Smartphone Application-Based Addiction Scale Research Articles

Validity, Reliability, and Measurement Invariance of the Thai Smartphone Application-Based Addiction Scale and Bergen Social Media Addiction Scale

Validity, Reliability, and Measurement Invariance of the Thai Smartphone Application-Based Addiction Scale and Bergen Social Media Addiction Scale

Factor structure and psychometric properties of an Arabic version of the Internet Gaming Disorder Scale, short form (IGDS-SF9).

In its most recent edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM), the American Psychological Association recognized that internet gaming disorder is a psychological condition and provides nine criteria for its diagnosis, and the Internet Gaming Disorder Scale, short form (IGDS-SF9) was developed to assess individuals. To develop and investigate the psychometric properties of an Arabic version of IGDS-SF9. A five-stage translation and verification process produced an Arabic version of IGDS-SF9, and a study was conducted using a sample of 410 respondents (45.6% females, mean age = 17.6, SD = 1.56) to assess its psychometric properties. Respondents completed the Arabic version, the Smartphone Addiction Scale, the Smartphone Application-Based Addiction Scale, the Hospital Anxiety and Depression Scale, as well as a demographic survey. Exploratory and confirmatory factor analyses, measurement invariance, item response theory, convergent, concurrent, criterion validity, and internal consistency reliability and test-retest reliability were employed to validate the scale. The exploratory factor analysis suggested the scale's unidimensional structure; the confirmatory factor analysis exhibited good model fit and factor loadings. Measurement invariance, and concurrent, convergent, and criterion validity were established, resulting in good internal consistency and test-retest reliability for the scale. The Arabic version of IGDS-SF9 is a valid and reliable measure for research and diagnosis in Arabic-speaking countries.

Determination of the cutoff point for Smartphone Application-Based Addiction Scale for adolescents: a latent profile analysis

BackgroundsThe Smartphone Application-Based Addiction Scale (SABAS) is a validated 6-item measurement tool for assessing problematic smartphone use (PSU). However, the absence of established cutoff points for SABAS hinders its utilities. This study aimed to determine the optimal cutoff point for SABAS through latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses among 63, 205. Chinese adolescents. Additionally, the study explored whether PSU screening with SABAS could effectively capture problematic social media use (PSMU) and internet gaming disorder (IGD).MethodWe recruited 63,205. adolescents using cluster sampling. Validated questionnaires were used to assess PSMU, IGD, and mental health (depression, anxiety, sleep disturbances, well-being, resilience, and externalizing and internalizing problems).ResultsLPA identified a 3-class model for PSU, including low-risk users (38.6%, n = 24,388.), middle-risk users (42.5%, n = 26,885.), and high-risk users (18.9%, n = 11,932.). High-risk users were regarded as “PSU cases” in ROC analysis, which demonstrated an optimal cut-off point of 23 (sensitivity: 98.1%, specificity: 96.8%). According to the cutoff point, 21.1% (n = 13,317.) were identified as PSU. PSU adolescents displayed higher PSMU, IGD, and worse mental health. PSU screening effectively captured IGD (sensitivity: 86.8%, specificity: 84.5%) and PSMU (sensitivity: 84.5%, specificity: 80.2%).ConclusionA potential ideal threshold for utilizing SABAS to identify PSU could be 23 (out of 36). Employing SABAS as a screening tool for PSU holds the potential to reliably pinpoint both IGD and PSMU.

Psychometric Properties of the Serbian Smartphone Application-Based Addiction Scale (SABAS) and Validation of the English Version Among Non-native English Speakers

AbstractThe present study evaluated the psychometric properties of the Serbian Smartphone Application-Based Addiction Scale (SABAS) and the original English version of the same scale administered to a Serbian-speaking sample. In Study 1, 599 participants completed Serbian SABAS, with 189 having both test and retest data. Results suggested good internal consistency (α = .81) and test–retest reliability (ICC = .795, p < .001, 95% CI [.731, .844], rtest-retest = .803) of the scale. Convergent validity of the SABAS was evaluated through correlations with the Smartphone Addiction Scale–Short Version (SAS-SV), as well as with anxiety, depression, worry, duration, and purpose of smartphone use. Divergent validity of the SABAS was evaluated through comparing the correlations with entertainment and productive smartphone use. The modified CFA model showed an acceptable fit (χ2(8) = 25.53, p = .001, CFI = .961, TLI = .926, RMSEA = .096, SRMR = .042), confirming the unidimensionality of the SABAS. In the second study, the English SABAS, completed by 335 non-native speakers from Serbia, also showed a good fit of the single-factor model (χ2(9) = 12.56, p = .184, CFI = .990, TLI = .984, RMSEA = .036, SRMR = 0.026), and good psychometric features. Based on the study’s findings, the Serbian version of SABAS is a reliable and valid measure for screening the risk of smartphone addiction. Moreover, the English version can be used among non-native Serbian English speakers.

How is the problematic smartphone use affected by social support? A research model supported by the mediation of Ikigai.

Social support and ikigai (making life worthwhile) have positive effects on problematic smartphone use and are seen to be related to each other. However, what mediates these relationships has not been adequately analyzed. This study aims to examine how the effect between social support and problematic smartphone use occurs by suggesting the mediator role of ikigai. The study was designed as quantitative and cross-sectional, and 1189 university participants aged 18 and over were reached online. The multidimensional scale of perceived social support, ikigai-9 scale, smartphone application-based addiction scale and sociodemographic information form were used as data collection tools in the study. The data obtained were carried out using SPSS 24 and Amos 25 statistical programs. Established hypotheses were tested with correlation, multiple regression and mediation analyzes. The results confirmed that social support was positively associated with ikigai, and ikigai was negatively associated with problematic smartphone use. In addition, interaction analyzes found that ikigai had a mediating effect. These findings show the importance of implementing specific applications based on the meaning and purpose of life (ikigai), especially for vulnerable groups, to minimize the problems that may arise with the excessive use of smartphones.

Problematic smartphone and social media use among undergraduate students during the COVID-19 pandemic: In the case of southern Ethiopia universities.

Smartphone and social media use are supposed to be integral parts of university students' daily lives. More specifically, smartphones and social media are frequently used for communication in daily life during the COVID-19 pandemic. Nonetheless, uninterrupted and persistent use of these technologies may lead to several psychological problems. Even though smartphones and social media were used more frequently during the pandemic, there is no evidence suggesting that the studies were not undertaken in low-income countries, including Ethiopia. Therefore, the current study aimed to assess problematic smartphone use and social media use among undergraduate university students in southern Ethiopia. A cross-sectional study was carried out among 1,232 university students using a simple random sampling technique. The Bergen Social Media Addiction Scale and Smartphone Application-Based Addiction Scale were used to collect data on social media and smartphone use, respectively. The Beck Depression Inventory, Generalized Anxiety Assessment Tool, Rosenberg Self-Esteem Scale, and Pittsburg Sleep Quality Index were standardized tools used to measure other independent variables. To identify factors, simple and multiple linear regression analyses were performed. A p-value of 0.05 was used to determine statistical significance. The overall response rate was 95%. The mean scores for problematic smartphone and problematic social media use were 17 ± 3.3/36 and 12.7 ± 2.2/30, respectively. A linear regression model revealed that being female, first-year students and poor sleep quality were significantly associated with problematic smartphone use. Factors associated with problematic social media use (PSMU) were depression, substance use, and urban residence. This study identified significant problems with smartphone and social media use among university students. Therefore, it is preferable to provide psychological counselling, educate students about safe, beneficial, and healthy internet use, and focus on recognized high-risk groups in order to give them special attention. It is also preferable to seek counselling about substance use. It is preferable to regularly screen and treat individuals with psychological problems in collaboration with stakeholders.

Exploring mediational roles for self-stigma in associations between types of problematic use of internet and psychological distress in youth with ADHD

BackgroundSeveral studies have linked the problematic use of the Internet (PUI) to psychological distress. Youth with attention deficit hyperactivity disorder (ADHD) are considered a particular disadvantaged population with a high risk of developing PUI, psychological distress, and self-stigma. Nonetheless, the interrelationships of PUI, self-stigma, and psychological distress in adolescents with ADHD are not well understood. AimsThis study investigated whether self-stigma mediates relationships between different forms of PUI, such as problematic gaming (PG), problematic social media use (PSMU), problematic smartphone use (PSPU), and psychological distress (i.e., depression, anxiety, and stress), in children with ADHD. Methods and proceduresWe recruited 100 youth with ADHD (mean age=10.80 [SD=3.07] years; 84 boys) from psychiatric outpatient clinics in Taiwan. All participants were assessed for PUI (via Internet Gaming Disorder-Short Form for PG, Bergan Social Medica Addiction Scale for PSMU, and Smartphone Application-Based Addiction Scale for PSPU), self-stigma (via Self-Stigma Short-Scale), and psychological distress (via Depression, Anxiety, Stress Scale). Outcomes and resultsThe results of path and bootstrapping analyses indicated that self-stigma mediated the associations between PSMU and PSPU, but not PG, and depression, anxiety, and stress. Conclusions and implicationsThis study expands the extant literature by revealing that self-stigma mediates the association between specific forms of PUI and psychological distress in adolescents with ADHD. Interventions aimed at reducing self-stigma and PUI, particularly PSMU and PSPU, may help decrease psychological distress among adolescents with ADHD.

Temporal associations between physical activity and three types of problematic use of the internet: A six-month longitudinal study.

Internet use has become an important part of daily living. However, for a minority it may become problematic. Moreover, problematic use of the Internet/smartphone (PUIS) has been associated with low physical activity. The present study investigated the temporal associations between three types of PUIS (i.e., problematic smartphone use [PSPU], problematic social media use [PSMU] and problematic gaming [PG]) and physical activity among Taiwanese university students. A six-month longitudinal survey study comprising three time points for assessments was conducted. From the original 974 participants, a total of 452 completed all three waves of an online survey comprising the International Physical Activity Questionnaire Short Form (IPAQ-SF) assessing physical activity level, Smartphone Application-Based Addiction Scale (SABAS) assessing PSPU, Bergen Social Media Addiction Scale (BSMAS) assessing PSMU, and Internet Gaming Disorder Short Form (IGDS9-SF) assessing PG. The linear mixed effects model found positive temporal associations of PSMU and PG with physical activity level (PSMU: B = 85.88, SE = 26.24; P = 0.001; PG: B = 36.81, SE = 15.17; P = 0.02). PSPU was not associated with physical activity level (B = 40.54, SE = 22.99; P=0.08). Additionally, the prevalence rates were 44.4% for at-risk/PSPU, 24.6% for at-risk/PSMU, and 12.3% for at-risk/PG. PSMU and PG unexpectedly demonstrated correlations with higher physical activity level. The nature of these relationships warrants additional investigation into the underlying mechanisms in order to promote healthy lifestyles among university students.

Evaluation of the English Version of the Smartphone Application-Based Addiction Scale (SABAS) among an Adolescent Sample

The increased use of smartphones among adolescents has highlighted the need to distinguish between problematic and non-problematic smartphone use. To date, there are a lack of short, easy-to-use, and valid psychometric tools to assess smartphone addiction. The primary aim of the present study was to conduct the first psychometric assessment and evaluation of the Smartphone Application-Based Addiction Scale (SABAS) among English-speaking adolescents. Participants were 1175 students recruited from across four different high schools in New Zealand, of which 1031 completed all questions and were used in the final analyses. Several psychometric tests were conducted to ascertain reliability and validity. The SABAS had high internal consistency. Consistent with earlier validation studies, the SABAS displayed weak-moderate, positive relationships with symptoms of depression (PHQ-2), anxiety (GAD-2), and sleep quality. Overall, the SABAS is a sound, unidimensional scale with robust psychometric properties and is a short and easy-to-use measure that can be used confidently among English-speaking adolescents.

Temporal associations between problematic use of the internet and self-stigma among people with substance use disorders: A cross-lagged model across one year

Self-stigma is a common experience for people with substance use disorders (SUDs). Understanding factors associated with self-stigma may aid in intervention development. This study investigated the reciprocal relationship between three types of problematic use of the internet [PUI; i.e. problematic use of social media (PUSM), problematic smartphone use (PSPU), and problematic gaming (PG)] and self-stigma among people with SUDs. This longitudinal study involved five waves of a survey given to individuals with SUDs in Taiwan. A total of 319 participants (85% male), with a mean age of 42.2 years (SD = 8.9), were recruited. The Smartphone Application-Based Addiction Scale, Bergen Social Media Addiction Scale, Internet Gaming Disorder-Short Form, and Self-Stigma Scale-Short Form were used. No significant associations between PUI and self-stigma were found in early waves (i.e., Waves 1 and 2). The earliest significant finding was identified between Wave 2 PSPU (smartphone) and Wave 3 self-stigma. Additionally, Wave 3 PSPU (smartphone) and PG (gaming) were associated with Wave 4 self-stigma, and Wave 4 PSPU (smartphone), PG (gaming), and PUSM (social media) were associated with Wave 5 self-stigma. Therefore, all three types of PUI (internet) may elevate self-stigma at different time points for individuals with SUDs. However, the reciprocal effects between self-stigma and PUI (internet) only occurred in PUSM (social media) at a later stage (i.e., from Wave 4 to Wave 5). In conclusion, people with SUDs who have PUI (internet) are at increased likelihood of developing more self-stigma, which may then increase subsequent PUSM (social media), forming a vicious cycle.

The roles of behavioral inhibition/activation systems and impulsivity in problematic smartphone use: A network analysis.

Behavioral inhibition/activation systems (BIS/BAS) and impulsivity are associated with problematic smartphone use (PSU). However, no studies to date have explored how the subdomains of BIS/BAS and the dimensions of impulsivity relate to the components of PSU in a joint framework. This study aimed to examine the relationships between the three constructs at a fine-grained level and identify the central nodes and bridge nodes of their relationships using network analysis. A regularized partial correlation network of PSU, BIS/BAS, and impulsivity communities was estimated to investigate the connections between variables and determine the expected influence and bridge expected influence for each variable based on data from 325 Chinese adults. PSU, BIS/BAS, and impulsivity were assessed using the Smartphone Application-Based Addiction Scale (SABAS), BIS/BAS scales, and Barratt Impulsiveness Scale-Version 11 (BIS-11), respectively. In addition to connections within each community, network analysis revealed that there were connections between different communities, especially connections to PSU. I2 "motor impulsivity" was strongly associated with PSU2 "conflict" and PSU6 "relapse"; BASR "BAS-reward responsiveness" was strongly associated with PSU5 "withdrawal." Nodes BASR "BAS-reward responsiveness" and PSU6 "relapse" were the most central variables, while nodes BASR "BAS-reward responsiveness" and I2 "motor impulsivity" were the strongest bridge variables. The connections between the subdomains of BIS/BAS and the components of PSU and between the dimensions of impulsivity and the components of PSU may be particularly important in the development and maintenance of PSU. The central variables identified here, along with the bridge variables, could be promising and effective targets for the prevention and intervention of PSU.

Applying network analysis to understand the relationships between impulsivity and social media addiction and between impulsivity and problematic smartphone use.

Prior studies have revealed the relationships between impulsivity and social media addiction (SMA) and between impulsivity and problematic smartphone use (PSU) based on total scores on standardized self-report scales. However, there has been a lack of studies exploring how the dimensions of impulsivity and components of SMA or PSU are interrelated. The present study aimed to investigate the structural relationships between the dimensions of impulsivity and components of SMA and PSU and determine the critical bridge node using network analysis. A total of 325 healthy adults aged 18-36 years participated in the study. SMA and PSU were assessed using the Bergen Social Media Addiction Scale (BSMAS) and Smartphone Application-Based Addiction Scale (SABAS), respectively. Impulsivity was measured by the Barratt Impulsiveness Scale Version 11 (BIS-11). Network analysis was used to construct an SMA-Impulsivity network and a PSU-Impulsivity network. Bridge centrality (bridge expected influence, BEI) was estimated to identify influential bridge nodes. In addition to relationships within each community, network analysis revealed that the dimensions of impulsivity were closely associated with the components of SMA and PSU. Particularly, I2 "motor impulsivity" had a relatively strong connection with SMA3 "mood modification" and SMA4 "relapse" in the SMA-Impulsivity network, and with PSU2 "conflict" and PSU5 "withdrawal" in the PSU-Impulsivity network. Moreover, I2 "motor impulsivity" was identified as the most critical bridge node in both networks. These findings demonstrate potential pathways between different dimensions of impulsivity and the components of SMA and PSU, providing new evidence relevant to understanding the underlying mechanisms that account for how highly impulsive individuals develop SMA and PSU, and highlight the critical bridge node-motor impulsivity-that may be a promising and effective target for the prevention and treatment of SMA and PSU.

COVID-19-Related Self-Stigma, Post-Traumatic Stress Disorder, Insomnia, and Smartphone Addiction Among Frontline Government Workers with COVID-19 Pandemic Control Duties.

PurposeThe duties related to COVID-19 control and prevention may have caused psychological stress for the individuals in charge (eg, frontline government workers) and have reportedly led to mental health issues, such as insomnia and post-traumatic stress disorder (PTSD). However, the prevalence of these COVID-19-related disorders and their associated factors remain unclear. Therefore, the purpose of the present study was to investigate the prevalence rates of insomnia, PTSD, COVID-19-related self-stigma, and smartphone addiction, along with the identification of risk factors and protective factors for Taiwan frontline government workers with COVID-19 pandemic control duties.MethodsThe survey was carried out with 151 participants between September and October 2021. All participants completed the Fear of COVID-19 Scale (assessing fear of COVID-19), Self-Stigma Scale (assessing self-stigma during the COVID-19 pandemic), Smartphone Application-Based Addiction Scale (assessing the risk of smartphone addiction), Insomnia Severity Index (assessing insomnia), Impacts of Event Scale-6 (assessing PTSD), and a self-designed set of questions assessing trait resilience.ResultsThe results showed that the prevalence rate was 31.1% for insomnia and 33.8% for PTSD. Furthermore, service duration (adjusted odds ratio [AOR] = 0.93; 95% confidence interval [CI] = 0.86, 0.999) and trait resilience (AOR = 0.19; 95% CI = 0.08, 0.46) were protective factors and fear of COVID-19 (AOR = 1.91; 95% CI = 1.02, 3.57) was a risk factor for insomnia. Fear of COVID-19 (AOR = 2.63; 95% CI = 1.35, 5.14), self-stigma (AOR = 3.62; 95% CI = 1.19, 11.02), and smartphone addiction (AOR = 1.09, 95% CI = 1.001, 1.19) were risk factors, and trait resilience was a protective factor (AOR = 0.58; 95% CI = 0.29, 1.17) for PTSD.ConclusionThe findings demonstrated a high prevalence of insomnia and PTSD. Risk-reducing strategies and protective factor promotion strategies are recommended to help reduce the symptoms of insomnia and PTSD among Taiwan frontline government workers.

Associations of Problematic Internet Use, Weight-Related Self-Stigma, and Nomophobia with Physical Activity: Findings from Mainland China, Taiwan, and Malaysia.

Insufficient physical activity is a common problem for university students because they may engage in sedentary lifestyle owing to excessive time spent on their smartphones and social media use. This may result in problematic internet use (PIU) and nomophobia (fear of not having a mobile phone). Moreover, prior evidence shows that weight-related self-stigma is an important factor contributing to low physical activity. Therefore, the present study examined the associations between PIU, nomophobia, and physical activity among university students across mainland China, Taiwan, and Malaysia. Participants (3135 mainland Chinese, 600 Taiwanese, and 622 Malaysian) completed the Bergen Social Media Addiction Scale (BSMAS), Smartphone Application-Based Addiction Scale (SABAS), Nomophobia Questionnaire (NMPQ), Weight Self-Stigma Questionnaire (WSSQ), and International Physical Activity Questionnaire Short Form (IPAQ-SF). The measurement invariance of the assessed questionnaires was supported across the three regions. The present findings analyzed using partial least squares structural equation modeling showed that (i) greater nomophobia was associated with higher levels of physical activity, (ii) greater weight-related self-stigma was associated with higher levels of physical activity, and (iii) greater nomophobia was associated with greater weight-related self-stigma. Although the present findings suggest the possibility that experiencing some level of nomophobia or weight-related self-stigma appears to help improve physical activity, it is not recommended that these be encouraged, but reducing PIU should be targeted as a means to improve physical activity.

Effects of sleep quality on the association between problematic internet use and quality of life in people with substance use disorder.

Problematic internet use, especially in people with substance use disorder, may negatively affect their quality of life (QoL). However, it is unclear whether sleep quality is a key mediator in the association between problematic internet use and QoL among people with substance use disorder. This study aimed to investigate the relationship between problematic internet use and QoL and how sleep quality may mediate the association between these two variables. Overall, 319 people (85% male) with substance use disorder (mean age 42.2 years, s.d. 8.9) participated in a cross-sectional study in Taiwan. The Smartphone Application-Based Addiction Scale, Bergan Social Media Addiction Scale, Internet Gaming Disorder-Short Form, Pittsburgh Sleep Quality Index and World Health Organization Quality of Life Questionnaire Brief Version were used. The prevalence of sleep problems was 56%. There were significant and direct associations between sleep quality and two types of problematic internet use, and between sleep quality and different dimensions of QoL. All types of problematic internet use were significantly and negatively correlated with QoL. Mediated effects of sleep quality in relationships between the different types of problematic internet use and all dimensions of QoL were significant, except for problematic use of social media. Different types of problematic internet use in people with substance use disorder may be directly associated with reduced QoL. Sleep quality as a significant mediator in this association may be an underlying mechanism to explain pathways between problematic internet use and QoL in this population.

Internet-Related Instruments (Bergen Social Media Addiction Scale, Smartphone Application-Based Addiction Scale, Internet Gaming Disorder Scale-Short Form, and Nomophobia Questionnaire) and Their Associations with Distress among Malaysian University Students.

The present study evaluated the psychometric properties of four instruments related to internet use, namely the Bergen Social Media Addiction Scale (BSMAS), Smartphone Application-Based Addiction Scale (SABAS), (nine-item) Internet Gaming Disorder Scale Short Form (IGDS9-SF), and Nomophobia Questionnaire (NMPQ) as well as their associations with psychological distress among Malaysian university students. A total of 380 Malaysian university students (71.6% females, mean age 24.0 years) were recruited through convenience sampling and completed an online survey including questions concerning socio-demographic background, social media addiction, smartphone addiction, internet gaming disorder, and nomophobia. Confirmatory factor analysis and Rasch analysis were applied to evaluate the psychometric properties of the instruments and Cronbach’s alpha value and McDonald’s omega value were used to confirm the internal consistency reliability of the instruments. The unidimensional structure was confirmed for the BSMAS, SABAS, and IGDS9-SF while the four-factor structure was confirmed for NMPQ. All instruments showed good internal consistency reliability. Promising validity and reliability were confirmed for BSMAS, SABAS, IGDS9-SF, and NMPQ. Therefore, they are useful to assess different types of problematic internet use among university students in Malaysia. Furthermore, a significant association was observed between internet use and psychological distress. The present study is the first to investigate the validity and reliability of BSMAS, SABAS, IGDS9-SF, and NMPQ among Malaysian university students using rigorous psychometric testing methods (i.e., Rasch analysis).

Reliability and validity study of the Indonesian Smartphone Application-Based Addiction Scale (SABAS) among college students

Background/ObjectiveSmartphone addiction, smartphone dependence, and compulsive smartphone use all describe similar phenomena that can cause problems in everyday daily life in many countries worldwide. Most scholars agree that it is the applications on smartphones that individuals have problems with rather than the smartphone itself. For this reason, smartphone application-based addiction is an issue of concern and one instrument has been specifically developed to assess this risk, namely, the Smartphone Application-Based Addiction Scale (SABAS). Although the SABAS has been translated into a number of languages, it has not been translated or validated into Indonesian. MethodsThe SABAS was translated into Bahasa Indonesian utilizing a cross-cultural method to ensure its linguistic validity. The linguistic validity of the Indonesian SABAS was ensured using international standard translation guidelines. Moreover, reliability and validity testing of the translated Indonesian SABAS were carried out using Cronbach’s α, McDonald’s ω, confirmatory factor analysis (CFA), and correlations with psychometric scales assessing psychological distress and nomophobia. ResultsUsing a sample of 458 participants (mean age = 22.46 years), reliability tests showed that the Indonesian SABAS was acceptable (Cronbach α = 0.74; McDonald’s ω = 0.79). Construct validity of the Indonesian SABAS was supported by satisfactory CFA fit indices; concurrent validity supported by good correlations with psychological distress (r = 0.50) and nomophobia (r = 0.61). ConclusionsThe Indonesian version of SABAS is valid and reliable to be used for assessing the risk of smartphone application-based addiction in college students.

Demographic characteristics, family environment and psychosocial factors affecting internet addiction in Chinese adolescents

BackgroundInternet addiction of adolescents has aroused social concern recently. The present study aims to identify predicting factors of internet addiction on adolescents. MethodsThe demographic characteristics and psychological characteristics of 50, 855 middle school students were investigated through Internet Gaming Disorder Scale- Short Form(IGDS9-SF), Smartphone Application-Based Addiction Scale (SABAS), Bergen Social Media Addiction Scale (BSMAS), Strengths and Difficulties Questionnaire-students (SDQS), 16-Item Version of the Prodromal Questionnaire (PQ-16), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7-item (GAD-7), Multidimensional Peer Victimization Scale (MPVS), Warwick-Edinburgh Mental Well-being Scale (WEMWBS), and Connor-Davidson Resilience Scale (CD-RISC10) were used to analyze factors associated with internet addiction by Pearson correlation coefficient and multiple hierarchical regression. ResultsIGDS9-SF, SABAS and BSMAS are positively correlated with SDQS, PQ-16, PHQ-9, GAD-7 and MPVS (r-values ranging from 0.180 to 0.488, p < 0.01). IGDS9-SF, SABAS and BSMAS are negatively correlated with WEMWB and CD-RISC (r-values ranging from −0.242 ~ −0.338, p < 0.01). Multiple hierarchical regression shown gender, one-child, twins, left-behind, rural, education (father), drink (father), smoke (father), CD-RISC-10, SDQS, PQ-16, PHQ-9, GAD-7 and MPVS predicted 32.7 % of the variance in internet gaming disorder (IGD) (F = 1174.949, p < 0.001). Group (junior and senior), Gender, Age, One-Child, Twins, Village, Education (father), Drink (father), Drink (mother), Smoke (father), WEMWBS, CD-RISC-10, SDQS, PQ-16, PHQ-9, GAD-7 and MPVS predicted 28.9 % of the total variance in social media addiction (SMA) (F = 982.932, p < 0.001). Fifteen variables [Gender, Age, Twins, Left-behind, Residence, Residence, Education (mother), Drink(father), Drink (mother), Smoke (father), WEMWBS, CD-RISC-10, PHQ-9, GAD-7 and MPVS] predicted 30.7 % of the variance in smartphone addiction (SA) (F = 1076.02, p < 0.001). ConclusionThe present study found that demographic characteristics, family environment and psychosocial factors were associated with internet gaming addiction, social media addiction and smartphone addiction. Negative psychological factors (such as anxiety and depression) play an important role in different behavioral addictions.

Does Smartphone Addiction, Social Media Addiction, and/or Internet Game Addiction Affect Adolescents' Interpersonal Interactions?

The purpose of this study is to investigate the correlations that levels of addiction to smartphones, social media, and online games have with levels of real-life and online interpersonal interactions among adolescents. In this cross-sectional study of adolescents in a college in Taiwan, structured questionnaire surveys were used to collect information. The questionnaire included the following: demographic background, Real Interpersonal Interaction Scale (RIIS), Internet Interpersonal Interaction Scale (IIIS), Smartphone Application-Based Addiction Scale (SABAS), Bergen Social Media Addiction Scale (BSMAS), and Internet Gaming Disorder Scale—Short Form (IGDS9-SF). Multiple regression analyses were carried out to investigate the correlations between SABAS, BSMAS, IGDS9-SF, and RIIS/IIIS. We recruited 998 students (413 boys). The average age was 17.18 ± 1.46. The study results show that adolescents with higher levels of addiction to smartphones and social media may have greater interpersonal interaction with friends in real life, but adolescents with high levels of addiction to online games may have less interpersonal interactions with friends in real life. Adolescents with high levels of addiction to smartphones, social media, and online games may have greater interpersonal interactions with friends online.

Adaptation and psychometric properties of an Arabic version of the smartphone addiction scale (SAS) in the context of Saudi Arabia

BackgroundThe growing accessibility to smartphones has raised concerns about addictive patterns associated with these technologies. A Smartphone Addiction Scale has been developed to assess individuals’ smartphone addiction. However, the psychometric properties of the Smartphone Addiction Scale are scarce in the context of Saudi Arabia. AimsThis study aimed to translate and adapt the Smartphone Addiction Scale (SAS) to Arabic and examine the psychometric properties of the Arabic scale in the context of Saudi Arabia. MethodsForward and backward translations were performed on the English SAS, as recommended by the World Health Organization (WHO, 2016). The translated version was initially administered to 20 students in a pilot study. In the full study, a sample of 624 participants (52.5% females, mean age = 25 years) responded to questionnaires containing SAS, the Hospital Anxiety and Depression Scale, and the Smartphone Application-Based Addiction Scale. The survey was sent via online platforms in order to reach as many and diverse participants as possible. Exploratory and confirmatory factor analyses were conducted. ResultsThe EFA resulted in a structure of six factors and the CFA indicated that the 6-factor model (daily disturbance, positive anticipation, withdrawal, cyberspace-oriented relationships, overuse, and tolerance) had a good fit in Saudi Arabia (CFI = 0.92, TLI = 0.90, RMSEA = 0.04, SRMR = 0.04). The scale was also gender invariant and exhibited adequate reliability and convergent and concurrent validity. ConclusionsThe SAS is a reliable and valid measure that can be used to assess smartphone addiction in Saudi Arabia.