Problematic smartphone use in a large nationally representative sample: Age, reporting biases, and technology concerns

Sports and exercise-related smartphone use is antagonistic to hedonic use in regular exercisers: A cross-sectional study examining the roles of exercise frequency and duration

Background

Hedonic smartphone use has been associated with dependence and addiction studied under the umbrella term Problematic Smartphone Use (PSU). Research usually explores total screen time as an index of PSU. A few studies suggest that exercise is inversely related to smartphone use time. However, it is unknown which primary characteristics of exercise behavior are related to more moderate smarthone use. Furthermore, the purpose of smartphone use, such as hedonic use associated with PSU versus utilitarian use, was not tested in the sports and exercise contexts. Hedonic use generally means playing with the smartphone for joy, distraction, and satisfaction. Utilitarian use implies practical and valuable use. There is a conjecture that sports involvement may foster utilitarian use through increased involvement in sports-related information-seeking, goal-setting, and self-monitoring.

Methods

Therefore, we examined whether weekly exercise frequency, workout duration, and perceived exercise intensity relate to total daily smarthone and hedonic use and whether this relationship is mediated by sports-related utilitarian device use. We tested regularly exercising adults (n = 360, 132 males, M age = 39.0 ± 9.8, M weekly exercise = 5.8 ± 1.9) who volunteered for this study and provided demographic information about their exercise habits and smartphone use.

Results

The results revealed that all exercise parameters mediated the total daily smartphone use, with perceived exercise intensity being a negative predictor. Further, exercise frequency and duration (but not intensity) positively predicted sports-related smartphone use, which inversely predicted hedonic use.

Conclusion

These results suggest that exercise parameters directly relate to daily smartphone use, which completely mediates hedonic use. These findings may partially account for the frequently reported inverse relationship between regular exercise and PSU by suggesting that the connection is mediated via sports-related smartphone use.

Fatigue, Internet Addiction and Symptoms of Long COVID-A Cross-Sectional Study of Polish Students

Introduction: Fatigue is the most persistent symptom in patients with long COVID. Moreover, Internet addiction itself has become a pandemic long-term effect. The aim of this study was to investigate the degree of fatigue and Internet addiction in a group of students with COVID-19 and to determine the relationship between fatigue and addiction in students with and without long COVID symptoms. Material and methods: A cross-sectional study was conducted among 402 Polish students aged 19-26. The 183 students who had COVID-19 signaled the presence of long COVID symptoms, which corresponded to 45.5% of the surveyed group. The Modified Fatigue Impact Scale was used to assess the level of fatigue, and the Kimberly Young questionnaire was used to assess the level of Internet addiction. Results: 19.7% (95% c.i.: 15.9-23.9%) of the students surveyed had a moderate level of Internet dependence (Internet addiction measure value of 50 points or more). Most of them did not complain of high levels of fatigue. Higher levels of dependence and fatigue were observed in subjects with long COVID symptoms (MFIS mean value was 26.5 in this group vs. 17.7 in the others; p = 0.0000 ***). The higher the respondents' level of dependence, the more they tended to feel tired (correlations were stronger in those with long COVID symptoms: rS = 0.23; p = 0.0017 **). Conclusions: In view of the results obtained, the study presented here has the potential to contribute to the international debate on the long-term health consequences of the COVID-19 pandemic and strategies to address them. The study provides data that may be useful in the development of educational and health policies that target the psychophysical well-being of patients with long COVID symptoms. This process should be considered as a long-term endeavor.

Measuring algorithmic bias to analyze the reliability of AI tools that predict depression risk using smartphone sensed-behavioral data

AI tools intend to transform mental healthcare by providing remote estimates of depression risk using behavioral data collected by sensors embedded in smartphones. While these tools accurately predict elevated depression symptoms in small, homogenous populations, recent studies show that these tools are less accurate in larger, more diverse populations. In this work, we show that accuracy is reduced because sensed-behaviors are unreliable predictors of depression across individuals: sensed-behaviors that predict depression risk are inconsistent across demographic and socioeconomic subgroups. We first identified subgroups where a developed AI tool underperformed by measuring algorithmic bias, where subgroups with depression were incorrectly predicted to be at lower risk than healthier subgroups. We then found inconsistencies between sensed-behaviors predictive of depression across these subgroups. Our findings suggest that researchers developing AI tools predicting mental health from sensed-behaviors should think critically about the generalizability of these tools, and consider tailored solutions for targeted populations.

Measuring algorithmic bias to analyze the reliability of AI tools that predict depression risk using smartphone sensed-behavioral data

AI tools intend to transform mental healthcare by providing remote estimates of depression risk using behavioral data collected by sensors embedded in smartphones. While these tools accurately predict elevated symptoms in small, homogenous populations, recent studies show that these tools are less accurate in larger, more diverse populations. In this work, we show that accuracy is reduced because sensed-behaviors are unreliable predictors of depression across individuals; specifically the sensed-behaviors that predict depression risk are inconsistent across demographic and socioeconomic subgroups. We first identified subgroups where a developed AI tool underperformed by measuring algorithmic bias, where subgroups with depression were incorrectly predicted to be at lower risk than healthier subgroups. We then found inconsistencies between sensed-behaviors predictive of depression across these subgroups. Our findings suggest that researchers developing AI tools predicting mental health from behavior should think critically about the generalizability of these tools, and consider tailored solutions for targeted populations.

Validation of a modified problematic use of mobile phones scale to examine problematic smartphone use and dependence

Over the past decade, the world population has experienced rapid and widespread adoption of smartphones due to their usefulness and convenience. However, researchers have identified a range of adverse behaviours associated with the adoption of smartphones and their higher use. These behaviours are collectively described as Problematic Smartphone Use and Dependence (PSUD). Despite growing research, the underlying processes and drivers leading to these behaviours are inadequately understood. This can partly be attributed to the absence of developed statistical tools and measures that allow researchers to build a comprehensive conceptual understanding of PSUD. To address this issue, this study proposes and evaluates a validated extension to the Problematic Use of Mobile Phones (PUMP) scale. The extension of this tool incorporates factors associated with substance dependence outlined in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), including additional items to measure PSUD accurately, referred to as the modified problematic use of mobile phones (MPUMP) scale. The newly developed tool was used in a cross-sectional online survey during September and October 2022, drawing on 1018 adult Australian participants. Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) were conducted to derive the underlying factors. The EFA revealed two distinct factors: Distraction and Dysregulation. Both factors exhibited high internal consistency, with Cronbach's Alpha coefficients of 0.92 and 0.86, respectively. A one-way analysis of variance (ANOVA) revealed significant variations inthe identified factors' mean scores across different socio-demographic characteristics. The study provides evidence that the MPUMP scale is a validated and reliable measure for accurately assessing PSUD. The study findings offer novel insights into the psychosocial and physical aspects of PSUD, providing a foundation for exploring the causes and potential interventions for PSUD.

Associations between nature exposure, screen use, and parent-child relations: a scoping review protocol

BACKGROUND

Today's youth are growing up in an evolving digital world, and concerns about the potential detrimental effects of excessive screen use on biopsychosocial outcomes in childhood are mounting. Parents worry about the impacts of screen-use on their children's wellbeing but at the same time frequently fail to meet their own ideal screen time limits regarding their children's screen use. There is an opportunity to shift research focus away from inflexible and often unrealistic childhood screen time guidelines towards exploration of positive parenting strategies that may have multiple beneficial and significant effects on children's screen-related outcomes. An emerging body of literature suggests that screen time and nature exposure act on psychosocial outcomes in contrasting ways. There is evidence to suggest that exposure to natural environments may counteract some of the potential negative psychosocial effects of excessive screen use; however, this relationship is poorly understood. The overarching aim of this scoping review is to source, categorise, and synthesise existing research exploring the associations between nature exposure, screen use, and parenting across childhood.

METHODS

This mixed-methods systematic scoping review will be conducted following Arksey and O'Malley's framework with methodological enhancements from Levac and associates and recommendations from the Joanna Briggs Institute's methodological guidance for conducting scoping reviews. Five electronic databases will be searched from August 2022 onwards. Two reviewers will independently screen titles, abstracts, and full-text articles. Peer reviewed articles related to the constructs of nature exposure, screen use, and parent/child relations will be considered in the context of early to late childhood. Study characteristics will be collated using a data charting tool collaboratively developed by the research team. Evidence will be presented using tabular and textual form and described using qualitative thematic analysis.

DISCUSSION

This review will gather information about how key definitions are conceptualised, defined, and measured across the literature and map existing trends and areas for future research. It is intended that this review will inform and guide future research direction, recommendations, and programs aimed at supporting parents to navigate the challenges of parenting in a digital age. OSF REGISTRATION: https://doi.org/10.17605/OSF.IO/TFZDV.

Excessive Smartphone Use is Associated with Depression, Anxiety, Stress, and Sleep Quality of Australian Adults

Problematic smartphone use has been associated with poorer mental health in different population groups; however, little is known about how levels of smartphone use were associated with mental health outcomes of adults in Australia. Using data from a cross-sectional survey among Australian adults aged 18-59 years (n = 655, Mean = 24.55 [SD = 5.59] years; 66% female), the current study aimed to examine association between problematic smartphone use and different psychological outcomes. Participants completed measures of problematic smartphone use with Mobile Phone Problem Use Scale (MPPUS), mental health outcomes with Depression, Anxiety, and Stress Scale (DASS-21), and Pittsburgh Sleep Quality Index (PSQI), in addition to some socio-demographics. Smartphone use was categorised into three groups: low-moderate, moderate-high, and high-severe. A total of 160 adults (24.4%) reported high-severe smartphone use. Multivariable linear regression analyses showed that smartphone use was inversely associated with psychological outcomes in a dose-dependent manner with high-severe smartphone uses having the most adverse effects. Compared to low-moderate use, average depression score was 3.5 points higher for moderate-high smartphone use (β = 3.51, 95% CI: 1.63-5.40) and 6.9 points higher for high-severe smartphone use (β = 6.91, 95% CI: 4.74-9.07). Similarly, average stress score was 3.4 points higher for moderate-high smartphone use (β = 3.40, 95% CI: 1.75-5.06) and 7.0 points higher for high-severe smartphone use (β = 7.02, 95% CI: 5.11-8.93). Similar association estimates were found for anxiety and sleep quality. Reducing smartphone use has the potential to optimise depression, anxiety, stress, and sleep quality; however, longitudinal research is warranted to establish directionality of the association.

Evaluating the Effectiveness of Apps Designed to Reduce Mobile Phone Use and Prevent Maladaptive Mobile Phone Use: Multimethod Study

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.

Psychometric validation of the Chinese version of the desire thinking questionnaire in adolescent mobile phone users

BACKGROUND

Desire thinking is a conscious and voluntary cognitive process that is closely linked to levels of craving and addictive behaviors. The Desire Thinking Questionnaire (DTQ) can be used to measure desire thinking in all age groups as well as in addicts. This measurement has also been translated into several languages. This study aimed to test the psychometric properties of the Chinese version of the DTQ (DTQ-C) among adolescent mobile phone users.

METHODS

One thousand and ninety-seven adolescents who own a mobile phone and are younger than 18 years old completed the DTQ-C and a battery of questionnaires assessing the big five personality traits, negative affect, brooding, self-control, craving, and problematic mobile phone use (PMPU). The psychometric analyses of the DTQ-C were conducted, including exploratory factor analysis (EFA), confirmatory factor analysis (CFA), reliability, and validity analysis.

RESULTS

The EFA revealed a 10-item two-factor structure (i.e., verbal perseveration and imaginal prefiguration) that was confirmed by the CFA. The results of CFA showed fit indexes of χ²/df = 4.83, CFI = 0.967, TLI = 0.954, RMSEA = 0.059, SRMR = 0.032. The total scale had internal consistency reliabilities of 0.93, which demonstrated that DTQ-C presented good reliability. The two dimensions were correlated with PMPU (r_{verbal perseveration} = 0.54; r_{imaginal prefiguration} = 0.45), neuroticism (r_{verbal perseveration} = 0.18; r_{imaginal prefiguration} = 0.14), conscientiousness (r_{verbal perseveration} = -0.19; r_{imaginal prefiguration} = -0.18), depression (r_{verbal perseveration} = 0.22; r_{imaginal prefiguration} = 0.16), anxiety (r_{verbal perseveration} = 0.26; r_{imaginal prefiguration} = 0.22), stress (r_{verbal perseveration} = 0.15; r_{imaginal prefiguration} = 0.10) and self-control (r_{verbal perseveration} = -0.29; r_{imaginal prefiguration} = -0.26), which demonstrated that DTQ-C presented good concurrent validity. The two factors of DTQ-C correlated weakly with brooding (ranging from 0.08 to 0.10). The principal component factor analysis of the two dimensions of desire thinking and craving showed that craving and desire thinking belonged to different dimensions. Both of which showed good divergent validity of desire thinking. Additionally, an examination of incremental validity revealed that two factors were both positively associated with PMPU beyond demographic characteristics, big five personality traits, negative affect, and self-control (B_{verbal perseveration} = 0.49 and B_{imaginal prefiguration} = 0.13).

CONCLUSIONS

It has been found that the 10-item DTQ-C is a reliable and valid measure of desire thinking in Chinese adolescent mobile phone users.

Impact of smartphone overuse on 1-year severe depressive symptoms and momentary negative affect: Longitudinal and experience sampling findings from a representative epidemiological youth sample in Hong Kong

Smartphone overuse can have detrimental impacts on youth mental health. How it may be longitudinally associated with depressive symptoms and functioning, and with daily momentary affect, remains to be investigated. A total of 3,033 young people were consecutively recruited from a large-scale epidemiological youth mental health study in Hong Kong. A subsample (n = 936) was followed-up after 1 year, with experience sampling data collected from 177 participants. Separate multivariable logistic regression models were applied to examine the prospective associations between smartphone overuse and depressive symptoms, with multilevel models fitted to examine its associations with momentary affect. The prevalence of smartphone overuse in the Hong Kong youth population was 29.3%. Smartphone overuse was significantly associated with more depressive symptoms and functional impairments both cross-sectionally and longitudinally. The associations between smartphone overuse and 1-year depressive symptoms were significant, even when accounting for baseline symptoms, social media use, and other risk and protective factors. Baseline depressive symptoms, in contrast, were not associated with 1-year smartphone overuse after adjusting for baseline smartphone overuse. Smartphone overuse was also significantly associated with higher levels of momentary negative affect, even when accounting for depressive symptoms. Strategies to mitigate the impact of smartphone overuse can have important long-term implications.

How and for Whom Is Mobile Phone Addiction Associated with Mind Wandering: The Mediating Role of Fatigue and Moderating Role of Rumination

With the increasing prevalence of mobile phone addiction, mobile phone addiction has been considered a prominent risk factor for internalizing or externalizing problems, such as psychological distress and irrational procrastination. However, few studies shed light on the effect of mobile phone addiction on mind wandering and the underlying mechanisms. This study speculated that the direct effect of mobile phone addiction on mind wandering may be linked to fatigue and that the level of an individual's personality characteristics, such as rumination, may influence both the direct and indirect effects of mobile phone addiction on mind wandering. To test these hypotheses, we recruited 1811 college students to complete the self-report questionnaires. The results indicated that mobile phone addiction was positively associated with mind wandering. This direct effect could be mediated by fatigue, and both the direct and indirect effects of mobile phone addiction on mind wandering could be moderated by rumination. Specifically, both the direct and indirect effects were stronger for students with high rumination. These findings enrich our understanding of how, why, and for whom mobile phone addiction is correlated with mind wandering.

The Roles of Primary Emotional Systems and Need Satisfaction in Problematic Internet and Smartphone Use: A Network Perspective

Problematic Internet and smartphone use (PIU and PSU, respectively) have received significant attention over the past years. In the current work, we studied the associations between PIU and PSU, primary emotional systems, and need satisfaction. The effective sample comprised 399 people who responded to scales measuring these variables. Bivariate correlation analysis showed that both PSU and PIU were positively associated with negative primary emotion traits (FEAR, ANGER, SADNESS) as well as lower scores on most of the need satisfaction factors. Network analysis showed that while PIU and PSU have a strong association with each other, in general, there were not many significant correlations between PSU, PIU, and other variables in the network. The associations being present were rather weak. Network analysis showed that PSU was positively associated with FEAR, ANGER, PLAY primary emotional systems. Both PSU and PIU had a negative association with safety and security and physiological needs satisfaction. Moreover, PSU had a positive link with belongingness need satisfaction, while higher PIU was associated with lower esteem and self-actualization need satisfaction. Addressing those unmet needs may be helpful in reducing problematic technology use, but further research testing this would be necessary.