Using a smartphone while walking: The cost of smartphone-addiction proneness
Gabrielle Naïmé MourraSylvain SénécalMarc FrédetteFranco LeporéJocelyn FaubertFrançois BellavanceAnn‐Frances CameronÉlise Labonté-LeMoynePierre‐Majorique Léger
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Abstract:
Distracted walking is an ever-increasing problem. Studies have already shown that using a smartphone while walking impairs attention and increases the risk of accidents. This study seeks to determine if smartphone-addiction proneness magnifies the risks of using a smartphone while walking. In an experimental design, participants, while walking on a treadmill and engaged in a smartphone task, were required to switch tasks by responding to an external stimulus, i.e., determining the direction of movement of a point-light walker. Participants were chosen to cover a range of smartphone-addiction proneness. Four smartphone-use conditions were simulated: a control condition with no smartphone-use, an individual conversation condition, a gaming condition, and a group conversation condition. Our results show that using a smartphone while walking decreases accuracy and increases the number of missed stimuli. Moreover, participants with higher smartphone-addiction proneness scores were also prone to missing more stimuli, and this effect was found regardless of experimental condition. The effect of the smartphone task on accuracy and the number of missed stimuli was mediated by the emotional arousal caused by the smartphone task. Smartphone-addiction proneness was positively correlated with a declared frequency of smartphone use while walking. Furthermore, of all the smartphone tasks, the gaming condition was found to be the most distracting.Keywords:
Smartphone application
Smartphone addiction
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There has been a growing literature that has utilized logged behavior from smartphones to study the impacts of technology use on individuals. One of these proposed impacts has been that people become addicted to their smartphones. Measurements of smartphone addiction do not appear to strongly correlate with actual behavior logged from smartphones. Instead, smartphone addiction may be better explained by distress rather than disordered behavior, but this has not been adequately tested. This study examined the relative contributions of self-reported and actual smartphone behavior alongside key mental health and individual differences in a pre-registered, two-wave study with a two-week re-test. 511 smartphone users (391 at Time 2) completed measures of smartphone usage, attitudes towards smartphone usage, smartphone addiction, other behavioral addictions, and individual differences. The results suggest smartphone addiction is principally driven by perceived rather than actual usage, especially where these are discordant. Self-reported smartphone usage, other behavioral addictions, and the impulsivity facet of negative urgency are more predictive of smartphone addiction than logged behavior. These results suggest that volume of smartphone usage is insufficient in of itself to explain problematic smartphone behavior and questions the criterion validity of smartphone addiction measurements.
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최근 스마트폰 사용자들이 급격히 증가함에 따라 다양한 사회적 문제점들이 발생되고 있다. 대표적으로, 과도한 스마트폰의 사용과 잘못된 이용습관은 '스마트폰 중독(smartphone addiction)'과 '스마트폰 질병(smartphone disease)'과 같은 새로운 사회적 문제점들을 야기시키고 있다. 본 연구에서는 이러한 문제들을 사전에 예방하기 위해 스마트폰 사용자의 패턴을 방향센서를 이용해서 수집하고 분석해서 스마트폰 중독 및 질병을 예방하는 시스템을 제안한다. 제안된 시스템은 사용자의 스마트폰 사용형태와 사용시간을 실시간으로 분석하여 위험수준에 도달하였을 경우, 사용자에게 이를 알려 줌으로써 사용자 자신이 사전에 위험을 인지할 수 있도록 하며, 자신의 의지로 스마트폰 사용을 절제하도록 하여 스마트폰 중독 및 질병을 사전에 예방할 수 있도록 제안한다. In recent years, in accordance with the rapidly increasing number of smartphone users, various social problems have started to occur. Examples of these problems are the overuse of smartphones and bad usage habits of smartphone users that can cause new social problems such as smartphone addiction and other smartphone related diseases. With the aim of preventing these social problems, this paper proposes a new smartphone addiction and disease prevention system. This system was developed by collecting and analyzing smartphone usage patterns. This proposed system analyzes the usage patterns and working hours of smartphone users in real time. If the detected smartphone usage patterns reach a dangerous level, the system will send warning messages to the user. This will enable users to recognize the unhealthy situation in advance by themselves. In addition, this solution could possibly prevent smartphone addiction and other smartphone related illness by preventing overuse and encouraging abstinence from using smartphones to the extent that it becomes harmful to the user.
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The number of smartphone users throughout the world is increasing day by day. Even the age of smartphone access, too, is decreasing with time. Today, smartphone addiction is the most important concern of parents and caretakers of teenagers. The increasing time spent by teenagers on smartphone raises the concern why they spend so much time on it. The present research tries to explore gender differences in smartphone usage pattern of adolescents and therefore, tries to explore possible reasons for both genders for increasing smartphone addiction. The present study was conducted on a sample of 300 adolescents and findings suggest that females and males have significantly different pattern of smartphone usage. The present study also tries to explore causes of problematic smartphone usage among females (as they spend significantly more amount of time on smartphones than males) and possible solutions for the same.
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Smartphone addiction
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Measurements of smartphone addiction weakly correlate with actual behaviour logged from smartphones. Instead, smartphone addiction may probe distress rather than disordered behaviour, but this has not been adequately tested. This study examined the relative contributions of self-reported and actual smartphone behaviour alongside key mental health and individual differences in a pre-registered, two-wave study with a two week re-test. 511 smartphone users (391 at Time 2) completed measures of smartphone usage, attitudes towards smartphone usage, smartphone and other behavioural addictions, and individual differences. Smartphone addiction is principally driven by perceived rather than actual usage, especially where these are discordant. Self-reported smartphone usage, other behavioural addictions, and the impulsive facet of negative urgency are more predictive of smartphone addiction than logged behaviour. These results fail to support the idea that volume of smartphone usage is a sufficient criterion for an addictive behaviour and questions the validity of smartphone addiction measurements.
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High dependence on smartphones can lead to unending, problematic, and addictive usage besides psychological impairments. Conventional methods of smartphone addiction diagnosis include smartphone addiction scales comprising a large number of questions, responses to which are subject to biasness. Smartphone applications are capable of tracking phone usage with precise and objective measures replacing the cumbersome task of filling long questionnaires. This study employs a specialized Android application to gather real-time data on smartphone usage and attempts to identify an optimal question set from commonly used smartphone addiction scales using soft computing. Four smartphone addiction scales have been identified with 43 distinct questions. A two-stage filter-wrapper feature selection model is used for implementing Information Gain filter method and Particle Swarm Optimization wrapper method for selecting an optimal set of questions contributing the most for the assessment of addiction. This optimal question set with real-time smartphone usage features is used to train the Logistic Regression model for prediction of smartphone addiction. The proposed methodology gives a performance accuracy of 98.61% and F1-score of 0.986. This study identifies an optimal question set comprising seven questions, which are the shortest among all existing smartphone addiction questionnaires and even shorter than most commonly used Smartphone Addiction Scale-Short Version.
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Soft Computing
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This paper delves into the intricate mechanisms underlying smartphone addiction, meticulously examining its multifaceted impacts on adolescents. Specifically, it discusses three pivotal aspects: the detrimental consequences smartphones inflict upon adolescent development, the ongoing discourse surrounding smartphone addiction, and the profound insights garnered from this debate. Furthermore, the paper offers pragmatic recommendations aimed at guiding adolescents towards responsible smartphone usage.
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Usage Prediction and Effectiveness Verification of App Restriction Function for Smartphone Addiction
In recent years, there has been a growing problem of smartphone addiction. As the excessive use of smartphones has negatively impacted our daily lives, many apps for reducing smartphone addiction have been developed around the world. In this study, we focus on the app restriction function, which is one of the key features of digital medicines for smartphone addiction, and analyze the usage of the function and verify its effectiveness. The results showed significant differences in both psychological and behavioral aspects between those who used the app restriction function and those who did not. Specifically, we found that the app restriction function was more likely to be used by those who were more aware of their smartphone addiction. We also found that the app restriction function was effective in lessening smartphone usage time, especially when the smartphone addiction is relatively moderate.
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