Abstract
Men’s cosmetic surgery rates are increasing globally. Existing literature suggests that social media engagement encourages women to undergo cosmetic surgery, yet the relationship between social media and cosmetic surgery for men remains underexamined. The aim of this study was therefore to explore if social media engagement impacted men’s interest in undergoing cosmetic surgery. Using an adapted version of the Passive and Active Use Measure to assess social media engagement, the relationship between social media engagement and cosmetic surgery consideration was explored. Among 311 American adult men (Mage = 37.7), passive social media engagement (e.g., viewing photos, browsing profiles) was found to have a small positive relationship with consideration of cosmetic surgery (p < .05, 95% CI [0.12, 0.49]). Conversely, Active Non-social media engagement (e.g., posting videos, tagging) and Active Social media engagement (e.g., posting statuses, commenting) did not predict cosmetic surgery consideration. These results demonstrate that the ways in which men use social media (rather than whether or not they use social media in general) determines their interest in cosmetic surgery. While social media engagement is a known correlate for appearance dissatisfaction in women, this study provides evidence that social media engagement is potentially also harmful to men’s body image. This preliminary research may contribute to informing best clinical practice for men experiencing body dissatisfaction. Namely, reducing passive social media use may alleviate men’s likelihood of pursing cosmetic surgery, in turn reducing their exposure to the physical and psychological risks associated with undergoing cosmetic surgery.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
More men are undergoing cosmetic surgery than ever before. In 2021, 13.7% of all surgical cosmetic procedures worldwide were performed on men (International Society of Aesthetic Plastic Surgery, 2021). In addition, approximately 23% of heterosexual men, 51% of homosexual men, and 7% of adolescent boys report being interested in undergoing cosmetic surgery (de Vries et al., 2014; Frederick & Essayli, 2016). As a result, psychological literature has recently started to focus on factors that might predict men’s interest in cosmetic surgery. However, this literature is still in its infancy.
The strongest and most common factors found to be related to cosmetic surgery consideration for men are age and sexual orientation. Homosexual men are more likely to consider cosmetic surgery than heterosexual men (de Vries et al., 2014), with homosexual men reporting higher desire for cosmetic surgery and body dissatisfaction (Frederick & Essayli, 2016). Both men and women undergo increased cosmetic surgery procedures in early-mid adulthood between the ages of 19–50 (International Society of Aesthetic Plastic Surgery, 2021; Tranter & Hanson, 2015). Multiple other social and demographic factors have been reported in the literature as contributing to men’s consideration of cosmetic surgery. Akin to women’s motivations for cosmetic surgery, some existing literature suggests that body dissatisfaction predicts men’s consideration of cosmetic surgery (Matera, et al., 2018; Swami et al. 2009; Wen et al., 2017). Peer influence, social comparisons (Jackson & Chen, 2015; Matera et al., 2018), and mirror-checking behaviours also appear to predict men’s cosmetic surgery interest (Frederick et al., 2007). Interestingly, results from a survey of over 1500 Australian men identified that men who had tertiary educations, were working class, and were employed in non-professional occupations were more interested in cosmetic surgery than their peers (Tranter & Hanson, 2015). This may in part reflect that some men engage in cosmetic surgery as a form of conspicuously demonstrating higher status through signalling that they have the money and time to do so (Folwarczny & Otterbring, 2021). In line with this theory, men in a recent study by Resenbaum and colleagues (2022) reported using cosmetic surgery to stay competitive in the dating scene (Rosenbaum et al., 2022). Taken together, these findings suggest that, overall, men may be motivated to undergo cosmetic surgery due to body image concerns and/or social comparisons.
Social Media and Cosmetic Surgery
Rapid development of internet engagement around the world is allowing more people to join social media than ever before (Kemp, 2021). One aspect of social media worth considering is the effect that social media is having on people’s relationships with appearance and body image. Social media frequently allows users to look at pictures and videos of others, share pictures of themselves, and curate an idealistic image of themselves (Kolesnyk et al., 2021; Kondakciu et al., 2022). The Tripartite Influence Model (Thompson et al., 2004) suggests that exposure to media (including social media) directly influences body image via social comparisons. This theory has been extensively supported by existing empirical evidence. For example, recent research found that increased Facebook engagement was associated with increased social comparisons (Ozimek & Bierhoff, 2020), and that women feel that they compare themselves more to others when using social media (Monks et al., 2021). Social comparisons were also found to moderate the positive relationship from frequency of women’s Instagram engagement to physical appearance anxiety and body dissatisfaction (Sherlock & Wagstaff, 2018). In line with these findings, social media engagement has been shown to predict women’s increased interest in cosmetic surgery (Hendrickse et al., 2017; Sherlock & Wagstaff, 2018). Given that existing literature suggests that men are motivated to undergo cosmetic surgery because of dissatisfied body image and social comparisons, it stands to reason that social media may influence men’s interest in cosmetic surgery similarly to women. To the authors’ knowledge, however, there is no literature to date that examines this phenomenon among men.
While there are limited studies exploring the direct link between social media engagement and cosmetic surgery for men, there has been research which explores the effect of social media on variables associated with cosmetic surgery interest. These studies suggest that men’s social media engagement positively predicts known cosmetic surgery correlates such as disordered eating, psychiatric issues, and body dissatisfaction (Abbas & Karadavut, 2017; Afsar, 2013; Chung et al., 2021; de Calheiros Velozo & Stauder, 2018; Lonergan et al., 2020; Lutzow et al., 2021; Mahon & Hevey, 2021; Ozimek & Bierhoff, 2020; Rambaree et al., 2020; Seidler et al., 2022; Walker et al., 2021). In sum, existing literature suggests that social media engagement is likely tied to their interest in cosmetic surgery.
Is All Social Media Made Equal?
While existing literature suggests social media engagement is likely to predict interest in cosmetic surgery, it also suggests that a certain way of engaging with social media is likely to elicit the social comparisons necessary to motivate social media users to consider cosmetic surgery. Gerson and colleague’s Active and Passive Use model (2017) deconstructs social media usage into Passive use, such as browsing; Active Non-social use, such as tagging and posting photos; and Active Social use, where people interact socially online such as chatting online or commenting on each other’s posts. Active and passive use of social media are being increasingly explored in research for their potentially differing effects on social-media users. One study about “selfies” (self-photographing) found that Active elements of selfie behaviour, such as selfie creation and posting, were generally unrelated to measures of loneliness, depression and anxiety, and life satisfaction. Passive use such as viewing the selfies of others, was related to lower wellbeing, increased negative affect, loneliness, and depression, likely through upward social comparison via comparing oneself to others. The relationship remains unclear, however, as another recent mixed-gender sample of Facebook users reported a positive relationship between Passive social media engagement (i.e., viewing, browsing, or consuming content) and social comparisons, but a negative relationship between Active social media engagement (i.e., creating and responding to content) and social comparisons, indicating that different ways of using social media might elicit different effects on social comparison (Nisar et al., 2019). This may be due to increased investment and need to curate one’s image in those who engage in Active use.
Verduyn and colleagues (Verduyn et al., 2022) have attempted to explain some of these contradictory findings through proposing that the Passive and Active Use model requires expansion and greater nuance to incorporate how the benefits of increased social capital and status do not arrive from all active use, but instead from active use where interactions are targeted (e.g., receiving a direct message rather than a public broadcast) and warm. If they are not, such as in instances of cyber-bullying, wellbeing may be harmed instead. Likewise, this revised model explains that passive use may only have harmful effects when upward social comparisons are made and when the content viewed is relevant to the viewer, rather than when passive use creates downward social comparisons which may boost the user’s confidence. As such, when exploring the effect social media engagement has on cosmetic surgery interest in men, we must also differentiate the effects of Active versus Passive engagement and consider Active and Passive in the context of gender and culture.
The Current Study
The literature to date has shown that there are multiple links between social media engagement, body image, and cosmetic surgery, as suggested by the Tripartite Influence Model of body image. There is, however, a gap in the literature in exploration of social media engagement and cosmetic surgery among men specifically. The aim of this study is to explore if social media engagement impacts men’s consideration of undergoing cosmetic surgery. Building upon repeated findings that active engagement with social media had a significant impact on body image and appearance attitudes (Abbas & Karadavut, 2017; Hendrickse et al., 2017; Kim & Chock, 2015; Meier & Gray, 2014), we hypothesise that Active Social media will positively predict men’s cosmetic surgery interest. As there has been minimal exploration of how Passive social media use impacts cosmetic surgery consideration for men, we examined this relationship in an exploratory way. That is, we did not test any specific hypotheses relating to passive social media use and men’s cosmetic surgery consideration.
Method
Ethics approval for conducting this study was obtained through the Monash University Human Research Ethics Commitee prior to recruitment (Project Number: 29797).
Participants
Participants were 311 men (Mage = 37.7) from the United States of America recruited via Cloud Research. The age range of responders was 18 to 75 years of age. The study was advertised on the Cloud Research website with an explanatory statement informing participants that this was a study examining men’s propensity for different personality traits and factors associated with body image. Participants were able to self-select if they wanted to complete the survey, and could then click on the advertisement to be taken to the participant information pack and consent forms. The majority of participants identified as White (including mixed-race White; 70.7%) and as either mostly or exclusively heterosexual (82.9%). Demographic information for race and sexual orientation are noted in Table 1. To be eligible to participate in this study, participants were required to be 18 years of age or older, identify as male, live in the United States of America, and be able to speak English fluently. Participants were limited to the United States of America to allow for more culturally homogenous data, given that there are cultural differences in appearance ideals and cosmetic surgery attitudes (Lowy et al., 2021; Thornborrow et al., 2020). There were no additional exclusion criteria. Participants were paid 1.89 USD for completing the questionnaire, which took approximately 25 min to complete the survey was only available to be completed online. This payment was distributed automatically through Cloud Research’s website. Screening for repetitive or unfinished responses was undertaken as part of data cleaning to remove responses completed by bots and/or inattentive participants. We acquired written consent from all participants.
Measures
Sexual Orientation
Sexual orientation was measured on a five-point version of the Kinsey Scale (Kinsey et al. 1948). This scale asked participants to rate their sexual orientation on a scale of one: exclusively homosexual/gay, to five: exclusively heterosexual/straight. A higher score represented stronger identification as heterosexual.
The “Consider” Subscale from the Acceptance of Cosmetic Surgery Scale
The first measure completed by participants was the “Consider” subscale from the Acceptance of Cosmetic Surgery Scale by Henderson-King and Henderson-King (2005, see Appendix 1). This subscale contained five items asking about participants’ likelihood to undergo cosmetic surgery, such as “I have sometimes thought about having cosmetic surgery”. Respondents rated their agreement with each statement on a Likert-type scale by selecting a rating from one (“strongly disagree”) to five (“strongly agree”). There was one reverse-scored item. Ratings were summed to calculate participants’ total scores, with higher scores indicating higher consideration of undergoing cosmetic surgery. This subscale demonstrated good reliability in the present study (α = 0.90).
Adapted Version of the Passive and Active Facebook Use Measure
The second questionnaire participants completed was an adapted version of Gerson and colleague’s Passive and Active Facebook Use Measure (2017, see Appendix 2). The original measure is comprised of 13 questions that ask participants to rate how often they engage in certain activities while using Facebook, however the adapted measure used in this study was reworded to ask about social media more broadly (i.e., to incorporate other social media platforms apart from Facebook). For example, the item “commenting (on statuses, wall posts, pictures, etc.)” was changed to “commenting (on posts, tweets, pictures, etc.)” and “chatting on Facebook chat” was changed to “chatting through direct messaging”. The questionnaire contains three subscales: Passive (four items), Active Non-Social (four items), and Active Social (five items), with the respective questions under each subscale being summed to provide a score for that domain. The Passive subscale included four items (α = 0.80) describing behaviours that are receptive only and include viewing or watching; for example, viewing photos, or viewing a friend’s profile. The Active Non-Social subscale contained four items (α = 0.88) identifying behaviours where the user posts or interacts with content on the platform, but not in a way that reinforces social relationships; for example, tagging photos, or creating and RSVPing to events. The Active Social subscale contains four items (α = 0.88) listing behaviours that involve an interaction between the user and someone in their social media audience which strengthens social connections; for example, commenting on the content of others or chatting through online chat. All subscales had good internal reliability in this study (Field, 2013). Participants were asked to rate how much time they spent doing certain activities on a five-point Likert-type scale from one (“never/0% of the time”) to five (“very frequently/100% of the time”). Scores were summed, with higher scores indicating higher engagement in the behavioural domain measured by each subscale.
Study Procedure
Following recruitment via Cloud Research, participants clicked on a link for the questionnaire which directed them to Qualtrics (https://www.qualtrics.com/). Initially participants were taken to an explanatory statement. Participants were next required to confirm that they met the eligibility criteria and provide consent. Participants who did not meet the eligibility criteria or did not consent were automatically directed to the end of the questionnaire. Next, demographic questions were presented. Participants then completed, in a randomised order, the Acceptance of Cosmetic Surgery Consider Subscale, the adapted Passive and Active Facebook Use Measure, and a series of other measures incorporated as part of a larger study on cosmetic surgery consideration in men. Within the Acceptance of Cosmetic Surgery Consider Subscale, participants were presented with an attention check that required them to select “strongly agree” to show they were paying attention. This was included as high rates of inattention in studies may inflate the risk of Type I Error (Abbey & Meloy, 2017). After completing all measures, participants were provided with a short debriefing statement containing a summarised statement about who to contact for further queries or distress.
Other Measures Within the Broader Study
Alongside data collection for the present study, additional data was collected for use in a larger project pertaining to cosmetic surgery. Participants completed scales that were not analysed within the present study. These included subscales from the Sociocultural Attitudes Towards Appearance Questionnaire-4 (Schaefer et al., 2017), the International Personality Item Pool (Goldberg et al., 2006), and the Contingencies of Self-Worth Scale (Crocker & Wolfe, 2001). These items all required respondents to provide answers using Likert scales, and contributed an additional 16, 20, and 15 items respectively.
Statistical Analyses and Power
Hierarchical multiple regression was planned a priori as the statistical test to examine our hypothesis while also controlling for age and sexual orientation, both known correlates with cosmetic surgery interest (Alleva et al., 2018; Li et al., 2016; Okumuş, 2020; Rosenbaum et al., 2022). In the hierarchical linear regression model, the demographic variables of age and sexual orientation were input into the first block. The second block of analysis had total scores on the Passive subscale added. In block three, Active Non-Social total scores were added. In block four, Active Social scores were added.
Necessary sample size was calculated for the regression model prior to data collection using G*Power version 3.1.9.7 (Faul et al. 2009). It was calculated that to have enough power (0.8) to detect a medium effect (f2 = 0.15) with an alpha level of 0.05 and five predictor variables, a sample size of 55 participants was needed. The calculation N ≥ 104 + m has also been recommended to calculate prerequisite sample size when testing individual predicters in multiple regression, where m is the number of predictor variables (Tabachnick & Fidell, 2019). For this research, this equation would be N ≥ 104 + 5, indicating the need for a minimum of 109 participants. Both sample size requirements were exceeded with inclusion of 311 participants and statistical power requirements were met.
Internal consistency was evaluated for each measure and is reported within the "Measures” section of this paper. Cronbach’s alphas for measures in the present study were considered acceptable if they fell above 0.70 and optimal if falling above 0.80 (Field, 2013).
Results
The datasets analysed during the current study are available in the Open Science Framework repository at https://osf.io/gmx6e/?view_only=b1faba2eb296482da621820dfc927117
Data Cleaning and Assumption Checking
Once the survey data were collected, they were imported into SPSS Statics Version 28 (SPSS). In preparation for analysis, the data were cleaned. Four hundred and three people responded to the online survey. A total of 89 respondents were excluded from analysis due to either declining to consent to their participation in the study, reporting that they did not meet the eligibility criteria, or failing to select the correct response for the attention check included (remaining N = 314). A further three cases were removed as one case’s metadata showed that those responses were a test by the software, one had not completed any measures beyond consent and eligibility questions, and one participant failed to answer any questions on the Passive and Active Use Measure. The data were also screened for bot activity (automated answers from online programs rather than true respondents) using common signs noted by Cloud Research; for example, giving the same answer across all measures within the study. No responses demonstrated trends which indicated bot responses. This resulted in a final sample size of 311 participants. There was no missing data for these participants apart from one participant choosing not to disclose his age.
Statistical assumptions for hierarchical regression were tested. Assumptions pertaining to linearity, multicollinearity, outliers, and influential points were met. One participant’s age was considered an outlier but was ultimately retained. Residuals were tested for the assumptions of independence of errors, homoscedasticity, and normal distribution. All assumptions were met. Given the inclusion of an outlier in our study, bootstrapping was utilised in the regression analysis to ensure that results were robust.
Preliminary Analysis
Mean scores, standard deviations, and Pearson’s correlations were calculated for all variables within the hierarchical multiple regression model (see Table 2).
Significant correlations existed between many of the variables. Each predictor variable had a significant positive correlation with the Consider subscale, such that all three social media behaviours were correlated with cosmetic surgery interest. Sexual orientation was also significantly positively correlated with the Consider subscale. Age was the only factor which did not show a statistically significant correlation.
Inferential Statistics
A four-block hierarchical multiple regression model was run using total scores on the Consider subscale as the dependent variable. This allowed for examination of the effect and significance of each factor independently as it was added to the model. Following adding age and sexual orientation to the model, as these were variables being separated out to be controlled for, Passive use was selected to be added in the second step, followed by Active Non-social use, and then Active Social use. This order was selected to match the order of engagement in Passive and Active behaviours temporally while using social media. It was considered that during social media use, it was likely Passive use would occur first from inherently being exposed to the content of others from the time of logging in to social media, while Active use would likely occur following this. Regression coefficient outcomes from the bootstrapped model are outlined below in Table 3, with overall results for the models in the regression shown in Table 4.
Results from the first block of analysis revealed that age and sexual orientation together had a significant linear relationship (F(2,307) = 6.52, p < 0.05) and significantly predicted cosmetic surgery consideration (p < 0.05). These variables, however, only had small correlations with cosmetic surgery consideration and explained only 4% of the change in cosmetic surgery consideration. These factors were then also added into all additional blocks to control for their effect on consideration of cosmetic surgery and allow for examination of social media use independently.
The second block including age, sexual orientation, and total scores on the Passive subscale together significantly predicted cosmetic surgery consideration (F(1,306) = 8.85, p < 0.05). The results revealed that there was a significant increase in cosmetic surgery consideration with increased passive social media use. There was a small yet significant positive relationship between Passive use and consideration of cosmetic surgery (p < 0.05, 95% CI [0.12, 0.49]), with each increasing point on the on the Passive subscale corresponding to a 0.32 increase in total score within the 25 points available for the Consider subscale. Passive social media use explained approximately 4% of the variance in scores on cosmetic surgery consideration and had the largest unique relationship with cosmetic surgery consideration (sr2=0.04).
Blocks 3 and 4, which added in Active Social and Active Non-social were not significantly predictive above and beyond the previous models (p > 0.05).
Discussion
Cosmetic surgery is becoming increasingly popular around the world, with a rising number of men undergoing cosmetic surgery procedures in the twenty-first century (The International Society of Aesthetic Plastic Surgery, 2020). One of the factors previously found to have an impact on cosmetic surgery interest in women is social media engagement; however, this is an under-researched phenomenon in men. As social media engagement continues to grow at a rapid pace (Kemp, 2021) it is timely to gain a better understanding of the way social media may influence men’s body image and steer them towards cosmetic surgery (Abbas & Karadavut, 2017). As such, the aim of this study was to explore if social media engagement influenced men’s interest in undergoing cosmetic surgery. We hypothesised that Active Social social media engagement would significantly positively predict men’s interest after controlling for age and sexual orientation. This hypothesis was not supported by our findings. Instead, this research found that higher passive social media engagement was significantly related to an increase in consideration of cosmetic surgery.
These findings contribute to the mixed picture of which exists in the literature about social media and appearance attitudes, although it is worth noting that previous research is strongly focussed on female populations with little investigation into adult men and their relationships with social media and appearance (Hendrickse et al., 2017; McLean et al., 2015). Nevertheless, the evidence base for women still provides useful guidance given the gap in the literature. Active social media behaviours such as commenting and ‘liking’ (Kim & Chock, 2015) and editing photos (McLean et al., 2015; Meier & Gray, 2014) have previously been found to be significantly related to body dissatisfaction and appearance behaviours for women. Conversely, findings from the present study implicate Passive social media engagement in men’s interest in cosmetic surgery. This suggests that perhaps the way social media influences men’s body image is unique and different from the ways it impacts women’s body image.
The positive correlations found in this research indicated that all social media behaviours were related with cosmetic surgery consideration for men; however, the finding that only Passive engagement was a significant predictor in the full hierarchical regression model suggests that neither type of active behaviour had an effect over and above that of Passive engagement. These results suggest that while both Active and Passive social media use might impact men’s body image, Passive use is alone enough to encourage men to undergo cosmetic surgery. Existing literature has demonstrated that, for all genders, simply viewing profile pictures is enough to trigger social comparisons with viewing of attractive profile pictures on social media resulting in more negative body image (Haferkamp & Krämer, 2011). Thus, it might be the case that for men this initial ‘blow’ to body image is enough to trigger a greater interest in cosmetic surgery.
One alternate explanation as to why only passive social media use predicted cosmetic surgery interest is that both passive social media use and cosmetic surgery interest may be uniquely predicted by a third underlying, extraneous variable. Self-esteem has been established as a predictive factor for engagement in cosmetic surgery, such that women with lower self-esteem are drawn to surgery (al Ghadeer et al., 2021; Yoon & Kim, 2020). Similarly, preliminary research has reported a relationship between self-esteem social media engagement in mixed-gender samples (Doğan & Çolak, 2016; Nisar et al., 2019; Ozimek & Bierhoff, 2020), such that those lower in self-esteem are drawn to passive social media engagement while those with higher self-esteem are more likely to be active social media users. Those with higher self-esteem may be more confident posting on social media and engaging with others content, while also being less likely to experience poor body image. In sum, self-esteem may act as an extraneous variable explaining the relationship between passive social media use and cosmetic surgery interest.
Limitations and Future Directions
This research provides important new information in exploring the relationship between social media engagement and cosmetic surgery consideration for men, a relationship which has not yet been thoroughly investigated. It contributes to the gap that exists in the literature for men in comparison to the research that exists for female populations. However, it was not without limitations.
For example, participants in this study were exclusively from the United States of America. As appearance attitudes and cosmetic surgery vary between cultures and generations (Burke et al., 2010; Lowy et al., 2021; Rodgers et al., 2019, 2020), the findings of this research are mostly limited to men within the United States of America or from other western nations, and thus lack generalisability. Future studies would benefit from accessing populations which are more diverse to allow for a more representative sample and replications of this study with comparisons between cultural groups. These findings are also limited to adult men. Cultural differences between generations in respect to appearance ideals and social media exposure would likely result in different results for adolescents who may have different attitudes with appearance and social media (Bengtsson & Johansson, 2018). Thus, future studies might explore how social media engagement predicts cosmetic surgery interest among adolescent boys; arguably, a more at-risk population.
This sample was predominantly heterosexual, reflecting higher rates of heterosexuality in the global population (Ipsos, 2021). While previous research indicates that homosexual men have higher interest in cosmetic surgery than the heterosexual male population, cosmetic surgery use among all men (queer and heterosexual) is on the rise. Thus, it is important that we examine (i) cosmetic surgery experiences for all men and (ii) how these experiences may be influenced by sexual orientation.
This study would also have benefited from utilising additional measures to capture richer data, such as total time spent engaging in passive and active behaviours, the social media platforms being used, or a breakdown of the type of content being viewed while using social media. A lack of other measures of social media engagement, for example time online or emotional intensity while using social media, means that this research was not able to explore any possible covariates of social media behaviours. In future research, it is recommended that these additional measures be incorporated to address this limitation and to contribute richer information to an emerging area of research. Additionally, the inclusion of other measures such as the Contingencies of Self-Worth Scale and Sociocultural Attitudes Towards Appearance Questionnaire had the potential to influence responses from participants by priming them to consider their feelings of self-worth and feelings about their appearance before answering the Passive and Active Use Measure or the Acceptance of Cosmetic Surgery Consideration subscale. The measures were presented online in a randomised order in an attempt to minimise any systematic priming that may occur, however it is possible that this may affect the results by increasing the salience of any dissatisfaction with appearance. Additionally, it is possible that the increased time required to complete all of the measures may have resulted in increased fatigue or distractibility for participants when compared to if they had only completed measures specific to this paper, resulting in reduced validity in the data. However, to account for this limitation, we randomised the order in which our questionnaire scales and items were presented. Future research may like to separate data collection in future to allow for greater attention on social media use and cosmetic surgery consideration.
The limited use of a self-report measure for social media use also means these results are subject to erroneous reports about social media engagement from the participants. Time spent on social media has been found to be under-estimated in self-report measures compared to objective measures (Verbeij et al., 2021), and so it is also possible that engagement in social media behaviours may also be underestimated in self-report studies. Future research may wish to implement Ecological Momentary Assessment methodologies.
A final limitation to consider is the possibility that only utilising online methods for recruitment and survey completion for a study examining online behaviours may contribute to sampling bias. It is possible that those with an interest in internet engagement or in appearance and cosmetic surgery may be more interested in responding to a survey such as this one. There is evidence that overall internet engagement may also affect body image and eating concerns (Rodgers & Melioli, 2016), and it is of concern that capturing participants through exclusively online recruitment may result in a participant pool with higher general internet engagement and higher exposure to general online media than the general population. The current sample showed normal levels of skewness and kurtosis on adapted Passive and Active Engagement Measure scores, indicating that there was not an overt bias towards high rates of engagement of social media. Nevertheless, as this study did not measure overall time on social media or total time spent online, it is still worthwhile to consider if participants’ quantity of time online may have been correlated with social media engagement, and if so, how the results may have been influenced by a negative relationship between internet engagement and body image (Rodgers & Melioli, 2016). Recruiting both online and offline in future research would account for this limitation.
Future research would be able to address many of these limitations and also further explore some of the potential explanations and mechanisms underlying these relationships. Examination of the potential moderating or mediating role of self-esteem is one avenue for future research to investigate. Additionally, incorporation of the extended Active–Passive Use model (Verduyn et al., 2022), through measuring not only Active and Passive factors but also measuring or manipulating how warm and targeted interactions are, may further explain why mixed findings are found between studies and contribute to an expansion of the original Active–Passive use model.
Implications of Findings
The findings of this research have important implications in a time when social media engagement is growing (Kemp, 2021). Clinically, this research indicates that increased passive media engagement may trigger men’s consideration of cosmetic surgery. While this research was not experimental and cannot establish a causal relationship, theoretical foundations such as the Tripartite Influence Model suggest that exposure to images of others while on social media could result in decreased body satisfaction and increased desire for cosmetic surgery. As dissatisfaction with appearance can result in risk of depression, eating disorders, and surgical complications from elective cosmetic surgery (Kaoutzanis et al., 2018; McLean et al., 2015; Ojubele et al., 2020), the findings of this research indicate that it may be useful to encourage men to reduce time spent passively browsing social media platforms if they are experiencing body dissatisfaction or if they want to trial non-surgical strategies to reduce their body dissatisfaction prior to elective cosmetic surgery. It is also worthwhile to consider if social media companies can take positive steps to promote balanced social media engagement and self-monitoring for men; for example, through offering alerts in response to high amounts of time spent passively browsing. While to date much attention has been paid to the negative effects social media has on women’s body image, men have been previously neglected in this space. We feel this study takes a valuable step towards opening much needed dialogue in the men’s mental health space.
Conclusions
This research contributes important findings in understanding gender, social media engagement, and cosmetic surgery. Passive engagement of social media was found to be significantly related to cosmetic surgery consideration for men, while Active Social and Active Non-Social engagement were not. Gender differences in how social media is related to cosmetic surgery consideration highlight the need for research and support unique to male populations. Ongoing exploratory and experimental research can build further understanding of the causal pathways between these variables while allowing for testing of fit to already established theories such as social comparison theory. Future research building upon this study will provide support for men in developing positive body image as well as additional non-surgical strategies to increase psychosocial wellbeing related to appearance.
Availability of Data and Materials
The datasets analysed during the current study are available in the Open Science Framework repository at https://osf.io/gmx6e/?view_only=b1faba2eb296482da621820dfc927117.
References
Abbas, O. L., & Karadavut, U. (2017). Analysis of the factors affecting men’s attitudes toward cosmetic surgery: Body image, media exposure, social network engagement, masculine gender role stress and religious attitudes. Aesthetic Plastic Surgery, 41(6), 1454–1462. https://doi.org/10.1007/s00266-017-0882-3
Abbey, J. D., & Meloy, M. G. (2017). Attention by design: using attention checks to detect inattentive respondents and improve data quality. Journal of Operations Management, 63–70. https://doi.org/10.1016/j.jom.2017.06.001
Afsar, B. (2013). The relation between Internet and social media engagement and the demographic and clinical parameters, quality of life, depression, cognitive function and sleep quality in hemodialysis patients. General Hospital Psychiatry, 35(6), 625–630. https://doi.org/10.1016/j.genhosppsych.2013.05.001
al Ghadeer, H. A., Alalwan, M. A., Alamer, M. A., Alali, F. J., Alkhars, G. A., Alabdrabulrida, S. A., al Shabaan, H. R., Buhlaigah, A. M., Alhewishel, M. A., & Alabdrabalnabi, H. A. (2021). Impact of self-esteem and self-perceived body image on the acceptance of cosmetic surgery. Cureus, 13(10), 1–11. https://doi.org/10.7759/cureus.18825
Alleva, J. M., Paraskeva, N., Craddock, N., & Diedrichs, P. C. (2018). Body appreciation in British men: Correlates and variation across sexual orientation. Body Image, 27, 169–178. https://doi.org/10.1016/j.bodyim.2018.09.004
Bengtsson, S., & Johansson, B. (2018). Media micro-generations: How new technologies change our media morality. Nordicom Review, 39(2), 95–110. https://doi.org/10.2478/nor-2018-0014
Burke, M. A., Heiland, F. W., & Nadler, C. M. (2010). From “overweight” to “about right”: Evidence of a generational shift in body weight norms. Obesity, 18(6), 1226–1234. https://doi.org/10.1038/oby.2009.369
Chung, A., Vieira, D., Donley, T., Tan, N., Jean-Louis, G., Gouley, K. K., & Seixas, A. (2021). Adolescent peer influence on eating behaviors via social media: Scoping review. Journal of Medical Internet Research, 23(6), 1–12. https://doi.org/10.2196/19697
Crocker, J., & Wolfe, C. T. (2001). Contingencies of self-worth. Psychological Review, 108(3), 593–623. https://doi.org/10.1037/0033-295X.108.3.593
de Calheiros Velozo, J., & Stauder, J. E. A. (2018). Exploring social media engagement as a composite construct to understand its relation to mental health: A pilot study on adolescents. Children and Youth Services Review, 91, 398–402. https://doi.org/10.1016/j.childyouth.2018.06.039
de Vries, D. A., Peter, J., Nikken, P., & de Graaf, H. (2014). The effect of social network site engagement on appearance investment and desire for cosmetic surgery among adolescent boys and girls. Sex Roles, 71, 283–295. https://doi.org/10.1007/s11199-014-0412-6
Doğan, U., & Çolak, T. S. (2016). Self-concealment, social network sites usage, social appearance anxiety, loneliness of high school students: A model testing. Journal of Education and Training Studies, 4(6), 176–183. https://doi.org/10.11114/jets.v4i6.1420
Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149
Field, A. (2013). Discovering statistics using IBM SPSS statistics. In Statistics (5th Editio, Vol. 58). Sage Publications. https://online.vitalsource.com/#/books/9781526422989/cfi/434!/4/4@0.00:16.5
Folwarczny, M., & Otterbring, T. (2021). Cosmetic surgeries as conspicuous consumption: disclosing information about having undergone cosmetic surgery signals social status. Psychology & Psychiatry Journal, 305. https://doi.org/10.31234/osf.io/n4p37
Frederick, D. A., & Essayli, J. H. (2016). “Male body image: the roles of sexual orientation and body mass index across five national U.S. studies”: correction to Frederick and Essayli (2016). Psychology of Men & Masculinity, 17(4), 351–351. https://doi.org/10.1037/men0000078
Frederick, D. A., Lever, J., & Peplau, L. A. (2007). Interest in cosmetic surgery and body image: Views of men and women across the lifespan. Plastic and Reconstructive Surgery, 120(5), 1407–1415. https://doi.org/10.1097/01.prs.0000279375.26157.64
Gerson, J., Plagnol, A. C., & Corr, P. J. (2017). Passive and Active Facebook Engagement Measure (PAUM): Validation and relationship to the Reinforcement Sensitivity Theory. Personality and Individual Differences, 117, 81–90. https://doi.org/10.1016/j.paid.2017.05.034
Goldberg, L. R., Johnson, J. A., Eber, H. W., Hogan, R., Ashton, M. C., Cloninger, C. R., & Gough, H. G. (2006). The international personality item pool and the future of public-domain personality measures. Journal of Research in Personality, 40, 84. https://doi.org/10.1016/j.jrp.2005.08.007
Haferkamp, N., & Krämer, N. C. (2011). Social comparison 2.0: Examining the effects of online profiles on social-networking sites. https://Home.Liebertpub.Com/Cyber, 14(5), 309–314. https://doi.org/10.1089/CYBER.2010.0120
Henderson-King, D., & Henderson-King, E. (2005). Acceptance of cosmetic surgery: Scale development and validation. Body Image, 2(2), 137–149. https://doi.org/10.1016/j.bodyim.2005.03.003
Hendrickse, J., Arpan, L. M., Clayton, R. B., & Ridgway, J. L. (2017). Instagram and college women’s body image: Investigating the roles of appearance-related comparisons and intrasexual competition. Computers in Human Behavior, 74, 92–100. https://doi.org/10.1016/j.chb.2017.04.027
International Society of Aesthetic Plastic Surgery. (2021). ISAPS international survey on aesthetic procedures performed in 2020. www.isaps.org
Ipsos. (2021). LGBT+ pride 2021 global survey: A 27 country Ipsos survey. https://www.ipsos.com/en/ipsos-lgbt-pride-2021-global-survey
Jackson, T., & Chen, H. (2015). Predictors of cosmetic surgery consideration among young Chinese women and men. Sex Roles, 73, 214–230. https://doi.org/10.1007/s11199-015-0514-9
Kaoutzanis, C., Winocour, J., Yeslev, M., Gupta, V., Asokan, I., Roostaeian, J., Grotting, J. C., & Higdon, K. K. (2018). Aesthetic surgical procedures in men: Major complications and associated risk factors. Aesthetic Surgery Journal, 38(4), 429–441. https://doi.org/10.1093/asj/sjx161
Kemp, S. (2021). Digital 2021 April statshot report. Datareportal. https://datareportal.com/reports/digital-2021-april-global-statshot
Kim, J. W., & Chock, T. M. (2015). Body image 2.0: Associations between social grooming on Facebook and body image concerns. Computers in Human Behavior, 48, 331–339. https://doi.org/10.1016/j.chb.2015.01.009
Kinsey, A. C., Pomeroy, W. B., & Martin, C. (1948). Sexual behavior in the human male. Saunders.
Kolesnyk, D., de Jong, M. G., & Pieters, R. (2021). Gender gaps in deceptive self-presentation on social-media platforms vary with gender equality: A multinational investigation. Psychological Science, 32(12), 1952–1964. https://doi.org/10.1177/09567976211016395
Kondakciu, K., Souto, M., & Zayer, L. T. (2022). Self-presentation and gender on social media: An exploration of the expression of “authentic selves.” Qualitative Market Research, 25(1), 80–99. https://doi.org/10.1108/QMR-03-2021-0039
Li, J., Li, Q., Zhou, B., Gao, Y., Ma, J., & Li, J. (2016). Predictive factors for cosmetic surgery: A hospital-based investigation. Springerplus, 5(1), 1543. https://doi.org/10.1186/s40064-016-3188-z
Lonergan, A. R., Bussey, K., Fardouly, J., Griffiths, S., Murray, S. B., Hay, P., Mond, J., Trompeter, N., & Mitchison, D. (2020). Protect me from my selfie: Examining the association between photo-based social media behaviors and self-reported eating disorders in adolescence. International Journal of Eating Disorders, 53(5), 755–766. https://doi.org/10.1002/eat.23256
Lowy, A. S., Rodgers, R. F., Franko, D. L., Pluhar, E., & Webb, J. B. (2021). Body image and internalization of appearance ideals in Black women: An update and call for culturally-sensitive research. Body Image, 39, 313–327. https://doi.org/10.1016/j.bodyim.2021.10.005
Lutzow, C. A., Hubbard, G., Giscombe, C., & Greenberg, L. (2021). Practice change: Social Media Screening Questionnaire to identify high-risk adult psychiatric patients. Perspectives in Psychiatric Care, 57(3), 1145–1149. https://doi.org/10.1111/ppc.12669
Mahon, C., & Hevey, D. (2021). Processing body image on social media: gender differences in adolescent boys’ and girls’ agency and active coping. Frontiers in Psychology, 12, Article 626763. https://doi.org/10.3389/fpsyg.2021.626763
Matera, C., Nerini, A., & Stefanile, C. (2018). Why are men interested in cosmetic surgery procedures? Examining the role of different forms of peer influence, social comparison, internalization, and body dissatisfaction. Body Image, 26, 74–77. https://doi.org/10.1016/j.bodyim.2018.06.003
McLean, S. A., Paxton, S. J., Wertheim, E. H., & Masters, J. (2015). Photoshopping the selfie: Self photo editing and photo investment are associated with body dissatisfaction in adolescent girls. International Journal of Eating Disorders, 48(8), 1132–1140. https://doi.org/10.1002/eat.22449
Meier, E. P., & Gray, J. (2014). Facebook photo activity associated with body image disturbance in adolescent girls. Cyberpsychology, Behavior, and Social Networking, 17(4), 199–206. https://doi.org/10.1089/cyber.2013.0305
Monks, H., Costello, L., Dare, J., & Reid Boyd, E. (2021). “We’re continually comparing ourselves to something”: Navigating body image, media, and social media ideals at the nexus of appearance, health, and wellness. Sex Roles, 84(3–4), 221–237. https://doi.org/10.1007/s11199-020-01162-w
Nisar, T. M., Prabhakar, G., Ilavarasan, P. V., & Baabdullah, A. M. (2019). Facebook usage and mental health: an empirical study of role of non-directional social comparisons in the UK. International Journal of Information Management, 48(September 2018), 53–62. https://doi.org/10.1016/j.ijinfomgt.2019.01.017
Ojubele, O., Tanski, S., White, S., & Bruce, M. (2020). The role of body dissatisfaction in mental health outcomes of adolescents. Journal of Adolescent Health, 66, S95–S96. https://doi.org/10.1016/j.jadohealth.2019.11.191
Okumuş, A. (2020). A qualitative assessment of women’s perspectives and experience of cosmetic surgery. European Journal of Plastic Surgery, 43(4), 467–474. https://doi.org/10.1007/s00238-020-01623-1
Ozimek, P., & Bierhoff, H. W. (2020). All my online-friends are better than me: Three studies about ability-based comparative social media engagement, self-esteem, and depressive tendencies. Behaviour and Information Technology, 39(10), 1110–1123. https://doi.org/10.1080/0144929X.2019.1642385
Qualtrics. (n.d.). Fraud detection. Retrieved September 25, 2021, from https://www.qualtrics.com/support/survey-platform/survey-module/survey-checker/fraud-detection/#BotDetection
Rambaree, K., Mousavi, F., Magnusson, P., & Willmer, M. (2020). Youth health, gender, and social media: Mauritius as a global place. Cogent Social Sciences, 6(1), Article 1774140. https://doi.org/10.1080/23311886.2020.1774140
Rodgers, R. F., Campagna, J., & Attawala, R. (2019). Stereotypes of physical attractiveness and social influences: The heritage and vision of Dr. Thomas Cash. Body Image, 31, 273–279. https://doi.org/10.1016/j.bodyim.2019.01.010
Rodgers, R. F., Fuller-Tyszkiewicz, M., Markey, C., Granero-Gallegos, A., Sicilia, A., Caltabiano, M., Blackburns, M. E., Hayami-Chisuwa, N., Strodl, E., Aimé, A., Dion, J., & lo Coco, G., Gullo, S., McCabe, M., Mellor, D., Castelnuovo, G., Probst, M., Manzoni, G., Begin, C., … Maïano, C. (2020). Psychometric properties of measures of sociocultural influence and internalization of appearance ideals across eight countries. Body Image, 35, 300–315. https://doi.org/10.1016/j.bodyim.2020.09.016
Rodgers, R. F., & Melioli, T. (2016). The relationship between body image concerns, eating disorders and internet engagement, part I: A review of empirical support. Adolescent Research Review, 1(2), 95–119. https://doi.org/10.1007/s40894-015-0016-6
Rosenbaum, M. S., Jensen, J., & Contreras-Ramírez, G. (2022). Forever young: Gay men and cosmetic medical treatments. Journal of Services Marketing, 36(1), 9–13. https://doi.org/10.1108/JSM-02-2021-0052
Schaefer, L. M., Harriger, J. A., Heinberg, L. J., Soderberg, T., & Kevin Thompson, J. (2017). Development and validation of the sociocultural attitudes towards appearance questionnaire-4-revised (SATAQ-4R). The International Journal of Eating Disorders, 50(2), 104–117. https://doi.org/10.1002/EAT.22590
Seidler, Z. E., Wilson, M. J., Rice, S. M., Kealy, D., Oliffe, J. L., & Ogrodniczuk, J. S. (2022). Virtual connection, real support? A study of loneliness, time on social media and psychological distress among men. International Journal of Social Psychiatry, 68(2), 288–293. https://doi.org/10.1177/0020764020983836
Sherlock, M., & Wagstaff, D. L. (2018). Exploring the relationship between frequency of Instagram engagement, exposure to idealized images, and psychological well-being in women. Psychology of Popular Media Culture, 8(4), 482–490. https://doi.org/10.1037/ppm0000182
Swami, V., Chamorro-Premuzic, T., Bridges, S., & Furnham, A. (2009). Acceptance of cosmetic surgery: Personality and individual difference predictors. Body Image, 6(1), 7–13. https://doi.org/10.1016/j.bodyim.2008.09.004
Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (Seventh Ed). Pearson Education.
The International Society of Aesthetic Plastic Surgery. (2020). ISAPS international survey on aesthetic/cosmetic procedures performed in 2019. www.isaps.org
Thompson, J. K., Heinberg, L. J., Altabe, M., & Tantleff-Dunn, S. (2004). Exacting beauty: Theory, assessment, and treatment of body image disturbance. American Psychological Association. https://doi.org/10.1037/10312-000
Thornborrow, T., Onwuegbusi, T., Mohamed, S., Boothroyd, L. G., & Tovée, M. J. (2020). Muscles and the media: a natural experiment across cultures in men’s body image. Frontiers in Psychology, 11, Article 495. https://doi.org/10.3389/fpsyg.2020.00495
Tranter, B., & Hanson, D. (2015). The social bases of cosmetic surgery in Australia. Journal of Sociology, 51(2), 189–206. https://doi.org/10.1177/1440783313487812
University of Washington. (2004). F-Tables. Retrieved March 28, 2023, from https://faculty.washington.edu/heagerty/Books/Biostatistics/TABLES/F-Tables/
Verbeij, T., Pouwels, J. L., Beyens, I., & Valkenburg, P. M. (2021). The accuracy and validity of self-reported social media engagement measures among adolescents. Computers in Human Behavior Reports, 3, Article 100090. https://doi.org/10.1016/j.chbr.2021.100090
Verduyn, P., Gugushvili, N., & Kross, E. (2022). Do social networking sites influence well-being? The extended active-passive model. Current Directions in Psychological Science, 31(1), 62–68. https://doi.org/10.1177/09637214211053637
Walker, C. E., Krumhuber, E. G., Dayan, S., & Furnham, A. (2021). Effects of social media engagement on desire for cosmetic surgery among young women. Current Psychology, 40(7), 3355–3364. https://doi.org/10.1007/s12144-019-00282-1
Wen, N., Chia, S. C., & Xiaoming, H. (2017). Does gender matter? Testing the influence of presumed media influence on young people’s attitudes toward cosmetic surgery. Sex Roles, 76, 436–447. https://doi.org/10.1007/s11199-016-0680-4
Yoon, S., & Kim, Y. A. (2020). Cosmetic surgery and self-esteem in South Korea: A systematic review and meta-analysis. Aesthetic Plastic Surgery, 44(1), 229–238. https://doi.org/10.1007/s00266-019-01515-1
Funding
Open Access funding enabled and organized by CAUL and its Member Institutions. $200 was provided to the first author by Monash University as part of the Graduate Diploma of Psychology (Advanced) program. Recruitment was combined with three other student projects, resulting in a total recruitment fund of $800 provided by Monash University. No funding was received to assist with the preparation of this manuscript.
Author information
Authors and Affiliations
Contributions
The current research project was conducted by Sian Truashein, under the supervision of Sarah Bonell while enrolled in the Graduate Diploma of Psychology (Advanced) at Monash University. The ethics application was completed by Sarah Bonell with the assistance of Sian Truasheim and was approved by Monash University Human Research Ethics Committee. The specific aims and hypotheses were determined by Sian Truasheim with input provided by Sarah Bonell. The study design, including choice of measures, was determined by Sian Truasheim, Robert Wilesmith, Karnik Shah, Catherine Suriarachi, and Sarah Bonell. Sian Truasheim, Robert Wilesmith, Karnik Shah, Catherine Suriarachi, and Sarah Bonell were responsible for data collection. Data analysis was conducted by the Sian Truasheim with support and guidance provided by Sarah Bonell and Rhys Lucky. The author prepared the final report and drafts were commented on by Sarah Bonell, Rhys Lucky, Lauren Shaw, Prem Sebastian. The written material presented here is the author’s own work.
Corresponding author
Ethics declarations
Ethics Approval and Consent to Participate
All participants gave informed consent to participate in this study and were de-identified during data analysis.
Conflict of Interests
The authors declare that they have no conflict of interest.
Research Involving Human Participants
This study was approved by the Monash University Human Research Ethics Committee (Project Number: 29797).
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendices
Appendix 1. Acceptance of Cosmetic Surgery Scale–Consider Subscale
Scored from 1–Strong disagreement to 5–Strong agreement. Question five is reverse scored.
Item | 1 | 2 | 3 | 4 | 5 |
---|---|---|---|---|---|
1. In the future, I could end up having some kind of cosmetic surgery | |||||
2. If I could have a surgical procedure done for free I would consider trying cosmetic surgery | |||||
3. If I knew there would be no negative side effects or pain, I would like to try cosmetic surgery | |||||
4. I have sometimes thought about having cosmetic surgery | |||||
5. I would never have any kind of plastic surgery |
Appendix 2. Passive and Active Facebook Engagement Measure–Adapted
Scored from 1–never (0% of the time) to 5–very frequently (100% of the time).
Item | 1 | 2 | 3 | 4 | 5 |
---|---|---|---|---|---|
1. Posting status updates | |||||
2. Commenting (on posts, tweets, pictures, etc.) | |||||
3. Chatting through direct messaging | |||||
4. Checking to see what someone is up to | |||||
5. Creating or RSVPing to events | |||||
6. Posting photos | |||||
7. Tagging photos | |||||
8. Viewing photos | |||||
9. Posting videos | |||||
10. Tagging videos | |||||
11. Browsing passively (without liking or commenting on anything) | |||||
12. Browsing actively (liking and commenting on posts, pictures and updates) | |||||
13. Looking through my friends' profiles |
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Truasheim, S., Bonell, S. Does Social Media Engagement Influence Men’s Consideration of Cosmetic Surgery?. J. technol. behav. sci. 9, 191–203 (2024). https://doi.org/10.1007/s41347-023-00317-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41347-023-00317-2