Research trends in social media addiction and problematic social media use: A bibliometric analysis

A validity and reliability study of the artificial intelligence attitude scale (AIAS-4) and its relationship with social media addiction and eating behaviors in Turkish adults

BACKGROUND

In recent years, there has been a rapid increase in the use of the internet and social media. Billions of people worldwide use social media and spend an average of 2.2 h a day on these platforms. At the same time, artificial intelligence (AI) applications have become widespread in many fields, such as health, education, and finance. While AI has the potential to monitor eating behaviors and provide personalized health support, excessive use of social media and AI can lead to negative effects. These include addiction and reduced quality of life. It is important to examine the attitude toward AI and its relationship with social media addiction, eating behavior, and life satisfaction. Research on the connection between AI attitudes and eating habits is lacking, which emphasizes the necessity of validating AIAS-4 in Turkish in order to ensure its efficacy in this context. The first stage of the study aimed to adapt Grassini's (2023) Artificial Intelligence Attitude Scale (AIAS-4) into Turkish and assess its validity and reliability. In the second stage, it was aimed to examine the relationship between artificial intelligence attitude and social media addiction, eating behavior, and life satisfaction.

METHODS

This study cross-sectional and methodological study was conducted in two stages in Türkiye. 172 adult individuals underwent a validity and reliability study in the first stage (43% of them were men and 57% were women), which involved adapting the AIAS-4 into Turkish. In the second stage, the relationships between artificial intelligence attitude, social media addiction, eating behavior, and life satisfaction of 510 individuals were evaluated with an average age of 24.88 ± 7.05 years (30.8% male, 69.2% female). Using the snowball sampling technique, the survey was carried out on adults by reaching out to staff and their families from both universities (Gazi University and Tokat Gaziosmanpaşa University) as well as students and their relatives. A face-to-face survey approach (delivered by an interviewer) was used for the study. In this study, the Social Media Addiction Scale-Adult Form(SMAS-AF) was used to assess social media addiction, the Scale of Effects of Social Media on Eating Behavior (SESMEB) was used to measure the impact of social media on eating behavior, the Contentment with Life Assessment Scale was used to evaluate life satisfaction, and the Eating Disorder Examination Questionnaire (EDE-Q total) was used to assess eating disorder symptoms. Pearson Correlation and Spearman Correlation according to normality and Linear regression analysis were used to analyse variables.

RESULTS

AIAS-4 was a valid and reliable instrument in this study conducted in Türkiye (Cronbach's alpha = 0.90 and McDonald's omega = 0.89). Individuals spend an average of 3.7 ± 1.99 h per day on social media. All participants used WhatsApp, while 89.8% used Instagram. A negative correlation was found between AIAS and EDE-Q total, (r=-0.119 p < 0.05). BMI correlated positively with EDE-Q total (r = 0.391, p < 0.01). Higher AIAS scores were associated with increased time spent on social media (r = 0.129, p < 0.001). Conversely, higher AIAS scores were associated with lower EDE-Q total scores (r= -0.119, p < 0.001). SESMEB correlated positively with EDE-Q total (r = 0.169; p < 0.001). The model showed that BMI (β = 0.311; p < 0.001), AIAS (β =-0.157, p = 0.005), SMAS-AF (β = 0.036; p = 0.002) and SESMEB (β = 0.022; p = 0.038) affected EDE-Q total (p < 0.001 R2 = 0.198).

CONCLUSION

This study revealed that the Artificial Intelligence Attitude Scale (AIAS) is valid and reliable for Turkish adults. The results show that BMI, social media addiction have positive, and AI attitude has negative impact on eating behaviors. These findings emphasize the importance of multidisciplinary approaches and awareness programs in the prevention and management of eating disorders.

Nursing students' personality traits, sleep quality, social media addiction, and academic performance: A multi-site structural equation model analysis

BACKGROUND

The associations between personality traits, sleep quality, social media addiction, and academic performance have been well-reported across the literature among university students. However, the interaction among these variables remains understudied among nursing students of underdeveloped countries like the Philippines.

PURPOSE

This study investigated the interrelationships of personality traits, sleep quality, social media addiction, and academic performance among Filipino nursing students.

METHODS

A correlational, cross-sectional design and convenience sampling was used to recruit nursing students (n = 823) from five nursing colleges in the Philippines. Three standardized instruments (10-item Personality Inventory, 19-item Pittsburgh Sleep Quality Index, and 6-item Bergen Social Media Addiction Scale) were used to collect data from June to August 2023. Covariance-based structural equation modeling (CB-SEM) was employed to analyze the data. STROBE checklist guided in reporting study results.

RESULTS

The emerging model demonstrated satisfactory model fit parameters. Nursing students reported high levels of extraversion (x̅=6.13, SD = 2.08) with low scores in emotional stability (x̅ =6.76, SD = 2.30) and openness to experiences (x̅ =8.80, SD = 2.09). The majority had poor sleep quality (x̅=8.35, SD = 3.12) and were at low risk for social media addiction (x̅=17.73, SD = 5.61). Conscientiousness (β = -0.13, p = 0.031) and emotional stability (β = -0.35, p = 0.002) inversely influenced sleep quality. Agreeableness (OR = 1.13, p = 0.007) and openness to experiences (OR = 1.11, p = 0.050) had a positive effect, while conscientiousness (OR = 0.84, p = 0.006) had a negative effect on high-risk social media addiction. Conscientiousness (β = 0.12, p = 0.010) significantly and positively influenced academic performance. Conscientiousness and emotional stability were able to measure 15.00 % of sleep quality's total variance.

CONCLUSION

Policymakers, nursing college administrators, and nurse educators could use these findings to evaluate students' personality traits and create programs that will promote better sleep quality and prevent social media addiction. Hence, enhancing academic performance.

Exploring the associations between symptom severity, metacognition, problematic social media use and cyberbullying in treatment naïve adolescents with Attention Deficit and Hyperactivity Disorder

This study investigates the relationship between ADHD symptom severity, metacognition, problematic social media use, and cyberbullying/cybervictimization in treatment-naïve adolescents. Understanding these relationships is vital for enhancing ADHD intervention strategies. Using a cross-sectional design, 97 adolescents meeting DSM-5 criteria for ADHD without any comorbidity and 97 healthy controls were assessed. Measures included the Metacognitions Questionnaire for Children, Social Media Disorder Scale, Revised Cyberbullying Inventory-II, and Revised Conners' Parent Rating Scale-Short. The comparisons were performed with independent samples' t tests and the associations were estimated by using Pearson's bivariate correlations and multiple regression analyses. Results revealed that adolescents with ADHD exhibited higher levels of dysfunctional metacognitions, problematic social media use, cyberbullying, and cybervictimization compared to controls. Regression analysis showed significant positive associations between ADHD symptoms, specific metacognitions (e.g., positive meta-worry, cognitive monitoring), and problematic social media use. This study, the first of its kind among treatment-naïve ADHD adolescents, provides valuable insights into the relationship between ADHD symptoms and particular metacognitions (i.e. positive meta-worry, cognitive monitoring) and problematic social media use. These findings contribute to a deeper understanding of ADHD in adolescence and may inform the development of targeted prevention and treatment strategies, particularly relevant given adolescents' susceptibility to social media's influence and their potential for cognitive flexibility in rehabilitation contexts.

Social media use, mental health and sleep: A systematic review with meta-analyses

BACKGROUND

The literature investigating the relationship between social media use, mental health, and sleep has produced inconsistent findings. Younger people spend more time on social media than other age groups, and are more likely to be impacted by social media use. This systematic review with meta-analysis aimed to synthesise the evidence on the associations between social media use, mental health, and sleep of young individuals.

METHODS

Electronic databases PubMed, Scopus and PsycINFO were searched using an established methodology and pre-determined search terms for studies that reported the association between social media use, mental health, and sleep.

RESULTS

The search yielded 6108 articles, of which 182 (n = 1,169,396) were eligible for the systematic review, and 98 (n = 102,683) could be included in the meta-analyses. The systematic review identified a high level of heterogeneity in the study results. Meta-analyses found small but significant positive associations between social media use, depression, and anxiety. In addition, problematic social media use was positively associated with depression, anxiety, and sleep problems, and negatively associated with wellbeing. Geographical location, anxiety measure type, study design, age, and gender were identified as potential moderators.

LIMITATIONS

Associations for specific social media platforms as well as some moderator effects were not examined due to an insufficient number of studies.

CONCLUSIONS

This study provides important evidence of an association between social media use/ problematic social media use, mental health, and sleep. The findings support future longitudinal research to identify the directions and underlying mechanisms of the inter-relationship between these variables.

The shield of the screen: The role of anger on the development of social media addiction and internet gaming disorder

This study aims to explore if the dimensions of anger can be risk factors for the development of social media addiction and an internet gaming disorder, considering that the correlation between anger and these specific subcategories of internet addiction can represent a core intervention in their prevention and treatment. 477 subjects, recruited among the general population, were assessed on-line by the following tools: STAXI-2; BSMAS, and IGDS9-SF. A correlation analyses showed a significantly positive relationship between the total score of the BSMAS and the STAXI-2 scales SANG (p < 0.0001), TANG (p < 0.0001), AX-O (p = 0.003), and AX-I (p < 0.0001), and between the total score of the IGDS9-SF and the STAXI-2 scales SANG (p = 0.002), TANG (p < 0.0001), AX-O (p = 0.001), AX-I (p < 0.0001), and AC-O (p = 0.004). A linear regression model showed how TANG and AX-I were direct predictors of the BSMAS total scores, and how AX-I was a direct predictor of the IGDS9-SF total scores. It appears plausible that there is a significant correlation between the dimensions of anger and the emergence of social media addiction and internet gaming: internet usage may serve as a coping mechanism for emotional or social challenges and as a protective screen to deal with negative emotions.

Social Media Use and Consumption of Prescription-Free Medications for Anxiety, Sleep, and Pain among Norwegian University Students

A relationship has been recognized between social media use and health issues. However, no studies have explored the potential link between social media use and consumption of over-the-counter (OTC) medications. We examined social media use, self-reported anxiety, depression, sleep problems, pain, and OTC medications use among Norwegian university students. The goal was to gain insights that would guide preventive health strategies for this target group. A quantitative, cross-sectional study was conducted with an online questionnaire distributed to university student Facebook groups in Norway. A total of 132 completed surveys were analyzed. Among the respondents, 28% experienced anxiety, 35% depression, 64% sleep problems, 71% headaches, and 78% musculoskeletal pain. Moreover, 56% reported using OTC analgesics or sleep aids, mostly purchased from community pharmacies. No statistically significant correlation was found between social media use and headache, musculoskeletal pain, sleep disturbances, or consumption of OTC medications among university students in Norway. The findings, however, demonstrated a positive trend, highlighting the need for further research with larger, more diverse samples, and potentially employing a qualitative or longitudinal design. We propose increased awareness of the potential negative effects of social media among university students, the inclusion of social media and health topics in study curricula, and the more proactive engagement of community pharmacists with young clients concerning the consumption of OTC medications.

From temperament to YouTube: exploring the link between childhood temperament, YouTube usage patterns, and emotional/behavioral problems among children

BACKGROUND

YouTube is a widely used video sharing and social networking platform among children and adolescents. However, research on YouTube usage among this population remains scarce. Specifically, studies on factors that influence children and adolescents' usage are clinically significant but largely lacking. Additionally, few studies have examined the association between usage and emotional/behavioral problems, which is fundamental to smartphone research. Therefore, this study explored the relationship between early childhood temperament, subsequent YouTube usage patterns, and emotional/behavioral problems.

METHODS

The Kids Cohort for Understanding Internet Addiction Risk Factors in Early Childhood (K-CURE) is the first long-term prospective cohort study in Korea aimed at understanding the long-term effects of media exposure on young children. The study included 195 children aged 8-11 years enrolled in the K-CURE study. Caregivers, predominantly mothers, who voluntarily participated during their visits to community centers for children's mental health in Korea's major cities, completed a detailed self-administered survey. Childhood temperament was measured in 2018 when the children were 5-8 years old. Subsequent YouTube usage patterns and emotional/behavioral problems were assessed in 2021. Data were analyzed using frequency analysis, correlation analysis, and multiple linear regression.

RESULTS

The study found that 21.0% of children started using YouTube before age 4, with the most common onset age being 8-9 years (30.3%). These children used YouTube on average 4.8 days per week for 68.5 min per day. Early childhood persistence was negatively associated with the subsequent YouTube usage duration, and the age at first YouTube use was negatively correlated with subsequent usage frequency. Furthermore, a younger age at first YouTube use and higher usage frequency were significantly associated with increased emotional/behavioral problems.

CONCLUSIONS

In the YouTube environment, where content is automatically recommended based on user preferences, traits related to usage patterns may be associated with persistence, which is linked to self-regulation. Considering the current trend where children use smartphones, contents frequently for very short durations, our findings highlight the importance of self-regulation in the media usage of children who are still developing. Additionally, our results provide fundamental information for future YouTube studies and illustrate similarities and differences between smartphone and YouTube research.

Predicting anxiety, depression, and insomnia among Bangladeshi university students using tree-based machine learning models

Background and Aims

Mental health problem is a rising public health concern. People of all ages, specially Bangladeshi university students, are more affected by this burden. Thus, the objective of the study was to use tree-based machine learning (ML) models to identify major risk factors and predict anxiety, depression, and insomnia in university students.

Methods

A social media-based cross-sectional survey was employed for data collection. We used Generalized Anxiety Disorder (GAD-7), Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index (ISI-7) scale for measuring students' anxiety, depression and insomnia problems. The tree-based supervised decision tree (DT), random forest (RF) and robust eXtreme Gradient Boosting (XGBoost) ML algorithms were used to build the prediction models and their predictive performance was evaluated using confusion matrix and receiver operating characteristic (ROC) curves.

Results

Of the 1250 students surveyed, 64.7% were male and 35.3% were female. The students' ages ranged from 18 to 26 years old, with an average age of 22.24 years (SD = 1.30). Majority of the students (72.6%) were from rural areas and social media addicted (56.6%). Almost 83.3% of the students had moderate to severe anxiety, 84.7% had moderate to severe depression and 76.5% had moderate to severe insomnia problems. Students' social media addiction, age, academic performance, smoking status, monthly family income and morningness-eveningness are the main risk factors of anxiety, depression and insomnia. The highest predictive performance was observed from the XGBoost model for anxiety, depression and insomnia.

Conclusion

The study findings offer valuable insights for stakeholders, families and policymakers enabling a more profound comprehension of the pressing mental health disorders. This understanding can guide the formulation of improved policy strategies, initiatives for mental health promotion, and the development of effective counseling services within university campus. Additionally, our proposed model might play a critical role in diagnosing and predicting mental health problems among Bangladeshi university students and similar settings.

Status and Influencing Factors of Social Media Addiction in Chinese Workers: Cross-Sectional Survey Study

BACKGROUND

Social media addiction (SMA) caused by excessive dependence on social media is becoming a global problem. At present, most of the SMA studies recruit college students as research participants, with very few studies involving workers and other age groups, especially in China.

OBJECTIVE

This study aims to investigate the current status of SMA among Chinese workers and analyze its influencing factors.

METHODS

From November 1, 2022, to January 30, 2023, we conducted an anonymous web-based questionnaire survey in mainland China, and a total of 5176 participants completed the questionnaire. The questionnaire included the Social Networking Service Addiction Scale, Maslach Burnout Inventory-General Survey scale, Mindful Attention Awareness Scale, as well as questionnaires regarding participants' social media use habits and demographic information.

RESULTS

Through strict screening, 3468 valid questionnaires were included in this study. The main findings of this study revealed the following: the average SMA score of workers was higher (mean 53.19, SD 12.04), and some of them (393/3468, 11.33%) relied heavily on social media; there were statistically significant differences in SMA scores among workers in different industries (F14,3453=3.98; P<.001); single workers (t3106=8.6; P<.001) and workers in a relationship (t2749=5.67; P<.001) had higher SMA scores than married workers, but some married workers (214/3468, 6.17%) were highly dependent on social media; the level of SMA among female workers was higher than that of male workers (t3466=3.65; P<.001), and the SMA score of workers negatively correlated with age (r=-0.22; P<.001) and positively correlated with education level (r=0.12; P<.001); the frequency of using social media for entertainment during work (r=0.33; P<.001) and the frequency of staying up late using social media (r=0.14; P<.001) were positively correlated with the level of SMA in workers; and the level of SMA in workers was significantly positively correlated with their level of burnout (r=0.35; P<.001), whereas it was significantly negatively correlated with their level of mindfulness (r=-0.55; P<.001).

CONCLUSIONS

The results of this study suggest that SMA among Chinese workers is relatively serious and that the SMA problem among workers requires more attention from society and academia. In particular, female workers, young workers, unmarried workers, highly educated workers, workers with bad social media habits, workers with high levels of job burnout, and workers with low levels of mindfulness were highly dependent on social media. In addition, occupation is an important influencing factor in SMA. Thus, the government should strengthen the supervision of social media companies. Medical institutions should provide health education on SMA and offer intervention programs for those addicted to social media. Workers should cultivate healthy habits while using social media.

Understanding University Students' Perspectives towards Digital Tools for Mental Health Support: A Cross-country Study

Background

Organisational and individual barriers often prevent university students from seeking mental health support. Digital technologies are recognised as effective in managing psychological distress and as a source of health-related information, thus representing useful options to address mental health needs in terms of accessibility and cost-effectiveness. However, university students' experiences and perspectives towards such interventions are little known.

Objectives

We thus aimed to expand the existing base of scientific knowledge, focusing on this special population.

Methods

Data were from the qualitative component of "the CAMPUS study", longitudinally assessing the mental health of students at the University of Milano-Bicocca (Italy) and the University of Surrey (UK). We conducted in-depth interviews and thematically analysed the transcripts using the framework approach.

Results

An explanatory model was derived from five themes identified across 33 interviews (15 for Italy, 18 for the UK). Students perceived that social media, apps, and podcasts could deliver relevant mental health content, ranging from primary to tertiary prevention. Wide availability and anonymity were perceived as advantages that make tools suitable for preventive interventions, to reduce mental health stigma, and as an extension of standard treatment. These goals can be hindered by disadvantages, namely lower efficacy compared to face-to-face contact, lack of personalisation, and problematic engagement. Individual and cultural specificities might influence awareness and perspectives on the use of digital technologies for mental health support.

Conclusion

Although considering some specific features, digital tools could be a useful instrument to support the mental health needs of students. Since personal contact remains crucial, digital tools should be integrated with face-to-face interventions through a multi-modal approach.

Exploring the dynamics of mobile app addiction: the interplay of communication, affective factors, flow, perceived enjoyment, and habit

The rapid proliferation of mobile apps and their increasing usage have led to growing concerns about potential addiction among users. Previous research has identified several factors that contribute to addiction, including flow, perceived enjoyment, and habit. However, the underlying mechanisms and the role of affective factors remain unclear. This study aims to elucidate the key factors that affect mobile app addiction by proposing a theoretical framework incorporating communication, affective factors, flow, perceived enjoyment, and habit. Data were collected from 320 mobile app users through a questionnaire survey. The research employed partial least squares structural equation modeling (PLS-SEM) to analyze the data and test the proposed relationships. The analysis indicates that communication is significantly associated with perceived enjoyment but does not directly affect flow and habit. The research unveils that positive affect significantly influences both flow and perceived enjoyment, but does not influence habit. Negative affect was found to have no significant effect on flow, perceived enjoyment, and habit. The results demonstrate that flow, perceived enjoyment, and habit are significantly related to addiction. The findings reveal that perceived enjoyment has a substantial impact on both flow and habit. These findings offer valuable guidelines for future research and practical implications for developers and policymakers in addressing the challenges associated with mobile app addiction.

Sleep Quality and Self-Stigma Mediate the Association Between Problematic Use of Social Media and Quality of Life Among People With Schizophrenia in Taiwan: A Longitudinal Study

OBJECTIVE

Problematic use of social media (PUSM) may affect sleep quality and self-stigma in people with schizophrenia and consequently reduce their quality of life (QoL). This longitudinal study investigated if sleep quality and self-stigma mediated relationships between PUSM and QoL.

METHODS

One-hundred-and-ninety-three outpatients with schizophrenia were recruited from a psychiatric center in Taiwan from April 2019 to August 2021 and participated in a longitudinal study at intervals of three months between measurements. QoL was assessed using the World Health Organization Quality of Life Questionnaire Brief Version; sleep quality using the Pittsburgh Sleep Quality Index; self-stigma using the Self-Stigma Scale-Short; and PUSM using the Bergen Social Media Addiction Scale. Via SPSS 20.0, general estimating equation models assessed temporal associations between variables. Via R software, mediating effects of self-stigma and sleep quality were examined through Monte Carlo simulations with 20,000 repetitions.

RESULTS

Mean scores of physical, psychological, social and environmental QoL ranged from 11.86 to 13.02. Mean scores of sleep quality and self-stigma were 9.1±4.5 and 2.2±0.8, respectively. Sleep quality and self-stigma were directly related to QoL (p<0.001) and mediated indirect relationships between PUSM and all components of QoL with a range of 95% confidence intervals spanning from -0.0591 to -0.0107 for physical QoL; -0.0564 to -0.0095 for psychological QoL; -0.0292 to -0.0035 for social QoL; and -0.0357 to -0.0052 for environmental QoL.

CONCLUSION

Sleep quality and self-stigma mediated relationships between PUSM and QoL in people with schizophrenia. Developing interventions targeting PUSM, sleep, and self-stigma may help improve QoL in people with schizophrenia.

Wellbeing, social media addiction and coping strategies among Chilean adolescents during the pandemic

Introduction

During the COVID-19 pandemic, adolescents had to deal with a range of mental health problems that has increased social media addiction levels with adverse effects on life satisfaction. Previous studies have explored coping mechanisms to deal with this addiction problem, but did not consider the need to simultaneously cope with different dimensions. Therefore, our study aimed to examine the moderating effect of various coping mechanisms on the relationship between social media addiction and adolescent life satisfaction.

Methods

Self-report questionnaires were applied to 1290 secondary school students (age mean = 16.03, SD = 1.27, range: 14 to 19; and 57% female). An exploratory and a confirmatory factor analysis were performed to determine the factor structure of the Brief-Cope 28 scale. Then, a descriptive and correlational analysis of the variables and a multiple linear regression analysis was performed.

Results

We found that the social media addiction risk was negatively associated with life satisfaction, adaptive strategies were positively correlated to life satisfaction, and maladaptive strategies were negatively correlated to it. Also, a moderation model was evaluated in which four stress management strategies, namely acceptance and perspective-taking, seeking socio-emotional support, active coping, and maladaptive strategies all conditioned the relationship between social media addiction risk and life satisfaction after controlling for demographic variables and the specific strategies of using comedy, religion and substance use. Results indicate additive and multiplicative effects of management strategies for stressful situations in the studied relationship. Seeking socio-emotional support and active coping were positively related to life satisfaction and maladaptive strategies were negatively associated with it. Multiplicative effects indicate that the relationship between the social media addiction risk and life satisfaction depends only on the acceptance and perspective taking that adolescents report. When adolescents reported having low or average levels of acceptance and perspective taking, there was a negative correlation with general life satisfaction, a connection that grew markedly stronger. In contrast, no connection between social media addiction and life satisfaction was detected for adolescents who report higher levels of acceptance and perspective-taking.

Discussion

Abuse of social media and the use of maladaptive stress coping strategies were risk factors that decreased life satisfaction among adolescents during the COVID-19 pandemic period.

Neurobiological risk factors for problematic social media use as a specific form of Internet addiction: A narrative review

Problematic social media use (PSMU) is a behavioral addiction, a specific form of problematic Internet use associated with the uncontrolled use of social networks. It is typical mostly for modern adolescents and young adults, which are the first generations fully grown up in the era of total digitalization of society. The modern biopsychosocial model of the formation of behavioral addictions, postulating the impact of a large number of biological, psychological, and social factors on addictive behavior formation, may be quite applicable to PSMU. In this narrative review, we discussed neurobiological risk factors for Internet addiction with a focus on current evidence on the association between PSMU and structural/ functional characteristics of the brain and autonomic nervous system, neurochemical correlations, and genetic features. A review of the literature shows that the vast majority of the mentioned neurobiological studies were focused on computer games addiction and generalized Internet addiction (without taking into account the consumed content). Even though a certain number of neuroimaging studies have been conducted for PSMU, there is practically no research on neuropeptide and genetic associations for PSMU to date. This fact points to the extremely high relevance of such studies.