Developmental Associations Between Media Use and Adolescent Prosocial Behavior

Abstract

Youth today spend a tremendous amount of time with digital media. The purpose of the present study was to estimate developmental associations between screen media use between the ages of 15 and 17 and corresponding changes in prosocial behavior. Participants (N = 1,509) were part of the Quebec Longitudinal Study of Child Development, a population-based study of children born in the province of Quebec, Canada. Youth self-reported internet and video game use and television or movies/DVD viewing, as well as prosocial behavior at the ages of 15 and 17. Analyses were conducted using multilevel linear modelling to account for between-, within-, and lagged-person effects. Internet and video game use accounted for less prosocial behavior at the within-person and lagged-person levels. Television use also accounted for lagged-person effects in prosocial behavior. Finally, internet use and television viewing contributed to between person differences in prosocial behavior. Our study presents strong statistical evidence that media use during adolescence can undermine the development of prosocial behavior.

Keywords

adolescence internet use media use prosocial behavior screen time television video games

Media use has quickly become the most popular pastime among youth. Adolescents spend an impressive 8 hours per day with digital media, on top of time spent using media for schoolwork (Rideout & Robb, 2019). Television and movie viewing remain popular; however, the popularity of video games and social media continue to climb (M. Anderson & Jiang, 2018). The same study suggests that media use by youth is of concern to parents, with 65% reporting they worry about their adolescent’s use of media. Indeed, research examining the psychosocial consequences of media use by youth has been highly publicized while also presenting mixed messages.

Viewing mainstream television programs and playing videogames have been linked to increases in aggression and decreased empathy and prosocial behavior in children (C. A. Anderson et al., 2010). At the same time research suggests that playing video games can provide emotional and social benefits to youth (Granic et al., 2014) and increase helping behavior when the contents are prosocial (Greitemeyer & Osswald, 2010). Research on the consequences of time spent online by youth is also mixed. Some studies suggest that time spent online by youth can lead to increased self-esteem, perceived social support, and identity exploration (Carrier et al., 2015). In contrast, other studies have linked social media use to isolation, depression, narcissism, and increased risk of being the perpetrator and target of online aggression (Álvarez-García et al., 2015; Best et al., 2014; Festl et al., 2013).

The extent to which media usage contributes to real-life prosocial behavior, reflecting the tendency to enact empathy and helping behavior toward others is an important question for research. Prosocial youth use less aggression, have higher quality interpersonal relationships, and earn higher wages in adulthood (Eron et al., 1987; Vergunst et al., 2019). As such, understanding how experiences with digital media contribute to the development of prosocial skills can confer advantages for both the individual and society. Adolescence is a sensitive period for the development of prosocial skills and foundational personality traits (Patton et al., 2016; Soto & Tackett, 2015). In particular, the prefrontal cortex undergoes significant reconstruction and rewiring during adolescence, resulting in improved perspective taking, abstract thinking, and empathy (Crone & Dahl, 2012). Furthermore, specific neurodevelopmental features of adolescence, such as increased brain plasticity, increased emotional reactivity, sensitivity to peer influence, impulsivity, and novelty seeking also make them particularly sensitive to environmental influences including media (Lee et al., 2014).

Youth who spend much of their time interacting with screen media are likely to experience reduced opportunities for face-to-face interactions with peers. According to one study, based on a large representative sample of American youth, there has been a generational decrease in the amount of time adolescents spend engaging in face-to-face interactions. In particular, the amount of time youth spent getting together with friends has decreased by an average of 1 hour a day in current generations (Twenge et al., 2019). Such face-to-face interactions are then important for building interpersonal competence and empathy (Konrath, 2012). As a result, the extent to which time spent with media during adolescence may interfere with the acquisition of important prosocial skills merits investigation.

To date, limited research has addressed the effect of screen time on positive interpersonal behavior in youth. We aim to advance research by performing statistical analyses allowing us to dissociate common vulnerability and estimate concurrent and lagged relationships between adolescent screen time and prosocial behaviors. For this purpose, we employ a study design in which different types of screen time (i.e., internet use, television viewing, and playing video games) and prosocial behavior were repeatedly measured over the course of 2 years. Within this design we employed a multivariate multilevel framework, distinguishing between three time-varying predictors of prosocial behaviors: (1) average media use over 2 years (between-person effect), (2) change in media use within a given year compared to one’s mean media use within that same year (within-person effect), and (3) media use the year before compared to one’s mean media use (lagged-within-person effect). Similar statistical approaches have been used in previous investigations of the consequences of child and adolescent screen time (Boers et al., 2019; Madigan et al., 2019). Modeling time-varying relationships between observational data using a multilevel framework, allows for a more rigorous evaluation of the nature of the association between media use and development and helps rule out common methodological issues related to omitted variable bias. Given the prior literature on media consumption and behavioral development, we hypothesize that youth who spend more time viewing television and movies, playing video games, and surfing the internet will show decreases in prosocial behavior.

Method

Sample

Participants in the present study were followed in the context of the Quebec Longitudinal Study of Child Development (1999–2020), conducted by the Institut de la statistique du Québec. This birth cohort study was based on a randomly selected, stratified sample of 2837 infants born between 1997 and 1998 in the province of Quebec. From this initial sample, 2,020 infants were selected for longitudinal follow-up. In total, 49.1% of participants were girls, 72% were described by their parent or primary caregiver as being Canadian, and 21.7% of parents reported being under the poverty line cut-off for Canadian families. At its baseline, the Quebec Longitudinal Study of Child Development has been deemed representative of children born into the province between 1997 and 1998 (Thibault et al., 2001). Our study draws on data collected during the adolescent phase of this longitudinal birth cohort study of child development. Our analytical sample was based on 1,509 youth with available data on media use. Questionnaires were administered predominantly in French, reflecting the linguistic distribution of the province of Quebec, Canada. This study received approval from the ethics review boards of the Institut de la statistique du Quebec and Université Sainte-Anne. From school entry onward, informed consent was obtained from the child and parents. The main predictors and outcomes for this study were collected in 2013 and 2015 when participants were in their third and fifth year of high school, respectively.

Measures: Outcome

Prosocial behavior: Participants self-reported prosocial behavior during the previous 6 months using all 7-items derived from the Social Behavior Questionnaire (Dobkin et al., 1995; Tremblay et al., 1994). Items included,

When someone got hurt, I didn’t hesitate to help them; When someone made a mistake, I felt sorry for them; When I witnessed an argument, I tried to stop it; When someone spilled or broke something, I offered to help clean it up; I helped people around me when they were having difficulty; I readily shared my belongings with others; I was kind to younger children.

Answers were ranked on a Likert-type scale ranging from 1 (never) to 3 (often). Mean scores were then rescaled from 0 to 10. Higher scores reflect higher levels of prosocial behavior. Cronbach’s alpha for prosocial skills were, α = .90 and .91 at ages 15 and 17 years, respectively.

Predictors

Screen Time: Youth responded to three questions assessing the amount of time they spent (1) watching television or videos/DVDs, (2) playing video games that were not on a computer, (3) accessing the internet on a computer to play games, do searches, chat or go on Facebook (excluding time spent on the internet at school). Answer options included (1) None, (2) Less than an hour, (3) 1 to 2 hours, (4) 3 to 5 hours, (5) 6 to 10 hours, (6) 11 to 14 hours, (7) 15 to 20 hours, or (8) more than 20 hours. Scores were converted to continuous measures of hours per day by using the midpoint value for each range with the exception of 20 or more hours, which was scored as 20 hours.

Data Analytic Strategy

We employed multilevel linear modeling while distinguishing between three time-varying effects on prosocial behavior: between-person effects (the effect of average screen time use over 2 years), within-person effects (change in screen time use within a given year compared with one’s mean screen time use within that same year), and lagged-within-person effects (screen time use the year before compared to one’s mean screen time use the following year). Between-person, within-person, and lagged-within-person effects were included within the same model, therewith assessing concurrent and lasting changes between variables. The time parameter (the survey waves) was coded as 1 or 2 and each model included gender as a covariate (coded as 1 for boys and 2 for girls). To assess the association of screen time and prosocial behavior, a multivariate multilevel model was performed for each type of screen time (i.e., internet use, television viewing, and video gaming) and the main outcome variable (i.e., prosocial behavior). Each multilevel linear model tested the null hypothesis at the one-tailed 95% confidence interval level.

Results

Compared with the initial representative population sample, our analytical sample was higher socioeconomic status (M = 0.10 vs. −0.21, p < .001) and contained more girls than boys (52% vs. 48%, p < .001). Descriptive statistics are presented in Table 1. Multilevel linear models were estimated using Mplus 8.3 software (Muthén & Muthén, 2016). As depicted in Figure 1, these computational multilevel models were able to estimate the extent to which changes in screen time behavior might result in concurrent or lasting changes in prosocial behaviors.

Table 1.

Descriptive Statistics.

Screen time	Age 15 years			Age 17 years
Screen time	M (SD)	Minimum–maximum	n	M (SD)	Minimum–maximum	n
Prosocial	6.66 (2.20)	0–10	1,436	7.13 (2.07)	0–10	1,187
Internet	1.00 (0.86)	0–2.86	1,389	1.08 (0.89)	0–2.86	1,188
Video games	0.47 (0.72)	0–2.86	1,431	0.43 (0.75)	0–2.86	1,234
TV/movies	0.80 (0.71)	0–2.86	1,428	0.74 (0.66)	0–2.86	1,235

Note. Data were compiled from the final master file of the Québec Longitudinal Study of Child Development (2013-2015), ©Gouvernement du Québec, Institut de la statistique du Québec.

Figure 1.

Multilevel linear model examining concurrent and cross-lagged associations between screen time and prosocial behavior.

The Association of Screen Time and Prosocial Behavior

Regression coefficients, 95% confidence intervals (95% CIs), and one-tailed p values are presented in Table 2. In terms of the associations between internet use and prosocial behavior, results indicated significant between-person (β = 0.25, 95% CI [0.09, 0.41], p = .001), within-person (β = −0.27, 95% CI [−0.34, −0.17], p = .001), and lagged-within-person associations (β = −0.32, 95% CI [−0.41, −0.18], p = .001). At the between-person level, these findings indicate that higher average levels of internet use over the course of 2 years were significantly associated with higher average levels of prosocial behavior. At the individual-level we found that increases in internet use in a given year were associated with less prosocial behavior in the same year (within-person effect) and the year that followed (lagged-within-person effect). A similar pattern of parameters was detected for video gaming and prosocial behavior. Playing video games was associated with less prosocial behavior at the within-person (β = −0.35, 95% CI [−0.40, −0.28], p = .001) and lagged-within-person levels (β = −0.47, 95% CI [−0.55, −0.34], p = .001), but not at the between-person level (β = 0.12, 95% CI [−0.03, 0.25], p = .05). Finally, for television viewing and prosocial behavior, we observed significant associations at the between-person (β = −0.31, 95% CI [−0.46, −0.11], p = .001) and lagged-within-person level (β = 0.27, 95% CI [0.06, 0.39], p = .001), but not at the within-person level (β = 0.16, 95% CI [−0.04, 0.25], p = .04).

Table 2.

Estimated Parameters for Multilevel Models Assessing the Effect of Internet Use, Television Viewing, and Video Gaming on Prosocial Behavior in Adolescents.

Predictors	Estimate	Pr(>\|t\|)	95% CI
Internet use
Intercept	2.53	0.000	[2.09, 2.95]
Time	0.14	0.000	[0.11, 0.17]
Sex	0.36^a	0.000	[0.30, 0.42]
Between-person	0.25^a	0.002	[0.09, 0.41]
Within-person	−0.27^a	0.000	[−0.34, −0.17]
Lagged-within-person	−0.31^a	0.000	[−0.41, −0.18]
Television viewing
Intercept	3.46	0.000	[2.98, 3.94]
Time	0.15	0.000	[0.11, 0.19]
Sex	0.35^a	0.000	[0.29, 0.40]
Between-person	−0.31^a	0.007	[−0.46, −0.1]
Within-person	0.16	0.04	[−0.04, 0.25]
Lagged-within-person	0.27^a	0.013	[0.11, 0.19]
Video gaming
Intercept	3.55	0.000	[3.12, 4.05]
Time	0.12	0.000	[0.09, 0.16]
Sex	0.28^a	0.000	[0.19, 0.38]
Between-person	0.12	0.054	[−0.03, 0.25]
Within-person	−0.35^a	0.000	[−0.40, −0.28]
Lagged-within-person	−0.46^a	0.000	[−0.55, −0.34]

Note. Data were compiled from the final master file of the Québec Longitudinal Study of Child Development (2013-2015), ©Gouvernement du Québec, Institut de la statistique du Québec.

Significant time-varying effect (one-tailed p value).

Discussion

In the present study, we found evidence for the temporal precedence of adolescent media use when examining associations between media use and prosocial behavior. Examination of within-person and lagged-person effects, which are especially powerful estimates of individual-level change, revealed that exposure to the internet and video games during adolescence contribute to decreases in helping behavior toward others. In particular, youth who were exposed to more internet and video games at age 15 years displayed less prosocial behavior at age 17 years. This observation of lagged effects over 2 years suggests that the influence of media on adolescent social skills is likely to be gradual and cumulative. At the within-person level, adolescents who spent more time engaged in internet use and playing video games also reported significantly less prosocial behavior toward others in that same year. In contrast, youth who spent more time watching television shows and movies showed increases in their tendency to behave prosocially toward others. Finally, at the between-person level, we observed a negative association between youth television consumption and prosocial behavior, whereas time spent online predicted more prosocial behavior in youth.

These divergent findings across mediums could have emerged for several reasons. First, media use may contribute to reduced helping behavior because it takes time away from empathy building learning experiences that generally involve face-to-face interactions. In particular, youth are likely to develop empathy and prosocial skills, by developing good quality relationships with parents, peers, and members of their community and through involvement in activities such as volunteering or team sports (Silke et al., 2018).

Second, the present results may also be content driven, though it was not possible to address this explanation in the present study. There is a large body of research suggesting that youth can learn to adopt prosocial or antisocial behavior through exposure to these behavors in media (C. A. Anderson et al., 2010; Coyne et al., 2018). The observed negative lagged-within person effect of video game playing on prosocial behavior is consistent with this literature. Acts of verbal and nonverbal aggression are featured frequently in video games and violent video games are tremendously popular among children and youth (Smith et al., 2003; Wilson, 2008). As an illustrative example, Fortnite, a combat game based on the principles of first-person and team-based shooting, grossed 2.4 billion USD in 2018, the highest annual revenue figure in gaming history to date (Perez, 2020). Over time, a diet rich in antisocial content places youth at risk of developing a social–cognitive bias known as the mean world syndrome, which is the belief that the world is more dangerous and hostile than it actually is (Gerbner, 1998). Such beliefs can then increase the likelihood of hostility toward others and reduce helping behavior (Bushman & Huesmann, 2012). In addition, recent data suggests that 96% of youth access social media platforms daily (Rideout & Robb, 2019). Interactive media may expose youth to peer-generated content, which is likely to be an especially powerful socialization mechanism. For example, in one study, the nature of adolescent’s digital interactions with their peer group influenced individual behavior, such that more socially aggressive texting within the peer group predicted more in-person aggression (Vollet et al., 2019).

Third, the observed associations could also have been driven by contextual features of youth media use. For instance, the paradoxical finding that television viewing contributes to an increase in prosocial behavior compared with video game playing and surfing the internet, could reflect that youth may be more likely to coview television and movies with peers and other family members, which could account for its positive contribution to prosocial behavior. In line with this hypothesis, active coviewing of media by parents has been linked to more positive psychosocial outcomes in adolescents (Padilla-Walker et al., 2016). Furthermore, results could reflect an interaction between context and content. For instance, youth may view more prosocial and family friendly content on television and more antisocial content online and while playing video games.

Last, with regard to the between-person effects, these observed effects are likely to be due to our modelling approach, which allowed us to partial out individual level-change, a more powerful estimate of influence between variables. Aggregate sample varying effects remained though it is more difficult to interpret these effects. The observed between person effects could indicate that exposure to television and surfing the internet lead to concurrent change in prosocial behavior. However, these effects could also indicate reverse causality, differences in individual dispositions to media use and prosocial behavior, and residual confounding. As a result, we believe caution is warranted in the interpretation of these results, which provide less certainty than the individual-level change indicators.

The additional consideration of content as well other relevant features of adolescent media usage could help clarify the conditions under which media usage contributes to real-life aggressive or prosocial acts. Specific features worth considering include the nature of online activities, (types of websites accessed and apps used), types of usage (i.e, interactive vs non interactive), characteristics of interactions (i.e., interaction with peer vs. nonpeer, types of user feedback), and user characteristics (i.e., motivation and intentions). Careful consideration of the additive and interactive contribution of these features in future longitudinal investigations will help advance our understanding of how and when media use may contribute to positive and negative youth outcomes. In particular, future research could examine the extent to which different child media use profiles, that differ in contents, types of usage and interactions, and time devoted to media, may contribute to social outcomes.

Several limits merit consideration. First, as previously noted, the present study was not able to account for the specific features of youth media use. In particular, it was not possible to account for how different media diets that may be higher or lower in prosocial versus antisocial contents contribute to youth behavior. This is likely to have resulted in the dilution of the effect of media contents on youth behavior. A second limitation is that our data were collected between 2013 and 2015. Because the rapid pace at which technology has infiltrated the lives of youth, it is likely that nature of contents and apps that youth are using today differs from those used 5 years ago. Finally, the present study is based on youth self-reports of media use, which are likely to lead to underestimates of actual use.

As our understanding of the impacts of digital media use on child health continue to evolve, health professionals and clinicians may be called upon to help youth adopt healthy media habits. For one, they are ideally positioned to include questions about media habits during consultations with adolescents. Furthermore, they can advise parents to monitor their child’s media use. Parental monitoring of child media habits has been linked to reduced screen time and lower probability of negative outcomes including aggression (Collier et al., 2016). In contrast, overly strict and rigid strategies by parents may backfire with older children and adolescents (Samuel, 2015). Consequently, democratic, respectful, collaborative approaches that involve youth in decision making and planning of family media routines are likely to be the most effective (Minges et al., 2015). Furthermore, through previously described social learning processes, parent’s own media use has also been identified as a determinant of unhealthy media use by youth (Lauricella et al., 2015). As such, preventive interventions aimed at improving child and youth media habits are likely to benefit from targeting parental media use as well.

The ability to develop strong and nurturing connections with others is a crucial component of lifelong well-being and mental health. The present study provides evidence that youth who expose themselves to media may be compromising their ability to enact empathy and behave in a prosocial way toward others. As a such, our findings support recommendations that caution adolescents to use media in moderation.

Footnotes

Acknowledgements

The Québec Longitudinal Study of Child Development was supported by funding from the ministère de la Santé et des Services sociaux, le ministère de la Famille, le ministère de l’Éducation et de l’Enseignement supérieur, the Lucie and André Chagnon Foundation, the Institut de recherche Robert-Sauvé en santé et en sécurité du travail, the Research Centre of the Sainte-Justine University Hospital, the ministère du Travail, de l’Emploi et de la Solidarité sociale and the Institut de la statistique du Québec.

Authors’ Note

Caroline Fitzpatrick is now at Université de Sherbrooke, Département de l’enseignement au préscolaire et au primaire, Sherbrooke, Canada, and University of Johannesburg, Department of Childhood Education, Johannesburg, South Africa.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Caroline Fitzpatrick

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