Objectively‐measured and self‐reported smartphone use in relation to surface learning, procrastination, academic productivity, and psychopathology symptoms in college students

Unveiling the relationship between social anxiety, loneliness, motivations, and problematic smartphone use: A network approach

BACKGROUND

Previous studies suggested social anxiety as an essential risk factor for problematic smartphone use, but the complex interactions and the most influential components affecting this relationship remain unclear. This study capitalizes on network analysis to identify the central factors and possible mediating paths among social anxiety, loneliness, five types of motivation, and problematic smartphone use.

MATERIAL AND METHODS

Employing 549 emerging adults, we obtained a stable network of the above variables. The central components and the stability of this network were also identified.

RESULTS

Within this network, the edge linking withdrawal behavior and use of application (APP) exhibits the most robust edge intensity. The central components include social comfort, use of APP, withdrawal behavior, and companionship while the bridge central nodes include social anxiety and escapism motivation. The direct link between social anxiety and PSU revealed only fragile edges with both withdrawal behavior and use of APP. Considering the possible mediating pathways, three pathways were observed in our network. Loneliness and escapism mediated the relationship between social anxiety and social comfort. Moreover, another mediating way was from social anxiety, loneliness, social interaction motivation, and escapism motivation to social comfort.

DISCUSSION

Based on the above identification of related components and pathways, future researchers could intervene against problematic smartphone usage in this socially anxious population.

Procrastination Mediates the Relationship between Problematic TikTok Use and Depression among Young Adults

Background: Although the prevalence of depression has increased significantly in recent years, especially in the young adult population, little is known about its causes and risk factors. The study aims to examine the mediating role of TikTok use in the relationships between procrastination and depression in young adults. Methods: A sample of 448 adults, ranging in age from 18 to 35 years (M = 24.45, SD = 3.76), including 214 men (48%), participated in the study. The cross-sectional survey consists of a modified Bergen Facebook Addiction Scale (BFAS) to assess problematic TikTok use (PTTU), the Pure Procrastination Scale (PPS) for procrastination measurement, and the nine-item Patient Health Questionnaire (PHQ-9) for screening depression symptoms. Results: The independent samples t-test indicates that emerging adults (ages ranging between 18 and 25 years) have more severe depression symptoms than young adults (26-35 years old). Gender differences were not found for procrastination, PTTU, and depression symptoms. Positive correlations were found between procrastination, PTTU, and depression symptoms. PTTU plays a mediating role in the associations between procrastination and depression. Conclusions: Both procrastination and PTTU treatment should be prioritized in the prevention and intervention programs for improving mental health among young adults. Some effective therapeutic methods are recommended.

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.

Bidirectional relations between problematic smartphone use and bedtime procrastination among Chinese university students: Self-control as a mediator

OBJECTIVE

Based on theoretical and empirical evidence, this study examined the longitudinal relationship between problematic smartphone use and bedtime procrastination and the potential mediating role of self-control.

METHODS

Between November 2021 and November 2022, a three waves longitudinal design was employed. Wave 1 included 622 Chinese college students (46.95% male, Mage = 18.16, SD = 0.73), with 6-month intervals between waves. The data was collected using self-report assessments.

RESULTS

The results of the cross-lagged panel models show that problematic smartphone use positively predicted later bedtime procrastination, and the bedtime procrastination also positively predicted later problematic smartphone use among college students. More importantly, self-control played a mediating role in their bidirectional predictive relationship.

CONCLUSIONS

These findings add to the understanding of the causal relationship between problematic smartphone use and bedtime procrastination and reveal the core psychological mechanisms underlying their vicious cycle, with important practical implications for the prevention and intervention of problematic smartphone use and sleep problems.

Fear of missing out and problematic smartphone use among Chinese college students: The roles of positive and negative metacognitions about smartphone use and optimism

BACKGROUND

Problematic smartphone use (PSU) has become a common phenomenon among college students. Fear of missing out (FoMO) is an important factor affecting PSU, but how FoMO affects PSU is not clear. Therefore, the mediating effect of positive and negative metacognitions about smartphone use (PMSU and NMSU) and the moderating effect of optimism are explored.

METHODS

514 Chinese college students aged 17 to 25 from 6 Chinese universities were investigated with the Trait-State FoMO Scale, the Metacognitions about Smartphone Use Questionnaire, the Temperament Optimism Scale, and the Smartphone Addiction Scale for College Students. The data were analyzed with SPSS software.

RESULTS

FoMO was positively associated with PSU, PMSU and NMSU mediated this association. Optimism moderated the relationship between FoMO and PSU, i.e., FoMO had a less prominent positive effect on PSU for college students with a high level of optimism.

CONCLUSIONS

There is a positive relationship which exists between FoMO and PSU among college students. In addition, PMSU and NMSU play mediating roles in FoMO and PSU, and optimism plays an moderating role in FoMO and PSU. These findings can help not only educators understand the predictors of PSU and develop interventions to effectively prevent PSU among college students but also college students reduce the level of PSU by improving their understanding of PMSU and NMSU and optimism level.

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.

Understanding the construction of 'behavior' in smartphone addiction: A scoping review

It has been claimed that smartphone usage constitutes a behavioral addiction, characterised by compulsive, excessive use of one's phone and psychological withdrawal or distress when the phone is absent. However, there is uncertainty about key phenomenological and conceptual details of smartphone addiction. One of the central problems has been understanding the processes that link smartphone usage, and addiction. The question this paper aims to answer is straightforward: based on measures utilised in the literature, what does 'behavior' mean in the context of smartphone addiction? A scoping review of the smartphone addiction literature was undertaken. This identified 1305 studies collecting smartphone addiction data. Just under half (49.89%) of all published smartphone addiction papers did not report the collection of any smartphone specific behaviors. Those that did tended to focus on a small cluster of self-reported behaviors capturing volume of overall use: hours spent using a smartphone per day, number of pickups, duration of smartphone ownership, and types of app used. Approximately 10% of papers used logged behavioral data on phones. Although the theoretical literature places increasing focus on context and patterns of use, measurements of behavior tend to focus on broad, volumetric measures. The number of studies reporting behavior has decreased over time, suggesting smartphone addiction is becoming increasingly trait-like. Both major phone operating systems have proprietary apps that collected behavioral data by default, and research in the field should take advantage of these capabilities when measuring smartphone usage.

Phoning It in: Social Anxiety, Intolerance of Uncertainty, and Anxiety Reduction Motivations Predict Phone Use in Social Situations

Based on meta-analysis, a strong link between social anxiety and phone use has been established in the literature, but the underlying mechanisms of why social anxiety might cause people to use their phones are poorly understood. Intolerance of uncertainty is a transdiagnostic factor of many anxiety disorders and may help explain why socially anxious people tend to use their mobile phones as a tool to cope with, or distract from, inherently ambiguous social interactions. This nonexperimental, correlational study had four core aims: to examine whether increases in social anxiety would relate to (1) increased phone usage during social interactions in groups or (2) phone dependency; to examine whether intolerance of uncertainty and motivation of phone use mediated either of these relationships. To test these models, an opportunity sample of 252 participants completed a series of online questionnaires containing measures of social anxiety, intolerance of uncertainty, and phone usage. Correlational analysis of results showed increased phone dependency and phone use in social groups for people with high social anxiety. Serial mediation analysis showed that people who were more socially anxious also reported higher levels of intolerance of uncertainty, greater motives to use phones to reduce anxiety, and higher phone use. We discuss these results with specific reference to compensatory internet use theory. In sum, it appears that for people with social anxiety, phone use in social situations tends to be motivated by reducing anxiety.

Smartphones and Learning: An Extension of M-Learning or a Distinct Area of Inquiry

The smartphone has become an integral part of the education landscape. While there has been significant smartphone research in education under the guise of m-learning, the unique role of the device suggests that m-learning may not be an appropriate characterization. The purpose of this paper is to review the use of m-learning as a primary descriptor for smartphone- and learning-related research. In support of this goal, the paper reviews the definitions associated with m-learning, smartphones, and related technologies from the perspective of educational research. In addition, a review of author keywords of research on smartphones in education is used to provide context to the classification of the research. Finally, three theoretically guided smartphone programs are presented as evidence of the unique nature of smartphone and learning research. This review concludes with recommendations for the characterization of future research.