The Relationship between Time Spent Online and Internet Addiction among Chinese College Freshmen: A Mediated Moderation Model

Zhang, Jintao; Chen, Chao; WANG, Lingjiao; Liu, Lu; Liu, Fenge; ZHAO, Fengchun; DENG, Linyuan; Fang, Xiaoyi

doi:10.3724/sp.j.1041.2014.01521

Cited by 21 publications

(16 citation statements)

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“…Internet addiction is also called pathological Internet use or Internet overuse. The term refers to network usage behavior in which individuals cannot control themselves and the behavior impairs the daily function (Niu G. et al, 2013; Zhang et al, 2013). Like other addictive behaviors, Internet addiction can characterize by (i) overuse (ii) withdrawal and anger or depression when computers are unavailable; (iii) tolerance (more time to use to meet needs); and (iv) negative social impact (Block, 2008).…”

Section: Introductionmentioning

confidence: 99%

The Relationship Between Adolescents’ Stress and Internet Addiction: A Mediated-Moderation Model

Feng

Zhong

2019

Front. Psychol.

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This cross-sectional study explored the impact of stress, social anxiety, and social class on Internet addiction among adolescents. The subjects—1,634 middle school students—were investigated using the Chinese Perceived Stress Scale (CPSS), the Social Anxiety Scale for Adolescents (SAS-A) Chinese Short Form, the Chinese Internet Addiction Scale (CIAS), and the Questionnaire of Family Social-economic Status. The results show that 12% of the adolescents investigated showed signs of Internet addiction. With the increase of grade, the tendency of Internet addiction and the number of addicts gradually increased. It also showed that Internet addiction is positively correlated with stress and social anxiety and negatively correlated with social class. Social anxiety partially mediates the impact of stress on Internet addiction and social class indirectly influences Internet addiction by moderating the relationship between stress and social anxiety. In conclusion, there is a mediated-moderation effect between stress and adolescent Internet addiction This means that adolescents from different social classes have different types of anxiety when they feel the stress, which influences their choices concerning internet use.

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Section: Introductionmentioning

confidence: 99%

The Relationship Between Adolescents’ Stress and Internet Addiction: A Mediated-Moderation Model

Feng

Zhong

2019

Front. Psychol.

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“…Social media can influence health knowledge, beliefs, and attitudes, and also health behaviors, especially for large groups of people [ 9 ]. Recently, with the dramatic growth of Web 2.0 technologies, online social networks have also grown and account for approximately 27.18% of all time spent online among Chinese college freshmen [ 12 ]. Because online social networks have several advantages, such as a large audiences, higher levels of user engagement [ 13 ], and higher retention levels of existing contacts [ 14 ], they might have numerous potential effects on changing health behaviors [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Social Media–Promoted Weight Loss Among an Occupational Population: Cohort Study Using a WeChat Mobile Phone App-Based Campaign

He¹,

Wu²,

Zhao³

et al. 2017

J Med Internet Res

131

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BackgroundBeing overweight and obese are major risk factors for noncommunicable diseases such as cardiovascular diseases. The prevalence of overweight and obesity is high throughout the world and these issues are very serious in the Shunyi District in China. As mobile technologies have rapidly developed, mobile apps such as WeChat are well accepted and have the potential to improve health behaviors.ObjectiveThis study aims to evaluate the effectiveness of a mobile app (WeChat) as an intervention on weight loss behavior.MethodsThis study was conducted among an occupational population from August 2015 to February 2016 in the Shunyi District of Beijing. Before the intervention, the Shunyi District Government released an official document for weight loss to all 134 government agencies and enterprises in Shunyi District. Participants willing to use our official WeChat account were enrolled in a WeChat group and received 6 months of interventions for weight loss; those who were not willing to use the account were in a control group given routine publicity on weight loss.ResultsIn total, 15,310 occupational participants including 3467 participants (22.65%) in the control group and 11,843 participants (77.35%) in the WeChat group were enrolled. Participants in the WeChat group lost more weight (mean 2.09, SD 3.43 kg) than people in the control group (mean 1.78, SD 2.96 kg), and the difference in mean weight loss between the two groups for males was significant based on the stratification of age and educational level. To control for confounding factors and to explore the effects of WeChat on weight loss, the propensity score method with a multinominal logistic regression was utilized. For males, this showed that the WeChat group (with both active and inactive subgroups) had a higher probability of maintaining weight, weight loss from 1 to 2 kg, or weight loss more than 2 kg than the control group. However, the control group had higher probability of weight loss from 0 to 1 kg. Being active in WeChat was likely to be associated with weight loss. The more active participants were in the weight loss program via WeChat, the more weight they lost.ConclusionsThe weight loss intervention campaign based on an official WeChat account focused on an occupation-based population in Shunyi District was effective for males. The more active male participants were in using WeChat, the more weight they lost. There might be no effect or there may even be a negative effect on weight loss for females. Future research should focus on how to improve adherence to the WeChat weight loss interventions, to improve and refine the WeChat content such as developing a variety of materials to attract interest, and to protect personal privacy, especially for females.

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“…Previous studies have reported that uncontrolled Internet use is closely related to a decline in family communication and supervision ( Van den Eijnden et al, 2010 ; Liu et al, 2012 ). Thus, the shift in interpersonal relationships tends to place college freshmen at risk of developing IA ( Zhang et al, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Reciprocal Relationship between Internet Addiction and Network-Related Maladaptive Cognition among Chinese College Freshmen: A Longitudinal Cross-Lagged Analysis

Han

2017

Front. Psychol.

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This study explored the reciprocal relationship between Internet addiction (IA) and network-related maladaptive cognition (NMC) in Chinese college freshmen. A short-term longitudinal survey with a sample of 213 college freshmen was conducted in Shandong province, China. The results revealed that IA can significantly predict the generation and development of NMCs, and that when such maladaptive cognitions have been established, they can further adversely affect the extent of the students’ IA. A vicious cycle was observed between these two variables, with IA having predictive priority in its relationship with NMC. This study also determined that the relationship between these two variables was the same for both males and females; therefore, the final model we established can be extensively applied to Chinese college freshmen, regardless of gender. Understanding the reciprocal relationship between these two variables can assist in interventions in IA at the outset of students’ college life.

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The Relationship between Time Spent Online and Internet Addiction among Chinese College Freshmen: A Mediated Moderation Model

Cited by 21 publications

References 0 publications

The Relationship Between Adolescents’ Stress and Internet Addiction: A Mediated-Moderation Model

The Relationship Between Adolescents’ Stress and Internet Addiction: A Mediated-Moderation Model

Social Media–Promoted Weight Loss Among an Occupational Population: Cohort Study Using a WeChat Mobile Phone App-Based Campaign

Reciprocal Relationship between Internet Addiction and Network-Related Maladaptive Cognition among Chinese College Freshmen: A Longitudinal Cross-Lagged Analysis

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