“Impulsive actions led to trouble, and trouble could have unpleasant consequences.” – Stieg Larsson
Smartphone usage has increased significantly in recent years because smartphones can be used for calls, texting, social media, and daily task-oriented activities. The average time of mobile devices use at global level in 2019 is 3 hours and 40 minutes. Studies conducted almost a decade ago showed that mobile phones were having a positive impact on users, such as improvement of quality of life, access to educational tools and content, and disease treatment (m-health). However, studies published recently have focused on the possible negative effects of the use of smartphones, specifically among heavy users of smartphones after work hours and in academic settings, due to decreased academic performance associated with sleep issues, lack of concentration, stress and anxiety. This study aims to find out whether heavy smartphone users show a tendency to devalue the consequences of their behavior over the long term by examining the relationship between their smartphone usage time and multiple categories of apps and data from consumer choice tasks as a measure of self-control as well as data from established screening tests for problematic smartphone use.
II. Theoritical Background
There are three relevant literature trends identified for this study. The first is a conceptualization and theoretical framework applied to the study of smartphone addiction. The smartphone addiction concept refers to a lack of ability to control the desire to use the mobile phone (Walsh et al., 2010). The general strain theory proposes that addictive behavior is caused by negative consequences sourced from high-stress levels (Agnew, 2001), the theory of self-regulation states that the lack of self-regulation in the use of smartphones is due to low self-control (Gökçearslan et al., 2016), and the Compensatory Internet Use Theory (CIUT) which states that addictive behaviors are generated by different motivations, among which the most important is stress (Kardefelt-Winther, 2014).
The second is the behavioural economics approach to the study of excessive consumption. According to the behavioral economics approach, addiction is a pattern of choosing one behavior over others available at the time in a specific context, which is influenced by the rewards and costs associated with each behavioral alternative (Ross et al., 2008). Consumers face multiple-choice situations involving various rewards with varying discounting intervals every day. In their most basic form, these situations include selecting between an option that provides a small but sooner reward (SSR) and another that provides a larger but later reward (LLR) (Arfer and Luhmann, 2015).
The third is problematic smartphone use. Problematic smartphone use (PSU) is defined as the inability to regulate the use of a smartphone, which generates negative consequences in the user’s daily life (Billieux, 2012). The study’s main objective is to establish if there are differences concerning the temporal discounting (impulsiveness) in a situation of choice for users with different levels of use or dependence on a smartphone or mobile apps. Therefore, the hypothesis :
H1. As the usage time of smartphones and apps increases, users will present greater impulsiveness in the intertemporal choice task.
H2. As the usage time of smartphones and apps increases, dependence on smartphones will become greater.
H3. As the dependence on smartphones becomes greater, the impulsiveness in the choice situation will be greater.
III. Research Methodology
This study adopted a pragmatic, deductive and quantitative approach, applying a cross-sectional survey design and a longitudinal measurement based on real use data for both smartphones and apps. A cross-sectional survey was conducted to measure smartphone dependence and followed by an intertemporal choice task to establish participants’ level of self-control and impulsiveness. Then, a behavioural record of longitudinal nature was applied to obtain objective measurements of usage time of the device and apps.
The study was conducted in Bogota, Colombia and the sample consisted of twenty students from a private university, Politecnico Grancolombiano.
3.3.1. Intertemporal choice task
The experiment was presented in E-Prime 3.0 by using Spanish. The design of the experimental conditions used fictitious rewards. In the experimental trials, the presentation of the alternatives was counterbalanced between the left and the right of the screen and the following variables were manipulated: waiting time for small-sooner (SS) options (today, 3 and 6 months), waiting time for larger-later (LL) options (6, 9 or 12 months). The reward values for the SS options were 5,000 pesos, 10,000 pesos, 15,000 pesos, 20,000 pesos, 25,000 pesos, 30,000 pesos, 35,000 pesos, 40,000 pesos, 45,000 pesos, and the reward value for the LL options was 50,000 pesos. Every amount from 5,000 to 45,000 pesos was repeated seven times, and the 50,000 pesos value was repeated 63 times.
3.3.2. Problematic smartphone use
The Spanish version of the Smartphone Addiction Inventory (SPAI) is used to measure the Problematic Smartphone Use reported by participants. This version showed adequate levels of validity through goodness of fit indices as well as good reliability of the global inventory and each of its corresponding factors: compulsive behaviour, functional impairment, abstinence, and tolerance.
3.3.3. Measurement of smartphone and app usage time
The StayFree® app was applied to measure daily usage time of installed apps and total smartphone usage time to give valid measurements regarding the use of the smartphone.
Participants will be included in the initial session in a computer room, and will be given the Intertemporal Choice Task and the SPAI-S for 30 minutes per participant. When it ended, each person was scheduled for another session in which he or she was assisted with downloading and using the StayFree® app and it was explained how to generate and forward the reports from the app regarding the use of the smartphone via e-mail.
3.5. Statistical analysis
Statistical analyses were conducted with the SPSS 22.0 software to run a logistic regression analysis test.
The study protocol was approved by the institutional research ethics committee at Institucion Universitaria Politecnico Grancolombiano. All of the participants provided a written informed consent voluntarily and were able to view example data in advance.
4.1 Descriptive Statistics
Based on data from 20 participants for 4 weeks, the results obtained:
4.2 Effect of smartphone and app usage time on intertemporal choice
The results described in Table 1 led to identifying the apps with the highest usage time and total smartphone usage time, which were established as predictor variables. The results doesn’t support H1 that, as the usage time of smartphones and apps increases, users will not present greater impulsiveness in the intertemporal choice task.
4.3 Relationship between smartphone and app usage time and perceived dependence on smartphones
Table 3 shows that the dependence on smartphones (SPAI score) was correlated with the smartphone’s total usage time and the usage time of the WhatsApp and Facebook apps using correlation analysis. The results support the hypothesis (H2) that, as the usage time of smartphones increases, perceived dependence increases as well.
4.4 Relationship between perceived dependence on the smartphone and intertemporal choice (impulsiveness)
Linear regression analysis was conducted with perceived dependence on the smartphone (SPAI score) and the average responses given by each participant in the 63 choice conditions. The results support the hypothesis (H3) that, as dependence on smartphones increases, users’ choice impulsiveness increases as well.
5.1. Key findings
The usage time of smartphones or apps was found to have no effect on the users’ intertemporal choice. The first hypothesis cannot be confirmed because even though the results evince a significant effect of the usage time of the Instagram app and age as mediating variables, the R2variables fail to show variance explained by the model when applying logistic regression as an analysis technique. However, a correlation was found between the total usage time of the smartphone and the WhatsApp and Facebook apps and the smartphone dependence level obtained with the SPAI-S score. This leads to the interpretation that smartphone dependence does not rely on the use of any particular app, but that the joint usage of the apps as a whole seems to have an effect on users’ reported dependence. These findings confirm the second hypothesis. Moreover, smartphone dependence had a significant and positive effect on the average of impulsive choice behaviour (SSR). This finding is relevant also because this relationship is established through data obtained in a choice test and opens the possibility to continue exploring the relationship between the use of mobile services and a choice pattern based on the concept of temporal discounting from the perspective of behavioural economics.
5.2. Theoretical implications
The possibility that smartphone usage time could predict participants’ responses in an intertemporal choice task was proposed. Although it was found that the total usage time had a positive and significant effect on dependence of smartphones, it failed to have any effect on intertemporal choice. The overall results provide the possibility to explore the connection between these variables further. Moreover, this study contributes to the literature on the use of smartphones from the perspective of behavioural economics in conjunction with traditional techniques such as screening tests as well as objective measures of use of smartphones and apps, finding a relationship between usage time and dependence on the device and a positive effect of this dependence on the average choice of the impulsive option.
5.3. Limitations and future research
There are some limitations in this study. First, the presentation of an immediate reward (SSR) took place through a fixed sequence, therefore caution must be exercised when comparing these results with those of studies applying a titrating sequence. Second, the sample consisted of college students, thus, future studies could include participants with different age ranges to calculate possible differences in impulsiveness levels concerning usage time of smartphones and apps. Third, although a small-N design perspective was applied, the sample size for future studies should be larger, including participants of different ages and occupations, which would give more depth to the results.
The overall goal of this study was to look into possible links between levels of smartphone and app use and patterns of impulsive choice, which are characterized by a preference for positive but immediate outcomes. Regarding this potential relationship, the time spent using a smartphone or application did not appear to influence the user’s intertemporal choice. Nonetheless, a positive correlation was discovered between the total time of smartphone use and the level of perceived dependence on smartphones. Furthermore, smartphone dependence significantly and positively affects the average impulsive choice behavior.
Reviewed from :
Robayo-Pinzon, O., Foxall, G. R., Montoya-Restrepo, L. A., & Rojas-Berrio, S. (2021). Does excessive use of smartphones and apps make us more impulsive? an approach from behavioural economics. Heliyon, 7(2), e06104. https://doi.org/10.1016/j.heliyon.2021.e06104
Ilustrasi oleh Fadhli Rahman Jamal
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