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Abstract Challenging others who post misinformation is a type of social correction that complements algorithm-based approaches. However, participation rates in such social acts remain limited. In this paper, we study design techniques that leverage principles of persuasive system design and communication theories to foster such prosocial behaviour across two distinct cultural contexts: the British and the Arab. A total of 462 participants completed an online survey (250 UK, 212 Arabs). The study compared the two cultural contexts regarding willingness to challenge misinformation and the persuasiveness of seven design techniques to increase that willingness, namely predefined question stickers, thinking face reaction, sentence openers, fact checker badge, social norm messages, tone detector, and private commenting. Moreover, it explores the impact of individuals’ characteristics on their perception of the techniques as being more or less persuasive than a standard comment box. The study found that the willingness to challenge misinformation was significantly higher in the Arab context than in the UK context. Moreover, except for the private commenting, all techniques were more impactful in the Arab context than in the UK context. Some techniques, such as predefined question stickers, were more effective in both cultures compared to the standard comment box, while others, like the fact checker badge, were more effective only in the Arab context. However, in the UK, sentence openers had a lower impact. Furthermore, personality traits, age, and perspective-taking showed the potential but also the varying impacts on the persuasiveness of the techniques on users’ correction of misinformation across both cultural contexts while pointing to the need for considering both personal and cultural factors in designing social-correction-based solutions.

Recommendation agents (RAs) have proven to be effective decision-making tools for customers, as they can boost trust and loyalty when customers shop online. They can analyse large amounts of data using machine learning algorithms and predictive analytics capabilities to provide highly relevant recommendations to users. In previous studies, several approaches have been implemented to refine and assess the effectiveness of these agents. As a new form of virtual reality universe, metaverses can be seen as a new venue for improvements in the performance of online RAs. By exploiting the capabilities of the metaverse and incorporating data about the user's behaviour and preferences, the performance of these systems can be enhanced in terms of the accuracy, diversity, and novelty of the generated recommendations. The metaverse can provide visually appealing and interactive recommendations, and there are several potential factors that can affect the customer's experience. The cognitive-affective-behavioural theory is used to develop the proposed research model. This study investigates the impact of the capabilities of the metaverse on three quality factors of RAs: diversity, accuracy, and novelty. The influence of the quality of the recommendations on affective trust and the influence of affective trust on customer loyalty are also examined. In addition, as this is an emerging technology, perceived privacy plays a crucial role in maintaining users' trust and confidence. Hence, the moderating influence of perceived privacy on the relationship between the quality and affective trust of RAs is examined. The moderating impact of product knowledge on the relationship between the individual perception of trust and loyalty is investigated. Data were acquired from 288 Malaysian respondents and analysed using the PLS-SEM method. The findings of this study show that the capabilities of the metaverse have favorable impacts on several quality factors of the recommender system, including accuracy, diversity, and novelty. Furthermore, these quality factors impact the perceived quality of RAs, which in turn impacts customer trust and loyalty. Perceived privacy acts as a moderator on the relationship between the quality of recommendations and the individual's perception of trust.

Abstract Background Family and school environment play a crucial role across the different developmental stages of adolescence. This paper investigates the potential mediating role of family and school environments in the relationship between the three psychosocial predictors of depression, anxiety, stress, and Internet addiction (IA). Specifically, it focuses on the two stages of early and middle adolescence. Methods The study involved a survey of 407 adolescents from Qatar, comprising 250 early adolescents and 157 middle adolescents. Inclusion criteria for the study included adolescents between the ages of 10 to 17 years old, residents of Qatar and studying in a Qatar-based school. To assess the constructs of the three psychosocial predictors, IA, family environment, the study utilized the Depression, Stress, and Anxiety Scale (DASS), the Internet Addiction Diagnostic Questionnaire (IADQ), and the Brief Family Relationship Scale, respectively. School environment was measured using questions from the “Health Behavior in School-aged Children: WHO Collaborative Cross-National survey/study (HBSC) 2013–2014. The study applied standard mediation analysis between the DASS components and IA with family and school environment as the mediators. Results Results from the mediation analysis reveal insights into the relationships between psychosocial predictors and IA. The findings indicate that family and school environments partially mediated the relationship with regards to depression, stress, and anxiety in early adolescents. In middle adolescents, family environment partially mediated the relationship with depression and stress and fully mediating the relationship with anxiety. Meanwhile, school environment only exhibited partial mediation in the relationship with anxiety in middle adolescence. Conclusions These results highlight the crucial role parents and schools play in addressing problematic technology usage that develops as a response to depression, anxiety, and stress among adolescents. Moreover, the study reveals nuances in the mediating role of family and school environment in early and middle adolescence. This highlights the evolving nature of these influences across the different stages of development. Notably, this study contributes to the literature by moving beyond the conventional focus on the so-called WEIRD population, and offering valuable insights from a region that is underrepresented in current research.

Abstract This study explores the impact of Internet addiction (IA), age, and essential and non-essential technology usage time on the physical and mental fatigue of adolescents. The research surveyed 477 adolescents from Qatar and employed the Internet Addiction Diagnostic Questionnaire (IADQ) and Chalder's Fatigue Scale for data collection. Multiple linear regression and Mann–Whitney U tests were utilized for analysis. The findings indicate that IA, non-essential usage time, and age are positively associated with overall fatigue among adolescents. IA and non-essential usage time are positively linked to physical fatigue, while IA, non-essential usage time, and age are positive predictors of mental fatigue. However, essential usage time is negatively associated with mental fatigue. These results highlight the importance of distinguishing technology usage based on intent and necessity, as well as differentiating between physical and mental fatigue when examining problematic technology usage. This study is among the few conducted in the Middle Eastern context.

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.

In recent years, concerns over the potential negative impacts of social network sites (SNS) on users’ digital wellbeing are on the rise. These concerns have sparked a growing demand for SNS to introduce changes to their business model and offer features that prioritize users’ wellbeing, even if it means introducing fees to users. Still, it is questionable whether such a new model is welcomed by users and commercially valid. In this paper, we investigate (i) people’s willingness to pay (WTP) for digital wellbeing services designed to foster more autonomy, control, and personal growth in users and (ii) the influence of sociodemographic variables, personality, and social networks use disorder (SNUD) on WTP. Data were collected through an online survey with participants from two distinct cultural contexts, the European and Arabic. The samples comprised 262 participants from Europe (Males: 57.63%) and 251 from Arab countries (Males: 60.56%). The participants ranged in age from 18 to 66 years (MEurope = 29.16, SD = 8.42; MArab = 31.24, SD = 8.23). The results revealed that a notable proportion of participants were willing to pay for digital wellbeing services (Europe: 24%; Arab: 30%). Females in the European sample demonstrated a higher WTP for “Mental Health Issues Minimization” compared to males. In the Arab sample, males showed a higher WTP for “Safeguarding Data Privacy” than females. Multiple regression analyses revealed that SNUD and the need for cognition emerged as significant and positive predictors of WTP in both the European and Arab samples. Differences in the relations of personality traits and sociodemographic variables on WTP in each sample were noted. These insights contribute to our understanding of the factors shaping individuals’ preferences and valuation related to digital wellbeing services on SNS and highlight the importance of considering sociodemographic variables and personal factors as well as cultural contexts when planning and introducing them.

Abstract Background This is one of the few studies that examines adolescent Internet addiction (IA) among Middle Eastern population. The purpose of this study is to determine whether adolescents’ family and school environments play a role in their Internet Addiction. Methods We conduced a survey that included 479 adolescents in Qatar. The survey collected demographic data, the Internet Addiction Diagnostic Questionnaire (IADQ), the Brief Family Relationship Scale (BFRS) and questions from the WHO Health Behavior in School-aged Children (HBSC) survey that assess school environment, academic performance, teacher support, and peer support of the adolescents. Factorial analysis, multiple regression, and logistic regression were used for statistical analysis. Results Family environment and school environment were negative and significant predictors of adolescent Internet addiction. The prevalence rate was 29.64%. Conclusion Results imply that interventions and digital parenting programs should not only target adolescents, but also include entities in the developmental environment of adolescents, i.e. their family and school.

Recent advancements in machine learning have spurred an increased integration of AI in critical sectors such as healthcare and criminal justice. The ethical and legal concerns surrounding fully autonomous AI highlight the importance of combining human oversight with AI to elevate decision-making quality. However, trust calibration errors in human-AI collaboration, encompassing instances of over-trust or under-trust in AI recommendations, pose challenges to overall performance. Addressing trust calibration in the design process is essential, and eXplainable AI (XAI) emerges as a valuable tool by providing transparent AI explanations. This paper introduces Calibrated-XAI (C-XAI), a participatory design framework specifically crafted to tackle both technical and human factors in the creation of XAI interfaces geared towards trust calibration in Human-AI collaboration. The primary objective of the C-XAI framework is to assist designers of XAI interfaces in minimising trust calibration errors at the design level. This is achieved through the adoption of a participatory design approach, which includes providing templates, guidance, and involving diverse stakeholders in the design process. The efficacy of C-XAI is evaluated through a two-stage evaluation study, demonstrating its potential to aid designers in constructing user interfaces with trust calibration in mind. Through this work, we aspire to offer systematic guidance to practitioners, fostering a responsible approach to eXplainable AI at the user interface level.

Artificial intelligence (AI) is built into many products and has the potential to dramatically impact societies around the world.This short theoretical paper aims to provide a simple framework that might help us understand how the introduction and/or use of products with AI might influence the well-being of humans.It is proposed that considering the dynamic Interplay between variables stemming from Modality, Person, Area, Culture and Transparency categories will help to understand the influence of AI on well-being. The Modality category encompasses areas such as the degree of AI being interactive, informational versus actualizing, or autonomous. The Person variable contains variables such as age, gender, personality, technological self-efficacy, and perceived competence when interacting with AI, whereas the Area variable can comprise a certain product where AI is in-built or a certain domain where AI is used to make a difference (such as the health sector, military sector, education sector, etc.). The Culture variable is of importance to understand because cultural settings might shape attitudes towards AI. Finally, this might also be true for transparent AI (or understandable/explainable AI), with high degrees of transparency likely to elicit trust.The proposed model suggests that there is no easy answer when one seeks to understand the impact of AI on the world and humans. Only by considering a myriad number of variables in a model, summed up in the acronym IMPACT (Interaction/Interplay of Modality-Person-Area-Culture-Transparency), we might get closer to an understanding of how AI impacts individuals’ well-being.

The spread of misinformation on social media is a critical issue. One potential solution to mitigate the spread is user corrections; however, users often refrain due to various concerns. Leveraging the established influence of user interface design (UID) on how user interact with and respond to misinformation, this study investigates how user interface features can be designed to motivate users to challenge misinformation. It is aimed at gaining insights into users’ needs and UID requirements that encourage this behaviour. We conducted four codesign sessions with 18 social media users (age range 20–60 years M=39.1; 10 female and 8 male). We applied the unified theory of acceptance and use of technology (UTAUT) as a theoretical framework and analysed our data based on the core constructs of this framework: performance expectancy, effort expectancy, social influence, and facilitating conditions. Our findings reveal four design considerations: creating secure and supportive environments, facilitating informed discussions through easy confrontation and access to reliable resources, leveraging recognition and social proof, and user support infrastructure. We also identified specific design elements with users, including indirection, semianonymity and privacy, simplicity, one-click challenging, easy access to reliable sources, recognition, displaying social proof, and platform support. These elements are aimed at reducing social discomfort and making the process of correcting misinformation more approachable for users. Our findings offer actionable insights for social media platform designers to reduce the spread of misinformation by creating environments that encourage constructive dialogues and allow users to challenge misinformation without fear of conflict.

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.

This study aimed to identify typical interactions between adolescents’ Internet addiction and family environment factors. 165 parents were surveyed about family environment and problematic Internet use for themselves and their adolescents. Three distinct clusters were identified. Cluster 1 (assertive interaction) involved non-addicted authoritative parents with adolescents at risk of addiction. These parents had occasional arguments with their adolescents. Cluster 2 (aggressive interaction) included at-risk authoritarian parents with Internet addicted adolescents. These parents often had arguments with their adolescents. Cluster 3 (lenient interaction) comprised non-addicted permissive parents with highly addicted adolescents. These parents constantly argue with their adolescents. As we have not identified a cluster where adolescents’ addiction was below minimal risk, we advocate the need to train parents along with adolescents on healthy technology use. The clusters identified can be used by professionals as a basis to produce diverse interventions that fit each of the identified family types.

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.

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.

In a world that is highly dependent on digital connectivity, technology use is becoming unavoidable, intense, and possibly harmful. The pervasiveness of technology which has been in tandem with the increasing number of reported cases of harmful usage styles, with some exhibiting symptoms of behavioural addiction, raised concerns around users’ psychological health and well-being. Digital Wellbeing is a new facet of human well-being that has recently emerged. While the term is yet to have a commonly agreed definition, it typically denotes a technology that promotes positivity, personal growth, and a usage that is balanced and healthy. In this paper, we aim to examine the extent, range, and nature of Digital Wellbeing research activity in human-computer interaction- (HCI-) related literature. We conducted a scoping review analysing 87 articles that researched Digital Wellbeing and its interrelation with technology design. Our analysis identified different meanings and constructs of the Digital Wellbeing concept, research trends, and a gap related to incorporating it in the design process. Accordingly, we recommend that an agreed-on definition for Digital Wellbeing and validated tools and frameworks are needed to ensure its integration in the digital design process. We also recommend that a wider research direction for HCI researchers and practitioners interested in Digital Wellbeing is needed to include the role of designers and societal institutions in the digital design process to ensure a design that is inclusive and well-being sensitive.

Objective This study aims to explore the user archetypes of health apps based on average usage and psychometrics. Methods The study utilized a dataset collected through a dedicated smartphone application and contained usage data, i.e. the timestamps of each app session from October 2020 to April 2021. The dataset had 129 participants for mental health apps usage and 224 participants for physical health apps usage. Average daily launches, extraversion, neuroticism, and satisfaction with life were the determinants of the mental health apps clusters, whereas average daily launches, conscientiousness, neuroticism, and satisfaction with life were for physical health apps. Results Two clusters of mental health apps users were identified using k-prototypes clustering: help-seeking and maintenance users and three clusters of physical health apps users were identified: happy conscious occasional , happy neurotic occasional , and unhappy neurotic frequent users. Conclusion The findings from this study helped to understand the users of health apps based on the frequency of usage, personality, and satisfaction with life. Further, with these findings, apps can be tailored to optimize user experience and satisfaction which may help to increase user retention. Policymakers may also benefit from these findings since understanding the populations’ needs may help to better invest in effective health technology.

Background Vaccination programs are effective only when a significant percentage of people are vaccinated. Social media usage is arguably one of the factors affecting public attitudes toward vaccines. Objective This study aims to identify if the social media usage factors can predict Arab people’s attitudes and behavior toward the COVID-19 vaccines. Methods An online survey was conducted in the Arab countries, and 217 Arab nationals participated in this study. Logistic regression was applied to identify what demographics and social media usage factors predict public attitudes and behavior toward the COVID-19 vaccines. Results Of the 217 participants, 56.2% (n = 122) were willing to get the vaccines, and 41.5% (n = 90) were hesitant. This study shows that none of the social media usage factors were significant enough to predict the actual vaccine acceptance behavior. However, some social media usage factors could predict public attitudes toward the COVID-19 vaccines. For example, compared to infrequent social media users, frequent social media users were 2.85 times more likely to agree that the risk of COVID-19 was being exaggerated (OR = 2.85, 95% CI = 0.86–9.45, p = .046). On the other hand, participants with more trust in vaccine information shared by their contacts were less likely to agree that decision-makers had ensured the safety of vaccines (OR = 0.528, 95% CI = 0.276–1.012, p = .05). Conclusion Information shared on social media may affect public attitudes toward COVID-19 vaccines. Therefore, disseminating correct and validated information about the COVID-19 vaccines on social media is important to increase public trust and counter the impact of incorrect misinformation.

With the success of COVID-19 vaccines in clinical trials, vaccination programs are being administered for the population with the hopes of herd immunity. However, the success of any vaccination program depends on the percentage of people willing to get vaccination which is influenced by social, economic, demographic, and vaccine-specific factors. Thus, it is important to understand public attitudes and perceptions toward vaccination. This study aims to measure public attitude toward vaccines and vaccinations before and during the COVID-19 pandemic, using public data from Twitter. A total of 880,586 tweets for 57,529 unique users were included in the study. Most of the tweets were posted in five languages: French, English, Swedish, Dutch, and Italian. These tweets were divided into two time periods: before COVID-19 (T1) and during COVID-19 (T2). This study observed the shift in the sentiments of the public attitude toward vaccines before and during COVID-19 pandemic. Both positive and negative shifts in sentiments were observed for the users of various languages but shifts toward positive sentiments were more prominent during the COVID-19 pandemic.

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.

Loot boxes are a popular mechanic within many video games, but it remains unclear if some forms of loot boxes can be seen of as gambling. However, the perspectives of players are often neglected, such as whether they see them as ‘fair’ game elements and how closely they feel this aligns with gambling. In this paper, we synthesise a conceptualisation for loot boxes through players’ actual experience and explore if there are any parallels with gambling. Twenty-one participants who played video games took part in the research through either an interview or online survey. Thematic analysis suggested that six themes were core to exploring loot boxes: Random Chance Effects, Attitudes Towards Content, Implementation, Parallels with Gambling, Game Design, and The Player. The results suggested both indirect and direct parallels with gambling from the players experiences. Implications of game design and classifying loot boxes as gambling are discussed in relation to game design and risk factors of gambling and purchasing behaviour.

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.

This paper aims to objectively compare the use of mental health apps between the pre-COVID-19 and during COVID-19 periods and to study differences amongst the users of these apps based on age and gender. The study utilizes a dataset collected through a smartphone app that objectively records the users’ sessions. The dataset was analyzed to identify users of mental health apps (38 users of mental health apps pre-COVID-19 and 81 users during COVID-19) and to calculate the following usage metrics; the daily average use time, the average session time, the average number of launches, and the number of usage days. The mental health apps were classified into two categories: guidance-based and tracking-based apps. The results include the increased number of users of mental health apps during the COVID-19 period as compared to pre-COVID-19. Adults (aged 24 and above), compared to emerging adults (aged 15–24 years), were found to have a higher usage of overall mental health apps and guidance-based mental health apps. Furthermore, during the COVID-19 pandemic, males were found to be more likely to launch overall mental health apps and guidance-based mental health apps compared to females. The findings from this paper suggest that despite the increased usage of mental health apps amongst males and adults, user engagement with mental health apps remained minimal. This suggests the need for these apps to work towards improved user engagement and retention.

Online gambling, unlike other offline addiction forms, provides unprecedented opportunities for monitoring users’ behaviour in real-time, along with the ability to adapt persuasive interactions and messages that would match the gamblers usage and personal context. Online gambling industry usually offers Application Programming Interfaces (APIs) that are mainly intended to allow third-party applications to interact with their services and enhance user’s experience. In this article, we claim that such API’s can also be utilised to retrieve gamblers’ online data, such as browsing and betting history and other available offers, and use it to build more proactive and intelligent responsible gambling systems. We report on our experience in this field and make the argument that the available data for persuasive marketing and usability should, under certain usage conditions, also be made available for responsible online gambling services. We discuss the psychological foundations of our proposed approach and the risks and challenges typically identified when building such a software-assisted intervention, persuasion and emotion regulation technology. We also explain the potential impact of corporate social responsibility and data protection prospects. Furthermore, we explore the required principles that should be followed by the gambling industry for enabling responsible online gambling. We finally propose a conceptual architecture to show our vision and explain how it can be implemented. In the broader context, the article is intended to provide insights on building behavioural awareness and regulation information systems related to problematic digital media usage.

The social norms approach is an established technique to bring about behaviour change through challenging misperceptions of peer behaviour. This approach is limited by a reliance on self-report and a lack of interactivity with the target population. At the same time, excessive use of digital devices, known as digital addiction, has been recognized as an emergent issue. There is potential to apply the social norms approach to digital addiction and, in doing so, address some of the limitations of the social norms field. In this study, we trialled a social norms intervention with a sample of smartphone users (n = 94) recruited from the users of a commercial app designed to empower individuals to reduce their device usage. Our results indicate that most of the sample overestimated peer use of smartphone apps, demonstrating the existence of misperceptions relating to smartphone use. Such misperceptions are the basis for the social norms approach. We also document the discrepancy between self-report and smartphone usage data as recorded through data collected directly from the device. The potential for the application of the social norms approach and directions for future research are discussed.

Gamification corresponds to the use of game elements to encourage certain attitudes and behaviours in a serious context. When applied to enterprise teamwork, gamification can lead to negative side-effects which compromise its benefits. For example, applying competitive elements such as leaderboard may lead to clustering amongst team members and encourage adverse work ethics such as intimidation and pressure. Despite the recognition of the problem in the literature, the research on concretising such gamification risks is scarce. There is also a lack of methods to identify gamification risks and their management strategies. In this paper, we conduct a multi-stage qualitative research and develop taxonomy of risks, risk factors and risk management strategies. We also identify the modalities of application of these strategies, including who should be involved and how. Finally, we provide a checklist to help the risk identification process as a first step towards a comprehensive method for eliciting and managing gamification risks to teamwork within enterprises.