Full length articleHow social media influence college students’ smoking attitudes and intentions
Introduction
Recent data indicate that approximately 16% of U.S. college students report having smoked a cigarette at some point, 10.6% report having smoked within the past 30 days, and 2.5% report they smoke daily (American College Health Association, 2015). Of all age groups, college-aged adults (age 18–24 years) show the highest rate of current use of tobacco products (Substance Abuse and Mental Health Services Administration, 2013). To prevent smoking prevalence among college students, it is critical to understand how they develop attitudes toward cigarette smoking and what affects their smoking behaviors. According to the theory of reasoned action (Ajzen & Fishbein, 1980) and the theory of planned behavior (Ajzen, 1985), individuals’ attitudes toward behavior determine their behavioral intentions. Based on these theories, some scholars have examined the effects of smoking attitudes on smoking intentions among college students. Mao et al. (2009) found that higher prosmoking attitudes were associated with higher likelihood to smoke in the next 6 months. Ling, Neilands, and Glantz (2009) also found that aggressive and critical attitudes against the tobacco industry were positively related to intentions to quit smoking.
Despite the considerable importance of smoking attitudes in predicting smoking intentions among college students, little is known about how social media usage affects students’ attitudes toward smoking. The tobacco industry has been using social media as channels for the marketing and promotion of tobacco products (Freeman and Chapman, 2007, Freeman, 2012). During recent years, social media have been found to be the most significant predictor of college students’ smoking. For example, disclosures of photos regarding smoking on social networking sites were indicative of their real-life smoking behaviors (van Hoof, Bekkers, van Vuuren, 2014). Zhu (2014) also found that prosmoking information scanning using social media influenced young adults’ smoking behavior. Depue, Southwell, Betzner, and Walsh (2015) found that exposure to tobacco use in social media predicted future smoking tendencies among young adults. Given that social smoking is one of the most prominent patterns of tobacco use among college students (Levinson et al., 2007, Moran et al., 2004), social media can function as an effective channel through which college students easily share their thoughts on smoking, which in turn foster their perceived peer norms on smoking. Thus, research needs to examine the effectiveness of social media in determining smoking attitudes as well as smoking intentions among college students.
To fulfil the study needs, we explore the relationship between social media usage and cigarette smoking among college students within a theoretical foundation, drawing on the influence of presumed influence (IPI) model (Gunther & Storey, 2003). The IPI model has been widely employed to delineate how media messages about smoking influence a target audience’s smoking via their effects on perceived peer norms (Gunther et al., 2006, Paek and Gunther, 2007, Paek et al., 2011). According to the IPI model, individuals assume that mass media influence the attitudes and behaviors of their peers, and such assumption in turn affects their own attitudes and behaviors. From this perspective, college students may assume that smoking-related messages in social media will influence the attitudes and behaviors of their peers, and these perceptions about peers will influence their own smoking attitudes and behaviors.
Previous IPI studies have focused on looking at the effects of smoking-related content predominantly on traditional media (Gunther et al., 2006, Paek and Gunther, 2007, Paek et al., 2011); however, relatively few studies have examined the effect of smoking-related content on social media using the IPI model. Using the theoretical framework of the IPI model to explore how smoking-related messages in social media influence college students’ smoking, this study adds to the currently small number of studies that apply the IPI model in social media settings (e.g., Bernhard, Dohle, & Vowe, 2015). In addition, the present study assumes that the acts of receiving and expressing messages on social media have distinct effects on the person so engaged, and thus distinguishes message expression and reception effects. This approach is differentiated from previous studies focused on exploring only reception effects (Gunther et al., 2006, Paek and Gunther, 2007, Paek et al., 2011). Lastly, this study seeks to contribute to the growing literature on the role of social media in predicting college students’ smoking attitudes and intentions.
Section snippets
How social media affect attitudes and behavioral intentions
The IPI model provides a theoretical framework for understanding how social media affect public attitudes and behaviors with respect to a specific issue. The model predicts that a person may perceive influences of media on others and adapt their own attitudes and behaviors to correspond to that perception (Gunther & Storey, 2003). The IPI model identifies three causal relationships among the key components that explain the mechanism of media influence.
The first relationship is the association
Hypothesized model
Guided by the theoretical rationale of the IPI model, this study examines the direct and indirect effects of smoking-related messages on social media on smoking attitudes and intentions among college students. To investigate these effects more thoroughly, the present research incorporates two communicative behaviors (i.e., message expression and reception) of social media and two main types (i.e., antismoking and prosmoking) of smoking-related messages into the hypothesized model (see Fig. 1).
Data collection
Data were collected via a web-based survey of undergraduate students at three Midwestern universities in the spring semester of 2012. We recruited potential participants through bulletin board notices, flyers, and announcements in classes. The survey was accessible from any computer with Internet access. Participants were given the option of taking the survey using their own computers or desktops in our research lab. They took approximately 15 minutes to complete the survey and received extra
Results
This study first assessed the hypothesized model with five goodness-of-fit indices, including the chi-squared statistic, the root mean square error of approximation (RMSEA), the comparative fit index (CFI), the Tucker–Lewis index (TLI), and the standardized root mean square residual (SRMR). All fit measures gave evidence of a poor model with the data, χ2 = 496.42, df = 36, p < 0.001, RMSEA = 0.19 (90% CI = 0.17 to 0.20), CFI = 0.75, TLI = 0.24, and SRMR = 0.13. According to the modification
Discussion
This research uses the IPI model as a theoretical model to examine how the expression and reception of smoking-related messages on social media affect college students’ smoking attitudes and intentions. Consistent with previous IPI research on smoking (Gunther et al., 2006, Paek and Gunther, 2007, Paek et al., 2011), the findings provide substantial evidence for most of the theoretical pathways of the proposed model. However, this is not a mere extension of past work. Indeed, the present study
Funding source
This research was supported by National Institutes of Health/National Cancer Institute Training Tobacco Scientists Mini Grant (P50 CA143188) from University of Wisconsin Center for Tobacco Research and Intervention.
References (57)
Antismoking campaign videos on YouTube and audience response: Application of social media assessment metrics
Computers in Human Behavior
(2015)- et al.
Son, you’re smoking on Facebook! College students’ disclosures on social networking sites as indicators of real-life risk behaviors
Computers in Human Behavior
(2014) - et al.
Peer influences: The impact of online and offline friendship networks on adolescent smoking and alcohol use
Journal of Adolescent Health
(2014) - et al.
Effect of smoking scenes in films on immediate smoking: A randomized controlled study
American Journal of Preventive Medicine
(2010) - et al.
The effects of SNS communication: How expressing and receiving information predict MERS-preventive behavioral intentions in South Korea
Computers in Human Behavior
(2016) From intentions to actions: A theory of planned behavior
- et al.
Understanding attitudes and predicting social behavior
(1980) National college health assessment (ACHA-NCHA) Spring 2015 reference group executive summary
(2015)- et al.
YouTube as a source of quitting smoking information
Tobacco Control
(2011) Social cognitive theory of mass communication
Media Psychology
(2001)
Do presumed online media effects have an influence on the online activities of politicians?
Policy & Internet
Scaled test statistics and robust standard errors for non-normal data in covariance structure analysis: A Monte Carlo study
British Journal of Mathematical and Statistical Psychology
A focus theory of normative conduct: Recycling the concept of norms to reduce littering in public places
Journal of Personality and Social Psychology
Implications of the normative fallacy in young adult smokers aged 19-24 years
American Journal of Public Health
Encoded exposure to tobacco use in social media predicts subsequent smoking behavior
American Journal of Health Promotion
Developmental correlates of psychological reactance
Journal of Cognitive Psychotherapy: An International Quarterly
The cognitive mediation model of learning from the news evidence from nonelection, off-year election, and presidential election contexts
Communication Research
The effect of political discussion in producing informed citizens: The roles of information, motivation, and elaboration
Political Communication
The role of theory in developing effective health communications
Journal of Communication
“I’ll be your cigarette – Light me up and get on with it”: Examining smoking imagery on YouTube
Nicotine & Tobacco Research
New media and tobacco control
Tobacco Control
Is ‘‘YouTube’’ telling or selling you something? Tobacco content on the YouTube video-sharing website
Tobacco Control
Defensive evaluation of antismoking messages among college-age smokers: The role of possible selves
Health Psychology
The persuasive press inference effects of mass media on perceived public opinion
Communication Research
Presumed influence on peer norms: How mass media indirectly affect adolescent smoking
Journal of Communication
The influence of presumed influence
Journal of Communication
Take two aspirin and tweet me in the morning: How Twitter, Facebook, and other social media are reshaping health care
Health Affairs
Examining how presumed media influence affects social norms and adolescents’ attitudes and drinking behavior intentions in rural Thailand
Journal of Health Communication
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