Integrating social media variables as predictors, mediators, and moderators within body image frameworks: Potential mechanisms of action to consider in future research. (March 2023) - Tylka, Tracy L.; Rodgers, Rachel F.; Calogero, Rachel M.; Thompson, J. Kevin; Harriger, Jennifer A.
Abstract: In this article, we consider how social media variables may be integrated as predictors, mediators, and moderators within dominant theoretical frameworks of body image in order to identify potential mechanisms of action that can be empirically examined in future research and used to direct prevention and intervention efforts. To achieve this goal, we first articulate social media variables that have been investigated as predictors, mediators, and moderators in body image research. Next, we present the following critical and sociocultural theoretical frameworks: social comparison theory, tripartite influence model, objectification theory, developmental theory of embodiment, acceptance model of intuitive eating, cultivation theory, and uses and gratifications theory. Additionally, we present the theory of development of critical body awareness, a newly developed model that may provide further insight regarding the relationships between social media and body image-related outcomes. For each model, we articulate extant research that has explored social media variables within its context and explicate how social media variables could potentially be studied as predictors, mediators, and moderators within its structure. To conclude, we address pertinent limitations and gaps within this research space that could direct future research across the theoretical frameworks. Highlights: We present social media variables that have been investigated in body image research. We review theoretical models that have examined social media variables within their structure. We outline and describe a novel theory, the development of critical body awareness. We offer suggestions for how social media variables could be studied as predictors, mediators, and moderators within each model. We offer five recommendations for research that help fill existing limitations and gaps.