studying normative behaviour. Girls indicate that smartphone usage is not accepted during social gatherings, whereas boys are neutral on this point. Study one found a contradiction in smartphone self-regulation where both age groups are in disagreement for their self-regulating abilities. Therefore, a follow-up study using interviews (N = 5), acting as preliminary study, investigating self-regulation has been completed. Results show no
difference in self-regulating behaviour between both age groups. With both studies it was possible to state that there is no difference in smartphone usage between adolescents and emerging adults.
THE SMART PHONE LIFECYCLE
The difference in smartphone use between adolescents and emerging adults.
From the beginning of this century a new trend developed called the “Smart
Revolution”. Smartphones rapidly became a worldwide trend, dramatically changing people’s
lives. Even though many of the changes in people’s lives are considered positive, some researchers argue that unfavourable effects take place as well (Kim et al., 2014), one of them being “smartphone addiction”.
In recent years several reports have stressed the notion of ‘compulsive Internet use’ or ‘Internet addiction’ among adolescents and emerging adults (van den Eijnden et al., 2010; Kuss et al., 2013). These reports show a lack of consensus among scholars on whether or not adolescents and emerging adults are compulsive Internet users and ‘addicted’ to the Internet. On one hand researchers argue that the overuse of Internet can negatively affect the social, physical, and intellectual activities of users (Yu, Kim & Hay, 2013). Others argue that the usage of Internet is changing and is now more frequently used for gaining knowledge and for staying connected with peers. This is especially the case with adolescents and emerging adults and can be seen as a new phenomenon where social connections are extended into the online world (Boyd, 2014; LaRose et al., 2014). This new way of using the Internet is not only seen as a negative. Scholars argue that online communication can actually strengthen offline relationships (van den Eijnden et al, 2008; Valkenburg & Peter, 2011).
LaRose, Lin and Eastin (2003) argue that ‘Internet addiction’ is not a correct term for adolescents and emerging adults’ Internet usage. They state that their media behaviour is habitual and causes loss of self-control when using the Internet instead of being an addiction. But how is addiction defined in general? Sussman and Sussman (2011) describe addiction as an engagement in behaviour to achieve appetitive (desiring) effects, a preoccupation with the behaviour, temporary satiation (saturation), loss of control over the behaviour, and suffering
negative consequences. In comparison, not all who use the Internet compulsively become so absorbed that they experience negative consequences (Yu et al., 2013). Internet addiction research shows that only between 1.5 percent and 11.3 percent of adolescents and between 8 percent and 13 percent of emerging adults show signs of Internet addiction (Ko et al., 2009; Kormas et al., 2011; Kuss et al., 2013; Park, Kim & Cho, 2007). Is it possible to state that adolescents and emerging adults are addicted to the Internet? LaRose et al., (2003) argue that they are not addicted, but have problems with controlling their Internet usage. Van Rooij et al. (2010) reason that people do not have addictive problems with the medium Internet, but with the various online activities. Internet addiction should therefore be redefined as deficient self-regulation (LaRose et al., 2003).
Moreover, the above studies have taken into account the effects of Internet as a whole, whether it is being used on personal computers, laptops or mobile phones. It is interesting to investigate whether the use of smartphone in itself causes different problems with self-regulation behaviour. Unlike personal computers and laptops, smartphones make sure that people can stay ‘connected’ 24/7, making it even more difficult for youth to regulate their Internet usage (Kuss et al., 2013).
According to Coyne, Padilla-Walker and Howard (2013), there is little scholars know about the changes in media behaviour from the time of adolescence to their emerging
adulthood. Scholars consider media use in both age groups as high. When looking at
smartphones, adolescents are seen as highly susceptible to the negative effects of smartphone usage. They use their smartphones more frequently and are more likely to admit being
‘addicted’ to their phone than adults (Kim et al., 2014). This statement indicates that media use changes over time. Unfortunately, research fails to fully understand why emerging adults show less ‘addictive’ signs when using their smartphones compared to adolescents. It is unknown if this change is due to differences in age or if smartphone usage has a natural
lifecycle. Kim et al. (2014) argue that adolescents are more addicted to smartphones than emerging adults and adults, however, when looking at the concept of “digital natives” from Prensky (2001), the opposite should be true. According to Prensky (2001), adolescents should be more effective in self-regulating their smartphone usage since they have been emerged in this digital technology since infancy. An opinion piece by Rian Visser (2013) is in line with Prensky’s reasoning. Visser (2013) argues that many adolescents are capable of turning of their smartphone while studying and do not feel the need to respond to messages
instantaneously. She wonders whether this is a normalisation of media usage.
With this information in mind, it is interesting to research if and how smartphone behaviour is changing, bearing in mind the digital nativeness of some age groups. Do adolescents and emerging adults differ in their motivations and self-regulating abilities in their usage of smartphones? Maybe there is a lifecycle in smartphone use where adolescents and emerging adults differ in their habitual behaviour, or have different attitudes towards smartphones. Or smartphone usage is influenced when saturation, due to external stimuli, is experienced. Therefore, the following research question will be investigated:
“To what extent do adolescents and emerging adults differ in their smartphone usage? Do age, motivations, self-regulating behaviour, and lifecycle contribute to changing
smartphone usage?”
Theoretical Background
To fully understand the possible differences in smartphone usage between adolescents and emerging adults and the causes of these differences, it is interesting to research if and how characteristics of each age group have any influence. These possible differences are essential to understand dissimilarities in time spent with smartphones and variations in
attitudes towards smartphone behaviour. The uses and gratifications theory will help to examine what motivates adolescents and emerging adults to use their smartphones and what differences between the two age groups could lead to increased or decreased use of
smartphones. Instrumental factor in the possible changes could be the difference in
smartphone usage and self-regulation between the two age groups. Subsequently, the lifecycle of smartphone usage will be analyzed, studying the differences in habitual- and normative smartphone behaviour. Next to that, it is questioned whether possible changes of smartphone usage by adolescents and emerging adults could be caused by saturation due to an oversupply of stimuli, changes in habitual behaviour or changes in social attitudes in smartphone use.
Adolescents vs. Emerging Adults
In order to get a clear picture on how adolescents and emerging adults differ in their smartphone usage, it is important to understand the origin this difference. Characteristical differences between the two age groups could explain the possible dissimilarities between the users. Moreover, these differences are essential in understanding dissimilarities in time spent with smartphones between the two age groups.
Adolescence is defined as the transitional phase between childhood and adulthood (Crone & Dahl, 2012; Boyd, 2014). Children in this age group are aged between 12 and 18 years old. Learning and adjusting, particularly in terms of long-term goals and personal aspirations characterize adolescence. It is a time where youth discover how to navigate new, and often compelling, social, physical, cognitive, and emotional challenges within themselves (Crone & Dahl, 2012; Boyd, 2014). During adolescence, there is a steady increase in the ability to use cognitive control over thoughts and actions and these arethe driving force behind cognitive development. This development increases the learning and successful adaption to a wide variety of social contexts and cultural influences (Crone & Dahl, 2012;
Boyd, 2014). This ability of adolescents to control their thoughts and actions is not only crucial for the direct learning of new skills, but also for behavioural control like avoiding distractions and quickly shifting priorities (Crone & Dahl, 2012). Developmental changes that are being observed in adolescence are the formation of their own unique identity, the need for peer relationships, autonomy from parental figures, and their increased sensation-seeking and risk-taking behaviour. These developmental changes will be linked to motivations for
smartphone use in the next chapter.
Emerging adulthood involves some social changes individuals go through between late adolescence and young adulthood (Coyne et al., 2013; Crone & Dahl, 2012;
Subrahmanyam et al., 2008). An emerging adult is typically aged between 19 and 25 and is distinguished by a transition to independence from social roles, normative expectations, as a more responsible individual. Emerging adults have not yet entered the enduring
responsibilities that are normative for adulthood, as they are still exploring possibilities in life related to personal identity, friends, family and career (Arnett, 2000; Coyne et al., 2013; Crone & Dahl, 2012). Making them feel in-between, they do not consider themselves adolescents, nor entirely adults as well (Arnett, 2000; Arnett, 2006). According to Arnett (2006), five features can distinguish emerging adulthood, namely: as the age of identity explorations, instability, being self-focussed, feeling in-between, and as the age of
possibilities. These developmental changes will also be linked to motivations for smartphone use in the next chapter.
Smartphone usage. The above information can help explain adolescents and emerging adult’s smartphone usage. It is difficult to precisely indicate how much time adolescents and emerging adults spend with their smartphones as smartphone use is often short but occurs relatively often (YoungWorks, 2013). Analysis show that 89 percent of Dutch adolescents aged 12 to 15 own a smartphone and 96 percent of Dutch emerging adults
aged 15 to 25 own a smartphone (CBS, 2014). Even though the age groups are not correctly divided among adolescent and emerging adults, the data show that smartphone ownership with emerging adults is higher than with adolescents. In the next chapter motivations for smartphone usage will be linked to the developmental differences between adolescents and emerging adults.
Motivations Smartphone Usage
In order to understand what motivates adolescents and emerging adults in using smartphones, it is important to comprehend their reasons for using smartphones. Individuals use certain media to satisfy needs. This satisfaction of needs is described in the uses and
gratifications theory. This theory, set out by Katz in 1953 (in: O’Donohoe, 1993), suggests
that communication research should not focus on what media do to people, but what people do with these media. The basis of the theory is the idea that media selection is based on the desire to satisfy various needs. This desire for gratification sets out the behavioural intention. In other words: the theory indicates that an individual will actively try to satisfy a certain need, the media use is goal-oriented, and the choice of the media is determined by previous experiences. Moreover, different media compete with each other for the need of satisfaction (Joo & Sang, 2013; O’Donohoe, 1993; Sundar & Limperos, 2013).
Gratification research on smartphone use has focussed on psychological needs and motives (entertainment, sociability, learning), content specific motivations (safety service, financial service), and social communication (texting, calling, chatting) (Kang & Jung, 2014). These gratifications overlap with gratification research from different types of media and most studies focus on the content gratifications and process gratifications of the medium. These gratifications concern the message itself as well as the actual use of the media
(Stafford, Stafford & Schkade, 2004; Sundar & Limperos, 2013). But these gratifications are fixed and do not take into account the social experience in the media. According to Sundar
and Limperos (2013) traditional research focuses on gratifying existing needs by using certain media. However, according to them, gratifications can also be triggered by features
individuals experience while using that particular medium. Sundar and Limperos (2013) explain that users are not always goal-directed at the beginning of their involvement with the media, but develop certain needs during their interaction with the media and in turn creating new rituals of using that medium. This ritualized media use is more habitual and for diverse reasons, like companionship, time consumption, and relaxation. It is less goal-orientated but gratifies more abstract needs of individuals (Joo & Sang, 2013). Habitual behaviour of smartphone usage will be explained in more detail later in this article.
The present study analyses whether developmental factors influence smartphone usage. These developmental factors are being seen as abstract motivations, or needs that can be gratified through smartphone use. When the need(s) is (are) gratified, individuals will use the smartphone again to keep gratifying the need(s). Smartphone use will then become habitual which reinforces the smartphone use as gratifying to their need(s) (Chen, 2010; Sundar & Limperos, 2013). The developmental factors of adolescents and emerging adults are being analyzed and compared with each other in order to provide an understanding in how motives for smartphone use could, possibly, be different between the two age groups. And this difference could possibly explain potential differences in time spent with smartphones. The developmental factors in this study are used as possible needs from individuals that ask for gratification through smartphone usage.
Adolescents vs. emerging adults. There are numerous reasons why adolescents and emerging adults use smartphones. However, based on the developmental tasks of both age groups, the choice was made to focus on four key features that stand out in their development:
identity development, peer relationships, intimacy, and autonomy. These developmental
mediate these developmental features through social networks (Subrahmanyam et al., 2008). Between childhood and adulthood, adolescents are struggling to find a balance
between dependence and independence from their parents (Boyd, 2014). They are developing knowledge and skills to be capable of functioning independently from their parents (Crone & Dahl, 2012; Boyd, 2014), and desire to become more autonomous from their parents by making their own decisions about life (Daddis, 2011). Emerging adults gain even more autonomy from their parents than adolescents. Most emerging adults can take responsibility for their own actions and can also make independent decisions (Coyne et al., 2013). Media are used to apply their own autonomy regarding their decision-making. Autonomy can be
expressed by the choice of which social media platform is being used, which music to listen to, which games to play, but also by choosing who to connect with and which information to share with these connections (Coyne et al., 2013).
During adolescence, adolescents start to form their own personal identity that is not exclusively defined by family ties, becoming less close with parents and exchanging parent dependency for peer dependency (Boyd, 2014; Fuligni et al., 2001), where peer opinions become increasingly salient (Crone & Dahl, 2012). Media become very important for
adolescents during this period as they use media to explore and establish a unique identity that is separate or sometimes even hidden from parent supervision (Padilla-Walker et al., 2012). They start to form their own unique identities as they explore the social world surrounding them (Davis, 2013; Steinberg & Morris, 2001). Research shows that media can play a role in multiple aspects of identity formation, including gender, sexuality and ethnicity. And
adolescents seek out media as a means to explore and form their identity in these contexts with the use of different types of media (Coyne et al., 2013). Arnett (2000; 2006) argues that identity exploration is more important during emerging adulthood as individuals explore numerous possibilities in their lives in various contexts, especially love, work and worldviews
(Arnett, 2000; Arnett, 2006; Crone & Dahl, 2012). As with adolescence, emerging adults use media to express and form their identity, especially in terms of gender, sexuality, and
ethnicity (Coyne et al., 2013). By using social media, they can explore possible identities and discover who they really are. But they can also express their identities by sharing information. By posting and sending messages through various social media platforms, statements are made about who he or she is creating one’s ‘one-and-only-me’ in terms of personal beliefs and standards. This posting and sending of messages can also be used to explore identities to find one’s own ‘true identity’ (Boyd, 2014; Coyne et al., 2013), using different context (parents, peers, teachers) and express themselves differently across these contexts (Steinberg & Morris, 2001).
Adolescent’s social interactions are shifting from self-oriented behaviour towards other-oriented behaviour (Crone & Dahl, 2012). Given that adolescents are becoming more dependent on their peers for advice and support, it makes sense that the use of media becomes more important (Boyd, 2014; Padilla-Walker et al., 2012). Where in adolescence peer
relationships become very important, emerging adults are looking for more intimacy in these relationships. Even though both age groups use social media to fulfill the need for social needs, emerging adults not only want to establish peer relationships but also increase their intimacy with others. They want to stay in close contact with their peers (Coyne et al., 2013).
Smartphones give adolescents and emerging adults the possibility to make use of various applications that can help develop their identity, establish peer relationships, intimacy, and give them the feeling of being autonomous from others. They can explore these in many different contexts (social network sites (SNS), instant message (IM) blogs, etc.) (Davis, 2013). Research shows, for example, that photo-sharing applications gratify the need for personal identity enhancement. By sharing photos online, adolescents and emerging adults can develop and express their own unique identity (Sundar & Limperos, 2013). Also, social
media platforms in general gratify the need to stay connected with peers (Subrahmanyam et al., 2008). All developmental needs can be gratified by the use of social media platforms on smartphones. However, it is not clear whether adolescents or emerging adults find it
important to gratify this need through the use of this media platform. This study will look at the possible difference in motivational use of the smartphone between the two age groups and whether this leads to differences in time using the smartphone. Therefore the following research question has been prepared:
RQ1: “To what extent does motivational smartphone usage differs between adolescents and emerging adults?”
Self-Regulation in Smartphone Usage
As previously discussed in the introduction, adolescents and emerging adults are prone to lose self-control when using the Internet. Causing many researchers to state that they are addicted to Internet. However, since research shows that only between 1.5 and 11.3 percent of adolescents and between 8 and 13 percent of emerging adults shows signs of Internet
addiction (Ko et al., 2009; Kormas et al., 2011; Kuss et al., 2013; Park et al., 2007). LaRose et al., (2003) argue that they have problems regulating their Internet usage, the so-called
deficient self-regulation. Farley and Kim-Spoon (2014) define self-regulation as an exertion of control over the self by the self and involves inhibiting or changing initial and dominant thoughts, feelings, or behaviours.
As smartphones enable users to stay online 24/7 and provide users with all possible social media platforms available, it is probable that users have more problems regulating their smartphone usage then their Internet usage. The constant online presence on social media platforms ensures that users receive a constant stream of new information available for them to read, view, and listen to. This makes it more difficult to regulate the usage of the
smartphone. Individuals with greater trait self-control are more likely to see which
components of their smartphone use are more prone to lose their self-control and therefore are better able to control their behaviour in the use of the smartphone (Redden & Haws, 2013). This is also called internal locus of control (Lee et al., 2014). Individuals with an internal locus of control are better at regulating their behaviours and therefore are better at following plans (Lee et al., 2014).
However, some people can control their self-regulating behaviours better than others (Redden & Haws, 2013). In this current study, it is questioned whether emerging adults can regulate their smartphone behaviour better then adolescents or whether this is the other way around. According to Prensky (2001) today’s college students are digital natives when it comes to new media. According to him, youth have grown up with the newest media and know how to mediate this into their life. Using it constantly, they have found a perfect
balance between media and other activities in their daily lives. In other words, Prensky thinks that today’s youth is better in regulating their media use than adults. However, smartphones have not been around for such a long time. Today’s college students have not grown up with these new devices, adolescents have. They have experienced the constant online presence whereas this is relatively new for emerging adults. Thus the question is whether adolescents might be better at regulating their smartphone usage compared to emerging adults. Therefore the following research question has been drafted:
RQ2: “To what extent do self-regulating smartphone abilities differ between adolescents and emerging adults?”
Lifecycle Smartphone Usage
Besides how adolescents and emerging adults may differ in their motivations for using smartphones, habitual behaviour, saturation, and changing social relations (norms) also have
an influence on how often smartphone are being used. These aspects are part of the lifecycle in smartphone usage. Behaviours and attitudes change over time and can therefore influence the way smartphones are being used by adolescents and emerging adults.
Habitual behaviour. Research by Oulasvirta et al. (2012) found that habits, especially checking habits, are an important factor contributing to smartphone usage. Habit is defined as an automatic behaviour triggered by situational cues, such as places, people, and preceding actions. Habits are learned dispositions to repeat past responses. A habit is mostly an automatic response that arises intentionally or unintentionally in the course of daily life (Wood & Neal, 2007)). This response is triggered when an individual enters a setting where the habit is typically performed (Wood & Neal, 2007). People make it a habit of using their smartphone often because it provides them with quick access to their social network,
communications, and news information (Oulasvirta et al., 2012), and is a form of habit to pass the time (Smock et al., 2011). But also the demands of responding to messages quickly and maintaining relationships lead to the habitual usage of smartphones (LaRose et al., 2014). These habits are triggered by different cues outside the device, such as situations and
emotional states. Individual’s smartphone behaviour is mostly automatic, as users can quickly check their phones. This helps individuals to relieve boredom, but also cope with lack of stimuli of everyday situations (Oulisvirta et al., 2012). Relieve of boredom can be triggered by the fact of seeing the smartphone laying on the table and reminding us of certain rewards of using the phone. This counts as well for the lack of stimuli. When someone is not
stimulated in an everyday activity, the smartphone can trigger a reminder of ‘fun’ when using the phone (Oulisvirta et al., 2012).
However, habits can have both positive and negatives outcomes on one’s behaviour. On the one hand, habits are necessary in control of action, and are an important behaviour facilitator. On the other hand, the automatic behaviour can become excessive where repetitive
habit behaviour can increase the risk of losing control over the smartphone, increasing the deficient self-regulation (LaRose et al., 2014). This is evident in the study of Oulisvirta et al. (2012) where checking habits could act as a ‘gateway’ to other applications on the
smartphone, leading to more time spent checking new content and information. Those individuals with good self-control, able to regulate their smartphone use, will experience less negative effects of habitual smartphone behaviour.
In this study the difference between adolescents and emerging adults habitual behaviour is analysed. Therefore the following research question has been drafted:
RQ3: “To what extent do adolescent and emerging adults differ in their habitual smartphone behaviour?”
Furthermore, the question whether adolescents or emerging adults show more self-control in their smartphone behaviour and also find their smartphone usage less habitual will be analysed. Therefore the following research question has been prepared:
RQ4: “To what extent do adolescents and emerging adults, who have self-control over their smartphone, show less habitual smartphone behaviour?”
Normative smartphone behaviour. Whereas habitual behaviour could possibly differ between the two age groups, it is also possible that habits change over time as social norms towards smartphone usage changes as well.
The theory of normative social behaviour is important in understanding adolescents’ and emerging adult’s smartphone behaviour. This theory explains that one’s perception of acceptable behaviour affects individual’s own behaviour through the interaction with injunctive norms, outcome expectations, and group identity (Rimal & Real, 2005). Most
studies focus on drinking and smoking behaviour (Gannon et al., 2014; Mead et al., 2013; Merill et al., 2013), however, the theory of normative social behaviour can also apply to smartphone usage.
Observing family, friends, and others engaging in certain behaviour may lead individuals to believe that that particular behaviour is acceptable and therefore normative (Mead et al., 2013). This may lead to the individual acting out that behaviour. Studies have shown that reference groups play a critical role in how normative information is perceived and acted upon as the acceptability of certain behaviour depends on the source of the information (Mead et al., 2013). When looking at drinking and smoking behaviour, parents and communities disapprove of this behaviour whereas peers tend to support this behaviour. Both groups thus have different norms about the behaviour, but research shows that the perception of friends is seen as more important (Mead et al., 2013), as identification with peers supports normative behaviour (Gannon et al., 2014). The social environment of an individual therefore is forming norms about certain behaviour. In this case on how smartphones are being used by adolescents and emerging adults. The frequent usage of smartphone is either normative or not normative.
The physical environment is also an important predictor of social norms in smartphone use (Mead et al., 2013). In social gathering with parents smartphone usage is mostly not allowed, whereas gatherings with friends’ smartphone is often accepted. However, this acceptance of frequent smartphone usage among friends could change during emerging adulthood. For emerging adults it becomes less accepted that smartphones are being used during conversations with others. They do not feel the need to be online constantly anymore (Boyd, 2014). Therefore, the social norms change from adolescence to emerging adulthood.
With the above information in mind, the differences in normative behaviours between the two age groups are analysed. Therefore the following research question has been drafted:
RQ5: “To what extent does normative smartphone behaviour differs between adolescents and emerging adults?”
Saturation. How habitual and normative smartphone behaviour can influence time is spent with the smartphone has been discussed. Another aspect influencing time spent with a smartphone is saturation. Unlike habits and norms where smartphone usage can increase and decrease, saturation will only decrease time spent with the smartphone. Individuals become saturated when an enjoyable experience becomes less enjoyable with repeated or prolonged exposure (Galak, Kruger & Loewenstein, 2013). With the use of smartphones individuals can become saturated on the overload of stimuli from their connections, also called connection overload (LaRose et al., 2014). This connection overload occurs when the demands imposed by the gathering, maintenance, and updating of social media has unfavourable effects on peoples’ everyday lives. Smartphones make it possible for individuals to always stay connected and are constantly distracted from other (important) activities by social media platforms that connect people 24/7 (LaRose et al., 2014).
With this information in mind, it is interesting to analyse how both adolescent and emerging adults experience saturation. Emerging adults are to be expected to experience saturation as they are exposed to smartphones longer than most adolescents. However, individuals who show great self-regulation may not experience saturation at all as they are able to manage their smartphone usage and times spent online. Therefore the following research questions has been prepared:
RQ6: “To what extent do emerging adults experience saturation compared to adolescents?”
saturation?”
With the above information in mind, it is questioned whether emerging adults experience a lifecycle in their smartphone usage. Habitual- and normative smartphone behaviour is supposed to change over time. Smartphone usage is assumed to eventually lead to feeling saturated. With this in mind, the following research question has been prepared:
RQ8: “To what extent do adolescents and emerging adults experience a lifecycle in
their smartphone usage?”
Figure 1 shows the research questions in a conceptual model. The model shows that all concepts are expected to have an influence on the smartphone usage of adolescents and emerging adults.
Method
Procedure
This study was conducted using a survey as data-collecting method. By using a survey it was possible to explain the social phenomenon ‘smartphone usage’ and how this usage changes from adolescence to emerging adulthood. Surveys were decided to be used as a data-collection method as these offer the opportunity to analyse motivations, self-regulation, and the lifecycle in a relatively short time. Next to that, a great number of respondents can be contacted in this short time frame ('t Hart & Snijkers, 2009). This study tries to explain the attitudes and motivations of smartphone usage and how these could possibly differ between adolescents and emerging adults. Subsequently, an analysis was made if the possible change in smartphone usage for emerging adults could be caused by self-regulation or is part of the natural lifecycle.
Since this study is partly focused on underage respondents, some ethical steps needed to be taken into account. In accordance with the legislation regarding ethics review of young people under eighteen years, it is required by law that parents or legal caregivers of a child give permission by means of an informed consent to participate in the study. In this case, the
active informed consents was chosen to be used. This entails that parents or legal caregivers
receive information about the study that is taking place and declare whether their child is allowed to participate in the research or not. Underage participants known by the researcher were chosen to be used and to ask family and friends of these participants to also take part in this research. This form of data collecting is called the snowball effect (Boeije, 2009).
As emerging adults are officially adults and over eighteen years of age, no informed consent from parents or legal caregivers is necessary. Therefore it was possible to contact the emerging adult group through different social media channels.
In order to prevent spurious connections and to have sufficient generalizability of the study, adolescent students from different sexes, ages and different educational levels were
asked to participate. For the emerging adults social media platforms were used in order to generate the same differences in sex, age, and educational level.
Sample
In total a number of 114 people aged twelve till twenty-five have participated in this research. Of these respondents only 90 were available for analysis, as the other respondents did not complete the survey. The respondents who participated in this study were found across the Netherlands, increasing the generalisation of the research. The sample consisted of 40 participants twelve till eighteen-year-old adolescents and 50 participants nineteen till twenty-five year old emerging adults. 62.5 Percent of adolescent participants were female (M=1.38, SD=0.49) and their main educational level is HAVO (M=2.68, SD=1.21). Of the emerging adult participants 62.0 percent was female (M=1.38, SD=0.49) and their main educational level is HBO (M=5.36, SD=1.19).
Measurement
The survey consisted of two parts (see Appendix I). In the first part of the study the participants are asked to answer some questions about their personal characteristics like age, gender, educational level, and their hometown. Also questioned was how often they use their smartphone in minutes on an average day and for which purpose (calling, texting, social media, music etc.). This is measured with a five-point Likert-scale with 1 = zero to fifteen minutes a day and 5 = sixty minutes a day or more. In the second part of the study,
participants are asked to answer questions about their smartphone behaviour. These questions are asked on the basis of several statements that together should measure the five concepts; motivations, habits, norms, self-regulation and saturation.
Motivations. The concept motivations consisted of sixteen statements that as a whole measured four latent variables (Identity Development, Peer Relationship, Intimacy, and
Autonomy). The statements in the survey were based on previous scales used by Smock et al.
(2011) and partially based on the article by Coyne et al. (2013). The statements were preceded with the statement: “I use my smartphone and corresponding applications…”. The
respondents could then answer the statement on the basis of a five-point Likert-scale, with 1 = disagree and 5 = agree. The average scores of these statements were then used to measure to what extent adolescents and emerging adults are motivated for using their smartphone. The factor analysis showed that the statements indeed form the four latent variables, as there are four scales with an eigenvalue higher than 1. In Table 1, the reliability values are mentioned of each scale.
Self-regulation. Fifteen statements measured the concept self-regulation and the statements were based partially on a pre-existing scale from Kim et al. (2014) and on articles by Ko et al. (2009) and Yoong (2004). The factor analysis indicated that there were four components with an eigenvalue higher than 1, each with their own specific self-regulating behaviour, namely; self-regulation in absence smartphone, negative self-regulation, positive self-regulation, and self-regulation peer experiences. Table 1 shows the related reliability values.
Habitual smartphone behaviour. There were four statements that measured the latent variable habit. These statements were based on the articles of Joo and Sang (2013) and Smock et al. (2011). As with the previous statements, all questions were preceded with the statement: “I use my smartphone and corresponding applications…”, and needed to be answered on a five-point Likert-scale. The factor analysis showed that the items together formed a reliable scale, with a Cronbach’s alpha of 0.73.
Normative smartphone behaviour. In total nine statements measured the concept normative behaviour. No scientific source has been found with a pre-existing scale.
written by Rian Visser in De Volkskrant (2013). The factor analysis showed that there were three components that have an eigenvaluehigher than 1. Each of the components represents specific normative behaviour, namely; normative behaviour when sending messages,
normative behaviour during social gatherings, and normative behaviour from peers. Table 1 shows the corresponding reliability values.
Saturation. In total four statements measured the concept saturation. The statements are based on an opinion piece from Rian Visser in De Volkskrant (2013) and the researchers own experience. The factor analysis showed that these statements together form one
component with an eigenvaluehigher than 1. These statements are then compared to six statements that together measured the decreased usage of smartphones under respondents. A factor analysis showed that these statements also form one component with an eigenvalue higher than 1.
Lifecycle. The possible lifecycle smartphone behaviour is tested with the concepts normative smartphone behaviour, habitual smartphone behaviour, and saturation on decreased smartphone usage. These concepts were analysed with a multiple regression analysis to test whether any of the concepts or all concepts as a whole influence the change in smartphone usage.
Table 1: Summary Cronbach’s alpha
Scale Cronbach’s alpha
Motivation Identity Development 0.74 Peer Relationship 0.67 Intimacy 0.71 Autonomy 0.73 Self-regulation Absence Smartphone 0.90 Negative 0.84 Positive 0.72 Peer experience 0.71
Habitual smartphone behaviour - 0.73
Normative smartphone behaviour
Sending messages 0.74 Social gatherings 0.74
Peers 0.53
Saturation
Saturation 0.81
Results
Adolescents and emerging adults spend most of their time sending messages (30 to 45 minutes a day) or visiting social media websites (15 to 30 minutes a day) on their smartphone. A one-sample t-test analysed how the respondents deviate from the central midpoint of the scale, see Table 2. With the exception of social media, all scales deviate significantly from the midpoint of the scale. Respondents indicate spending more time sending messages than the average of the scale, whereas listening to music, playing video games, and calling score significantly below the average of the scale.
Table 2: Averages smartphone usage (μ = 3)
M (SD) t p CI Full sample (N=90) Messaging 3.53 (1.24) (89) 4.09 < 0.00 [3.27, 3.79] Social Media 2.91 (1.46) (89) -0.58 0.565 [-2.61, 3.22] Music 2.60 (1.53) (89) -2.49 < 0.05 [2.28, 2.92] Games 1.46 (0.89) (89) -16.48 < 0.00 [1.27, 1.64] Calling 1.31 (0.76) (89) -21.11 < 0.00 [1.15, 1.47]
Using an independent t-test the presence of any significant differences between adolescents and emerging adults in their time using their smartphone was analysed (Table 3). The only significant difference that has been found is between adolescents and emerging adult’s music use and video game play. Adolescents listen to music more often on their smartphone than emerging adults. This is a big effect. Adolescents spend more time playing video games on their smartphone compared to emerging adults. However, this is a small effect. Another independent t-test further analysed whether there are any differences between genders in both age groups. These analysis show that in both age groups there are no
Table 3: Averages and differences smartphone usage per age group and gender M (SD) t p CI d Adolescents (N = 40) Emerging Adults (N = 50) Messaging 3.38 (1.27) 3.66 (1.21) (88) -1.09 0.280 [-0.81, 0.24] Social Media 2.63 (1.50) 3.14 (1.40) (88) -1.68 0.096 [-1.12, 0.09] Music 3.33 (1.49) 2.02 (1.30) (88) 4.43 < 0.00 [0.72, 1.89] 0.94 Games 1.68 (1.02) 1.28 (0.73) (88) 2.14 < 0.05 [0.03, 0.76] 0.45 Calling 1.18 (0.50) 1.42 (0.91) (88) -1.53 0.129 [-0.56, 0.07] Adolescents (N = 40) Girls (N =25) Boys (N = 15) Messaging 3.56 (1.29) 3.07 (1.22) (38) 1.19 0.241 [-0.35, 1.33] Social Media 2.68 (1.55) 2.53 (1.46) (38) 0.30 0.768 [-0.85, 1.15] Music 3.44 (1.56) 3.13 (1.41) (38) 0.63 0.536 [-0.69, 1.30] Games 1.44 (0.77) 2.07 (1.28) (38) -1.94 0.600 [-1.28, 0.03] Calling 1.20 (0.50) 1.13 (0.52) (38) 0.40 0.689 [-0.27, 0.40] Emerging Adults (N = 50) Girls (N =31) Boys (N = 19) Messaging 3.81 (1.17) 3.42 (1.26) (48) 1.10 0.277 [-0.32, 1.09] Social Media 3.19 (1.40) 3.05 (1.43) (48) 0.34 0.734 [-0.69, 0.97] Music 2.06 (1.34) 1.95 (1.27) (48) 0.31 0.761 [-0.65, 0.89] Games 1.26 (0.68) 1.32 (0.82) (48) -0.27 0.789 [-0.49, 0.37] Calling 1.42 (0.85) 1.42 (1.02) (48) -0.01 0.995 [-0.54, 0.53]
Using a MANOVA an interaction between age and gender was tested on the different smartphone uses of adolescents and emerging adults. This test showed that there is no
significant interaction effect between age and gender (Table 4).
Table 4: Interaction age & gender
F p Messaging 0.04 0.842 Social Media 0.00 0.993 Music 0.10 0.758 Games 2.30 0.133 Calling 0.04 0.838
Adolescents and emerging adults’ motivational smartphone use
A one-sample t-test analysed how the respondents deviate from the central midpoint on the four scales in motivational smartphone behaviour (Table 5). With the exception of
identity formation, on all scales respondents deviate significantly from the midpoint.
Respondents indicate using their smartphone most often for their peer relations and for
intimacy. Identity development and autonomy score the lowest in motivational smartphone
behaviour. Even though, peer relations and intimacy scores are above the central midpoint of the scale, respondents are still indicating neither to agree nor disagree using these as
motivational smartphone behaviour.
Table 5: Averages motivational smartphone usage (μ = 3)
M (SD) t p CI Full sample (N=90) Peer Relations 3.60 (0.71) (89) 8.05 < 0.00 [3.46, 3.75] Intimacy 3.21 (0.78) (89) 2.49 < 0.05 [3.04, 3.37] Identity Development 2.87 (0.92) (89) -1.37 0.174 [2.67, 3.06] Autonomy 2.36 (0.78) (89) -7.70 < 0.00 [2.20, 2.53]
An independent t-test analysed whether there are any significant differences between adolescents and emerging adults in their motivational smartphone behaviour (Table 6). The only significant difference has been found in the sought autonomy of users. Both age groups indicate they somewhat disagree in using their smartphone for autonomy. However,
adolescents score higher on this scale then emerging adults. This is a medium effect.
Another independent t-test further analysed whether there are any differences between genders in both age groups. This analysis shows that there are no significant differences between boys and girls in both age groups (Table 6).
Table 6: Averages motivational smartphone use and difference between age groups and gender M (SD) t p CI d Adolescents (N = 40) Emerging Adults (N = 50) Peer Relations 3.60 (0.75) 3.61 (0.69) (88) -0.05 0.958 [-0.31, 0.29] Intimacy 3.23 (0.87) 3.18 (0.71) (88) -0.30 0.765 [-0.28, 038] Identity Development 2.89 (1.03) 2.85 (0.83) (88) 0.19 0.849 [-0.35, 0.43] Autonomy 2.59 (0.86) 2.19 (0.67) (88) 2.40 < 0.05 [-0.07, 0.71] 0.52 Adolescents (N = 40) Girls (N =25) Boys (N = 15) Peer Relations 3.63 (0.63) 3.55 (0.95) (38) 0.34 0.734 [-0.42, 0.59] Intimacy 3.16 (0.86) 3.36 (0.91) (38) -0.68 0.501 [-0.78, 0.39] Identity Development 2.72 (0.94) 3.17 (1.16) (38) -1.34 0.190 [-1.12, 0.23] Autonomy 2.37 (0.91) 2.92 (0.67) (38) -2.02 0.051 [-1.10, 0.00] Emerging Adults (N = 50) Girls (N =31) Boys (N = 19) Peer Relations 3.66 (0.62) 3.53 (0.79) (48) 0.66 0.515 [-0.27, 0.54] Intimacy 3.27 (0.76) 3.04 (0.60) (48) 1.16 0.252 [-0.18, 0.65] Identity Development 2.88 (0.84) 2.80 (0.84) (48) 0.31 0.756 [-0.42, 0.57] Autonomy 2.22 (0.72) 2.44 (0.61) (48) 0.40 0.688 [-0.32, 0.48]
A MANOVA analysed whether there is an interaction effect between age and gender on the four different motivational behaviours for using a smartphone. The analysis shows that there is no interaction effect, see Table 7.
Table 7: Interaction motivational smartphone usage on age & gender
F p
Peer Relations 0.02 0.884
Intimacy 1.59 0.211
Identity Development 1.67 0.200
Autonomy 3.66 0.059
Subsequently, the question whether age and motivational smartphone use have an influence on the changes in smartphone usage have been examined using a multiple
not useful in analysing the influence of age and motivation on the changes in smartphone usage.
Adolescents and emerging adults’ self-regulating smartphone abilities
Using a one-sample t-test respondents’ deviation from the central midpoint of the scales in self-regulating smartphone abilities was analysed (Table 8). With the exception of
peer experiences, respondents score significantly different from the midpoint of the scales.
Respondents indicate that that they somewhat disagree in their experience of positive and
negative self-regulating abilities. They also somewhat disagree that their peers think they
cannot regulate their own smartphone behaviour. Respondents disagree that they can regulate their behaviour when their smartphone is absent.
Table 8: Averages self-regulation smartphone use (μ = 3)
M (SD) t p CI Full sample (N=90) Positive 2.80 (1.03) (89) -1.88 < 0.05 [2.58, 3.01] Peer Experience 2.68 (1.24) (89) -2.47 0.064 [2.42, 2.94] Negative 2.18 (1.01) (89) -7.73 < 0.00 [1.97, 2.39] Absence Smartphone 1.80 (0.98) (89) -11.56 < 0.00 [1.60, 2.01]
Using an independent t-test the presence of any significant differences between adolescent and emerging adults self-regulating abilities was analysed (Table 9). However, no significant difference has been found. With another independent t-test the presence of any possible significant differences between genders in the two age groups was analysed (Table 9). Nevertheless, no significant difference between boys and girls can be found in both age groups.
Table 9: Averages self-regulation smartphone use and difference between age groups and gender M (SD) t p CI Adolescents (N = 40) Emerging Adults (N = 50) Positive 2.68 (1.16) 2.89 (0.91) (88) -1.00 0.320 [-0.65, 022] Peer Experience 2.70 (1.14) 2.66 (1.32) (88) 0.15 0.880 [-0.49, 0.57] Negative 2.22 (1.13) 2.15 (0.91) (88) 0.34 0.733 [-0.35, 0.50] Absence Smartphone 1.88 (1.09) 1.74 (0.89) (88) 0.67 0.505 [-0.28, 0.56] Adolescents (N = 40) Girls (N =25) Boys (N = 15) Positive 2.83 (1.34) 2.42 (0.75) (38) 1.07 0.291 [-0.36, 1.17] Peer Experience 2.82 (1.14) 2.50 (1.17) (38) 0.85 0.398 [-0.44, 1.08] Negative 2.31 (1.20) 2.07 (1.04) (38) 0.65 0.518 [-0.51, 1.00] Absence Smartphone 1.82 (1.19) 1.97 (0.94) (38) -0.42 0.680 [-0.88, 0.58] Emerging Adults (N = 50) Girls (N =31) Boys (N = 19) Positive 2.78 (0.99) 3.07 (0.76) (38) -1.08 0.288 [-0.82, 0.25] Peer Experience 2.76 (1.28) 2.50 (1.40) (38) 0.66 0.509 [-0.52, 1.04] Negative 2.31 (0.98) 1.88 (0.72) (38) 1.63 0.110 [-0.10, 0.95] Absence Smartphone 1.88 (0.93) 1.51 (0.81) (38) 1.47 0.148 [-0.14, 0.90]
With the use of a MANOVA any possible interaction effects between age and gender on self-regulating smartphone abilities were analysed. This analysis, however, shows that there is no interaction effect on any of the scales (Table 10).
Table 10: Interaction self-regulating abilities on age & gender
Subsequently, the question if age and self-regulation have an effect on the changes in smartphone usage was analysed using a multiple regression model. The model shows that age and self-regulation does not have a significant influence on changes in smartphone usage F (5, 84) = 1.399, p = 0.233. F p Positive 2.357 0.128 Peer Experience 0,01 0.910 Negative 0.17 0.683 Absence Smartphone 1.50 0.225
Adolescents and emerging adults’ habitual smartphone behaviour
A one-sample t-test analysed that respondents significantly deviate from the central midpoint on the scale habitual smartphone behaviour (Table 11). Respondents indicate that they neither agree nor disagree having habitual smartphone behaviour. An independent t-test does not show a significant difference between the two age groups, t(88) =0.66, p=0.509, CI =[-0.24, 0.47].
Table 11: Difference in habitual behaviour between age groups and gender
M (SD) t p CI d
Full sample (N=90) 3.80 (0.84) (89) 9.06 < 0.00 [3.63, 3.98]
Adolescents Girls (N = 25) 3.90 (0.93)
(38) 0.29 0.773 [-0.50, 0.66] Boys (N = 15) 3.82 (0.78)
Emerging adults Girls (N = 31) 3.94 (0.66)
(48) 2.10 < 0.05 [0.02, 0.95] 0.59 Boys (N = 19) 3.45 (0.98)
Another independent t-test further analysed whether there are any differences between genders in both age groups. This test shows that there is a significant difference between emerging adult boys and girls. Even though both boys and girls indicate to neither agree nor disagree having habitual smartphone behaviour, girls score significantly higher than boys. This is a medium effect.
Using a two-way ANOVA a possible interaction effect between age and gender has been tested on habitual smartphone behaviour. This test shows that there is no interaction effect between age and gender, F = 1.23, p = 0.270.
Effect of self-control on habitual smartphone behaviour
In order to analyse whether adolescents and emerging adults with positive self-regulating abilities over their smartphone behaviour show less habitual behaviour, it is
necessary to first test whether these two concept correlate with each other before being able to perform a regression analysis. With the use of a Pearson’s rank correlation the correlation
between the two concepts was examined. According to the test there is no significant correlation between people with positive self-regulation and their habitual behaviour, rS =
-0.20, p=0.06.
Since the correlation test shows that there is no significant correlation between the two concepts, it is not possible to perform a regression analysis.
Adolescents and emerging adults’ normative behaviour
With the use of a one-sample t-test respondent deviation from the central midpoint of the scales in normative smartphone behaviour was analysed (Table 12). On all scales,
respondents deviate significantly from the midpoint of the scale. Respondents indicate that smartphones should not be used during social gathering. Next to that, respondents neither agree nor disagree that their peer’s normative behaviour is similar as their owns. When it comes to sending messages, respondents indicate that they somewhat disagree on the question if messages should be answered immediately.
Table 12: Averages normative smartphone behaviour (μ = 3)
M (SD) t p CI
Full sample (N=90)
Social Gatherings 4.08 (0.96) (89) 10.67 < 0.00 [2.30, 2.65]
Peers 3.55 (0.78) (89) 6.75 < 0.00 [3.88, 4,29]
Sending Messages 2.48 (0.85) (89) -5.87 < 0.00 [3.39, 3.72]
Using an independent t-test the presence of any significant differences between adolescent and emerging adults in normative smartphone behaviour was analysed (Table 13). No significant differences between the two age groups have been found. With another
independent t-test the presence of any possible significant differences between genders in both age groups were analysed (Table 13). The only significant difference has been found under adolescent boys and girls in their normative behaviour during social gatherings. Girls more or less agree that smartphones should not be used during social gatherings, whereas
boys neither agree nor disagree smartphones should not be used in these circumstances. This is a medium effect.
Table 13: Averages normative smartphone behaviour and difference between age groups and gender
M (SD) t p CI d Adolescents (N = 40) Emerging Adults (N = 50) Social gathering 3.90 (1.04) 4.23 (0.88) (88) -1.63 0.107 [-0.73, 0.07] Peers 3.63 (0.85) 3.49 (0.72) (88) 0.84 0.401 [-0.19, 0.47] Sending messages 2.64 (0.88) 2.34 (0.80) (88) 1.71 0.092 [-0.05, 0.66] Adolescents (N = 40) Girls (N =25) Boys (N = 15) Social gathering 4.18 (0.69) 3.43 (1.35) (38) 2.32 < 0.05 [0.95, 1.40] 0.70 Peers 3.83 (0.74) 3.31 (0.96) (38) 1.91 0.063 [-0.03, 1.06] Sending messages 2.65 (0.90) 2.63 (0.90) (38) 0.06 0.955 [-0.58, 0.61] Emerging Adults (N = 50) Girls (N =31) Boys (N = 19) Social gathering 4.31 (0.90) 4.11 (0.86) (48) 0.78 0.439 [-0.32, 0.72] Peers 3.55 (0.74) 3.40 (0.70) (48) 0.69 0.495 [-0.28, 0.57] Sending messages 2.30 (0.79) 2.41 (0.84) (48) -0.46 0.645 [-0.58, 0.36]
A MANOVA further tested whether there are any possible interaction effects between gender and age on normative smartphone behaviour. This analysis shows that there are no interaction effects to be found, see Table 14.
Table 14: Interaction normative smartphone behaviour on age en gender
F p
Social gathering 1.79 0.184
Peers 1.21 0.275
Sending messages 0.12 0.735
Adolescents and emerging adults’ smartphone saturation
A one-sample t-test analysed how much adolescents and emerging adults deviate from the central midpoint in the scales smartphone saturation (Table 15). Respondents significantly deviate from the central midpoint in both scales. Both in the scale saturation and decreased
smartphone usage, respondents significantly score lower than the central midpoint.
Respondents somewhat disagree that they experience saturation and decreased smartphone usage.
Table 15: Averages smartphone saturation (μ = 3)
M (SD) t p CI
Full sample (N=90)
Saturation 2.38 (1.03) (89) -5.71 < 0.00 [2.17, 2.60]
Decreased Smartphone Use 2.32 (0.88) (89) -7.37 < 0.00 [2.13, 2.50]
An independent t-test analysed possible differences between the two age groups (Table 16). No significant difference has been found between the two age groups however. Another independent t-test further analysed whether there are any possible differences between genders in both age groups (Table 16). Again, no significant difference has been found.
Table 16: Averages decreased time spend with smartphone and saturation differences between age group and gender M (SD) t p CI Adolescents (N = 40) Emerging Adults (N = 50) Saturation 2.21 (1.02) 2.53 (1.02) (88) -1.48 0.144 [-0.75, 0.11] Decreased Smartphone use 2.34 (0.96) 2.30 (0.81) (88) 0.18 0.856 [-0.34, 0.41] Adolescents (N = 40) Girls (N =25) Boys (N = 15) Saturation 2.42 (1.11) 1.85 (0.75) (38) 1.76 0.087 [-0.09, 1.23] Decreased Smartphone use 2.39 (0.91) 2.26 (1.07) (38) 0.41 0.682 [-0.51, 0.77] Emerging Adults (N = 50) Girls (N =31) Boys (N = 19) Saturation 2.70 (0.97) 2.24 (1.05) (48) 1.59 0.118 [-0.12, 1.05] Decreased Smartphone use 2.37 (0.84) 2.19 (0.77) (48) 0.75 0.458 [-0.30, 0.66]
A MANOVA further analysed whether there is any possible interaction effect between age and gender on the decreased smartphone time and saturation. The analysis shows,
however, that there is no interaction effect (Table 17).
Table 17: Interaction decreased time spend with smartphone and saturation on age & gender
F p
Saturation 0.06 0.810
Decreased Smartphone use 0.02 0.904
Subsequently, the decrease of time spent with their smartphone from people who indicate to experience saturation was examined by use of a regression model. This model is significant F (1, 88) = 4.600, p < 0.05 and therefore useful in analysing the influence
experienced saturation has on decreased time spent with smartphone. However, the predictive power is very weak. Only 5% of the difference in the variable decreased smartphone usage can be predicted by the variable saturation (R2 = 0.050). Saturation b* = 0.223, t = 2.15, p < 0.05, 95% CI [0.01, 0.37] has a significant relation with the dependent variable decreased
smartphone usage. The more saturation is experienced, the more individual’s decrease their
times spent with smartphones. Every increase in saturation will lead to a decrease in time spent with smartphone of 0.23.
Effect self-control on saturation
To analyse whether adolescents and emerging adults with greater self-regulating abilities experience less saturation than people who have no self-regulation, it is necessary to first examine whether the two concepts correlate with each other before being able to perform a regression analysis. Pearson’s rank correlation shows that the two concepts have a
significant correlation r = 0.26, p =0.013.
To analyse how self-regulating abilities can have an influence on a person’s saturation a regression model can be performed. This model is significant: F (I, 88) = 6.453, p < 0.01
and therefore useful in analysing the influence self-regulation on saturation. However, the predictive power is very weak. Only 6.8% of the differences in the variable saturation can be predicted by the variable self-regulation (R2 = 0.068). Self-regulation b* = 0.261, t = 2.54, p < 0.01, 95% CI [0.06, 0.46] has a significant relation with the dependent variable saturation. The more self-control a person has over its smartphone, the more saturation is experienced. Every increase in self-control will lead to an increase in saturation of 0.26.
Adolescents’ and emerging adults’ smartphone lifecycle
To analyse whether adolescents and emerging adults experience a lifecycle in their smartphone usage, the concepts saturation, habitual behaviour, and normative behaviour are analysed on the possible influence on change in smartphone usage. First, it is necessary to examine whether the concepts correlate with each other. Pearson’s rank correlation shows that only the concept saturation correlates significantly with decreased smartphone usage (Table 18).
Table 18: Correlation decreased smartphone usage (N = 90) p Age 0.856
Saturation < 0.05
Habitual behaviour 0.297
Normative Behaviour: Social gathering 0.370
Peers 0.148
Sending messages 0.070
A multiple regression model further analysed whether saturation, habitual behaviour, and normative behaviour have an influence on decreased smartphone usage. Age is also taken into account as a factor influencing the decreased usage. The model shows none of the concepts have a significant influence on the variable decreased smartphone usage (Table 19). Further, the model shows that the concept saturation has a significant influence on the
keeping age a constant factor. All other concepts show no significant influence, but do show a slight influence on the significance of the concept saturation. With the concept habitual
behaviour added saturation becomes slightly more significant, whereas the concept normative behaviour does not have that influence on saturation. It is clear from this model that
smartphone saturation has an influence on the decreased usage of smartphones, whereas the other concepts part of the smartphone lifecycle does not.
Table 19: summary regression analysis for variables predicting smartphone lifecycle (N = 90)
Conclusion
In this study the question to what extent adolescents and emerging adults experience a lifecycle in their smartphone usage has been examined by means of a survey. Smartphone use is expected to undergo a lifecycle as users habitual- and normative smartphone behaviour changes over time. Next to that, smartphone usage is assumed to eventually lead to users feeling saturated due to an oversupply of stimuli. It was studied if motivational factors,
self-regulation affecting smartphone usage, habitual-, normative smartphone behaviour and saturation could indicate changes in smartphone behaviour between adolescents and
emerging adults. 90 Adolescents and emerging adults between the ages of twelve and twenty-five years old have participated in this research. The survey consisted of two parts in order to answer the research question ‘To what extent do adolescents and emerging adults experience
a lifecycle in their smartphone usage?’ accurately.
motivational smartphone usage differ between adolescents and emerging adults?” For motivational smartphone use the possible difference between the two age groups in their
intrinsic need for Identity formation, Peer relationship, Intimacy, and Autonomy and how this need influences their behavioural intent to use their smartphone has been analysed. The results indicate that, except for sought autonomy from parents, adolescents and emerging adults do not differ in their motivational smartphone usage. For sought autonomy there is a significant difference between the sought autonomy of adolescents and emerging adults. Adolescents indicate using their smartphone more for autonomy than emerging adults, but it has to be stated that this difference is very limited.
Secondly, smartphone self-regulating abilities have been studied to answer research question two: “To what extent do self-regulating smartphone abilities differ between
adolescents and emerging adults?” The results suggest that both age groups can neither
regulate nor not-regulate their smartphone behaviour. Adolescents and emerging adults indicate to having no problems when they cannot use their smartphone. But when asked whether they can reduce their smartphone use, they indicate having problems with this. Thus creating a contradiction on their self-regulating behaviour.
Finally, the lifecycle of smartphone usage has been examined. Here, the habitual- and
normative smartphone behaviour was analysed next to the possible saturation experienced.
Research question three first studied “To what extent do adolescent and emerging adults
differ in their habitual smartphone behaviour?” Results show that both adolescents and
emerging adults neither agree nor disagree using their smartphone out of habit. Indicating that adolescents and emerging adults may not always be aware of their automatic smartphone behaviour and which situational cues trigger their smartphone usage. Results did indicate that there is a significant difference between emerging adult boys and girls. Emerging adult girls are more willing to suggest that they use their smartphone out of habit compared to boys.
However, this difference is limited. Furthermore, research question four “To what extent do
adolescent and emerging adults, who have self-control over their smartphone, show less habitual smartphone behaviour?”, suggest that adolescents and emerging adults with greater
self-regulating abilities will have less habitual behaviour. However, analyses show that these two concepts do not correlate with each other.
Secondly, research question five studied
“To what extent does normative smartphone
behaviour differ between adolescents and emerging adults?” There are three concepts that
were analysed in normative smartphone behaviour namely, sending messages, social
gatherings, and normative behaviour of peers. Results show that adolescents and emerging
adults somewhat disagree that messages should be answered immediately. Emerging adults somewhat agree that smartphones should not be used during social gatherings, while adolescents neither agree nor disagree on this point. However, when analysing gender
differences in each group, a significant difference is found between adolescent boys and girls and their smartphone norms during social gatherings. Girls somewhat agree that smartphones should not be used, whereas boys are neutral on this point. When asked whether their peers think messages should be answered immediately, both adolescents and emerging adults neither agree or disagree their peers have these norms. It is possible to state that there is no significant difference in smartphone norms between adolescents and emerging adults. There is, however, a significant difference between genders. Nevertheless, this difference has only been found between adolescents.
Thirdly, research question six studied “To what extent do emerging adults experience
saturation compared to adolescents?” Both adolescents and emerging adults somewhat
disagree to experience saturation. Indicating that there is no difference in saturation levels between the two age groups and respondents do not indicate using their smartphones less often. Nonetheless, every increase in saturation experienced will decrease the time
