Determining Typical Smartphone Usage: What Data Do We Need?

Testing the validity of the smartphone pervasiveness scale for adolescents with self-reported objective smartphone use data

An ongoing and heated scientific debate pertains to the conceptualization and quantification of adolescents' problematic smartphone use (PSU). To address the limitations of existing surveys, the smartphone pervasiveness scale for adolescents (SPS-A) has been designed to measure the subjective frequency of smartphone usage during significant moments within daily routines. Given the weak correlations in prior literature between self-reported PSU metrics and objective use data, this study investigates the relationships between diverse self-reported objective metrics of smartphone engagement-that is duration, frequency, and count of notifications-and the SPS-A scale, employing a cohort of Swiss adolescents (N = 1396; Mage = 15.8, SDage = 0.81; 59% female). The findings reveal a substantial correlation between the total objectively measured duration of smartphone engagement and the SPS-A scale (r = .41 for iOS users and r = .42 for Android users). Moreover, a similar trend emerges as users are categorized by their level of objective use, with each category displaying a linear augmentation in smartphone pervasiveness levels. Instead, modest correlations emerge when considering the quantity of device unlocks and notifications. Noteworthy, no gender disparities emerged. These results add to our knowledge about the usefulness of the concept and measurement of smartphone pervasiveness: not only the SPS-A is a valid alternative to scales on "smartphone addiction" to capture non-pathological PSU, but it is also a better predictor of smartphone objective duration of use than self-reported measures. The correlation found between self-reported pervasiveness and actual use is discussed in light of the debate about the relevance of screen time in the study of PSU.

Problematic smartphone usage, objective smartphone engagement, and executive functions: A latent variable analysis

The negative consequences of smartphone usage have seen frequent discourse in popular media. While existing studies seek to resolve these debates in relation to executive functions, findings are still limited and mixed. This is partly due to the lack of conceptual clarity about smartphone usage, the use of self-reported measures, and problems related to task impurity. Addressing these limitations, the current study utilizes a latent variable approach to examine various types of smartphone usage, including objectively measured data-logged screen time and screen-checking, and nine executive function tasks in 260 young adults through a multi-session study. Our structural equation models showed no evidence that self-reported normative smartphone usage, objective screen time, and objective screen-checking are associated with deficits in latent factors of inhibitory control, task-switching, and working memory capacity. Only self-reported problematic smartphone usage was associated with deficits in latent factor task-switching. These findings shed light on the boundary conditions of the link between smartphone usage and executive functions and suggest that smartphone usage in moderation may not have inherent harms on cognitive functions.

Smartphone and Instagram use, body dissatisfaction, and eating disorders: investigating the associations using self-report and tracked data

BACKGROUND

Previous research has linked smartphone and Instagram use to higher body dissatisfaction (BD) as well as eating disorder (ED) symptomatology. However, these studies have typically been limited to using self-report measures for technology use which, as shown by scientific literature, might not be reliable. In the present work, we combine self-reported assessments as well as tracked smartphone and Instagram use.

METHODS

The effective sample comprised N = 119 women (34 with ED diagnosis history) who were queried about BD and ED symptomatology, and who provided the data about their smartphone and Instagram use duration for each day of the previous week.

RESULTS

The study results show that women with an ED diagnosis history scored higher on both BD as well as ED scales. Although women with an ED diagnosis history had higher smartphone screen time, there were no statistically significant differences in Instagram screen time. Tracked smartphone use duration was positively correlated with both BD and ED symptomatology, but the role of Instagram use needs to be further elucidated.

CONCLUSIONS

The results of this study show that while BD and ED symptomatology are correlated with smartphone use, it may be that Instagram use is not the main contributor to that relationship.

Strain, loss of time, or even gain? A systematic review of technology-based work extending and its ambiguous impact on wellbeing, considering its frequency and duration

Especially in knowledge-intensive professions, workers engage in work-related communication and access digital work content outside of working hours. Scientific research on technology-based work extending has flourished in recent decades, but yielded inconclusive results about its relationship with workers' wellbeing and focused on different temporal characteristics of the behaviour. Consequently, in this article, we address the question of whether different temporal characteristics of technology-based work extending, such as the frequency and duration of the behaviour, may have different consequences for workers' wellbeing. In the course of a systematic literature review, we analyzed 78 empirical studies published between 2007 and 2021 that investigate the relationship between the self-rated frequency and the self-rated duration of work extending behaviours and 14 wellbeing indicators. Whereas most studies examined the frequency of work extending behaviours and its consequences, only 19 studies examined the effects of its duration. Based on our findings, we propose three effects: The strain effect of frequent work extending, the gain effect of sustained work extending, and the loss-of-private-time effect inherent to work extending and independent from its frequency and duration. Our findings not only provide in-depth information on a widespread contemporary behaviour and its psychological implications, we also reveal research gaps and shed light on behaviours associated with role transitions and thus contribute to boundary theory.

Associations of smartphone usage patterns with sleep and mental health symptoms in a clinical cohort receiving virtual behavioral medicine care: a retrospective study

Study Objectives

We sought to develop behavioral sleep measures from passively sensed human-smartphone interactions and retrospectively evaluate their associations with sleep disturbance, anxiety, and depressive symptoms in a large cohort of real-world patients receiving virtual behavioral medicine care.

Methods

Behavioral sleep measures from smartphone data were developed: daily longest period of smartphone inactivity (inferred sleep period [ISP]); 30-day expected period of inactivity (expected sleep period [ESP]); regularity of the daily ISP compared to the ESP (overlap percentage); and smartphone usage during inferred sleep (disruptions, wakefulness during sleep period). These measures were compared to symptoms of sleep disturbance, anxiety, and depression using linear mixed-effects modeling. More than 2300 patients receiving standard-of-care virtual mental healthcare across more than 111 000 days were retrospectively analyzed.

Results

Mean ESP duration was 8.4 h (SD = 2.3), overlap percentage 75% (SD = 18%) and disrupted time windows 4.85 (SD = 3). There were significant associations between overlap percentage (p < 0.001) and disruptions (p < 0.001) with sleep disturbance symptoms after accounting for demographics. Overlap percentage and disruptions were similarly associated with anxiety and depression symptoms (all p < 0.001).

Conclusions

Smartphone behavioral measures appear useful to longitudinally monitor sleep and benchmark depressive and anxiety symptoms in patients receiving virtual behavioral medicine care. Patterns consistent with better sleep practices (i.e. greater regularity of ISP, fewer disruptions) were associated with lower levels of reported sleep disturbances, anxiety, and depression.

The interplay between social media use and problematic internet usage: Four behavioral patterns

Objective

The study aims to identify typical interplay between the use of social media apps on smartphones and Problematic Internet Usage (PIU).

Method

Our study utilizes data from a smartphone app that objectively monitors user usage, including the apps used and the start and finish times of each app session. This study included 334 participants who declared a need to be aware of their smartphone usage and control it. Problematic Internet Usage (PIU) was measured using the Problematic Internet Use Questionnaire-Short Form-6 (PIUQ-SF6). The total PIU score can range from 6 to 30, with a score above 15 indicating that a person is at risk of PIU. Time spent on Social Media (SM) apps of Facebook, WhatsApp, and Instagram, and whether people used each of these apps were studied along with the total PIU score. K-Prototype clustering was utilized for the analysis.

Results

Four distinct clusters, typifying the relationship between social media use and PIU, were identified. All the individuals in Cluster 1 (Light SM Use Cluster; Cluster size = 270, 80.84% of total dataset) spent between 0 and 109.01 min on Instagram, between 0 and 69.84 min on Facebook, and between 0 and 86.42 min on WhatsApp and its median PIU score was 17. Those who were in cluster 2 (Highly Visual SM Cluster; Cluster size = 23, 6.89% of total dataset) all used Instagram, and each member spent between 110 and 307.63 min on Instagram daily. The cluster median PIU score and average daily usage of Instagram were respectively 20 and 159.66 min. Those who were in Cluster 3 (Conversational SM Cluster; Cluster size = 19, 5.69% of total dataset) all used WhatsApp, and spent between 76.68 and 225.22 min on WhatsApp daily. The cluster median PIU score and average time spent per day on WhatsApp were 20 and 132.65 min, respectively. Those who were in Cluster 4 (Social Networking Cluster; (Cluster size = 22, 6.59% of total dataset) all used Facebook, and each spent between 73.09 and 272.85 min daily on Facebook. The cluster median PIU score and average time spent per day on Facebook were 18 and 133.61 min respectively.

Conclusion

The clusters indicate that those who use a particular social media app spend significantly less time on other social media apps. This indicates that problematic attachment to social media occurs primarily for one of three reasons: visual content and reels, conversations with peers, or surfing network content and news. This finding will help tailor interventions to fit each cluster, for example by strengthening interpersonal skills and resistance to peer pressure in the case of Cluster 3 and increasing impulse control in the case of Cluster 2.

A Preliminary Evaluation of the Effects of a Contingency Management + Deposit Contract Intervention on Problematic Smartphone Use With College Students

Problematic smartphone use (PSU) is smartphone usage that is, in some way, damaging to the user. PSU represents a growing public health concern that could be addressed via behavioral intervention. We recruited six college students who reported negative side effects of smartphone use and sought to decrease their PSU. The effects of a contingency management (CM) + deposit contract intervention on PSU was evaluated. During the CM + deposit contract condition, participants deposited $40 and had the opportunity to earn back their entire deposit by meeting daily smartphone usage goals. To promote adherence to study protocols, participants also had the opportunity to earn a $20 cooperation bonus. For all participants, lower levels of PSU were observed during intervention relative to baseline. The CM + deposit contract intervention produced consistent decreases in PSU for four participants (mean reduction percentages above 40% were obtained) and had inconsistent effects on PSU for two participants (mean reduction percentages below 20%). Maintenance of intervention effects was limited for all participants. Although preliminary, results suggest that CM + deposit contract interventions could be a viable, low-cost approach to addressing PSU. Potential explanations for our findings and avenues for future research are discussed.

Smartphone use and daily cognitive failures: A critical examination using a daily diary approach with objective smartphone measures

While smartphones have brought many benefits and conveniences to users, there is continuing debate regarding their potential negative consequences on everyday cognition such as daily cognitive failures. A few cross-sectional studies have found positive associations between smartphone use and cognitive failures. However, several research gaps remain, such as the use of cross-sectional designs, confounds related to stable individual differences, the lack of validity in self-report measures of smartphone use, memory biases in retrospective self-reports, and the lack of differentiation between smartphone checking and smartphone screen time. To simultaneously address the aforementioned shortcomings, the current study examined the within-person associations between various objective indicators of smartphone use and daily cognitive failures using a 7-day daily diary study. Multilevel modelling revealed that smartphone checking, but not total smartphone screen time, predicted a greater occurrence of daily cognitive failures at the within-person level. Surprisingly, we also found negative within-person associations between smartphone screen time for social- and tools-related applications and daily cognitive failures, suggesting that some types of smartphone use may temporarily benefit one's cognitive functioning. This finding demonstrates the importance of studying the specific functions of smartphone use and their differential cognitive consequences, as well as highlights the complex relations between smartphone use and cognition.

The Family Level Assessment of Screen Use-Mobile Approach: Development of an Approach to Measure Children's Mobile Device Use

BACKGROUND

There is a strong association between increased mobile device use and worse dietary habits, worse sleep outcomes, and poor academic performance in children. Self-report or parent-proxy report of children's screen time has been the most common method of measuring screen time, which may be imprecise or biased.

OBJECTIVE

The objective of this study was to assess the feasibility of measuring the screen time of children on mobile devices using the Family Level Assessment of Screen Use (FLASH)-mobile approach, an innovative method that leverages the existing features of the Android platform.

METHODS

This pilot study consisted of 2 laboratory-based observational feasibility studies and 2 home-based feasibility studies in the United States. A total of 48 parent-child dyads consisting of a parent and child aged 6 to 11 years participated in the pilot study. The children had to have their own or shared Android device. The laboratory-based studies included a standardized series of tasks while using the mobile device or watching television, which were video recorded. Video recordings were coded by staff for a gold standard comparison. The home-based studies instructed the parent-child dyads to use their mobile device as they typically use it over 3 days. Parents received a copy of the use logs at the end of the study and completed an exit interview in which they were asked to review their logs and share their perceptions and suggestions for the improvement of the FLASH-mobile approach.

RESULTS

The final version of the FLASH-mobile approach resulted in user identification compliance rates of >90% for smartphones and >80% for tablets. For laboratory-based studies, a mean agreement of 73.6% (SD 16.15%) was achieved compared with the gold standard (human coding of video recordings) in capturing the target child's mobile use. Qualitative feedback from parents and children revealed that parents found the FLASH-mobile approach useful for tracking how much time their child spends using the mobile device as well as tracking the apps they used. Some parents revealed concerns over privacy and provided suggestions for improving the FLASH-mobile approach.

CONCLUSIONS

The FLASH-mobile approach offers an important new research approach to measure children's use of mobile devices more accurately across several days, even when the child shares the device with other family members. With additional enhancement and validation studies, this approach can significantly advance the measurement of mobile device use among young children.

Problematic internet usage: the impact of objectively Recorded and categorized usage time, emotional intelligence components and subjective happiness about usage

Most research on Problematic Internet Usage (PIU) relied on self-report data when measuring the time spent on the internet. Self-reporting of use, typically done through a survey, showed discrepancies from the actual amount of use. Studies exploring the association between trait emotional intelligence (EI) components and the subjective feeling on technology usage and PIU are also limited. The current cross-sectional study aims to examine whether the objectively recorded technology usage, taking smartphone usage as a representative, components of trait EI (sociability, emotionality, well-being, self-control), and happiness with phone use can predict PIU and its components (obsession, neglect, and control disorder). A total of 268 participants (Female: 61.6%) reported their demographic and completed a questionnaire that included Problematic Internet Usage Questionnaire short form (PIUQ–SF–6), Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), level of happiness with the amount and frequency of smartphone use, and living conditions (whether alone or with others). Their smartphone usage was objectively recorded through a dedicated app. A series of one-way ANOVA revealed no significant difference in PIU for different living conditions and a significant difference in the subjective level of happiness with phone usage (F (3, 264) = 7.55, p < .001), as well as of the frequency of usage where the unhappy group had higher PIU (F (3, 264) = 6.85, p < .001). Multiple linear regression analysis showed that happiness with phone usage (β = −.17), the actual usage of communication (β = .17), social media (β = .19) and gaming apps (β = .13), and trait EI component of self-control (β = −.28) were all significant predictors of PIU. Moreover, gender, age, and happiness with the frequency of phone usage were not significant predictors of PIU. The whole model accounted for the total variance of PIU by 32.5% (Adjusted R² = .287). Our study contributes to the literature by being among the few to rely on objectively recorded smartphone usage data and utilizing components of trait EI as predictors.

Established Adults, Who Self-Identify as Smartphone and/or Social Media Overusers, Struggle to Balance Smartphone Use for Personal and Work Purposes

Smartphone ownership and use continues to proliferate, allowing people to easily access online communication, entertainment, and information. Importantly, individuals can perceive that they overuse their smartphone and/or the social media applications (apps) they access on their devices. Much of the research on smartphone overuse has focused on youth and emerging adults, with little research focusing on individuals in the established adulthood stage of life. This study examines smartphone use among established adults who perceive that they overuse their smartphone and/or social media. As part of a larger study, we conducted in-depth interviews with 21 individuals (30-45 years old) who self-identified as smartphone and/or social media overusers. Data were collected through a pre-survey, 1-hour interview, and smartphone use screenshots. Audio-recorded interviews were transcribed and then coded using NVivo software. Participants' average age was 35.9 years (SD = 4.1). The majority of the sample were female (67%), White (76%), and had a master's degree or higher (76%). Participants spent an average of 215 min on their smartphone daily, primarily using social media, video conferencing, and texting apps. Issues with smartphone use occurred when there was an unclear separation between work and personal use. Participants felt pressure to always respond quickly to work emails. An effort was made to limit smartphone use for work and during family time to be present for their family. Established adults strive to balance smartphone use for personal and work purposes. Creating boundaries for how and when established adults use their smartphone may help them find this balance.

Influence of digital environment on the cognitive function of schoolchildren and students

Aim. To analyze studies on the influence of digital environment on cognitive development of schoolchildren and students.

Material and methods. To achieve this aim, pedagogical research methods were used, which include work with literature on the stated topic, analysis of their content, logical generalization, citation, bibliographic listing, and annotation were used. An important role was played by generalization method and identification of patterns of longterm digital environment influence on a person.

Results. An analysis of the literature has shown that digital environment influence on cognitive development of schoolchildren and students is the subject of research by many authors. One group of scientists considers the digital environment to be a neutral factor in relation to younger generation cognitive function. But, in parallel, studies are being conducted in which scientists has the opposite position. This group includes Russian and Western scientists from Harvard, Oxford, Manchester, Sydney Universities and King’s College London. Over the past twenty years, from 1998 to 2018, they have conducted studies on the impact of electronic devices and the Internet on cognitive functions of the younger generation. In total, 139 papers were published, in which the authors studied the effect of digital environment on cognitive changes from the standpoint of psychology, psychiatry, neurobiology, and other sciences. These studies proved that digital environment affects, first of all, the change in the brain, which acts as a bioplatform for the formation of cognitive functions in schoolchildren and students. And a change in cognitive functions cannot but affect the cognitive processes of attention, memory, thinking, as well as the skills necessary for cognition.

Conclusion. The presented data from Russian and foreign studies revealed facts proving that the digital environment is a factor that changes the cognitive development in children, adolescents and students. The use of the Internet as an ultra-easy way to obtain information leads to the fact that a person blurs the boundaries between his own capabilities and the capabilities of electronic devices, attributing to himself their superpowers.

An Objective System for Quantitative Assessment of Television Viewing Among Children (Family Level Assessment of Screen Use in the Home-Television): System Development Study

BACKGROUND

Television viewing among children is associated with developmental and health outcomes, yet measurement techniques for television viewing are prone to errors, biases, or both.

OBJECTIVE

This study aims to develop a system to objectively and passively measure children's television viewing time.

METHODS

The Family Level Assessment of Screen Use in the Home-Television (FLASH-TV) system includes three sequential algorithms applied to video data collected in front of a television screen: face detection, face verification, and gaze estimation. A total of 21 families of diverse race and ethnicity were enrolled in 1 of 4 design studies to train the algorithms and provide proof of concept testing for the integrated FLASH-TV system. Video data were collected from each family in a laboratory mimicking a living room or in the child's home. Staff coded the video data for the target child as the gold standard. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were calculated for each algorithm, as compared with the gold standard. Prevalence and biased adjusted κ scores and an intraclass correlation using a generalized linear mixed model compared FLASH-TV's estimation of television viewing duration to the gold standard.

RESULTS

FLASH-TV demonstrated high sensitivity for detecting faces (95.5%-97.9%) and performed well on face verification when the child's gaze was on the television. Each of the metrics for estimating the child's gaze on the screen was moderate to good (range: 55.1% negative predictive value to 91.2% specificity). When combining the 3 sequential steps, FLASH-TV estimation of the child's screen viewing was overall good, with an intraclass correlation for an overall time watching television of 0.725 across conditions.

CONCLUSIONS

FLASH-TV offers a critical step forward in improving the assessment of children's television viewing.

Behavioral Consistency in the Digital Age

Efforts to infer personality from digital footprints have focused on behavioral stability at the trait level without considering situational dependency. We repeated a classic study of intraindividual consistency with secondary data (five data sets) containing 28,692 days of smartphone usage from 780 people. Using per-app measures of pickup frequency and usage duration, we found that profiles of daily smartphone usage were significantly more consistent when taken from the same user than from different users (d > 1.46). Random-forest models trained on 6 days of behavior identified each of the 780 users in test data with 35.8% accuracy for pickup frequency and 38.5% accuracy for duration frequency. This increased to 73.5% and 75.3%, respectively, when success was taken as the user appearing in the top 10 predictions (i.e., top 1%). Thus, situation-dependent stability in behavior is present in our digital lives, and its uniqueness provides both opportunities and risks to privacy.

Piloting Smartphone Digital Phenotyping to Understand Problematic Internet Use in an Adolescent and Young Adult Sample

Problematic Internet use (PIU) preferentially affects youth development, particularly youth with psychiatric conditions. Studies attempting to understand PIU and its impact on adolescent mental health have been limited by cross-sectional design and self-report data. Even with a small sample size, digital phenotyping (DP) methodology can address these limitations through repeated sampling and collection of survey and sensor data through personal smartphones. This study pilots a 6-week DP protocol in 28 youth in mental health treatment in order to assess relationships between PIU, mood symptoms, and daily behaviors like smartphone engagement and daily travel in this high-risk population. Our results found shared associations between depression and PIU, where symptom severity of both worsened in the setting of decreased smartphone engagement. These clinically relevant findings indicate that, rather than uniformly worsening mental health, increased digital engagement may actually provide short-term relief from negative affect in youth with psychiatric comorbidities.

Loneliness unlocked: Associations with smartphone use and personality

Communication and relationships have been dramatically altered among emerging adults thanks to the rapid adoption of the smartphone in just over a decade. Studying the effects of evolving personal technology helps researchers understand both the detriments of widespread adoption and the benefits that accompany the technology. One such area of concern is the relationship of technology with loneliness. Emerging adulthood is described as the period of transition from adolescence to adulthood, taking place from age 18-25. This period is characterized by change, exploration, but also a vulnerability to psychological distress. Young adults are not only at greater risk of loneliness compared to other developmental stages, but report greater distress about being lonely (Rokach, 2000). Previous research has found support for the hypothesis that use of social communication on the Internet has a bidirectional relationship with loneliness (Nowland et al., 2018); use of the Internet can support relationships and decrease loneliness, but if used as a compensation for social skill deficits, the Internet can also displace quality time spent in relationships, and thereby increase loneliness. This study examines loneliness and its relationship with smartphone use, while also accounting for individual differences in facets of neuroticism, communication apprehension, emotional support, and nomophobia for emerging adults. Participants (N = 302; M_AGE = 18.85) completed self-report measures of loneliness and the individual differences variables. They also reported average daily smartphone data of screen time, pickups, and application (app) use, which was measured by their personal devices. Correlations indicated loneliness was positively associated with screen time, social media app use, neuroticism, social recognition, communication anxiety, and nomophobia. Loneliness was negatively associated with smartphone pickups, communication application use, need for affiliation, and emotional support. A regression analysis revealed that neuroticism, need for affiliation, social recognition, emotional support, and smartphone pickups were significant predictors of loneliness, when taking into account all the individual difference and smartphone use variables. Neuroticism and loneliness have a strong relationship, but a hierarchical regression showed that over and above neuroticism and its facets, smartphone screen time and pickups predict loneliness. Overall, the results for this sample of emerging adults supported the hypotheses by Nowland et al. (2018) about social use of the Internet, but applied to smartphone use. More time spent on one's smartphone and on social media apps is related to increased loneliness, and is discussed in context of identity development. More frequent use (pickups) and use of communication apps is related to decreased loneliness and is discussed with respect to development of relationship intimacy. These results suggest that loneliness in young adults is related to different types of smartphone use, even when accounting for stable characteristics such as personality. Finally, neuroticism remains a significant variable in understanding loneliness, and further examination of lower-order facets help define a more nuanced profile in individual differences.

Effects of young adults' smartphone use for social media on communication network heterogeneity, social capital and civic engagement

Purpose

This study examines the direct and indirect effect mechanisms of how using smartphones for social media is associated with college students' civic engagement via levels of communication network heterogeneity and social capital. In addition, this study tests whether such indirect effects mechanisms are moderated by the need to belong.

Design/methodology/approach

The study analyzes data from an online survey (N = 580) conducted at a public university. The PROCESS macro is used to examine the mediation association between mobile social media use, communication network heterogeneity, social capital, and civic engagement and the moderated mediation conditional upon need to belong.

Findings

College students who often use smartphones for social media were more likely to communicate with people who have different socio-demographic characteristics and different opinions. There was also a positive mediation mechanism between smartphone use for social media, network heterogeneity, social capital and civic engagement, which means that college students who often use mobile social media are more likely to communicate with heterogeneous others and develop a sense of social capital, which in turn led to greater levels of civic engagement. Importantly, these indirect effects of smartphone use for social media on civic engagement were stronger for those with greater levels of need to belong.

Originality/value

The findings of the current study are significant given that little is known about how young adults' mobile social media use is associated with communication network heterogeneity and civic engagement in their everyday life. The research expands the research agenda by investigating the most popular interactive communication media platforms.

Link between Excessive Smartphone Use and Sleeping Disorders and Depression among South Korean University Students

The purpose of this study was to explore the link between smartphone use and sleeping disorders and depression among university students in South Korea. South Korea has the highest mobile phone penetration rate as well as the highest rate of suicide of any of the Organization for Economic Cooperation and Development (OECD) nations, thus making this study of great importance. The core aim was to see whether the excessive use of smartphones has an association with sleeping disorders and depression. A cross-sectional analysis was performed to establish if there was any link between smartphone use and sleeping disorders and depression. Samples from 188 participants were used for this study. Data were collected using two well-established questionnaires, the Center for Epidemiologic Studies-Depression (CES-D) and the Athene Insomnia Scale (AIS), as well as a few questions on smartphone use. A few demographic questions were added to the questionnaire. The results of this study concluded that a significant relationship exists between smartphone use and depression. However, the finding of this research could not uncover a significant relationship between smartphone use and sleeping disorders among university students in South Korea. The excessive use of smartphones shows a relationship to an unhealthy lifestyle. There is a clear indication that the overuse of smartphones could be linked to depression. Furthermore, the study found that students with depression also tend to have sleeping disorders.

Open-source smartphone app and tools for measuring, quantifying, and visualizing technology use

Psychological science has spent many years attempting to understand the impact of new technology on people and society. However, the frequent use of self-report methods to quantify patterns of usage struggle to capture subtle nuances of human-computer interaction. This has become particularly problematic for devices like smartphones that are used frequently and for a variety of purposes. While commercial apps can provide an element of objectivity, these are 'closed' and cannot be adapted to deliver a researcher-focused 'open' platform that allows for straightforward replication. Therefore, we have developed an Android app that provides accurate, highly detailed, and customizable accounts of smartphone usage without compromising participants' privacy. Further recommendations and code are provided to assist with data analysis. All source code, materials, and data are freely available (see links in supplementary materials section).

Absence of Objective Differences between Self-Identified Addicted and Healthy Smartphone Users?

Smartphones are used by billions of people worldwide. However, some psychologists have argued that use of this technology is addictive, even though little research utilises objective smartphone usage records to verify this claim. We conducted an exploratory study to identify whether behavioural differences exist between those who self-identify as addicted smartphone users and those who do not. We gathered retrospective smartphone usage data from 131 Android users and asked them about their past use to compare their perception of their usage against their actual usage. We could not identify any reliable differences between the smartphone activity of those self-identified as addicted smartphone users and other users. Furthermore, smartphone scales are generally good at identifying who believes themselves to be addicted, although they do not reflect objective smartphone use. This study questions the use of self-report measures to diagnosis behavioural addictions without relevant psychopathological constructs and emphasises the need for more rigorous study to conceptualise smartphone addiction.

Investigating Associations Between Screen Time and Symptomatology in Individuals With Serious Mental Illness: Longitudinal Observational Study

BACKGROUND

Increasing screen time exposure from digital devices like smartphones has shown a variety of mixed associations with cognition, behavior, and well-being in adults and children but little is known about its associations with symptomatology in individuals with serious mental illness.

OBJECTIVE

To determine the range of associations between screen time and symptoms of individuals with mental illness, we utilized a method called specification curve analysis.

METHODS

In this observational study, we recruited smartphone-owning adults (≥18 years old) with schizophrenia and healthy controls. We installed 2 research-source smartphone apps, mindLAMP and Beiwe, to collect survey results, cognitive test results, and screen time metrics over a period of 3 months. Surveys were scheduled for twice a week, but participants were instructed to take the surveys naturally as much or as little as they wanted. Screen time was collected continuously in the background. A total of 140 participants was recruited from the outpatient clinic population as well as through general public advertising. Age-matched, smartphone-owning healthy controls were also part of the recruitment pool. A specification curve analysis was a priori designed to explore the relationship between every combination of independent variable and dependent variable in order to demonstrate to what degree screen time relates to symptoms in individuals with serious mental illness.

RESULTS

The sample consisted of 88 participants (54 with schizophrenia and 34 healthy controls) who completed both the initial and follow-up visits, completed at least one self-reported survey, and had a minimum passive data cutoff of 5 consecutive days. While we found an association between smartphone screen time metrics and cognition (adjusted R²=0.107, P<.001), specification curve analysis revealed a wide range of heterogenous associations with screen time from very negative to very positive. The effects differed based on diagnostic group, age bracket, type of regression model used, and the specific independent and dependent variables selected for analysis.

CONCLUSIONS

The associations between screen time and mental health in patients with schizophrenia are heterogenous when examined with methods that reduce analytical bias. The heterogeneity in associations suggests that complex and personalized potential effects must be understood in the greater context of an individual. This analysis of longitudinally collected screen time data shows potential for future research that could benefit from high resolution metrics on smartphone use.

Does excessive use of smartphones and apps make us more impulsive? An approach from behavioural economics

Purpose

Problematic smartphone use has been associated with negative effects in work and school environments. This study proposes the application of a behavioural economics perspective to establish whether heavy smartphone users show a tendency to devalue the consequences of their behaviour in the long term. To address this proposition, the study sought to establish how an objective measurement of usage time of smartphones and apps might help to predict, firstly, participants’ choice behaviour and, secondly, their perceived dependence levels.

Design/methodology/approach

An objective measurement of the usage time of smartphones and apps was conducted over four weeks (N = 560 data points), and a computer-based intertemporal choice task and the Spanish version of the Smartphone Addiction Inventory (SPAI) were applied. The participants were twenty undergraduate college students.

Findings

Although the usage time of devices and apps failed to predict the choice behaviour, a correlation was found between the total usage time of smartphones and WhatsApp and Facebook apps and users’ dependence level. On the other hand, dependence had a positive effect on the average selection of the impulsive choice.

Originality/value

This paper proposes the application of a behavioural economics perspective to explore the relationship between objectively measured usage time of smartphone and apps, choice behaviours in an intertemporal task and users’ perceived dependence levels. This allows us to consider an alternative to the traditional psychiatric approach in an environment of increasing access to and use of mobile digital platforms.

Validation of Self-Reported Smartphone Usage Against Objectively-Measured Smartphone Usage in Hong Kong Chinese Adolescents and Young Adults

OBJECTIVE

This study evaluated the validity of self-reported smartphone usage data against objectively-measured smartphone usage data by directly tracking the activities in the participants' smartphone among Chinese adolescents and young adults in Hong Kong.

METHODS

A total of 187 participants were recruited (mean age 19.4, 71.7% female) between 2017 and 2018. A smartphone usage tracking app was installed on all participants' smartphone for 7 consecutive days. After the 7-day monitoring period, they completed a selfadministered questionnaire on smartphone usage habits.

RESULTS

Although the correlation between self-reported and objectively-measured total smartphone usage time was insignificant (ρ=-0.10, p=0.18), in three out of the four usage domains were positively and significantly correlated, namely social network (ρ=0.21, p=0.005), instant messaging (ρ=0.27, p<0.001), and games (ρ=0.64, p<0.001). Participants' self-report of the total time spent on smartphones exceeded the objective data by around 760 min per week (self-reported 1,930.3 min/wk vs. objectively-measured 1,170.7 min/wk, p<0.001). Most of the over-reporting was contributed by the web browsing domain (self-reported 447.8 min/wk vs. objectively-measured 33.3 min/wk, p<0.001).

CONCLUSION

Our results showed large discrepancies between self-reported smartphone and objectively-measured smartphone usage except for self-reported usage on game apps.

Anomaly detection to predict relapse risk in schizophrenia

The integration of technology in clinical care is growing rapidly and has become especially relevant during the global COVID-19 pandemic. Smartphone-based digital phenotyping, or the use of integrated sensors to identify patterns in behavior and symptomatology, has shown potential in detecting subtle moment-to-moment changes. These changes, often referred to as anomalies, represent significant deviations from an individual's baseline, may be useful in informing the risk of relapse in serious mental illness. Our investigation of smartphone-based anomaly detection resulted in 89% sensitivity and 75% specificity for predicting relapse in schizophrenia. These results demonstrate the potential of longitudinal collection of real-time behavior and symptomatology via smartphones and the clinical utility of individualized analysis. Future studies are necessary to explore how specificity can be improved, just-in-time adaptive interventions utilized, and clinical integration achieved.

Associations between Problematic Smartphone Use, Unhealthy Behaviors, and Mental Health Status in Korean Adolescents: Based on Data from the 13th Korea Youth Risk Behavior Survey (2017)

OBJECTIVE

We aimed to assess the associations between problematic smartphone use, unhealthy behaviors, and mental health status among adolescents.

METHODS

The data for this cross-sectional study were obtained from the 13th Korea Youth Risk Behavior Survey (2017). From among the 62,276 adolescents who participated in this nationwide web-based survey, 54,603 (87.7%) who used smartphones were selected as the study population. Unhealthy behaviors included smoking, drinking, physical inactivity, skipping breakfast, and fast food consumption. For the examination of mental health status, we considered sleep disturbances, stress, depressive symptoms, suicidal ideation, and suicide attempts. The associations between problematic smartphone use, unhealthy behaviors, and mental health were analyzed using multiple logistic regression analyses.

RESULTS

More than four hours of use on weekdays (31.3%) and weekends (61.3%) and the use of smartphones for communication (46.9%) were associated with unhealthy behaviors and mental health problems. Furthermore, adolescents who experienced conflicts with family (22.3%) and friends (25.8%) and academic problems (3.4%) were likely to have health problems.

CONCLUSION

The results suggest that problematic smartphone use may disrupt adolescents' health. Therefore, there is a need for prevention programs for problematic smartphone use at home and at school to improve adolescents' health.

Fear of Missing Out (FoMO) and social media's impact on daily-life and productivity at work: Do WhatsApp, Facebook, Instagram, and Snapchat Use Disorders mediate that association?

Fear of Missing Out (FoMO) is the tendency to experience anxiety over missing out on rewarding experiences of others. It has been associated with daily-life disruptions, such as distractions during driving. FoMO has also consistently been a predictor of Internet, smartphone, and social networks use disorders. In the current work, we investigated the association between FoMO and social media use's impact on daily-life and productivity at work. In addition, we aimed to determine whether WhatsApp, Facebook, Instagram, and Snapchat Use Disorders mediate that relationship. The effective sample comprised 748 German-speaking study participants from the general population (age M = 38.63, SD = 12.10; 336 men, 412 women) who took part in an online survey study. Bivariate analyses showed that severity of all social networks use disorders were positively correlated with FoMO and social media's negative impact on daily-life and productivity at work. Furthermore, controlling for age and gender, mediation analyses showed that out of all platforms, only Snapchat Use Disorder did not mediate the association between FoMO and social media's negative impact on daily-life and productivity at work. These results provide further evidence about FoMO's central role in digital technology use-related disorders.

Comparing Smartphone, WhatsApp, Facebook, Instagram, and Snapchat: Which Platform Elicits the Greatest Use Disorder Symptoms?

In recent years, smartphone and social networking services (SNS) use have received a great amount of scholarly attention regarding their potentially addictive effects. Conceptualized as smartphone or SNS use disorder, research has consistently demonstrated relations with daily-life impairments. However, Smartphone Use Disorder (SmUD), WhatsApp Use Disorder (WAUD), Facebook Use Disorder (FBUD), Instagram Use Disorder (IGUD), or Snapchat Use Disorder (SCUD) scores have not been compared with each other. This comparison could provide insight into which device/platform could be most related to daily-life impairments. The effective sample of this study comprised 439 German-speaking individuals (age M = 25.08, SD = 9.74; 271 women) who reported actively using a smartphone, as well as WhatsApp, Facebook, Instagram, and Snapchat, and responded to the respective use disorder scales. Within-subjects analysis of variance and post hoc tests (p values adjusted with the Holm method) were used to compare smartphone and SNS use disorder scale scores. The results suggest that SmUD scores are highest in comparison with other SNS platforms. Although WAUD and IGUD scores did not differ from each other, these scores were higher than for FBUD and SCUD. SCUD scores were higher than FBUD scores. These results provide novel insight into how the smartphone and different SNSs may relate to engagement in problematic digital technology use.

Cognition in Context: Understanding the Everyday Predictors of Cognitive Performance in a New Era of Measurement

Background

Research suggests that variability in attention and working memory scores, as seen across time points, may be a sensitive indicator of impairment compared with a singular score at one point in time. Given that fluctuation in cognitive performance is a meaningful metric of real-world function and trajectory, it is valuable to understand the internal state-based and environmental factors that could be driving these fluctuations in performance.

Objective

In this viewpoint, we argue for the use of repeated mobile assessment as a way to better understand how context shapes moment-to-moment cognitive performance. To elucidate potential factors that give rise to intraindividual variability, we highlight existing literature that has linked both internal and external modifying variables to a number of cognitive domains. We identify ways in which these variables could be measured using mobile assessment to capture them in ecologically meaningful settings (ie, in daily life). Finally, we describe a number of studies that have already begun to use mobile assessment to measure changes in real time cognitive performance in people’s daily environments and the ways in which this burgeoning methodology may continue to advance the field.

Methods

This paper describes selected literature on contextual factors that examined how experimentally induced or self-reported contextual variables (ie, affect, motivation, time of day, environmental noise, physical activity, and social activity) related to tests of cognitive performance. We also selected papers that used mobile assessment of cognition; these papers were chosen for their use of high-frequency time-series measurement of cognition using a mobile device.

Results

Upon review of the relevant literature, it is evident that contextual factors have the potential to meaningfully impact cognitive performance when measured in laboratory and daily life environments. Although this research has shed light on the question of what gives rise to real-life variability in cognitive function (eg, affect and activity), many of the studies were limited by traditional methods of data collection (eg, involving retrospective recall). Furthermore, cognition has often been measured in one domain or in one age group, which does not allow us to extrapolate results to other cognitive domains and across the life span. On the basis of the literature reviewed, mobile assessment of cognition shows high levels of feasibility and validity and could be a useful method for capturing individual cognitive variability in real-world contexts via passive and active measures.

Conclusions

We propose that, through the use of mobile assessment, there is an opportunity to combine multiple sources of contextual and cognitive data. These data have the potential to provide individualized digital signatures that could improve diagnostic precision and lead to meaningful clinical outcomes in a wide range of psychiatric and neurological disorders.

Teenagers, screens and social media: a narrative review of reviews and key studies

INTRODUCTION

In light of growing concerns about an increasingly digital adolescence, the academic field investigating how digital technologies affect adolescents' psychological well-being is growing rapidly. In the last years, much research has amassed, and this has been summarised in over 80 systematic reviews and meta-analyses.

MATERIALS AND METHODS

Systematic reviews, meta-analyses and key studies are reviewed to provide insights into the state of current research linking digital technology and social media use to well-being; possible future directions and improvements are discussed.

RESULTS

When examining the reviews, it becomes evident that the research field is dominated by cross-sectional work that is generally of a low quality standard. While research has highlighted the importance of differentiating between different types of digital technology use many studies do not consider such necessary nuances. These limitations aside, the association between digital technology use, or social media use in particular, and psychological well-being is-on average-negative but very small. Furthermore, the direction of the link between digital technology use and well-being is still unclear: effects have been found to exist in both directions and there has been little work done to rule out potential confounders.

CONCLUSIONS

Reviewing the last decade of reviews in the area, it is evident that the research field needs to refocus on improving transparency, interpreting effect sizes and changing measurement. It also needs to show a greater appreciation for the individual differences that will inherently shape each adolescent's reaction to digital technologies.

A simple location-tracking app for psychological research

Location data gathered from a variety of sources are particularly valuable when it comes to understanding individuals and groups. However, much of this work has relied on participants’ active engagement in regularly reporting their location. More recently, smartphones have been used to assist with this process, but although commercial smartphone applications are available, these are often expensive and are not designed with researchers in mind. To overcome these and other related issues, we have developed a freely available Android application that logs location accurately, stores the data securely, and ensures that participants can provide consent or withdraw from a study at any time. Further recommendations and R code are provided in order to assist with subsequent data analysis.

Rumination and negative smartphone use expectancies are associated with greater levels of problematic smartphone use: A latent class analysis

Problematic smartphone use (PSU) is related to psychopathology symptoms, such as depression and anxiety. However, less is known about how responses to and coping with psychopathology correlate with PSU. We conducted a web survey of 286 American college students, querying depression and anxiety symptoms, rumination (a coping process to avoid negative emotion), PSU, and expectancies about smartphone use for mood alleviation. We conducted latent class analysis (LCA) of PSU symptom ratings, finding support for two latent subgroups of participants, involving mild and severe PSU, especially distinguished by severity of withdrawal symptoms. Rumination and negative smartphone use expectancies (i.e., to reduce distress) positively related to the more symptomatic PSU class. Results are discussed in context of the I-PACE theoretical model of problematic internet use (PIU). We emphasize the importance of response variables in I-PACE, such as internet-related cognitive bias and coping, over background psychopathology variables in influencing PIU and PSU.

Passive objective measures in the assessment of problematic smartphone use: A systematic review

Research focussing on problematic smartphone use has predominantly employed psychometric tests which cannot capture the automatic processes and behaviours associated with problematic use. The present review aimed to identify passive objective measures that have been used or developed to assess problematic smartphone use. A systematic search was conducted using Web of Science, Scopus, PsychInfo and PubMed databases to identify passive objective measures that have been employed to assess problematic smartphone use, resulting in 18 studies meeting the inclusion criteria. Objective data that were monitored predominantly focussed on general screen usage time and checking patterns. Findings demonstrate that passive monitoring can enable smartphone usage patterns to be inferred within a relatively short timeframe and provide ecologically valid data on smartphone behaviour. Challenges and recommendations of employing passive objective measures in smartphone-based research are discussed.

Digital detox: The effect of smartphone abstinence on mood, anxiety, and craving

Whether behavioural addictions should be conceptualised using a similar framework to substance-related addictions remains a topic of considerable debate. Previous literature has developed criteria, which allows any new behavioural addiction to be considered analogous to substance-related addictions. These imply that abstinence from a related object (e.g., smartphones for heavy smartphone users) would lead to mood fluctuations alongside increased levels of anxiety and craving. In a sample of smartphone users, we measured three variables (mood, anxiety, and craving) on four occasions, which included a 24-hour period of smartphone abstinence. Only craving was affected following a short period of abstinence. The results suggest that heavy smartphone usage does not fulfil the criteria required to be considered an addiction. This may have implications for other behavioural addictions.

Smartphone use and study behavior: A Korean and Australian comparison

Smartphone use amongst university students is widespread and a common practice while studying. However, this usage can lead to academic performance costs. This study examined the relationship between smartphone use during study, problematic smartphone use and academic performance in Korean and Australian university students. 119 Korean and 270 Australian students aged between 18 and 26 years completed a survey comprised of a smartphone usage questionnaire, smartphone addiction scale and self-report of their current GPA score. Average smartphone use and problematic smartphone use were found to be significantly higher for Korean compared to Australian students. A positive relationship was found between smartphone use and problematic smartphone use. For Australian students, a negative relationship was found between smartphone use and GPA. Results indicate that smartphone use and smartphone addiction proneness are currently higher for Korean students compared to Australian students. Furthermore, the more time a student spends using their smartphone, the more at risk they are for problematic smartphone use and possible academic performance costs.