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Body Image 51 (2024) 101767

Available online 16 July 2024 1740-1445/© 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Social media and body image: Relationships between social media appearance preoccupation, self-objectification, and body image

Kyle M. Brasil a,*,1, Callie E. Mims a,2, Mary E. Pritchard b,3, Ryon C. McDermott c,4

a University of South Alabama, Department of Psychology, 75 South University Blvd, Mobile, AL 36688, USA b Boise State University, Department of Psychological Science, 1910 University Dr. Boise, ID 83725-1715, USA c University of South Alabama, Department of Counseling and Instructional Sciences, University Commons 3600, Mobile, AL 36688, USA

A R T I C L E I N F O

Keywords: Social media usage Gender Body dissatisfaction Body image Drive for thinness Drive for leanness Drive for muscularity Shame Surveillance

A B S T R A C T

Nearly 85 % of emerging adults report using at least one social media site. Research suggests that viewing and internalizing unrealistic body ideals often displayed online may pose harmful effects on young people’s body image. However, studies on the relationships between social media usage and body image have predominantly focused on women’s drive for thinness. We sought to explore the relationships between social media appearance- related preoccupation (SMARP), body shame and surveillance, and drives for leanness, muscularity, and thin- ness, specifically examining the moderating role of gender within these relationships. Data from 939 under- graduate students (n = 240 men) were analyzed using multigroup structural equation modeling. Surveillance significantly mediated the positive associations between SMARP and drive for leanness for women and men. For SMARP and drive for muscularity, surveillance was a mediator for men only. Shame emerged as a significant mediator of the positive association between SMARP and drive for thinness for women and men. Moderated mediation was supported, such that the indirect effect of SMARP on drive for thinness was significantly stronger for women. These results suggest that for men in particular, SMARP is not necessarily associated with increased drives for leanness and muscularity unless men are also engaging in body surveillance.

1. Introduction

According to the Pew Research Center (2021), nearly 85 % of emerging adults (18–29 years old) use at least one social media site. Research suggests that collegiate males and females who view and then internalize unrealistic body ideals that they see online may experience body dissatisfaction (Andrew, Tiggemann, & Clark, 2016; Legkauskas & Kudlaitė, 2022; Stein, Krause, & Ohler, 2019). In fact, recent research suggests that body dissatisfaction and physical appearance comparisons have increased in young women since the beginning of the COVID-19 pandemic (Penalba-Sánchez et al., 2022; Vall, Andrés, González, & Saldaña, 2023). This has been attributed to the widespread use of social media during the pandemic (Penalba-Sánchez et al., 2022). Men’s social media usage has also grown over time, and two-thirds of men report using at least one social media site (Pew Research Center, 2021).

However, the majority of research on the correlations between social media and body image has focused on women. Given the increase in social media usage in college students during the pandemic (Bennett et al., 2020; Penalba-Sánchez et al., 2022) and its correlation to body dissatisfaction in young adults, the present study sought to further explore the relationship between social media and body dissatisfaction with a specific emphasis on how these variables interact with gender.

1.1. Body Shame, Body Surveillance, and Body Dissatisfaction: The Role of Social Media

Whymight the use of social media be associated with higher levels of body dissatisfaction? Sociocultural theory posits that body dissatisfac- tion in young adults results from exposure to Westernized body image ‘ideals’ where bodies are displayed as objects, along with the

* Correspondence to: Department of Psychology, University of South Alabama, University of South Alabama College of Science, 75 South University Blvd, USA. E-mail address: [email protected] (K.M. Brasil).

1 orcid.org/0000-0002-5682-6130 2 orcid.org/0000-0003-0901-951X 3 orcid.org/0000-0002-4704-5869 4 orcid.org/0000-0002-4887-6066

Contents lists available at ScienceDirect

Body Image

journal homepage: www.journals.elsevier.com/body-image

https://doi.org/10.1016/j.bodyim.2024.101767 Received 5 February 2024; Received in revised form 20 June 2024; Accepted 5 July 2024

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internalization of the belief that rewards are gained when onemeets said body image ideals (Morrison, Kalin, & Morrison, 2004; Thompson, Heinberg, Altabe, & Tantleff-Dunn, 1999; Tiggemann, 2011; Tylka, 2011). One often cited sociocultural model of body dissatisfaction, the Tripartite theory, further suggests that media is one of three primary drivers of appearance pressures from social contexts that serve to rein- force Westernized ideals of both thinness and muscularity (Barnhart et al., 2023; Schaefer, Harriger, Heinberg, Soderberg, & Kevin Thomp- son, 2017; Thompson et al., 1999; Tylka, 2011). The internalization of these body ideals lends itself to using similar others as a comparison point to ascertain if one is measuring up (e.g., Social Comparison The- ory, Festinger, 1954). Repeated exposure to these media ideals also contributes to self-objectification, where one feels the need to constantly monitor/surveil one’s appearance as compared to those ideals (Fredrickson & Roberts, 1997). If one feels they do not meet sociocul- tural body standards, they may feel a sense of shame about their body (Fredrickson & Roberts, 1997; McKinley & Hyde, 1996). In fact, research suggests that the use of social media sites such as Instagram and Facebook is correlated with greater social comparison (Hanna et al., 2017), particularly appearance-related comparison (Di Gesto, Nerini, Policardo, & Matera, 2021) and self-objectification in college students (Garcia, Bingham, & Liu, 2022; Hanna et al., 2017). In turn, the use of self-objectifying social media is associated with higher levels of body surveillance, which is related to an increase in body shame among male and female adolescents, college students, and adults (Hanna et al., 2017; Manago, Ward, Lemm, Reed, & Seabrook, 2015; Rollero, Gattino, De Piccoli, & Fedi, 2018; Salomon & Brown, 2019). This connection ap- pears to be stronger in females than in males (Manago et al., 2015; Salomon & Brown, 2019). This is not surprising as sociocultural appearance norms tend to be more rigid for females, which are more harmful to body image perceptions than the less-rigid body standards presented to males (Buote, Wilson, Strahan, Gazzola,& Papps, 2011). As a result, women expect to be judged more harshly for failing to meet appearance norms (Fredrickson & Roberts, 1997), as they tend to be more focused on others’ approval than their male counterparts. This other-centered focus is associated with higher levels of body surveil- lance and more self-objectification behaviors on social media (Salomon & Brown, 2019). This is consistent with Rollero et al. (2018), who found that females reported higher levels of body shame than males and that the internalization of media standards exhibited a stronger predictive relationship with body surveillance in women than men. Similarly, Buote et al. (2011) reported that women are more likely than men to believe they should be able to achieve the ideal appearance, leading to self-blame when they feel they have failed (see also Franzoi et al., 2012; Tamplin, McLean, & Paxton, 2018).

Following trends in other literature on body image, studies on the relationship between social media usage and body image have pre- dominantly focused on women (Harriger, Thompson, & Tiggemann, 2023). Despite this gender gap, researchers focused on the relationships between social media, body image, and disordered eating outcomes have found conflicting evidence for gender differences (Holland & Tig- geman, 2016). While some researchers suggest that the pathway from social media use to body dissatisfaction, as mediated by self-objectification, is often stronger in women, other researchers sug- gest that body shame may play a critical role within this relationship for men as well as women. Indeed, several studies have demonstrated that social media usage, particularly on sites that involve greater visual impression management, such as Instagram or Facebook (Manago et al., 2015), and body shame are key predictors of lower body esteem in men (Boursier & Gioia, 2022). In stark contrast, Yeung, Massar, and Jonas (2021) identified that while pressure from the media was significantly associated with higher muscle dissatisfaction through increased social comparison, body surveillance was not significantly associated with muscularity dissatisfaction. Xiaojing (2017) supported similar findings; while body surveillance mediated the relationship between social media use and body dissatisfaction among female adolescents, it was not a

significant mediator for male adolescents. Additionally, researchers suggest that men and women may be differentially affected by different types of media images. Skowronski, Busching, and Krahé (2022) found that when female adolescents viewed sexualized female images on social media sites like Instagram, they endorsed greater internationalization of the thin ideal and valuing of appearance over competence, which sub- sequently led to body surveillance. On the other hand, when male ad- olescents viewed sexualized male images, this led to internalization of the muscular ideal, which then led to body surveillance. Taken together, these findings suggest the need for greater research on the gender-conditional relationships between media usage, body shame and surveillance, and body dissatisfaction.

1.2. Social media use and body dissatisfaction

1.2.1. Social media and drive for thinness/muscularity Although research has established connections between social media

usage and body dissatisfaction (Andrew et al., 2016; Legkauskas & Kudlaitė, 2022; Stein et al., 2019), body dissatisfaction comes in many forms. One of the most widely studied forms of body dissatisfaction is the drive for thinness, which is indicated by a preoccupation with dieting and weight (Garner, 2004) and is more commonly reported by female college students than male college students (Brown, Forney, Klein, Grillot, & Keel, 2020). Research suggests that female college students who spend more time on social media are more likely to report a drive for thinness (Ghiţă et al., 2021). Similar to body shame and body surveillance, evidence supports the pathway from social media use to appearance comparison to the subsequent drive for thinness (Fardouly& Vartanian, 2015; Foster, O’Mealey, Farmer, & Carvallo, 2022; Piccoli, Carneghi, Grassi, & Bianchi, 2022). Research further suggests that body surveillance serves as a mediator between social media use and the drive for thinness in young women (Butkowski, Dixon,&Weeks, 2019; Seekis, Bradley, & Duffy, 2020). Thus, it can be postulated that the use of appearance-based social media leads to appearance comparison, which leads to body surveillance, which leads to social appearance anxiety, which ultimately leads to a drive for thinness in female college students (Seekis et al., 2020).

Although evidence in female adolescents (Slater & Tiggemann, 2010) and college students (Ghiţă et al., 2021) points to the influence of social media use and the drive for thinness, the evidence in men is less clear. For example, research suggests that adolescent females exhibit higher levels of body surveillance, body shame, appearance anxiety, and drive for thinness than adolescent males. Further, Slater and Tiggemann (2010) reported that while correlations between body surveillance, body shame, appearance anxiety, and drive for thinness were significant in both male and female adolescents, the correlations were significantly stronger in females than in males. Ghiţă et al. (2021) suspected that these gender differences may be the result of time spent on social media, as female college students spend twice the amount of time per day on social media than males. In addition, Hawes, Zimmer-Gembeck, and Campbell (2020) reported that female adolescents and young adults exhibit more preoccupation with appearance-related content on social media as well as maladaptive social media use than male adolescents and young adults. Drawing from Slater and Tiggemann (2010), Ghiţă et al. (2021) found a positive correlation between the drive for thinness and the length of time students spent on Instagram per day in females but not in males. This is not surprising as Watson, Murnen, and College (2019) found that, when exposed to idealized images, collegiate females generated significantly more negative social comparisons than colle- giate men (see also Franzoi et al., 2012). Watson et al. (2019) posited that collegiate men and women may experience sociocultural appearance-related norms differently and, thus, may engage in different cognitive processes when comparing themselves to idealized images. It should be noted, however, that very little research has been conducted on the relationship between social media use and drive for thinness in male samples, particularly concerning social media use.

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One reason research on the drive for thinness and social media in men may be lacking is that most studies of men’s body dissatisfaction focus on the drive for muscularity or, more recently, the drive for leanness. Similar to research on women and the drive for thinness, ev- idence supporting the tripartite model of sociocultural influence has been found in men. Specifically, Tylka (2011) found that media pressure leads to internalization of the mesomorphic ideal, which then leads to both muscularity and body fat dissatisfaction in collegiate men. Furthermore, the existing research on men’s social media use suggests the possibility of a similar mediating role of body shame or surveillance. For example, Schoenenberg and Martin (2020) identified in their sample of exercising men who utilize Instagram that the internalization of beauty ideals perpetuated by the media significantly mediated the relationship between Instagram use and drive for muscularity and muscle dysmorphia symptoms. They highlighted the importance of exposure to the muscular ideal on men’s body image as well as theorized that social media use may act as a maintaining mechanism for men’s body image issues and their clinical correlates. In addition, Piatkowski et al. (2022) found that social media and peer pressure were directly associated with the drive for muscularity in a sample of men who lift weights and take supplements.

Outside of men who lift, some research on the association between social media and the drive for muscularity in men has focused on college student populations. College students tend to more heavily utilize social media (Pew Research Center, 2021) and struggle with body image issues at higher rates than community, non-college-attending populations (De & Chakraborty, 2015; Frederick et al., 2007). Pritchard and Cramblitt (2014) found in their study of 264 college-aged men and women that drive for muscularity was significantly associated with the internaliza- tion of general and athletic media images as well as body comparison. Expanding on these findings, more recent research has identified that in collegiate men, viewing “fitspiration” directly predicted men’s drive for muscularity attitudes as well as muscularity-enhancing behaviors (Seekis, Bradley, & Duffy, 2021). They also identified that the rela- tionship between specific social media activities and drive for muscu- larity attitudes was serially mediated through body surveillance and social physique anxiety. Therefore, these findings indicate the possibil- ity that social media use could predict drive for muscularity in men in a similar fashion as the drive for thinness in women, with body surveil- lance acting as a mediator within this relationship.

1.2.2. Drive for leanness: a novel concept Over the last two decades, researchers have noted a shift within body

ideals for men and women. As knowledge of the negative effects of hyper-thinness and hyper-muscularity grew, researchers began to study an athletic ideal, which proposes that the ideal body is both lean and toned (Thompson, van den Berg, Roehrig, Guarda, & Heinberg, 2004; Watson et al., 2019). Despite initial hopes that this would be associated with less harmful outcomes than previous ideals, research suggests that the lean/athletic ideal also correlates with greater body dissatisfaction (Betz & Ramsey, 2017; Robinson et al., 2017) and disordered eating pathology (Bell, Donovan, & Ramme, 2016).

Compared to research on the drives for thinness and muscularity and social media usage, very little research has been conducted on how so- cial media use relates to the drive for leanness in men and women. In a study of 353 British college students, Tod, Edwards, and Hall (2013) found that the drive for leanness was significantly associated with the internalization of a media-portrayed athletic ideal and perceived pres- sure from the media to attain a lean physique. In research focused exclusively on women, viewing “fitspiration” images on social media has been associated with the drive for thinness, body dissatisfaction (Seekis et al., 2020), and comparison tendencies (Fardouly et al., 2018). Although the literature is growing slowly, the relative lack of studies investigating the relationships between social media usage, its clinical correlates, and drive for leanness needs to be addressed. Thus, the cur- rent literature base may not create a full picture of how social media use,

as well as associated variables such as body shame and surveillance, work together to impact men’s and women’s body image.

1.3. Present study

Research has established a direct association between social media usage and body shame and surveillance in both men and women (Hanna et al., 2017; Manago et al., 2015; Rollero et al., 2018; Salomon& Brown, 2019). However, some research indicates that this relationship may be stronger in women than in men. In addition, research also supports a positive relationship between social media usage and the drive for thinness in women, such that greater social media usage in women has been linked to higher levels of drive for thinness (Ghiţă et al., 2021). Research supports positive associations between body shame and sur- veillance and drive for thinness in men and women (Slater & Tigge- mann, 2010). However, the number of studies that have specifically examined these pathways in women greatly outnumber studies exam- ining these variables in men.

Likewise, relatively little research has examined the relationships between social media usage, body shame and surveillance, and drives that may be more relevant to men’s experiences of body ideals, specif- ically the drive for muscularity and the drive for leanness. Nevertheless, a few studies have pointed to a similar relationship between social media and the drive for muscularity in men. Specifically, men who report greater social media use also report higher levels of drive for muscularity (Piatkowski et al., 2022; Schoenenberg & Martin, 2020). Strikingly, few studies have examined the relationships between social media and drive for leanness. This related but distinct construct implies that ideal bodies are lean, fit, and toned in men. In addition, Smolak and Murnen (2008) reported significant relationships between body shame and surveillance and the drive for leanness in men and women. How- ever, regressions were run separately for men and women, and did not allow for tests of mediated moderation. This represents a significant gap within the literature onmen’s body image. Indeed, the drive for leanness represents a unique and highly influential component of men’s and women’s body image, as bodies that are simultaneously thin and toned (as opposed to just thin) are increasingly idealized in Western cultures for both men and women.

Importantly, while a few studies have examined gender differences in the aforementioned relationships, the majority of these studies have analyzed gender as a covariate/predictor variable in regression ana- lyses, which do not specifically account for the interaction of gender with other predictor variables or examine the effects of the interaction on the dependent variable within these studies (i.e., body shame or surveillance, drives for thinness, leanness, and/or muscularity). In addition, research on gender differences in these relationships tends to utilize traditional regression analyses, which do not account for biases in measurement error or measurement bias between groups and do not provide a detailed account of model fit, making them a less accurate way to identify true differences between groups (Kline, 2023). Thus, to accurately depict gender differences in the relationships between social media usage, body shame and surveillance, and body-image drives, it is important to examine gender’s moderating role within these relation- ships, as well as to account for potential forms of bias in the measure- ment of these constructs between men and women. In other words, research examining gender differences within these relationships would benefit from identifying whether there are true differences between gender groups and ruling out differences due to measurement bias or error.

Accordingly, the present study sought to examine the relationships between social media usage, body shame and surveillance, and drives for leanness, muscularity, and thinness, specifically looking at the moderating role of gender within these relationships. We advanced four hypotheses in relation to our theory-driven model (see Fig. 1 and enumerated below). Specifically, we hypothesized that greater social media usage would positively predict greater drive for leanness, drive

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for muscularity (Piatkowski et al., 2022; Schoenenberg&Martin, 2020), and drive for thinness (Ghiţă et al., 2021) in both men and women and that these relationships would be mediated by body shame and sur- veillance (Seekis et al., 2020; Slater & Tiggemann, 2010). In addition, we predicted that these mediation effects might be conditional on gender, such that the relationships between social media usage and body shame and surveillance would be stronger for women than for men based on the findings of Slater and Tiggemann (2010). In addition, we hypothesized that the relationships between social media, shame, and surveillance and drive for thinness would be stronger for women whereas the relationship between social media, shame, surveillance and drive for muscularity would be stronger for men, based upon research that drive for thinness is more commonly reported by collegiate women (Brown et al., 2020) and drive for muscularity is more commonly re- ported by collegiate men (Edwards, Tod, & Molnar, 2014; Frederick et al., 2007). We made no hypotheses relating to the effect of gender on the relationships between body shame and surveillance and drive for leanness or drive for muscularity, given the limited research in this area for both women and men.

In sum, we hypothesized that (see Fig. 1):

1) Relationships between social media appearance-related preoccupa- tion (Independent Variable; IV) and drive for thinness, drive for leanness, and drive for muscularity (Dependent Variables; DVs) would be mediated both by body shame and body surveillance (Seekis et al., 2020; Slater & Tiggemann, 2010).

2) Gender would moderate the direct associations between social media usage (IV) and body shame and surveillance (mediators), such that these relationships would be stronger for women than for men (Slater & Tiggemann, 2010).

3) Gender would moderate the direct associations between shame and surveillance (mediators) and drive for thinness (DV), such that these relationships would be stronger for women than for men (Brown et al., 2020).

4) The indirect effects of social media appearance-related preoccupa- tion (IV) on the drives for thinness, leanness, and muscularity (DVs) via body shame and surveillance (mediators) will be moderated by gender. Specifically, the indirect effects of social media appearance-

related preoccupation (IV) via body shame and surveillance (medi- ators) on drive for thinness (DV) will be stronger for women. Conversely, the indirect effects of social media appearance-related preoccupation (IV) via body shame and surveillance (mediators) on drive for muscularity (DV) will be stronger for men.

2. Method

2.1. Participants

The initial sample consisted of 1201 undergraduate students from the University of South Alabama and Boise State University. Two hun- dred thirty-five students were removed from the initial sample for failing attention check questions on the survey. In addition, three participants were removed for failure to complete at least 80 % of the survey items. Finally, as the paper focused on gender as the primary variable, we eliminated four Trans, nine non-binary, and nine individuals who preferred not to specify their gender because we did not have enough individuals from any of those gender identities to be able to run our analyses. The final sample for analysis totaled 938 participants (see

Drive for Thinness

Drive for Leanness

Shame

SMARP

Surveillance Drive for Muscularity

Fig. 1. Proposed Model in which the relationships between social media appearance-related preoccupation (SMARP) and drive for thinness, drive for leanness, and drive for muscularity is mediated by body shame and body surveillance.

Table 1 Participant Demographics.

Baseline Characteristic n %

Gender Male 240 25.59 % Female 698 74.41 % Race Caucasian/White 706 73.4 % African American or Black 98 10.2 % Hispanic/Latino/a/x 61 6.4 % Asian 34 3.5 % Multiracial 28 2.9 % Middle Eastern 9 1.0 % Pacific Islander 5 0.5 % Native American or Indigenous Peoples 3 0.2 % Not listed 8 0.7 % Preferred not to say 10 1.1 %

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Table 1 for participant demographic information). Participants ranged in age from 18 to 51 years of age (M = 19.38, SD = 3.09).

2.2. Measures

2.2.1. Social media appearance-related preoccupation The Social Media Appearance-Related Preoccupation scale (SMARP),

a 5-statement scale, was used to assess the degree to which participants engage in negative preoccupation with appearance and comparison on social media (Hawes et al., 2020). Participants rated their agreement with each statement (e.g., “I feel like I want to change my diet after viewing other people’s pictures online.”) on a 7-point Likert-type scale (1 = strongly disagree to 7 = strongly agree). Responses were averaged to create a scale score, with higher scores indicating a greater level of appearance-related preoccupation (α = .92 for women and α = .89 for men).

2.2.2. Objectified body consciousness scale: body shame and body surveillance

We used two of the subscales on the Objectified Body Consciousness Scale (OBCS; McKinley & Hyde, 1996): body shame (e.g., “I feel ashamed of myself when I haven’t made the effort to look my best.”) and body surveillance (e.g., “During the day, I think about how I look many times.”). For both subscales, participants were asked to indicate how much they agreed or disagreed with each statement on a 6-point scale (1 = strongly disagree to 6 = strongly agree; Sinclair, 2010). The body shame subscale consisted of 8 statements assessing the degree to which internalized cultural body standards affect the participants’ perceived self-worth. Responses were averaged to create a scale score, with higher scores indicating a higher level of body shame (α = .86 for women and α = .83 for men). The 8-item body surveillance subscale measured the degree to which participants observed their body through how it looks rather than how it feels. Responses were averaged to create a scale score, with higher scores indicating higher levels of body surveillance (α = .85 for women and α = .84 for men).

2.2.3. Drive for Leanness Scale (DLS) The Drive for Leanness scale (Smolak &Murnen, 2008), a 6-item

scale, was used to assess one’s desire to have relatively low body fat while simultaneously having toned, physically fit muscles (e.g., “I think the best looking bodies are well-toned.”). Items were rated on a scale ranging from 1 (never) to 6 (always). Items were averaged, with a higher score indicating greater levels of drive for leanness (α = .86 for female participants, α = .87 for male participants).

2.2.4. Drive for Muscularity Scale (DMS) The Drive for Muscularity scale measured individuals’ desire to have

greater levels of muscularity (McCreary & Sasse, 2000). The DMS con- tains 15 items (e.g., “I wish that I were more muscular.”) scored on a 6-point Likert-type scale, where 1 = always and 6 = never. Scores were recoded, and then responses were averaged to create a total score (α = .89 for women and α = .88 for men in the present study), with a higher score indicating a greater drive for muscularity.

2.2.5. Drive for Thinness (DFT) subscale The Drive for Thinness scale, a 7-item subscale of the Eating Disorder

Inventory – 3 (Garner, 2004), was used to assess an individual’s pre- occupation with weight and thinness (e.g., “I think about dieting.”). Per the scoring instructions (Garner, 2004), each item was scored using a 6-point scale ranging from always to never. Items were then recoded to a 4-point scale (always =3; never = 0). Positive items were reverse scored, and then all items were averaged to create a scale score (α = .92 for women, α = .86 for men for the current study), with higher scores indicating a greater drive for thinness.

2.3. Procedure

This study was cross-sectional in design. Participants were recruited from Boise State University and the University of South Alabama. Once we received approval from the Institutional Review Board at each institution, participants were recruited using the Sona Systems partici- pant recruitment platform. Students read researcher-provided de- scriptions from various studies and then self-selected to participate in our online survey on the survey-hosting platform (Qualtrics). Partici- pants were told that the purpose of the study was to explore the re- lationships between media and college students’ thoughts and feelings about appearance (body image) constructs. Before completing the sur- vey, students were asked to read an informed consent form and indicate their consent to participate by clicking a button. Students completed the survey on their own time and were assured of the anonymity of their responses. The survey contained several scales, shown in random order to participants. Participants received course credit for their participation.

2.4. Analysis plan

We used multi-group structural equation modeling (SEM) to examine our hypothesized model (see Fig. 1) by testing measurement and structural differences in the model between men and women. Consistent with suggested best practices (Kline, 2023), we first tested a measure- ment model to verify that all of our latent variables were sufficiently represented by their respective manifest indicators for both genders. We then examined our structural model to test our hypothesized direct and indirect effects. In order to determine the significance of the indirect effects (i.e., mediation) of shame and surveillance, we calculated bias-corrected bootstrapped confidence intervals (Shrout & Bolger, 2002).

Given that we examined a potential moderating effect by gender, we additionally tested all of our models for invariance between women and men. Specifically, we tested (a) configural invariance (i.e., determina- tion of whether the model as a whole provided acceptable fit for each group while not imposing any cross-group equality constraints), (b) metric invariance (i.e., testing for equivalence between groups on the factor loading from each manifest variable on its respective latent var- iable), and (c) direct-effects invariance (i.e., determination of equiva- lency between groups on the direct and indirect effects). These forms of invariance between groups are necessary for moderation in SEM (Kline, 2023). Additionally, invariance testing is a hierarchal process in which configural invariance is a necessary prerequisite for examining metric invariance, which is a precondition for examining direct-effects invari- ance. If significant differences in the strength of the associations (i.e., indirect and direct effects) are found, then moderation is supported (Kline, 2023). Moreover, measurement and structural invariance tests are a more rigorous approach compared to traditional regression by (a) reducing the biasing effects of measurement error, (b) ensuring that any evidence of moderation is not due to measurement bias favoring or disadvantaging one group, and (c) providing a detailed and nuanced picture of model fit.

For all of our models, we used the following recommended cutoff and fit indices (Hu & Bentler, 1999; Kline, 2023) to evaluate each model: Comparative Fit Index (CFI) and the Tucker Lewis Index (TLI) (where values close to.95 are indicative of a good fit for both CFI and TLI); the Root Mean Square Error of Approximation (RMSEA) with 90 % confi- dence intervals [CI] (where low values.06 and high values less than.10 are indicative of a good fit), and the Standardized Root-Mean-square Residual (SRMR; where values less than.08 are indicative of a good fit). We also reported the chi-square test statistic (where a non-significant value is indicative of a perfect fit to the data). However, we interpreted the chi-square test statistic with caution due to its sensitivity to sample size (Kline, 2023).

To evaluate our measurement invariance in our models, we used a

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nested model approach in which a more parsimonious model (i.e., a model with cross-group equality constraints imposed) is compared against a less parsimonious model (i.e., a model without cross-group equality constraints). Specifically, we used a scaled chi-square differ- ence test, where a significant increase indicated that the more parsi- monious model was a worse fit to the data. However, chi-square difference tests are extremely sensitive to sample size (Kline, 2023). Therefore, we interpreted the chi-square difference test with caution.

To evaluate the invariance of the direct and indirect effects, we used a direct model approach and calculated the bias-corrected bootstrapped confidence intervals (CIs) of the between-groups difference on the paths in question (i.e., direct and indirect effects; Cheung & Lau, 2012). Within this approach, a 99 % CI of the between-group difference that does not contain zero indicates a statistically significant difference be- tween groups on the comparison of interest.

3. Results

3.1. Preliminary analyses

Prior to conducting our primary analyses, we screened our data for missingness, univariate outliers, and assumptions of normality. Miss- ingness values for all measures of interest were below 2 % and are considered to meet the assumption of at least missing at random (Meyers, Gamst, & Guarino, 2017). For the SMARP, OBCS Surveillance subscale, OBCS Shame subscale, DFT, and DLS, there were no univariate outliers (i.e., z-scores greater than the absolute value of three). For the DMS, there was only one univariate outlier that was kept for analyses due to being less than 2 % of the sample (Meyers et al., 2017). For women, surveillance and SMARP were moderately negatively skewed (i. e., approaching but not exceeding one), whereas for men, only DT was moderately positively skewed. The other measures were normally skewed (i.e., below the absolute value of 0.5) for women andmen. Given the departures from normality and the size of our sample, we used a full information likelihood estimator with robust standard errors for model fit. Lastly, due to our high bivariate correlations, we examined our variables for multicollinearity. Specifically, we examined tolerance and variable inflation factor (VIF) in regression models with our predictor variables (i.e., SMARP, shame, and surveillance) and one dependent variable (i.e., drives for thinness, leanness, and muscularity) by gender. All of our tolerances were above 0.1, and our VIFs were below 2.50, indicating minimal multicollinearity (Meyers et al., 2017). See Table 2 for our results.

3.2. Primary Analyses

3.2.1. Measurement Model First, we formed our measurement model using three parcels for all

of our selected instruments to create the latent variables of the

constructs of interest (i.e., social media appearance-related preoccupa- tion, body shame, body surveillance, drive for thinness, drive for muscularity, and drive for leanness). In order to generate our parcels, we used a factorial parceling procedure (Little, Cunningham, Shahar, & Widaman, 2002; cf., Matsunaga, 2008), where we conducted unidi- mensional exploratory factor analyses of each instrument. High and low items were then iteratively assigned to one of the three parcels to form the latent variables.

Our measurement models evidenced acceptable fit for women (n = 698) χ2 (120) = 307.908, p < .001 (CFI =.977, TLI =.970, RMSEA =.047 [90 % CI=.041,.054], SRMR=.033), and men (n = 240) χ2 (120) = 267.270, p < .001 (CFI =.939, TLI =.923, RMSEA =.072 [90 % CI =.060,.083], SRMR =.057). Moreover, our configural pooled CFA, where all paths were freely estimated between women and men, also evidenced an acceptable fit (n = 938) χ2 (240) = 576.9111, p < .001 (CFI =.969, TLI =.960, RMSEA =.055 [90 % CI =.049,.060], SRMR =.041). Thus, the latent factors were evidenced to adequately represent the variation of their respective items across women and men. See Ta- bles 3 and 4 for the correlations and factor loadings of the measurement model. For women, all correlations were positive and statistically sig- nificant. For men, the association between drive for muscularity and drive for thinness was negative and statistically non-significant, whereas all of the other associations were positive and statistically significant.

3.2.2. Measurement Invariance In accordance with best practices in SEM (Kline, 2023) and with

evidence for configural invariance, we continued the hierarchical invariance testing process. Specifically, we needed evidence for at least metric invariance (i.e., the same construct is being measured between groups by constraining factor loadings to be the same) in order to make meaningful comparisons and to evaluate the possibilities of moderation and moderated mediation. Our results indicated support for metric invariance with acceptable fit indices: (n = 938) χ2 (252) = 596.796, p < .001 (CFI =.968, TLI =.961, RMSEA =.054 [90 % CI =.048,.060], SRMR=.042). Furthermore, our scaled chi-square test indicated that the metric model was a better fit to the data than the configural model, Difference Test Scaling Correction = 1.13, Sattora-Bentler Scaled χ2

difference = 20.15, Δ χ2 degrees of freedom = 12, p = .0642.

3.2.3. Structural Model Direct Effects and Direct Effects Invariance Table 5 displays our direct paths and moderation tests of direct ef-

fects. For women, the direct paths from shame to drive for thinness, surveillance to drive for thinness, surveillance to drive for leanness, shame to drive for muscularity, SMARP to shame, and SMARP to sur- veillance were all positively and statistically significantly related. For men, the direct paths from shame to drive for thinness, SMARP to drive for thinness, surveillance to drive for leanness, surveillance to drive for muscularity, SMARP to shame, and SMARP to surveillance were all positively and statistically significantly related. Additionally, for men,

SMARP to drive for leanness and SMARP to drive for muscularity were significantly but negatively associated. Using bias-corrected boot- strapped confidence intervals (CIs; 1000 iterations), we tested the between-group differences on the paths in question (i.e., moderation). See Table 4 for our results. Our results indicated that moderation was supported for surveillance to drive for muscularity, SMARP to drive for thinness, SMARP to drive for leanness, and SMARP to drive for muscu- larity. The relationships between surveillance to drive for muscularity and SMARP to drive for thinness were stronger for men, whereas the relationships between SMARP to drive for leanness and SMARP to drive for muscularity were positive for but not significant for women and negative and significant for men.

3.2.4. Structural Model Indirect Effects and Indirect Effects Invariance Additionally, we used bias-corrected bootstrapped CIs to evaluate

our indirect paths (i.e., mediation). See Table 6 for our results. Our re- sults indicated several significant indirect paths; specifically, shame was

Table 2 Multicollinearity Results.

Model Tolerance VIF

Drive for Thinness SMARP 0.43 (0.56) 2.31 (1.78) Shame 0.47 (0.59) 2.13 (1.69) Surveillance 0.49 (0.63) 2.05 (1.58) Drive for Leanness SMARP 0.43 (0.56) 2.31 (1.78) Shame 0.47 (0.59) 2.13 (1.69) Surveillance 0.49 (0.63) 2.05 (1.58) Drive for Muscularity SMARP 0.43 (0.56) 2.31 (1.78) Shame 0.47 (0.59) 2.13 (1.69) Surveillance 0.49 (0.63) 2.05 (1.58)

Note. Women’s results are not in parentheses and men’s results are within parentheses.

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a significant mediator of the association between SMARP and drive for thinness for women, B = .414, 99 % CI = [.308,.521], and men, B = .211, 99 % CI = [.072,.399]. Surveillance was a significant mediator of the association between SMARP and drive for leanness for women, B = .113, 99 % CI = [.027,.205], and men, B = .210, 99 % CI = [.089,.386]. Lastly, with regard to drive for muscularity and SMARP, surveillance was a significant mediator for men, B = .182, 99 % CI = [.024,.391], but not for women, B = .009, 99 % CI = [− .094,.104]. We again used bias-corrected bootstrapped CIs (1000 iterations) to test the between-group differences on the mediations (i.e., moderated- mediation). Table 5 contains all of our results, which supported moderated mediation for SMARP → Shame → drive for thinness where the effects were stronger for women.

4. Discussion

Social media usage has become ubiquitous among emerging adults (Pew Research Center, 2021). While social media use does offer poten- tial for positive outcomes (e.g., connection, finding interests; Anderson & Jiang, 2018; Seabrook, Kern, & Rickard, 2016), due, in part, to exposure to and internalization of appearance norms presented online

researchers have also found associations with various risks and negative outcomes such as body dissatisfaction, shame, and surveillance (Andrew et al., 2016; Garcia et al., 2022; Hanna et al., 2017; Legkauskas & Kudlaitė, 2022; Morrison et al., 2004; Stein et al., 2019; Thompson et al., 1999; Tiggemann, 2011; Tylka, 2011). When examining these associa- tions, researchers have predominantly focused on women’s social media use and its associations with body dissatisfaction, thus leaving several questions about the generalizability of these findings in male pop- ulations unanswered. To address these issues, the present study tested the relationships between social media usage, body shame and surveil- lance, and drives for leanness, muscularity, and thinness, specifically looking at the moderating role of gender within these relationships. Our results partially supported four hypotheses.

4.1. Hypothesis 1

Based on previous research (Seekis et al., 2020; Slater & Tiggemann, 2010), we expected that body shame and body surveillance would mediate the relationships between social media appearance-related preoccupation and the three drives (thinness, leanness, and muscu- larity) in male and female college students. This hypothesis was partially supported. As expected, body shame mediated the relationship between SMARP and drive for thinness in collegiate women and men, but not the relationships between SMARP and drive for leanness or drive for muscularity. Our results align with Schettino et al.’s (2023) findings in male and female college-aged individuals that appearance-based com- parison on social media is correlated with body shame and the subse- quent internalization of beauty ideals presented in the media. Similarly, Martins et al. (2007) found that body shame mediated the relationship between self-objectification (typically based on comparison to media images) and the drive for thinness in gay men. The lack of a significant relationship between body shame and the drive for muscularity in our research likewise supports similar findings by Smolak and Murnen (2011), Keum et al. (2022), and Parent and Moradi (2011), all of whom found no significant relationship between these constructs in men.

Body surveillance mediated the association between SMARP and drive for leanness for women and men. This is a novel finding but is consistent with previous research that found body surveillance pre- dicted drive for leanness in male and female college students (Smolak & Murnen, 2008). Finally, body surveillance significantly mediated the relationship between SMARP and drive for muscularity in men but not for women. Although previous research supported the relationship be- tween SMARP and the drive for muscularity (Seekis et al., 2021), the mediation for men but not women was surprising. Contrary to our findings, for example, Xiaojing (2017) reported that body surveillance mediated the relationship between social media use and body dissatis- faction, a construct often correlated with drive for muscularity (Bergeron & Tylka, 2007), in female adolescents but not in male ado- lescents; we found the opposite to be true. Given that research

Table 3 Correlations in the Measurement Model.

Variable 1 2 3 4 5 6

1. SMARP – .77 * ** (.68 ***) .75 * ** (.62 ***) .72 * ** (.56 ***) .30 * * (.18 *) .18 * ** (.21 **) 2. Shame – .73 * ** (.61 ***) .86 * ** (.64 ***) .29 * ** (.18 *) .21 * ** (.22 **) 3. Surveillance – .71 * ** (.38 ***) .36 * ** (.49 ***) .18 * ** (.45 ***) 4. DT – .37 * ** (.18 *) .18 * ** (− .02) 5. DL – .60 * ** (.49 ***) 6. DM – Mean 4.55 3.40 4.07 3.45 3.69 2.48

(3.45) (3.05) (3.64) (2.66) (4.08) (3.44) SD 1.64 1.14 .97 1.36 .99 .89

(1.58) (1.05) (.97) 1.13 (.99) (.95)

Notes. Men’s values are in parentheses; SMARP = social media appearance-related preoccupation, DT = drive for thinness, DL = drive for leanness, DM = drive for muscularity. Means and Standard Deviations (SD) are for raw (non-latent) variables, and correlations represent relationships between latent variables. * p < .05, * * p < .01, * ** p < .001.

Table 4 Factor Loadings in the Measurement Model.

Scale and Parcel B SEB ß p

SMARP Parcel 1 — — .93 (.91) < .001 (<.001) Parcel 2 .98 (.97) .03 (.06) .91 (.89) < .001 (<.001) Parcel 3 .97 (.99) .03 (.07) .83 (.76) < .001 (<.001) Shame Parcel 1 — — .88 (.90) < .001 (<.001) Parcel 2 .96 (1.01) .04 (.06) .76 (.74) < .001 (<.001) Parcel 3 1.24 (1.04) .04 (.09) .84 (.79) < .001 (<.001) Surveillance Parcel 1 — — .82 (.79) < .001 (<.001) Parcel 2 1.12 (1.13) .05 (.09) .79 (.81) < .001 (<.001) Parcel 3 1.09 (1.07) .05 (.10) .84 (.82) < .001 (<.001) DT Parcel 1 — — .90 (.86) < .001 (<.001) Parcel 2 1.06 (.87) .03 (.07) .89 (.76) < .001 (<.001) Parcel 3 1.12 (.89) .03 (.08) .89 (.83) < .001 (<.001) DM Parcel 1 — — .98 (.93) < .001 (<.001) Parcel 2 .92 (1.07) .03 (.06) .85 (.85) < .001 (<.001) Parcel 3 .87 (.93) .03 (.07) .78 (.77) < .001 (<.001) DL Parcel 1 — — .77 (.80) < .001 (<.001) Parcel 2 .97 (1.07) .04 (.06) .76 (.81) < .001 (<.001) Parcel 3 1.12 (.93) .06 (.07) .87 (.88) < .001 (<.001)

Note. SMARP = social media appearance-related preoccupation, DT = drive for thinness, DL = drive for leanness, DM = drive for muscularity, men are repre- sented in parentheses, first parcel was used to identify the latent variable.

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examining the relationships between social media use, body surveil- lance, and drive for muscularity is relatively sparse, more work in this area is needed to better elucidate the role of gender within these relationships.

4.2. Hypothesis 2

Hypothesis two predicted that gender would moderate the direct associations between social media usage and body shame and surveil- lance, such that these relationships would be stronger for women than for men. This hypothesis was not supported; men and women evidenced statistically significant and equivalent relationships between these constructs. Our findings are inconsistent with previous research that

social media may be associated with greater body shame and surveil- lance in women than in men (Manago et al., 2015; Rollero et al., 2018; Salomon & Brown, 2019). Instead, our findings align with more recent research (Boursier& Gioia, 2022), which supports the significant role of body shame and self-objectification in perpetuating men’s appearance concerns and body esteem. Taken together, our findings suggest that body shame and surveillance may be becoming increasingly relevant to men’s appearance concerns, as men’s use of social media, as well as their use of image-oriented social media (i.e., Instagram, TikTok, Snapchat), has increased (Ortiz-Ospina, 2017). In addition, as social media algo- rithms become more complex, content becomes more “rabbit-holed,” thereby potentially increasing exposure to media-perpetuating appear- ance ideals in users of all genders who are more vulnerable to the deleterious effects of viewing such images (Harriger, Evans, Thompson, & Tylka, 2022). Outside of changes in social media usage, these findings could also point to a larger shift in sociocultural shifts in body accep- tance and diversity. The body acceptance movement often promoted on social media narratives, while a potential factor in the reduction of women’s body dissatisfaction over time (Karazsia et al., 2017), has been predominantly aimed at girls and women. Given that homogenous, rigid body norms are more harmful to body image than heterogenous, flexible norms (Buote et al., 2011), it is possible that the body acceptance movement is acting as a protective factor for women’s body image, but not men’s.

4.3. Hypothesis 3

In line with the existing literature (Brown et al., 2020), we predicted that gender would moderate the direct associations between shame, surveillance, and drive for thinness, such that these relationships would be stronger for women than for men. This hypothesis was partially supported. Our results suggested that while body shame was positively related to drive for thinness, gender did not moderate this relationship. Moreover, body surveillance was positively related to the drive for thinness in women but not men, yet the moderation analyses revealed no significant conditional effect by gender on these pathways. The fact that gender did not significantly moderate the association between body surveillance and drive for thinness indicates that the difference in the p-value of this pathway between men and women may have more to do with the precision (i.e., the amount of error in the prediction equation)

Table 5 Direct Paths and Moderation tests of Direct Effects for Women and Men.

Direct Path B SEB ß p Bootstrapped Difference Estimate and 99 % CIs (Moderation)

SMARP → Shame .485 (.381) .022 (.033)

.768 (.703)

< .001 (<.001) .104 [− .005,.198]

SMARP →Surveillance .400 (.338) .024 (.046) .750 (.678)

< .001 (<.001) .062 [− .092,.189]

SMARP → DT .063 (.357) .042 (.071) .082 (.475)

.131 (<.001)

-.294 [¡ .542, ¡ .106]

SMARP → DL .035 (¡.225)

.045 (.067) .698 (¡.465)

.435 (.001) .260 [.065,.478]

SMARP → DM .013 (¡.431)

.054 (.083) .022 (¡.602)

.804 (<.001)

.444 [.191,.728]

Shame → DT .853 (.554) .074 (.157) .698 (.400)

< .001 (<.001) .299 [− .209,.755]

Shame → DL .027 (− .018)

.067 (.126) .032 (− .020)

.683 (.887) .045 [− .328,.404]

Shame → DM .159 (.189) .076 (.178) .167 (.144)

.037 (.287) -.030 [− .574,.433]

Surveillance → DT .200 (− .149)

.080 (.140) .139 (− .099)

.012 (.289) .349 [− .058,.765]

Surveillance → DL .281 (.621) .079 (.135) .276 (.640)

< .001 (<.001) -.339 [− .803,.032]

Surveillance → DM .022 (.537) .092 (.182) .020 (.375)

.811 (<.001)

-.515 [¡ 1.066, ¡ .006]

Note. SMARP = social media appearance-related preoccupation, DT = drive for thinness, DL = drive for leanness, DM = drive for muscularity, men are represented in parentheses, significant results are bolded, and comparisons were made such that it was women minus men, therefore positive results indicate stronger associations for women and negative results indicate stronger associations for men.

Table 6 Indirect Paths and Moderated-Mediation tests of Indirect Effects for Women and Men.

Indirect Path B 99 % CIs Bootstrapped Difference Estimate and 99 % CIs (Moderated-Mediation)

SMARP → Shame → DT

.414 (.211)

[.308,.521] ([.072,.399])

.202 [.004,.387]

SMARP→ Shame → DL

.013 (− .007)

[− .067,.090] ([− .134,.114])

.020 [− .122,.176]

SMARP → Shame → DM

.077 (.072)

[− .019,.170] ([− .096,.255])

.005 [− .210,.197]

SMARP → Surveillance → DT

.080 (− .050)

[− .008,.154] ([− .187,.074])

.131 [− .015,.296]

SMARP → Surveillance → DL

.113 (.210)

[.027,.205] ([.089,.386])

-.097 [− .301,.051]

SMARP → Surveillance → DM

.009 (.182)

[− .094,.104] ([.024,.391])

-.173 [− .388,.004]

Note. SMARP = social media appearance-related preoccupation, DT = drive for thinness, DL = drive for leanness, DM = drive for muscularity, men are repre- sented in parentheses, significant results are bolded, and comparisons were made such that it was women minus men, therefore positive results indicate stronger associations for women and negative results indicate stronger associ- ations for men.

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than a difference in the magnitude of the relationship between these constructs. Thus, although the regression coefficients were statistically similar in magnitude between men and women, the lower standard error in the regression equation for women likely explains why the p-value was below.05. By contrast, the relationship between body surveillance and drive for muscularity was conditional upon gender, such that this relationship was stronger for men. Finally, gender did not moderate the relationships between shame and surveillance and drive for leanness.

The significant associations between body shame and drive for thinness, as well as the non-significant relationships between body shame and other drives found in the present study and prior research (Keum et al., 2022; Parent & Moradi, 2011), may be representative of the correlations between weight stigma and body shame in both men and women (Bidstrup, Brennan, Kaufmann, & De La Piedad Garcia, 2022). Indeed, in an obesophobic culture, it may be the case that feelings of body-related shame may be more strongly associated with concerns of thinness compared to muscularity or leanness. Conversely, body sur- veillance appears to be more related to muscularity and thinness as gendered body ideals, such that greater body surveillance predicted the drive for thinness in women but not men and more strongly predicted the drive for muscularity in men than in women. While limited research has explored these relationships differentially in men and women, this is consistent with theory, suggesting that the muscular ideal is more relevant for men than women (Karazsia et al., 2017; Oehlhof, Musher-Eizenman, Neufeld, & Hauser, 2009) and expands on findings from Seekis et al. (2021), who identified body surveillance as a mediator between social media usage and drive for muscularity. The importance of gendered body ideals when considering the relationship between body surveillance and internalization of appearance ideals may also work to explain the discrepancy in the literature, which is largely divided on the relative role of body surveillance in predicting men’s body image disturbance as compared to women’s. Specifically, our findings align with research suggesting that body surveillance may be more relevant to men’s drive for muscularity and women’s drive for thinness (Skowronski et al., 2022).

4.4. Hypothesis 4

With regard to hypothesis four (i.e., indirect effects will be moder- ated by gender), our hypothesis was partially supported. First, exam- ining the indirect effects (i.e., mediation), our results indicated that shame mediated the relationship between SMARP and drive for thin- ness, and surveillance mediated the relationship between SMARP and drive for leanness. These mediations were significant for women and men and were in the positive direction. Surveillance also mediated the relationship between SMARP and drive for muscularity but only for men, and this mediation was in the positive direction. Notably, our bivariate correlations, direct effects, and indirect effects results indicated a sup- pression effect for men with regard to the associations between SMARP, surveillance, and drive for muscularity and the associations between SMARP, surveillance, and drive for leanness. Specifically, at the bivar- iate level (where there are no covariates), these variables were moder- ately to strongly positively correlated. When examining the direct effects (where other variables are in the model and they are controlling for each other), the SMARP → drive for muscularity and SMARP → drive for leanness relationship became negative. However, as surveillance was entered as a mediator, these paths became positive.

One tentative theoretical explanation for these suppression effects is that body surveillance is necessary to clarify the relationship between SMARP and maladaptive outcomes (i.e., increased drives for leanness and muscularity). Said another way, for men, social media appearance- related preoccupation is not necessarily associated with increased drives for leanness and muscularity unless men are also engaging in body surveillance. Interestingly, the suppression effect did not exist for the women in our sample, and this may indicate that men have some level of protection against the direct impacts of engaging with social media

compared to women. Indeed, the cultural objectification of women’s bodies has led women to have historically been subjected to appearance- related pressures through various forms of media at higher levels than men (Conley & Ramsey, 2011; Hatton & Trautner, 2022). Thus, since men (until more recently) have experienced less pressure about their appearances through media, it may take time for a more direct associ- ation to appear. Additionally, researchers have noted gendered differ- ences in social media experiences (Ghiţă et al. 2021; Hawes et al. 2020) that may partially explain the possible protective factor(s) for men in the present study. For example, female college students have been found to spend twice as long on social media than men, and as length of time on social media has been found to predict drive for thinness in collegiate women (Ghita et al., 2021), it is possible that time spent on social media may be a potential moderator of this relationship. Nevertheless, it is important to remember that interpretation of suppression effects is extremely difficult and often sample-specific and speculative (Kline, 2023; Tu, Gunnell, & Gilthorpe, 2008). Thus, our interpretation of the present results should be considered with caution.

In addition to a possible suppression effect, we found evidence for moderated mediation in the SMARP → Shame → DT path. Specifically, this association was positive and statistically significant for both genders but stronger for women than men. This is consistent with previous findings and theories that shame is, on average, a more salient variable for women than men when examining body dissatisfaction-related ex- periences (Fredrickson & Roberts, 1997; Hanna et al., 2017; Manago et al., 2015; Rollero et al., 2018; Salomon& Brown, 2019). Surprisingly, our results did not support moderatedmediation in the SMARP → Shame → DM or SMARP → Surveillance → DM paths. However, the result for the SMARP → Surveillance → DM relationship trended toward signifi- cance. Furthermore, it trended in the expected direction that the asso- ciations were stronger for men than women. It may be the case that we were unable to find significance in this path due to our sample being predominantly composed of women. Future researchers should consider continuing to examine potential gender differences in this and similar models with larger samples of men.

4.5. Limitations and future directions

As with any study, our study is not without limitations. First, we cannot make causal inferences because our study was cross-sectional. While our model was theoretically driven, future researchers should consider examining longitudinal designs to tease apart causality and directionality. A number of alternative models should be examined. For example, it may be the case that there is a positive feedback loop among our variables that creates a negative spiral for individuals struggling with body dissatisfaction and engaging in social media use. Second, we used a convenience sample from two university SONA participant pools. Participants can choose what studies to participate in for credit, and there may be a selection bias. Third, the two universities were in different geographical locations (i.e., Mountain West and Gulf Coast), possibly increasing our results’ generalizability, but it may also create heterogeneity in the sample that may have influenced the results. The sample size was not sufficient to examine our model for differences between gender and sample location. Fourth, our participants were predominantly White and identified as women. Thus, our study would benefit from replications with diverse samples to support and generalize our results further or potentially identify cultural and regional nuances. Fifth, our sample included some outliers based on age. We chose to include these participants as they are also college students; the number of individuals was small (i.e., less than 2 %), and it likely did not in- fluence our results (Meyers et al., 2017). However, their experiences and social media use are likely different from that of traditional-aged college students. As such, future researchers should consider examining age cohorts as body dissatisfaction can exist across the lifespan (Hockey, Milojev, Sibley, Donovan, & Barlow, 2021).

Sixth, because our sample was predominately cisgender, we

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excluded transgender and other gender minorities. Future researchers should replicate our study with larger samples of individuals who identify as a minoritized gender. Their experiences with body dissatis- faction are likely to be different and compounded by additional factors (e.g., are they transitioning, do their physical features align with how they identify; McGuire et al., 2016). It may also be the case that these individuals are engaging with social media in a different way (e.g., viewing different material, seeking community and affirmation) that may increase or buffer them against body dissatisfaction and risk (Buss et al., 2022; Selkie et al., 2020). Lastly, our study was quantitative by design, and future researchers should consider qualitative and mixed- method approaches. These approaches can help the field to better un- derstand people’s experiences with and reasons for engaging in social media use. Relatedly, because we employed a quantitative design, we relied on self-report measures with inherent limitations. Most notably, for the present model, shame and drive for thinness were highly related to the point where those latent variables may represent different aspects of the same construct. Variance decomposition approaches such as bifactor modeling (see Rodriguez, Reise, & Haviland, 2016 for a review) may be necessary to specify the present model in future research.

4.6. Clinical/practical implications

Despite some limitations, our findings may help inform approaches to assess and treat body dissatisfaction in men and women. Social media is here to stay and will likely play a bigger role in individuals’ lived experiences as cohorts that will have had access to continually expanding social media platforms at younger and younger ages transi- tion to college (Vogels, Gelles-Watnick, & Massarat, 2022). Indeed, re- searchers have become increasingly concerned about the potential negative impacts of social media, especially related to body dissatis- faction (Andrew et al., 2016; Legkauskas & Kudlaitė, 2022; Stein et al., 2019). However, to our knowledge, no evidence-based or evidence-supported clinical treatments explicitly assess or treat the role that social media may play as a risk and/or maintaining factor of body dissatisfaction. Based upon our results and those of previous researchers (Andrew et al., 2016; Legkauskas & Kudlaitė, 2022; Stein et al., 2019), we argue that clinicians should commonly assess and evaluate their clients’ social media use, especially when body dissatisfaction concerns are present, regardless of gender. Our results also indicate that there may be nuanced differences based on their clients’ gender that clinicians should be aware of to inform their clinical decision-making. For example, endorsing higher levels of body surveillance may be a risk factor for drive for thinness in women and drive for muscularity in men. As such, clinicians may find it helpful to assess and target body sur- veillance in treatment for women presenting with a high drive for thinness or restrictive eating behaviors, as well as in men presenting with an elevated drive for muscularity or muscle dysmorphia symptoms. Targeting body surveillance in men presenting with elevated body image concerns may be especially important, given that our research supports this construct as an important predictor of increased drive for leanness and drive for muscularity in men. In addition, given that we found that body shame may be more related to the drive for thinness than other appearance-related drives, in treatment-presenting in- dividuals with a high drive for thinness, it may be important to explore feelings of shame, core beliefs centered around not being “good enough” (as alluded to on the OBCS: Body Shame subscale), as well as the direct association between these thoughts and feelings and one’s appearance. Again, targeting body shame within a treatment context may be espe- cially important for women based on our findings that the moderated-mediation pathway from SMARP to Shame to Drive for Thinness was stronger in women than in men.

With regard to direct intervention, social media likely plays a role in the development and reinforcement of maladaptive and distorted beliefs (e.g., unrealistic standards of beauty and attraction), increasing social comparisons, and additional impacts that have yet to be identified and

require continued research. Cognitive behavioral therapy (CBT) is an evidence-based approach to treating body dissatisfaction and eating disorders (Cassone, Lewis, & Crisp, 2016; Linardon, 2018). CBT commonly focuses on challenging maladaptive beliefs and developing more adaptive and balanced beliefs (Beck, 2011). These approaches within CBT can be readily adapted and applied to experiences specific to social media use and body dissatisfaction, along with challenging social comparisons. In addition to CBT, depending on the client, it may also be appropriate to consider family therapy, another evidence-based approach for treating body dissatisfaction and eating pathology (Ke En Gan, Xi Wu, Chow, Kuang Yeung Chan, & Klainin-Yobas, 2022). Within family therapy specifically, sessions could be dedicated to not only counter messages from the media but also garner support from the family to help address maladaptive social media use (e.g., access to so- cial media, regulation of social media content/usage, psychoeducation on risks of social media). As researchers and clinicians continue to develop treatments for body dissatisfaction, they should develop and incorporate interventions related to social media and evaluate their efficacy.

Our results also carry implications for university and college coun- seling centers (UCCCs) and the larger collegiate and university systems. Social media use and body dissatisfaction are common across campuses (De & Chakraborty, 2015; Frederick et al., 2007; Pew Research Center, 2021). UCCCs and collegiate administration have the opportunity to develop and implement macro-level interventions, such as outreach, that can serve as prevention and intervention for body dissatisfaction. Indeed, UCCCs and different departments across campuses commonly implement body positivity programming, healthy eating programming, and others (e.g., The Body Project). Given that these entities are already doing this work, they can develop psychoeducational workshops or outreach events that address the roles social media may play in body dissatisfaction. For example, they could consider providing psycho- education on how images are commonly altered through filters on social media platforms, the risks of social media, and ways to connect with the campus community outside of the use of social media.

5. Conclusion

Our study contributes to our understanding of the relationships be- tween social media appearance-related preoccupation, self- objectification, and body image (drive for thinness, leanness, and muscularity) in a sample of college student women and men. Our results support general similarities between women and men that body shame and surveillance do mediate the relationships between SMARP and the drives of body image. Indeed, our second hypothesis was not supported in which we predicted that gender would moderate the direct associa- tions such that the relationships were stronger for women than men. However, our results became more nuanced and varied by gender when examining the indirect paths and which drives (i.e., thinness, leanness, and muscularity). We also found a suppression effect for men only in that at the bivariate level SMARP, surveillance, and drive for muscu- larity and SMARP, surveillance, and drive for leanness were moderately positively correlated. At the direct effects level, the associations between SMARP and drive for muscularity and SMARP and drive for leanness became negative. Once surveillance was entered as a mediator, these associations became positive again. explanation that, for men, social media-related preoccupation is not necessarily correlated with increased drives for leanness and muscularity unless men are also engaging in surveillance. However, this interpretation is tentative and warrants further evaluation.

Social media usage is on the rise and a common fixture within college students’ lives (Pew Research Center, 2021). Previous researchers have indicated the risks of social media use and body dissatisfaction (Andrew et al., 2016; Legkauskas & Kudlaitė, 2022; Stein et al., 2019). However, researchers have predominantly focused on women and the drive for thinness. Our study expands upon previous researchers’ work by

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including and examining men’s experiences and including drives for muscularity and leanness. Our study also helps to clarify these re- lationships by incorporating shame and surveillance from self-objectification theory. By understanding the impacts of social media and examining risk factors (i.e., shame and surveillance), clinicians and campus communities can develop programs and interventions to address and mitigate the potential impacts of social media usage.

Funding statement

Research reported in this publication was not funded.

Author contributions

All authors agree to be accountable for ensuring the integrity and accuracy of this work.

Data registration

This study was not preregistered. Data is available upon request.

AI Statement

No AI tools were used for any portion of this study.

Authorship statement

I am the lead author on this submission. To the best of our knowl- edge, our authorship team has adhered to all editorial policies for sub- mission as outlined by the Body Image. Additionally, we attest that all authors have contributed (as noted in the manuscript data) in mean- ingful ways that meet the criteria for authorship. Lastly, we have sub- mitted our conflict of interest statements and other statements requested and required by the journal.

CRediT authorship contribution statement

Ryon C. McDermott:Writing – review & editing, Writing – original draft, Methodology, Formal analysis, Data curation, Conceptualization. Callie E. Mims: Writing – review & editing, Writing – original draft, Methodology, Conceptualization. Mary E. Pritchard: Writing – review & editing, Writing – original draft, Methodology, Formal analysis, Data curation, Conceptualization.KyleM. Brasil:Writing – review& editing, Writing – original draft, Methodology, Formal analysis, Data curation, Conceptualization.

Declaration of Competing Interest

All authors declare that there are no interests that may influence or bias this study. Additionally, this study was not funded.

Data Availability

Data will be made available on request.

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