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In recent years, there has been a growing need for social media platforms to offer services that preserve and promote users' digital wellbeing, including better protection of personal data and balanced technology usage. However, the current business model of social media is often seen as in conflict with users' digital wellbeing. In 2020, a study investigated users' willingness to pay monetary fees for social media digital wellbeing services. In the present work, we replicated this study in Q4 of 2022, aiming to explore any changes in interest and willingness to pay for these services. In addition, we extended the replication by conducting qualitative analysis on participants' comments to gain deeper insight and identify reasons for payment and reasons for rejecting to pay. Data were collected from 262 participants through an online questionnaire. The survey focused on four services: better data protection, less use of data for marketing, aiding users in controlling their prolonged usage, and reducing fake news and radicalisation on social media. The results showed that the willingness to pay for these services was significantly higher in 2022 compared to the results published in 2020. Participants expressed concerns about the feasibility and fairness of the alternative business model, which requires users to pay for safety and support. Our findings suggest a growing interest in digital wellbeing services, emphasizing the need for social media platforms to assess the feasibility of alternative business models, identify user segments, and take measures to enhance consumers' trust, accordingly.
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Purpose: The proliferation of smartphones, accompanied by internet facilities, has contributed to a decrease in sleep quality over the last decades. It has been revealed that excessive internet usage impacts the physical and mental health of smartphone users, while personality traits (PT) could play a role in developing internet addictions and preventing their negative effects. The objective of the present study is to assess the role of PT and smartphone usage in sleep quality. Method: The sample comprised 269 participants, 55% females, within the age range of 15-64 years. We objectively collected one-week smartphone apps usage data from the participants. They also responded to demographics and the PT (BFI-10) questionnaires. The usage data of smartphone apps were processed to calculate smartphone usage amounts and sleep variables, including sleep duration, sleep distraction, sleeping time, and wake-up time. The data were analyzed using the correlation coefficient and regression analyses. Results: The results indicated that more smartphone usage was associated with reduced sleep duration, increased sleep distraction, and later bedtime. Furthermore, smartphone users with the conscientiousness trait had a longer sleep duration, earlier sleeping time, less sleep distraction, and earlier wakeablity. Sleep distraction was positively associated with openness. Extraversion and neuroticism were found to be positive predictors of early wakeablity. Neuroticism had a negative association with early wakeablity. Finally, the implications of the study have been discussed. Conclusion: Our study's usage of data that was acquired objectively has strong methodological qualities. The present study is the first to contribute to the literature on the role of PT and objectively measured smartphone usage in the prediction of sleep quality. We found that smartphone use and sleep variables are associated with PT. Other scholars can use our dataset for benchmarking and future comparisons.
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Recent meta-analytical evidence indicates a mild association between higher neuroticism and lower conscientiousness scores and a tendency towards problematic social media use (PSMU). However, fear of missing out (FoMO) has emerged as a critical variable in understanding the positive link between neuroticism and PSMU. Given the replication crisis in psychology, this study aimed to reinvestigate personality-PSMU associations and, crucially, the less-studied FoMO mediation effect. To ensure generalizability of the findings, we recruited two diverse samples with European and Arabian backgrounds. The results revealed a significant total effect of neuroticism on PSMU for both cultural groups, with the European sample demonstrating a fully mediated effect via FoMO, whereas the Arab sample showed a partially mediated effect via FoMO, along with a significant direct effect. This study contributes to the existing literature by highlighting the importance of FoMO as a mediator between neuroticism and PSMU and some minor potential cultural differences in this association.
Assuntos
Mídias Sociais , Humanos , Personalidade , Neuroticismo , Árabes , MedoRESUMO
Purpose: The growing awareness and concern about the excessive use of social media have led to an increasing number of studies investigating the underlying factors contributing to this behavior. In the literature, it is discussed that problematic social media use (PSMU) can impact individuals' mental health and well-being. Drawing on the Interaction of Person-Affect-Cognition-Execution (I-PACE) model, this study aimed to examine the association between the need for affect (affect approach and affect avoidance) and PSMU (operationalized via the social media disorder scale), as well as the mediating role of fear of missing out (FoMO) in that relation. Participants and Methods: Data were collected via an online survey from 513 participants in European and Arabic countries. Regression and mediation analyses were conducted to explore the relationships between affect approach, affect avoidance, FoMO, and PSMU. Results: Regression analysis results indicated that both affect approach and affect avoidance as part of the need for affect construct significantly predicted PSMU in both cultural contexts. Mediation analysis showed that FoMO partially mediated the relationship between affect approach and PSMU in the Arab sample but not in the European sample. Beyond this, FoMO partially mediated the relationship between affect avoidance and PSMU in both cultural samples. Conclusion: The present study indicates that managing emotions could be an effective strategy to combat PSMU. In line with this and against the background of the data business model behind social media companies, we deem it to be of importance to minimize triggers related to FoMO in the design of social media platforms (for example, push notifications). This might be particularly relevant for individuals with a high inclination towards affect approach and affect avoidance.
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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 (ß = -.17), the actual usage of communication (ß = .17), social media (ß = .19) and gaming apps (ß = .13), and trait EI component of self-control (ß = -.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.