RESEARCH ARTICLE
Factors Influencing Facebook Usage and Facebook Addictive Tendency in University Students: The Role of Online Psychological Privacy and Facebook Usage Motivation Fu-Yuan Hong* & Su-Lin Chiu The Center for General Education, Taipei College of Maritime Technology, Taipei, Taiwan
Abstract There are few studies analysing the influence of personal traits and motivation factors on Facebook usage and Facebook addictive tendency as seen in university students. In this study, 225 Taiwanese university students completed a questionnaire to determine their online psychological privacy scale, Facebook usage motivation scale, Facebook usage scale and Facebook addictive tendency scale, in order to evaluate the items that can be conceptualized as the effect of university students’ online psychological privacy personal trait and motive factors, and Facebook usage motivation with respect to Facebook usage and Facebook addictive tendency. The study found that a desire for more online psychological privacy correlates with a stronger motivation to use Facebook and more Facebook usage behaviour among university students who may become high-risk groups for Facebook addictive tendency. The study found that a desire for or an acceptance of a lower online psychological privacy correlates with a stronger motivation to use Facebook among university students who may have more Facebook usage behaviour. This study can help understand university students’ Facebook usage and Facebook addictive tendency and provide feature indicators for those who may become high-risk groups for Facebook addictive tendency. Finally, this study conducts discussion and proposes relevant suggestions for future study. Copyright © 2014 John Wiley & Sons, Ltd. Received 2 September 2013; Revised 26 March 2014; Accepted 23 April 2014 Keywords online psychological privacy; Facebook usage motivation; Facebook usage; Facebook addictive tendency *Correspondence Fu-Yuan Hong, The Center for General Education, Taipei College of Maritime Technology, No. 212, Sec. 9, Yen Ping N. Rd., Taipei, Taiwan. E-mail: [email protected] Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/smi.2585
Introduction For university students, Facebook has become a mainstream communication tool (Ellison, Steinfield, & Lampe, 2007). However, some students, such as those with a high degree of caution (Ryan & Xenos, 2011) or low amiability (Landers & Lounsbury, 2006), may use Facebook less frequently. It is noteworthy that Facebook has found itself under harsh criticism regarding the enactment of highly contentious privacy policies and privacy-sensitive features (Boyd, 2008). Some users prefer anonymity and physical distance; namely, the features of individual differences, which can determine personal Internet usage forms (McKenna & Bargh, 2000). Some individuals show a preference for having online separation from others when present on the Internet and the ability to adjust and control personal information (Berscheid, 1977; Derlega & Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
Chaikin, 1977). Solitude and anonymity online can be referred to as online psychological privacy. Therefore, this study is interested in exploring whether the psychological trait of desiring online psychological privacy would drive individuals who prefer to be solitary through separation or online anonymity to restrict their Facebook usage. On one hand, dimensions of privacy preference, such as solitude (Burger, 1995; Goossens et al., 2009) and anonymity (Mikami, Szwedo, Allen, Evans, & Hare, 2010), correlate significantly with interpersonal and psychological adaptation issues. However, few studies have analysed how online psychological privacy affects Facebook usage conditions and addiction. Meanwhile, previous studies have proven that there is a significant correlation between Internet usage motivation and Internet addiction (Charney & Greenberg, 2002; Chen, Ross, & Yang, 2011; Chou & Hsiao,
Facebook Usage and Facebook Addictive Tendency
2000; LaRose, 2011). Furthermore, social networking site (SNS) network users’ motivation was more likely to stimulate users to engage in SNS-using behaviour (Chen, 2012; Lin & Lu, 2011). However, there are few studies that analyse how SNS usage motivation affects Facebook usage conditions and addiction. In addition, there is a significant positive correlation between Facebook usage and Facebook addiction (Hong, Huang, Lin, & Chiu, 2014). Thus, this study uses the two concepts of online personal traits and motivation factors to analyse their effect on Facebook usage and Facebook addictive tendency, and the possible developmental mechanisms for university student Facebook usage and Facebook addictive tendency.
Literature review Online psychological privacy and Facebook usage With the progress of information and communication technologies, privacy issues receive increased attention. However, when evaluating literature on technological privacy use, there are multiple forms of privacy, including information privacy, contact privacy, social/communication privacy, physical privacy and expression privacy (Buchanan, Paine, Joinson, & Reips, 2007; DeCew, 1997; Dinev & Hart, 2004; Joinson & Paine, 2007). The so-called online psychological privacy in this study is similar to individual inclinations regarding solitude, isolation and anonymity in real-world social interaction contexts (Pedersen, 1979; Rustemli & Kokdemir, 1993), which are expressed when using the Internet. Because SNS users are often university students who use such sites to gain opportunities for offline and faceto-face interactions, this differs from the use of traditional websites. SNS users share similar physical environments with other online members in the hope of increasing the trust and closeness experienced in online communities. However, as it is difficult for SNSs to control member expansion, there tend to be more expected members than actual members; thus, this expectations may not conform to actual conditions (Gross, Acquisti, & Heinz, 2005). At the same time, some personal psychological traits may restrict the potential for Facebook usage. The study by Larson and Bell (1983) showed that, when compared with those with low privacy preference, those with a high privacy preference are less likely to orally communicate with strangers, ask questions and express themselves. They are also more nervous and less fluent when interacting with strangers. At the same time, the main concept of solitude in privacy preference tends to be described as shyness, corresponding with those who have more social anxiety, as they more often choose to avoid others (Leary, 1983). Those with social anxiety are also described as having less interaction with others and as having exaggerated negative
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social views of others (DePaulo, Epstein, & Lemay, 1990; Schlenker & Leary, 1982). Since people with more social anxiety find that they are unhappy when dealing with others (Burger, 1995), they tend to avoid social interaction, and the preference for solitude satisfies their need for avoiding social interaction. The preceding discussion shows that the privacy expectations of SNSs may not conform to the requirements of those with a high privacy preference, and Facebook usage would present their avoidance of interpersonal interactions and low self-disclosure. In other words, those with a high online psychological privacy preference may use Facebook less frequently in order to conform to their need to avoid social interactions and reduce the amount of self-disclosure. Thus, this study hypothesizes that people with a high online psychological privacy preference would use Facebook less. Online psychological privacy and Facebook addictive tendency The dimension of privacy preference, incorporating solitude, separation and anonymity, tends to correlate significantly with interpersonal and psychological adaptation issues. A preference for solitude would have a significant positive correlation with a measure of loneliness (Burger, 1995; Goossens et al., 2009). Furthermore, research suggests that a preference for solitude is more closely tied to maladjustment in early adolescence than in late adolescence (Wang, Rubin, Laursen, Booth-LaForce, & Rose-Krasnor, 2013). Furthermore, personal anonymity would cause personal self-perception to disappear (Diener, 1980). Many studies have shown that people who believe their identities are unknown are less likely to express altruism and are more likely to be devoted to antisocial behaviour, hostility and punitive manners (Diener, Fraser, Beaman, & Kelem, 1976; Ellison, Govern, Petri, & Figler, 1995; Rehm, Steinleitner, & Lilli, 1987; Silke, 2003; Zimbardo, 1975). At the same time, the study by Mikami et al. (2010) stated that adolescents with poor social skills are more likely to engage in anonymous online activities, whereas well-adapted adolescents would use SNSs with higher visibility. To summarize, personal privacy preference characteristics in real-life interactions may result in increased interpersonal and psychological adaptation problems. This study further hypothesizes that, when an individual is using Facebook, he or she would also apply privacy preference traits, which may be determined by daily life, psychological dependence or compensation obstacles. Therefore, this study hypothesizes that if one has a high inclination toward online psychological privacy, one would have greater problems with Facebook addictive tendency. Facebook usage motivation and Facebook usage The use and gratification theory states that individuals choose and utilize specific media in order to achieve Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
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satisfaction of needs, interests and objectives (Katz, Blumler, & Gurevitch, 1974; Roy, 2009; Stafford, 2008), which results in the individual’s increased online time. The study by Séguin-Levesque, Laliberté, Pelletier, Blanchard, and Vallerand (2003) showed that motivation significantly correlates with the amount of time spent on the Internet each week. More concretely, gratifications, benefits and attempts at Internet use (such as leisure, entertainment, relaxation, stimulation and companionship) would also significantly predict actual Internet usage (Perse & Ferguson, 2000); at the same time, information motivation and social interaction motivation would also positively predict the amount of time spent lingering on websites (Ko, Cho, & Roberts, 2005). The preceding text shows that individuals would increase Internet usage in order to satisfy Internet usage motivation. This situation is also applicable to SNS usage. For instance, there is a significant correlation between Facebook usage motivation and the amount of time one spends on Facebook each day (Ross et al., 2009; Spitzberg, 2006). However, correlation analysis is usually based on samples from Western society. In a Western cultural context, there are more personal cultural value characteristics, namely, an emphasis on independence, personal goals and self-reliance (Hofstede, 1980; Markus & Kitayama, 1991; Triandis, 1995). Individuals are interdependent with others, and group identity is more important than personal identity (Triandis, McCusker, & Hui, 1990). Therefore, this study aims to further analyse the relationship between Facebook usage motivation and Facebook usage to understand whether these results can be generalized for Taiwan, with its collectivist social values. This question is worthy of further analysis in this study. Facebook usage, motivation and Facebook addictive tendency The Internet can satisfy many personal needs, and these personal needs are an important indicator for predicting extreme and problematic Internet usage by university students (Chou & Hsiao, 2000; Song, Larose, Eastin, & Lin, 2004). Past studies on Internet addiction and online game addiction showed that online games give players different extrinsic and intrinsic motivations (Elaine, 1997); they also provide players with strong intrinsic motivation and the desire to find satisfaction (Rheingold, 1993). Since Internet addiction is primarily driven by uncontrollable intrinsic motivation (Chou & Chou, 1999; Young, 1998), intrinsic motivation also plays an important role in online game addiction. Studies show that excessive online game usage is due to high intrinsic motivation, and at the same time, online games provide many extrinsic rewards, such as money, fame and power, in order to attract players (Wan & Chiou, 2007). Thus, personal motivation is a highly influential mechanism for addiction. Furthermore, research has found that the more time one spends Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
Facebook Usage and Facebook Addictive Tendency
on Facebook, the more likely one is to become part of a high-risk group for Facebook addiction (Karaiskos, Tzavellas, Balta, & Paparrigopoulos, 2010; Thompson & Lougheed, 2012). This study also assumes that university students who have high Facebook usage motivation and spend more time on Facebook will also have more problems with Facebook addictive tendency.
Method Participants This study takes university students as pilot study participants, with a total of 206 valid questionnaires, among which 96 are men (46.6%) and 110 are women (53.4%). In addition, the participants of this study were collected using convenience sampling from two universities in northern Taiwan conducted over 6 weeks. As for gender distribution, there were 157 men (69.8%) and 68 women (30.2%). Freshmen were represented by 68 students (30.2%); sophomores by 53 (23.6%); juniors by 49 (21.8%); and seniors by 55 (24.4%). Of the 250 questionnaires released, 225 valid questionnaires were returned. The response rate in this study was 90.0%. The students were between 18 and 22 years of age, which conformed to the age requirements regarding university students as research participants. Measures Variables in this study included online psychological privacy, Facebook usage motivation, Facebook usage and Facebook addictive tendency. Pilot studies used to determine which items should be used in this study included the online psychological privacy scale, the Facebook usage motivation scale and the Facebook addictive tendency scale. No Facebook usage scale was used. Firstly, validity analysis of scales in this study was based on factor analysis and correlation analysis. Factors were selected based upon eigenvalue > 1 and the scree test. Orthogonal rotation was conducted by varimax, with items with factor loading lower than 4 and double loading being eliminated (Tabachnick & Fidell, 2007). The design of the scales in this study is shown as follows. Online psychological privacy scale The three factors, solitude, isolation and anonymity, were selected from the privacy preference scale by Pedersen (1979) and Rustemli and Kokdemir (1993) for a total of 15 items. Online psychological privacies analysed in this study were limited to psychological and social privacy and did not include private relationships, such as connections and visits with family and friends, as this type of intimacy has physical distance features as its basis. Therefore, intimacy preferences for family and friends were deleted, and the original real-life context was converted to the online context. For instance, ‘I need to be alone and away from everyone’ was changed to ‘When online, I need to be alone
Facebook Usage and Facebook Addictive Tendency
and away from everyone’; ‘I like to be in a room by myself’ was changed to ‘I like to browse the Internet alone’. This scale had a total of 12 questions, where scale scoring used a five-point Likert scale (1 = does not conform at all to 5 = completely conforms). The Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy was 0.899, and the Bartlett test of sphericity was χ 2(66) = 1301.391(p < 0.001), which showed that there was a good factor analysis fit. This study used a standard eigenvalue greater than 1 to conduct exploratory factor analysis and obtained three factors that could explain 67.189% of the variance, namely, ‘online solitude’ (four items), ‘online separation’ (five items) and ‘online anonymity’ (three items). Solitude means the desire to be alone and not to be disturbed and stresses the ability to keep a distance from others online. Isolation means the desire to remain separated from online sound and away from the effects of being seen by others. Anonymity means the desire to stay hidden in a network context. The internal consistency α coefficients of subscales of the ‘online psychological privacy scale’ are 0.84, 0.89 and 0.70, respectively, and the total consistency in Cronbach’s α coefficient is 0.89, which shows that this scale has good reliability.
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divided into the three functions of use applications, including games, browsing the news feed and the chat room. Thus, the researcher uses open-ended questions, such as ‘How much time do you spend on Facebook applications, including games, on average each day?’ ‘How much time, on average, do you spend on the Facebook news feed each day?’ and ‘How much time, on average, do you spend on Facebook chat rooms each day?’ Finally, the total amount of time spent by university students on Facebook in 1 day is the total amount of time spent on these three functions.
Facebook usage motivation scale Regarding the Facebook usage motivation scale, the researcher referred to literature and used the open-ended question, ‘Why do you use Facebook?’ for 65 undergraduate students who were not part of the study’s sample and who were taking psychology classes. Finally, the researcher compiled the contents into 29 items. This scale uses a five-point Likert scale (1 = does not conform at all to 5 = completely conforms), where a high total score means the respondent identifies with the motivation. The KMO measure of sampling adequacy is 0.914, and the Bartlett test of sphericity is χ 2(120) = 2005.820 (p < 0.001), which results in two factors that explain 57.828% of the variance. The two factors are ‘instrumental motivation’ (10 items) and ‘emotional motivation’ (six items), for a total of 16 items. Instrumental motivation means using Facebook as a tool for accessing and sharing new information and contact with friends. Emotional motivation means using Facebook to vent emotions and eliminate boredom. The internal consistency α coefficients of ‘Facebook usage motivation scale’ subscales are 0.92 and 0.80, respectively. The internal consistency Cronbach’s α coefficient of all items is 0.89, which shows that this scale has good reliability.
Facebook addictive tendency scale We modified Young’s (1998) Internet addiction scale in order to render it suitable to the Facebook usage context by changing the original interrogative sentences to affirmative sentences. For instance, ‘How often did you find that the time you spent online was longer than expected?’ was changed to ‘The time I spent on Facebook was usually longer than I expected’. ‘How often do you ignore family issues to spend time online?’ was changed to ‘I would ignore school work to spend more time on Facebook’. Finally, the original Internet addiction scale used a five-point Likert scale; however, in order to allow participants to distinguish positive from negative inclinations and to avoid giving them a strong value in the middle, a six-point Likert scale was used (1 = does not conform at all to 6 = completely conforms). We conducted factor analysis, where the KMO measure of sampling adequacy was 0.850, and the Bartlett test of sphericity was χ 2(36) = 1113.174 (p < 0.001), which derived three factors that explained 72.713% of the variance. The three factors were ‘life problems’ (three items), ‘withdrawal and tolerance’ (three items) and ‘substitute satisfaction’ (three items), for a total of nine items. ‘Life problems’ meant that college students using Facebook ended up having academic, time management and life problems. ‘Withdrawal and tolerance’ meant that college students needed to use Facebook more and more to get satisfaction, and when not using Facebook, they would feel that they were experiencing difficulties. ‘Substitute satisfaction’ meant that college students would use Facebook to get satisfaction, and they would thirst to use Facebook again. The internal consistency α coefficients of the ‘Facebook addictive tendency scale’ subscales were 0.82, 0.79 and 0.75, respectively, and the internal consistency Cronbach’s α coefficient of all items was 0.88, which showed that this scale has good reliability.
Facebook usage scale Facebook usage refers to the amount of time university students spend using Facebook, with a minute being the unit of time. Facebook usage includes three items, as taken from the answers given by undergraduate students in psychology classes when asked by the researcher. On the basis of usage frequency, they are
Data analysis The purpose of this study was to analyse the correlations among university students’ online psychological privacy, Facebook usage motivation, Facebook usage and Facebook addictive tendency. In order to achieve this research purpose, we firstly used descriptive statistical analysis on the university students’ self-reported Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
F.-Y. Hong and S.-L. Chiu
Facebook Usage and Facebook Addictive Tendency
online psychological privacy, Facebook usage motivation, Facebook usage and Facebook addictive tendency conditions. Bivariate correlations were used to evaluate online psychological privacy, Facebook usage motivation, Facebook usage and Facebook addictive tendency. Finally, we constructed a hypothetical model to explore the correlations among online psychological privacy, Facebook usage motivation, Facebook usage and Facebook addictive tendency, in which the prediction variables were online psychological privacy and Facebook usage motivation. The mediating variable was Facebook usage, and the outcome variable was Facebook addictive tendency. We used literature to hypothesize that online psychological privacy and Facebook usage motivation could both significantly predict Facebook usage and Facebook addictive tendency, and Facebook usage could significantly predict Facebook addictive tendency. Structure equation modelling using AMOS 18 (Serial: 5081790, Taiwan) was then employed to assess the relationships between variables. In addition, the parameter estimation method in the hypothetical model was the maximum likelihood approach, and the indices used to measure model fit included χ 2, goodness-of-fit index (GFI), comparative fit index (CFI) and root mean square error of approximation (RMSEA). The standard for the χ 2 value was under 3 (Bagozzi & Yi, 1988), the GFI and CFI indices had to exceed 0.9 (Bentler, 1988; Hu & Bentler, 1999), whereas the RMSEA index had to be under 0.08 (Browne & Cudeck, 1993) to have acceptable fit values.
The model’s predictive and explanatory ability was evaluated using path coefficients and R2 values.
Results Preliminary analyses and data analysis plan This study found that university students use Facebook for an average of 402.17 min/day. Next, this study further analysed the normal distribution of the variables, finding that the skew coefficients of the amount of time spent on Facebook applications (including games), the Facebook news feed and on the Facebook chat room are all greater than 3. Thus, data conversion is conducted by square root extraction. As seen in Table I, after data conversion, the skew coefficient is smaller than 3, and subsequent data analysis will use the converted data. This study further found a significant negative correlation between preferences for psychological privacy online and Facebook usage (r = 0.15, p < 0.05). There is a significant positive correlation between preferences for psychological privacy online and Facebook addiction (r = 0.17, p < 0.01). There is a significant positive correlation between Facebook usage motivation and Facebook usage (r = 0.24, p < 0.001) and Facebook addiction (r = 0.38, p < 0.001). There is a significant negative correlation between Facebook usage and Facebook addiction (r = 0.25, p < 0.001). However, there is no correlation between preferences for psychological privacy online and Facebook usage motivation (r = 0.04, p > 0.05) (Table II).
Table I. Summary of descriptive statistical data (n = 225) Variable Online psychological privacy—online separation Online psychological privacy—online solitude Online psychological privacy—online anonymity Facebook usage motivation—instrumental motivation Facebook usage motivation—emotional motivation Facebook usage—time spent using Facebook applications (including games)† Facebook usage—time spent using Facebook news feed† Facebook usage—Time spent using Facebook chat room† Facebook addiction tendency—withdrawal and tolerance Facebook addiction tendency—life problems Facebook addiction tendency—substitute satisfaction
Range
Mean
Standard deviation
Skew coefficient
Kurtosis coefficient
4–19
7.95
3.12
0.52
0.24
4–20
10.22
3.72
0.20
0.19
3–15
8.44
2.57
0.09
0.18
10–50
37.58
7.04
0.45
1.01
6–30
17.10
4.71
0.01
0.07
0–1440.00 (0–37.95)
152.08 (9.97)
221.76 (7.28)
3.35 (1.10)
13.77 (2.12)
0–1440.00 (0–37.95)
154.66 (10.37)
233.49 (6.87)
3.44 (1.66)
13.66 (3.60)
0–1095.00 (0–33.09)
95.43 (8.01)
136.29 (5.61)
3.63 (1.10)
17.69 (2.46)
†
3–18
6.37
3.29
0.81
0.10
3–16 3–18
5.93 8.86
2.91 3.66
0.84 0.15
0.19 0.50
Extract the square root for score conversion; the data in the parentheses show the data after extracting the square root.
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IV. Facebook addictive tendency
†
1.00 0.68*** 0.58*** 1.00 0.28*** 0.26*** 0.26*** 1.00 0.58*** 0.19** 0.18** 0.22** 0.31*** 0.40*** 0.13 0.18** 0.08 0.15* 0.15* 0.35*** 0.30*** 0.38*** 0.24*** 0.19** 0.19** 0.09 0.37*** 0.14* 0.10 0.13 0.20** 0.03 0.00 0.07 0.10 0.15* 0.04 6.87 5.61 3.30 2.91 3.66
II. Facebook usage motivation III. Facebook usage
10.38 8.01 6.37 5.93 8.86
0.07 0.12 0.15* 0.32*** 0.04
1.00 1.00 0.10 1.00 0.40*** 0.11 1.00 0.01 0.11 0.08 1.00 0.43*** 0.11 0.05 0.07 1.00 0.57*** 0.50*** 0.19** 0.13 0.13 3.12 3.72 2.57 7.04 4.71 7.28 7.95 10.22 8.44 37.58 17.10 9.97
1. Online separation 2. Online solitude 3. Online anonymity 4. Instrumental motivation 5. Emotional motivation 6. Time spent using Facebook applications (including games)† 7. Time spent using Facebook news feed † 8. Time spent using Facebook chat room † 9. Withdrawal and tolerance 10 Life problems 11. Substitute satisfaction I. Online psychological privacy
SD: standard deviation. Extract the square root for score conversion; the data in the parentheses show the data after extracting the square root. And take square root for score conversion in correlation analysis. *p < 0.05; **p < 0.01; ***p < 0.001.
1.00 0.57***
11 10 9 8 7 6 5 4 3 2 1 SD M Subscale Variable
Table II. Summary of correlation coefficients (n = 225)
F.-Y. Hong and S.-L. Chiu
1.00
Facebook Usage and Facebook Addictive Tendency
Assessing the model fit The hypothetical model, as proposed in this study, assumes that online psychological privacy and Facebook usage motivation can both significantly predict Facebook usage and Facebook addictive tendency, and Facebook usage can significantly predict Facebook addictive tendency. The resulting fit value is χ 2(39, n = 225) = 2.324, p = 0.000, GFI = 0.934, CFI = 0.926 and RMSEA = 0.077. According to the standard for the χ 2 value, the GFI, CFI and RMSEA index, the fit results are ideal. Evaluation of the standardized regression coefficients shows that online psychological privacy can significantly predict Facebook usage ( 0.176) and Facebook addictive tendency (0.302). The hypothesis that the desire to ensure online psychological privacy can significantly predict Facebook usage and Facebook addictive tendency was supported. These results mean that those with high online psychological privacy will spend less time on Facebook and have more problems with Facebook addictive tendency. Facebook usage motivation can significantly predict Facebook usage (0.320) and Facebook addictive tendency (0.439). The hypothesis that Facebook usage motivation can significantly predict Facebook usage and Facebook addictive tendency was supported. These results mean that those with high Facebook usage motivation will spend more time on Facebook and have more problems with Facebook addictive tendency. Finally, Facebook usage can significantly predict Facebook addictive tendency (0.296). The hypothesis that Facebook usage can significantly predict Facebook addictive tendency was supported. These results mean that those who spend more time on Facebook will have more problems with Facebook addictive tendency. As shown in Figure 1, the indirect effects in this study are ranked as follows: the indirect effect of Facebook usage motivation on Facebook addictive tendency is 0.094; the indirect effect of online psychological privacy on Facebook addictive tendency is 0.052. The two indirect effects are not significant. In addition, 13.3% of Facebook usage variance can be explained by online psychological privacy and Facebook usage motivation, while online psychological privacy, Facebook usage motivation and Facebook usage can effectively explain 42.3% of the variance of Facebook addictive tendency.
Discussion The purpose of this study is to analyse the effects of personal trait factors and motive factors of Internet usage on Facebook usage and Facebook addictive tendency, as well as the roles they play, during the construction of an analytical model of Facebook usage and Facebook addictive tendency for university students. Research results show that online psychological privacy can negatively predict Facebook usage and positively predict Facebook addictive tendency, and Facebook Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
F.-Y. Hong and S.-L. Chiu
Facebook Usage and Facebook Addictive Tendency
Figure 1. Analytical model of Facebook usage and Facebook addictive tendency of university students
usage motivation can positively predict Facebook usage and Facebook addictive tendency. Finally, Facebook usage can positively predict Facebook addictive tendency. These results can be provided for understanding university student Facebook usage forms and further broaden the understanding of the possible factors for Facebook addictive tendency. More specifically, the main contribution of this study is to provide the empirical support that university students with high Facebook usage motivation and preferences for psychological privacy online may become high-risk groups for Facebook addictive tendency. Meanwhile, university students who have more Facebook usage time may reflect a trend of Facebook use increasing students’ psychological and social stimulation and rewards paired with university students who have more Facebook usage time also having lower online psychological privacy. Firstly, we find that personal trait factors of Internet usage are significant for the suppression of Facebook usage behaviour. This means that those with the trait or desire for high online psychological privacy spend less time on Facebook, which supports the hypotheses of this study. This result reflects that they may decrease Facebook usage owing to a preference for online solitude, online separation and online anonymity, as they like to regulate and control self-disclosed information (Burger, 1995) in order to prevent negative feedback from others (Valkenburg, Peter, & Schouten, 2006). In other words, university students with high Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
online psychological privacy may reduce the time spent on Facebook as a coping mechanism to deal with the high level of self-disclosure of information on Facebook, which may result in negative feedback. On the other hand, in the process of social interaction, those with a high privacy preference experience more shyness and social anxiety (DePaulo et al., 1990; Leary, 1983; Schlenker & Leary, 1982) and would tend to avoid social interaction. Those with a preference for high online psychological privacy might spend less time on Facebook to avoid indirect social interaction, such as that which occurs when using the Facebook news feed. This may be because the Facebook news feed function shows personal information, which troubles the individuals trying to conceal personal basic data and would indirectly add to their sense of anxiety. In order to lessen this negative feeling, they reduce the time spent on Facebook. Facebook usage motivation is another important influential factor for Facebook usage behaviour. Not only do our findings conform to previous research results (Ross et al., 2009; Spitzberg, 2006), but our results also receive empirical support from non-Western university students. Research shows that the motivation in university students for high Facebook usage may be caused by the increased psychological and social stimulation that comes from using the medium. This stimulation reward will drive users to respond by spending even more time on Facebook, browsing the Facebook news feed and using the chat room to gain new information.
Facebook Usage and Facebook Addictive Tendency
This will allow the user to establish and maintain interpersonal relationships and to express personal feelings on Facebook. It is worth mentioning that literature shows that Facebook usage motivation and personal trait factors are independent structures (Ross et al., 2009), and our results conform to this research result that show there is no correlation between preferences for psychological privacy online and Facebook usage motivation. Next, we find that online psychological privacy can positively predict Facebook addictive tendency. This result supports the hypothesis that if online psychological privacy is high, then there would be more problems with Facebook addictive tendency. This result can better represent the personal privacy preference traits of real-life interpersonal interactions, but with more influence mechanisms of interpersonal and psychological adaptation problems, which can also be extended to the virtual internet world. This may be because there are significant correlations between the dimensions of privacy preference and problems in interpersonal and psychological adaptation, which are reflected in the excessive Facebook usage of university students. For instance, a preference for solitude would have a significant positive correlation with a measure of loneliness, and a significant negative correlation with a measure of extraversion (Burger, 1995). Adolescents with poorer social skills are more likely to engage in anonymous online activity (Mikami et al., 2010). Thus, when facing interpersonal problems and psychological trouble, students with a preference for high online psychological privacy seek to decrease the resulting anxiety, and they may become addicted to Facebook usage as a coping strategy for dispelling these tensions. Therefore, we suggest that when dealing with Facebook addictive tendency in university students, it may be possible to begin by elevating their interpersonal interaction techniques, broadening their interpersonal networks and creating positive self-evaluations. At the same time, Facebook usage motivation can also significantly predict Facebook addictive tendency. The determined motive factors, as identified by our results regarding Facebook addictive tendency, can be divided into two types of motivational paths. The first is instrumental motivation, for instance, obtaining information, catching up with friends and wasting time. Emotional motivation includes having fun, trying new things and having an outlet for emotions, which would enhance positive emotions and alleviate negative emotions. Other addictive emotional motivations, such as alcohol addiction, also tend to be connected to emotional problems, such as social anxiety and depression (Stewart, Morris, Mellings, & Komar, 2006). This suggests that university students addicted to Facebook, owing to emotional motivation, are more likely to form maladaptive or pathological patterns. This is very meaningful for future practical projects in preventing Facebook addictive tendency, as identification may
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drive the motivation forms in university student Facebook addictive tendency, which can allow for further understanding of the psychological reward mechanisms of Facebook addictive tendency behaviour and serve as the basis for future reduction of addictive behaviours. Finally, we also find that the more time spent on Facebook, the greater the possibility of Facebook addictive tendency. Our results not only support the hypotheses proposed by this study but also conform to that of previous studies (Karaiskos et al., 2010; Thompson & Lougheed, 2012). Perhaps this is because adolescents use excessive Facebook usage to satisfy their emotional needs (Kalpidou, Costin & Morris, 2011), and it shows that Facebook usage can be used as an external indicator of whether university students are addicted to Facebook. However, university students with Facebook addictive tendency often experience adaptation problems in daily life, academic performance, family relationships and psychology. Therefore, it is more important to develop future strategies to prevent Facebook addictive tendency by identifying the protection and risk factors of student Facebook addictive tendency. It is worth noting that the negative indirect effect between online psychological privacy and Facebook addictive tendency through Facebook usage is not significant in this model. This means that high online psychological privacy may not necessarily produce addiction through Facebook overuse behaviour. This may be because, as a previous study discovered, even though Internet usage may not lead to addiction, Internet addicts can show more Internet usage behaviour (Charlton & Danforth, 2004). Hong, Chiu, and Huang (2012) hold the opinion that the greater the instances of mobile phone addiction problems, the more mobile phone usage will exist. This shows that mobile phone overuse behaviour does not necessarily produce addiction, but if addiction is present, the mobile phone usage will increase. Since Facebook usage belongs to the same interactive technology as the Internet and the mobile phone, it should therefore have the same impact. Therefore, it is important to develop future studies to further analyse this viewpoint. There are many methodological limitations and prospects for future study worthy of attention. Facebook usage in this study refers to the self-evaluation of time spent on news feeds, applications and chat rooms, which may differ on the basis of personal evaluation and perceptions of time precision. Perhaps future studies can use observations or journal records to evaluate Facebook usage in order to enhance precision. In addition, even though the model constructed in this study fits the sample of 225 university students, future studies should be reproduced and confirmed by other sample groups. At the same time, although the online psychological privacies proposed by this study can significantly explain the possibility of Facebook Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
F.-Y. Hong and S.-L. Chiu
Facebook Usage and Facebook Addictive Tendency
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Appendix I Online psychological privacy scale Online solitude
1 2 3 4
Online separation
5 6 7 8
Online anonymity
9 10 11 12
I like to play internet games by myself and avoid interacting with others I would rather be online alone, because this can maintain my solitude I would rather enjoy the fun of being online and would not want to go out with others As much as possible, I would avoid meeting friends I don’t like to chat online When online, I need to be alone and away from everyone I like to go online by myself and not be bothered by other people I like to go online quietly and not interact with other people I like to browse the internet alone I don’t like to publicize my information online I don’t like to publicize my thoughts or opinions online to be seen by others Maintaining anonymity online would make me feel safe
Facebook addictive tendency scale Life problems
1 2
3
My academic performance and attention have been affected by going on Facebook. My academic work or grades have been affected because I have spent too much time on Facebook. When people ask me what I do on Facebook, I would be more defensive or private. (Continues)
Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
F.-Y. Hong and S.-L. Chiu
Facebook Usage and Facebook Addictive Tendency
(Continued) Withdrawal and tolerance
4
5
6 Substitute satisfaction
7 8 9
When not on Facebook, you would still think about going on Facebook or imagine that you are on Facebook. When not on Facebook, you would feel sad, depressed, and uneasy, but these feelings disappear when you go on Facebook. The time I spend on Facebook is usually longer than I expected. I like to meet new friends on Facebook. I discovered that I would want to go on Facebook again. Before my obligations, I would first check Facebook to see if there are updated information or games to play.
Facebook usage motivation scale Instrumental motivation
Emotional motivation
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
Can gain information Connect with friends Use up time Can conveniently contact other people Share information See what is going on with friends Keep in touch with old friends Make new friends Answer questions Save on telephone bills Because it is fun Try more things Outlet for emotions Play games to try to improve rankings Curiosity Blindly following usage by others
Factors Influencing Facebook Usage and Facebook Addictive Tendency in University Students: The Role of Online Psychological Privacy and Facebook Usage Motivation Fu-Yuan Hong* & Su-Lin Chiu The Center for General Education, Taipei College of Maritime Technology, Taipei, Taiwan
Abstract There are few studies analysing the influence of personal traits and motivation factors on Facebook usage and Facebook addictive tendency as seen in university students. In this study, 225 Taiwanese university students completed a questionnaire to determine their online psychological privacy scale, Facebook usage motivation scale, Facebook usage scale and Facebook addictive tendency scale, in order to evaluate the items that can be conceptualized as the effect of university students’ online psychological privacy personal trait and motive factors, and Facebook usage motivation with respect to Facebook usage and Facebook addictive tendency. The study found that a desire for more online psychological privacy correlates with a stronger motivation to use Facebook and more Facebook usage behaviour among university students who may become high-risk groups for Facebook addictive tendency. The study found that a desire for or an acceptance of a lower online psychological privacy correlates with a stronger motivation to use Facebook among university students who may have more Facebook usage behaviour. This study can help understand university students’ Facebook usage and Facebook addictive tendency and provide feature indicators for those who may become high-risk groups for Facebook addictive tendency. Finally, this study conducts discussion and proposes relevant suggestions for future study. Copyright © 2014 John Wiley & Sons, Ltd. Received 2 September 2013; Revised 26 March 2014; Accepted 23 April 2014 Keywords online psychological privacy; Facebook usage motivation; Facebook usage; Facebook addictive tendency *Correspondence Fu-Yuan Hong, The Center for General Education, Taipei College of Maritime Technology, No. 212, Sec. 9, Yen Ping N. Rd., Taipei, Taiwan. E-mail: [email protected] Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/smi.2585
Introduction For university students, Facebook has become a mainstream communication tool (Ellison, Steinfield, & Lampe, 2007). However, some students, such as those with a high degree of caution (Ryan & Xenos, 2011) or low amiability (Landers & Lounsbury, 2006), may use Facebook less frequently. It is noteworthy that Facebook has found itself under harsh criticism regarding the enactment of highly contentious privacy policies and privacy-sensitive features (Boyd, 2008). Some users prefer anonymity and physical distance; namely, the features of individual differences, which can determine personal Internet usage forms (McKenna & Bargh, 2000). Some individuals show a preference for having online separation from others when present on the Internet and the ability to adjust and control personal information (Berscheid, 1977; Derlega & Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
Chaikin, 1977). Solitude and anonymity online can be referred to as online psychological privacy. Therefore, this study is interested in exploring whether the psychological trait of desiring online psychological privacy would drive individuals who prefer to be solitary through separation or online anonymity to restrict their Facebook usage. On one hand, dimensions of privacy preference, such as solitude (Burger, 1995; Goossens et al., 2009) and anonymity (Mikami, Szwedo, Allen, Evans, & Hare, 2010), correlate significantly with interpersonal and psychological adaptation issues. However, few studies have analysed how online psychological privacy affects Facebook usage conditions and addiction. Meanwhile, previous studies have proven that there is a significant correlation between Internet usage motivation and Internet addiction (Charney & Greenberg, 2002; Chen, Ross, & Yang, 2011; Chou & Hsiao,
Facebook Usage and Facebook Addictive Tendency
2000; LaRose, 2011). Furthermore, social networking site (SNS) network users’ motivation was more likely to stimulate users to engage in SNS-using behaviour (Chen, 2012; Lin & Lu, 2011). However, there are few studies that analyse how SNS usage motivation affects Facebook usage conditions and addiction. In addition, there is a significant positive correlation between Facebook usage and Facebook addiction (Hong, Huang, Lin, & Chiu, 2014). Thus, this study uses the two concepts of online personal traits and motivation factors to analyse their effect on Facebook usage and Facebook addictive tendency, and the possible developmental mechanisms for university student Facebook usage and Facebook addictive tendency.
Literature review Online psychological privacy and Facebook usage With the progress of information and communication technologies, privacy issues receive increased attention. However, when evaluating literature on technological privacy use, there are multiple forms of privacy, including information privacy, contact privacy, social/communication privacy, physical privacy and expression privacy (Buchanan, Paine, Joinson, & Reips, 2007; DeCew, 1997; Dinev & Hart, 2004; Joinson & Paine, 2007). The so-called online psychological privacy in this study is similar to individual inclinations regarding solitude, isolation and anonymity in real-world social interaction contexts (Pedersen, 1979; Rustemli & Kokdemir, 1993), which are expressed when using the Internet. Because SNS users are often university students who use such sites to gain opportunities for offline and faceto-face interactions, this differs from the use of traditional websites. SNS users share similar physical environments with other online members in the hope of increasing the trust and closeness experienced in online communities. However, as it is difficult for SNSs to control member expansion, there tend to be more expected members than actual members; thus, this expectations may not conform to actual conditions (Gross, Acquisti, & Heinz, 2005). At the same time, some personal psychological traits may restrict the potential for Facebook usage. The study by Larson and Bell (1983) showed that, when compared with those with low privacy preference, those with a high privacy preference are less likely to orally communicate with strangers, ask questions and express themselves. They are also more nervous and less fluent when interacting with strangers. At the same time, the main concept of solitude in privacy preference tends to be described as shyness, corresponding with those who have more social anxiety, as they more often choose to avoid others (Leary, 1983). Those with social anxiety are also described as having less interaction with others and as having exaggerated negative
F.-Y. Hong and S.-L. Chiu
social views of others (DePaulo, Epstein, & Lemay, 1990; Schlenker & Leary, 1982). Since people with more social anxiety find that they are unhappy when dealing with others (Burger, 1995), they tend to avoid social interaction, and the preference for solitude satisfies their need for avoiding social interaction. The preceding discussion shows that the privacy expectations of SNSs may not conform to the requirements of those with a high privacy preference, and Facebook usage would present their avoidance of interpersonal interactions and low self-disclosure. In other words, those with a high online psychological privacy preference may use Facebook less frequently in order to conform to their need to avoid social interactions and reduce the amount of self-disclosure. Thus, this study hypothesizes that people with a high online psychological privacy preference would use Facebook less. Online psychological privacy and Facebook addictive tendency The dimension of privacy preference, incorporating solitude, separation and anonymity, tends to correlate significantly with interpersonal and psychological adaptation issues. A preference for solitude would have a significant positive correlation with a measure of loneliness (Burger, 1995; Goossens et al., 2009). Furthermore, research suggests that a preference for solitude is more closely tied to maladjustment in early adolescence than in late adolescence (Wang, Rubin, Laursen, Booth-LaForce, & Rose-Krasnor, 2013). Furthermore, personal anonymity would cause personal self-perception to disappear (Diener, 1980). Many studies have shown that people who believe their identities are unknown are less likely to express altruism and are more likely to be devoted to antisocial behaviour, hostility and punitive manners (Diener, Fraser, Beaman, & Kelem, 1976; Ellison, Govern, Petri, & Figler, 1995; Rehm, Steinleitner, & Lilli, 1987; Silke, 2003; Zimbardo, 1975). At the same time, the study by Mikami et al. (2010) stated that adolescents with poor social skills are more likely to engage in anonymous online activities, whereas well-adapted adolescents would use SNSs with higher visibility. To summarize, personal privacy preference characteristics in real-life interactions may result in increased interpersonal and psychological adaptation problems. This study further hypothesizes that, when an individual is using Facebook, he or she would also apply privacy preference traits, which may be determined by daily life, psychological dependence or compensation obstacles. Therefore, this study hypothesizes that if one has a high inclination toward online psychological privacy, one would have greater problems with Facebook addictive tendency. Facebook usage motivation and Facebook usage The use and gratification theory states that individuals choose and utilize specific media in order to achieve Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
F.-Y. Hong and S.-L. Chiu
satisfaction of needs, interests and objectives (Katz, Blumler, & Gurevitch, 1974; Roy, 2009; Stafford, 2008), which results in the individual’s increased online time. The study by Séguin-Levesque, Laliberté, Pelletier, Blanchard, and Vallerand (2003) showed that motivation significantly correlates with the amount of time spent on the Internet each week. More concretely, gratifications, benefits and attempts at Internet use (such as leisure, entertainment, relaxation, stimulation and companionship) would also significantly predict actual Internet usage (Perse & Ferguson, 2000); at the same time, information motivation and social interaction motivation would also positively predict the amount of time spent lingering on websites (Ko, Cho, & Roberts, 2005). The preceding text shows that individuals would increase Internet usage in order to satisfy Internet usage motivation. This situation is also applicable to SNS usage. For instance, there is a significant correlation between Facebook usage motivation and the amount of time one spends on Facebook each day (Ross et al., 2009; Spitzberg, 2006). However, correlation analysis is usually based on samples from Western society. In a Western cultural context, there are more personal cultural value characteristics, namely, an emphasis on independence, personal goals and self-reliance (Hofstede, 1980; Markus & Kitayama, 1991; Triandis, 1995). Individuals are interdependent with others, and group identity is more important than personal identity (Triandis, McCusker, & Hui, 1990). Therefore, this study aims to further analyse the relationship between Facebook usage motivation and Facebook usage to understand whether these results can be generalized for Taiwan, with its collectivist social values. This question is worthy of further analysis in this study. Facebook usage, motivation and Facebook addictive tendency The Internet can satisfy many personal needs, and these personal needs are an important indicator for predicting extreme and problematic Internet usage by university students (Chou & Hsiao, 2000; Song, Larose, Eastin, & Lin, 2004). Past studies on Internet addiction and online game addiction showed that online games give players different extrinsic and intrinsic motivations (Elaine, 1997); they also provide players with strong intrinsic motivation and the desire to find satisfaction (Rheingold, 1993). Since Internet addiction is primarily driven by uncontrollable intrinsic motivation (Chou & Chou, 1999; Young, 1998), intrinsic motivation also plays an important role in online game addiction. Studies show that excessive online game usage is due to high intrinsic motivation, and at the same time, online games provide many extrinsic rewards, such as money, fame and power, in order to attract players (Wan & Chiou, 2007). Thus, personal motivation is a highly influential mechanism for addiction. Furthermore, research has found that the more time one spends Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
Facebook Usage and Facebook Addictive Tendency
on Facebook, the more likely one is to become part of a high-risk group for Facebook addiction (Karaiskos, Tzavellas, Balta, & Paparrigopoulos, 2010; Thompson & Lougheed, 2012). This study also assumes that university students who have high Facebook usage motivation and spend more time on Facebook will also have more problems with Facebook addictive tendency.
Method Participants This study takes university students as pilot study participants, with a total of 206 valid questionnaires, among which 96 are men (46.6%) and 110 are women (53.4%). In addition, the participants of this study were collected using convenience sampling from two universities in northern Taiwan conducted over 6 weeks. As for gender distribution, there were 157 men (69.8%) and 68 women (30.2%). Freshmen were represented by 68 students (30.2%); sophomores by 53 (23.6%); juniors by 49 (21.8%); and seniors by 55 (24.4%). Of the 250 questionnaires released, 225 valid questionnaires were returned. The response rate in this study was 90.0%. The students were between 18 and 22 years of age, which conformed to the age requirements regarding university students as research participants. Measures Variables in this study included online psychological privacy, Facebook usage motivation, Facebook usage and Facebook addictive tendency. Pilot studies used to determine which items should be used in this study included the online psychological privacy scale, the Facebook usage motivation scale and the Facebook addictive tendency scale. No Facebook usage scale was used. Firstly, validity analysis of scales in this study was based on factor analysis and correlation analysis. Factors were selected based upon eigenvalue > 1 and the scree test. Orthogonal rotation was conducted by varimax, with items with factor loading lower than 4 and double loading being eliminated (Tabachnick & Fidell, 2007). The design of the scales in this study is shown as follows. Online psychological privacy scale The three factors, solitude, isolation and anonymity, were selected from the privacy preference scale by Pedersen (1979) and Rustemli and Kokdemir (1993) for a total of 15 items. Online psychological privacies analysed in this study were limited to psychological and social privacy and did not include private relationships, such as connections and visits with family and friends, as this type of intimacy has physical distance features as its basis. Therefore, intimacy preferences for family and friends were deleted, and the original real-life context was converted to the online context. For instance, ‘I need to be alone and away from everyone’ was changed to ‘When online, I need to be alone
Facebook Usage and Facebook Addictive Tendency
and away from everyone’; ‘I like to be in a room by myself’ was changed to ‘I like to browse the Internet alone’. This scale had a total of 12 questions, where scale scoring used a five-point Likert scale (1 = does not conform at all to 5 = completely conforms). The Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy was 0.899, and the Bartlett test of sphericity was χ 2(66) = 1301.391(p < 0.001), which showed that there was a good factor analysis fit. This study used a standard eigenvalue greater than 1 to conduct exploratory factor analysis and obtained three factors that could explain 67.189% of the variance, namely, ‘online solitude’ (four items), ‘online separation’ (five items) and ‘online anonymity’ (three items). Solitude means the desire to be alone and not to be disturbed and stresses the ability to keep a distance from others online. Isolation means the desire to remain separated from online sound and away from the effects of being seen by others. Anonymity means the desire to stay hidden in a network context. The internal consistency α coefficients of subscales of the ‘online psychological privacy scale’ are 0.84, 0.89 and 0.70, respectively, and the total consistency in Cronbach’s α coefficient is 0.89, which shows that this scale has good reliability.
F.-Y. Hong and S.-L. Chiu
divided into the three functions of use applications, including games, browsing the news feed and the chat room. Thus, the researcher uses open-ended questions, such as ‘How much time do you spend on Facebook applications, including games, on average each day?’ ‘How much time, on average, do you spend on the Facebook news feed each day?’ and ‘How much time, on average, do you spend on Facebook chat rooms each day?’ Finally, the total amount of time spent by university students on Facebook in 1 day is the total amount of time spent on these three functions.
Facebook usage motivation scale Regarding the Facebook usage motivation scale, the researcher referred to literature and used the open-ended question, ‘Why do you use Facebook?’ for 65 undergraduate students who were not part of the study’s sample and who were taking psychology classes. Finally, the researcher compiled the contents into 29 items. This scale uses a five-point Likert scale (1 = does not conform at all to 5 = completely conforms), where a high total score means the respondent identifies with the motivation. The KMO measure of sampling adequacy is 0.914, and the Bartlett test of sphericity is χ 2(120) = 2005.820 (p < 0.001), which results in two factors that explain 57.828% of the variance. The two factors are ‘instrumental motivation’ (10 items) and ‘emotional motivation’ (six items), for a total of 16 items. Instrumental motivation means using Facebook as a tool for accessing and sharing new information and contact with friends. Emotional motivation means using Facebook to vent emotions and eliminate boredom. The internal consistency α coefficients of ‘Facebook usage motivation scale’ subscales are 0.92 and 0.80, respectively. The internal consistency Cronbach’s α coefficient of all items is 0.89, which shows that this scale has good reliability.
Facebook addictive tendency scale We modified Young’s (1998) Internet addiction scale in order to render it suitable to the Facebook usage context by changing the original interrogative sentences to affirmative sentences. For instance, ‘How often did you find that the time you spent online was longer than expected?’ was changed to ‘The time I spent on Facebook was usually longer than I expected’. ‘How often do you ignore family issues to spend time online?’ was changed to ‘I would ignore school work to spend more time on Facebook’. Finally, the original Internet addiction scale used a five-point Likert scale; however, in order to allow participants to distinguish positive from negative inclinations and to avoid giving them a strong value in the middle, a six-point Likert scale was used (1 = does not conform at all to 6 = completely conforms). We conducted factor analysis, where the KMO measure of sampling adequacy was 0.850, and the Bartlett test of sphericity was χ 2(36) = 1113.174 (p < 0.001), which derived three factors that explained 72.713% of the variance. The three factors were ‘life problems’ (three items), ‘withdrawal and tolerance’ (three items) and ‘substitute satisfaction’ (three items), for a total of nine items. ‘Life problems’ meant that college students using Facebook ended up having academic, time management and life problems. ‘Withdrawal and tolerance’ meant that college students needed to use Facebook more and more to get satisfaction, and when not using Facebook, they would feel that they were experiencing difficulties. ‘Substitute satisfaction’ meant that college students would use Facebook to get satisfaction, and they would thirst to use Facebook again. The internal consistency α coefficients of the ‘Facebook addictive tendency scale’ subscales were 0.82, 0.79 and 0.75, respectively, and the internal consistency Cronbach’s α coefficient of all items was 0.88, which showed that this scale has good reliability.
Facebook usage scale Facebook usage refers to the amount of time university students spend using Facebook, with a minute being the unit of time. Facebook usage includes three items, as taken from the answers given by undergraduate students in psychology classes when asked by the researcher. On the basis of usage frequency, they are
Data analysis The purpose of this study was to analyse the correlations among university students’ online psychological privacy, Facebook usage motivation, Facebook usage and Facebook addictive tendency. In order to achieve this research purpose, we firstly used descriptive statistical analysis on the university students’ self-reported Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
F.-Y. Hong and S.-L. Chiu
Facebook Usage and Facebook Addictive Tendency
online psychological privacy, Facebook usage motivation, Facebook usage and Facebook addictive tendency conditions. Bivariate correlations were used to evaluate online psychological privacy, Facebook usage motivation, Facebook usage and Facebook addictive tendency. Finally, we constructed a hypothetical model to explore the correlations among online psychological privacy, Facebook usage motivation, Facebook usage and Facebook addictive tendency, in which the prediction variables were online psychological privacy and Facebook usage motivation. The mediating variable was Facebook usage, and the outcome variable was Facebook addictive tendency. We used literature to hypothesize that online psychological privacy and Facebook usage motivation could both significantly predict Facebook usage and Facebook addictive tendency, and Facebook usage could significantly predict Facebook addictive tendency. Structure equation modelling using AMOS 18 (Serial: 5081790, Taiwan) was then employed to assess the relationships between variables. In addition, the parameter estimation method in the hypothetical model was the maximum likelihood approach, and the indices used to measure model fit included χ 2, goodness-of-fit index (GFI), comparative fit index (CFI) and root mean square error of approximation (RMSEA). The standard for the χ 2 value was under 3 (Bagozzi & Yi, 1988), the GFI and CFI indices had to exceed 0.9 (Bentler, 1988; Hu & Bentler, 1999), whereas the RMSEA index had to be under 0.08 (Browne & Cudeck, 1993) to have acceptable fit values.
The model’s predictive and explanatory ability was evaluated using path coefficients and R2 values.
Results Preliminary analyses and data analysis plan This study found that university students use Facebook for an average of 402.17 min/day. Next, this study further analysed the normal distribution of the variables, finding that the skew coefficients of the amount of time spent on Facebook applications (including games), the Facebook news feed and on the Facebook chat room are all greater than 3. Thus, data conversion is conducted by square root extraction. As seen in Table I, after data conversion, the skew coefficient is smaller than 3, and subsequent data analysis will use the converted data. This study further found a significant negative correlation between preferences for psychological privacy online and Facebook usage (r = 0.15, p < 0.05). There is a significant positive correlation between preferences for psychological privacy online and Facebook addiction (r = 0.17, p < 0.01). There is a significant positive correlation between Facebook usage motivation and Facebook usage (r = 0.24, p < 0.001) and Facebook addiction (r = 0.38, p < 0.001). There is a significant negative correlation between Facebook usage and Facebook addiction (r = 0.25, p < 0.001). However, there is no correlation between preferences for psychological privacy online and Facebook usage motivation (r = 0.04, p > 0.05) (Table II).
Table I. Summary of descriptive statistical data (n = 225) Variable Online psychological privacy—online separation Online psychological privacy—online solitude Online psychological privacy—online anonymity Facebook usage motivation—instrumental motivation Facebook usage motivation—emotional motivation Facebook usage—time spent using Facebook applications (including games)† Facebook usage—time spent using Facebook news feed† Facebook usage—Time spent using Facebook chat room† Facebook addiction tendency—withdrawal and tolerance Facebook addiction tendency—life problems Facebook addiction tendency—substitute satisfaction
Range
Mean
Standard deviation
Skew coefficient
Kurtosis coefficient
4–19
7.95
3.12
0.52
0.24
4–20
10.22
3.72
0.20
0.19
3–15
8.44
2.57
0.09
0.18
10–50
37.58
7.04
0.45
1.01
6–30
17.10
4.71
0.01
0.07
0–1440.00 (0–37.95)
152.08 (9.97)
221.76 (7.28)
3.35 (1.10)
13.77 (2.12)
0–1440.00 (0–37.95)
154.66 (10.37)
233.49 (6.87)
3.44 (1.66)
13.66 (3.60)
0–1095.00 (0–33.09)
95.43 (8.01)
136.29 (5.61)
3.63 (1.10)
17.69 (2.46)
†
3–18
6.37
3.29
0.81
0.10
3–16 3–18
5.93 8.86
2.91 3.66
0.84 0.15
0.19 0.50
Extract the square root for score conversion; the data in the parentheses show the data after extracting the square root.
Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
IV. Facebook addictive tendency
†
1.00 0.68*** 0.58*** 1.00 0.28*** 0.26*** 0.26*** 1.00 0.58*** 0.19** 0.18** 0.22** 0.31*** 0.40*** 0.13 0.18** 0.08 0.15* 0.15* 0.35*** 0.30*** 0.38*** 0.24*** 0.19** 0.19** 0.09 0.37*** 0.14* 0.10 0.13 0.20** 0.03 0.00 0.07 0.10 0.15* 0.04 6.87 5.61 3.30 2.91 3.66
II. Facebook usage motivation III. Facebook usage
10.38 8.01 6.37 5.93 8.86
0.07 0.12 0.15* 0.32*** 0.04
1.00 1.00 0.10 1.00 0.40*** 0.11 1.00 0.01 0.11 0.08 1.00 0.43*** 0.11 0.05 0.07 1.00 0.57*** 0.50*** 0.19** 0.13 0.13 3.12 3.72 2.57 7.04 4.71 7.28 7.95 10.22 8.44 37.58 17.10 9.97
1. Online separation 2. Online solitude 3. Online anonymity 4. Instrumental motivation 5. Emotional motivation 6. Time spent using Facebook applications (including games)† 7. Time spent using Facebook news feed † 8. Time spent using Facebook chat room † 9. Withdrawal and tolerance 10 Life problems 11. Substitute satisfaction I. Online psychological privacy
SD: standard deviation. Extract the square root for score conversion; the data in the parentheses show the data after extracting the square root. And take square root for score conversion in correlation analysis. *p < 0.05; **p < 0.01; ***p < 0.001.
1.00 0.57***
11 10 9 8 7 6 5 4 3 2 1 SD M Subscale Variable
Table II. Summary of correlation coefficients (n = 225)
F.-Y. Hong and S.-L. Chiu
1.00
Facebook Usage and Facebook Addictive Tendency
Assessing the model fit The hypothetical model, as proposed in this study, assumes that online psychological privacy and Facebook usage motivation can both significantly predict Facebook usage and Facebook addictive tendency, and Facebook usage can significantly predict Facebook addictive tendency. The resulting fit value is χ 2(39, n = 225) = 2.324, p = 0.000, GFI = 0.934, CFI = 0.926 and RMSEA = 0.077. According to the standard for the χ 2 value, the GFI, CFI and RMSEA index, the fit results are ideal. Evaluation of the standardized regression coefficients shows that online psychological privacy can significantly predict Facebook usage ( 0.176) and Facebook addictive tendency (0.302). The hypothesis that the desire to ensure online psychological privacy can significantly predict Facebook usage and Facebook addictive tendency was supported. These results mean that those with high online psychological privacy will spend less time on Facebook and have more problems with Facebook addictive tendency. Facebook usage motivation can significantly predict Facebook usage (0.320) and Facebook addictive tendency (0.439). The hypothesis that Facebook usage motivation can significantly predict Facebook usage and Facebook addictive tendency was supported. These results mean that those with high Facebook usage motivation will spend more time on Facebook and have more problems with Facebook addictive tendency. Finally, Facebook usage can significantly predict Facebook addictive tendency (0.296). The hypothesis that Facebook usage can significantly predict Facebook addictive tendency was supported. These results mean that those who spend more time on Facebook will have more problems with Facebook addictive tendency. As shown in Figure 1, the indirect effects in this study are ranked as follows: the indirect effect of Facebook usage motivation on Facebook addictive tendency is 0.094; the indirect effect of online psychological privacy on Facebook addictive tendency is 0.052. The two indirect effects are not significant. In addition, 13.3% of Facebook usage variance can be explained by online psychological privacy and Facebook usage motivation, while online psychological privacy, Facebook usage motivation and Facebook usage can effectively explain 42.3% of the variance of Facebook addictive tendency.
Discussion The purpose of this study is to analyse the effects of personal trait factors and motive factors of Internet usage on Facebook usage and Facebook addictive tendency, as well as the roles they play, during the construction of an analytical model of Facebook usage and Facebook addictive tendency for university students. Research results show that online psychological privacy can negatively predict Facebook usage and positively predict Facebook addictive tendency, and Facebook Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
F.-Y. Hong and S.-L. Chiu
Facebook Usage and Facebook Addictive Tendency
Figure 1. Analytical model of Facebook usage and Facebook addictive tendency of university students
usage motivation can positively predict Facebook usage and Facebook addictive tendency. Finally, Facebook usage can positively predict Facebook addictive tendency. These results can be provided for understanding university student Facebook usage forms and further broaden the understanding of the possible factors for Facebook addictive tendency. More specifically, the main contribution of this study is to provide the empirical support that university students with high Facebook usage motivation and preferences for psychological privacy online may become high-risk groups for Facebook addictive tendency. Meanwhile, university students who have more Facebook usage time may reflect a trend of Facebook use increasing students’ psychological and social stimulation and rewards paired with university students who have more Facebook usage time also having lower online psychological privacy. Firstly, we find that personal trait factors of Internet usage are significant for the suppression of Facebook usage behaviour. This means that those with the trait or desire for high online psychological privacy spend less time on Facebook, which supports the hypotheses of this study. This result reflects that they may decrease Facebook usage owing to a preference for online solitude, online separation and online anonymity, as they like to regulate and control self-disclosed information (Burger, 1995) in order to prevent negative feedback from others (Valkenburg, Peter, & Schouten, 2006). In other words, university students with high Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
online psychological privacy may reduce the time spent on Facebook as a coping mechanism to deal with the high level of self-disclosure of information on Facebook, which may result in negative feedback. On the other hand, in the process of social interaction, those with a high privacy preference experience more shyness and social anxiety (DePaulo et al., 1990; Leary, 1983; Schlenker & Leary, 1982) and would tend to avoid social interaction. Those with a preference for high online psychological privacy might spend less time on Facebook to avoid indirect social interaction, such as that which occurs when using the Facebook news feed. This may be because the Facebook news feed function shows personal information, which troubles the individuals trying to conceal personal basic data and would indirectly add to their sense of anxiety. In order to lessen this negative feeling, they reduce the time spent on Facebook. Facebook usage motivation is another important influential factor for Facebook usage behaviour. Not only do our findings conform to previous research results (Ross et al., 2009; Spitzberg, 2006), but our results also receive empirical support from non-Western university students. Research shows that the motivation in university students for high Facebook usage may be caused by the increased psychological and social stimulation that comes from using the medium. This stimulation reward will drive users to respond by spending even more time on Facebook, browsing the Facebook news feed and using the chat room to gain new information.
Facebook Usage and Facebook Addictive Tendency
This will allow the user to establish and maintain interpersonal relationships and to express personal feelings on Facebook. It is worth mentioning that literature shows that Facebook usage motivation and personal trait factors are independent structures (Ross et al., 2009), and our results conform to this research result that show there is no correlation between preferences for psychological privacy online and Facebook usage motivation. Next, we find that online psychological privacy can positively predict Facebook addictive tendency. This result supports the hypothesis that if online psychological privacy is high, then there would be more problems with Facebook addictive tendency. This result can better represent the personal privacy preference traits of real-life interpersonal interactions, but with more influence mechanisms of interpersonal and psychological adaptation problems, which can also be extended to the virtual internet world. This may be because there are significant correlations between the dimensions of privacy preference and problems in interpersonal and psychological adaptation, which are reflected in the excessive Facebook usage of university students. For instance, a preference for solitude would have a significant positive correlation with a measure of loneliness, and a significant negative correlation with a measure of extraversion (Burger, 1995). Adolescents with poorer social skills are more likely to engage in anonymous online activity (Mikami et al., 2010). Thus, when facing interpersonal problems and psychological trouble, students with a preference for high online psychological privacy seek to decrease the resulting anxiety, and they may become addicted to Facebook usage as a coping strategy for dispelling these tensions. Therefore, we suggest that when dealing with Facebook addictive tendency in university students, it may be possible to begin by elevating their interpersonal interaction techniques, broadening their interpersonal networks and creating positive self-evaluations. At the same time, Facebook usage motivation can also significantly predict Facebook addictive tendency. The determined motive factors, as identified by our results regarding Facebook addictive tendency, can be divided into two types of motivational paths. The first is instrumental motivation, for instance, obtaining information, catching up with friends and wasting time. Emotional motivation includes having fun, trying new things and having an outlet for emotions, which would enhance positive emotions and alleviate negative emotions. Other addictive emotional motivations, such as alcohol addiction, also tend to be connected to emotional problems, such as social anxiety and depression (Stewart, Morris, Mellings, & Komar, 2006). This suggests that university students addicted to Facebook, owing to emotional motivation, are more likely to form maladaptive or pathological patterns. This is very meaningful for future practical projects in preventing Facebook addictive tendency, as identification may
F.-Y. Hong and S.-L. Chiu
drive the motivation forms in university student Facebook addictive tendency, which can allow for further understanding of the psychological reward mechanisms of Facebook addictive tendency behaviour and serve as the basis for future reduction of addictive behaviours. Finally, we also find that the more time spent on Facebook, the greater the possibility of Facebook addictive tendency. Our results not only support the hypotheses proposed by this study but also conform to that of previous studies (Karaiskos et al., 2010; Thompson & Lougheed, 2012). Perhaps this is because adolescents use excessive Facebook usage to satisfy their emotional needs (Kalpidou, Costin & Morris, 2011), and it shows that Facebook usage can be used as an external indicator of whether university students are addicted to Facebook. However, university students with Facebook addictive tendency often experience adaptation problems in daily life, academic performance, family relationships and psychology. Therefore, it is more important to develop future strategies to prevent Facebook addictive tendency by identifying the protection and risk factors of student Facebook addictive tendency. It is worth noting that the negative indirect effect between online psychological privacy and Facebook addictive tendency through Facebook usage is not significant in this model. This means that high online psychological privacy may not necessarily produce addiction through Facebook overuse behaviour. This may be because, as a previous study discovered, even though Internet usage may not lead to addiction, Internet addicts can show more Internet usage behaviour (Charlton & Danforth, 2004). Hong, Chiu, and Huang (2012) hold the opinion that the greater the instances of mobile phone addiction problems, the more mobile phone usage will exist. This shows that mobile phone overuse behaviour does not necessarily produce addiction, but if addiction is present, the mobile phone usage will increase. Since Facebook usage belongs to the same interactive technology as the Internet and the mobile phone, it should therefore have the same impact. Therefore, it is important to develop future studies to further analyse this viewpoint. There are many methodological limitations and prospects for future study worthy of attention. Facebook usage in this study refers to the self-evaluation of time spent on news feeds, applications and chat rooms, which may differ on the basis of personal evaluation and perceptions of time precision. Perhaps future studies can use observations or journal records to evaluate Facebook usage in order to enhance precision. In addition, even though the model constructed in this study fits the sample of 225 university students, future studies should be reproduced and confirmed by other sample groups. At the same time, although the online psychological privacies proposed by this study can significantly explain the possibility of Facebook Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
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Appendix I Online psychological privacy scale Online solitude
1 2 3 4
Online separation
5 6 7 8
Online anonymity
9 10 11 12
I like to play internet games by myself and avoid interacting with others I would rather be online alone, because this can maintain my solitude I would rather enjoy the fun of being online and would not want to go out with others As much as possible, I would avoid meeting friends I don’t like to chat online When online, I need to be alone and away from everyone I like to go online by myself and not be bothered by other people I like to go online quietly and not interact with other people I like to browse the internet alone I don’t like to publicize my information online I don’t like to publicize my thoughts or opinions online to be seen by others Maintaining anonymity online would make me feel safe
Facebook addictive tendency scale Life problems
1 2
3
My academic performance and attention have been affected by going on Facebook. My academic work or grades have been affected because I have spent too much time on Facebook. When people ask me what I do on Facebook, I would be more defensive or private. (Continues)
Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
F.-Y. Hong and S.-L. Chiu
Facebook Usage and Facebook Addictive Tendency
(Continued) Withdrawal and tolerance
4
5
6 Substitute satisfaction
7 8 9
When not on Facebook, you would still think about going on Facebook or imagine that you are on Facebook. When not on Facebook, you would feel sad, depressed, and uneasy, but these feelings disappear when you go on Facebook. The time I spend on Facebook is usually longer than I expected. I like to meet new friends on Facebook. I discovered that I would want to go on Facebook again. Before my obligations, I would first check Facebook to see if there are updated information or games to play.
Facebook usage motivation scale Instrumental motivation
Emotional motivation
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Stress and Health (2014) © 2014 John Wiley & Sons, Ltd.
Can gain information Connect with friends Use up time Can conveniently contact other people Share information See what is going on with friends Keep in touch with old friends Make new friends Answer questions Save on telephone bills Because it is fun Try more things Outlet for emotions Play games to try to improve rankings Curiosity Blindly following usage by others
