Skip to main content
NCBI home page
Clinical Neuropsychiatry logoLink to Clinical Neuropsychiatry
. 2025 Jun;22(3):243–252. doi: 10.36131/cnfioritieditore20250307

“Too Good to be True”: An Explorative Study of Photo Manipulation, Body Image Dissatisfaction and Critical Thinking

Amelia Rizzo 1,§, Martina Barbera 2,§, Fuat Aydoğdu 3, Müge Akbağ 4
PMCID: PMC12302813  PMID: 40735380

Abstract

Objective

Several studies have demonstrated an increase in body dissatisfaction following the use of photo filters; however, the role of intervening factors such as critical thinking has often been overlooked. The aim of this research was to investigate the relationships between photographic manipulation, body dissatisfaction, and critical thinking, taking into account the mediating role of critical thinking.

Method

A convenience sample of 500 Italian-speaking subjects (44% male; 56% female) aged between 18 and 60 years (Mage = 25.7; SD = 17.8) participated at the study. The instruments used were: (1) the Revised Photo Manipulation Scale; (2) the Body Uneasiness Test; (3) the Fake Subscale of the Critical Processing of Beauty Images Scale; (4) a specifically constructed task for recognizing photographic manipulation (5) three control questions.

Results

The results obtained show a positive relationship between the use of photo manipulation and body image dissatisfaction. Critical thinking has a partial mediating role in the relationship between body image dissatisfaction and photo manipulation.

Conclusions

To delve deeper into the findings, the participants’ ability to correctly classify natural and filtered photos have been described. Clinical and research implications are discussed.

Keywords: digital body image, photo manipulation, critical thinking, selfie

1. Introduction

Taking selfies and using filters to enhance one's own image has become a daily habit for millions of people. According to data from the Digital Global Overview (Starri, 2024), 60% of the world's population uses social media; it means that approximately 4.76 billion users are exposed daily to social profiles characterized by perfect bodies. Rojo et al. (2023) have demonstrated, based on the available literature (Fardouly et al., 2015; Karsay et al., 2017), how, the excessive exposure to contents related to physical appearance on social media, contributes to the development of behaviors focused on appearance, like constantly examining one's own body: this can manifest as a form of self-objectification. Self-objectification refers to the tendency to view and evaluate one's own body from an external observer's perspective, prioritizing its appearance over its functionality or other intrinsic attributes. This construct is linked to societal and media-driven pressures that promote idealized beauty standards, often leading individuals to internalize these expectations and excessively focus on their physical presentation (Fredrickson & Roberts, 1997). Furthermore, recent research has explored the psychological characteristics and behaviors associated with taking selfies, such as narcissistic tendencies and body dissatisfaction (Rojo et al., 2023). These behaviors can escalate into problematic patterns, including compulsive selfie-taking and appearance-enhancing practices, which further reinforce self-objectification; the study by Giordano et al. (2019) sheds light on how such practices intertwine with broader psychological concerns, offering valuable insights into the underlying mechanisms.

Indeed, research indicates that there is a motivation, such as preparing, applying makeup, and dressing up before sharing photos, which implies a significant time investment in preparing for a selfie. Furthermore, photos are often deleted when they do not receive an adequate number of likes after several posts.

An increasing number of studies, although not entirely consistent, have highlighted how the use of social media can negatively impact body image and self-esteem (Fardouly & Vartanian, 2015; Mingoia et al., 2017). However, while some studies have supported a path that predicts an increase in body dissatisfaction following exposure to social media content (Fardouly & Holland, 2018; Holland & Tiggemann, 2016; Tamplin et al., 2018), others (Rousseau et al., 2017; Saiphoo & Vahedi, 2019) have suggested the reverse relationship, namely that high levels of body dissatisfaction can lead to greater engagement on social platforms.

This latter position is supported by a study conducted by Bossen and Kottasz (2020), applying the Uses and Gratifications Theory (Blumler & Katz, 1974), which suggests that users actively select the type, quantity, and nature of media they consume.

The current trends and challenges on social media serve as triggers that reinforce the imposed perception of beauty (Choukas-Bradley et al., 2020). For instance, practices like beauty standards mimicry, where individuals imitate or emulate the appearance of celebrities or influencers adhering to conventional beauty standards, and Filtered Reality Challenges, involving the use of filters or editing tools to enhance one's appearance, contribute to an unrealistic portrayal of beauty (Kleemans et al., 2016). These trends can impact individuals' perceptions of their natural features, promoting a sense of inadequacy among those who do not align with these standards (Perloff, 2014).

Regarding photo manipulation activities, it is crucial to underscore how, in addition to the filters on social networks like Instagram, manipulations can be performed using other programs, such as GIMP, PIXLR or PhotoScape X.

Correlational research has demonstrated that levels of selfie manipulation are associated with body and facial dissatisfaction (stated that faces hold particular significance in the context of selfies) (McLean et al., 2015); indeed, a study conducted by Wang et al. (2019) highlighted how the frequency of selfie manipulation predicts an increase in face and body dissatisfaction. Additionally, exposure to manipulated photos on Instagram leads to higher dissatisfaction compared to exposure to unaltered photos from the same profile (Tiggemann & Zinoviev, 2019).

Summarizing, the collective findings from literary studies provide significant support for a notable association between photo manipulations and body concerns (Andrew et al., 2015; Beos et al., 2021; Jáuregui-Lobera et al., 2013). Moreover, it has been demonstrated that this relationship can be much more complex than a direct path, highlighting the need for detailed analyses to understand and identify potential influencing factors on this relationship (Beos et al., 2021; Lonergan et al., 2018; McLean et al., 2015).

However, scientific research has often overlooked the role of intervening factors that may influence the relationship between body dissatisfaction and photo manipulation. Critical thinking emerges as an important skill that allows for objective analysis of information, evaluation of source quality (Norris, 1985, p.40); it embraces the ability to assess the reliability of images and identify potential signs of manipulation (e.g., presence of different pixels around edges, or parts of an image that appear inconsistent with the rest); in this way, it is possible to determine if a photo accurately represents reality. Additionally, it can facilitate the evaluation of motivations behind a selfie (Silverblatt, 1996), such as to document an experience or if it is seeking approval from others through likes or comments.

As demonstrated by Bennett et al. (2023) ‘Media Processing Theory’ posits that media messages are more likely to be accepted when they are perceived as realistic, relatable to the viewer's experiences, and highly desirable. In the context of media literacy, critical thinking involves understanding the broader purpose of media, including the techniques used in its production, recognition of portrayed values and perspectives, awareness of media's potential influence on behavior and attitudes, and acknowledgment that media messages may not accurately represent reality (Primack et al., 2006; Silverblatt, 1996).

The relationship between critical thinking abilities, photo manipulation behaviours and body image dissatisfaction has been explored in very limited ways; a small number of qualitative and experimental studies provide some support.

One of these studies revealed that the phenomenon of self-reference, where people actively employ defensive media strategies, (such as critically analysing the techniques used to enhance a selfie before posting it), has been explored in various studies, leading interesting results: Andrew et al. (2015) revealed that this tendency is linked to a more positive perception of one's body; it allows to develop a healthier and more accepting view of physical appearance.

In an experimental context, McLean et al. (2016), focusing particularly on adolescents, showed that girls who exhibit high levels of criticism tend to report greater satisfaction with their body image; this suggests that a critical and reflective approach can have a positive impact on the perception of one's body, helping to mitigate external pressures and unrealistic expectations.

Tamplin et al. (2018) contributed to this field of study, proposing that critical thinking can serve as a protective shield against the negative effects of social media exposure. The incessant bombardment of idealized images and the pressure to conform to certain aesthetic standards can have significant repercussions on self-perception. However, developing the ability to critically analyse these media contents can help counteract these negative effects, promoting a more realistic and positive view of one's body.

In summary, research suggests that encouraging a critical approach towards media can be an effective strategy to promote psychological well-being. For instance, studies by Burnette et al. (2017) and Mahon and Hevey (2021) propose that awareness of image retouching or artificial manipulation diminishes the negative impact of such images on body dissatisfaction. Considering the studies present in the literature, previously analysed, this work aimed to investigate the relationships among body dissatisfaction, photo manipulation, and critical thinking, and to examine the ability to discern the use of filters in photos. The specific research questions can be formulated as follows:

RQ1 - Are there significant relationships among body image dissatisfaction, photo manipulation and critical thinking?

RQ2 - Does critical thinking have a mediating role in the relationship between body image dissatisfaction and photo manipulation?

RQ3 – Are participants able to correctly classify natural vs. filtered images?

2. Materials and methods

2.1. Participants and procedure

A convenience sample was collected through the distribution of a Google Forms® link containing the battery of questionnaires on Social Media platforms such as: Facebook, Instagram, Twitter, Telegram and WhatsApp groups, with the aim of extending the involvement of participants throughout Italy. Participants were requested to complete a battery of questionnaires with an approximate duration of 15 minutes.

Through the informed consent form (containing information regarding data confidentiality, the option to discontinue participation at any time, and assurances of anonymity), each participant provided their consent before proceeding with the survey.

As the questionnaire was administered online, we adhered to ethical guidelines for internet-based research by requesting explicit consent prior to participation and ensuring the anonymity of all respondents. The present survey followed ‘The Internet Research: Ethical Guidelines 3.0’ issued by the Association of Internet Researchers (AoIR), approved by the AoIR membership October 6, 2020 (Franzke et al., 2020).

A socio-demographic questionnaire was used to collect general data from participants. The questionnaire included items on gender, age, place of residence (categorized as Northern, Central, or Southern Italy, and the Islands), and employment status. These variables were analyzed to provide a comprehensive overview of the sample's demographic characteristics.

A total sample of 500 participants was collected. Among them, 280 identified as female (56%), 219 as male (43.8%), and 1 participant as non-binary (0.2%). The participants' ages ranged from 15 to 60 years (M = 25.7, SD = 17.8), with 220 residing in Northern Italy (44%), 107 in Central Italy (21.4%), 112 in Southern Italy (22.4%), and 61 on the Islands (12.2%). Regarding employment status, 208 participants (41.6%) identified as students, 206 (41.2%) as full-time employees, 72 as working students (14.4%), and 14 (2.8%) as neither studying nor working.

2.2. Measures

The measures used for the assessment were: (1) the Revised Photo Manipulation Scale (McLean et al., 2015); (2) the Body Uneasiness Test (Cuzzolaro et al., 2006); (3) the Fake Subscale of the Critical Processing of Beauty Images Scale (Engeln-Maddox & Miller, 2008); (4) a specifically constructed task for recognizing photographic manipulation; (5) three control questions.

Figure 1.

Figure 1.

Open in a new tab

Images selected for the recognition task (in order of administration)

2.2.1 Photo Manipulation Scale (PMS-R)

The Photo Manipulation Scale (PMS-R) is a self-report questionnaire composed of 11 items, aimed at investigating digital modification activities of photographs before they are posted on social media (McLean et al., 2015). The Italian version of the instrument, by Gioia et al. (2021), consists of 8 items on a 5-point Likert scale (1= “never”; 5 = “always”). The total score reflects how often individuals turn to digital manipulation: higher scores indicate greater engagement in this type of behaviour. The PMS-R is divided into 3 subscales: use of filters (items n. 1,2,3); body image manipulation (items n. 4,5,6); facial image manipulation (items n. 7,8). The instrument exhibits good psychometric properties (Cronbach's α = .80). In the present study, the instrument used in Italian demonstrated good reliability (α Cronbach = .82).

2.2.2 Body Uneasiness Test (BUT)

The Body Uneasiness Test (BUT) is a self-report instrument designed for the assessment of body image (Cuzzolaro et al., 2006). It is divided into two parts; the first (BUT A) assesses 5 factors: weight phobia, body image concern, compulsive control, avoidance behaviours, and depersonalization, through 34 items on a 6-point scale, from 0 (never) to 5 (always); a higher score signifies a greater level of impairment. The second part ("Regarding my body, in particular, I detest") (BUT B) assesses specific concerns regarding various parts of the body and other related aspects such as blushing, sweating, through 37 items on a scale from 1 (never) to 5 (always). In literature, the scale has shown good psychometric properties of reliability and validity (Cronbach's α = .90), as well as in the present study (Cronbach's α = .95).

2.2.3 Fake Subscale of the Critical Processing of Beauty Images Scale

The Fake Subscale is adapted from the Critical Processing of Beauty Images Scale (Engeln-Maddox & Miller, 2008). With items like "That kind of perfection is not real", it is designed to assess frequency of thoughts that images presented in the media, depicting female/ male models, have been artificially created and are unrealistically perfect. Consisting of 5 items (translated from English to Italian through back translation with 99,8 % of word matching) rated on a five-point scale, from 1 (never) to 5 (always) (See table 1). A total score (range from 5 to 25) was calculated from the sum of the items. Higher scores reflect a higher frequency of critical processing of images. The original scale showed good reliability and validity (Cronbach’s α = .92. The "Fake Subscale" subscale of the "Critical Processing of Beauty Images Scale" was used due to its suitability for the purpose of the study. Firstly, to use the scale in Italian culture translation procedures were carried out and then a pilot study was conducted to test the comprehensibility. Then the Cronbach’s α internal consistency coefficient of the scale was calculated and was confirmed in the present study (Cronbach's α = .92).

Table 1.

Descriptive statistics of the study variables (N=500)

  M SD Skewness SD Kurtosis SD Tolerance VIF
Body İmage Dissatisfaction 102.99 28.94 0.15 0.11 -0.66 0.22 1.00 1.00
Critical Thinking 17.89 5.17 -0.42 0.11 -0.57 0.22 0.88 1.13
Photo Manipulation 19.57 6.65 -0.04 0.11 -1.15 0.22 - -
Open in a new tab

2.2.4 Manipulated Photo Recognition Task

A recognition task has been constructed, in which participants were asked to observe a sequence of 6 photographs (3 featuring male subjects and 3 featuring female subjects), which differed in the number of filters applied. The goal was to assess critical thinking skills regarding photographic content. For each photograph, participants were asked to indicate how much the image is retouched from 0 ('completely natural') to 10 ('completely modified').

Sample pictures were obtained through Pinterest (www.pinterest.com), a free visual search platform; then they were then sorted by two independent experimenters based on the observed number of filters, with a 100% matching. Additionally, the images were inserted into JPEGsnoop®, an original software for Windows systems capable of checking if an image has been manipulated. Images 1 and 4 were severely modified (3 or more filters); Images 2 and 5 slight modified (1/2 filter) and Images 3 and 6 completely natural (0 filters).

2.2.5 Control questions

In the present study, to delve deeper into the issues addressed in this work, 3 control questions have been formulated.

Participants were asked to indicate their level of satisfaction on a scale from: 0 ('completely dissatisfied') to 10 ('completely satisfied'). The first question was posed at the end of the administration of the Photo Manipulation Scale (PMS): ‘How satisfied are you overall with your digital image?’. The remaining two control questions were presented at the end of the Body Uneasiness Test (BUT): ‘How satisfied are you overall with your real image?’ and ‘How much do you prefer your image with filters?’.

2.3. Data analysis

The data were analyzed using SPSS 27.0 social science statistical software. The data set was represented using distribution indicators such as means and standard deviations. Before proceeding with the statistical analyses, it was tested whether the data set was normally distributed and whether there was a problem of multicollinearity between the variables. Where possible, correlations were calculated using the Pearson Product Moment Correlation coefficient. In the study, body image dissatisfaction was identified as the independent, critical thinking as the mediator, and photo manipulation as the dependent variables, and the relationships between these variables were tested using simple mediation model analysis. Mediation model was analyzed using the bootstrapping method. Bootstrapping was performed with PROCESS Basic Mediation Model 4 (Hayes, 2017). Statistical significance was set at p<.05.

3. Results

3.1. Preliminary analysis

The descriptive statistics, including the mean, standard deviation, skewness, and kurtosis values of the scores obtained from the scales belonging to the variables addressed in the study, are presented in table 1.

Examining table 1, the skewness and kurtosis coefficients of the scores obtained from the scales for the body image dissatisfaction, critical thinking and photo manipulation variables that are the subject of the study vary between +1.5 and -1.5. According to Tabachnick et al. (2013), the fact that the skewness and kurtosis values are within this range indicates that the data set is normally distributed. Furthermore, because regression-based statistical analyses are conducted, as a precondition, whether there is a multicollinearity problem between variables was checked by calculating tolerance and VIF values. A tolerance value lower than 0.10 and a VIF value higher than 10 indicates that there is multicollinearity between independent variables. Looking at table 1, the tolerance values range from 0.88 to 1.00 and the VIF values range from 1.00 to 1.13. Therefore, since the calculated tolerance and VIF values meet the specified criteria, we may say that no multicollinearity problem exists between the variables.

3.1.1. Control variables

The study also examined the effect of gender and age variables on participants' level of photo manipulation. The results showed that there is a low level negative and significant relationship between age and photo manipulation (r= -0.14; p<0.01). As age increases, there is a decrease in photo manipulation behavior. Whether the level of photo manipulation differs according to gender was examined by independent groups t-test and it was concluded that there is a significant difference in photo manipulation scores in terms of gender (t= 11.26; p<0.01). According to this finding, males (M= 22.96; SD= 6.04) show more photo manipulation behavior than females (M= 16.95; SD= 5.87). Due to their effects on photo manipulation, gender and age variables were included as covariates in the mediation analysis.

3.2. Correlations

In accordance with the first objective of the study (RQ1), the relationships among the variables were examined prior to the mediation analysis using the Pearson Product Moment Correlation Coefficient technique, and the results are presented in table 2.

Table 2.

Correlations among study variables (N=500)

    1 2
1. Body Image Dissatisfaction    
2. Critical Thinking 0.34**  
3. Photo Manipulation 0.56** 0.49**
Open in a new tab

Note: **p<0.001

The first objective of the study (RQ1) was to test the relationships among body image dissatisfaction, photo manipulation and critical thinking. Table 2 shows that strong correlation (r≥ 0.50, p<0.001) were obtained between body image dissatisfaction and photo manipulation. Unexpectedly, the results indicated a positive correlation between critical thinking and body image dissatisfaction (r= 0.34, p<0.001). In other words, the tendency to judge retouched photos increases as body dissatisfaction increases. Besides, critical thinking showed significant and positive relation to photo manipulation (r= 0. 49, p<0.001).

3.3 The mediating role of critical thinking between body image dissatisfaction and photo manipulation

The second aim of the study (RQ2) whether critical thinking have a mediating role in the relationship between body image dissatisfaction and photo manipulation. Regression-based bootstrapping analysis technique was used to test the mediating role of critical thinking. Bootstrapping analysis was performed using PROCESS Macro (Model 4) with SPSS Plug-in, with 5000 samples (Hayes, 2017). The estimations were evaluated with 95% confidence interval. Due to their effects on photo manipulation behaviour, age and gender were included as covariates. Figure 2 shows the mediation model tested and results.

Figure 2.

Figure 2.

Open in a new tab

Mediation model

Not: R2=0.47; F (4, 495) = 108.15; **p<0.001; Unstandardized Beta coefficients were reported.

As shown in figure 2, the results of the regression-based bootstrapping analysis indicate that body image dissatisfaction directly predicts photo manipulation (β= 0.11, p<0.001). Body image dissatisfaction positively predicts critical thinking, which is the mediating variable of the study (β= 0.04, p<0.001). In addition, critical thinking also predicts body image dissatisfaction directly in a positive way (β= 0.32, p<0.001). In the mediator model analysis, when critical thinking was included in the regression model, the relationship between body image dissatisfaction and photo manipulation decreased but remained significant (β=0.09, p<0.001). This finding indicates that critical thinking has a partial mediating role in the relationship between body image dissatisfaction and photo manipulation. On the other hand, the mediation model for predicting photo manipulation was found to be significant [F (4, 495) = 108.15, p< .001, R2=.47] and the variables explained 47% of the total variance of photo manipulation.

After this stage, whether the partial mediation effect of the mediating variable was significant or not was tested on a bootstrap sample of 5000 participants and the estimates were evaluated with 95% confidence intervals. The findings are presented in table 3.

Table 3.

Bootstrapping results for the direct and indirect effects of body image dissatisfaction on photo manipulation

  Boot Effect SE LLCI ULCI
Total Effect (c: X→Y) 0.11 0.008 0.09 0.12
Direct Effect (c’: X→Y) 0.09 .008 0.08 0.11
Indirect Effect (X→M→Y) 0.014 0.004 0.01 0.02
Completely Standardized Indirect Effect 0.06 0.02 0.03 0.09
Open in a new tab

Notes: p<.001; X= Body dissatisfaction; Y= Photo manipulation; M=Critical thinking. Confidence Level: 95%, Bootstrap Samples: 5000 for percentile bootstrap confidence intervals.

Analyzing table 3, the results reveal that criticism for beauty images serves as a partial mediator in the relationship between body image dissatisfaction and photo manipulation, in other words, the indirect effect is significant (BootEffect= 0.014, 95% CI [-0.008, -0.021]). Researchers state that in order to speak of the significance of the mediation effect, there should be no value of zero (0) between the lower (LLCI) and upper (ULCI) limits of the 95% confidence interval (Preacher & Hayes, 2004). Therefore, this finding satisfies this criterion. In addition, the completely standardized effect size of the mediation effect was found to be 0.06. This value show that the mediation effect in the model has a moderate effect size. In mediation analysis, an effect size close to .01 is interpreted as a small effect, close to .09 as a medium effect, and close to .25 as a large effect (Preacher & Kelley, 2011; Cohen, 2013). Finally, these findings suggest that body image dissatisfaction has not only a direct but also an indirect effect on photo manipulation through criticism for beauty images.

3.3. The ability of participants to correctly classify natural vs. filtered images

The third aim of the study (RQ3) is to evaluate the accuracy in distinguishing between natural and filtered images.

To further investigate the results that emerged, through the analysis of the responses obtained to the recognition task, it seems that images featuring female subjects are more often perceived as modified, regardless of the presence or absence of filters (See Graph 1). Images featuring male subjects show greater variability in perceptions, with some images perceived as 'fairly modified' and others as 'completely modified'. There is a general tendency to overestimate the use of photo manipulation; it means that the provided photos have been assessed as more retouched than they are.

4. Discussion

The primary aim of this study was to explore the relationship between digital manipulation, body image dissatisfaction, and critical thinking in the general population. The results demonstrated significant positive correlations between digital manipulation and body image dissatisfaction (RQ1): individuals who tended to post retouched images of themselves, altering aspects of their body, face, skin, and environment, also exhibited higher levels of body dissatisfaction measured by the BUT. Therefore, it could be stated that: high levels of body dissatisfaction may lead to increased efforts in photo manipulation to conform to current beauty standards. In the present study emerged a clear preference for one's digital image and the digitally enhanced version using filters. The results suggest that, in general, a slightly higher percentage of people are satisfied with their digital image compared to their real one. This highlights how the use of filters and photo manipulation tools can contribute to making the digital image more appreciated than the real image for a significant portion of people. Overall, the results suggest that for many, the digital image is viewed more favorably than the real one, in part due to the use of filters and photo editing tools that enhance the perception of the digital image. These observations are consistent with several studies that correlated body image dissatisfaction and photo manipulation and filter overuse with implication on body self-esteem (De Vaate et al., 2018; Fox & Rooney, 2014; Re et al., 2023; Rizzo et al., 2024a; Rousseau, 2020).

Figure 3.

Figure 3.

Open in a new tab

Response to Manipulated photo recognition task

Legend : F = Female figure; M =Male figure; (>3) = with 3 or more filters / severely modified; (1/2) = with one or two filters /slightly modified; (0) = with zero filters /completely natural.

Regarding the role of critical thinking (RQ2), there have been few experimental studies on reference, which have demonstrated an inversely proportional association between critical thinking and body dissatisfaction (Andrew et al., 2015). Exposure to media portraying the thin ideal can lead to increased dissatisfaction with one's body, especially among adolescent girls. It's critical to understand what factors can mitigate or worsen the detrimental impact of media exposure on body dissatisfaction, to help prevent such issues. McLean et al. (2016) demonstrated that the ability to critically analyze media content help to lessen the harmful effects of internalizing the thin ideal and making upward appearance comparisons on the girls' satisfaction with their bodies.

From these premises it was hypothesized body image dissatisfaction to correlate inversely with critical thinking. However, the obtained results do not align with what was expected. The present study revealed a positive relation between body image dissatisfaction and critical thinking about unreal beauty / images digitally retouched.

Surprisingly, the more the body uneasy, the more the tendency to criticize social media images. This could be explained by the fact that individuals with heightened body image dissatisfaction may be more sensitive to idealized body images prevalent on social media platforms; they may compare themselves unfavorably to these images, leading to increased criticism as a coping mechanism or a way to express dissatisfaction. Additionally, people unhappy with their body may notice differences between idealized images and reality, leading them to criticize and doubt the authenticity of social media pictures (Rizzo & Alparone, 2024). Therefore, findings demonstrate that strong direct relationship between body image dissatisfaction and photo manipulation, as well as a notable indirect effect through the mediation of criticism towards beauty images (Rizzo et al., 2024b; Khabbache et al., 2024).

Moreover, results indicate that the pathway from body image dissatisfaction to engaging in photo manipulation is influenced both directly and indirectly by the internalization and critique of social media beauty standards; the assimilation of social media beauty ideals may lead individuals to compare themselves unfavourably to idealized images, intensifying their body dissatisfaction. As a result, they may be more inclined to engage in photo manipulation to attain or approximate these standards (Tiggemann & Slater, 2013).

Furthermore, regarding the ability to correctly classify natural and filtered photos (RQ3) it has been observed a difficulty in properly identify manipulated images, especially for slightly manipulated and completely natural images. Surprisingly, the photos with slight modifications (1/2 filters) have a low correct classification rate, particularly for the female figure (Photo 5 F), which might indicate that subtle changes are harder to detect or classify than more severe modifications or no modifications at all (0). There appears to be a trend where completely natural photos (Photo 3 F and Photo 6 M) have a lower rate of being correctly classified compared to those with filters, especially significant in the case of the female figure; it means that untouched photos were mistakenly classified as retouched, and photos with minimal retouching were considered as extremely retouched, with gender effects (Fardouly et al., 2015).

In fact, the highest recognition rate is for a male figure with significant modifications (>3 filters), suggesting that the presence of multiple filters on male figures may make them easier to classify correctly for participants performing the recognition task. This latter data could be explained through the influence of gender stereotypes or prejudices: women are often subject to beauty stereotypes that promote specific physical traits, such as flawless skin and a lean and toned body, while men are influenced by different stereotypes that emphasize muscularity and other specific physical attributes as ideals of male beauty (Engeln et al., 2013; Tiggemann & Anderberg, 2019).

The elevated perception of alterations in female images may originate from cultural and social aesthetic expectations that place a greater emphasis on women's physical appearance, promoting unrealistic beauty ideals (Karsay et al., 2017). Moreover, women might feel pressured to meet certain beauty standards, prompting them to use filters or make adjustments to fit these ideals. Social media pressures are crucial here, as they often focus more on altered female images, making it seem like women edit their photos more than men (Gurari et al., 2006).

It is essential to emphasize that these observations are generalizations and that attitudes toward modified images differ widely based on cultural and individual factors. Further research could enhance our understanding, considering individual and cultural nuances that impact perceptions and practices related to edited images (Rizzo et al., 2023).

Summarizing, individuals with high body dissatisfaction tend to overestimate retouching, that is, they tend to believe that others' photos are retouched (and the greater the tendency to manipulate their own photos). Surprisingly, this also happens when such photos are moderately retouched (e.g., saturation) or completely natural, adopting the thought mode: 'such beauty cannot be real without retouching'.

This result could be explained as a 'dysfunctional self-esteem protection mechanism', a thinking mode or a series of behaviors adopted to protect self-esteem, but which paradoxically could have a negative impact on mental health and interpersonal relationships. Consequently, a person with high body dissatisfaction may overestimate or underestimate others' retouching tendency to protect their self-esteem by averting a potential threat (Bennett et al., 2023; Zogmaister & Maricutoiu, 2022).

Alternatively, the influence of affective processes can affect critical judgment: emotions can influence the ability to evaluate and analyze the content we are exposed to. Negative emotions, such as dissatisfaction with one's body, can affect critical thinking skills, making it more difficult to analyze content, causing cognitive distortions like selective information filtering f.e. identifying a greater number of filters used to modify images in others' photos.

Both points emphasize the importance of understanding the interaction between body dissatisfaction, emotions, and the perception of digital images. These factors can contribute to a distorted perception of others' images and influence individuals' psychological well-being (Rizzo et al., 2025).

This result is slightly comparable with the data available in the literature, as far as our knowledge goes, there are no studies that have investigated the role of recognizing retouching in relation to body image. For this reason, future studies should offer a more in-depth understanding of how these factors can interact and impact self-perception and perceptions of others.

In general, in line with previous research findings, it was possible to strengthen the hypothesis that digital modification of photographs are associated with high levels of negative feelings towards one's own body (De Vaate et al., 2018). Furthermore, the relationship between critical thinking and body dissatisfaction was explored, an area that has been relatively underexplored in previous scientific studies (Andrew et al., 2015; Tamplin et al., 2018), leading entirely new and unexpected results. These findings could be further investigated in future studies, considering the role of additional intervening variables (e.g., rumination, self-objectification, gender differences, and cultural differences) (Lee-Won et al., 2020).

These results may pave the way for the development of media literacy programs aimed at enhancing users' skills for publishing personal content and evaluating the content to which we are exposed daily, often expressions that deviate from reality (Jáuregui-Lobera et al., 2013; Bruno et al., 2024).

5. Limitations and conclusions

Some limitations of the study should be also pointed out. First, the administration took place online, preventing adequate control over the completion setting, which may have led to superficial responses. Additionally, self-administered questionnaires may be subject to bias, as individuals may not always be objective about themselves and their experiences (Ashleigh & Mansi, 2012).

Regarding critical thinking measurement tools, specific tests for evaluating critical skills about content published on social media are not yet available in the Italian context. The test used in this research, the Fake Subscale, is a subscale derived from the Critical Processing of Beauty Images, a tool designed for evaluating critical processing of content in traditional media (e.g., magazines and TV).

The study shed light on the intricate relationship between body image satisfaction, critical thinking, and the ability to detect photo manipulation. It was found that those with higher levels of body dissatisfaction and more pronounced critical thinking skills faced challenges in accurately identifying altered images. This suggests that personal biases and concerns about body image may influence the effectiveness of critical thinking in the context of media consumption. Body image significantly affects everyday interactions and self-esteem, with repercussions for mental and social well-being (Cedro et al., 2022; Mento et al., 2017; Mento et al., 2023); understanding and navigating the often-distorted portrayals of bodies in media is vital for maintaining a healthy self-perception in our digital age. These insights point to the complexity of cognitive processes involved in media literacy and body image perception, highlighting the need for further research to inform educational programs and interventions.

References

  1. Andrew, R., Tiggemann, M., & Clark, L. (2015). The protective role of body appreciation against media-induced body dissatisfaction. Body Image, 15, 98–104. 10.1016/j.bodyim.2015.07.005 [DOI] [PubMed] [Google Scholar]
  2. Ashleigh, M., & Mansi, A. (2012). The psychology of people in organisations. https://eprints.soton.ac.uk/80399/ [Google Scholar]
  3. Bennett, B. L., Martin-Wagar, C. A., Boswell, R. G., Forrest, L. N., Perelman, H., & Latner, J. D. (2023). Skepticism of and critical thinking about media messages: Conflicting relationships with body dissatisfaction. Eating Behaviors, 51, 101820. 10.1016/j.eatbeh.2023.101820 [DOI] [PubMed] [Google Scholar]
  4. Beos, N., Kemps, E., & Prichard, I. (2021). Photo manipulation as a predictor of facial dissatisfaction and cosmetic procedure attitudes. Body Image, 39, 194–201. 10.1016/j.bodyim.2021.08.008 [DOI] [PubMed] [Google Scholar]
  5. Blumler, J. G., & Katz, E. (1974). The uses of mass communications: Current perspectives on gratifications research. In J. G. Blumler & E. Katz (Eds.), Sage annual reviews of communication research(Vol. 3). Sage. https://eric.ed.gov/?id=ED119208 [Google Scholar]
  6. Bossen, C. B., & Kottasz, R. (2020). Uses and gratifications sought by pre-adolescent and adolescent TikTok consumers. Young Consumers, 21(4), 463–478. 10.1108/yc-07-2020-1186 [DOI] [Google Scholar]
  7. Bruno, F., Mautone, A., Ait Ali, D., Fassima, A., Khabbache, H., & Rizzo, A. (2024). Evaluating Facebook scales: A systematic review of the psychological assessment tools. Advances in Medicine, Psychology, and Public Health, 2(3), 142–156. 10.5281/zenodo.13351015 [DOI] [Google Scholar]
  8. Burnette, C. B., Kwitowski, M. A., & Mazzeo, S. E. (2017). “I don’t need people to tell me I’m pretty on social media:” A qualitative study of social media and body image in early adolescent girls. Body Image, 23, 114–125. 10.1016/j.bodyim.2017.09.001 [DOI] [PubMed] [Google Scholar]
  9. Cedro, C., Mento, C., Piccolo, M. C., Iannuzzo, F., Rizzo, A., Muscatello, M. R. A., & Pandolfo, G. (2022). Sexual desire and body image. Gender differences and correlations before and during COVID-19 Lockdown. International Journal of Environmental Research and Public Health, 19(7), 4351. 10.3390/ijerph19074351 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Choukas-Bradley, S., Nesi, J., Widman, L., & Galla, B. M. (2020). The Appearance-Related Social Media Consciousness Scale: development and validation with adolescents. Body Image, 33, 164–174. 10.1016/j.bodyim.2020.02.017 [DOI] [PubMed] [Google Scholar]
  11. Cohen, J. (2013). Statistical Power Analysis for the Behavioral Sciences. In Routledge eBooks. 10.4324/9780203771587 [DOI] [Google Scholar]
  12. Cuzzolaro, M., Vetrone, G., Marano, G., & Garfinkel, P. (2006). The Body Uneasiness Test (BUT): development and validation of a new body image assessment scale. Eating and Weight Disorders - Studies on Anorexia Bulimia and Obesity, 11(1), 1–13. 10.1007/bf03327738 [DOI] [PubMed] [Google Scholar]
  13. De Vaate, J. B. A., Veldhuis, J., Alleva, M. J., Konijn, A. E., & Van Hugten, H. C. (2018). Show your best self(ie): an exploratory study on selfie-related motivations and behavior in emerging adulthood. Telematics and Informatics, 35(5), 1392–1407. 10.1016/j.tele.2018.03.010 [DOI] [Google Scholar]
  14. Engeln-Maddox, R., & Miller, S. A. (2008). Talking back to the media ideal: the development and validation of the critical processing of beauty images scale. Psychology of Women Quarterly, 32(2), 159–171. 10.1111/j.1471-6402.2008.00420.x [DOI] [Google Scholar]
  15. Engeln, R., Sladek, M. R., & Waldron, H. (2013). Body talk among college men: content, correlates, and effects. Body Image, 10(3), 300–308. 10.1016/j.bodyim.2013.02.001 [DOI] [PubMed] [Google Scholar]
  16. Fardouly, J., Diedrichs, P. C., Vartanian, L. R., & Halliwell, E. (2015). Social comparisons on social media: the impact of Facebook on young women’s body image concerns and mood. Body Image, 13, 38– 45. 10.1016/j.bodyim.2014.12.002 [DOI] [PubMed] [Google Scholar]
  17. Fardouly, J., & Holland, E. (2018). Social media is not real life: the effect of attaching disclaimer-type labels to idealized social media images on women’s body image and mood. New Media & Society, 20(11), 4311–4328. 10.1177/1461444818771083 [DOI] [Google Scholar]
  18. Fardouly, J., & Vartanian, L. R. (2015). Social media and body image concerns: current research and future directions. Current Opinion in Psychology, 9, 1–5. 10.1016/j.copsyc.2015.09.005 [DOI] [Google Scholar]
  19. Fox, J., & Rooney, M. C. (2014). The Dark Triad and trait self-objectification as predictors of men’s use and self-presentation behaviors on social networking sites. Personality and Individual Differences, 76, 161–165. 10.1016/j.paid.2014.12.017 [DOI] [Google Scholar]
  20. Franzke, A. S., Bechmann, A., Zimmer, M., Ess, C., & Association of Internet Researchers. (2020). Internet research: Ethical guidelines 3.0. https://aoir.org/reports/ethics3.pdf [Google Scholar]
  21. Fredrickson, B. L., & Roberts, T. (1997). Objectification Theory: toward understanding women’s lived experiences and mental health risks. Psychology of Women Quarterly, 21(2), 173–206. 10.1111/j.1471-6402.1997.tb00108.x [DOI] [Google Scholar]
  22. Gioia, F., McLean, S., Griffiths, M. D., & Boursier, V. (2021). Adolescents’ selfie-taking and selfie-editing: a revision of the photo manipulation scale and a moderated mediation model. Current Psychology, 42(5), 3460–3476. 10.1007/s12144-021-01702-x [DOI] [Google Scholar]
  23. Giordano, C., Salerno, L., Pavia, L., Cavani, P., Lo Coco, G., Tosto, C., & Di Blasi, M. (2019). Magic Mirror on the Wall: Selfie-Related behavior as mediator of the relationship between narcissism and problematic smartphone use. PubMed, 16(5–6), 197–205. 10.36131/clinicalnpsych2019050602 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Gurari, I., Hetts, J. J., & Strube, M. J. (2006). Beauty in the “I” of the beholder: effects of idealized media portrayals on implicit Self-Image. Basic and Applied Social Psychology, 28(3), 273–282. 10.1207/s15324834basp2803_6 [DOI] [Google Scholar]
  25. Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2nd ed.). Guilford Press. [Google Scholar]
  26. Holland, G., & Tiggemann, M. (2016). A systematic review of the impact of the use of social networking sites on body image and disordered eating outcomes. Body Image, 17, 100–110. 10.1016/j.bodyim.2016.02.008 [DOI] [PubMed] [Google Scholar]
  27. Jáuregui-Lobera, I., Ezquerra-Cabrera, M., Carbonero-Carreño, R., & Ruiz-Prieto, I. (2013). Weight misperception, Self-Reported physical fitness, dieting and some psychological variables as risk factors for eating disorders. Nutrients, 5(11), 4486–4502. 10.3390/nu5114486 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Karsay, K., Knoll, J., & Matthes, J. (2017). Sexualizing media use and Self-Objectification. Psychology of Women Quarterly, 42(1), 9–28. 10.1177/0361684317743019 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Khabbache, H., Ali, D. A., Cherqui, A., Allioui, A., Abidli, Z., Elturk, J., Yildirim, M., Bragazzi, N. L., Nucera, G., Szarpak, L., Rizzo, A., & Chirico, F. (2024). Adaptation and validation of the Moroccan dialect version of the Nomophobia Questionnaire (NMP-Q): among university students. Heliyon, 10(17), e36256. 10.1016/j.heliyon.2024.e36256 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Kleemans, M., Daalmans, S., Carbaat, I., & Anschütz, D. (2016). Picture Perfect: The direct effect of manipulated Instagram photos on body image in adolescent girls. Media Psychology, 21(1), 93–110. 10.1080/15213269.2016.1257392 [DOI] [Google Scholar]
  31. Lee-Won, R. J., Joo, Y. K., Baek, Y. M., Hu, D., & Park, S. G. (2020). “Obsessed with retouching your selfies? Check your mindset!”: Female Instagram users with a fixed mindset are at greater risk of disordered eating. Personality and Individual Differences, 167, 110223. 10.1016/j.paid.2020.110223 [DOI] [Google Scholar]
  32. Lonergan, A. R., Bussey, K., Mond, J., Brown, O., Griffiths, S., Murray, S. B., & Mitchison, D. (2018). Me, my selfie, and I: the relationship between editing and posting selfies and body dissatisfaction in men and women. Body Image, 28, 39–43. 10.1016/j.bodyim.2018.12.001 [DOI] [PubMed] [Google Scholar]
  33. Mahon, C., & Hevey, D. (2021). Processing body image on social media: gender differences in adolescent boys’ and girls’ agency and active coping. Frontiers in Psych logy, 12. 10.3389/fpsyg.2021.626763 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. 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. 10.1002/eat.22449 [DOI] [PubMed] [Google Scholar]
  35. McLean, S. A., Paxton, S. J., & Wertheim, E. H. (2016). Does media literacy mitigate risk for reduced body satisfaction following exposure to Thin-Ideal Media? Journal of Youth and Adolescence, 45(8), 1678–1695. 10.1007/s10964-016-0440-3 [DOI] [PubMed] [Google Scholar]
  36. Mento, C., Donne, M. L., Crisafulli, S., Rizzo, A., & Settineri, S. (2017). BMI at early puerperium: body image, eating attitudes and mood states. Journal of Obstetrics and Gynaecology, 37(4), 428–434. 10.1080/01443615.2016.1250727 [DOI] [PubMed] [Google Scholar]
  37. Mento, C., Rizzo, A., Liga, F., Zito, C., Bruno, A., Muscatello, M. R. A., Tanaka, Y., Kawai, T., & Silvestri, M. C. (2023). Eating behaviors and body self-esteem in couple’s satisfaction during COVID-19 quarantine. Nutrition and Health. 10.1177/02601060231166162 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Mingoia, J., Hutchinson, A. D., Wilson, C., & Gleaves, D. H. (2017). The relationship between social networking site use and the internalization of a Thin Ideal in females: a meta-analytic review. Frontiers in Psychology, 8. 10.3389/fpsyg.2017.01351 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Norris, S. P. (1985). Synthesis of research on critical thinking. Educational Leadership, 42(8), 40–45. [Google Scholar]
  40. Perloff, R. M. (2014). Social media effects on young women’s body image concerns: Theoretical Perspectives and an Agenda for research. Sex Roles, 71(11–12), 363–377. 10.1007/s11199-014-0384-6 [DOI] [Google Scholar]
  41. Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods Instruments &Amp Computers, 36(4), 717–731. 10.3758/bf03206553 [DOI] [PubMed] [Google Scholar]
  42. Preacher, K. J., & Kelley, K. (2011). Effect size measures for mediation models: Quantitative strategies for communicating indirect effects. Psychological Methods, 16(2), 93–115. 10.1037/a0022658 [DOI] [PubMed] [Google Scholar]
  43. Primack, B. A., Gold, M. A., Switzer, G. E., Hobbs, R., Land, S. R., & Fine, M. J. (2006). Development and validation of a smoking Media Literacy Scale for adolescents. Archives of Pediatrics and Adolescent Medicine, 160(4), 369. 10.1001/archpedi.160.4.369 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Re, A., Bruno, F., & Malvica, S. (2023). The influence of beauty filters on body self-awareness: an exploratory research on self-objectification. In Incontri. Il corpo come fonte di storia e pratiche del discorso (pp. 253–272). Corisco Edizioni. [Google Scholar]
  45. Rizzo, A., Princiotta, E., & Iuele, G. (2023). Exploring the link between smartphone use, recorded violence, and social sharing in 80 case studies in Italy. Psych, 5(4), 1241–1255. 10.3390/psych5040082 [DOI] [Google Scholar]
  46. Rizzo, A., & Alparone, D. (2024). Surfing Alone: from internet addiction to the era of smartphone dependence. International Journal of Environmental Research and Public Health, 21(4), 436. 10.3390/ijerph21040436 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Rizzo, A., Barbera, M., Commendatore, M., Marafioti, G., & Maggio, M. G. (2024a). Joinson's Facebook Questionnaire: Italian adaptation and validation. Advances in Medicine, Psychology, and Public Health, 2(1), 19–26. 10.5281/zenodo.11397532 [DOI] [Google Scholar]
  48. Rizzo, A., Batra, K., Yıldırım, M., Bulut, S., Tordonato, G., De Maio, V., Khabbace, H., Szarpak, Ł., Bahramizadeh, M., Yousefi, R. N., & Chirico, F. (2024b). Social media: stress factors or coping strategies? A pilot study in a sample of Italian teachers. Iranian Rehabilitation Journal, 22(2), 333–344. 10.32598/irj.22.2.2288.1 [DOI] [Google Scholar]
  49. Rizzo, A., Calandi, L., Faranda, M., Rosano, M. G., Carlotta, V., & Vinci, E. (2025). Stigma against mental illness and mental health: the role of social media. Advances in Medicine, Psychology, and Public Health, 2(2), 125–130. 10.5281/zenodo.13223184 [DOI] [Google Scholar]
  50. Rojo, M., Beltrán-Garrayo, L., Del Camino Del Blanco-Barredo, M., & Sepúlveda, A. R. (2023). Spanish validation of two social media appearance-related constructs associated with disordered eating in adolescents: the Appearance-related Social Media Consciousness scale (ASMC) and the Critical Thinking about Media Messages scale (CTMM). Body Image, 45, 401–413. 10.1016/j.bodyim.2023.04.004 [DOI] [PubMed] [Google Scholar]
  51. Rousseau, A., Eggermont, S., & Frison, E. (2017). The reciprocal and indirect relationships between passive Facebook use, comparison on Facebook, and adolescents’ body dissatisfaction. Computers in Human Behavior, 73, 336–344. 10.1016/j.chb.2017.03.056 [DOI] [Google Scholar]
  52. Rousseau, A. (2020). Adolescents’ selfie-activities and idealized online self-presentation: an application of the sociocultural model. Body Image, 36, 16–26. 10.1016/j.bodyim.2020.10.005 [DOI] [PubMed] [Google Scholar]
  53. Saiphoo, A. N., & Vahedi, Z. (2019). A meta-analytic review of the relationship between social media use and body image disturbance. Computers in Human Behavior, 101, 259–275. 10.1016/j.chb.2019.07.028 [DOI] [Google Scholar]
  54. Silverblatt, A. (1996). Media literacy: Keys to interpreting media messages. Praeger. [Google Scholar]
  55. Starri, M. (2024, January 30). DIGITAL 2023 - I dati Italiani - We Are Social Italy. We Are Social Italy. https://wearesocial.com/it/blog/2023/02/digital-2023-i-dati-italiani/ [Google Scholar]
  56. Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2013). Using multivariate statistics (6th ed., pp. 497–516). Pearson. [Google Scholar]
  57. Tamplin, N. C., McLean, S. A., & Paxton, S. J. (2018). Social media literacy protects against the negative impact of exposure to appearance ideal social media images in young adult women but not men. Body Image, 26, 29–37. 10.1016/j.bodyim.2018.05.003 [DOI] [PubMed] [Google Scholar]
  58. Tiggemann, M., & Slater, A. (2013). NetGirls: the Internet, Facebook, and body image concern in adolescent girls. International Journal of Eating Disorders, 46(6), 630–633. 10.1002/eat.22141 [DOI] [PubMed] [Google Scholar]
  59. Tiggemann, M., & Anderberg, I. (2019). Social media is not real: the effect of ‘Instagram vs reality’ images on women’s social comparison and body image. New Media & Society, 22(12), 2183–2199. 10.1177/1461444819888720 [DOI] [Google Scholar]
  60. Tiggemann, M., & Zinoviev, K. (2019). The effect of #enhancement-free Instagram images and hashtags on women’s body image. Body Image, 31, 131–138. 10.1016/j.bodyim.2019.09.004 [DOI] [PubMed] [Google Scholar]
  61. Wang, Y., Xie, X., Fardouly, J., Vartanian, L. R., & Lei, L. (2019). The longitudinal and reciprocal relationships between selfie-related behaviors and self-objectification and appearance concerns among adolescents. New Media & Society, 23(1), 56–77. 10.1177/1461444819894346 [DOI] [Google Scholar]
  62. Zogmaister, C., & Maricutoiu, L. P. (2022). Mirror, mirror on the wall, tell me that I have succeeded at it all: Self-esteem and the defensive mechanisms against failure. Social Psychology of Education, 25(5), 1221–1248. 10.1007/s11218-022-09723-5 [DOI] [Google Scholar]

Articles from Clinical Neuropsychiatry are provided here courtesy of Giovanni Fioriti Editore

RESOURCES