Procrastination on Social Networks: Triggers and Countermeasures

Procrastination on social networking sites (SNS) can impact academic performance and user’s well-being. SNSs embed features that encourage users to be always connected and updated, e.g., the notification features. Such persuasive features can exploit peer pressure as well and lead users to believe they are expected to interact immediately, especially for those who may have less impulse control and seek for relatedness and popularity. We argue that SNS can be built to host countermeasures for such behavior and help people regulate their usage and preoccupation about it better. In this paper, we presented a mixed-method study including a qualitative (i.e., focus groups, diary, interviews, and co-design) and a quantitative phase (i.e., a survey) with 334 participants. Through the qualitative phase, we identified: (1) features of an SNS seen by participants as facilitators for procrastination, e.g., notification, immersive design, and surveillance of presence, and (2) countermeasures, such as reminders, chat timer, and goal setting, can be facilitated via SNS design to combat procrastination, and (3) a pairing between the features and the countermeasures. We then (4) confirmed these results and the pairing through the survey phase. Our study showed that countermeasures could be implemented to be universal across all SNS on one or even more device

The Impact of Objectively Recorded Smartphone Usage and Emotional Intelligence on Problematic Internet Usage

This study examined the effects of gender, age, objective smartphone usage data, and Emotional Intelligence (EI) on Problematic Internet Use (PIU) and its components (obsession, neglect, and control disorder). The study relied on objective data of smartphone usage as a representative of technology use collected by a monitoring application of smartphone usage. PIU and EI were measured through the Problematic Internet Usage Questionnaire short form (PIUQ-SF-6) and Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), respectively. The current cross-sectional study was carried out with 268 participants (Female: 61.6%, ages from 15 to 64) from ten different countries. The analysis was performed using multiple linear regression. The results of the multiple regression models showed that gender and age did not reveal a significant influence on PIU or its components. Smartphone usage had a positive and significant effect on PIU, while EI inversely and significantly affected PIU and accounted for 24.6% of PIU total variance. Similarly, smartphone usage and EI significantly affected the PIU components, accounting for 15.9% of obsession variance, 12.9% of neglect variance, and 16.4% of control disorder variance. Our findings contribute to the literature by objectively evaluating the influence of time spent using the internet on PIU. It is one of the first studies to rely on objectively measured smartphone usage data and compare findings to previous studies that relied on self-reported data. When used to regulate usage, the monitoring applications of smartphone usage should be better contextualized to reflect users’ psychometrics

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

Smartphone Usage before and during COVID-19: A Comparative Study Based on Objective Recording of Usage Data

Most studies that claimed changes in smartphone usage during COVID-19 were based on self-reported usage data, e.g., that collected through a questionnaire. These studies were also limited to reporting the overall smartphone usage, with no detailed investigation of distinct types of apps. The current study investigated smartphone usage before and during COVID-19. Our study used a dataset from a smartphone app that objectively logged users’ activities, including apps accessed and each app session start and end time. These were collected during two periods: pre-COVID-19 (161 individuals with 77 females) and during COVID-19 (251 individuals with 159 females). We report on the top 15 apps used in both periods. The Mann–Whitney U test was used for the inferential analysis. The results revealed that the time spent on smartphones has increased since COVID-19. During both periods, emerging adults were found to spend more time on smartphones compared to adults. The time spent on social media apps has also increased since COVID-19. Females were found to spend more time on social media than males. Females were also found to be more likely to launch social media apps than males. There has also been an increase in the number of people who use gaming apps since the pandemic. The use of objectively collected data is a methodological strength of our study. Additionally, we draw parallels with the usage of smartphones in contexts similar to the COVID-19 period, especially concerning the limitations on social gatherings, including working from home for extended periods. Our dataset is made available to other researchers for benchmarking and future comparisons