Problematic smartphone use: The role of reward processing, depressive symptoms and self-control
Introduction
Smartphones have become a ubiquitous element of daily life for many individuals, allowing us to stay connected to friends and family, conduct business, and engage in leisure activities. Eight-one percent of Americans reported owning one or more devices in 2018 (Pew Research Center Infographic, 2019), and 46% of users reported that they could not live without their smartphone (Ning et al., 2018). When defined as the degree that smartphone use is related to a disturbance of daily life, anticipation of use, withdrawal, overuse and tolerance (Kwon et al., 2013), the incidence rate of problematic smartphone use is fairly high (M = 19%, range = 3%-65%; Gutiérrez et al., 2016), and similar to other forms of pathological technology use (e.g., Internet gaming, Gentile et al., 2017; Internet, Cask et al., 2012). The current study builds upon extant literature related to Internet gaming disorder (Duvan et al., 2014, Raiha et al., 2020) and substance abuse (Joyner et al., 2019), which reveals an attenuation of neural activity related to reward processing, by exploring the association between problematic smartphone use and reward processing, and by considering the unique and shared associations between problematic smartphone use, reward processing, depressive symptoms and self-control.
Problematic smartphone use is consistently associated with poor mental health outcomes and reduced self-control (Guitierrez et al., 2016; Kim et al., 2018, Kliestik et al., 2020). Mental health outcomes include increased depression, anxiety, stress, and suicidal ideation (Kim et al., 2017), in addition to increases in negative affect and decreases in positive affect (Horwood & Anglim, 2019). A number of studies reveal an association between self-control and problematic smartphone use. Kim et al. (2016) found that individual differences in both self-control and impulsivity were unique predictors of problematic smartphone use. Consistent with this finding, individuals with attention deficit hyperactivity disorder (ADHD) experience higher levels of problematic smartphone use (Kim, 2018).
The problematic use of technology related to video games, social media, and the Internet is consistently associated with poor decision making related to a disruption of reward processing in behavioral studies. For instance, problematic use of first-person shooter video games is related to an increase in disadvantageous choices in the Iowa Gambling Task (IGT) and a decrease in learning from positive and negative feedback in the Probabilistic Selection Task (Bailey et al., 2013). The problematic use of social media is also related to poor decision making in the IGT (Meshi et al., 2019), reflecting a tendency to continue to choose from disadvantageous decks as the task progresses. Likewise, individuals reporting pathological Internet use demonstrate poor decision making in a gambling task similar to the IGT (Sun et al., 2009). These outcomes are often attributed to a failure to learn from or use prior negative feedback to guide decision making supported by the medial frontal cortex (Tranel, 2002). In the context of the current study, some evidence reveals negative correlations between problematic smartphone use and gray matter volume and resting state hemodynamic activity in the anterior cingulate cortex that is part of the reward system (Horvath et al., 2020). Together, such findings lead to the prediction that problematic smartphone use will be associated with a reduction in neural activity elicited during reward processing in addition to measures of brain volume and resting state activity revealed in previous research (Horvath et al., 2020).
Event-related brain potentials (ERPs) have been used extensively to explore the neural correlates of reward processing in gambling tasks and other paradigms (Walsh & Anderson, 2012). In the current study, we focus on the reward positivity (RewP)/feedback negativity (FN) and the frontal P3, which are related to reward processing and maximal in amplitude over the frontal-central region of the scalp (Proudfit, 2015, West et al., 2014). The RewP represents greater positivity for gains than for losses between 200 and 350 ms after the onset of feedback indicating the outcome of a decision (Proudfit, 2015). In contrast, the frontal P3 peaks around 400 ms after the onset of feedback and represents greater positivity for losses than for gains (West et al., 2014).
The RewP and frontal P3 are both sensitive to poor mental health outcomes and self-control. The amplitude of the RewP is reduced in individuals with substance abuse disorder (SUD, Joyner et al., 2019) and Internet gaming disorder (Raiha et al., 2020), revealing an effect of pathology on ERPs related to reward processing. The RewP is also attenuated in depressed individuals (Foti & Hajcak, 2009; Novak et al., 2016), an effect that can be observed several years before the emergence of symptoms in individuals at risk for the development of depression (Bress et al., 2013). The amplitude of the frontal P3 is reduced in individuals with low self-control and in those with high levels of action video game play. For self-control, Ba et al., (2016) reported that the amplitude of the frontal P3 for losses (i.e., balloon explosions in the BART) was reduced in risky drivers relative to safe drivers. Related to problematic technology use, the amplitude of the frontal P3 is reduced in high action gamers -- some of whom may experience problematic gaming given the large correlation between hours of play and pathology (Bailey et al., 2013) – relative to non-gamers (Bailey & West, 2017). The similar effect of problematic substance and technology use, depression, and self-control on the RewP and frontal P3 led us to wonder whether a disruption of reward processing might represent a common cause of the associations between problematic smartphone use, depressive symptoms and self-control.
The current study builds upon the extant literature by establishing whether problematic smartphone use is associated with an attenuation of neural activity related to reward processing. The study also sought to determine whether reward processing, depressive symptoms and self-control represent common or unique predictors of problematic smartphone use. In contrast to prior research (Horvath et al., 2020), the study included individuals with smartphone pathology scores reflecting low, moderate, and high levels of problematic use. The modified doors task provided measures of ERP activity related to feedback processing. An advantage of the task is that ERPs are relatively independent of the effect of learning, in contrast to a task like the IGT wherein feedback processing and learning are confounded (Tranel, 2002). We predicted there would be a negative correlation between problematic smartphone use and the ERP correlates of reward processing (i.e., RewP, frontal P3). Additionally, we predicted that the amplitude of the parietal P3 – a neural correlate of decision making and attentional allocation (Kok, 2001) – would not be correlated with problematic smartphone use. Considering the parietal P3 allowed us to determine whether any association between problematic smartphone use and the RewP/frontal P3 was selective to reward processing or instead reflects a more general effect on attention and information processing. We also sought to determine whether reward processing, depressive symptoms, and self-control are uniquely related to problematic smartphone use, or instead whether these associations reflect a common underlying factor.
Section snippets
Participants
Ninety-nine individuals were recruited from the Department of Psychology and Neuroscience participant pool and the university student population to participate in the study. For the participant pool, students registered in introductory and intermediate level psychology courses logged into an online system that advertised studies and selected a time to participate. To increase the representation of individuals with high levels of problematic smartphone use, the SAS-SV was sent to all students at
ERP components
The ERP components were analyzed with a set of 2 (outcome: win or loss) × 2 (agent: person or computer) ANOVAs.
3.1.1. For the RewP, the main effects of agent, F(1,93) = 166.42, p < .001, η2p = .64, and outcome, F(1,93) = 25.59, p < .001, η2p = .216, were significant (Table 1, Fig. 2). The interaction was also significant, F(1,93) = 8.44, p = .005, η2p = .083, and a simple main effects test revealed that the effect of outcome was significant for the person select trials, F(1,93) = 24.26,
Reward processing and pathological smartphone use
Our analyses revealed that problematic smartphone use was negatively related to ERPs associated with both gains (RewP) and losses (frontal P3) in the person, but not computer, choice condition. These findings may indicate that problematic smartphone use is associated with a disruption of positive and negative reward prediction errors related to feedback processing (Hassell et al., 2019). The lack of significant correlations between problematic smartphone use and the RewP/frontal P3 for computer
Funding
Funding for the study was provided by the Elizabeth P. Allen Professorship of DePauw University. The university had no role in the study design, data collection or interpretation, writing the manuscript, or the decision to submit the paper for publication.
The authors thank the participants of the NeuroIS Retreat 2020 for helpful comments in developing the project, and Kuzivakwashe Chinyanya and Kate Cowger for assistance with data collection and processing.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
References (39)
- et al.
Did I do that? The association between action video gaming experience and feedback processing in a gambling task
Computers in Human Behavior
(2017) - et al.
EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent components analysis
Journal of Neuroscience Methods
(2004) - et al.
Depression and reduced sensitivity to non-rewards versus rewards: Evidence from event-related potentials
Biological Psychology
(2009) - et al.
Structural and functional correlates of smartphone addiction
Addictive Behaviors
(2020) - et al.
Problematic smartphone usage and subjective and psychological well-being
Computers in Human Behavior
(2019) Psychological issues and problematic use of smartphone: ADHD’s moderating role in the association among loneliness, need for social assurance, need for immediate connection, and problematic use of smartphone
Computer in Human Behavior
(2018)The assessment and analysis of handedness: The Edinburgh inventory
Neuropsychologia
(1971)- et al.
Validation and psychometric properties of a short version of Young’s Internet Addiction Test
Computers in Human Behavior
(2013) - et al.
Learning from experience: Event-related potential correlates of reward processing, neural adaptation, and behavioral choice
Neuroscience and Biobehavioral Reviews
(2012) - et al.
Beyond the FN: A spatio-temporal analysis of the neural correlates of feedback processing in a virtual Blackjack game
Brain and Cognition
(2014)
Risk-taking on the road and in the mind: Behavioural and neural patterns of decision making between risky and safe drivers
Ergonomics
What would my avatar do? Gaming, pathology, and risky decision making
Frontiers in Psychology
Decision making, impulse control and loss of willpower to resist drugs: A neurocognitive perspective
Nature Neuroscience
Blunted neural response to rewards prospectively predicts depression in adolescent girls
Psychophysiology
Altered reward processing in pathological computer gamers - ERP results from a semi-natural gaming-design
Brain and Behavior
Center for epidemiologic studies depression scale: Review and revision (CESD and CESD-R)
Internet gaming disorder in children and adolescents
Pediatrics
Cell-phone addiction: A review
Frontiers in Psychiatry
The importance of agency in human reward processing
Cognitive, Affective, & Behavioral Neuroscience
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