Development of the Preference for Online Social Interaction Scale for Chinese Adolescents

By You, Zhiqi; Tian, Yuan et al. | Social Behavior and Personality: an international journal, January 1, 2016 | Go to article overview

Development of the Preference for Online Social Interaction Scale for Chinese Adolescents


You, Zhiqi, Tian, Yuan, Kong, Fanchang, Zhou, Zongkui, Zheng, Youjie, Social Behavior and Personality: an international journal


With the popularization of the Internet, adolescents aged between 10 and 19 years have become the fastest growing Internet community in China according to the 27th statistical report on the China Internet Network Development State (China Internet Network Information Center, 2011). This statistic shows that the Internet is an integral part in the lives of adolescents, which significantly impacts their education, living style, how they communicate, and their values (Subrahmanyam, Smahel, & Greenfield, 2006; Valkenburg & Jochen, 2007). In the web-surfing activities of adolescents, communication behaviors occupy the majority of their time (Boneva, Quinn, Kraut, Kiesler, & Shklovski, 2006). Many adolescents in China communicate with each other through the Internet via social networking sites, instant messaging tools, emails, and multiplayer online games.

In light of this trend, a growing number of researchers have sought to improve their understanding of the interaction difference between online and face-to-face communication (Chung, 2013). Some researchers have proposed the concept of preference for online social interaction (POSI), a cognitive individual-difference concept that refers to the individual's belief that, with online interpersonal interactions, he or she is safer, more efficacious, more confident, and more comfortable than with traditional face-to-face (FtF) social activities (Caplan, 2003). To assess preference for online social interaction Caplan (2010) developed a subscale of generalized problematic Internet use (GPIU) that contains three items: 1) I prefer online social interaction over FtF communication; 2) Online social interaction is more comfortable for me than FtF interaction; and 3) I prefer communicating with people online rather than FtF. Since then, more and more related studies on this issue have been conducted, such as studies on the influence of preference for online social interaction on online gaming (Haagsma, Caplan, Peters, & Pieterse, 2013), and on gender difference in preference for online social interaction (Kimbrough, Guadagno, Muscanell, & Dill, 2013). These researchers adopted the scale developed by Caplan as the measurement of POSI.

However, Caplan's (2010) scale has two primary limitations. First, Caplan suggested that POSI was an important component of GPIU. Thus, the POSI scale is a part of the GPIU scale and there is no specific scale to measure POSI. Second, the items in the scale developed by Caplan do not fully explain the definition of POSI. The second item in the scale is designed to measure the comfort of online social interaction, but it does not include the features of validity, safety, and confidence. The other two items are similar and are designed to measure the overall comparison of feelings about online social interaction and FtF interaction. Caplan argued that people with POSI perceive online interaction to be less threatening than FtF interaction and they perceive themselves to be more socially efficacious when interacting with others online compared with FtF interaction (Caplan, 2003, 2005, 2007, 2010) but the scale does not contain items to assess either the feeling of being threatened in FtF interaction or the perception of being more socially efficacious. We believed that the items in the scale should fully explain the definition of POSI and should be designed to measure the details of feelings about online social interaction. Recently, some scholars have put forward the idea that the amount of time spent in online social interaction is also an important dimension of POSI (Zhou & Gu, 2008). In some other scales designed to assess Internet use, frequency is also considered as one of the key measurement items (Wangberg et al., 2008). For example, in their responses to a survey designed to assess preferences for texting and talking on a cell phone (Reid & Reid, 2007), participants in the study were provided with two ostensibly objective estimates that were expected to reflect biased judgments of preferred usage of their cell phones; an estimate of the number of text messages they sent in a typical month, and a similar estimate of the number of voice calls they made in the same month. …

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