The heterogeneity of social anxiety symptoms among Chinese adolescents: Results of latent profile analysis

2020 ◽  
Vol 274 ◽  
pp. 935-942
Author(s):  
Meng Yu ◽  
Hui Zhou ◽  
Meifang Wang ◽  
Xinfeng Tang
2018 ◽  
Vol 59 ◽  
pp. 74-81 ◽  
Author(s):  
Meng Yu ◽  
Gregory S. Chasson ◽  
Mengcheng Wang ◽  
Yawen Zhu ◽  
Qian Xu ◽  
...  

2014 ◽  
Vol 34 (2) ◽  
pp. 282-293 ◽  
Author(s):  
Chee Keng John Wang ◽  
Yanlin Sun ◽  
Woon Chia Liu ◽  
Jiaxin Yao ◽  
Do Young Pyun

2021 ◽  
Author(s):  
Tomosumi Haitani ◽  
Naomi Sakai ◽  
Koichi Mori ◽  
Tomohito Houjou

Purpose: Adults who stutter (AWS) often experience social anxiety. Social anxiety is explained by several situational factors, one of which is a factor for telephone, which is unique to AWS. This unique social anxiety, which has not been observed in individuals with social anxiety disorder (SAD), may lead to heterogeneity or distinct subtypes of AWS. The present study aimed to investigate the heterogeneity of social anxiety in AWS in terms of feared social situations.Methods: Social anxiety was measured using the fear/anxiety scale of the Liebowitz Social Anxiety Scale (LSAS). The scores of the five subscales in the LSAS in 562 AWS were analyzed using latent profile analysis. First, the number of latent classes (subtypes) was determined through statistical criteria and interpretability. Next, the profiles of social anxiety, demographic data, communication attitudes, and the overall severity of social anxiety of the subtypes were investigated.Results: Five latent class solutions led to good classifications. About one-quarter of AWS (156) were included in a subtype with sub-clinical levels of overall severity of social anxiety but severe social anxiety in telephone situations. Among them, 100 AWS showed severe social anxiety only in telephone situations. Psychosocial factors, including employment status and communication attitude, were related to extracted subtypes.Conclusions: Some AWS have severe social anxiety specific to telephone situations, which is not proportional to the overall severity of social anxiety. The telephone-specific subtype of social anxiety has not been empirically extracted in principal diagnosis of SAD and can be unique in AWS.


2020 ◽  
Vol 9 (3) ◽  
pp. 698-708
Author(s):  
Ji-Bin Li ◽  
Anise M.S. Wu ◽  
Li-Fen Feng ◽  
Yang Deng ◽  
Jing-Hua Li ◽  
...  

AbstractBackground and aimsProblematic online social networking use is prevalent among adolescents, but consensus about the instruments and their optimal cut-off points is lacking. This study derived an optimal cut-off point for the validated Online Social Networking Addiction (OSNA) scale to identify probable OSNA cases among Chinese adolescents.MethodsA survey recruited 4,951 adolescent online social networking users. Latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses were applied to the validated 8-item OSNA scale to determine its optimal cut-off point.ResultsThe 3-class model was selected by multiple criteria, and validated in a randomly split-half subsample. Accordingly, participants were categorized into the low risk (36.4%), average risk (50.4%), and high risk (13.2%) groups. The highest risk group was regarded as “cases” and the rest as “non-cases”, serving as the reference standard in ROC analysis, which identified an optimal cut-off point of 23 (sensitivity: 97.2%, specificity: 95.2%). The cut-off point was used to classify participants into positive (probable case: 17:0%) and negative groups according to their OSNA scores. The positive group (probable cases) reported significantly longer duration and higher intensity of online social networking use, and higher prevalence of Internet addiction than the negative group.ConclusionsThe classification strategy and results are potentially useful for future research that measure problematic online social networking use and its impact on health among adolescents. The approach can facilitate research that requires cut-off points of screening tools but gold standards are unavailable.


Sign in / Sign up

Export Citation Format

Share Document