Effects of thin-ideal instagram images: The roles of appearance comparisons, internalization of the thin ideal and critical media processing

Body Image 31 (2019) 181–190

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Effects of thin-ideal instagram images: The roles of appearance comparisons, internalization of the thin ideal and critical media processing Fay Anixiadis a , Eleanor H. Wertheim a,∗ , Rachel Rodgers a,b,c , Brigitte Caruana a a

School of Psychology and Public Health, La Trobe University, Bundoora (Melbourne), VIC, Australia APPEAR, Department of Applied Psychology, Northeastern University, Boston, MA, USA c Department of Psychiatric Emergency & Acute Care, Lapeyronie Hospital, CHRU, Montpellier, France b

a r t i c l e

i n f o

Article history: Received 3 May 2019 Received in revised form 8 October 2019 Accepted 8 October 2019 Keywords: Body dissatisfaction Appearance comparison Body image Instagram Thin-ideal media literacy Social media

a b s t r a c t Recent research has pointed to potential negative effects on young women of using social networking sites. We examined whether exposure to thin-idealised images of users’ bodies, typical of those posted on Instagram, would result in changes in state mood and body dissatisfaction. We further examined women’s reported thoughts when viewing such images to explore qualitatively their cognitive experiences. Female participants (N = 126) reported on trait body dissatisfaction and body comparison, and state body dissatisfaction and mood, and were randomly assigned to view and describe their thoughts about either images depicting the Western thin-ideal or control images (scenery). The control sample increased mood and decreased body dissatisfaction more than thin-ideal participants following exposure, with only marginal moderating effects of trait appearance comparison and internalization of the thin-ideal. In a sample that viewed the thin-ideal images (n = 91) upward body comparison thoughts and positive thoughts related to the bodies depicted were associated with negative mood changes. Media awareness and literacy thoughts were not protective; however, thoughts unrelated to the thin-ideal bodies were protective. Findings suggest that while young women appeared largely resilient to short-term exposure to Instagram images of thin-idealized peers, a subset of women appeared to be at risk. © 2019 Elsevier Ltd. All rights reserved.

1. Introduction Most contemporary young women in Western societies engage with social media (Perrin, 2015), and increasing evidence suggests that due to predominant featuring of stereotypically attractive individuals, exposure to social media is associated with body image and eating concerns (Fardouly & Vartanian, 2016; Rodgers & Melioli, 2016). Research examining the mechanisms accounting for the effects of exposure to traditional media (e.g., magazines) on body image has highlighted the role of factors that increase vulnerability such as internalization of appearance ideals and appearance comparison processes (Dittmar & Howard, 2004; Fardouly, Pinkus, & Vartanian, 2017; Krawczyk & Thompson, 2015; Tiggemann & Polivy, 2010), as well as protective factors including media literacy (McLean, Paxton, & Wertheim, 2016a). To date, however, examinations of the factors that increase risk or in contrast are protective of the effects of exposure to social media on body image are scarce.

∗ Corresponding author at: Department of Psychology and Counselling, La Trobe University, Bundoora (Melbourne), 3086, Australia. E-mail address: [email protected] (E.H. Wertheim). https://doi.org/10.1016/j.bodyim.2019.10.005 1740-1445/© 2019 Elsevier Ltd. All rights reserved.

The current study aimed to increase our understanding of these relationships and clarify factors that may modulate vulnerability to the effects of exposure to social media on body image. Social media offers various interactive, photo-based platforms that can be) used for sharing and reacting to user-generated content. Instagram is a primarily photo-based platform on which users can post images of themselves and solicit feedback from other users in the forms of “likes” and comments. Given the strong emphasis on self-presentation through images of oneself (“selfies”), and the widespread use of digital modification and editing techniques to enhance images posted to social media such that they closely emulate appearance ideals, sociocultural theory would predict that exposure to social media may be detrimental to body image among young women (Rodgers, 2016; Thompson, Heinberg, Altabe, & Tantleff-Dunn, 1999). Indeed, sociocultural theories of body image and eating concerns describe how unrealistic and unrepresentative bodies and appearances in the media lead many individuals to internalize socially constructed appearance ideals (Thompson et al., 1999; Wertheim, Paxton, & Blaney, 2004). This internalization and ensuing upward appearance comparisons (comparisons to people who are deemed to look better), are posited to result in body dis-

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satisfaction. In contrast, media literacy is thought to protect from these effects by decreasing internalization of ideals as a personal standard, and by limiting appearance comparisons (McLean et al., 2016a). Consistent with predictions of sociocultural theory, an increasing body of research has documented a relationship between social media use and poor body image, and has suggested that engaging with photo-based platforms is most tightly associated with body image outcomes (Fardouly & Vartanian, 2016; Holland & Tiggemann, 2016; Rodgers & Melioli, 2016). A systematic review (Holland & Tiggemann, 2016) found that several longitudinal studies have supported a longitudinal association between social media use and poorer body image over time (see also de Vries, Peter, de Graaf, & Nikken, 2016). Smith, Hames, and Joiner (2013) revealed that maladaptive use of social media (i.e., engaging in appearance comparisons), in female university students, was associated with high levels of body dissatisfaction. In addition to longitudinal research, cross-sectional studies suggest that greater use of social media platforms and image-posting activities, are most likely to contribute to the development of body dissatisfaction in young women and adolescent girls (McLean, Paxton, Wertheim, & Masters, 2015; Holland & Tiggemann, 2016). Despite these results, correlational designs are unable to determine the directionality of effects (Fardouly & Vartanian, 2016). Experimental designs are therefore needed in order to determine the impact that social media has on body dissatisfaction. Therefore, several experimental studies have examined the effects of exposure to social media images on body image. Findings, while varied, suggest that exposure to idealized images of individuals in noncommercial contexts, such as those found on Instagram platforms and other social media, can be associated with decreased post exposure body satisfaction in young women (Brown & Tiggemann, 2016; Hogue & Mills, 2019; Slater, Varsani, & Diedrichs, 2017; Tamplin, McLean, & Paxton, 2018; Tiggemann & Zaccardo, 2015). As described above, sociocultural theory highlights the internalization of appearance ideals and social comparison as critical processes accounting for the effects of media exposure on body image (Grabe, Ward, & Hyde, 2008; Thompson et al., 1999). Specifically, one of the ways the theory describes these processes as being implicated is through a moderated pathway, whereby traits levels of internalization of the thin-ideal and appearance comparison tendencies are thought to increase vulnerability to media exposure effects. Regarding the moderated pathways, meta-analytic investigations of the relationship between more traditional forms of media exposure and body image outcomes have confirmed that young women with high levels of thin-ideal internalization and appearance comparison are most susceptible (Dittmar & Howard, 2004; Dittmar, Halliwell, & Stirling, 2009; Groesz, Levine, & Murnen, 2002). Similarly, some experimental studies have found that trait internalization (Krawczyk & Thompson, 2015), and trait levels of appearance comparison (Dittmar & Howard, 2004), increase vulnerability to media exposure effects, such that those who strongly endorse appearance ideals and have higher tendency to engage in appearance comparisons, experience the greatest changes in body image following exposure. In the context of exposure to social media, findings regarding these moderated relationships have been somewhat mixed. One study found that trait levels of appearance comparison moderated the effects of exposure to social media images on satisfaction with facial features, but not weight and shape (Fardouly, Diedrichs, Vartanian, & Halliwell, 2015). In another study, women were allocated to one of four conditions, including exposure to self-compassion quotes, Fitspiration images, Fitspiration images with self-compassion quotes, or control images of home interiors (Slater et al., 2017). Findings revealed that internalization moderated the effect on body satisfaction of viewing

self-compassion quotes as compared to control images, such that for young women with high levels of internalization viewing the self-compassion quotes was associated with greater body satisfaction compared to those who viewed control images (Slater et al., 2017). Other studies have failed to replicate these relationships and found no moderating role of trait level internalization or appearance comparison on the effects of exposure to Instagram images on body image among young women (Tamplin et al., 2018; Tiggemann & Zaccardo, 2015). In addition to examining these risk factors, a smaller body of research has focused on clarifying the role of protective factors such as media literacy and critical processing of media (McLean et al., 2016a). In the media literacy model proposed by Primack et al. (2006) a focus is critical thinking, which involves making informed, independent judgements about media, through understanding that media may not represent reality, that media content portrays certain values and perspectives, and that media content influences attitudes and behaviors. Thus, media literacy involves recognizing that media images can be manipulated to achieve desired effects (e.g., through how the photo is framed initially or subsequently edited), are not necessarily realistic, and reflect the values and motivations of the poster (McLean, Paxton, & Wertheim, 2016b; McLean et al., 2016a). An aim of media literacy knowledge (trait level literacy) is to enable individuals to think critically about images viewed in the moment (state level critical media processing). This protective role of media literacy has been examined in empirical studies. Findings for traditional media have been somewhat mixed with some research supporting the protective nature of trait level media literacy (McLean et al., 2016a), and other research failing to replicate this relationship for state level demonstrations of media literacy involving critical processing (Andrew, Tiggemann, & Clark, 2015). Regarding social media, a study examining the protective role of trait social media-related literacy found that young women with higher levels of social media literacy reported smaller changes in body satisfaction following exposure to Instagram images (Tamplin et al., 2018). To our knowledge, however, no examinations of the protective role of critical media processing (demonstrated state level media literacy) on the effects of exposure to social media images have been conducted. The present study aimed to replicate findings regarding exposure to thin-idealized images from different types of media and extend those findings by examining effects of images typical of social media peer postings, as opposed to celebrities or professional models. A novel aim of the study was to examine the thoughts of women while viewing those images, to explore possible mechanisms influencing effects of image exposure. An experimental design was used to examine the impact on young women of being exposed to body-focused images of young women representing the Western thinness ideal and identified as originating from Instagram compared to non-body focused Instagram-style scenery photos. We aimed to determine whether exposure to thin-ideal Instagram postings depicting young women and identified as typical of Instagram, would result in increased body dissatisfaction and negative mood, and which women would be most affected by such exposure. The content was designed to resemble content posted by peers on Instagram, rather than identifiable celebrities or professional models, since one of the differences between social media and traditional media is the presence of user generated peer content that may increase perceptions of the similarity of the target and thereby social comparison processes. Trait characteristics, including body comparison tendencies and internalization of the thin-ideal, were examined as moderators. Consistent with the literature reviewed above, Hypothesis 1 was that trait body comparison tendencies would moderate the effect of condition (exposure to thin-idealized versus control scenery images) on post-exposure state body dissatisfaction and mood. It

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was expected that the greatest increases in body dissatisfaction and negative mood following image exposure would be reported by women with higher body comparison tendencies who viewed the thin-ideal images. Similarly Hypothesis 2 replicated the same question, examining instead trait internalization of the thin-ideal as the moderator. To extend current research, a further aim was to examine whether particular types of thoughts were associated with worsening, or improving, of state mood or body dissatisfaction. A thought elicitation (thought listing) method was used, which is common in social and clinical psychology research (Cacioppo & Petty, 1981), but has been used rarely in the body image field (Engeln-Maddox, 2005; Watson & Murnen, 2019). The approach involves individuals reporting their thoughts related to specific stimuli that have just been presented, from which thought content is assessed. This method avoids issues with retrospective self-reports that ask individuals to generalize over time, since reported thoughts are immediately accessible (Cacioppo, von Hippel, & Ernst, 1997), and it potentially reduces demand responding compared to directly asking about specific types of thoughts (e.g., frequency of comparing), as the thought-elements being assessed are not specified to participants. We aimed to qualitatively explore young women’s cognitive experiences of viewing the Instagram-sourced body-focused thinidealized images, to better understand women’s responses to those images. If upward body comparisons operate as key mechanisms for a worsening in body dissatisfaction and mood, then one would expect some women to report thoughts illustrating such comparisons. Two prior body image studies have used thought-listing methods, showing participants images of women identified as from advertisements (Engeln-Maddox, 2005) or nonspecified ‘social media’ (Watson & Murnen, 2019). Both studies found greater upward comparisons were associated with trait internalization of the thin ideal and trait body dissatisfaction, but neither examined their association with responses to the viewed images. Consistent with predictions of sociocultural theory regarding the respective risk and protective roles played by appearance comparison, we expected (Hypothesis 3) that greater numbers of thoughts comparing the participant’s own body to the women’s bodies depicted in the thin-ideal images, particularly thoughts indicating upward comparisons, would be associated with greater post-viewing increases in body dissatisfaction and negative mood post exposure. Similarly, if critical media processing was protective of effects of viewing thin-ideal images, then we expected that thoughts indicating critical media processing (and implying media literacy) would be associated with less worsening of negative mood or body dissatisfaction following image exposure.

2. Method 2.1. Participants For the randomized experiment comparing responses to two types of Instagram-style images (thin-ideal versus scenery), 126 female participants aged 18–29 years (M = 23.28, SD = 2.58) were recruited via Prolific Academic, a British crowd-sourcing webbased platform that allows researchers to recruit individuals to participate in online surveys in exchange for money. An a priori power analysis using G*Power (v. 3.0.10) indicated a sample size of 112 would detect an effect of f2 =.10 (small to moderate) entering 3 variables in a regression equation, using an alpha level of .05 and power of .80. Initially 141 participants responded. Fifteen participants were excluded because they provided incorrect validity check responses, completed the study in a very short time, reported a body mass

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index (BMI; Garrow & Webster, 1985) unlikely to be accurate (one participant with BMI = 7.4), or reported being male or “other.” Participants lived in the United Kingdom (58.7%), Europe (29.5%), North America (8.7%), Asia (1.6%), and South America (1.6%). Most were Caucasian (79.4%), with 6.3% Hispanic, 5.6% Asian, and 8.7% other. Regarding education, 11.9% completed postgraduate, 43.7% undergraduate, 25.4% part of undergraduate, 4% trade or technical qualification, 12.7% high school, and 2.4% primary school. The average BMI of participants was 24.66 (SD = 5.25). To supplement the second set of analyses, examining types of thoughts reported when viewing thin-ideal images and their associations with body dissatisfaction and mood changes, a further 28 participants (age M = 21.72, SD = 2.30) were allocated to the thinideal condition (originally 30 participants, one was dropped as an outlier with BMI = 14.8, another due to uncodable data, with none failing other validity checks). 2.2. Measures 2.2.1. Demographics Participants reported gender, age, country of residence, ethnicity, level of education, weight, and height. Body mass index (BMI; kg/m2 ) was calculated. 2.2.2. Social media usage Participants reported whether they had accounts with popular social media platforms (Instagram, Facebook, Pinterest, We Heart It, Snapchat) and how much time they spend on these sites weekly, daily and on average. 2.2.3. Trait appearance comparison tendencies The Physical Appearance Comparison Scale-Revised (trait appearance comparison, PACS-R; Schaefer & Thompson, 2014) assessed trait appearance comparisons. Eleven items such as “When I’m at a party, I compare my body shape to the body shape of others” were rated regarding frequency from 1 (never) to 5 (always). The mean of items was calculated, with higher trait appearance comparison scores indicating greater appearance comparison tendencies. Scores on the PACS-R have been shown to have good convergent and incremental validity with theoretically related variables (e.g., body dissatisfaction, weight concern, and dietary restraint) in young adult women (Schaefer & Thompson, 2014). Our experimental sample’s Cronbach’s alpha was .87. 2.2.4. Internalization of the thin-ideal The Internalization Thin - Low Body Fat subscale of the Sociocultural Attitudes Towards Appearance Questionnaire (internalization, SATAQ-4; Schaefer et al., 2015) assessed internalization of the thin-ideal. Participants rated 5 items, such as “I think a lot about looking thin” from 1 (definitely disagree) to 5 (definitely agree). Total scores ranged from 5 to 25, with higher scores indicating greater internalization. Scale scores have demonstrated good internal consistency in young women (␣ = .85) and good convergent validity with measures of body image (Schaefer et al., 2015). Our experimental sample’s Cronbach’s alpha was .78, mean inter-item r = .41. 2.2.5. State body dissatisfaction and mood Visual Analogue Scales (VAS; Heinberg & Thompson, 1995) assessed state body dissatisfaction and mood prior to and immediately after exposure to the experimental images. Participants selected a spot on a horizontal line from 0 (not at all; one end of the line) to 100 (very much; other end) to indicate how they feel ‘right now.’ Item ratings, including fat, physically attractive (reverse coded), and satisfied with your body size (reverse coded)

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were averaged, with higher scores indicating greater state body dissatisfaction. Five items such as depressed and happy (reverse coded) were averaged, with higher scores indicating more negative mood. Body dissatisfaction and mood VAS scores have been shown to have good convergent validity and to be sensitive to state changes over short time frames (Fardouly et al., 2015; Heinberg & Thompson, 1995). Our experimental sample’s Cronbach’s ␣ was .81 for state body dissatisfaction and ␣ = .80 for negative mood. 2.3. Experimental stimulus materials Intervention condition images included nine thin-idealized images of young (age 18 to 25), thin, attractive Caucasian women in minimal apparel (e.g., bathing suits) in which the body was the focus, engaged in activities such as taking a selfie, walking, or lying on the beach. To highlight the peer-posted nature of images, production values of selected images did not appear professional (e.g., through framing of the photo, or activity depicted). To avoid images being recognised individuals, images were selected from social networks of the researchers rather than women with large numbers of followers. The control condition images comprised nine primarily scenery photos. To increase the believability of these images being Instagram-sourced, four included a person as a small element in the picture. Those control-images depicted young women whose bodies were not highlighted. The number of images was informed by Groesz et al.’s (2002) findings that when thin-ideal stimuli exceeded nine images, effect sizes were smaller, possibly due to habituation. Images were sourced from Instagram and three authors reached consensus on 24 images, which were tested in a pilot study in which women rated 12 thin-idealized images, 10 images in which the focus was the scenery, and 2 photos of nonthin-ideal women for comparison purposes. In that pilot study, eight female participants were recruited from Prolific Academic using the same selection criteria and methods as for the main study. After answering demographic questions, a definition of the Western thin-ideal was provided and tested in multiple-choice format to ensure attention and understanding. Participants rated the degree to which the 24 randomly presented images depicted the Western thin-ideal (1 = not at all, 2 = a little, 3 = moderately, 4 = a lot). All thin -ideal images had a mean and median of at least 3.5, with control scenery images with a person in them all having a mean and median of 2 or lower regarding the depicted woman. 2.4. Items to address validity of data Two attention-check questions directing participants to select a particular answer were embedded in trait measures. Participants who failed a check were excluded. During the pilot study (N = 8), researcher coding of body-related thoughts into positive, neutral, or negative implication categories, was found to be difficult when participants used a thinness-related word without further description. Therefore to increase reliability when coding body shape-related thoughts, at the end of the study participants were asked to rate how they perceived three common thinness-related words (thin, skinny, slim), by selecting a spot on a horizontal line ranging from 0 (negative) to 10 (positive). Ratings of ‘5’ were considered neutral, under 5 negative, and over 5 positive. This rating was used in coding thoughts to determine whether a particular participant’s body-related thought implied a positive, neutral, or negative judgement about the depicted body. After completing post-exposure ratings, the final 57 participants in the thin-ideal images conditions rated from 1 (never) to 5 (always) when viewing the images how often they compared their own body to the women in the images, and how frequently they see images like those just viewed posted on social media by friends.

2.5. Procedure Following ethics committee approval from X, the pilot study to select stimulus images was completed. Prolific Academic was used to recruit participants for the pilot study and main study. This worker crowd-sourcing platform compares favourably to similar platforms, such as Amazon Mechanical Turk in yielding reliable responses (Peer, Brandimarte, Samat, & Alessandro, 2017). Prolific Academic standard screening questions determined which of their participant pool saw the ad for the study. Participants needed to be registered with Prolific as female biologically, between 18 and 29 years old. To address ethics committee concerns about including vulnerable individuals, participants who registered with Prolific Academic as having an uncontrolled mental illness that impacted their daily life or being very underweight were excluded. Eligible participants needed to have at least 95% positive researcher feedback from prior research projects. Through the Prolific Academic website, eligible participants, answering an ad for a study titled How do people respond to Instagram images, accessed a weblink to an anonymous Qualtrics survey for which they would be paid GBP 2.20. For the main study, following the participant information statement (which defined the study as about responses to Instagram images) and online informed consent, participants first answered demographic questions and reported Instagram and other social media usage. Trait measures of internalization and body comparison were completed, followed by pre-exposure visual analogue scales assessing state body dissatisfaction and mood. The first 141 (initial experimental sample) were then randomly allocated to view either thin-ideal body-focused images or control scenery images. To further prime participants to consider the images they viewed as Instagram images, they were all presented with the same description of Instagram, which included information such as it being an app allowing shared photos, connectable to other social media, with features such as hashtags and geotags. During this description, to begin exposure, participants viewed embedded images of three of the nine Instagram images depicting either thin-ideal images or scenery images consistent with the allocated condition. These images were described as “examples of Instagram images.” Participants then viewed six further images for each of which they were asked to “write three sentences that came to mind when viewing the image.” Thought listing occurred after each of the six photos to ensure sufficient attention was paid to the images and to allow immediate rather than retrospective reporting of thoughts. Three comment boxes were provided under each image for these thoughts. Participants then completed post-exposure state body dissatisfaction and mood and rated the thinness-related words. To assist in obtaining sufficient upward comparison thoughts to conduct the thought-listing related analyses, 28 further participants (supplementary sample) completed the thin-ideal condition using the same source (Prolific Academic), selection criteria and methods as for the experimental sample. These women did not differ from the experimental thin-ideal group on any demographic or trait variable (all ps < .15), except that internalization was higher for the supplementary sample t(89) = -2.45, p = .016. In total, n = 91 women were thereby included in thought-listing analyses. 2.6. Data analysis Data were analyzed using the Statistical Package for the Social Science software (SPSS; v. 25). Data screening, preparation, and assumptions testing were performed. Assumptions for multiple regressions (non-multicollinearity, homoscedasticity) were tested and met for the experimental sample. Standardized indices of skewness and kurtosis were all within ± 3.29 (␣ < .001, two-tailed, Tabachnick & Fidell, 2007). Inspection of residual scatterplots sug-

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Table 1 Correlations Between Demographics, Trait Body Comparison and Internalization of the Thin-Ideal, and Pre-Image-Exposure State Body Dissatisfaction and Mood (N = 126). Variables

1

2

3

4

5

6

7

1. Age 2. BMI 3. Education a 4. Appearance comparison 5. Internalization 6. Pre-body dissatisfaction 7. Pre-negative mood M (SD)

− .164 −.440*** .121 −.042 .030 −.070 23.28 (2.58)

− .053 .245** .043 .232** .058 24.66 (5.25)

− −.156 −.040 .091 .035 –

− .531*** .435*** .311** 34.92 (10.77)

− .376*** .266** 15.76 (4.30)

− .528*** 56.38 (23.14)

− 45.67 (21.58)

Note. Pre = pre-exposure to image stimuli, Internalization = Internalization of the thin-ideal. Pearson’s product moment correlations are presented except for education correlations which are Spearman’s rho. *p < .05, **p < .01, ***p < .001.

gested bivariate relationships were linear. Scatterplots of residuals suggested no multivariate outliers. Pearson product-moment correlation coefficients (Table 1) between pre-exposure variables and demographics were examined to assess for multicollinearity. As a preliminary check, independent samples t-tests compared differences among the thin-ideal and scenery conditions on measures administered before the thoughtelicitation task and demographics. In order to retain continuous variables as the moderators, four hierarchical multiple regression analyses tested the experimental hypotheses, with standardized residual change scores (pre to post image exposure) for state mood and state body dissatisfaction being the two dependent measures. Standardized residual change scores were calculated using regressions by entering the relevant pre-exposure state scale as the independent variable and the parallel post-exposure state scale as the dependent measure and saving the standardized residual as a new variable. For each regression, condition (thin-ideal images = 1, scenery images = 0) and the mean-centered moderator variable (either appearance comparison tendencies or trait internalization of the thin-ideal) were entered at Step 1, with the interaction effect (condition × centered moderator variable) entered at Step 2. To examine moderation effects, planned comparisons involved simple slopes regressions conducted separately for each group predicting body dissatisfaction and mood standardised residual change scores from the centered moderator variable. Tolerance and VIF for regression models were all within acceptable limits for these analyses (Pallant, 2013). Thought coding was completed for 91 participants (the 63 thinideal condition participants in the randomized experiment and 28 supplementary thin-ideal condition participants), who supplied 1638 thoughts. Themes based on the thought-elicitation data were independently generated by two authors with knowledge of existing literature on body image, appearance comparisons, and media literacy (FA, EW, the latter having numerous publications in those fields), with final categories being consensus based. Theoretical frameworks informed key coding categories of upward body comparison (Thompson et al., 1999) and media literacy (based on McLean et al., 2016a, 2016b) with reference to the data. The remaining categories were inductively generated based on the data itself (Braun & Clarke, 2006). After those two coders independently rated a trial set of thoughts and clarified discrepancies, they independently coded 1000 thoughts to establish reliability and reached consensus. The remaining thoughts were coded by one coder. Cohen’s Kappa agreement of at least .63 (substantial agreement) was required for category retention, although all but one retained category exceeded .80 (Landis & Koch, 1977). Since coding categories were skewed, frequencies of hypothesis-related coding categories were correlated using Spearman’s rho, with standardized residual pre-post change scores of state mood and body dissatisfaction. Transformed variables were used for a follow-up regression to examine unique variance explained by the significant thought categories.

Cohen’s (1988) effect size conventions were used. For Cohen’s d small = 0.20, medium = 0.50, large = 0.80, for correlations small = .10, medium = .30, large = .50, for squared semi-partial correlations (partial eta squared) and R2 change small = .02, medium = .13, large = .26. 3. Results 3.1. Preliminary correlational analyses Correlations were performed among demographic variables and pre-image-exposure measures (see Table 1). While some correlations, such as between pre-exposure mood and body dissatisfaction, showed strong correlations, no multicollinearity was found. Pre-body dissatisfaction and pre-negative mood were significantly positively associated with internalization and trait appearance comparison, the latter two of which were intercorrelated significantly. Higher BMI was associated with greater trait appearance comparison and state body dissatisfaction but not internalization. 3.2. Participant characteristics 3.2.1. Experimental groups Independent samples t-tests investigated possible baseline differences between conditions: 0 = scenery (n = 63) and 1 = thin ideal (n = 63) on age, BMI, education, trait appearance comparison, thinideal internalization, pre-exposure mood, and pre-exposure body dissatisfaction. The two groups did not differ significantly on any variable, all ts(124) < 1.93, ps > .05. 3.2.2. Social media engagement The preponderance of participants reported currently having an Instagram (85.7%), and/or Facebook (88.1%) account. Most participants reported using Instagram on a daily basis (72.2%), with 41.7% spending more than 10 min a day using it. Of Instagram users who formerly, but not currently, had an account (7.9%), 40% reported having checked their account daily. Although 6.4% of the sample reported never using Instagram, all participants reported currently or formerly using some type of social media. In the subset of participants (n = 57) who rated frequency of seeing (thin-ideal body-focused) images like those they just viewed posted by friends on social media, 97.4% indicated they saw them at least sometimes, with 56.4% saying they saw them at least half the time. 3.3. Regressions predicting mood and body dissatisfaction from condition and moderators 3.3.1. Negative mood with trait appearance comparison as a moderator Regarding change in mood following viewing Instagram-like images, Step 1 of the multiple regression was significant, explain-

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ing 5.4% of the variance in pre-post residual change score for mood, F(2, 123) = 3.48, p = .034. The condition main effect was significant, t = 2.54, ˇ = .23, p = .012, with a semi-partial correlation of rsp = .22, a small effect; M standardized residual change for control condition = −0.21, SD = 0.94, for thin-ideal condition = 0.21, SD = 1.02, with less mood improvement over time for the thin-ideal condition than the control condition. To further clarify changes, paired samples t-tests (comparing pre to post mood) found that after viewing the photos, mood improved significantly in both conditions, with the scenery condition t(62) = −10.35, p < .001, pre- M = 47.38 (SD = 19.80), post M = 32.49 (SD = 17.61), resulting in a large effect, d = 0.80, and the thinideal condition t(62) = −5.99, p < .001, pre-M = 43.94 (SD = 23.26), post-M = 34.43 (SD = 20.13), resulting in a medium effect, d = 0.43. The trait appearance comparison main effect was not significant, t = 1.13, ˇ = .10, p = .26. At Step 2, the condition × appearance comparison interaction effect resulted in a nonsignificant tendency to increase the variance explained (2.3%), F = 3.09, t = 1.757, ˇ = .21, p = .081, rsp = .15, indicating a small effect size. Given the marginal significance level, correlations were conducted to clarify this interaction: greater appearance comparison tendencies were associated with fewer mood improvements in the thin-ideal condition, r = .25, p = .049, a small effect, but not the control scenery condition, r = −.05, p = .71.

3.3.2. Negative mood with internalization of the thin-ideal as a moderator The regression was repeated with internalization of the thinideal as the moderator. In the first step, the significant condition effect was replicated as above, rsp = .21. The main effect of the internalization moderator at Step 1 was not significant, t = 0.47, ˇ = .04, p = .639, rsp = .002. The condition × internalization interaction effect at Step 2 again had a nonsignificant tendency to increase variance explained (2.7%), t = 1.87, ˇ = .21, p = .063, with a medium effect size, rsp = .16. Given the marginal significance, correlations were conducted: greater appearance comparison tendencies tended to be associated with fewer mood improvements, in the thin-ideal condition, r = .21, p = .09, a small effect, but not the control scenery condition, r = −.11, p = .39.

3.3.3. Body dissatisfaction with trait appearance comparison tendency as a moderator For body dissatisfaction changes, Step 1 of the multiple regression model was significant, explaining 6.9% of the variance in the body dissatisfaction pre-post standardized residual change score, F(2, 123) = 4.52, p = .013. The condition main effect was significant, t = 2.64, ˇ = .233, p = .009, rsp = .23, indicating a small effect size; control condition M standardized residual change = −0.20, SD = 0.72, thin-ideal condition M standardized residual change = 0.20, SD = 1.19, with fewer improvements in body dissatisfaction over time for the thin-ideal than control condition. Paired samples t-tests (pre versus post body dissatisfaction for the conditions separately) showed that after viewing images, body dissatisfaction decreased significantly in the scenery condition, t(62) = 2.78, p = .012, pre M = 57.78 (SD = 23.21), post M = 55.29 (24.18), d = 0.11, indicating a small effect size, but not in the thinideal condition, t(62) = −1.24, p = .220, pre M = 54.97 (SD = 23.16), post M = 56.98 (24.71), d = 0.08. The trait appearance comparison main effect was nonsignificant, t = 1.87, ˇ = .165, p = .064, rsp = .16, with a small effect size. At Step 2, the addition of the condition × appearance comparison interaction effect explained a nonsignificant 0.5% additional variance, F (1, 122) = 0.61, t = 0.78, ˇ = .094, p = .435, rsp = .068.

3.3.4. Body dissatisfaction with internalization of the thin-ideal as a moderator The above regression was repeated with internalization of the thin-ideal as the moderator. At Step 1, once again the main effect of condition was significant, replicating the above analysis, rsp = .21, and the moderator was not significant, t = 1.26, ˇ = .111, p = .209, rsp = .11. The condition × internalization interaction effect at Step 2 again had a nonsignificant tendency to increase variance explained (2.5%), t = 1.84, ˇ = .208, p = .069, with a small effect size, rsp = .16. Given the marginal significance, correlations were conducted: greater internalization tendencies tended to be associated with fewer body dissatisfaction improvements, in the thin-ideal condition, r = .23, p = .07, a small effect, but not the control scenery condition, r = −.03, p = .78. 3.4. Thought coding process and themes generated Ratings of the shape-related words indicated slim was most positively rated and skinny least, F(2, 97) = 73.14, p < .001, etap 2 = .601; however, substantial variation existed: thin (36.4% rated it as positive, 15% neutral, 48.5% negative), skinny (24.2%, 12.1%, 63.6%), slim (77.8%, 11.1%, 11.1%). Therefore, as planned, when a participant’s response included one of these words, the coder referred to that participant’s own rating of the word to code the body-related thought as positive, neutral, or negative. Table 2 displays the themes based on thoughts elicited while viewing thin-ideal images, sample thoughts, frequencies of thought types, and Cohen’s Kappas. The theoretically-informed category of upward body comparisons was coded when the thought suggested a desire to have a body or body part like that depicted in the image. At least one explicit upward body comparison thought was reported by 24.2% of participants (15.4% made one body comparison, 8.8% made 4 or more comparisons). Demonstrating validity of the upward comparison coding, frequencies of upward comparing thoughts correlated rho = .31, n = 57, p = .003 with trait body comparison and rho = .37, n = 57, p = .009, with retrospective selfreport of frequency of with one’s own body to the images. A further inductively-derived category of ‘other comparisons’ was created (to contrast with upward body comparisons category), including thoughts of looking similar to the depicted person (non-upward comparisons) or desiring another non-body related aspect of what was depicted in the image. In total, 26% of participants reported thoughts indicating these other sorts of comparisons. A strong set of inductively derived themes involved thoughts about the depicted women’s overall body shape or size or about other body characteristics of the depicted women, with 93.4% of women making at least one such body comment, most of which were positive judgements about the body. Supporting validity of the image stimuli, most of thoughts commenting on the depicted women’s bodies were positive judgements (61% positive, 24.2% neutral, with only 16% negative body thoughts). In addition, there were significantly more body-focused thoughts than person-focused thoughts, t(90) = 4.62, p < .001. As shown in Table 2, a critical media processing theme emerged, which implied media literacy knowledge and demonstrated application. Several categories of critical media processing reflecting key critical processing categories theoretically aligned with a systematic review of the field (McLean et al., 2016a) were coded. The categories included stating elements of the photo looked unreal; or framed for a specific effect or edited; the person was posing (thus implying an unrealistic image); or inferring motivations of the photo poster. A further inductively-derived theme related to awareness of the image as being created for, and belonging to, social or mass media. Some of these thoughts simply referenced the photo nature of the image or referred to social media or ads. In addition, the positive body-related judgements and upward comparisons

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Table 2 Coding Categories for Thoughts About the Thin-Ideal Images, Sample Thoughts, Percentage of Thin-Ideal Condition Sample Reporting Thinking Those Thought Types at Least Once, and Mean Number of Times Each Thought Type Reported. Codes Body comments a Positive judgements Neutral comments Negative judgements Comparisons Upward body comparison Other comparisons Fitness or health Person-focused Positive features Neutral features Negative features Media awareness Photo nature of image Social media or ads Social media literacy Awareness of posing Poster motivations Photo appears edited or manipulated Unrealistic image Other focus (e.g., scenery, clothes)

Sample thoughts

% of sample

M (SD)

Cohen’s Kappa

she has a nice body, model, nice tan, shapely buttocks, nice long legs, pretty girl; slim, thin, or skinny words when rated > 5 she has a flat stomach, she’s kind of normal shaped, tanned, boobs, long legs, long hair; slim, thin, or skinny words when rated 5 too thin, looks like she has anorexia, her stomach is weird, the ribs are scaring me; slim, thin, or skinny words when rated < 5

86.8

3.20 (2.82)

.834

37.4

0.82 (1.36)

.747

51.6

1.25 (1.72)

.801

24.2

0.68 (1.81)

.861

26.4 27.5

0.51 (1.16) 0.47 (0.98)

.874 .816

41.8 18.7 24.7 80.2 76.9 26.4 81.3 49.5 42.9 30.8 25.3 92.3

0.95 (1.51) 0.27 (0.65) 0.45 (0.93) 2.68 (2.43) 2.24 (2.06) 0.44 (1.00) 2.91 (3.08) 1.07 (1.53) 1.00 (1.63) 0.41 (0.73) 0.44 (0.99) 5.43 (4.03)

.838 .703 .634

I wish I was as skinny as her, my waist will never be that small, I need to go to the gym, I would kill for that body shape she has a similar body to me, I wish I was in the water, I would love to be there fit, she’s fit and healthy, her body looks healthy enough she has confidence, she is comfortable with her body, having fun she likes to go to the beach, she has a particular style idiot, doesn’t look that happy, insecure nice photo, classic bathroom selfie, composition of the photo is good Insta, sponsored image, influencer, looks like a bad pop up ad she’s obviously posing, posing to look slimmer, poser looking for likes, needs approval of others, trying to show off looks photoshopped, filter, altered, has this one been edited not realistic, doesn’t represent her body shape, she looks so fake lovely beach location, she is on a holiday, wearing a nice hat, bikini, America, mirror, summer

.816 .861 .877 .899 .921 .779 .862

Note. % = percentage of women reporting that type of thought at least once. M = mean times across six images that the type of thought was reported. a Any thoughts including the words thin, skinny, or slim were categorised into positive body judgements, negative body judgements, or neutral body comments based on the participant’s own rating (from 0 to 10) of their perception of that word (completed after the thought elicitation task). A participant rating of 0–4 for that word resulted in coding the thought as a negative judgement, 5 as neutral, and 6–10 as a positive judgement.

noted earlier could be considered relevant to the desirability media literacy component, with high levels of those thoughts suggesting lower critical media non-desirability processing. For the scenery sample, coding was only completed for bodyrelated thoughts, as a manipulation check. A Yates corrected ␹2 (2) = 86.73, p < .001, showed that the thin-ideal condition reported significantly more thoughts commenting on a depicted woman’s body than the scenery condition. For scenery participants, 71.4% (n = 45) reported no body-related thoughts, 23.8% (n = 15) reported one such thought, and 4.8% (n = 3) reported two or three body-related thoughts. In contrast, for thin-ideal participants, 6.6% (n = 6) reported no body thoughts, 13.2% (n = 12) reported one body thought, and 80.2% (n = 73) reported two or more body-related thoughts.

The three predictive thought types were not completely independent: positive body thoughts correlated with upward comparison thoughts, rs = .31, p = .003, and rs = −.51, p < .001, with other thoughts, although upward comparison thoughts did not correlate significantly with other thoughts, rs = −.14, p = .21. Therefore, to identify independent predictors, an exploratory regression was run entering the three significant thought predictors in one block predicting mood change: positive body (log10 transformed), upward comparison (inverse transformed), other thoughts (square root transformed). The regression model was significant, F(3,86) = 4.07, R = .353, R2 = .124, Adj R2 = .094, p = .009, with the only significant predictor being upward comparison, ␤ = .249, t = 2.43, p = .017 (other thoughts ␤ = −.110, positive body/shape thoughts ␤ = .135). 4. Discussion

3.4.1. Relationships between thoughts and change in body dissatisfaction and mood (Hypothesis 3) and moderator variables Spearman’s rho correlations examined the relationship between frequencies of different types of thoughts reported while viewing thin-ideal images and mood residual change score between pre- and post-viewing of those images (n = 90). Improvements in mood were associated with fewer positive body and shape-related thoughts (related to the depicted woman), rs = .30, p = .004, and fewer upward body comparisons, rs = .22, p = .033. Mood changes were not associated with either media awareness or social media literacy thoughts (either the overall social media literacy variable or any of the individual media literacy variables), or positive person-related or negative body and shape related thoughts (ps > .05). However, an improvement in mood was associated with more thoughts about extraneous topics (other than body or media characteristics) such as noting the setting or clothing, rs = −.27, p = .009. The pre-post body dissatisfaction residual change score was not significantly correlated with frequencies of any of these types of thoughts (ps < .05). No demographic variables correlated significantly with any frequency of thoughts variables, all ps > .20.

Our study aimed to add to our understanding of the factors that might increase or decrease risk of the detrimental impact of social media exposure on body image. Our findings indicated that exposure to control scenery images resulted in greater improvements in both mood and body dissatisfaction compared to exposure to thin-ideal body-focused images. Somewhat unexpectedly mood improved in both the scenery and thin-ideal conditions, although body dissatisfaction ratings improved significantly in the control condition only. Contrary to Hypotheses 1 and 2, moderator effects of trait appearance comparison tendency and internalization of the thin-ideal were not found. However, given that results approached significance, further analyses examined the patterns of findings. While for the control condition there were no significant relationships between moderator variables and changes in outcome variables, in the thin-ideal condition greater internalization of the thin-ideal tended to be associated with fewer mood and body dissatisfaction improvements, and greater appearance comparison tendencies tended to be associated with fewer improvements in negative mood. Overall, these findings do not pro-

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vide strong support for theories positing that trait characteristics, specifically appearance comparison tendencies and internalization of the thin-ideal, influence effects of exposure to social media-style thin-idealized images when the images selected simulate those of unknown peers (Fardouly et al., 2015; Slater et al., 2017). Regarding Hypothesis 3, examining the relationship between thoughts reported while viewing the thin-ideal stimulus materials and self-reported mood and body image outcomes, small effects were found for three types of thoughts when predicting changes in mood but not body dissatisfaction. Providing support for the importance of appearance comparisons experienced in the moment (Tiggemann & Zaccardo, 2015), more frequent positive thoughts about the body of the person in the image, more upward body comparisons, and more extraneous (neither body nor media) related thoughts were all associated with less improvement in mood. There were no significant relationships between mediaassociated or critical media processing thoughts and mood or body dissatisfaction changes. A first point to be made regarding these findings relates to the relatively small effects of the thin-ideal images in this study and the fact that there were primarily mood improvements in the scenery condition rather than mood deterioration in the thin-ideal condition. Several explanations are possible. First, the activity of viewing images and listing thoughts may have in general been more engaging for participants than typical surveys they complete, and the mood enhancing effect of the method may have been dampened by the more challenging subject matter in the thin-ideal condition. Alternatively, the current study’s scenery images, which are similar to control “travel” images in other studies of effects of objectified images (Brown & Tiggemann, 2016; Tiggemann & Zaccardo, 2015), may not have been neutral, but rather mood enhancing. The reduction in negative mood we found for the scenery condition is consistent with some of the prior research using such images (Brown & Tiggemann, 2016; Tiggemann & Zaccardo, 2015). The lack of deterioration of mood in the thin-ideal condition, and indeed slight improvement, is an interesting finding. Some previous experimental research has also failed to find a significant deterioration of mood among young women exposed to social media images promoting appearance ideals (Tiggemann & Zaccardo, 2015). Although the focus in this study was the manipulation of the presence of thinideal content between conditions, other aspects of images may also have an impact on individuals’ evaluations and reactions to them, including the iconography, and the affect displayed in the images (Rodgers, Kruger, Lowy, Long, & Richard, in press). Future research should aim to clarify the ways in which social media images impact mood, and the mechanisms for these effects. Second, in the present study, women compared themselves with similar unfamiliar young women, not with known celebrities and models portrayed on Instagram and depicting very strict beauty standards. Comparison target may be relevant, although in at least one study images described as celebrities versus peers were rated as similarly attractive and the effects of exposure to them did not differ (Brown & Tiggemann, 2016). In the current study while the images were deemed attractive by most participants, they may not have been as aspirational and toned as Thinspiration and Fitspiration images which are often used in studies of this nature (Brown & Tiggemann, 2016; Robinson et al., 2017) and thus they may not have triggered as many social comparison and negative effects. Consistent with the idea that the type of image is important, Robinson et al. (2017) found that women who were exposed to athletic-ideal images reported higher body dissatisfaction than those exposed to traditional idealised images. However, even Fitspiration images used in past studies have not guaranteed substantial changes in mood or state body dissatisfaction post-exposure (Slater et al., 2017).

Finally, the somewhat limited effects of the thin-ideal images may be due to low dosage. We used nine images, as Groesz et al. (2002) meta-analysis of studies of exposure to mass media found that exceeding nine images reduced effects. However, as social media studies with positive findings tend to include more images (Brown & Tiggemann, 2016; Robinson et al., 2017), social mediarelevant exposure may require a greater dosage. A novel aspect of this study involved the thought elicitation process, which enabled an examination of possible mechanisms behind state changes when viewing thin-idealized images. Three types of thoughts were associated with a suppression of any mood enhancing effects of the study (positive appraisals of the bodies depicted and upward comparison thoughts) or appeared protective (other-focused thoughts). However, the only type of thought contributing unique variance was upward body comparisons. These findings provide some support that upward appearance comparison measured as a state variable in the moment as a cognitive experience is a risk factor (Thompson et al., 1999) for negative mood following exposure to thin-idealized images. The finding that those thoughts were not associated with body dissatisfaction changes, may suggest that the thought processes elicited during exposure had a more direct effect on transient mood than on evaluations of one’s body, the latter of which might be related to automatic affect responses to a greater extent than conscious cognitive ones. Almost all women reported having thoughts about the bodies of the women in the images, and 87% reported positive judgements. More frequent positive thoughts about the bodies depicted in the thin-ideal images were associated with increases in negative mood (or fewer reductions in negative mood), although the findings suggested this effect was accounted for by upward comparisons, so positive judgements about the body in an image do not appear to be a risk on their own. The converse, reporting ‘other’ types of thoughts such as noticing clothing or the environment (i.e., thoughts that did not relate to the body, the person or media awareness or literacy) appeared somewhat protective, although again, once upward comparisons were accounted for it did not contribute unique variance. This finding suggests that the allocation of attention to features other than the thin-ideal bodies depicted in images may decrease the processing of these, and therefore be protective. Other work has described how preferential processing of shape and weight related stimuli may constitute a risk factor for body dissatisfaction (Rodgers & DuBois, 2016). Our findings are consistent with this pathway, and suggest that encouraging individuals to focus on unrelated and peripheral aspects of thin-ideal imagery when encountered may be protective for body image. While our findings provide support for upward appearance comparison as a mechanism of action in explaining mood changes, the effect size was relatively small. Most participants did not report thoughts suggesting upward comparisons, with only 24% of the sample reporting an upward comparison, and just 9% making more than one upward comparison. While not directly comparable due to differing numbers of images and thoughts listed, Engeln-Maddox (2005) similarly found that a minority of women (30%) reported upward comparing thoughts, when viewing objectified images in advertisements. This pattern, combined with the finding that most women did not report worse mood and body dissatisfaction after exposure to thin-ideal images, suggests that indeed most women are protected from short-term exposure to media images. Nonetheless, our findings do confirm a subset of young women at risk when viewing thin-idealized images of women who could be unfamiliar peers (Rodgers, 2016). Further research would benefit from examining a larger sample of these high-risk women. In addition, prior research suggests that exposure to images itself may not be most problematic, rather greater engagement in image-based activities such as sharing and commenting on photos (Holland & Tiggemann,

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2016) or manipulating posted photos (McLean et al., 2015) are associated with negative body image outcomes of social media use. Thoughts suggesting a level of media or social media awareness and a critical approach to viewing images, including thoughts relating to the realism of the image and motivations of the poster, were relatively common in the sample although not as common as bodyfocused comments. Almost half the women commented at least once that the person depicted was posing, 40% noted at least once the motivations of the poster, somewhat less than a third noted that the photo looked edited, and a quarter commented that an aspect of the image looked unrealistic. However greater critical media thinking in these realms did not correlate with changes in mood or body dissatisfaction following viewing the thin-ideal images. These findings should be interpreted in light of the fact that critical media processing thoughts were assessed but not media literacy knowledge per se. Our focus was on whether application of media literacy took place while viewing images, to understand whether these were mechanisms that affected responses to viewing objectified images. Nonetheless, the lack of relationship between critical media processing related to realism and changes in mood and body dissatisfaction is contrary to theories positing that media literacy plays a protective role in exposure to idealised images (McLean et al., 2016a) and a prior study where a greater belief that Instagram selfies were digitally modified was associated with lesser internalization of the thin-ideal (Vendemia & DeAndrea, 2018). Our findings are, however, consistent with some research indicating no protective effects of self-reported frequency of use of media processing strategies (Andrew et al., 2015). Furthermore, EngelnMaddox (2005), whose thought-elicitation method informed our design, and Watson and Murnen (2019) also found that ‘counterarguments,’ which involved similar thoughts to the critical media processing assessed in our study, did not correlate significantly with trait-level body dissatisfaction. Similarly, consistent with our findings, investigations of the use of disclaimers on media images that warn that photos have been digitally manipulated, with the goal of raising awareness of the unrealistic nature of such images, have generally failed to reveal any protective effects for an individual’s body (Ata, Thompson, & Small, 2013; Bury, Tiggemann, & Slater, 2016; Fardouly & Holland, 2018). The context may also be relevant, as Tamplin et al. (2018) found that commercial, but not peer (more relevant to our study), social media literacy was protective against body dissatisfaction following advertising-style thin-ideal stimuli. Future research should examine whether particular forms of critical media processing or media literacy knowledge are protective in specific contexts and examine effects of media literacy interventions. Thoughts assessed in the current study included those most immediately accessible to participants, with the focus being on whatever thoughts arose when viewing the images. Most thoughts reported were other-focused, i.e., related to the individual in the image or aspects of the photo itself. Future research could manipulate the frame of reference, probing for both other-focused thoughts and self-focused thoughts (Cacioppo et al., 1997). Probing for self-focused thoughts can encourage additional reporting of upward comparisons (Engeln-Maddox, 2005; Watson & Murnen, 2019) and self-evaluations, of which negative self-evaluations have been found to be most predictive of mental health problems (Cacioppo et al., 1997). Furthermore, in addition to researchers coding thoughts, participants can rate aspects of their own thoughts, for example, intensity, salience or personal relevance, which can yield richer cognitive processing data (Cacioppo et al., 1997). Limitations of any study need identification. While there was diversity in participants’ residence, over half were UK-based and 79% of participants were Caucasian. As prior research suggests a link between culture, ethnicity, and body image concerns (Crago,

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Shisslak, & Estes, 1996), further research is needed on other types of samples. In addition, the images used were all Caucasian, so future research should better match racial characteristics to participants. Our study did not utilize a cover story to distract participants from the study’s purpose. This may have potentially increased demand characteristics, and it would be useful to account for this in future research. Our study assessed only demonstrated critical media processing thoughts, not media literacy per se; in future a measure of media literacy per se would be helpful to add to studies of this nature. Including a trait media literacy measure could also help validate the related thought coding, which was not done in this study. Finally, the images shown were sourced from Instagram and participants rated them as similar to those they would see on Instagram; however, participants did not directly engage with images on Instagram. In future, further cues associated with Instagram, such as comments and hashtags, could be included or direct access to images on Instagram used to assess impact of these elements of social media. Strengths of the study included a randomized experimental design to distinguish the effects of thin-ideal images relative to the control scenery images. In support of external validity, the thinidealized images were sourced from Instagram, and selection of the images was informed by ratings of a representative sample accessed from the same source (Prolific Academic). The use of an online crowdsourcing platform has advantages in that a community sample can be accessed and the online platform has external validity as this is how Instagram images will be viewed. Validity checks were undertaken to ensure attention to questions, and participants with very low response times were eliminated. Our method of assessing body comparisons of going beyond trait or retrospective self report, to synchronous thought-elicitation while women viewed the images is an advance in this research field, where comparison estimates are typically based on trait measures or retrospective self reports of frequency of comparing. In conclusion, this study extended existing research by examining young women’s responses to peer-posted Instagram images, and examining not only who responded most strongly to image exposure, but also what state cognitive processes were associated with changes in mood and body dissatisfaction. While effects of trait appearance comparisons and internalization of the thin-ideal on responses to thin-ideal images were found to be only marginal, further research with a greater number of high-risk women is needed to clarify these effects. Women reporting thoughts reflecting positive judgements about the bodies depicted and upward comparisons were most vulnerable to negative mood changes. Thoughts while viewing images focused on critical media literacy were not protective although thoughts suggesting attention was paid to extraneous elements of the image were. This research informs theories of risk and protective factors related to exposure to thin-idealized images and suggests that developing protective interventions targeting body comparison and other cognitive processes while viewing thin-ideal images may be a useful direction to take in future. References Andrew, R., Tiggemann, M., & Clark, L. (2015). The protective role of body appreciation against media-induced body dissatisfaction. Body Image, 15, 98–104. http://dx.doi.org/10.1016/j.bodyim.2015.07.005 Ata, R. N., Thompson, J. K., & Small, B. J. (2013). Effects of exposure to thin-ideal media images on body dissatisfaction: Testing the inclusion of a disclaimer versus warning label. Body Image, 10, 472–480. http://dx.doi.org/10.1016/j. bodyim.2013.04.004 Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3, 77–101. http://dx.doi.org/10.1191/ 1478088706qp063oa Brown, Z., & Tiggemann, M. (2016). Attractive celebrity and peer images on Instagram: Effect on women’s mood and body image. Body Image, 19, 37–43. http://dx.doi.org/10.1016/j.bodyim.2016.08.007

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