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True colors: Grayscale setting reduces screen time in college students
Abstract
Excessive smartphone use has been related to numerous negative outcomes including anxiety, depression, sleep deficits, and lower life satisfaction. Though empirical works have made these associations, prior works have not addressed how to make phones less appealing and reduce screen time. One hundred sixty-one undergraduate students participated in a longitudinal study of smartphone use. Seventy-three had their phones changed to grayscale for eight to 10 days to evaluate if the absence of bright and saturated colors reduces screen time and negative affectivity. Participants who had their phones in grayscale spent significantly less time on social media and internet browsing compared to Time 1, though it appears grayscale did not influence video screen time. In addition, total screen time was significantly less for these individuals by an average of 37.90 min each day. The influence of grayscale did not account for improvement in anxiety or depression symptomology as both control and experimental groups improved compared to Time 1. It appears changing to grayscale makes smartphones less gratifying and can assist individuals in controlling their smartphone use. Suggestions and implications for future research are outlined.
... A total of 19 studies in the literature have evaluated the effectiveness of 13 apps in reducing mobile phone use and MMPU (See Multimedia Appendix 4 for more details). These studies used various types of research designs, including randomized controlled trials (5/19, 26%) [32][33][34][35][36], experimental designs (6/19, 32%) [37][38][39][40][41][42], interviews (4/19, 21%) [37,40,43,44], cross-sectional designs (8/19, 34%) [11,38,39,[44][45][46][47][48], longitudinal studies (3/19, 16%) [34,38,42], and observational research-secondary data [49]. Some of the studies (5/19, 26%) used a combination of different designs [11,37,39,40,44]. ...
... The EPHPP guideline consists of 8 criteria: study design, selection bias, dropouts, blinding, intervention integrity (if applicable), data collection, analysis, and confounding. The findings revealed that, of the 19 studies, 1 (5%) was of methodologically strong quality [34], 6 (32%) were of moderate quality [32,33,35,36,39,40], and the remaining 11 (58%) were of weak quality [11,37,38,41,42,[44][45][46][47][48][49]. Meta-analyses of the quantitative data could not be conducted owing to the heterogeneity of the data and the quality of the included studies. ...
... The study findings revealed that 4 (31%) of the 13 apps can effectively reduce mobile phone use. Specifically, Screen Time (iOS) [11,[32][33][34]39,40], Forest and Screen Time [43], and AntiSocial [36] were found to be effective in reducing mobile phone use. Various intervention strategies were also found to be effective in reducing mobile phone use, including the use of grayscale mode [11,32,33,39,40], app limit feature [34]; and mixed interventions [11,36]. ...
Background:
Mobile apps are a popular strategy for reducing mobile phone use and preventing maladaptive mobile phone use (MMPU). Previous research efforts have been made to understand the features of apps that have the potential to reduce mobile phone use and MMPU. However, there has been a lack of a comprehensive examination of the effectiveness of such apps and their features.
Objective:
This paper investigated existing apps designed to reduce mobile phone use and prevent MMPU and examined the evidence of their effectiveness. The research aimed to provide a comprehensive analysis of app features that can reduce mobile phone use and MMPU, while also assessing their effectiveness. In addition, we explored users' perceptions of these apps and the various features the apps offer to understand potential adoption issues and identify opportunities.
Methods:
This study used 3 methods: a review of scientific evidence, content analysis, and sentiment analysis.
Results:
Our study comprehensively examine the common features of 13 apps designed to reduce mobile phone use. We extracted and classified the features into 7 types: self-tracking, social tracking, goal setting, blocking, gamification, simplification, and assessment. The effectiveness of these apps in reducing mobile phone use and MMPU varied from weak to strong. On the basis of content analysis, self-tracking and goal setting were the most frequently used features, whereas gamification and assessment were used the least frequently. The intervention strategies that effectively reduce mobile phone use and MMPU included using grayscale mode, app limit features, and mixed interventions. Overall, users tended to accept these apps, as indicated by sentiment scores ranging from 61 to 86 out of 100.
Conclusions:
This study demonstrates that app-based management has the potential to reduce mobile phone use and MMPU. However, further research is required to evaluate the effectiveness of app-based interventions. Collaborations among researchers, app developers, mobile phone manufacturers, and policy makers could enhance the process of delivering, evaluating, and optimizing apps aimed at reducing mobile phone use and MMPU.
... The devices are designed to capture and hold the person's attention. It is accomplished through the utilization of appealing luminous saturated colors that stimulate the visual attention system (Holte & Ferraro, 2020). In a replication of this study, Holte et al. (2021) found that with greyscale settings, the daily screentime decreased by 21.76 min. ...
... Therefore, there is the assumption, that the smartphone use is less pleasurable, what is minimizing the urge to engage with the device. Previous research has demonstrated that shifting one's smartphone screens to grayscale is an effective way to decrease smartphone use (Holte et al., 2021;Holte & Ferraro, 2020). ...
... It is assumed, that a grayscale setting is less attractive, and therefore the smartphone is less frequently used. This would replicate the results of Holte and Ferraro (2020) and Holte et al. (2021), who discovered that individuals who changed their smartphone to grayscale setting decreased the time on their smartphones. ...
Increasingly, problematic smartphone use behavior (PSU) and excessive consumption are reported. In this study, an experiment was developed to investigate the influence of screen coloration using the grayscale setting on smartphone usage time in repeated measurements. We also investigated how individuals perceived suffering correlates with smartphone usage time and PSU, and whether differences exist by smartphone usage type (social, process, habitual). 240 subjects completed a questionnaire about smartphone usage time, PSU, perceived suffering, and smartphone usage types. Afterward, their smartphones were switched to grayscale setting for at least 24h, and thereafter 92 of these participants completed the second questionnaire. Analyses showed that grayscale setting decreases usage time and that there is a positive correlation between PSU, smartphone usage duration, and perceived suffering. The types of use (process and habitual) influence one's perceived suffering. Thus, it shows that individuals are aware of their PSU and suffer from it. Using grayscale setting is effective in reducing smartphone use time.
... 17,18 We chose grayscale mode as a widely accessible design friction tool. 19 Color perception literature indicates that an absence of bright, saturated colors reduces gratification and salience of eye-catching stimuli. [20][21][22][23][24] We argue that grayscale mode steers individuals toward reducing usage by making the experience less rewarding without active goalsetting, thus it can be considered effortless self-control. ...
... [20][21][22][23][24] We argue that grayscale mode steers individuals toward reducing usage by making the experience less rewarding without active goalsetting, thus it can be considered effortless self-control. 19,25 We argue that both strategies should lead to a usage reduction when compared with self-tracking. a We expected an immediate reduction for the design friction strategy since it makes the mobile experience less gratifying from the beginning. ...
... a We expected an immediate reduction for the design friction strategy since it makes the mobile experience less gratifying from the beginning. [17][18][19] The goal-setting strategy should lead to a gradual reduction, as consumers may find it difficult to reduce usage initially when relying on self-control. Due to habit formation, successful goal achievement on day 1 should facilitate achievement thereafter. ...
Many consumers nowadays wish to reduce their smartphone usage in the hope of improving productivity and well-being. We conducted a pre-registered field experiment (N = 112) over a period of several weeks to test the effectiveness of two widely available digital strategies for screen time reduction. The effectiveness of a design friction intervention (i.e., activating grayscale mode) was compared with a goal-setting intervention (i.e., self-commitment to time limits) and a control condition (i.e., self-monitoring). The design friction intervention led to an immediate, significant reduction of objectively measured screen time compared with the control condition. Conversely, the goal-setting intervention led to a smaller and more gradual screen time reduction. In contrast to the popular belief that reducing screen time has broad benefits, we found no immediate causal effect of reducing usage on subjective well-being and academic performance.
... Evidence is also mixed regarding the effectiveness of behavioural interventions that target phone use to reduce depression. One study found that limiting social networking site use to 10 min per platform per day reduced depression (Hunt et al., 2018); another intervention also reduced screen time but found no such effect (Holte & Ferraro, 2020). Researchers continue to debate the nature and magnitude of the link between smartphone use and specific aspects of well-being (Twenge et al., 2020). ...
... Our intervention focuses on nudges (Thaler & Sunstein, 2021): here, small changes to phone settings or the environment intended to reduce phone use. Changing the smartphone display to greyscale, for example, can reduce screen time, problematic smartphone use, and anxiety (Holte et al., 2021;Holte & Ferraro, 2020). The effectiveness of such nudges can be explained by the Fogg Behaviour Model, which posits that habitual behaviours result from the combination of motivation, ability, and prompts (Fogg, 2019). ...
... Such an intervention could be useful to reach a larger population than those who would be willing to apply any specific strategy. For example, switching the screen to greyscale has several benefits (Holte et al., 2021;Holte & Ferraro, 2020), but this strategy had some of the lowest compliance rates (e.g., 38% in Study 1; Table A1). Further, combining intervention strategies in a more flexible approach could allow for easier recruiting of larger samples and may improve long-term compliance. ...
Problematic smartphone use is rising across the world. We tested an intervention with ten strategies that nudge users to reduce their smartphone use, for example by disabling non-essential notifications and changing their display to greyscale. Participants first completed baseline measures of smartphone use, well-being, and cognition before choosing which intervention strategies to follow for two to six weeks. Study 1 (N = 51) used a pre-post design while Study 2 (N = 70) compared the intervention to a control group who monitored their screen time. Study 1 found reductions in problematic smartphone use, screen time, and depressive symptoms after two weeks. Study 2 found that the intervention reduced problematic smartphone use, lowered screen time, and improved sleep quality compared to the control group. Our brief intervention returned problematic smartphone use scores to normal levels for at least six weeks. These results demonstrate that various strategies can be combined while maintaining feasibility and efficacy.
... Given the multi-dimensional nature of smartphones, it is easy to understand why society as adopted it in great numbers. In particular, 81% of American's owned a smartphone in 2019 (Pew Research Center, 2019) and young adults average over four hours of use each day (Holte & Ferraro, 2020). In other words, it is typical for young adults to spend roughly 25% of their waking hours on their phone. ...
... Thus, after providing a review of existing PSU interventions, the current study will propose and evaluate the efficacy of the grayscale phone display in reducing PSU. Research by Holte and Ferraro (2020) found switching one's phone to grayscale reduced objectively measured screentime. However, since they did not measure PSU, it remains to be seen if this method reduces PSU. ...
... Lastly, given the replicability crisis in psychology (see Pashler & Wagenmakers, 2012), efforts to replicate and extend findings are vital to further understand of how useful the grayscale screen display is at influencing smartphone use and psychopathology. Thus, it is beneficial to assess if the findings of Holte and Ferraro (2020) are replicated in this work and to further extend the findings by including PSU. ...
Problematic smartphone use (PSU) is a topic that is routinely examined in the empirical literature. Given an individual’s inability to control their phone use, PSU is commonly related to a host of negative outcomes including declines in academic and work productivity, sleep difficulties, risky driving and psychopathological concerns. Though PSU may be related to issues in individuals lives, there is currently a paucity of empirical works that evaluate methods to reduce PSU. Prior work has shown switching one’s phone display to grayscale is an efficacious method in reducing phone use. Though, it has not been previously studied if this reduces PSU. This study consisted of 133 college students who came to the lab on two separate visits. After receiving baseline data, 63 participants had their phone’s screen display changed to grayscale and told to not switch it back until after their second visit. Participants who had their phones in grayscale exhibited a significant decrease in PSU, anxiety, and screen time during their second visit. Though it should be noted, no significant changes to depression were found and the decrease in anxiety experienced by grayscale condition participants may not be clinically significant. Aside from these considerations, it appears smartphone use in grayscale is less gratifying, which makes it easier for individuals to regulate their smartphone use. A discussion of study limitations and implications for future research is outlined.
... Other aspects that link the use of new technologies to intrinsic motivation derive precisely from their technological characteristics for example smartphones are engineered to elicit intrinsic motivation among users through hedonic attributes, such as vivid and saturated color schemes [75][76][77], while also engaging the user's attentional system [78,79]. Recent scholarly investigations involving the removal of color displays from smartphones have indicated that such alterations lead to reduced user satisfaction and subsequently result in diminished smartphone utilization [80,81]. Given that the satisfaction users derive from their device is intertwined with its usage, we anticipate this to be a catalyst for phubbing behavior, which is a particular case of use. ...
... This could mean that people who are more motivated by internal factors may have more phubbing behaviors. This finding is consistent with recent scientific evidence showing that a decrease in intrinsic motivation-based features is associated with lower smartphone use [80,81]. The second hypothesis, H2, argues that there is a positive correlation between phubbing and online vigilance, i.e., the tendency to constantly monitor other people's online activity. ...
Phubbing affects an individual’s social life and well-being. It has been found to affect romantic relationships, communication and social skills, and emotional and behavioral problems. Some relationships that phubbing has with, for example, smartphone addiction, Internet addiction, social media addiction, FoMO, and neuroticism are well known and established in the literature. However, phubbing is not exclusively reducible to addiction or personality-driven dynamics. For this reason, this study is aimed at exploring the motivations behind phubbing behavior. Firstly, the research is aimed at confirming the relationships between phubbing and technology-related addictions (e.g., social media addiction and mobile phone addiction) and personality traits (e.g., neuroticism and conscientiousness). In addition, the study is aimed at examining the relationship between phubbing and three potential individual-level factors for possible phubbing modeling: intrinsic motivation, boredom state, and online vigilance. A total of 551 participants took part in the study (mean age = 32 years; SD = 14.15 ). After confirming the relationships that phubbing has with the abovementioned variables, a hierarchical regression model was produced in order to model the phubbing phenomenon as comprehensively as possible. The final model explained approximately 72% of the variance in phubbing. The primary contributors to the explained variance were variables related to the dependent use of new technologies, dimensions of online vigilance, boredom, and intrinsic motivation for using new technologies. Sociodemographic factors and personality traits accounted for a smaller portion of the variance (3.4% and 9.1%, respectively). These findings suggest that the individual-level factors driving phubbing behavior are related to intrinsic motivation, online vigilance, and boredom, rather than sociodemographic factors or personality traits. The study encourages further research to explore and expand upon the range of motivations underlying phubbing behavior, while considering factors related to dysfunctional or addictive technology use.
... While our study was still ongoing, two studies with similar research questions were published (Holte & Ferraro, 2020;Olson et al., 2021). Some of the results of these studies are consistent with the results of our study while others are not. ...
... Some of the results of these studies are consistent with the results of our study while others are not. In the study by Holte and Ferraro (2020), greyscale had a significant effect on usage time, but not on mental health (other variables such as PSU and subjective usage behaviour were not measured). The results of both this previous study and our qualitative analysis showed that participants believed greyscale was effective, suggesting this intervention to be promising. ...
This field experiment aimed to address the issue of problematic smartphone usage (PSU) by examining the effectiveness of two frequently advised techniques to deal with PSU: moving problematic applications to a different page of the phone and changing the phone into greyscale. For one week, 97 student participants used their smartphone under one of the following three conditions: move app, greyscale, or control condition. Compared to the week before the intervention, participants significantly reduced their objective smartphone usage, but their self-reported PSU increased. These effects also emerged in the control group, which might have been due to heightened awareness of the participants of their smartphone usage. A major implication of the study is the need of using multiple outcome measures to understand the complex relationship between perceptions and behaviour. This study could be used as a blueprint for future research examining the effectiveness of interventions in the field of PSU.
... In recent years, the topic of smartphone addiction and its consequences has gained increasing attention. Hence, researchers have been interested in investigating various methods to reduce smartphone screen time, such as using different apps that provide notifications about screen usage (Loid, Täht & Rozgonjuk, 2020) or adjusting the grayscale settings (Holte & Ferraro, 2020;Holte, Giesen & Ferraro, 2023;Wickord & Quaiser-Pohl, 2023). To contribute to this emerging field of study, we investigated the Bonanza Box as a new method to reduce screen time. ...
... While some studies report positive effects of digital detox, others find no or even negative effects (Radtke et al., 2022;Schmuck, 2020). Further approaches focus on, for instance, manipulating the display in grayscale (Holte & Ferraro, 2020), leaving the smartphone out of reach (Ward et al., 2017), or providing a psychological training program (Keller et al., 2021;Kent et al., 2021). ...
Background: Overuse of smartphones can have harmful health effects. Patricularly, overuse of social media apps are related to problematic forms of smartphone use because individuals find it difficult to finish their smartphone session (e.g., on Instagram). Aims: This randomized controlled pilot study aims at examining effects and intervention characteristics of a digital nudge-based intervention aiming to interrupt Instagram usage. Method: A total of 70 Instagram users (47% female; Mage: 31 years) were enrolled and randomly assigned to the intervention (n = 33) or control group (n = 37). Across 14 days, the intervention group received notifications from a pool of 80 messages (e.g., stimulating reflection on smartphone use), whenever Instagram was used for 3 minutes. Self-reported problematic smartphone use as well as time of overall smartphone use and Instagram use were assessed via five weekly online questionnaires. Results: The longitudinal sample comprised 40 participants. Significant reductions in self-reported problematic smartphone use were observed in both groups, but no significant changes were found for the time of smartphone and Instagram use. The intervention had a minor relevance for six participants who received less than 7 notifications across 14 days. For 17 participants, the number of notifications ranged between 12 and 139, with a median duration of closing Instagram after 6:44 minutes (range: 1:06 to 23:47 minutes). Limitations: A small convenience sample was investigated and findings do not generalize to the general population. Conclusion: High interindividual differences were found in how the intervention worked providing insights for future nudge-based interventions.
... These widely used datasets have inspired the development of emotional computing, which is Machine Learning (ML). Study [17] reports that in everyday human interaction, human emotions are primarily expressed through facial expressions (55%) voice (38%) and words (7%) Textual, auditory, and visual signals are generally referred to as physical data. ...
Affective computing, as its name implies, focuses on the recognition of human emotions, sentiments, and feelings. This interdisciplinary field encompasses diverse areas such as languages, sociology, psychology, computer science, and physiology. However, there is a notable absence of research exploring the interaction between machine learning (ML) and mixed reality (XR) for affective computing. This paper aims to address this gap by discussing the importance of affective computing and delving into its concepts, methods, and outcomes. Drawing upon ML and XR approaches, we conduct a comprehensive survey of recent methodologies employed in affective computing. Additionally, we examine state-of-the-art approaches and available affective data resources. Furthermore, we explore various applications where affective computing has a significant impact, providing valuable insights for future scholars seeking to deepen their understanding of its relevance and practical implications.
... One method to reduce usage is to set the smartphone to vibrate when the time limit for using the app is exceeded [49]. Furthermore, the grayscale display settings of smartphones reduce usage time by an average of 39.70 min per day [50]. In addition, a previous study concluded that selfcontrol is an effective intervention to prevent smartphone addiction [51]. ...
Previous studies have reported that increased smartphone use is associated with cognitive function decline. To date, the hemodynamics in the prefrontal cortex (PFC) due to smartphone addiction have not been elucidated. This study aimed to examine the relationship between smartphone addiction and PFC activity. After measuring the smartphone usage time using an application, we evaluated smartphone addiction, depression, and sleep quality using questionnaires. In addition, to assess PFC activity, which is responsible for working memory, we measured cerebral blood flow in the PFC during verbal and spatial working memory tasks (VWM and SWM, respectively). Cerebral blood flow was measured in terms of the oxygenated hemoglobin levels using a 16-channel (Ch) near-infrared spectrometer. Data from 79 participants were analyzed. First, we found that smartphone addiction was positively correlated with depression, but not with the smartphone usage time and sleep quality. Second, after excluding the influence of depression, we found that smartphone addiction was negatively correlated with cerebral blood flow in Ch10 during VWM and in Ch6, 7, and 10 during SWM. These Chs correspond to the frontopolar cortex (FPC), which is part of the PFC, suggesting that smartphone addiction may reduce FPC activity.
... In the previous sections, we have sketched out a scenario that is as follows: On the one hand, there are multiple interventions, some of which have also been shown to be effective in a number of studies (Holte & Ferraro, 2020;Kim et al., 2019b;Ko et al., 2015;Lyngs et al., 2020;Tseng et al., 2019). On the other hand, we see that digital distractions continue to be a problem that DSCTs seem to not fully address. ...
Distractions are ubiquitous in today’s technology-saturated environments, an issue that significantly impacts learning contexts employing digital technologies and yields detrimental effects on learning. Digital self-control tools, which aim to assist users in their efforts to reduce digital distractions, are numerous and readily available. Despite several dedicated empirical studies focusing on specific tools, there remains a notable lack of information regarding their daily use and helpfulness. Furthermore, the sheer variety of these tools prompts questions about their universal helpfulness and the potential influence of individual differences.
To address these issues, we surveyed a sample of higher-education students, totaling 273 individuals. These students reported on their media use, satisfaction with learning, and experiences with features of digital self-control tools. Our study’s findings indicate a discrepancy in the perception and awareness of these features; those deemed most helpful are among the least known, and conversely, common features are often perceived as unhelpful.
Our research also uncovered a negative correlation between habitual media use and the use of less restrictive features. Another identified issue was constraints on the use of these tools for learning, as platforms often serve dual purposes for both education and entertainment. We delve into these practical problems and propose future research directions to further advance the understanding of digital self-control tools.
... Recently, many researchers have attended to this matter by dedicating their studies to uncovering antecedents and consequences of excessive smartphone use. As a result, many different constructs, such as problematic use (Cheng and Meng, 2021;Elhai et al., 2018;Regan et al., 2020;Zerach, 2020), excessive use (Aranda and Baig, 2018;Holte and Ferraro, 2020;Loid et al., 2020), compulsive smartphone use (Chen et al., 2017;Wang et al., 2014;Wang and Lee, 2020;Zhang et al., 2014), and habitual smartphone use (Van Deursen et al., 2015;Roffarello and De Russis, 2021) have emerged. The predominant label to describe excessive use of IT however, has been that of IT addiction, or, specific to the context of smartphone use, smartphone addiction (Van Deursen et al., 2015;Lan et al., 2018;Lin et al., 2017). ...
According to the theory of IT-mediated state-tracking, the intended and unintended consequences of constantly checking digital devices can be judged by the resulting problem of attention and by whether the checking led to information that served the individual’s enduring goal. While this perspective offers numerous benefits over the common practice of labeling excessive information technology use as addiction, as of yet, the constructs of problem of attention (PoA) and service to enduring goal (SEG) lack empirical measures. Thus, this paper develops measurement scales for the constructs PoA and SEG following an established construct development methodology. We evaluate the measures’ validity and reliability and demonstrate that PoA and SEG differ from existing similar concepts. With the help of our newly developed constructs the quality of constant checking habits can be assessed which enables future studies to scrutinize the theorized preventive role of self-control in the context of smartphone habits.
... In sum, as long as APIs are closed, scientists will further study social media effects by asking participants about their online use and perhaps by imitating platforms using experimental setups. This way, we know for instance that the endowment effect might be a good explanation for why people have problems in quitting social media [52,53], and that nudging mechanisms are a likely explanation for the power of read-receipt functions (working for some via social pressure; [54]) or that colors are of relevance to hold a grip on user attention [55]. Compared to the many questionnaire studies being conducted on addiction symptoms in the field of social media and wellbeing, the power of design elements driving social media use is still understudied. ...
Purpose of the Review
Social media attracts billions of users worldwide, and research has investigated how screen time or time spent online is linked to well-being. Additionally, addictive-like behaviors towards the social media platforms are a focus of many studies. However, related research often neglects the simple fact that social media companies have willingly created immersive online environments with the aim to “persuade” users to spend as much time possible on their social media apps to watch ads and enlarge their digital footprints.
Recent Findings
We think that it is of utmost importance to better understand how the many design elements on social media platforms—ranging from the like-button to endless scrolling—impact the psyche and behavior of users. Such knowledge will not only help to better understand how problematic social media use evolves but will also provide important knowledge on how more healthy social media platforms could look like in the future. In this context, the present article also critically reflects the time well-spent initiative by the industry.
Summary
From our view, the many problems around social media will only be solved if the data business model is abandoned. As long as companies base their business model on the digital surveillance of people’s lives, no changes towards healthier social media platforms can be expected.
... These widely used datasets have inspired the development of emotional computing, which is Machine Learning (ML). Study [17] reports that in everyday human interaction, human emotions are primarily expressed through facial expressions (55%) voice (38%) and words (7%) Textual, auditory, and visual signals are generally referred to as physical data. ...
As the name suggests, affective computing aims to recognize human emotions, sentiments, and feelings. There is a wide range of fields that study affective computing, including languages, sociology, psychology, computer science, and physiology. However, no research has ever been done to determine how machine learning (ML) and mixed reality (XR) interact together. This paper discusses the significance of affective computing, as well as its ideas, conceptions, methods, and outcomes. By using approaches of ML and XR, we survey and discuss recent methodologies in affective computing. We survey the state-of-the-art approaches along with current affective data resources. Further, we discuss various applications where affective computing has a significant impact, which will aid future scholars in gaining a better understanding of its significance and practical relevance.
... The results of this study showed that these notifications do not really reduce smartphone use nor self-reported PSU. Holte and Ferraro (2020) conducted an experiment that entailed making smartphones less appealing by changing the phones to grayscale for 8-10 days. They found that total screen time was reduced by an average of almost 40 min per day, suggesting that by targeting the appearance (or, essentially, the functionality) of smartphones may reduce the usage of these devices. ...
Since the proliferation of smartphones, the general public as well as researchers have shown a growing interest in their potentially addictive effects. Over the past years, smartphone use research has grown exponentially. While scholars have moved away from “smartphone addiction” terminology in contemporary research and opted for alternative terminology (e.g., “problematic smartphone use” and “smartphone use disorder”) and frameworks, excessive smartphone use has been found to be correlated with depression and anxiety, as well as loss of productivity at work and school. This chapter provides a broader view of this research domain by exploring the following issues: is “smartphone addiction” a real phenomenon? How does it develop? Are some people more prone to experiencing it than others? How can it be assessed, and if one experiences this issue, how could it be treated? We aim to answer these questions in the current work. In addition, we outline some concerns with the construct of “smartphone addiction” while also providing insights into the latest research on this topic.KeywordsSmartphone addictionProblematic smartphone useSmartphone use disorderInternet addictionInternet use disorderSocial media addiction
... Another major limitation is the nature of OMSU data: the data do not include a more fine-grained view on what exactly people were doing on their smartphones. Recent work has shown that communication, social media, and instant messaging-based applications may primarily drive engagement in smartphone use (Lowe-Calverley & Pontes, 2020;Rozgonjuk, Sindermann, Elhai, Christensen, et al., 2020), and altering the settings of one's smartphone (e.g., grayscaling the screen, hiding notifications, etc) may reduce one's smartphone usage (Holte & Ferraro, 2020;Olson et al., 2021). Based on these results, one may hypothesize that FoMO, too, may be associated with specific applications use -for instance, reducing the functionality of image and video content-based applications (e.g., Instagram, YouTube, etc) may lead to decreases in the use of those applications, and perhaps also in the long run in FoMO. ...
Fear of Missing Out (FoMO) is associated with self-reported problematic smartphone use (PSU) severity, but there is little investigation that includes objectively measured smartphone use. The aim of the current study was to provide insights into this domain. We combined the partially published data from two previous U.S.-based studies with college student samples that tracked smartphone use data with a different focus from the current study. Both data sets included socio-demographic measures, FoMO and PSU scale scores, and data for objectively measured screentime and frequency of screen unlocks over a week, amounting up to more than a thousand observations. FoMO had a strong correlation with self-reported PSU severity; however, FoMO was not associated with objectively measured smartphone use variables. FoMO did not predict behavioral smarthpone use over a week in multilevel modeling for repeated measures. Even though FoMO is a strong predictor of self-reported PSU severity, it does not predict objectively measured smartphone use.
... Despite this lack of data, we are optimistic that users can be nudged towards a healthier use of online content by clever system design [36]. For instance, a recent experimental work demonstrated that smartphone and social media use can be significantly reduced by an easy intervention, namely switching from a color mode on the smartphone to a gray scale color mode [54]. Moreover, we are convinced that an improvement of problem behavior with respect to smartphones in general, and social media/gaming more specifically, can be achieved if platforms are designed in a less "persuasive way." ...
Purpose of Review
The present paper provides an accessible overview on the potential of digital phenotyping and mobile sensing not only shedding light on the nature of Internet Use Disorders (IUD), but also to provide new ideas on how to improve psycho-diagnostics of mental processes linked to IUD.
Recent Findings
In detail, the psycho-diagnostic areas of prevention, treatment, and aftercare in the realm of IUDs are focused upon in this work. Before each of these areas is presented in more specificity, the terms digital phenotyping and mobile sensing are introduced against the background of an interdisciplinary research endeavor called Psychoinformatics. Obstacles to overcome problems in this emerging research endeavor—sensing psychological traits/states from digital footprints—are discussed together with risks and chances, which arise from the administration of online-tracking technologies in the field of IUDs.
Summary
Given the limited validity and reliability of traditional assessment via questionnaires or diagnostic interviews with respect to recall bias and tendencies to answer towards social desirability, digital phenotyping and mobile sensing offer a novel approach overcoming recall bias and other limitations of usual assessment approaches. This will not only set new standards in precisely mapping behavior, but it will also offer scientists and practitioners opportunities to detect risky Internet use patterns in a timely manner and to establish tailored feedback as a means of intervention.
... Our data further indicate that reducing the problematic use of social media and messaging apps (particularly image-based SN app use) might help to reduce the overall SmUD tendencies of a person. Of interest is a recent study [36] that suggests that switching the smartphone mode from color mode to gray mode helps to reduce the time spent on smartphones and social media apps. Image-based SN apps might be particularly less interesting when images are only presented in gray mode. ...
Background
Social communication via instant messaging (IM) and social networking (SN) apps makes up a large part of the time that smartphone users spend on their devices. Previous research has indicated that the excessive use of these apps is positively associated with problematic smartphone use behaviors. In particular, image-based SN apps, such as Instagram (Facebook Inc) and Snapchat (Snap Inc), have been shown to exert stronger detrimental effects than those exerted by traditional apps, such as Facebook (Facebook Inc) and Twitter (Twitter Inc).
Objective
In this study, we investigated the correlation between individuals’ tendencies toward smartphone use disorder (SmUD) and objective measures of the frequency of smartphone usage. Additionally, we put to test the hypothesis that the pathway linking the frequency of actual smartphone usage to self-reported tendencies toward SmUD was mediated by the increased frequency of IM and SN app usage.
Methods
We recruited a sample of 124 adult smartphone users (females: 78/124, 62.9%; age: mean 23.84 years, SD 8.29 years) and collected objective information about the frequency of smartphone and SN app usage over 1 week. Participants also filled in a self-report measure for assessing the multiple components of tendencies toward SmUD. Bivariate associations were investigated by using Spearman correlation analyses. A parallel mediation analysis was conducted via multiple regression analysis.
Results
The frequency of smartphone usage, as well as the use of IM apps (Messenger, Telegram, and WhatsApp [Facebook Inc]), Facebook, and image-based apps (Instagram and Snapchat), had significant positive associations with at least 1 component of SmUD, and the cyberspace-oriented relationships factor exhibited the strongest associations overall. We found support for an indirect effect that linked actual smartphone usage to SmUD tendencies via the frequency of the use of image-based SN apps.
Conclusions
Our novel results shed light on the factors that promote SmUD tendencies and essentially indicate that image-based SN apps seem to be more strongly associated with problematic smartphone behaviors compared to IM apps and traditional SN apps, such as Facebook.
... Smartphone usage is most commonly discouraged by issuing warnings or prohibiting usage beyond a specified amount of time on the phone, such as Screen Time feature on an iPhone. Other methods include changing the screen to grayscale, which reduces users' satisfaction [9], or increasing the usage cost by enforcing additional tasks on users [11]. However, although these methods discourage smartphone use at the time of issue, simple warnings are ineffective and excessively severe restrictions tend to frustrate users [10]. ...
Smartphones have become a central part of information processing devices. Smartphones are used for information searching, taking photographs, listening to music, and socializing. However, as the number of smartphone users continues to expand, a number of problems related to smartphone overuse have emerged. Smartphone overuse is most commonly discouraged by issuing warnings to users or imposing a time limit on usage. However, although these methods discourage smartphone use at the time of issue, simple warnings are ineffective and excessively severe restrictions can frustrate users. This paper proposes a system that messages users through an anthropomorphic character when their smartphone has been overused. The system, called “CHIAPON”, was experimentally evaluated on 25 college students. The results showed that message notification by an anthropomorphic character can improve users’ motivation to reduce their smartphone use, but the extent of this reduction was not clarified. However, the participants using CHIAPON perceived the system positively, suggesting that the effect of the system can increase with long-term use.
... Our data further indicate that reducing the problematic use of social media and messaging apps (particularly image-based SN app use) might help to reduce the overall SmUD tendencies of a person. Of interest is a recent study [36] that suggests that switching the smartphone mode from color mode to gray mode helps to reduce the time spent on smartphones and social media apps. Image-based SN apps might be particularly less interesting when images are only presented in gray mode. ...
BACKGROUND
Online social communication via instant messaging (IM) and social networking (SN) applications make up for a large part of the time smartphone users spend on their devices. Previous research indicates that the excessive use of these applications positively associates with smartphone-related addictive behaviors. In particular, image-based SN apps, such as Instagram and Snapchat, have been shown to exert stronger detrimental effects than traditional apps, such as Facebook and Twitter.
OBJECTIVE
We investigate the correlation between individual tendency towards smartphone use disorder (SmUD) and objective measures of frequency of smartphone usage. Additionally, we explore a mediation pathway linking frequency of actual smartphone usage and self-reported tendencies towards SmUD by route of increased frequency of usage of IM and SN apps.
METHODS
We recruited a sample of N = 124 adult smartphone users (62.9% females; mean age of M=23.84 (SD = 8.29) years) and collected objective information about the frequency of smartphone and SN app usage over one week. Participants also filled in a self-report measure assessing multiple components of tendencies toward smartphone use disorder. Bivariate associations were investigated using Spearman correlations. A parallel mediation analysis was implemented via multiple regression analysis.
RESULTS
The frequency of smartphone usage, as well as the use of IM apps (Messenger, Telegram, WhatsApp), Facebook, and image-based apps (Instagram, Snapchat), had significant positive associations with at least one component of a smartphone use disorder, with the facet cyberspace-oriented relationships exhibiting the strongest associations. We find support for an indirect effect linking actual smartphone usage and smartphone use disorder tendencies via frequency of use of image-based SN apps.
CONCLUSIONS
This novel result sheds light on the factors promoting smartphone use disorder and essentially indicates the features implemented in the considered image-based SN apps as being potentially more “addictive” than those available in IM apps and traditional SN apps, such as Facebook.
Wenn es also in diesem kurzen Text darum geht, die Frage zu stellen, was Schulische Digitalisierung ist, geht es um vieles. Es geht darum auszuloten, wo Digitalisierung hinschreitet und zu überlegen, wo man mit ihr hinwill, während es natürlich auch darauf ,ankömmt die Welt zu verändern‘. Dass es beim durch Digitalisierung angestoßenen Veränderungsprozess im Kern um Technik geht, ist eines der sprichwörtlichen Kernmissverständnisse (Abschnitt 2). Es gilt daher den Fokus zu verschieben: von der Frage der Technisierung hin zu zwei anderen Fragen. Es geht um die Fragen, was Digitalisierung mit unserem räumlichen, zeitli- chen, sozialen und psychischen Weltverhältnis anstellt (Abschnitt 3), und wie sich dadurch soziale Praktiken verändern; Veränderungen, die sich noch in unsere so- ziale (Rollen), psychologische (Selbst- und Fremdverhältnisse) und sogar physi- sche (Körper) Grundkonstitution einschreiben.
Die Tragweite von Digitalisierung zu begreifen heißt, die Möglichkeiten zu erfassen, was diese Digitalisierung alles kann (Leistungsspektrum) und vielleicht auch zu bedenken, was sie so alles anstellt (Wirkungsspektrum). Begreift man Schulische Digitalisierung schließlich als gesellschaftspolitisches Projekt, ist ein gesunderes Maß an Realismus hilfreich. Wir leben nicht in der besten aller tech- nischen Welten. Die Grenzen der profanen Wirklichkeit sind entsprechend Ge- genstand des vierten und letzten Abschnitts dieses Kapitels. Ganz am Ende dieses Buchs kommen wir auf diese Punkte zurück und formulieren ein Plädoyer für eine ambitionierte, aber bodenständige ,Revolution‘ in Sachen Schulischer Digitalisierung und lassen damit unserem Optimismus freien Lauf.
Wir leben nicht in der besten aller digitalen Welten. Fragen der Ausstattung drängen weiterhin, noch längst sind nicht alle Probleme bezüglich der Wartung/des Supports in Bezug auf Technik und Netzwerke etc. geklärt und auch die Möglichkeiten der methodischen und didaktischen Weiterbildung sind noch nicht vollständig ausgereift. Aber ist das Warten auf die perfekten Bedingungen nicht ein Trugbild? Steht der Perfektionismus nicht dem Guten im Weg? Das Material, das benötigt wird, um schulische Digitalisierungsprozesse anzugehen, ist vorhanden. An die Protagonist*innen schulischer Digitalisierung gerichtet: Was Sie benötigen, ist ein Zugriff auf digitale Technik, die es erlaubt schulische Praxis umzubauen. Diese Technik nutzt Ihnen wenig, wenn Sie sich nicht vor- stellen können, wozu Sie diese Technik gebrauchen können. Ganz entscheidend ist insofern, dass Sie ein Verständnis für die Potentiale schulischer Digitalisierung entwickeln und somit auch Ihre eigenen Digitalisierungsziele formulierenkönnen. Zuletzt ist ohne die Bereitschaft der schulischen Akteur*innen – allen voran der Lehrkräfte – eine schulische Digitalisierung nicht zu haben. Wenn Sie auf diese drei Ressourcen – digitale Technik, ein Digitalisierungsverständnis und Ihre eigene Bereitschaft – zurückgreifen können, fehlt ihnen nur noch der Mut anzufangen.
Klug genutzt, kann Digitalisierung helfen, Effizienz und Effektivität schuli- scher Lehr- und Lernprozesse zu verbessern und diese attraktiver zu gestalten, herkunftsbedingter sozialer Ungleichheit zu begegnen sowie das Lernen und Be- treuen zu personalisieren. Wir plädieren dafür damit einfach anzufangen. Die Digitalisierung von Schule erfordert eine sehr ambitionierte, aber bodenständige Revolution. Für Schulen, Schulleitungen und Lehrkräfte bedeutet dies das Folgende:
Schulische Digitalisierung ist ein unabgeschlossenes Projekt. Dieses Buch erörtert praxisnah Möglichkeiten, Grenzen und Herausforderungen der Digitalisierung in Schulen. Der erste Teil fokussiert Grundlagen: Was bedeutet es, wenn Schule digitaler wird? Welche Forschungsergebnisse gibt es hierzu? Welche Bedeutung haben Lernmanagementsysteme (LMS), Open Educational Resources (OER) und Gamification? Der zweite Teil richtet die Aufmerksamkeit auf Rahmenbedingungen wie Achtsamkeit und Datenschutz sowie auf Themen wie Digitale Gewalt / Cybermobbing und die Rolle von Smartphones im Unterricht.
Digital disconnection has emerged as a concept describing the actions people take to limit their digital connectivity to enhance their well-being. To date, evidence on its effectiveness is mixed, leading to calls for greater consideration of why, how, when, and for whom digital disconnection works. This article responds to these calls, presenting a framework that differentiates four key harms that contribute to experiences of digital ill-being (time displacement, interference, role blurring, and exposure effects). Using these four harms as a starting point, the framework explains: (1) why people are motivated to digitally disconnect; (2) how specific disconnection strategies (i.e., placing limits on time, access, channels, and contents, interactions and features) may help them; and for whom (3) and under which conditions (when) these strategies can be effective.
In response to the growing public concern about digital well-being, many tools have been developed for individuals to reduce their screen time. An understudied but promising self-nudge intervention is turning off smartphone screen colors (i.e., grayscaling). Since a grayscale setting is available on all smartphones, it has the potential to be an easily implemented intervention. The main aim of the current study was to assess the efficacy of a grayscale intervention by addressing its effects on both objective smartphone behavior as well as on daily subjective indicators of digital well-being. Participants’ smartphone use was tracked for 2 weeks ( N = 84). The first week served as a baseline measure, followed by a 1-week grayscale intervention. Findings indicate that daily screen time was significantly reduced by 20 min, yet the daily number of phone unlocks did not change, suggesting deep-rooted checking habits. Moreover, grayscaling improved perceived control over one's smartphone use, and reduced perceived overuse, online vigilance, and stress, but did not affect productivity or sleep quality. Overall, findings indicate that grayscaling is an effective strategy to reduce screen time and improve digital well-being.
Objective. To determine pharmacy student reactions to and experiences with an intervention based upon the principle of salience to reduce psychological attraction and attention to smartphones. Method. For a period of 3 weeks, participants were directed to change their smartphone's color setting to grayscale mode, turn off social media notifications, remove social media icons from smartphone home screen, and place the device away from bed when sleeping. A thematic analysis was performed on responses to an anonymous, open-ended survey question that asked participants to record any positive/negative changes to their life and well-being as a result of participating in the study. Results. Thematic analysis revealed twenty unique themes, which provided a variety of notable observations including a reduction in both smartphone and social media use, reduced allure because of grayscale mode, frustrations caused by grayscale mode, increased productivity, and general improvements in sleep, face-to-face interactions, and overall well-being Conclusion. Results of this study provide initial evidence that changes to smartphone settings and physical placement at night may lead to positive outcomes. Participants reported primarily positive effects regarding well-being and reduced smartphone usage as a result of participating in the study. In many cases, less time on smartphones meant improved sleep, more productivity, more time for social/leisure activities, improved face-to-face interactions, and/or improvement in well-being.
Digital distractions can interfere with goal attainment and lead to undesirable habits that are hard to get red rid of. Various digital self‐control interventions promise support to alleviate the negative impact of digital distractions. These interventions use different approaches, such as the blocking of apps and websites, goal setting, or visualizations of device usage statistics. While many apps and browser extensions make use of these features, little is known about their effectiveness. This systematic review synthesizes the current research to provide insights into the effectiveness of the different kinds of interventions. From a search of the ‘ACM’, ‘Springer Link’, ‘Web of Science’, ’IEEE Xplore’ and ‘Pubmed’ databases, we identified 28 digital self‐control interventions. We categorized these interventions according to their features and their outcomes. The interventions showed varying degrees of effectiveness, and especially interventions that relied purely on increasing the participants' awareness were barely effective. For those interventions that sanctioned the use of distractions, the current literature indicates that the sanctions have to be sufficiently difficult to overcome, as they will otherwise be quickly dismissed. The overall confidence in the results is low, with small sample sizes, short study duration, and unclear study contexts. From these insights, we highlight research gaps and close with suggestions for future research.
Currently about 2.71 billion humans use a smartphone worldwide. Although smartphone technology has brought many advances, a growing number of scientists discuss potential detrimental effects due to excessive smartphone use. Of importance, the likely culprit to understand over-usage is not the smartphone itself, but the excessive use of applications installed on smartphones. As the current business model of many app-developers foresees an exchange of personal data for allowance to use an app, it is not surprising that many design elements can be found in social media apps and Freemium games prolonging app usage. It is the aim of the present work to analyze several prominent smartphone apps to carve out such elements. As a result of the analysis, a total of six different mechanisms are highlighted to illustrate the prevailing business model in smartphone app development. First, these app-elements are described and second linked to classic psychological/economic theories such as the mere-exposure effect, endowment effect, and Zeigarnik effect, but also to psychological mechanisms triggering social comparison. It is concluded that many of the here presented app-elements on smartphones are able to prolong usage time, but it is very hard to understand such an effect on the level of a single element. A systematic analysis would require insights into app data usually only being available for the app-designers, but not for independent scientists. Nevertheless, the present work supports the notion that it is time to critically reflect on the prevailing business model of ‘user data in exchange for app-use allowance’. Instead of using a service in exchange for data, it ultimately might be better to ban or regulate certain design elements in apps to come up with less addictive products. Instead, users could pay a reasonable fee for an app service.
Understanding how people use technology remains important, particularly when measuring the impact this might have on individuals and society. However, despite a growing body of resources that can quantify smartphone use, research within psychology and social science overwhelmingly relies on self-reported assessments. These have yet to convincingly demonstrate an ability to predict objective behavior. Here, and for the first time, we compare a variety of smartphone use and ‘addiction’ scales with objective behaviors derived from Apple's Screen Time application. While correlations between psychometric scales and objective behavior are generally poor, single estimates and measures that attempt to frame technology use as habitual rather than ‘addictive’ correlate more favorably with subsequent behavior. We conclude that existing self-report instruments are unlikely to be sensitive enough to accurately predict basic technology use related behaviors. As a result, conclusions regarding the psychological impact of technology are unreliable when relying solely on these measures to quantify typical usage.
Mobile devices and apps offer promising opportunities for both patients and healthcare professionals, for example, to monitor and assess health status, and also to provide relevant health information. However, health information seeking within a mood-tracking app has not yet been addressed by research. To bridge this gap, the depression-related health information seeking of 6,675 users of a mood-tracking smartphone app was unobtrusively monitored. The study shows that self-monitored depressive symptoms are associated with higher depression-related information seeking within the app. Health information seeking was low in general, with differences across 12 depression-related topics (e.g., depressive thoughts, a depression diagnosis, or depression facts), but the findings are also promising as the smartphone app was shown to be a place where users can inform themselves about health topics related to the main purpose of the app. Smartphone apps would therefore seem to be a vehicle through which to provide additional health information about, for example, comorbidities, or pre- or post-interventions, even going beyond the original purposes of such mobile health (mHealth) monitoring apps.
Gambling Disorder is a prevalent psychiatric condition often linked to dysfunction of cognitive domains regulating impulsive behavior. Despite the centrality of impulsivity to neurobiological models of Gambling Disorder, a comprehensive meta-analysis of all impulsive cognitive domains has yet to be conducted. It is also not clear whether cognitive deficits in Gambling Disorder extend to those with problem (at-risk) gambling. A systematic review was undertaken of case–control studies examining the following cognitive domains in Gambling Disorder or in at-risk (problem) gambling: attentional inhibition, motor inhibition, discounting, decision-making, and reflection impulsivity. Case–control differences in cognition were identified using meta-analysis (random-effects modeling). Moderation analysis explored potential influences of age, gender, presence/absence of comorbidities in cases, geographical region, and study quality on cognitive performance. Gambling Disorder was associated with significant impairments in motor (g = 0.39–0.48) and attentional (g = 0.55) inhibition, discounting (g = 0.66), and decision-making (g = 0.63) tasks. For problem gambling, only decision-making had sufficient data for meta-analysis, yielding significant impairment versus controls (g = 0.66); however, study quality was relatively low. Insufficient data were available for meta-analysis of reflection impulsivity. There was evidence for significant publication bias only for the discounting domain, after an outlier study was excluded. Study quality overall was reasonable (mean score 71.9% of maximum), but most studies (~85%) did not screen for comorbid impulse control and related disorders. This meta-analysis indicates heightened impulsivity across a range of cognitive domains in Gambling Disorder. Decision-making impulsivity may extend to problem (at-risk) gambling, but further studies are needed to confirm such candidate cognitive vulnerability markers.
Introduction:
Prior research has found that psychopathology constructs such as depression and anxiety are associated with problematic use of Facebook (PFU). In the present study, we examined a structural equation model whereby depression, social anxiety and lower life satisfaction predicted PFU severity, while analyzing mediating variables including rumination, fear of missing out (FoMO), and frequency of Facebook use, as well as age and gender as covariates.
Method:
Participants were 296 college students administered a web survey of instruments measuring these constructs.
Results:
Modeling results demonstrate that FoMO and rumination were significantly related to PFU severity. Facebook use frequency was related to PFU severity. FoMO and rumination each mediated relations between social anxiety and PFU severity.
Conclusions:
Results are discussed in the context of prior work on FoMO and excessive technology use, as well as several relevant theoretical frameworks.
With mobile phones becoming central parts of our lives, mobile technology gets criticized for its negative impact on people's well-being. Studies generally report negative associations between mobile phone use (MPU) and well-being. However, few studies contrast the relationship of MPU with different concepts of positive psychology. The aim of this study was to investigate the relationship between MPU and different concepts of positive psychology: life satisfaction, well-being, and mindfulness. Data from 461 German speaking participants answering an online-questionnaire were analyzed. Overall, results suggest that participants who use their mobile phones more often report lower well-being, life satisfaction, and mindfulness scores. Furthermore, results imply that the relationships between positive psychology concepts and MPU differ between men and women. Results indicate that MPU and its associations with concepts of positive psychology are relevant areas for research and deserve more attention.
Depression is the most common metal disorder linked to media use. Theoretically, the relationship between depression and media use has been conceptualized as a linear function. However, depressive symptoms vary from dysphoric moods to severely depressed states with major social impairment, thus providing a strong alternative rationale for a non-linear relationship. This paper reports on findings from a representative telephone survey of the general German population (N = 2002) including both the respondents’ motivation behind spending time using traditional media and a measure to screen for depression in the general population. The curve-fitting methodology revealed that the associations between depression and media use are described by a cubic growth function for newspapers, the radio, magazines, and books; associations with television use were positive, but more complex. The relationship between depression and media use should be modeled as a polynomial function for more accurate estimations in the future.
This paper explores compulsive use of YouTube by university students and investigates how the uses and gratifications perspective and the personality perspective work together to explain compulsive use of the social medium. It compares the effects of motivation to use YouTube for information with motivation to use the platform for entertainment, and examines how the different motivational effects compare with those of personality. It also explores the influence of compulsive use of YouTube on academic motivation. Data from 807 students at a Malaysian university were analysed using hierarchical multiple regression. Stronger motivation to use YouTube for information and learning is associated with lower compulsive use, while stronger motivation to use YouTube for entertainment is associated with higher compulsive use. Entertainment motivation has a stronger effect than information motivation. Although tendency to compulsive use differs with personality traits, the motivation effects are independent of personality. Compulsive YouTube use negatively influences academic motivation. While educators can take risks of compulsive use into account when they propose YouTube resources to their students, information literacy education and training can play an additional role in risk reduction by alerting social media users to the risks of compulsive use and helping them to develop self-management strategies.
Introduction: In three consecutive studies, we aimed to investigate the relationship between problematic Internet use (PIU), Internet Gaming Disorder (IGD) and implicit learning abilities, and impulsivity/risk-taking among online video gamers and control participants.
Methods: In study 1, male visitors, recruited at the “Gamescom” in Cologne (2013), filled in a short version of the Internet Addiction Test (s-IAT), the Online Gaming Addiction Scale (OGAS), and completed an experimental task to assess implicit learning abilities. In study 2, a group of WoW gamers and control participants completed the same set up, in order to replicate the results of study 1. Study 3 used a modified version of the experiment to measure impulsivity/risk-taking in a group of healthy participants.
Results: In study 1, results revealed a significant negative correlation between the s-IAT score and the measure of implicit learning among male Gamescom participants. In study 2, the s-IAT and WoW addiction scores were negatively correlated with implicit learning only in male WoW players, which mirrors the results from study 1. In study 3, the OGAS score was positively correlated with the experimental measure of impulsivity/risk-taking.
Conclusion: In the current research project, deficient implicit learning was linked to PIU only in male participants with (a tendency towards) IGD. These findings might help to disentangle some opposing results on this relationship, when considering the gender of participants. Furthermore, higher risk-taking tendencies were associated with IGD among healthy participants, thus, suggesting the potential of risk taking as a predictor of IGD in a non-gamer population.
Within the last two decades, many studies have addressed the clinical phenomenon of Internet-use disorders, with a particular focus on Internet-gaming disorder. Based on previous theoretical considerations and empirical findings, we suggest an Interaction of Person-Affect-Cognition-Execution (I-PACE) model of specific Internet-use disorders. The I-PACE model is a theoretical framework for the processes underlying the development and maintenance of an addictive use of certain Internet applications or sites promoting gaming, gambling, pornography viewing, shopping, or communication. The model is composed as a process model. Specific Internet-use disorders are considered to be the consequence of interactions between predisposing factors, such as neurobiological and psychological constitutions, moderators, such as coping styles and Internet-related cognitive biases, and mediators, such as affective and cognitive responses to situational triggers in combination with reduced executive functioning. Conditioning processes may strengthen these associations within an addiction process. Although the hypotheses regarding the mechanisms underlying the development and maintenance of specific Internet-use disorders, summarized in the I-PACE model, must be further tested empirically, implications for treatment interventions are suggested.
Method:
We conducted a systematic review of the relationship between problematic use
with psychopathology. Using scholarly bibliographic databases, we screened 117
total citations, resulting in 23 peer-reviewer papers examining statistical relations
between standardized measures of problematic smartphone use/use severity
and the severity of psychopathology.
Results:
Most papers examined problematic use in relation to depression, anxiety, chronic
stress and/or low self-esteem. Across this literature, without statistically adjusting
for other relevant variables, depression severity was consistently related to
problematic smartphone use, demonstrating at least medium effect sizes. Anxiety
was also consistently related to problem use, but with small effect sizes. Stress
was somewhat consistently related, with small to medium effects. Self-esteem
was inconsistently related, with small to medium effects when found. Statistically
adjusting for other relevant variables yielded similar but somewhat smaller
effects.
Limitations:
We only included correlational studies in our systematic review, but address the
few relevant experimental studies also.
Conclusions:
We discuss causal explanations for relationships between problem smartphone
use and psychopathology.
This study examined how social media use related to sleep quality, self-esteem, anxiety and depression in 467 Scottish adolescents. We measured overall social media use, nighttime-specific social media use, emotional investment in social media, sleep quality, self-esteem and levels of anxiety and depression. Adolescents who used social media more – both overall and at night – and those who were more emotionally invested in social media experienced poorer sleep quality, lower self-esteem and higher levels of anxiety and depression. Nighttime-specific social media use predicted poorer sleep quality after controlling for anxiety, depression and self-esteem. These findings contribute to the growing body of evidence that social media use is related to various aspects of wellbeing in adolescents. In addition, our results indicate that nighttime-specific social media use and emotional investment in social media are two important factors that merit further investigation in relation to adolescent sleep and wellbeing.
Background:
Social media (SM) use is increasing among U.S. young adults, and its association with mental well-being remains unclear. This study assessed the association between SM use and depression in a nationally representative sample of young adults.
Methods:
We surveyed 1,787 adults ages 19 to 32 about SM use and depression. Participants were recruited via random digit dialing and address-based sampling. SM use was assessed by self-reported total time per day spent on SM, visits per week, and a global frequency score based on the Pew Internet Research Questionnaire. Depression was assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) Depression Scale Short Form. Chi-squared tests and ordered logistic regressions were performed with sample weights.
Results:
The weighted sample was 50.3% female and 57.5% White. Compared to those in the lowest quartile of total time per day spent on SM, participants in the highest quartile had significantly increased odds of depression (AOR = 1.66, 95% CI = 1.14-2.42) after controlling for all covariates. Compared with those in the lowest quartile, individuals in the highest quartile of SM site visits per week and those with a higher global frequency score had significantly increased odds of depression (AOR = 2.74, 95% CI = 1.86-4.04; AOR = 3.05, 95% CI = 2.03-4.59, respectively). All associations between independent variables and depression had strong, linear, dose-response trends. Results were robust to all sensitivity analyses.
Conclusions:
SM use was significantly associated with increased depression. Given the proliferation of SM, identifying the mechanisms and direction of this association is critical for informing interventions that address SM use and depression.
Over the last decade, research into "addictive technological behaviors" has substantially increased. Research has also demonstrated strong associations between addictive use of technology and comorbid psychiatric disorders. In the present study, 23,533 adults (mean age 35.8 years, ranging from 16 to 88 years) participated in an online cross-sectional survey examining whether demographic variables, symptoms of attention-deficit/hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety, and depression could explain variance in addictive use (i.e., compulsive and excessive use associated with negative outcomes) of two types of modern online technologies: social media and video games. Correlations between symptoms of addictive technology use and mental disorder symptoms were all positive and significant, including the weak interrelationship between the two addictive technological behaviors. Age appeared to be inversely related to the addictive use of these technologies. Being male was significantly associated with addictive use of video games, whereas being female was significantly associated with addictive use of social media. Being single was positively related to both addictive social networking and video gaming. Hierarchical regression analyses showed that demographic factors explained between 11 and 12% of the variance in addictive technology use. The mental health variables explained between 7 and 15% of the variance. The study significantly adds to our understanding of mental health symptoms and their role in addictive use of modern technology, and suggests that the concept of Internet use disorder (i.e., "Internet addiction") as a unified construct is not warranted. (PsycINFO Database Record
Background and aims:
The usage of smartphones has increased rapidly in recent years, and this has brought about addiction. The aim of the current study was to investigate the relationship between smartphone use severity and sleep quality, depression, and anxiety in university students.
Methods:
In total, 319 university students (203 females and 116 males; mean age = 20.5 ± 2.45) were included in the study. Participants were divided into the following three groups: a smartphone non-user group (n = 71, 22.3%), a low smartphone use group (n = 121, 37.9%), and a high smartphone use group (n = 127, 39.8%). All participants were evaluated using the Pittsburgh Sleep Quality Index, Beck Depression Inventory, Beck Anxiety Inventory; moreover, participants other than those in the smartphone non-user group were also assessed with the Smartphone Addiction Scale.
Results:
The findings revealed that the Smartphone Addiction Scale scores of females were significantly higher than those of males. Depression, anxiety, and daytime dysfunction scores were higher in the high smartphone use group than in the low smartphone use group. Positive correlations were found between the Smartphone Addiction Scale scores and depression levels, anxiety levels, and some sleep quality scores.
Conclusions:
The results indicate that depression, anxiety, and sleep quality may be associated with smartphone overuse. Such overuse may lead to depression and/or anxiety, which can in turn result in sleep problems. University students with high depression and anxiety scores should be carefully monitored for smartphone addiction.
We investigated the flexor pollicis longus (FPL) tendon and median nerve in smartphone users by ultrasonography to assess the effects of smartphone addiction on the clinical and functional status of the hands.
One-hundred-two students were divided into 3 groups: Non-users, high and low smartphone-users. Smartphone Addiction Scale (SAS) scores and grip and pinch strengths were recorded. Pain in thumb movement and rest and hand function were evaluated on a visual analog scale (VAS) and the Duruöz Hand Index (DHI) respectively. The cross sectional areas (CSA) of the median nerve and the FPL tendon were calculated bilaterally with ultrasonography.
There were significantly higher median nerve CSAs in the dominant hands of the high smartphone users than non-dominant hands (P<0.001). The SAS scores correlated with the VAS pain for movement and rest, the DHI scores, and pinch strength (P<0.05, r=0.345, 0.272, 0.245, and 0.281 respectively).
Smartphone overuse enlarges the median nerve, causes pain in the thumb, and decreases pinch strength and hand functions. This article is protected by copyright. All rights reserved.
© 2015 Wiley Periodicals, Inc.
OPEN ACCESS: http://sgo.sagepub.com/content/5/1/2158244015573169
The cell phone is ever-present on college campuses and is frequently used in settings where learning occurs. This study assessed the relationship between cell phone use and actual college grade point average (GPA) after controlling for known predictors. As such, 536 undergraduate students from 82 self-reported majors at a large, public university were sampled. A hierarchical regression (R2 = .449) demonstrated that cell phone use was significantly (p < .001) and negatively (β = −.164) related to actual college GPA after controlling for demographic variables, self-efficacy for self-regulated learning, self-efficacy for academic achievement, and actual high school GPA, which were all significant predictors (p < .05). Thus, after controlling for other established predictors, increased cell phone use was associated with decreased academic performance. Although more research is needed to identify the underlying mechanisms, findings suggest a need to sensitize students and educators about the potential academic risks associated with high-frequency cell phone use.
Depression is a debilitating condition that adversely affects many aspects of a person's life and general health. Earlier work has supported the idea that there may be a relationship between the use of certain media and depression. In this study, we tested if self-report of depression (SRD), which is not a clinically based diagnosis, was associated with increased internet, television, and social media usage by using data collected in the Media Behavior and Influence Study (MBIS) database (N = 19,776 subjects). We further assessed the relationship of demographic variables to this association. These analyses found that SRD rates were in the range of published rates of clinically diagnosed major depression. It found that those who tended to use more media also tended to be more depressed, and that segmentation of SRD subjects was weighted toward internet and television usage, which was not the case with non-SRD subjects, who were segmented along social media use. This study found that those who have suffered either economic or physical life setbacks are orders of magnitude more likely to be depressed, even without disproportionately high levels of media use. However, among those that have suffered major life setbacks, high media users—particularly television watchers—were even more likely to report experiencing depression, which suggests that these effects were not just due to individuals having more time for media consumption. These findings provide an example of how Big Data can be used for medical and mental health research, helping to elucidate issues not traditionally tested in the fields of psychiatry or experimental psychology.
A field experiment examined whether increasing opportunities for face-to-face interaction while eliminating the use of screen-based media and communication tools improved nonverbal emotion–cue recognition in preteens. Fifty-one preteens spent five days at an overnight nature camp where television, computers and mobile phones were not allowed; this group was compared with school-based matched controls (n = 54) that retained usual media practices. Both groups took pre- and post-tests that required participants to infer emotional states from photographs of facial expressions and videotaped scenes with verbal cues removed. Change scores for the two groups were compared using gender, ethnicity, media use, and age as covariates. After five days interacting face-to-face without the use of any screen-based media, preteens’ recognition of nonverbal emotion cues improved significantly more than that of the control group for both facial expressions and videotaped scenes. Implications are that the short-term effects of increased opportunities for social interaction, combined with time away from screen-based media and digital communication tools, improves a preteen’s understanding of nonverbal emotional cues.
Adolescence is a time of increasing vulnerability for poor mental health, including depression. Sleep disturbance is an important risk factor for the development of depression during adolescence. Excessive electronic media use at night is a risk factor for both adolescents' sleep disturbance and depression. To better understand the interplay between sleep, depressive symptoms, and electronic media use at night, this study examined changes in adolescents' electronic media use at night and sleep associated with smartphone ownership. Also examined was whether sleep disturbance mediated the relationship between electronic media use at night and depressive symptoms. 362 adolescents (12-17 year olds, M = 14.8, SD = 1.3; 44.8 % female) were included and completed questionnaires assessing sleep disturbance (short sleep duration and sleep difficulties) and depressive symptoms. Further, participants reported on their electronic media use in bed before sleep such as frequency of watching TV or movies, playing video games, talking or text messaging on the mobile phone, and spending time online. Smartphone ownership was related to more electronic media use in bed before sleep, particularly calling/sending messages and spending time online compared to adolescents with a conventional mobile phone. Smartphone ownership was also related to later bedtimes while it was unrelated to sleep disturbance and symptoms of depression. Sleep disturbance partially mediated the relationship between electronic media use in bed before sleep and symptoms of depression. Electronic media use was negatively related with sleep duration and positively with sleep difficulties, which in turn were related to depressive symptoms. Sleep difficulties were the more important mediator than sleep duration. The results of this study suggest that adolescents might benefit from education regarding sleep hygiene and the risks of electronic media use at night.
Background and aims:
Likening mobile phone use dependency to the classification of excessive behaviors may be necessarily equivalent in seriousness to previously established addictions such as problematic computing or excessive gambling. The aim of the study explores into the behavior of excessive use of mobile phones as a pathological behavior.
Methods:
Two studies investigated criteria for problematic mobile phone usage by examining student (Study 1, N = 301) and nonstudent (Study 2, N = 362) responses to a set of adapted mobile phone addiction inventories. Study 1 investigated cell phone addiction inventories as constructs designed to measure problematic cell phone use. Additionally, Study 2 sought to predict age, depression, extraversion, emotional stability, impulse control, and self-esteem as independent variables that augment respondents' perceptions of problematic use.
Results:
The results from Study 1 and Study 2 indicate that 10 to 25% of the participants tested exhibited problematic cell phone usage. Additionally, age, depression, extraversion, and low impulse control are the most suitable predictors for problematic use.
Conclusions:
The results of the two studies indicate that problematic mobile phone use does occur and ought to be taken seriously by the psychological community. Presently, there is limited data providing conclusive evidence for a comprehensible categorization of cell phone addiction, as well as a unified explanatory model specific to problematic mobile phone use. Studies such as this one may contribute substantial findings, adding scientific significance, and offering a valuable submission for the ongoing progress of creating intervention frameworks relative to "virtual addictions".
Research on the social and psychological effects of mobile phone communication primarily is conducted using self-report measures of use. However, recent studies have suggested such measures of mobile phone communication use contain a significant amount of measurement error. This study compares the frequency of mobile phone use measured by self-report questions with error-free log data automatically collected through an Android smartphone application. Using data from 310 Android phone users in Japan, we investigate the extent to which nonrandom measurement error exists in self-report responses to questions about mobile phone use and predictors of this error. Our analysis shows that users generally overreport their frequency of mobile communication and that overestimation is better predicted by proxy measures of social activity than demographic variables. We further show an example of how overreporting can result in an overestimation of the effects of mediated communication on civic engagement. Finally, the value of behavioral log data in mediated communication research is discussed.
Despite an explosion in the popularity of text messaging (short message service, or SMS texting), little research has documented the prevalence of its use in various dimensions of the social landscape of young adults. We examined text messaging patterns in various social situations in a sample of college students. Unsurprisingly, participants placed a good deal of importance on texting and reported using texts frequently to stay in touch with friends and loved ones. However, a good number of participants reported texting in seemingly inopportune situations, such as while in the shower, while at work, during religious services, and while having sex. Further, most participants reported texting in situations that may be considered by some as social breaches, such as while on a date, while socializing in person with others, and to break up with and cheat on a romantic partner. Results suggest that drawbacks of this convenient, fast, and faceless mode of communication include disinhibition and inattention to one's immediate social environment.
The aim of this study was to develop a self-diagnostic scale that could distinguish smartphone addicts based on the Korean self-diagnostic program for Internet addiction (K-scale) and the smartphone's own features. In addition, the reliability and validity of the smartphone addiction scale (SAS) was demonstrated.
A total of 197 participants were selected from Nov. 2011 to Jan. 2012 to accomplish a set of questionnaires, including SAS, K-scale, modified Kimberly Young Internet addiction test (Y-scale), visual analogue scale (VAS), and substance dependence and abuse diagnosis of DSM-IV. There were 64 males and 133 females, with ages ranging from 18 to 53 years (M = 26.06; SD = 5.96). Factor analysis, internal-consistency test, t-test, ANOVA, and correlation analysis were conducted to verify the reliability and validity of SAS.
Based on the factor analysis results, the subscale "disturbance of reality testing" was removed, and six factors were left. The internal consistency and concurrent validity of SAS were verified (Cronbach's alpha = 0.967). SAS and its subscales were significantly correlated with K-scale and Y-scale. The VAS of each factor also showed a significant correlation with each subscale. In addition, differences were found in the job (p<0.05), education (p<0.05), and self-reported smartphone addiction scores (p<0.001) in SAS.
This study developed the first scale of the smartphone addiction aspect of the diagnostic manual. This scale was proven to be relatively reliable and valid.
Smartphone use in health care work settings presents both opportunities and challenges. The benefits could be severely undermined if abuse and overuse are not kept in check. This practice-focused research paper examines the current panorama of health software applications. Findings from existing research are consolidated to elucidate the level and effects of distraction in health care work settings due to smartphone use. A conceptual framework for crafting guidelines to regulate the use of smartphones in health care work settings is then presented. Finally, specific guidelines are delineated to assist in creating policies for the use of smartphones in a health care workplace.
The goal of this study is to investigate how flow experience and diverse smartphone activities play a role in influencing people's perceived boredom during free time. Through a telephone survey, data were gathered from a probability sample of 653 smartphone users. Results indicate that the more people who engage in pleasure-seeking, short-lived, and diversionary hedonic activities, the stronger the feeling that their physical involvement is lacking. Eudaemonic activities, such as information seeking, significantly predicted a lack of meaningful involvement, while utilities significantly predicted a perceived slowness of time and lack of mental involvement. Findings also revealed that people achieve flow state when they use a smartphone for entertainment, information seeking, and sociability, especially when they feel bored, sense a lack of meaningful involvement, and want their free time to last. Furthermore, the interaction effects found in the study provide a more nuanced view about the ways in which eudaemonic smartphone activities (especially for information seeking and sociability) can interact with flow experience to regulate perceived boredom in free time. This study suggests that app designers should recognize the role of newly developed hedonic and eudaemonic functions of the smartphone which may significantly alleviate perceived boredom in free time.
We propose an updated version of the Interaction of Person-Affect-Cognition-Execution (I-PACE) model, which we argue to be valid for several types of addictive behaviors, such as gambling, gaming, buying-shopping, and compulsive sexual behavior disorders. Based on recent empirical findings and theoretical considerations, we argue that addictive behaviors develop as a consequence of the interactions between predisposing variables, affective and cognitive responses to specific stimuli, and executive functions, such as inhibitory control and decision-making. In the process of addictive behaviors, the associations between cue-reactivity/craving and diminished inhibitory control contribute to the development of habitual behaviors. An imbalance between structures of fronto-striatal circuits, particularly between ventral striatum, amygdala, and dorsolateral prefrontal areas, may be particularly relevant to early stages and the dorsal striatum to later stages of addictive processes. The I-PACE model may provide a theoretical foundation for future studies on addictive behaviors and clinical practice. Future studies should investigate common and unique mechanisms involved in addictive, obsessive-compulsive-related, impulse-control, and substance-use disorders.
Background:
Problematic smartphone use (PSU) is associated with depression and anxiety symptom severity throughout the literature. However, many important psychopathology constructs have not been examined for associations with PSU severity. Worry and anger are two psychopathology constructs receiving little empirical scrutiny in relation to PSU, but theoretically should demonstrate significant relationships. Furthermore, few studies have used person-centered analyses, such as mixture modeling, to analyze possible latent subgroups of individuals based on PSU symptom ratings.
Method:
We conducted a web survey of 300 American college students, using the Smartphone Addiction Scale-Short Version, Penn State Worry Questionnaire-Abbreviated Version, and Dimensions of Anger Reactions-5 Scale.
Results:
Conducting mixture modeling using latent profile analysis, we found most support for a three-class model of latent groups of individuals based on their PSU item ratings. Adjusting for age and sex, worry and anger scores were significantly higher in the more severe PSU classes.
Discussion:
Results are discussed in the context of uses and gratifications theory, as well as compensatory internet use theory, in terms of individual differences explaining excessive technology use.
Limitations:
Limitations include the non-clinical nature of the sample.
Conclusions:
Worry and anger may be helpful constructs in understanding the phenomenology of PSU, and psychological interventions for worry and anger may offset PSU.
People increasingly use social media to record and share their experiences, but it is unclear whether or how social media use changes those experiences. Here we present both naturalistic and controlled studies in which participants engage in an experience while using media to record or share their experiences with others, or not engaging with media. We collected objective measures of participants' experiences (scores on a surprise memory test) as well as subjective measures of participants' experiences (self-reports about their engagement and enjoyment). Across three studies, participants without media consistently remembered their experience more precisely than participants who used media. There is no conclusive evidence that media use impacted subjective measures of experience. Together, these findings suggest that using media may prevent people from remembering the very events they are attempting to preserve.
Background:
Although males more frequently develop Internet gaming disorder (IGD) as compared with females, few studies have examined gender-related neurocognitive differences in IGD. TASK AND DESIGN: fMRI and subjective data were collected from 119 subjects (IGD, male 29, female 25; recreational game use (RGU), male 34, female 31) when they were actively playing games and during a forced mandatory break. Analyses investigating effects of group (IGD, RGU) and gender (male, female) on the functional connectivity (FC) of executive control and reward systems linked to the dorsolateral prefrontal cortex (DLPFC) and striatum, respectively, were performed. Correlations between FC and subjective craving measures were also calculated.
Results:
Gaming-group-by-gender interactions were observed. During gaming in males but not in females, the FC between the DLPFC and superior frontal gyrus was relatively decreased, and that between the striatum and thalamus was relatively increased. During the mandatory break, changes in the FC between DLPFC and superior frontal gyrus and the FC between the striatum and thalamus varied by gender with greater RGU-IGD differences observed in females. Significant correlations between FC and self-reported craving were observed.
Conclusions:
During both gaming and a forced mandatory break, brain regions implicated in executive control and reward processing showed changes in FC that varied by gender. Brain regions implicated in executive control showed differential FC in males during gaming, and FC during the forced mandatory break appeared relevant to both genders, and perhaps particularly for females. The findings suggest possible neural mechanisms for why males appear more likely to develop IGD, and why it may be particularly difficult for individuals with IGD to cease gaming.
In recent years, researchers have been showing an increasing interest in the conceptualization of problematic Facebook use, and its associations with individual characteristics. The present meta-analysis aimed to summarize the findings of the recent literature on this topic with the aim of understanding the specific features of this phenomenon (that is, its associations with the time spent online and the broader concept of Internet addiction), and the individual characteristics of Facebook users (including gender differences, personality traits, self-esteem levels, and motivations for using Facebook). The sample included 56 independent samples with a total of 27,867 participants (59.22% females; mean age = 23.94 years (SD=4.75). Briefly, results showed a small gender effect favoring females and a positive association between problematic Facebook use, time spent online and Internet addiction, whereas a negative association was found with self-esteem. Neuroticism and conscientiousness were the most clearly personality traits associated with problematic Facebook use, and the strongest associations observed between problematic Facebook use and motives with internal source and motives with negative valence. This comprehensive meta-analysis makes contributions to understanding the phenomenon of problematic Facebook use and its relation with individual characteristics.
Little is known about how people use their smartphones, and whether usage patterns are related to psychopathology and problematic smartphone use. We sampled 296 college students, and administered self-report scales to assess frequency of using various smartphone features, and problematic smartphone use. We also assessed psychopathology constructs (ruminative thinking and emotion regulation deficits), and demographics (age and gender) as potential covariates of smartphone use patterns. Using latent class analysis, we identified two distinct classes of smartphone feature use, with one class representing especially heavy use (particularly that of social networking, audio and visual entertainment, and image- and video-taking), and the other class involving light use (particularly that of social networking, audio entertainment and image- and video-taking). Higher levels of rumination, and higher levels of cognitive reappraisal as an emotion regulation strategy, were related to the heavy use class. The heavy use class scored higher on all problematic smartphone use outcome variables. Results aid in understanding the nature and relation of smartphone usage patterns to psychopathology and problematic smartphone usage.
Research demonstrates that depression and anxiety symptom severity are related to problematic
smartphone use (PSU). However, less is known about variables mediating these relationships. This
study aimed to test whether proneness to boredom increased PSU. We also tested whether boredom proneness mediates relations between both depression and anxiety symptom severity with PSU. Using a cross-sectional design, we surveyed 298 American college students about their frequency of smartphone use, levels of PSU, depression, anxiety, and boredom proneness. Using structural equation modeling, we modeled depression and anxiety symptom severity predicting boredom proneness, in turn predicting levels of PSU and smartphone use frequency (SUF). Results demonstrate that boredom proneness predicted PSU, but not SUF. Boredom proneness mediated relations between both depression and anxiety symptom severity with PSU levels (but not usage
frequency). We discuss the phenomenon in terms of depressed or anxious college students having difficulty attending to their schoolwork, subsequently experiencing boredom, and engaging in PSU to relieve their boredom.
For many individuals, excessive smartphone use interferes with everyday life. In the present study, we recruited a non-clinical sample of 296 participants for a cross-sectional survey of problematic smartphone use, social and non-social smartphone use, and psychopathology-related constructs including negative affect, fear of negative and positive evaluation, and fear of missing out (FoMO). Results demonstrated that FoMO was most strongly related to both problematic smartphone use and social smartphone use relative to negative affect and fears of negative and positive evaluation, and these relations held when controlling for age and gender. Furthermore, FoMO (cross-sectionally) mediated relations between both fear of negative and positive evaluation with both problematic and social smartphone use. Theoretical implications are considered with regard to developing problematic smartphone use.
Little is known about the mechanisms of smartphone features that are used in sealing relationships between psychopathology and problematic smartphone use. Our purpose was to investigate two specific smartphone usage types – process use and social use – for associations with depression and anxiety; and in accounting for relationships between anxiety/depression and problematic smartphone use. Social smartphone usage involves social feature engagement (e.g., social networking, messaging), while process usage involves non-social feature engagement (e.g., news consumption, entertainment, relaxation). 308 participants from Amazon’s Mechanical Turk internet labor market answered questionnaires about their depression and anxiety symptoms, and problematic smartphone use along with process and social smartphone use dimensions. Statistically adjusting for age and sex, we discovered the association between anxiety symptoms was stronger with process versus social smartphone use. Depression symptom severity was negatively associated with greater social smartphone use. Process smartphone was more strongly associated with problematic smartphone use. Finally, process smartphone use accounted for relationships between anxiety severity and problematic smartphone use.
Unlabelled:
This study aimed to examine differences in muscle activity between young people with and without neck-shoulder pain (n = 20 in each group), when they performed texting on a smartphone. Texting was compared between using both hands ('bilateral texting') and with only one hand ('unilateral texting'). Texting tasks were also compared with computer typing. Surface electromyography from three proximal postural muscles and four distal hand/thumb muscles on the right side was recorded. Compared with healthy controls, young people with neck-shoulder pain showed altered motor control consisting of higher muscle activity in the cervical erector spinae and upper trapezius when performing texting and typing tasks. Generally, unilateral texting was associated with higher muscle loading compared with bilateral texting especially in the forearm muscles. Compared with computer typing, smartphone texting was associated with higher activity in neck extensor and thumb muscles but lower activity in upper and lower trapezius as well as wrist extensors.
Practitioner summary:
This study demonstrated that symptomatic individuals had increased muscle activity in the neck–shoulder region when texting on a smartphone. Contemporary ergonomic guidelines should include advice on how to interact with handheld electronic devices to achieve a relaxed posture and reduced muscle load in order to reduce the risk of musculoskeletal disorders.
Approximately 40% of mobile phone use studies published in scholarly communication journals base their findings on self-report data about how frequently respondents use their mobile phones. Using a subset of a larger representative sample we examine the validity of this type of self-report data by comparing it to server log data. The self-report data correlate only moderately with the server log data, indicating low criterion validity. The categorical self-report measure asking respondents to estimate “how often” they use their mobile phones fared better than the continuous self-report measure asking them to estimate their mobile phone activity “yesterday.” A multivariate exploratory analysis further suggests that it may be difficult to identify under- and overreporting using demographic variables alone.
The majority of research on cell phone use has focused on adolescent and young adult users with less attention on cell phone use by those older than 25 years of age. In this study, adult participants from 18-68 years completed a survey about their own use of cell phones and the contexts in which they considered cell phone use appropriate. There were age and gender differences in beliefs about the etiquette as to when cell phone use was appropriate. Older participants and women advocated for more restricted cell phone use in most social situations. Men differed from women in that they viewed cell phone calls as more appropriate in virtually all environments including intimate settings. Across all age groups in all communication settings, cell phones were used to text. The only exception was that romantic partners were more likely to receive a call than a text. In the younger age groups, texting communication is so normative that over 25% had dumped or were dumped by a romantic partner The preponderance of gender similarities point to cell phone usage as a stable communication vehicle for maintaining social contact.
Although the uses and gratifications approach lacks a single general theory, it is not inherently atheoretical, and the author suggests how progress can be made in dealing with four conceptual issues facing this tradition: the nature of the "active" audience; the role of gratification orientations in mediating effects; the social origins of media needs and uses; and the interest shared with students of popular culture in perceptions of and cognitions about mass media content formed by audience members.
The impact of different types of coping styles on adolescents' depressive symptoms was investigated in a prospective study. One hundred and ninety-four adolescents participated in 4 annual assessments of coping styles and depressive symptoms. Longitudinal analyses revealed long-term differences in depressive symptoms, depending on coping style. Adolescents with an approach-oriented coping style reported the fewest depressive symptoms at Time 3 and Time 4, whereas avoidant copers reported the most at both times. Higher levels of depressive symptoms 2 years later were found in all adolescents who used avoidant coping, irrespective of whether they used avoidant coping consistently at Time 1 and Time 2 or changed from approach-oriented coping to avoidant coping at Time 2. This effect was independent of gender and time. The results suggest that most adolescents show an overall adaptive way of coping, but a small subgroup shows a fairly rigid use of avoidant coping. They further suggest that all forms of avoidant coping, whether stable or not, were linked with high levels of depressive symptoms even 2 years later.
Results from a random sample of 532 college students show that students who made the heaviest use of SMS (Short Message Service) were motivated by its convenience, its low cost, and its utility for coordinating events. People who were socially anxious and were unwilling-to-communicate face-to-face and were put off by the confusing acronyms used in mobile messaging appeared to be those who spent less time, and not more, using SMS despite the fact that SMS could help overcome student’s shyness about bringing up difficult topics with friends. In broad terms, SMS is a social technology and has become a popular communication utility for college students.