Sad Kids, Sad Media? Applying Mood Management Theory to Depressed Adolescents' Use of Media

Abstract

Mood management studies typically have found that adults will select media that enhance positive moods and reduce negative moods. In this study, adolescents diagnosed with major depressive disorder and control adolescents without psychiatric disorders were called on customized cell phones up to 4 times a day and asked about their current mood state and media use for five extended weekends across an 8-week period. Mood effects on subsequent media use, mood during media consumption, and media effects on subsequent mood were examined. Results indicated that adolescents who consumed fun media tended to do so in a way that sustained, rather than enhanced their prior positive mood levels during and after consumption-if they turned to media. Adolescents in more negative moods did not often use media to improve their moods. When they did, boys were more likely than girls to use media that ultimately reduced negative mood levels. Findings are discussed in light of the literature on mood management, adolescence, and depression.

ACKNOWLEDGMENT

This research was supported by National Institute of Mental Health (NIMH) Grants P01 MH41712 (N.D. Ryan, PI, R.E. Dahl, Co-PI) and R24 research network MH67346 (R.E. Dahl, PI). We are grateful to Laura Trubnick, Jennifer Jakubcak, and the Child and Adolescent Neurobehavioral Laboratory staff at WPIC for their role in assessing the study participants. We are also grateful to Amy Shirong Lu at UNC for assisting with the content analysis of media, and to Mary Beth Oliver, Joanne Cantor, and Marina Krcmar for their assistance in developing the media items.

Notes

1. Though related, positive and negative affect have been shown to differ physiologically (Larsen, Norris, & Cacioppo, 2003), conceptually (Forbes, Williamson, Ryan, & Dahl, 2004), and empirically (Laurent et al., 1999). Thus, we treat these two valences separately in this study.

2. The grand mean for perceived fun quality for all media (television, music, books, magazines, Internet/computers, video games) was 2.94 (SD = 1.42). Video games received the highest fun ratings (M = 3.74, SD = 1.20); books received the lowest (M = 2.29, SD = 1.32). The grand mean for perceived sad quality for all media was 1.25 (SD = .65). Television had the highest sad ratings (M = 1.29, SD = .70); computer media the lowest (M = 1.12, SD = .40).

3. Linear mixed models (LMM) can simultaneously analyze random effects, repeated measures and hierarchical effects. Whereas general linear models (GLM) use listwise deletion for missing cases, LMM draw from individual and pooled differences and can thus include incomplete cases in the analysis. Unfortunately, there are currently no universally accepted effect size estimates equivalent to η² that can be derived from LMM (e.g., see Jiang, 2007). The LMM in this study use a restricted maximum likelihood (REML) algorithm to compute coefficients for our predictors, as REML handles biases due to high correlations and outliers better than other algorithms (e.g., Diggle, 1988; Thompson, 1985). We used a scaled identity covariance type for our random effect and a diagonal covariance matrix for the fixed effect. For more information, see Jiang (2007) and Verbeke and Molenberghs (2000).