The present investigated the role of personal factors, usage types on smartphone habits, and addiction. In addition, the effect of smartphone habits on smartphone addiction was investigated. The study used a sample of the Dutch population. It can be concluded that some personal factors and the type of usage affect smartphone habits and smartphone addiction. The results show that some people are at a higher risk to become smartphone addicts than others. Smartphone addiction and smartphone habits are complex issues. There are some factors that only affect habits or addiction.
The model consist two usage types: Process usage and Social usage.
Process usage of the smartphone is the biggest determinant of smartphone habits and addiction. Therefore, when people use their smartphones intensively for process usage purposes, they are at a higher risk to develop smartphone habits and a smartphone addiction. Process usage can lead to addiction because of the pleasurable experiences that function as a reward. Rewards can make people feel better and are responsible for small dopamine releases in the brain. Rewards re-enforce actions, making these actions likely to reoccur. Addiction can develop when people keep seeking for this pleasure and do not have control over their behavior. This finding confirms the results of prior research on process usage and addiction. state that internet addicts tend to more extensively use the internet for process purposes. An explanation for this finding is that process-oriented usage is focused on rewards; therefore, gambling, gaming, and even social media are so addictive because of their reward aspects, which include winning, unlocking new features, or receiving new notifications. Smartphones have numerous applications focused on pleasure, escaping the reality and those features can be accessed 24/7.
There is also an indirect effect of process usage on smartphone addiction through smartphone habit. This effect enforces the relation between process usage and addiction. Process usage can cause an addiction directly and, thus, also indirectly. Therefore, process usage activities on smartphones are typical activities that entail the process of developing smartphone addiction, where the rewarding aspect is responsible for the repeating acts that lead to uncontrollable behavior. For example, when checking your Facebook account for new notifications or newsfeeds, this new notification or newsfeed act as a reward. Thus, checking will reoccur because of the reward and it can develop into an addiction that can no longer be controlled.
Social usage of the smartphone has a direct effect on smartphone habits but does not directly affect smartphone addiction. So, people who extensively use their smartphones for social purposes create smartphone habits faster; in an indirect way, this could lead to smartphone addiction. This finding to some extent contradicts past research on media addiction and social usage gratifications., internet addicts used the internet extensively for social purposes. In a more recent study by Lopez-Fernandez, Honrubia-Serrano, Freixa-Blancart, and Wilson , smartphone addicts were found to spend most time for social purposes. Past research conclude that media addicts spend most time on social applications and are dependent on those applications because they isolate themselves (Lopez-Fernandez et. al). Thus, prior research claims that social usage have a direct effect on smartphone addiction. An explanation for the conflicting findings could be that a smartphone is a device designed for social and interaction purposes. Anno 2016, there are many social applications available used by the majority of people for communication to strengthen their business and for both online and offline private relationships. Most people declare that they use social media to maintain their offline social networks (Salehan & Negahban,). Thus, this does not immediately mean a stronger focus or dependency on only digital interaction. Besides, the indirect effect still supports the findings of prior research where social usage was found to have an effect on smartphone addiction. So developing smartphone addiction can be a process. It could be that social usage smartphone habits can make a person less active in face-to-face communication and increase social stress. Therefore, the likelihood to get independent on digital communication increases . Note that this contrary finding must be carefully handled. The nature of the items on social usage is based on general social gratifications and is not specified into online or offline social gratifications.
Besides usage types, the effect of personal factors on habits and addiction was investigated. The model consists of three personality factors: Emotional Intelligence, Social Stress, and Self-Regulation. Emotional intelligence has no effect on smartphone habits or smartphone addiction. This contradicts prior research on Emotional Intelligence and (internet) addiction (Engelberg & Sjoberg; Kun and Demotrovics,). Past research showed that a worse score on EI was negatively related to mental and physical well-being of a person (Engelberg & Sjoberg, 2004). In internet addiction literature, EI was negatively related to internet addiction. By contrast, no relation between EI and smartphone addiction was found in the present study. To our knowledge, this is the first study that investigated smartphone addiction and EI, as there are only seven studies on behavioral addiction and EI, which makes this phenomenon relatively new, especially in the domain of digital addiction (Kun & Demotrovics,). An explanation of the finding is that EI is not completely responsible for the choice that people make how to communicate. It is the stress that makes people uncomfortable in social situations and how introvert one is. Introvert people are comfortable with lower level of social interaction than extraverts (Matthews, Roberts & Zeidner, ; Young,). To conclude, it could be that emotional intelligence has an influence on addiction but in a rather indirect way, as compared to other factors, such as stress and personality.
Another explanation for the inconsistent finding is the method used. Emotional Intelligence is the skill to recognize emotions of self and others; therefore, it might not be correctly assessed with a self-report method because of the inappropriate self-perception or providing socially-desirable answers (Matthews, Roberts, & Zeidner,).
Social stress is the most important personal determinant for smartphone addiction; however, it does not affect smartphone habits. When people have high levels of social stress, they are more likely to develop a smartphone addiction. This is in line with past research on (internet) addiction. A high level of social stress creates anxiety to be in the spotlight or interact with people in real life. Thus, people tend to escape social interactions in real life and focus more on online or more anonymous communication, such as communication via the internet or a smartphone (Whang, Lee, & Chang,). While it is clear that social stress contributes to the development of an addiction, it is unclear how and why. There could be some explanations, however. A smartphone in particular can function as a safe environment where people do not have to communicate, socialize, or present themselves in real life with direct interaction (Jin & Park,). At the same time, it is also possible that people in an addiction use the smartphone to an excessive extent to escape from stress: smartphones have many applications and functions that are rewarding and can help relieve stress and escape from the reality (Haverlag, 2016; Park & Lee,).
Research on self-regulation and smartphone addiction is relatively new. In the present study, self-regulation does affect smartphone addiction. However, self-regulation does not affect smartphone habits. So, while failure of self-regulation — a low score on self-regulation — causes a higher risk to get addicted to a smartphone, it does not contribute to habit forming. This finding contradicts a prior study La Rose and Eastin. They state that failure of self-regulation could lead to more media habits and can develop into media addiction. Failure of self-regulation could lead to more media usage than desired and lead to reoccurring of self-regulation failure. This causes a negative spiral which leads to more and more exposure to media. This explains that habits can turn into an addiction. Metcalfe and Mischel’s study can support this research finding. These authors call deficient self-regulation ‘a hot state of mind’, which is controlled by emotions and is an automatic process steered by impulses. However, they also claim that habits are still to some extent regulated by personal and social norms, so habits are not equivalent to total failure of self-regulation. A possible explanation that confirms the finding of the relation between self-regulation and addiction can be found in an overview of self-regulation failure (Baumeister & Heatherton,). According to Baumeister and Heatherton, failure of self-regulation is loss of (self-) control and behavior that is steered by emotions. Addiction is losing self-control, so that people with an addiction are out of control of their behavior. This is not the case when people develop habits. Habits are automatic behavior rituals, but without a total loss of self-control and, with habitual behavior, there is no complete loss of self-regulation (Metcalfe & Mischel, ).
Alongside with personal factors and type of usage, two demographic characteristics were investigated, namely, gender and age. The most significant results were on age, between older people (over 35 years old) and younger people (younger than 35 years old). Age has a significant effect on social stress, self-regulation, process usage, social usage, smartphone habits, and smartphone addiction. The significant differences in the results suggest the following. Older people have less social stress compared to younger people. Older people are better in self-regulation than younger people. Older people spend less time on the smartphone for process usages than younger people. Older people spend less time on the smartphone for social usages than younger people. Older people are less likely to develop smartphone addiction than younger people. Indirectly, the effect of age also suggests that, if older people develop a smartphone addiction, it is more likely to occur through smartphone habits.
The main conclusion that can be made from these findings is that, in general, older people have a lower risk to become smartphone addicts than younger people. The findings give a new insight into smartphone addiction and the important role of age. Above all, the results give a clue to the understanding of how differently people develop and use smartphones across different generations. Younger people use their smartphones more intensively in general and more for process and social usage than older people. Past research on internet addiction and age is relatively scarce. Most research is done with young (adolescents) samples (Weinstein & Lejoyeux,). Therefore, reflecting on past research on smartphone addiction and age is difficult. It could be that the environment plays a key role. Over the years, we learn differently and have different technologies at our disposal. Jones, Jo, & Martin, state that the environment we live in has a important influence on our personality. Therefore, differences between generations could occur. This conclusion can be made because the younger generation of today — the Millenials — is more into digital communication than elderly. When people from this generation feel lonely or need belongingness, they will earlier use digital devices such as computers and smartphones (Pearson, Carmon, Tobola, & Fowler, 2010). Thereby, this generation does rely on digital communication for social interaction, learning, and in cases when they need a solution. In addition, they have more problems with causal communication (Kubiatko, ). In the research on the on Millenials, Cabral (2010) found that Millenials were heavy users of social media and some that quit had the same symptoms as drugs addicts in rehab.
Differences in personal factors (social stress and self-regulation) between age groups were also detected. Older people have less social stress and are better in self-regulation. Generation difference could play a role in the difference between personal factors. Millenials are grown up with an overload of digital innovations. New communication technologies influence our fear for communicating offline and present ourselves in real life. This is supported by Kabiatko who states that Millennials have more social anxiety. Also, prior research contends that younger people are more prone to react on impulses than older people. Younger people are used to immediate rewards and feedback (Strauss & Howe,). An explanation could therefore be that older people are more often in a cool state of mind compared to younger people; so, they are less likely to react on impulses (Metcalfe & Mischel, ). Also, self-regulation can be learned and needs motivation to pursue and succeed in obtaining certain goals. It could be that older people are more settled and have different interests and motivational goals (Diehl, Siemegon, & Schwarzer,). All these factors could lead to more self-control and self-regulation. In combination with the lower social stress level, it is possible that the degree of self-control and performance in offline communication is higher for older people than younger people.
The difference in personal factors also has an indirect effect on smartphone habit and smartphone addiction. In favor of older people, due to their personal factors, older people are less likely to create smartphone habits and smartphone addiction. If they develop an addiction, this happens through smartphone habits, as older people are less prone to impulsive behavior and are less expectant of immediate rewards. It could be that older people first develop habits and addiction through operant conditioning.
Beyond age, there are also significant gender differences. Gender has a significant effect on social stress and social usage of smartphones. The significant differences obtained in the results reflect the following: Men experience less social stress than women. Men use their smartphones less for social gratifications than women. Due to the significant effects, there is also an indirect effect of gender on smartphone habits and smartphone addiction. This proves that personal factors and type of usage are important factors that influence these phenomena.
The main conclusion of these findings is that gender has no direct effect on smartphone habits and smartphone addiction. This means that the risk to become a smartphone addict is not really dependent on gender. However, due to the differences in social usage and social anxiety, women are slightly more prone to get addicted. The detected differences in personal factors and usage could explain why and how the smartphone is being used by males and females. The findings support past research on the topic. According to Lee, Chang, Lin, and Cheng (2016), males are more task-oriented, while females are more socially oriented. This means that, when compared to men, women use their smartphones more to maintain their social relationships. Women have more conversations than men and gossip more on the phone than men do (Jenaro, Gomez-Vela, Gonzalez-Gil, & Caballo,). Furthermore, women have a stronger relationship with their smartphones. Jenaro et al. also state that females have more social anxiety related to speaking in public, speaking to strangers, speaking in groups, and presenting themselves. To reduce social anxiety, they use their smartphones more for social purposes. Therefore, they are more prone to develop an addiction.
In sum, this research explored and contributed to the smartphone addiction literature. First, our results provide an insight on who is likely to be a smartphone addict and how smartphone addiction develops. In our study, 1.3% of the sample was addicted to their smartphone. This addiction can be developed both directly and indirectly (i.e. via smartphone habits). But who is the smartphone addict? According to previous addiction studies, young introvert men are at a high risk of developing internet and game addiction. This research partly supports past research but states that gender is not a determinant of smartphone addiction. Overall, our results suggest that the smartphone addict can be described as (1) a young person, younger than the average age of 35; (2) a person who has a social stress higher than average; (3) a person who has a below average self-regulation power and (4) uses the smartphone more extensively for process gratifications than others do on average. Finally, our results show that addiction can be developed through habits or directly, this will depends on each individual person.
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