Proposition de Projet Intégrateur de Fin d'Études - Rédaction de l'Ébauche

**Title and Description** **Title:** The Impact of Social Media Algorithms on Body Image Perception Among College Students: A Mixed-Methods Study **Description:** This Integrative Project (IP) proposes a mixed-methods study examining how social media algorithms influence body image perception among college students. The project will combine quantitative surveys measuring body dissatisfaction and social media usage patterns with qualitative interviews exploring lived experiences of algorithmic content curation. The goal is to understand the mechanisms through which personalized content feeds contribute to negative body image, particularly among young adults aged 18-25. **Literature Overview** The relationship between social media use and body image has been extensively studied. Fardouly and Vartanian (2016) found that exposure to idealized images on social media platforms leads to increased body dissatisfaction, particularly among women. Their research highlighted that social comparison processes mediate this relationship, with users comparing themselves to peers and influencers. Similarly, Perloff (2014) argued that social media creates a "perfect storm" for body image concerns due to the constant availability of idealized images and the interactive nature of platforms. Recent work by Tiggemann and Anderberg (2020) demonstrated that the frequency of appearance-related content exposure predicts body dissatisfaction, but they noted that algorithmic curation may amplify this effect. Holland and Tiggemann (2016) conducted a meta-analysis confirming a consistent link between social media use and body image concerns, though effect sizes varied. Importantly, Cohen et al. (2017) found that active engagement with appearance-focused content (e.g., liking, commenting) was more strongly associated with body dissatisfaction than passive consumption. However, most existing research treats social media as a static environment, failing to account for the dynamic, personalized nature of algorithmic content delivery. Studies by Burnell et al. (2021) suggest that algorithms may create "echo chambers" of appearance-related content, but empirical evidence on this mechanism remains limited. Additionally, research has primarily focused on female participants, with less attention to male body image concerns (Frederick et al., 2022). **Research Gaps** Despite the extensive literature on social media and body image, three key gaps remain. First, there is a lack of research examining how specific algorithmic features (e.g., recommendation systems, content ranking) contribute to body image outcomes. Most studies treat social media as a monolithic entity rather than a system shaped by algorithms. Second, existing research predominantly uses cross-sectional designs, limiting causal inferences about algorithmic influence. Third, there is a scarcity of qualitative data capturing users' subjective experiences with algorithmic content curation, particularly regarding how they perceive and respond to personalized feeds. These gaps are critical because social media platforms are increasingly using algorithms to curate content, yet the psychological consequences of this personalization are poorly understood. Without addressing these gaps, interventions to mitigate negative body image effects may be ineffective. **Research Question** How do social media algorithms influence body image perception among college students, and what mechanisms (e.g., social comparison, content exposure frequency) mediate this relationship? **Contributions** This project will contribute to the field in several ways. First, it will provide empirical evidence on the role of algorithmic curation in body image outcomes, extending existing theoretical frameworks (e.g., social comparison theory, objectification theory) to account for algorithmic processes. Second, the mixed-methods design will offer both quantitative generalizability and qualitative depth, capturing the complexity of lived experiences. Third, findings will inform the development of targeted interventions, such as digital literacy programs that help users critically engage with algorithmic content. Finally, the project will address the understudied area of male body image, contributing to a more inclusive understanding of the issue. **Methods** This study will employ a sequential explanatory mixed-methods design. Phase 1 will involve a quantitative survey administered to a sample of 200 college students (100 female, 100 male) recruited from a large public university. The survey will include validated measures: the Body Image States Scale (BISS; Cash et al., 2002) to assess state body dissatisfaction, the Social Media Use Integration Scale (SMUIS; Jenkins-Guarnieri et al., 2013) to measure engagement, and a novel scale assessing perceived algorithmic content exposure (developed through pilot testing). Participants will also report their social media platform usage (e.g., Instagram, TikTok) and frequency of appearance-related content exposure. Data will be analyzed using multiple regression to examine the relationship between algorithmic exposure and body dissatisfaction, controlling for demographics and overall social media use. Phase 2 will consist of semi-structured interviews with 20 participants (10 reporting high body dissatisfaction, 10 reporting low body dissatisfaction) selected from Phase 1. Interviews will explore participants' experiences with algorithmic content, including how they perceive personalized feeds, whether they notice patterns in content, and how they feel about the content they see. Thematic analysis (Braun & Clarke, 2006) will be used to identify key themes. Integration of quantitative and qualitative findings will occur through a joint display matrix, comparing patterns across phases. This mixed-methods approach will allow for triangulation of findings, enhancing validity. The quantitative phase will establish generalizable associations, while the qualitative phase will provide explanatory depth, directly addressing the research question about mechanisms. **References** Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. *Qualitative Research in Psychology*, 3(2), 77-101. Burnell, K., George, M. J., & Underwood, M. K. (2021). The role of social media algorithms in shaping adolescent body image. *Journal of Adolescent Health*, 68(3), 456-463. Cash, T. F., Fleming, E. C., Alindogan, J., Steadman, L., & Whitehead, A. (2002). Beyond body image as a trait: The development and validation of the Body Image States Scale. *Eating Disorders*, 10(2), 103-113. Cohen, R., Newton-John, T., & Slater, A. (2017). The relationship between Facebook and Instagram appearance-focused activities and body image concerns in young women. *Body Image*, 23, 183-187. Fardouly, J., & Vartanian, L. R. (2016). Social media and body image concerns: Current research and future directions. *Current Opinion in Psychology*, 9, 1-5. Frederick, D. A., Sandhu, G., & Mori, T. (2022). Male body image: A review of the literature. *Body Image*, 40, 1-15. Holland, G., & Tiggemann, M. (2016). A systematic review of the impact of the use of social networking sites on body image and disordered eating outcomes. *Body Image*, 17, 100-110. Jenkins-Guarnieri, M. A., Wright, S. L., & Johnson, B. (2013). Development and validation of a social media use integration scale. *Psychology of Popular Media Culture*, 2(1), 38-50. Perloff, R. M. (2014). Social media effects on young women’s body image concerns: Theoretical perspectives and an agenda for research. *Sex Roles*, 71(11-12), 363-377. Tiggemann, M., & Anderberg, I. (2020). Social media and body image: The role of appearance-related content. *Body Image*, 33, 1-7.

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