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Published in final edited form as: J Child Media. 2019 Dec 27;15(2):10.1080/17482798.2019.1706184. doi: 10.1080/17482798.2019.1706184

Reducing Television Influences on US Adolescents Who are High Reactance

Cristel Antonia Russell 1, Denise Buhrau 2, Anne Hamby 3
PMCID: PMC8078140  NIHMSID: NIHMS1547701  PMID: 33927781

Abstract

Watching a lot of television (TV), where alcohol consumption is depicted frequently and mostly positively, can enhance teens’ drinking intentions. This influence is particularly problematic among high-reactance teens (that is, those with a predisposition to resist adult control). This study documents one strategy parents can use to counteract TV influences: parental presence during the TV viewing experience (co-viewing). Survey data were collected from a nationally representative sample of parents and their children aged 13–17 (N = 396). Parents reported how they monitored their children’s TV consumption, and adolescents completed a survey in which they reported the amount of TV they watch, completed a trait reactance scale and indicated their views and intentions regarding drinking. Results revealed that the influence of TV viewing on adolescents’ drinking intentions was lower for teens high in trait reactance who grew up with parents who co-view television with them. This did not occur when parents adopted instructive or restrictive communication strategies. The parental monitoring strategy of co-viewing thus emerges as a promising protective approach for a population that has traditionally been considered vulnerable (i.e., high reactance teens).

1. Introduction

Alcohol remains the most widely used substance by adolescents in the US (SAMHSA, 2018). Underage drinking is a serious public health challenge, threatening not only adolescent development but also the health and lives of others, given issues such as driving under the influence. Some adolescents are more predisposed to engage in risky alcohol consumption than others: In particular, adolescents who are high in psychological reactance (Brehm, 1966; Brehm & Brehm, 1981) demonstrate a tendency to engage in risk seeking behavior (Grandpre, Alvaro, Burgoon, Miller, & Hall, 2003). Psychological reactance is a personality trait associated with a predisposition to resist adult control, to feel invulnerable, to think in simplified, superficial ways, and to imitate adult behaviors (without understanding the consequences of such behaviors) (Dowd et al., 1988; Miller, Burgood, Grandpre, & Alvaro, 2006; Van Petegem, Soenens, Vansteenkiste, & Beyers, 2015). High trait reactance teens are an especially vulnerable group in terms of alcohol abuse.

In addition to adolescent personality characteristics, the embedded context in which adolescents are socialized exerts a strong influence on their alcohol consumption; in particular, the favorable depiction of alcohol consumption on television has been identified as an exacerbating factor for adolescent intentions to drink. Social learning and behavioral modeling theories have long documented TV as a key medium through which youths learn about consuming substances (Brown, Halpern, & L’Engle, 2005; Collins, Elliott, Berry, Kanouse, & Hunter, 2003; Strasburger, Jordan, & Donnerstein, 2012). Today’s adolescents avidly consume TV programs on a range of platforms including smartphones, tablets, and laptops (Nielsen, 2018). TV content is not only an effective medium for traditional advertising, including of alcohol beverages (CAMY, 2015; Chung et al., 2010), its content is also rife with positive images of drinking. Alcohol messages are omnipresent in films, TV series, and other audiovisual programs popular with youth (Bergamini, Demidenko, & Sargent, 2013; Russell & Russell, 2009; Strasburger et al., 2012). The prevalence of alcohol messages on TV and their association with positive outcomes raise concerns about the socialization power of TV in the area of alcohol beliefs (American Academy of Pediatrics, 2013; Gabrielli, Traore, Stoolmiller, Bergamini, & Sargent, 2016; Russell, Russell, & Grube, 2009).

Against this backdrop, parents of teens, particularly high-reactance teens, have reason to be concerned. What can parents do to forestall the influence of the ubiquitous, favorable depiction of alcohol on their teens’ behavior – particularly among teens who expressly resist adults’ attempts to address their behavior? While TV exerts a strong socializing influence on teens’ behaviors, parents also play an important role in the ways they guide how their children watch television. Parental monitoring strategies, or the ways in which parents approach media use and content with their children in a home environment, affect how children interpret and internalize media messages (Chen & Austin, 2012; Padilla-Walker, Coyne, Kroff, & Memmott-Elison, 2018). This, in turn, leads to differences in behavioral outcomes (Chen & Austin, 2012; Valkenburg, Krcmar, Peeters, & Marseille, 1999). Given that the relationships between parents and their children’s TV viewing habits tend to stay stable as children become teenagers (Bleakley, Jordan, & Hennessy, 2013), parental monitoring strategies may affect whether and how TV influences youths, even as children become more independent consumers of TV. For instance, parents place time limits on their children’s media consumption: a 2019 study found that 34% of US parents put limits on their children’s viewing of live TV (Statista, 2019). Although teens are increasingly viewing TV on other devices, about 50% of video viewing time still happens on a TV set, giving the opportunity for co-viewing (Common Sense, 2017). Even as teen media consumption shifts to personal devices it is important to understand whether and how parental monitoring strategies shape the influence of media on children’s behavior.

This research focuses on one type of parental monitoring that may be particularly effective at reducing the influence of TV viewing on high reactance teens’ intentions to drink: Specifically, the parental monitoring strategy of co-viewing, an approach where parents and children watch TV together may be effective, especially in contrast to other approaches that involve restriction or instruction, to which highly reactant teens would be less receptive. Even without active communication, co-viewing is considered a form of monitoring. The mere presence of the parent can influence children’s responses to the program compared to viewing alone; the salient presence of a parent may influence the nature of adolescents’ thoughts as part of their internal audience (Bryce & Leichter, 1983; Nathanson, 2002).

While past research suggests that high reactance teens resist overt attempts to influence their behavior (Dowd, et al. 1988; Hong, 1992), some research suggests that they can be receptive to information presented in a non-persuasive manner (Veldhuis, Konjin, & Seidell, 2014); that is, information that makes a risk salient, but that is not viewed as possessing persuasive intent, serves as an effective approach to communication with high-reactance teens. We propose that the mere presence of parents during media viewing represents a similar influence: they may make the risks of alcohol consumption salient to the teen without being coupled with persuasive intent (as opposed to other forms of parental mediation).

Thus, this research examines the untested proposition that parental monitoring styles may alter the relationship between adolescents’ trait reactance and TV viewing’s influence on drinking intentions (Fujioka & Austin, 2002). Specifically, the research explores the interplay of parental co-viewing strategy and adolescent trait reactance on the relationship between TV viewing and adolescent drinking intentions. We draw from parent-child data collected in a US-based cross-sectional study to test these relationships.

2. Material and methods

2.1. Study sample

Survey data were collected online from a nationally representative sample of parents and children aged 13–17 in the United States of America. Parent participants were recruited via the panel of a professional research company. Requirements for parental consent and child assent were followed in adherence with the authors’ Institutional Review Boards and in compliance with International Chamber of Commerce guidelines. The panel company sent parents an invitation describing the study. Upon parents’ consent for themselves and their child, parents answered questions about habits as a parent, including TV monitoring strategies. They then received a login for their child to access their own survey, which began with an informed consent form that outlined the study. Once assent was given, the adolescent participants completed the survey on a secure website, with instructions to do so away from parents’ view.

Of the 520 parents contacted, 416 (80%) provided consent and 399 (96%) of the children assented.

2.2. Study variables

2.2.1. Parental Monitoring Styles

To assess the styles of monitoring that parents used for their children’s TV consumption, parents were asked to “Think especially about when your child was a bit younger, and indicate how often you act in each of the following ways.” Though we were primarily interested in the parental co-viewing strategy, we measured and control for other forms of parental monitoring in order to isolate the influence of co-viewing on behavior: Instructive communication involves parents actively discussing TV’s content with their children to facilitate their understanding of media messages (Austin, 1993; Fujioka & Austin, 2002; Nathanson, 2001). This active, reasoning-centered form of monitoring increases children’s critical viewing skills on topics such as the potential negative influence of advertising (Austin & Pinkleton, 2001; Buijzen &Valkenburg, 2005), and is related to the process through which parents foster the development of media literacy in their children (Austin, Pinkleton, Chen, & Austin, 2015; Chen, Porter, Estabrooks, & Zoellner, 2017; Livingstone & Helsper, 2006). With restricting access, parents set rules for TV viewing hours or prohibit the viewing of certain content (Valkenburg et al., 1999; Dalton et al., 2006), although most rulemaking is related to what children can watch (e.g., inappropriate content) rather than how much they can watch (Kaiser Family Foundation, 2007; Rideout, Foehr, & Roberts, 2010). All three monitoring strategies were measured using existing scales (Valkenburg et al., 1999; see table 1 for measures).

Table 1.

Measures, Descriptive Statistics, and Correlation Matrix

Correlations
α M (SD) Instructive Restrictive Co-viewing Reactance Intentions
TV Viewing (answered by adolescents, n = 396) 25.27 (13.34) .17** −.01 .10 .06 .11*
Parental Monitoring Strategies (1 = strongly disagree, 5 = strongly agree; answered by parents, n = 396)
.57**
Instructive communication items
 • Try to help the child understand what s/he sees on TV .91 3.32 (.92) .69** .09+ .07
 • Point out why some things actors do are good
 • Point out why some things actors do are bad
 • Explain the motives of TV characters
 • Explain what something on TV really means
Restricting Access items .90 3.25 (1.01) .39** .14** .10*
 • Tell your child to turn off TV when s/he is watching an unsuitable program
 • Set specific viewing hours for your child
 • Forbid your child to watch certain programs
 • Restrict the amount of child viewing
 • Specify in advance the programs that may be watched
Co-viewing items .89 3.82 (.80) −.09 −.07
 • Watch together because you both like a program
 • Watch together because of a common interest in a program
 • Watch your favorite program together
 • Laugh with your child about the things you see on TV
Trait Reactance (1 = strongly disagree, 5 = strongly agree; answered by adolescents) .88 3.13 (.78) .29**
 • I become angry when my freedom of choice is restricted.
 • I become frustrated when I am unable to make free and independent decisions.
 • I am content only when I am acting of my own free will.
 • The thought of being depending on others aggravates me.
 • When something is prohibited, I usually think “that’s exactly what I am going to do.
 • Regulations trigger a sense of resistance in me.
 • I find contradicting others stimulating.
Drinking Intentions (1 = very unlikely, 7 = very likely; answered by adolescents) .95 1.81 (1.60)
In the next year, how likely is it that you will
 • Drink any alcohol
 • Drink several alcoholic drinks in a row
 • Drink enough to get drunk
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2.2.2. Adolescent Variables

The adolescent survey was introduced as a personality and lifestyle study. Respondents indicated the hours per week they watch each of eight categories of programs on any device (e.g., TV, computer, mobile phone): sports, comedy, documentaries, dramas, cartoons, sitcoms, soap operas, reality shows, and movies. This was used to capture the total number of TV hours viewed per week across genres and media devices (ranging from 0 −80; O’Guinn & Shrum, 1997). We trimmed outliers (participants with scores + or - 3 SDs above the mean; 3 participants) to account for the large standard deviations that result from this summative measure (Reifman & Keyton, 2010), which resulted in a final sample of 396 participants.

Trait reactance was measured on a 7-item scale (Clayton, Segress, & Caudill, 2007; Hong, 1992; Hoyle, Stephenson, Palmgreen, Lorch, & Donohew, 2002; Russell, Russell, Boland, & Grube, 2013). Drinking intentions were measured with three items. Both sets of items were combined into composites. Table 1 outlines all measures and the descriptive statistics.

2.2.3. Controls

Adolescents reported gender, age, and subjective socio-economic status (SES) on a scale from 0 to 10 designed for adolescent respondents (Goodman et al., 2001). Teens also reported their drinking consumption over the past 30 days (Bowman, Stein, & Newton, 1975): (1 = none in the past 30 days, 2 = once in the past 30 days, 3 = 2–3 times in the past 30 days, 4 = 1–2 times a week, 5 = 3–4 times a week, 6 = 5–6 times a week, 7 = every day). Since 85.1% of adolescents reported not consuming any alcohol in the past month, the adolescent consumption measure was dichotomized as 0 (no drinking in past 30 days) or 1. These low consumption rates are in line with past research on adolescents (Chen, Grube, Bersamin, Waiters, & Keefe, 2005; Jang, Rimal, & Cho, 2013; Marcoux & Shope, 1997) and justify our focus on future drinking intentions.

2.3. Data Analysis

SPSS version 24 was used to conduct a regression with weekly TV viewing, parental co-viewing, and reactance predicting drinking intentions, controlling for past drinking, age, gender, and subjective SES, and the other parental monitoring variables (instructive communication and restricting access). We were specifically interested in the interaction between parental co-viewing, reactance, and TV viewing on drinking intentions. The three-way interactions represent the effect of the combined influence of the three variables in the context of the main effects and two-way interactions; that is, when controlling for the influence of these other effects. We mean-centered all continuous predictors (Aiken & West, 1991; Jaccard, Wan, & Turrisi, 1990). The regression results appear in Table 2.

Table 2.

Multiple Regression Results Predicting Drinking Intentions

b
Intercept .89**
Reactance .23**
Age .12*
Gender (1 = female) −.12*
SES .07
TV viewing −.01
Past Drinking 3.06**
Parental Restriction .11
Parental Instruction .11
Parental Co-viewing −.08
Restriction × Reactance −.01
Instruction × Reactance −.06
Co-viewing × Reactance .00
TV × Reactance −.01
TV × Co-viewing −.02*
TV × Instruction .02
TV × Restriction .01
TV × Restriction × Reactance .00
TV × Instruction × Reactance .01
TV × Co-viewing × Reactance −.04**
Adj R2 .61
F 32.22
p <.001
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NOTE:

*

p < .05

**

p < .01

3. Results

Participants (50% males) varied in age: 13 (3.3%), 14 (28.0%), 15 (28.7%), 16 (34.8%), and 17 (5.3%). The sample was ethnically diverse (62% Caucasian, 10% African American, 8% Hispanic, 4% Asian, 4% other; participants were not forced to select an option). The SES measure was normally distributed, offering a range of socio-economic backgrounds in the sample with 35.7% perceiving their family being as well-off as other families, 28.0% worse-off (below scale mid-point), and 36.3% better-off.

As reported in Table 2, there is a positive main effect of reactance, past drinking, and age on drinking intentions, as well as gender, such that males expressed higher drinking intentions. The analysis reveals a significant three-way interaction between TV viewing, trait reactance, and the co-viewing monitoring strategy. Examination of the VIFs indicated that variables were not affected by multicollinearity (VIFs < 5).

To unfold this interaction, we treated co-viewing as the first order moderator, and reactance as the higher order moderator. The moderating influence of co-viewing on the TV viewing – drinking intentions relationship is significant at higher levels of reactance (1 SD above the mean: β = −.06, F(1,375) = 12.76, p < .001) and average levels of reactance (mean: β = −.02, F(1,375) = 4.39, p = .04) but not at low levels of reactance (p > .48). In other words, a co-viewing parental monitoring strategy moderates the television viewing effect only with adolescents who are higher in reactance.

To explore the nature of this difference, we focused on the interaction between co-viewing and TV viewing at higher levels of reactance. The moderating influence of co-viewing on the relationship between TV viewing on drinking intentions is such that, in households with higher levels of co-viewing, the association between TV viewing and drinking intentions becomes more negative. The relationship between TV viewing and drinking intentions is negative and significant for high reactance teens who have average (β = −.02, t(375) = −2.04, p = .04) and high (1 SD above the mean; β = −.07, t(370) = −3.08, p < .001) levels of co-viewing in their households. See figure 1.

Figure 1.

Figure 1

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Three-way interaction: Reactance X TV Viewing X Co-viewing Effects on Drinking Intentions

4. Discussion

This study, based on data from parents and children, finds that the interactive effect of adolescents’ trait reactance and TV viewing on drinking intentions depends on the parental monitoring strategy of co-viewing. Specifically, for higher reactance adolescents, co-viewing is a beneficial parenting strategy in terms of shaping the influence of media on drinking intentions. The influence of media consumption on drinking intentions is reduced for high reactance teens from households with high levels of co-viewing.

These results suggest a promising approach for a population that has traditionally been considered vulnerable (i.e., high reactance teens). Building on previous findings that high trait reactance buffers the effect of TV on adolescents’ drinking intentions (Russell et al., 2013), this study further shows that the positive effect of high reactance among high-TV viewers is contingent upon the parental monitoring strategy of co-viewing. That is, reactance is only helpful (related to lower drinking intentions) if adolescents grew up in a household with high levels of co-viewing. These findings suggest that co-viewing may activate the “boomerang” effect known to characterize the responses of high reactance teens; that is, rather than internalizing pro-drinking depictions as appropriate among teens, they reject it.

It is noteworthy that neither the instructive nor the restrictive parental monitoring styles moderate the influence of TV viewing on adolescents’ drinking intentions, nor do they interact with trait reactance. This aligns with past research which noted that restrictive monitoring style would be less effective in influencing children’s responses to media consumption because it does not promote dialogue (Austin, Pinkleton, & Fujioka, 2000). It stands in contrast however with research findings that promote instructive communication as an active, reasoning-centered form of monitoring that increases children’s critical viewing skills on topics such as the potential negative influence of advertising (Austin & Pinkleton, 2001; Buijzen &Valkenburg, 2005). The instructive communication approach to developing media literacy involves explicit communication between parents and their children (Austin et al., 2015; Chen et al., 2017; Livingstone & Helsper, 2006).

In contrast, the results of the present study suggest that parents can foster media literate behavior in their children in more subtle ways (which is a particularly important consideration with high reactance teens), through their mere presence. The current work thus suggests that parents’ overt efforts to develop media literacy in their children may not always be the most effective approach; rather, the ideal approach should be tailored based on aspects of the child (such as whether they hold a highly reactant personality). Proponents of media literacy may use the distinction between active and passive approaches to media-related parenting activities in developing recommendations for best practice: parents may be better advised to simply be present during their children’s media consumption if they sense that their children would rebel against direct communication attempts.

Given the increasing shift of media consumption to internet streaming services and on devices such as smartphones and tablets, parents may need to be intentional about co-viewing media with their children more than ever (Kallio & Ruusuvuori, 2019). This research signals that parents should make efforts to experience media with their children in a way that the child perceives as motivated by a desire to share an experience, rather than monitor and control. While smartphones and streaming media may present parents with an attractive way to occupy their child’s attention, such as while traveling in the car or while waiting at a restaurant, the current work suggests that this approach might forego a valuable opportunity to subtly shape the influence of media on children’s risk-related intentions. In essence, parents should make an explicit effort to co-view media with their children, despite the trend in the opposite direction.

One of the strengths of this study is its reliance on data merging monitoring strategies reported by the parents with data on TV viewing, personality and drinking intentions measured from their teenage children. We do acknowledge the dynamic nature of parental monitoring strategies and recommend that future research continue to assess the staying power of parental monitoring strategies, beyond childhood and into adolescence. Longitudinal approaches are warranted to address one of the limitations of the cross-sectional approach adopted here, especially to assess how behavioral intentions, such as those measured in this study, ultimately guide actual behavior. In addition, qualitative research approaches such as ethnographies (Kallio & Ruusuvuori, 2019) could extend the current survey results by examining more closely the ways in which parenting strategies influence how children understand television and how their modeling behaviors emerge over time. Finally, extending this research to other risky behavior domains (Kallio & Ruusuvuori, 2019) such as sex or violence will allow validation of the potential for co-viewing to reduce the negative influences of television on influential audiences.

Biography

Cristel is a leading researcher at the intersection of entertainment and marketing. She has received funding for her research on the nature and impact on youth of substance messages in entertainment through grants from the United States’ National Institutes of Health (including for this project).

Dr. Buhrau conducts research on consumer behavior, particularly in the context of health behaviors. She focuses on topics such as planning and goal pursuit, health communication, and the role of temporal orientation in decision-making.

Dr. Hamby’s research interests fall in the areas of consumer psychology and consumer welfare, exploring topics such as the marketing implications of public policy on society.

Contributor Information

Cristel Antonia Russell, Graziadio School of Business, Pepperdine University, Malibu, CA, USA

Denise Buhrau, College of Business, Stony Brook University, Stony Brook, NY 11794, USA

Anne Hamby, Boise State University, School of Business; Micron Business and Economics Building Room 2240; 1910 University Dr.; Boise, ID 83725, USA.

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