Classification of probable online social networking addiction: A latent profile analysis from a large-scale survey among Chinese adolescents

The interplay of psychological resilience and adolescent mobile phone addiction in Henan province, China: insights from latent class analysis

Background

The aim of this study was to classify distinct subgroups of adolescents based on the severity levels of their mobile phone addiction and to investigate how these groups differed in terms of their psychosocial characteristics. We surveyed a total of 2,230 adolescents using three different questionnaires to assess the severity of their mobile phone addiction, stress, anxiety, depression, psychological resilience, and personality. Latent class analysis was employed to identify the subgroups, and we utilized Receiver Operating Characteristic (ROC) curves and multinomial logistic regression for statistical analysis. All data analyses were conducted using SPSS 26.0 and Mplus 8.5.

Methods

We classified the subjects into subgroups based on their mobile phone addiction severity, and the results revealed a clear pattern with a three-class model based on the likelihood level of mobile phone addiction (p < 0.05). We examined common trends in psychosocial traits such as age, grade at school, parental education level, anxiety levels, and resilience. ROC analysis of sensitivity versus 1-specificity for various mobile phone addiction index (MPAI) scores yielded an area under the curve (AUC) of 0.893 (95% CI, 0.879 to 0.905, p < 0.001). We also determined diagnostic value indices for potential cutoff points ranging from 8 to 40. The optimal cutoff value for MPAI was found to be >14, which corresponded to the maximum Youden index (Youden index = 0.751).

Results

The latent classification process in this research confirmed the existence of three distinct mobile phone user groups. We also examined the psychosocial characteristics that varied in relation to the severity levels of addiction.

Conclusion

This study provides valuable insights into the categorization of adolescents based on the severity of mobile phone addiction and sheds light on the psychosocial characteristics associated with different addiction levels. These findings are expected to enhance our understanding of mobile phone addiction traits and stimulate further research in this area.

Characteristics and influencing factors of anticipated HIV stigma among HIV-negative/unknown MSM in China: A regression mixture model

BACKGROUND

Anticipated HIV stigma among men who have sex with men's (MSM) has a severe negative effect on their physical and mental health wellbeing and hence requires specific attention. The current study aims to identify the characteristics and the psychosocial influencing factors of anticipated HIV stigma in MSM using regression mixture model (RMM) and to determine the cut-off point of the seven-item Anticipated HIV Stigma Questionnaire (AHSQ) using the receiver operating characteristic (ROC) analysis.

METHODS

A cross-sectional study was conducted among HIV-negative/unknown MSM from Blued online platform in China from December 16th, 2020 to March 1st, 2021, enrolling 1394 participants. Data were collected on demographic characteristics, perceived social support, anticipated HIV stigma, depressive symptoms, and HIV knowledge. Latent profile analysis was performed to identify different profiles of anticipated HIV stigma level. Chi-square test, analysis of variance, and RMM analysis were conducted to explore the influencing factors in different profiles. ROC analyses were carried out to identify the cut-off value of anticipated stigma.

RESULTS

Among the participants, three profiles of anticipated stigma were identified: "low anticipated HIV stigma" (12.0%), "moderate anticipated HIV stigma" (52.1%), and "severe anticipated HIV stigma" (35.9%). RMM analysis showed that higher income and higher levels of knowledge were positively associated with moderate anticipated HIV stigma, whereas full-time job and social support were negatively associated with moderate anticipated HIV stigma; higher income, depressive symptoms, and knowledge were positively associated with severe anticipated HIV stigma, whereas minor ethnicity and social support were negatively associated with severe anticipated HIV stigma. ROC curve of the AHSQ showed that the optimal cut-off value of ≥16 could indicate positive anticipated HIV stigma.

CONCLUSION

The study focuses on the level of anticipated HIV stigma and its psycho-socio influencing factors among HIV-negative/unknown MSM. It provides evidence for implementing relevant psychological interventions to HIV-negative/unknown MSM.

Depression and stress are associated with latent profiles of problematic social media use among college students

Background

The previous literature has demonstrated that depression, anxiety, and stress are significant predictors of problematic social media use. However, the manifestation of problematic social media use varies, and the predictive relationship between depression, anxiety, and stress with different subgroups of problematic social media use remains unclear. The aim of this research was to evaluate latent subgroups of problematic social media use among college students and to investigate the impact of depression, anxiety, and stress on these latent subgroups.

Methods

A survey was carried out among college students in China using a cross-sectional approach. A total of 955 participants were included, with a mean age of 19.50 ± 1.22 years. Participants completed questionnaires containing the Bergen Social Media Addiction Scale (BSMAS) and the Depression, Anxiety, and Stress Scale-21 (DASS-21). The study employed latent profile analysis (LPA) to investigate latent subgroups of Chinese college students with problematic social media use, and a robust three-step approach was used to develop predictive regression mixed models of depression, anxiety, and stress on latent subgroups.

Results

Problematic social media use of Chinese college students can be categorized into four latent subgroups, namely, the high-risk group, the moderate-risk with pleasure group, the moderate-risk with compulsion group, and the low-risk group. The regression model showed that there was a significant difference between the high-risk group and the low-risk group on the stress scale. There was a significant difference between the moderate-risk with pleasure group and the moderate-risk with compulsion group on the depression scale.

Conclusion

Problematic social media use is heterogeneous, with depression and stress being potentially key factors influencing problematic social media use. Depression would make college students more likely to be moderate-risk with compulsion problematic social media users than moderate-risk with pleasure problematic social media users, and stress would make college students more likely to be high-risk problematic social media users than low-risk problematic social media users.

Evaluation of the nutrition literacy assessment questionnaire for college students and identification of the influencing factors of their nutrition literacy

BACKGROUND

Nutrition health has become a major public health issue in both high and middle-income countries. Nutrition literacy is an important indicator to evaluate the effect of public health intervention and one of the important concepts in health promotion. Thus, this study aimed to verify the reliability and validity of a nutrition literacy assessment questionnaire (NLAQ) and investigate the associated factors of nutrition literacy among college students.

METHODS

We conducted a cross-sectional online survey of college students from April to November 2022 in Wuhan (N = 774). We employed the Cronbach's alpha coefficient, exploratory and confirmatory factor analysis to evaluate the reliability and validity. We used latent profile analysis to classify the nutrition literacy. We conducted Chi-square test and binary logistic regression to identify the influencing factors.

RESULTS

The Cronbach's alpha coefficient of the NLAQ and its dimension was ranging from 0.837 to 0.909. The common factors were consistent with the original dimensions. All indicators met the requirements (χ2/df = 6.16 < 8, GFI = 0.929, NFI = 0.939, CFI = 0.948, RMSEA = 0.082 < 0.1). College students' disciplines (χ2 = 7.769, P = 0.021), mothers' education level (χ2 = 26.599, P < 0.001), and fathers' occupation type (χ2 = 11.218, P = 0.024) had impacts on nutrition literacy.

CONCLUSION

The NLAQ has good reliability and validity, and could be used as a measurement tool to evaluate college students' nutrition literacy. Schools and families should take targeted measures to improve the college students' nutrition literacy.

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

BACKGROUNDS

The 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).

METHOD

We 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).

RESULTS

LPA 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%).

CONCLUSION

A 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 Screening Instruments for Social Network Use Disorder in Children and Adolescents: A Systematic Review

IMPORTANCE

Children and adolescents spend considerable time on the internet, which makes them a highly vulnerable group for the development of problematic usage patterns. A variety of screening methods have already been developed and validated for social network use disorder (SNUD); however, a systematic review of SNUD in younger age groups has not been performed.

OBJECTIVE

To review published reports on screening tools assessing SNUD in children and adolescents with a maximum mean age of 18.9 years.

EVIDENCE REVIEW

To identify instruments for the assessment of SNUD, a systematic literature search was conducted in the databases PsycINFO, PubMed, Web of Science, PsycArticles, and Scopus. The final search took place on May 2, 2022. Psychometric properties of available tools were examined and evaluated to derive recommendations for suitable instruments for individuals up to 18 years of age.

FINDINGS

A total of 5746 publications were identified, of which 2155 were excluded as duplicates. Of the remaining 3591 nonredundant publications, 3411 studies were assessed as not relevant after title and abstract screening. A full-text analysis of 180 remaining studies classified as potentially eligible resulted in a final inclusion of 29 studies revealing validation evidence for a total of 19 tools. The study quality was mostly moderate. With regard to validation frequency, 3 tools exhibited the largest evidence base: Social Media Disorder Scale (SMDS), the short version of the Bergen Facebook Addiction Scale, and Bergen Social Media Addiction Scale-Short Form (BSMAS-SF). Among these, 1 study tested a parental version (SMDS-P) for its psychometric properties. Taking all criteria into account, the strongest recommendation was made for the SMDS and BSMAS-SF.

CONCLUSIONS AND RELEVANCE

Results suggest that the SMDS-SF and BSMAS-SF were appropriate screening measures for SNUD. Advantages of the SMDS are the availability of a short version and the possibility of an external parental rating.

Perceived stigma among discharged patients of COVID-19 in Wuhan, China: A latent profile analysis

Background

Perceived stigma has greatly influenced the life quality of the COVID-19 patients who recovered and were discharged (RD hereafter). It is essential to understand COVID-19 stigma of RD and its related risk factors. The current study aims to identify the characteristics of perceived COVID-19 stigma in RD using latent profile analysis (LPA), to explore its psycho-social influencing factors, and to determine the cut-off point of the stigma scale using receiver operating characteristic (ROC) analysis.

Methods

A cross-sectional study was conducted among COVID-19 RD in 13 communities in Jianghan District, Wuhan City, Hubei Province, China from June 10 to July 25, 2021, enrolling total 1,297 participants. Data were collected on demographic characteristics, COVID-19 perceived stigma, post-traumatic stress disorder (PTSD), anxiety, depression, sleep disorder, fatigue, resilience, social support, and peace of mind. LPA was performed to identify different profiles of perceived COVID-19 stigma level. Univariate analysis and multinominal logistic regression analysis were conducted to explore the influencing factors in different profiles. ROC analyses was carried out to identify the cut-off value of perceived stigma.

Results

Among the participants, three profiles of perceived stigma were identified: "low perceived COVID-19 stigma" (12.8%), "moderate perceived COVID-19 stigma" (51.1%), and "severe perceived COVID-19 stigma" (36.1%). Multinominal logistic regression analysis revealed that older age, living with other people, anxiety, and sleep disorder were positively associated with moderate perceived COVID-19 stigma, while higher educational level was negatively associated with moderate perceived COVID-19 stigma. Female, older age, living with other people, anxiety, and sleep disorder were positively associated with severe perceived COVID-19 stigma, while higher educational level, social support, and peace of mind were negatively associated with severe perceived COVID-19 stigma. ROC curve of the Short Version of COVID-19 Stigma Scale (CSS-S) for screening perceived COVID-19 stigma showed that the optimal cut-off value was ≥ 20.

Conclusion

The study focuses on the issue of perceived COVID-19 stigma and its psycho-socio influencing factors. It provides evidence for implementing relevant psychological interventions to COVID-19 RD.

Distinct patterns of problematic smartphone use and related factors in Chinese college students

BACKGROUND

This study aimed to categorize different subgroups of problematic smartphone use in Chinese college students. Differences in gender and psychosocial characteristics of the categorized groups were also examined.

METHODS

A total of 1123 participants completed the Mobile Phone Addiction Index Scale, the Center for Epidemiologic Studies Depression Scale, the Perceived Social Support Scale, and the Perceived Stress Scale. Using latent profile analysis, we identified different subgroups of problematic smartphone use in college students. Multivariate logistic regression analysis was implemented to examine the relationship between latent classes and demographic and psychosocial covariates.

RESULTS

The four following latent classes were identified: a low-risk group, a moderate-risk with no evasiveness group, a moderate-risk with evasiveness group, and high-risk group that accounted for 11%, 24.1%, 35.5%, and 29.4% of the total sample, respectively. Further analysis revealed that female participants were more likely to be in the moderate-risk with evasiveness and high-risk groups, and individuals with depressed mood were more likely to be in the moderate-risk and high-risk groups.

CONCLUSIONS

Classifying college students according to the features of problematic smartphone use is potentially useful for understanding risk factors and developing targeted prevention and intervention programs.

Needs affordance as a key factor in likelihood of problematic social media use: Validation, latent Profile analysis and comparison of TikTok and Facebook problematic use measures

Despite increasing concerns of maladaptive cognitive responses associated with social media, estimates of its prevalence are lacking in the literature. Further, existing studies have disproportionately focused on Facebook, while ignoring the penetration of TikTok and concerns of associated maladaptive behaviors. This study aims to 1) validate scale measures for problematic Facebook and TikTok use (PFU and PTTU) 2) comparatively assess the underlying cognitive pathways of the PFU and PTTU among a sample of university students, 3) determine the cut-off score of the PTTU assessment scale using Latent Profile Analysis (LPA) and 4) evaluate the contribution of specific criteria in the diagnosis of PTTU. The scales used to assess PFU and PTTU were found to have appropriate psychometric properties. The scores between the PFU and PTTU scales were found to be strongly associated, however, the relationship was stronger in the group of Facebook users than in the group of TikTok users. Further, the manifestation of problematic use was not consistent between TikTok and Facebook. Loneliness was positively associated with both PFU and PTTU, while self-esteem was negatively associated with PFU only. The optimal cut-off score of the PTTU scale was determined to be 21, giving 8.7% as the estimated prevalence of PTTU. The criteria with the highest predictive power in the diagnosis of addiction among university students were "withdrawal" and "relapse". The study concludes that while the underlying addiction pathways are similar between platforms the manifestation of maladaptive behavior and the drivers for usage intensity and problematic use are unique.

Status and Influencing Factors of Social Media Addiction in Chinese Medical Care Professionals: A Cross-Sectional Survey

Background

In modern society, social media addiction (SMA) has become a serious problem in many countries, including China. Almost every medical care professional has their own social media account. They are also at risk for SMA, but no SMA studies in Chinese medical care professionals have been published. This study aims to investigate the status and influencing factors of SMA among Chinese medical care professionals.

Methods

A cross-sectional study was conducted among 519 physicians and nurses from two randomly selected hospitals using a questionnaire that included the Social Networking Service Addiction Scale (SNSAS), Maslach's Burnout Inventory-General Survey (MBI-GS), the General Self-efficacy Scale (GSES), and eight demographic datasets.

Results

This study's findings showed that most of the participants' (357,68.79%) scores reached 2.5 points (half of the highest possible score), indicating that SMA scores of Chinese medical care professionals were relatively high. Significant differences in SMA scores by age (p < 0.01), marital status (p < 0.01), professional title (p < 0.01), and working years (p < 0.01) were found. Income satisfaction (p < 0.01) and sleep quality (p < 0.05) were negatively correlated with SMA. The GSES score was not correlated with SMA (p = 0.377). Burnout significantly positively affected SMA (p < 0.01).

Conclusion

Our study found that the SMA scores of Chinese medical care professionals were relatively high. To reduce the SMA level of the medical care population, we should first start with reducing burnout, enabling medical care professionals to achieve sufficient sleep, increasing medical staff income, and providing more opportunities for promotion.

What Is the Optimal Cut-Off Point of the 10-Item Center for Epidemiologic Studies Depression Scale for Screening Depression Among Chinese Individuals Aged 45 and Over? An Exploration Using Latent Profile Analysis

Background

The main objective of the current study was to gain insight into the heterogeneity and profiles of depressive symptoms in Chinese individuals aged 45 and over and to determine the optimal cut-off point for the 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10) to provide a reference for future practical application.

Methods

The participants were 16,997 Chinese community-dwelling adults aged 45 years or older who completed survey interviews for the 2018 China Health and Retirement Longitudinal Study. The current study utilised latent profile analysis (LPA) to identify distinct profiles based on participants' responses to CES-D-10 items, and receiver operating characteristic (ROC) curve analyses were applied to determine the optimal cut-off point for the CES-D-10 scale.

Results

A three-profile solution was suggested as the optimum and included a "minimal depression" group (63.1%), "mild depression" group (23.4%) and "moderate-severe depression" group (13.5%); 36.9% (95% CI: 36.2 ∼ 37.6%) were considered at risk for probable depression. The "minimal depression" group was viewed as "non-cases," and the remaining were viewed as "cases" that served as the reference standard for the ROC analysis, which obtained an AUC value of 97.8% (95% CI: 97.7-98.0%) and identified an optimal cut-off point of 10 (sensitivity:91.93%, specificity: 92.76%, and accuracy: 92.45).

Conclusion

The identification of these distinct profiles underscores the heterogeneity in depressive symptoms among Chinese middle-aged and older adults. The CES-D-10 scale was demonstrated to have acceptable psychometric properties, with a cut-off point of 10 recommended for future research and practical application.

Subpopulations of Addictive Behaviors in Different Sample Types and Their Relationships with Gender, Personality, and Well-Being: Latent Profile vs. Latent Class Analysis

BACKGROUND

Relatively strong theoretical assumptions and previous studies concerning co-occurring addictive behaviors suggest a subpopulation representing general proclivity to behavioral addictions (BAs), and there are gender-specific subpopulations. This study aimed to compare latent profile analysis (LPA) and latent class analysis (LCA) as the methods of investigating different clusters of BAs in the general student population and among students positively screened for at least one BA. Participants and procedure: Analyses of six BAs (study, shopping, gaming, Facebook, pornography, and food) and their potential antecedents (personality) and consequences (well-being) were conducted on a full sample of Polish undergraduate students (N = 1182) and a subsample (n = 327) of students including individuals fulfilling cutoff for at least one BA.

RESULTS

LPA on the subsample mostly replicated the previous four profiles found in the full sample. However, LCA on a full sample did not replicate previous findings using LPA and showed only two classes: those with relatively high probabilities on all BAs and low probabilities. LCA on the subsample conflated profiles identified with LPA and classes found with LCA in the full sample.

CONCLUSIONS

LCA on dichotomized scores (screened positively vs. negatively) were less effective in identifying clear patterns of interrelationships between BAs based on relatively strong theoretical assumptions and found in previous research. BAs can be investigated on the whole spectrum of behavior, and person-centered analyses might be more useful when they are based on continuous scores. This paper provides more detailed analyses of the four basic clusters of BAs, prevalence, and co-occurrence of particular BAs within and between them, their gender and personality risk factors, relationships to well-being, and their interrelationships as emerging from the results of this and previous studies.

Internet Behavior Preferences Predict Pathological Internet Use: A Latent Profile Analysis

Recent research in the underlying structure of pathological Internet use (PIU) has produced considerable debate among academics, in which a new “person-centered” approach of studying PIU has recently gathered support but produced mixed results. This study used the latent profile analysis (LPA) to estimate the types of PIU in a large sample of college students (n = 1,400, aged 17–25 years). Participants provided information on demographics, PIU, and Internet behavior preferences. The adolescent pathological Internet use (APIU), which served as the basis of LPA, was used for searching subgroups that represent participants with PIU. LPA identified the PIU classes, and regressions identified the psychological predictors of class membership. Participants were classified into pathological users, pathological-tendency users, preferential users, and ordinary Internet users. In comparison with pathological Internet users, lower Internet gaming and communication preference were associated with pathological-tendency users, preferential users, and ordinary Internet users. The distinct types of college students belong to each PIU class, suggesting that individual differences may be incorporated into the prevention efforts.

Modelling the Contribution of Metacognitions, Impulsiveness, and Thought Suppression to Behavioural Addictions in Adolescents

The most common behavioral addictions in adolescents are Internet Gaming Disorder (IGD), Compulsive Sexual Behavior Disorder (CSBD), and Problematic Social Networks Use (PSNU). In the present study, we investigated whether thought suppression and impulsiveness mediate the relationship between metacognitions and these three behavioral addictions (IGD, CSBD and PSNU). In Study 1 (n = 471), we examined whether online gaming thought suppression and impulsiveness mediate the relationship between metacognitions and IGD. In Study 2 (n = 453), we examined whether sex thought suppression and impulsiveness mediate the relationship between metacognitions and CSBD. In Study 3 (n = 1004), we examined whether social media thought suppression and impulsiveness mediate the relationship between metacognitions and PSNU. Results of path analysis indicated, across the three studies, the importance of both thought suppression and impulsiveness as mediators between metacognitions and the three behavioral addictions (IGD, CSBD and PSNU) being investigated. These findings provide an opportunity for therapists as well as educators to gain a better insight into the link between metacognitions, thought suppression, impulsiveness, and behavioral addictions as part of developmental behavior among adolescents.

The relationships between negative emotions and latent classes of smartphone addiction

The relationships between negative emotions and smartphone addiction has been tested through the literature. However, most of the studies applied variable-centered approaches. The heterogeneity of smartphone addiction severity has not been examined for the associations with negative emotion variables. The purposes of the present study is to explore the latent classes of smartphone addiction and analyze the relationships between depression, social anxiety and boredom and these subgroups. The Smartphone Addiction Scale-Short Version (SAS-SV) and three negative emotion scales were employed to conduct a survey of 539 college students. Mplus8.3 software was applied to perform the latent class analysis (LCA) based on the smartphone addiction symptom ratings. ANOVA and multinomial logistic regression were used to explore the differences among these latent categories and the associations between these subgroups and negative emotion variables. Results demonstrated that Negative emotional variables were significantly correlated with smartphone addiction proneness. Based on their scores on the Smartphone Addiction Scale, smartphone users were divided into three latent classes: low risk class, moderate class and high risk class. Women were more likely to be classified in the high-risk class. The severity of depression and boredom was able to predict the membership of the latent class effectively; while social anxiety failed to do this in the high risk class.