The Differential Susceptibility to Media Effects Model

Valkenburg, Patti M.; Peter, Jochen

doi:10.1111/jcom.12024

Cited by 844 publications

(902 citation statements)

References 64 publications

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“…The individual differences we found in the effects of exposure to positive social media posts are in line with current views of media effects (e.g., Fikkers et al, 2016;Oliver, 2002;Valkenburg & Peter, 2013;van Oosten et al, 2015). These views posit that the effects of media messages depend on how a certain individual processes these messages (Fikkers et al, 2016;Oliver, 2002;Valkenburg & Peter, 2013;van Oosten et al, 2015).…”

Section: Discussionsupporting

confidence: 75%

“…According to recent advances in media effects research, the same media messages can result in different effects depending on how these messages are processed (e.g., Fikkers et al, 2016;Oliver, 2002;Valkenburg & Peter, 2013;van Oosten et al, 2015). In line with this perspective, the literature and reasoning above illustrate two ways of processing social information that can result in opposing effects on mood.…”

Section: Individual Differences: the Moderating Role Of Social Comparmentioning

confidence: 83%

“…These views posit that the effects of media messages depend on how a certain individual processes these messages (Fikkers et al, 2016;Oliver, 2002;Valkenburg & Peter, 2013;van Oosten et al, 2015). As a result, scholars have called for more research into individual differences in media effects (e.g., Oliver, 2002;Valkenburg & Peter, 2013).…”

Section: Discussionmentioning

confidence: 99%

“…As individual differences in social comparison orientation are related to differential processing of social information on social media (Lee, 2014) and the processing of social information is, in turn, related to differential effects of media messages (Fikkers et al, 2016;Valkenburg & Peter, 2013;van Oosten et al, 2015), social comparison orientation also moderates the effects of social media use (Fardouly et al, 2015;Kleemans et al, 2016;Vogel et al, 2015). In an experiment among 112 female participants aged 17-25, women with high levels of appearance comparison orientation were unhappier with their face, skin, and hair after browsing Facebook for 10 minutes than after browsing a control website, while this difference did not emerge among women lower in appearance comparison orientation (Fardouly et al, 2015).…”

Section: Individual Differences: the Moderating Role Of Social Comparmentioning

confidence: 99%

“…Media effects research indicates that there are important individual differences in how messages are processed and, as a result, in how they affect the viewer (Fikkers, Piotrowski, & Valkenburg, 2016;Valkenburg & Peter, 2013;van Oosten, Peter, & Boot, 2015). Most relevant to the current topic, a number of experiments show that individuals' tendency to engage in social comparison influences the effects of exposure to social media content (Fardouly et al, 2015;Kleemans, Daalmans, Carbaat, & Anschutz, 2016;Vogel et al, 2015).…”

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confidence: 99%

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Social Comparison as the Thief of Joy: Emotional Consequences of Viewing Strangers’ Instagram Posts

et al. 2017

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Section: Discussionsupporting

confidence: 75%

Section: Individual Differences: the Moderating Role Of Social Comparmentioning

confidence: 83%

Section: Discussionmentioning

confidence: 99%

Section: Individual Differences: the Moderating Role Of Social Comparmentioning

confidence: 99%

mentioning

confidence: 99%

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Social Comparison as the Thief of Joy: Emotional Consequences of Viewing Strangers’ Instagram Posts

et al. 2017

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Analysis of Social Media Use, Mental Health, and Gender Identity Among US Youths

Coyne,

Weinstein,

Sheppard

et al. 2023

JAMA Netw Open

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ImportanceMental health among children and adolescents is a critical public health issue, and transgender and gender nonbinary youths are at an even greater risk. Social media has been consistently associated with youth mental health, but little is known about how gender identity interacts with this association.ObjectiveTo use a risk and resilience approach to examine the association between social media use and mental health among transgender, gender nonbinary, and cisgender youths.Design, Setting, and ParticipantsThis cross-sectional study analyzed data collected from an online survey between May and August 2021. Participants included a random sample of US youths; eligibility requirements included being aged 10 to 17 years and residing in the US. Statistical analysis was performed from February to April 2022.Main Outcomes and MeasuresSocial media use (time, type of use, favorite site, social comparisons, mindfulness, taking intentional breaks, cleaning and curating feeds, problematic use, and media literacy programs at their school) and mental health (depression, emotional problems, conduct problems, and body image) as main outcomes.ResultsParticipants included 1231 youths aged 10 to 17 years from a national quota sample from the United States; 675 (54.8%) identified as cisgender female, 479 (38.9%) as cisgender male, and 77 (6.3%) as transgender, gender nonbinary, or other; 4 (0.3%) identified as American Indian or Alaska Native, 111 (9.0%) as Asian, 185 (15.0%) as Black, 186 (15.1%) as Hispanic or Latinx, 1 (0.1%) as Pacific Islander, 703 (57.1%) as White, and 41 (3.3%) as mixed and/or another race or ethnicity. Gender identity moderated both the strength and the direction of multiple associations between social media practices and mental health: active social media use (eg, emotional problems: B = 1.82; 95% CI, 0.16 to 3.49; P = .03), cleaning and/or curating social media feeds (eg, depression: B = −0.91; 95% CI, −1.98 to −0.09; P = .03), and taking intentional breaks (eg, depression: B = 1.03; 95% CI, 0.14 to 1.92; P = .02).Conclusions and RelevanceIn this cross-sectional study of gender identity, social media, and mental health, gender identity was associated with youths’ experiences of social media in ways that may have distinct implications for mental health. These results suggest that research about social media effects on youths should attend to gender identity; directing children and adolescents to spend less time on social media may backfire for those transgender and gender nonbinary youths who are intentional about creating safe spaces on social media that may not exist in their offline world.

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Longitudinal Associations Between Use of Mobile Devices for Calming and Emotional Reactivity and Executive Functioning in Children Aged 3 to 5 Years

et al. 2023

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ImportanceMobile devices are often used to keep young children occupied or calm, but it is not known whether this practice influences child development.ObjectiveTo examine the longitudinal, bidirectional associations between the parent-reported frequency of using mobile devices to calm young children and children’s executive functioning (EF) and emotional reactivity, testing moderation by child sex and temperament.Design, Setting, and ParticipantsThis prospective cohort study included a community-based convenience sample of English-speaking parents of typically developing children aged 3 to 5 years. The study duration was from August 2018 to January 2020, with baseline (T1), 3-month follow-up (T2), and 6-month follow-up (T3) waves.ExposuresParent-reported frequency of use of mobile devices to calm children when upset (5-point Likert scale).Main Outcomes and MeasuresAt each wave, the child’s EF was assessed with the Behavior Rating Inventory of Executive Function–Preschool Version Global Executive Composite and emotional reactivity with the Child Behavior Checklist Emotional Reactivity subscale. Structural equation models were built to examine cross-lagged associations of the use of devices for calming, EF, and emotional reactivity, testing for moderation by child sex or temperament (Child Behavior Questionnaire–Very Short Form surgency score, median split).ResultsOf 422 eligible parents with data at T1, 375 (88.9%) provided data at T2 and 366 (86.7%) at T3. At baseline, the mean (SD) age of the 422 children was 3.8 (0.5) years, the number of boys in the sample was 224 (53.1%), the number of individuals of non-Hispanic White race and ethnicity was 313 (74.2%), and among the parents, 254 (60.2%) had a college degree or higher. Among the boys, the use of devices to calm at T2 was associated with higher emotional reactivity at T3 (r [standardized regression coefficient] = 0.20; 95% CI, 0.10-0.30), while higher emotional reactivity at T2 had a nonsignificant association with increased device use for calming at T3 (r = 0.10; 95% CI, −0.01 to 0.21). Among children with high temperamental surgency, the use of devices to calm at T2 was associated with increased emotional reactivity at T3 (r = 0.11; 95% CI, 0.01-0.22), while higher emotional reactivity at T2 was associated with increased device use for calming at T3 (r = 0.13; 95% CI, 0.02-0.24).Conclusions and RelevanceThe findings of this study suggest that the frequent use of mobile devices for calming young children may displace their opportunities for learning emotion-regulation strategies over time; therefore, pediatric health care professionals may wish to encourage alternate calming approaches.

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The Differential Susceptibility to Media Effects Model

Cited by 844 publications

References 64 publications

Social Comparison as the Thief of Joy: Emotional Consequences of Viewing Strangers’ Instagram Posts

Social Comparison as the Thief of Joy: Emotional Consequences of Viewing Strangers’ Instagram Posts

Analysis of Social Media Use, Mental Health, and Gender Identity Among US Youths

Longitudinal Associations Between Use of Mobile Devices for Calming and Emotional Reactivity and Executive Functioning in Children Aged 3 to 5 Years

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