An experimental online study on the impact of negative social media comments on anxiety and mood

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This study investigates how negative comments on social media affect adults’ anxiety and mood. In an experimental study involving 128 adult participants (85 female, 43 male), individuals were asked to share blog posts on a simulated internet forum. Subsequently, they were exposed to either negative, neutral, or positive comments, and their mood and anxiety levels were measured using validated scales. Results showed that negative comments significantly increased anxiety and decreased mood compared to neutral or positive comments, while gender did not show any significant effects. Younger adults reported stronger anxiety responses to negative comments than older adults, suggesting heightened sensitivity among younger users. These findings highlight the psychological impact of negative social media comments on adults and underscore the importance of strategies for managing online negativity. This research expands our understanding of social media's effects on adult mental health. Biological sciences/Psychology Health sciences/Health care/Quality of life social media anxiety negative comment mood state cyberpsychology Figures Figure 1 Introduction With the development of modern science and technology, social media has dramatically changed how people interact worldwide, becoming a mainstream channel of human communication. Facebook, Twitter, Instagram, and TikTok have grown rapidly, reaching over five billion users worldwide (Petrosyan, 2024 ) and reshaping public discourse, communication, and information sharing. The popularity of social media has brought about an accessible means of information sharing, challenging the dominance of more traditional media such as newspapers, radio or TV. Individuals and organizations can now influence public opinion, creating social movements in ways that were not possible before. For example, the Arab Spring is a well-known event that mobilized social forces promoting social change through media like Twitter or Facebook (Tran, 2024 ). This mode of communication enabled social media to transcend its technical product positioning. Social media has increasingly influenced cultural, economic, and political discourse in modern society (Idachaba et al., 2023 ). Social media allows relatively free speech and provides rich learning resources to promote equality in education; the Open Educational Practice website is a good example (Jackson, 2014 ; Ossiannilsson, 2023 ). Additionally, social media provides a platform for marginalized groups to make their voices heard, enabling them to bring societal changes (O'Byrne, 2019 ). It also creates a brand community for businesses to foster customer trust and loyalty (Laroche et al., 2013 ). While social media facilitates global connectivity and information exchange, it also presents significant psychological risks, such as increased exposure to negative interactions and cyberbullying (Aimeur et al., 2023 ; Shu et al., 2017 ). The overuse of social media can also lead to user addiction, making them feel lonely (Kolas & von Mühlenen, 2024a ) and affecting their emotional health (Acar et al., 2022 ). Unwanted abstinence from or prevented access to social media can also lead to feelings of boredom and cravings (Kolas & von Mühlenen, 2024b ). Braghieri et al. ( 2022 ) conducted a quasi-experimental study by gradually introducing Facebook across colleges, allowing them to assess its impact on student mental health. Their findings revealed that the platform's rollout led to a significant decline in mental wellbeing, particularly among women, and was linked to increased use of mental health services and decreased academic performance. They attributed these effects to the role of Facebook in promoting unfavorable social comparisons—highlighting the psychological costs of harmful or comparative content on social media. Hunt et al. ( 2018 ) conducted a randomized controlled trial in which college students were assigned either to a group that reduced their social media use or to a group that maintained their usual habits. Participants who limited their use reported significantly lower levels of loneliness and depression compared to the control group, providing further evidence that reducing exposure to potentially harmful social media content can benefit emotional wellbeing. While these studies establish a general link between social media use and mental health, relatively little is known about the specific emotional impact of negative user comments. For instance, Chen et al. (2017) found that participants exhibited stronger negative emotional responses to hostile, uncivil disagreements than to polite ones, suggesting that the tone and delivery of comments on social media may directly influence users’ emotional experiences. This paper will focus on the negative effect that social media provides on cyberbullying. More specifically, on social media, users’ real identities are not easily directly linked to the content they post. This promotes their perception of anonymity and generally makes them feel less morally sensitive (Barlett et al., 2018 ; Ge, 2020 ). When moral constraints are weakened, users feel less inhibited. The online disinhibition phenomenon increases the likelihood of producing negative comments on social media (Wang et al., 2022 ). These negative comments, including – but not limited to – sarcasm, personal attacks, malicious provocations and discrimination, can often contribute to psychological distress. Studies indicate that cyberbullying on social media correlates with increased psychological stress and depressive symptoms (O'Reilly et al., 2018; Radovic et al., 2017 ). In addition, negative comments can aggravate an individual’s symptoms. Adolescents with anxiety disorders often have low self-esteem, which makes them more sensitive to comments on social media (Calancie et al., 2017 ). Even minor negative comments can impact their self-esteem, which is going to lead to more anxiety, possibly creating a vicious cycle. Fortunately, with the publication of these studies, more attention has been paid to the impact of negative comments on adolescents, and interventions have been proposed. Most previous research has examined the impact of negative comments on adolescents, yet there is limited understanding of these effects in adults (Alipan, 2020, 2021). This study uses an experimental method to address this gap by evaluating the effects of negative social media comments on adult anxiety and mood, hypothesizing that such comments will elevate anxiety and reduce mood. Previous research has also shown that women are more likely to feel anxious than men (Bahrami & Yousefi, 2011 ; Stumpf et al., 2015 ). Therefore, it is predicted that female participants will be more affected by negative comments than male participants. Method Participants A power analysis using G-Power (Faul et al., 2007 ) indicated that a minimum of 128 participants would be required to detect a medium effect size (f = .25) in a 2 (Gender) x 3 (Comment Type) between-subjects ANOVA, with α = 0.05 and power (1 – β) = 0.80. To account for potential attrition, 142 adult participants were recruited via Prolific's online research platform ( www.prolific.com ). Only English-speaking participants were chosen to ensure they understood the written blogs and comments well. All participants gave written informed consent and were compensated £7 for participation. Twelve participants chose to withdraw their data at the end of the study, and one participant failed the attention checks, leaving 129 participants (85 females, 43 males, and 1 “other”), all over 18 years old (M = 37.0, SD = 12.73). The study was approved by the Ethics Committee of the Department of Psychology at the University of Warwick, and all methods were performed in accordance with the University’s guidelines and regulations. The study design, materials, and hypotheses were pre-registered on the Open Science Framework (Ai & von Mühlenen, 2024). Design, Stimuli, and Measures The study used a between-subjects design with two independent variables: comment type (negative, neutral, or positive) and participant gender. While participants were randomly assigned to a comment condition, gender served as a quasi-experimental factor. This design aims to investigate how the two variables affected participants' mood states and anxious levels, examining their individual effects and interactions. We used AI-generated blogs to maintain better experimental control over content length and quality rather than having participants write their own blogs. This approach also minimized variability due to differences in individual writing ability and effort. There were eight blogs (short texts of 75–100 words), each underlined by a picture that matched the blog's theme. The blogs were presented in pairs, and participants had to choose each time one topic for their blog. The option to choose was primarily introduced to enhance participants’ motivation and engagement with the material (e.g., Deci & Ryan, 2013 ). The topics included the following pairs: shopping/building Lego, gaming/drinking, gardening/baking, and upscale dinner/trip. The eight pictures were sourced from an internet source of freely usable images ( www.unsplash.com ). They showed people walking in an antique shopping arcade (Fin, 2016 ), buildings built in Lego (Alphacolor, 2017 ), two people playing on videogame consoles (Jeshoots, 2017 ), a close-up image of a cocktail drink (Tai, 2019 ), a person watering garden plants (Spiske, 2018 ), a raspberry cake (Tukhfatullina, 2019 ), a salmon and vegetable dish (Lee, 2016 ), or people walking in an alleyway (Ibáñez, 2018 ). Each blog was followed by ten comments, which were either negative, neutral, or positive. For example, a negative comment would be, “These Lego models look really childish; don't you think you're too old for this?”, a neutral comment would be, “Hi, where do you usually buy your Lego sets?”, and a positive comment would be, “You're so talented with Lego, it's truly impressive!”. Thus, each participant saw 40 comments out of a total of 240 (i.e., 8 x 3 x 10) comments. The content of the blog posts and comments generated using ChatGPT (OpenAI, 2024) are fully available on the Open Science Framework (Ai & von Mühlenen, 2025; see file “Procedure.docx”). The participants’ mood states were measured using Mayer and Gaschke’s ( 1988 ) Brief Mood Introspection Scale (BMIS). The scale includes 16 adjectives describing different moods, such as ”lively”, ”happy”, or ”gloomy”. Participants were asked to rate each word on a scale from 1 (“definitely do not feel”) to 4 (“definitely feel”) to indicate how well the words described their current mood. Anxiety level was measured with Spielberger et al.’s ( 1970 ) State-Trait Anxiety Inventory (STAI original Form X-1), which is suitable for measuring anxiety across different cultures (see Spielberger et al. 1971 ). Only the state scale (STAI-S) was used, which contains 20 short statements, such as “I feel calm”, ”I feel secure”, or ”I am tense”. Participants had to rate each statement on a four-point scale from 1 (“not at all”) to 4 (“very much”) to indicate how they felt right at this moment. Procedure The experiment started by explaining the purpose of the study, the data handling, and the participant rights, followed by the consent form and questions about age and gender. In the first part of the experiment, participants were asked to imagine that they were a blogger with a hundred thousand followers who would update their blog regularly every day. They further had to imagine that they were sitting in front of their computer and that they would, with a happy heart, share something exciting. Participants then pressed “continue” before seeing the first two topics with the corresponding blogs and images. They were told they did not need to write anything; they just had to select the topic that interested them more, and the chosen blog would be automatically shared. Please note that participants were unaware that their choice had no effect whatsoever; its purpose was only to make them feel more immersed. Participants were then asked to wait while other users (apparently) were viewing and commenting on their blog. After a few seconds, a new page appeared showing the comments on their blog, which were either all negative, neutral, or positive, depending on their condition. They were asked to read the comments carefully, as they may get questions related to them later. This procedure of choosing and reading comments was repeated four times. In the second part of the experiment, participants completed the BMIS and the STAI-S. Both questionnaires contained two attention checks, where participants were asked to select a particular answer (e.g., “select 3”). After completing the questionnaires, to neutralize any negative emotions potentially caused by the comments, participants were shown a funny 90-second video on YouTube (Masefield, 2014 ). At the end, participants were debriefed and redirected to Prolific to be compensated for their participation. Data Analysis BMIS mood scores were calculated separately for each participant by adding the responses of all pleasant items (e.g., “happy”) and the reversed responses of all unpleasant items (e.g., “gloomy”; for item coding, see Mayer & Gaschke, 1988 ). The sums were then divided by sixteen, the number of items, to have the final scores again ranging from 1 to 4. Mean scores were calculated instead of sum scores, as they more clearly reflect the response scale, where 1 indicates “not at all” and 4 indicates “very much”. Individual STAI-S anxiety scores were calculated by adding all negative items (e.g., “I am tense”) and reversed positive items (e.g., “I feel calm”, for item coding, see Skapinakis, 2023 ). The sums were again divided by the number of items to have the final scores ranging from 1 to 4. The data was analyzed using JASP (JASP Team 2024 ). Results State-Trait Anxiety Inventory (STAI) Participants selecting “prefer not to say” in one or more responses (7) were excluded from the following analysis. The data from one participant who selected “other” for gender was excluded because the group size was too small for meaningful analysis. Figure 1 A shows the anxiety scores averaged across participants for each combination of Gender and Comment Type. A 2x3-way univariate ANOVA with the between-subject factors Gender (male, female) and Comment Type (negative, neutral, positive) revealed a significant main effect of Comment Type, F(2, 115) = 19.74, p < .001, η p 2 = .256. Two-tailed post-hoc tests (Holm, 1979 ) revealed that negative comments lead to significantly higher anxiety scores than neutral or positive comments (2.42 vs. 1.77 and 1.55, respectively; both p < .001, the difference between the latter two was not significant). Because Levene’s test revealed an unequal variance between groups, F(5, 115) = 5.45, p < .001, the significant Comment Type effect was confirmed with a Kruskal-Wallis test, H(2) = 26.83, p < .001. Figure 1 A suggests that male participants receiving negative or neutral comments were more anxious than female participants. However, the Gender main effect, F(1, 115) = 2.77, p = .099, η p 2 = .024, and the interaction between Gender and Comment Type, F(2, 115) = 2.37, p = .098, η p 2 = .040, were both only marginally significant. During a preliminary inspection of the data, it was discovered that the Prolific sample had an unexpectedly widespread age range (18 to 73 years). Given the evidence that older and younger adults differ in their social media use, such as frequency, purpose, and preferred platforms (Gottfried, 2024 ; Li et al., 2021 ), we decided to conduct further exploratory analyses to examine age-related effects (note that these were not pre-registered). Participants were split by the median (Mdn = 35 years) into a younger age group (N = 61, M = 26.72, SD = 4.23) and an older age group (N = 60, M = 48.13, SD = 9.37). Age Group (younger, older) was then added as an additional factor to the current design to test whether anxiety levels differed with age. The 2x2x3-way ANOVA with the factors Age Group, Gender, and Comment Type revealed a significant main effect of Age Group, F(1, 109) = 6.73, p = .011, η p 2 = .058, due to younger participants reporting to be more anxious than older participants (2.07 vs. 1.77, respectively). None of the other effects involving Age Group reached significance (all p > .20). Brief Mood Introspection Scale (BMIS) Participants selecting “prefer not to say” in one or more responses (5) were excluded from the analysis. The data from the participant selecting “other” for gender (1) was not included. The mood scores averaged across the remaining 123 participants are shown in Fig. 1 B. A 2x3-way ANOVA with the between-subject factors Gender and Comment Type revealed a significant main effect of Comment Type, F(2, 117) = 28.13, p < .001, η p 2 = .325: Two-tailed post-hoc tests revealed that negative comments lead to significantly lower mood scores than neutral or positive comments (2.37 vs. 3.05 and 3.25, respectively), mirroring the reversed pattern of the anxiety scores (compare Fig. 1 A and 1 B). Note that Levene’s test was nonsignificant for mood (p = .103), indicating sufficient equality of variance between groups. Gender effects were not significant (all p > .182). Adding Age Group as an additional factor to the ANOVA revealed a significant Age main effect, F(2, 111) = 5.10, p = .026, η p 2 = .044, due to younger participants reporting less pleasant mood than older participants (2.79 vs. 3.01, respectively). None of the interactions involving Age Group reached significance (all p > .090). Mayer and Gaschke ( 1988 ) proposed that three other sub-scores can be computed from the BMIS (in addition to pleasant versus unpleasant mood). For example, twelve of the 16 BMIS items can also be used to represent arousal (10 items, e.g., “lively”, “sad”) versus calm mood (2 items: “tired”, “calm”). Although these sub-scores were not included in the pre-registered analysis plan, they were explored in a post-hoc analysis. Individual arousal scores were calculated by summing up arousal items and reversing calm items, and by dividing the sum by the number of items. The 2 x 3 ANOVA with Gender and Comment Type revealed significant main effects for Gender, F(1, 117) = 6.15, p = .015, η p 2 = .050, and Comment Type, F(1, 117) = 4.69, p = .012, η p 2 = .073: Male participants reported overall more arousal than female participants (2.39 vs. 2.26, respectively), and negative comments lead to more arousal than neutral comments (2.44 vs. 2.24). Adding Age Group to the ANOVA revealed a significant interaction between Age Group and Condition, F(1, 111) = 4.11, p = .019, η p 2 = .069: Older participants were overall less aroused by negative or positive comments (compared to neutral comments) than younger participants (0.03 or -0.05 vs. 0.29 or 0.18, respectively). The BMIS can also represent positive versus tired mood (7 items) and negative versus relaxed mood (6 items). For positive versus tired mood, the pattern mirrored that of pleasant mood, with significant main effects for both Comment Type and Age Group. In contrast, the negative versus relaxed mood pattern resembled the inverse of pleasant mood. Blog Choices The primary purpose of allowing participants to choose blog topics was to enhance their engagement with the material. The number of participants selecting each option was as follows: shopping (n = 49) versus building Lego (n = 80), gaming (n = 63) versus drinking (n = 66), gardening (n = 60) versus baking (n = 69), and upscale dinner (n = 23) versus trip (n = 106). Independent-samples t-tests conducted for each pair revealed no significant effects on anxiety (all p > .078), pleasant mood, or the other three mood sub-scores (all p > .062), indicating that anxiety and mood were not influenced by participants’ specific topic choices. Discussion This study was designed to explore how negative comments on social media affect the mood state and anxiety levels of adults of different genders. The results showed that negative comments significantly increased anxiety and caused more unpleasant moods compared with positive or neutral comments, with gender showing only a marginal effect on anxiety and no significant influence on unpleasant moods. What we didn't expect was a wide range of ages, so we included age as a factor and found that younger people were more likely to have anxiety and negative moods than older people. These results align with previous findings on adolescents (O'Reilly et al., 2018), but extend the evidence to adults, underscoring the potential psychological impacts of negative social media interactions across age groups. Arousal levels were also affected by age, gender, and comment type. Male participants reported greater overall arousal than females, and younger participants exhibited stronger arousal responses to both negative comments. These findings mirror those of anxiety, which fits with the well-established concept that anxiety is associated with increased arousal, both subjectively and physiologically (e.g., Barlow, 2004 ). Subdividing the adult sample revealed that the adverse psychological effects of social media persisted among younger adults but appeared to diminish in older adults. Younger adults may still form their self-identity and social roles (Bonnie et al., 2015 ; Hatano et al., 2022 ), emphasising their online image and perceived social attractiveness. This heightened concern can make them more vulnerable to negative emotions in response to criticism or competitive interactions (Callan et al., 2015 ; Chou & Edge, 2012 ). Another possible explanation is that younger adults may be more affected by the psychological construct of Fear of Missing Out (FOMO), which can intensify stress responses to social comparisons and critical feedback (Przybylski et al., 2013 ) and increase feelings of jealousy (Sharifian et al., 2021 ). For example, when they see comments like "The products I purchase are more luxurious than yours," they experience increased jealousy. Jealous emotion can lead to anxiety (Irshad et al., 2024 ). Another possible explanation is that younger adults may be more affected by the psychological construct of Fear of Missing Out (FOMO), which can heighten stress reactions to social comparisons and negative feedback (Przybylski et al., 2013 ), and may also increase feelings of jealousy (Sharifian et al., 2021 ). For instance, encountering comments like “The products I purchase are more luxurious than yours” could provoke stronger jealousy responses, which in turn can fuel anxiety (Irshad et al., 2024 ). The subdivision of age in our study aligns with prior research suggesting that adults tend to be more psychologically resilient than adolescents (Gomez et al., 2013 ; Hu et al., 2015 ). This may reflect a gradual, linear increase in mental toughness across the lifespan, supporting the need for future studies to examine age-related effects in greater detail (Gooding et al., 2012 ). These findings suggest that intervention strategies should be tailored to specific age groups. For example, younger adults may benefit from cognitive reappraisal training to better manage social comparisons and reinterpret negative evaluations on social media (Denny & Ochsner, 2014 ). For older adults (35 + years), enhancing digital literacy could reduce the risk of misinterpreting online interactions, particularly through an improved understanding of algorithmic filtering and content presentation (Carrasco-Dajer et al., 2024 ). Although prior research has found gender differences in anxiety responses, with women generally reporting higher anxiety levels (Bahrami & Yousefi, 2011 ; Stumpf et al., 2015 ), our study observed slightly higher anxiety ratings among men in response to negative social media comments. This result may reflect gender-specific pressures within the context of online environments. One possible explanation is that men may experience greater pressure to conform to social expectations around emotional restraint and interpersonal conduct, particularly when attempting to maintain traditional markers of masculinity, such as projecting a positive body image (Brasil et al., 2024 ; Lonergan et al., 2021 ; Warren, 2024 ). As a result, negative evaluations may pose a stronger threat to men’s self-esteem, leading to elevated anxiety. Furthermore, men may interpret such evaluations as a challenge to their social standing, increasing the perceived risk of exclusion and triggering heightened social stress (Lamarche et al., 2017 ). In contrast to the STAI, which explicitly measures anxiety, the BMIS provides a composite assessment of the overall mood state by aggregating multiple mood components. However, this aggregation can produce a "cancellation effect" that may obscure underlying gender differences. When facing negative evaluations, individuals may experience a mix of emotional responses—such as anxiety, anger, and disappointment—whose intensity and dominance may differ by gender. For instance, women may be more likely than men to experience sadness in such situations (Samra et al., 2022 ). If one participant reports high anxiety and low sadness, and another the reverse, their overall mood scores may converge, masking actual emotional differences. Moreover, our experiment did not record individual differences among participants. For example, having prior social support and having high self-efficacy can lead to better mood and less anxiety (Rohde et al., 2023 ; Williamson et al., 2019 ). Personality traits and emotional intelligence, to a certain extent, determine individuals' coping abilities and strategies (DeLongis & Holtzman, 2005 ; Yöney, 2001 ). If men and women had similar levels in these areas, the gender difference might be cancelled out, which in line with overall explains why gender has only a very subtle effect. Although we employed a highly realistic experimental design, enhancing the external validity of the results—meaning that most people would react similarly to negative comments as the sample in our experiment (Findley et al., 2021 ). There are still many designs that need improvement. Firstly, participants may have realized they were part of an experiment, which could have led to the observer effect, where participants were aware that the experimenter would observe their data and change their responses (Sykes, 1978 ). Secondly, the comments received by participants were all generated by ChatGPT. Although these comments were designed to be negative, neutral, or positive, they may not fully reflect the complexity and diversity of comments in real social media environments. Real online comments also include non-text elements like emojis (Park et al., 2013 ). Thirdly, our participants were mainly adult native English speakers, likely from Western cultural backgrounds. Different cultures use social media differently (Kim et al., 2011 ). Individuals from specific cultural backgrounds may be more inclined to gain confidence through social media, making them more sensitive to the influence of negative comments. This study’s reliance on simulated social media comments, while valuable for experimental control, may not fully capture the complex dynamics of real-world interactions. Future studies could utilize actual social media platforms to increase ecological validity. For example, researchers could ask participants to post something during the experiment on their real Instagram account. More objective data on mood state and anxiety levels could be obtained with physiological indicators or behavioral measurements, such as heart rate, skin conductance responses, and facial expression analysis, combined with self-report measures. To more accurately reflect the social media environment, researchers can collect user comments from real media like Twitter or construct a diverse comment library that includes elements like metaphors and emojis to simulate the complexity of real comments. Furthermore, recruiting a culturally diverse sample would provide a more comprehensive understanding of how different populations are affected by social media negativity. Finally, the current findings underscore the need for social media platforms and mental health organizations to provide resources for managing negative online interactions, potentially through digital literacy programs or features that allow users to moderate their exposure to certain content. Data availability The datasets generated and analyzed during the current study, along with the corresponding R scripts, are available in the OSF repository at https://doi.org/10.17605/OSF.IO/EF4ND Declarations Data availability The datasets generated and analyzed during the current study, along with the corresponding R scripts, are available in the OSF repository at https://doi.org/10.17605/OSF.IO/EF4ND Funding This work was supported by the Undergraduate Research Support Scheme of the University of Warwick awarded to the first author (YA). Author information Authors and Affiliations Department of Psychology, University of Warwick, Coventry, CV4 7AL, United Kingdom Yuetong Ai & Adrian von Mühlenen Acknowledgements None Author contributions YA: Conceptualization, Data curation, Funding acquisition, Methodology, Formal analysis, Writing – Original Draft. AM: Conceptualization, Data curation, Formal analysis, Methodology, Writing – Review and Editing. Corresponding author Correspondence to Adrian von Mühlenen Ethics declaration Competing interests The authors declare no competing interests. References Acar, I. H., Avcılar, G., Yazıcı, G. & Bostancı, S. The roles of adolescents’ emotional problems and social media addiction on their self-esteem. Curr. Psychol. 41 (10), 6838–6847. https://doi.org/10.1007/s12144-020-01174-5 (2022). Ai, Y. & von Muhlenen, A. How Do Negative Comments Directed at Adults on Social Media Affect Their Anxious Level and Mood State. (2025)., April 3 https://doi.org/10.17605/OSF.IO/EF4ND Aimeur, E., Amri, S. & Brassard, G. Fake news, disinformation and misinformation in social media: a review. Social Netw. Anal. Min. 13 (1), 30. https://doi.org/10.1007/s13278-023-01028-5 (2023). Alipan, A., Skues, J. L. & Theiler, S. They will find another way to hurt you: Emerging adults’ perceptions of coping with cyberbullying. Emerg. Adulthood . 9 (1), 22–34. https://doi.org/10.1177/2167696818816896 (2021). Alipan, A., Skues, J. L., Theiler, S. & Wise, L. Defining cyberbullying: A multifaceted definition based on the perspectives of emerging adults. Int. J. Bullying Prev. 2 , 79–92. https://doi.org/10.1007/s42380-019-00018-6 (2020). Alphacolor. [White and multicolored building scale mode]. Unsplash. (2017). https://unsplash.com/photos/ipmwlGIXzcw Bahrami, F. & Yousefi, N. Females are more anxious than males: a metacognitive perspective. Iran. J. Psychiatry Behav. Sci. 5 (2), 83–90 (2011). Barlett, C. P., DeWitt, C. C., Maronna, B. & Johnson, K. Social media use as a tool to facilitate or reduce cyberbullying perpetration: A review focusing on anonymous and nonanonymous social media platforms. Violence Gend. 5 (3), 147–152. https://doi.org/10.1089/vio.2017.0057 (2018). Barlow, D. H. Anxiety and its disorders: The nature and treatment of anxiety and panic (Guilford Press, 2004). Bonnie, R. J., Stroud, C., Breiner, H. & National Research Council., & Young adults in the 21st century. In Investing in the health and wellbeing of young adults. National Academies Press (US). (2015). Braghieri, L., Levy, R. E. & Makarin, A. Social media and mental health. Am. Econ. Rev. 112 (11), 3660–3693. https://doi.org/10.1257/aer.20211218 (2022). Brasil, K. M., Mims, C. E., Pritchard, M. E. & McDermott, R. C. Social media and body image: Relationships between social media appearance preoccupation, self-objectification, and body image. Body Image . 51 , 101767. https://doi.org/10.1016/j.bodyim.2024.101767 (2024). Calancie, O., Ewing, L., Narducci, L. D., Horgan, S. & Khalid-Khan, S. Exploring how social networking sites impact youth with anxiety: A qualitative study of Facebook stressors among adolescents with an anxiety disorder diagnosis. Cyberpsychology: J. Psychosocial Res. Cyberspace . 11 (4). https://doi.org/10.5817/CP2017-4-2 (2017). Callan, M. J., Kim, H. & Matthews, W. J. Age differences in social comparison tendency and personal relative deprivation. Pers. Indiv. Differ. 87 , 196–199. https://doi.org/10.1016/j.paid.2015.08.003 (2015). Carrasco-Dajer, C. M., Vera-Calzaretta, A. R., Ubillos-Landa, S., Oyanedel, J. C. & Díaz-Gorriti, V. Impact of a culturally adapted digital literacy intervention on older people and its relationship with health literacy, quality of life, and wellbeing. Front. Psychol. 15 , 1305569. https://doi.org/10.3389/fpsyg.2024.1305569 (2024). Chen, G. M. & Ng, Y. M. M. Nasty online comments anger you more than me, but nice ones make me as happy as you. Comput. Hum. Behav. 71 , 181–188. https://doi.org/10.1016/j.chb.2017.02.010 (2017). Chou, H. T. G. & Edge, N. They are happier and having better lives than I am: The impact of using Facebook on perceptions of others' lives. Cyberpsychology Behav. Social Netw. 15 (2), 117–120. https://doi.org/10.1089/cyber.2011.0324 (2012). Deci, E. L. & Ryan, R. M. Intrinsic motivation and self-determination in human behavior (Springer Science & Business Media, 2013). DeLongis, A. & Holtzman, S. Coping in context: The role of stress, social support, and personality in coping. J. Pers. 73 (6), 1633–1656. https://doi.org/10.1111/j.1467-6494.2005.00361.x (2005). Denny, B. T. & Ochsner, K. N. Behavioral effects of longitudinal training in cognitive reappraisal. Emotion 14 (2), 425–433. https://doi.org/10.1037/a0035276 (2014). Faul, F., Erdfelder, E., Lang, A. G. & Buchner, A. G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods . 39 (2), 175–191. https://doi.org/10.3758/BF03193146 (2007). Fin, H. [Person walking inside building near glass]. Unsplash. (2016). https://unsplash.com/photos/2TLREZi7BUg Findley, M. G., Kikuta, K. & Denly, M. External validity. Annu. Rev. Polit. Sci. 24 (1), 365–393. https://doi.org/10.1146/annurev-polisci-041719-102556 (2021). Ge, X. Social media reduce users' moral sensitivity: Online shaming as a possible consequence. Aggressive Behav. 46 (5), 359–369. https://doi.org/10.1002/ab.21904 (2020). Gomez, M., Vincent, A. & Toussaint, L. L. Correlates of resilience in adolescents and adults. Int. J. Clin. Psychiatry Mental Health . 1 (1), 18–24. https://doi.org/10.12970/2310-8231.2013.01.01.2 (2013). Gooding, P. A., Hurst, A., Johnson, J. & Tarrier, N. Psychological resilience in young and older adults. Int. J. Geriatr. Psychiatry . 27 (3), 262–270. https://doi.org/10.1002/gps.2712 (2012). Gottfried, J. Americans’ social media use. Pew Res. Cent. , 31. (2024). https://www.jstor.org/stable/resrep63512 Hatano, K., Luyckx, K., Hihara, S., Sugimura, K., Becht, I. & A Daily identity processes and emotions in young adulthood: a five-day daily-diary method. J. Youth Adolesc. 51 (9), 1815–1828. https://doi.org/10.1007/s10964-022-01629-x (2022). Holm, S. A simple sequentially rejective multiple test procedure. Scand. J. Stat. 6 (2), 65–70 (1979). http://www.jstor.org/stable/4615733 Hu, T., Zhang, D. & Wang, J. A meta-analysis of the trait resilience and mental health. Pers. Indiv. Differ. 76 , 18–27. https://doi.org/10.1016/j.paid.2014.11.039 (2015). Hunt, M. G., Marx, R., Lipson, C. & Young, J. No more FOMO: Limiting social media decreases loneliness and depression. J. Soc. Clin. Psychol. 37 (10), 751–768. https://doi.org/10.1521/jscp.2018.37.10.751 (2018). Ibáñez, C. [Few people walking on pathway between buildings]. Unsplash. (2018). https://unsplash.com/photos/ZmqBWZoWpsI Idachaba, A. A., Ejime, O. S. & Terneng, K. Social media and the promotion of national integration in Nigeria in communication, media and power relations in a multicultural society: Context, issues and perspectives for development. ACSPN Book Series 8. (2023). http://www.acspn.com.ng Irshad, M. et al. Impact of psychological entitlement on engagement in learning activities and psychological anxiety: the mediating role of envy. BMC Psychol. 12 (1), 477. https://doi.org/10.1186/s40359-024-01961-w (2024). JASP Team. JASP (Version 0.18.3) [Computer software]. (2024). Jackson, B. F. Censorship and freedom of expression in the age of Facebook. New. Mexico Law Rev. 44 (1), 121–167 (2014). Jeshoots [Two people playing Sony PS4 game console]. Unsplash. (2017). https://unsplash.com/photos/eCktzGjC-iU Kim, Y., Sohn, D. & Choi, S. M. Cultural difference in motivations for using social network sites: A comparative study of American and Korean college students. Comput. Hum. Behav. 27 (1), 365–372. https://doi.org/10.1016/j.chb.2010.08.015 (2011). Kolas, J. & Von Mühlenen, A. Addicted to socialising and still lonely: A comparative, corpus-driven analysis of problematic social networking site use. J. Behav. Addictions . 13 (1), 163–176. https://doi.org/10.1556/2006.2023.00061 (2024a). Kolas, J. & Von Mühlenen, A. Checking in to check out? The effect of boredom on craving, behavioural inhibition and social networking site use. Int. J. Mental Health Addict. https://doi.org/10.1007/s11469-024-01349-2 (2024b). Lamarche, L., Ozimok, B., Gammage, K. L. & Muir, C. Men respond too: The effects of a social-evaluative body image threat on shame and cortisol in university men. Am. J. Men's Health . 11 (6), 1791–1803. https://doi.org/10.1177/1557988317723406 (2017). Laroche, M., Habibi, M. R. & Richard, M. O. To be or not to be in social media: How brand loyalty is affected by social media? Int. J. Inf. Manag. 33 (1), 76–82. https://doi.org/10.1016/j.ijinfomgt.2012.07.003 (2013). Lee, C. [Cooked food]. Unsplash . (2016). https://unsplash.com/photos/awj7sRviVXo Li, W., Lin, X., Wu, J., Xue, W. & Zhang, J. Impacts social media have on young generation and older adults. In 4th International Conference on Humanities Education and Social Sciences (pp. 294–300). Atlantis Press. (2021). https://doi.org/10.2991/assehr.k.211220.051 Lonergan, A. R., Mitchison, D., Bussey, K. & Fardouly, J. Social media and eating and body image concerns among men and boys. In J. M. Nagata, T. A. Brown, S. B. Murray, & J. M. Lavender (Eds.), Eating disorders in boys and men (pp. 307–316). Springer Nature Switzerland AG. (2021). https://doi.org/10.1007/978-3-030-67127-3_20 Masefield, S. Funny Xmas Communication [Video]. YouTube. (2014)., 4 December https://www.youtube.com/watch?v=YQ3qgIMURgI Mayer, J. D. & Gaschke, Y. N. The experience and meta-experience of mood. J. Personal. Soc. Psychol. 55 (1), 102–111. https://doi.org/10.1037/0022-3514.55.1.102 (1988). O'Byrne, W. I. Educate, empower, advocate: Amplifying marginalized voices in a digital society. Contemp. Issues Technol. Teacher Educ. 19 (4), 640–669 (2019). https://www.learntechlib.org/primary/p/188279/ O’Reilly, M. et al. Is social media bad for mental health and wellbeing? Exploring the perspectives of adolescents. Clin. Child Psychol. Psychiatry . 23 (4), 601–613. https://doi.org/10.1177/1359104518775154 (2018). OpenAI. ChatGPT (Mar 14 version) [Large language model]. (2023). https://chat.openai.com/chat Ossiannilsson, E. Open educational resources: A catalyst for social justice and equality. In (eds Olivier, J. & Rambow, A.) Open educational resources in higher education (15–33). Springer, Singapore. https://doi.org/10.1007/978-981-19-8590-4_2 (2023). Park, J., Barash, V., Fink, C. & Cha, M. Emoticon style: Interpreting differences in emoticons across cultures. In Proceedings of the International AAAI Conference on Web and Social Media, 7 (1), 466–475. (2013). https://doi.org/10.1609/icwsm.v7i1.14437 Petrosyan, A. Number of internet and social media users worldwide as of July 2024 [Chart]. Statista. (2024)., Aug 19 https://www.statista.com/statistics/617136/digital-population-worldwide/#statisticContainer Przybylski, A. K., Murayama, K., DeHaan, C. R. & Gladwell, V. Motivational, emotional, and behavioral correlates of fear of missing out. Comput. Hum. Behav. 29 (4), 1841–1848. https://doi.org/10.1016/j.chb.2013.02.014 (2013). Radovic, A., Gmelin, T., Stein, B. D. & Miller, E. Depressed adolescents' positive and negative use of social media. J. Adolesc. 55 , 5–15. https://doi.org/10.1016/j.adolescence.2016.12.002 (2017). Rohde, J. et al. Investigating relationships among self-efficacy, mood, and anxiety using digital technologies: Randomized controlled trial. JMIR Formative Res. 7 (1), e45749. https://doi.org/10.2196/45749 (2023). Samra, A., Warburton, W. A. & Collins, A. M. Social comparisons: A potential mechanism linking problematic social media use with depression. J. Behav. Addictions . 11 (2), 607–614. https://doi.org/10.1556/2006.2022.00023 (2022). Sharifian, N. et al. Measurement invariance of social media use in younger and older adults and links to socioemotional health. Innov. Aging . 5 (2), igab009. https://doi.org/10.1093/geroni/igab009 (2021). Shu, K., Sliva, A., Wang, S., Tang, J. & Liu, H. Fake news detection on social media: A data mining perspective. ACM SIGKDD Explorations Newsl. 19 (1), 22–36. https://doi.org/10.1145/3137597.3137600 (2017). Skapinakis, P. Spielberger state-trait anxiety inventory. In (ed Maggino, F.) Encyclopedia of quality of life and wellbeing research. Springer, Cham. https://doi.org/10.1007/978-3-031-17299-1_2825 (2023). Spielberger, C. D., Gonzalez-Reigosa, F., Martinez-Urrutia, A., Natalicio, L. F. & Natalicio, D. S. The state-trait anxiety inventory. Interamerican J. Psychol. 5 , 145–158 (1971). Spielberger, C. D., Gorsuch, R. L. & Lushene, R. E. STAI: Manual for the state-trait anxiety inventory (Consulting Psychologists, 1970). Spiske, M. [Person watering plant]. Unsplash. (2018). https://unsplash.com/photos/sFydXGrt5OA Stumpf, A. et al. Relations between the characteristics and psychological comorbidities of chronic pruritus differ between men and women: women are more anxious than men. Br. J. Dermatol. 172 (5), 1323–1328. https://doi.org/10.1111/bjd.13492 (2015). Sykes, R. E. Toward a theory of observer effect in systematic field observation. Hum. Organ. 37 (2), 148–156. https://doi.org/10.17730/humo.37.2.g663443211026724 (1978). Tai. [Clear margarita glass on selective focus photography] . Unsplash. (2019). https://unsplash.com/photos/2EBTwzczg2A Tran, R. Technology and the Arab spring: Catalyst not cause. Liberated Arts: J. Undergrad. Res. , 11 (1). (2024). Article 10. Tukhfatullina, A. [Raspberry cake]. Unsplash. (2019). https://unsplash.com/photos/Mzy-OjtCI70 Wang, X., Qiao, Y., Li, W. & Dong, W. How is online disinhibition related to adolescents’ cyberbullying perpetration? Empathy and gender as moderators. J. Early Adolescence . 42 (5), 704–732. https://doi.org/10.1177/02724316211064515 (2022). Warren, A. The association between social media, toxic masculinity, and depression in young adult males [Doctoral dissertation, National Louis University]. Digital Commons at NLU. (2024). https://digitalcommons.nl.edu/diss/852 Williamson, J. A., Oliger, C., Wheeler, A. & O’Hara, M. W. More social support is associated with more positive mood but excess support is associated with more negative mood. J. Social Personal Relationships . 36 (11–12), 3588–3610. https://doi.org/10.1177/0265407519831771 (2019). Yöney, H. Emotional intelligence. Marmara Med. J. 14 (1), 47–52 (2001). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5448411","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":449368769,"identity":"631792b7-82b7-4663-ac6a-7010bab0eeb9","order_by":0,"name":"Yuetong Ai","email":"","orcid":"","institution":"University of Warwick","correspondingAuthor":false,"prefix":"","firstName":"Yuetong","middleName":"","lastName":"Ai","suffix":""},{"id":449368770,"identity":"9ce95f06-9c7d-47b1-ad13-f51066d82622","order_by":1,"name":"Adrian von Mühlenen","email":"data:image/png;base64,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","orcid":"","institution":"University of Warwick","correspondingAuthor":true,"prefix":"","firstName":"Adrian","middleName":"","lastName":"von Mühlenen","suffix":""}],"badges":[],"createdAt":"2024-11-13 16:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5448411/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5448411/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-10810-8","type":"published","date":"2025-07-22T15:56:52+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82032238,"identity":"a69f4da4-da55-4574-a062-4b2691380e56","added_by":"auto","created_at":"2025-05-06 07:30:57","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":434030,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots showing (A) anxiety score and (B) pleasant mood score as a function of comment type (negative, neutral, positive) with separate distributions for female (blue) and male (orange) participants. Bars represent the interquartile range; whiskers indicate the full data range.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5448411/v1/84d94ddbdf06154711b2dbca.jpg"},{"id":87756573,"identity":"ba3ec22c-81c0-4f5a-ad83-01c3ceba144f","added_by":"auto","created_at":"2025-07-28 16:04:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1032956,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5448411/v1/180670fe-5866-4578-9fae-e113ad895577.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An experimental online study on the impact of negative social media comments on anxiety and mood","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWith the development of modern science and technology, social media has dramatically changed how people interact worldwide, becoming a mainstream channel of human communication. Facebook, Twitter, Instagram, and TikTok have grown rapidly, reaching over five billion users worldwide (Petrosyan, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and reshaping public discourse, communication, and information sharing. The popularity of social media has brought about an accessible means of information sharing, challenging the dominance of more traditional media such as newspapers, radio or TV. Individuals and organizations can now influence public opinion, creating social movements in ways that were not possible before. For example, the Arab Spring is a well-known event that mobilized social forces promoting social change through media like Twitter or Facebook (Tran, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This mode of communication enabled social media to transcend its technical product positioning. Social media has increasingly influenced cultural, economic, and political discourse in modern society (Idachaba et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Social media allows relatively free speech and provides rich learning resources to promote equality in education; the Open Educational Practice website is a good example (Jackson, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ossiannilsson, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, social media provides a platform for marginalized groups to make their voices heard, enabling them to bring societal changes (O'Byrne, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). It also creates a brand community for businesses to foster customer trust and loyalty (Laroche et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile social media facilitates global connectivity and information exchange, it also presents significant psychological risks, such as increased exposure to negative interactions and cyberbullying (Aimeur et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Shu et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The overuse of social media can also lead to user addiction, making them feel lonely (Kolas \u0026amp; von M\u0026uuml;hlenen, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024a\u003c/span\u003e) and affecting their emotional health (Acar et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Unwanted abstinence from or prevented access to social media can also lead to feelings of boredom and cravings (Kolas \u0026amp; von M\u0026uuml;hlenen, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBraghieri et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) conducted a quasi-experimental study by gradually introducing Facebook across colleges, allowing them to assess its impact on student mental health. Their findings revealed that the platform's rollout led to a significant decline in mental wellbeing, particularly among women, and was linked to increased use of mental health services and decreased academic performance. They attributed these effects to the role of Facebook in promoting unfavorable social comparisons\u0026mdash;highlighting the psychological costs of harmful or comparative content on social media.\u003c/p\u003e \u003cp\u003eHunt et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) conducted a randomized controlled trial in which college students were assigned either to a group that reduced their social media use or to a group that maintained their usual habits. Participants who limited their use reported significantly lower levels of loneliness and depression compared to the control group, providing further evidence that reducing exposure to potentially harmful social media content can benefit emotional wellbeing. While these studies establish a general link between social media use and mental health, relatively little is known about the specific emotional impact of negative user comments. For instance, Chen et al. (2017) found that participants exhibited stronger negative emotional responses to hostile, uncivil disagreements than to polite ones, suggesting that the tone and delivery of comments on social media may directly influence users\u0026rsquo; emotional experiences.\u003c/p\u003e \u003cp\u003eThis paper will focus on the negative effect that social media provides on cyberbullying. More specifically, on social media, users\u0026rsquo; real identities are not easily directly linked to the content they post. This promotes their perception of anonymity and generally makes them feel less morally sensitive (Barlett et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ge, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). When moral constraints are weakened, users feel less inhibited. The online disinhibition phenomenon increases the likelihood of producing negative comments on social media (Wang et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These negative comments, including \u0026ndash; but not limited to \u0026ndash; sarcasm, personal attacks, malicious provocations and discrimination, can often contribute to psychological distress. Studies indicate that cyberbullying on social media correlates with increased psychological stress and depressive symptoms (O'Reilly et al., 2018; Radovic et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In addition, negative comments can aggravate an individual\u0026rsquo;s symptoms. Adolescents with anxiety disorders often have low self-esteem, which makes them more sensitive to comments on social media (Calancie et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Even minor negative comments can impact their self-esteem, which is going to lead to more anxiety, possibly creating a vicious cycle. Fortunately, with the publication of these studies, more attention has been paid to the impact of negative comments on adolescents, and interventions have been proposed.\u003c/p\u003e \u003cp\u003eMost previous research has examined the impact of negative comments on adolescents, yet there is limited understanding of these effects in adults (Alipan, 2020, 2021). This study uses an experimental method to address this gap by evaluating the effects of negative social media comments on adult anxiety and mood, hypothesizing that such comments will elevate anxiety and reduce mood. Previous research has also shown that women are more likely to feel anxious than men (Bahrami \u0026amp; Yousefi, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Stumpf et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Therefore, it is predicted that female participants will be more affected by negative comments than male participants.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eA power analysis using G-Power (Faul et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) indicated that a minimum of 128 participants would be required to detect a medium effect size (f\u0026thinsp;=\u0026thinsp;.25) in a 2 (Gender) x 3 (Comment Type) between-subjects ANOVA, with α\u0026thinsp;=\u0026thinsp;0.05 and power (1 \u0026ndash; β)\u0026thinsp;=\u0026thinsp;0.80. To account for potential attrition, 142 adult participants were recruited via Prolific's online research platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.prolific.com\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.prolific.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Only English-speaking participants were chosen to ensure they understood the written blogs and comments well. All participants gave written informed consent and were compensated \u0026pound;7 for participation. Twelve participants chose to withdraw their data at the end of the study, and one participant failed the attention checks, leaving 129 participants (85 females, 43 males, and 1 \u0026ldquo;other\u0026rdquo;), all over 18 years old (M\u0026thinsp;=\u0026thinsp;37.0, SD\u0026thinsp;=\u0026thinsp;12.73). The study was approved by the Ethics Committee of the Department of Psychology at the University of Warwick, and all methods were performed in accordance with the University\u0026rsquo;s guidelines and regulations. The study design, materials, and hypotheses were pre-registered on the Open Science Framework (Ai \u0026amp; von M\u0026uuml;hlenen, 2024).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDesign, Stimuli, and Measures\u003c/h3\u003e\n\u003cp\u003eThe study used a between-subjects design with two independent variables: comment type (negative, neutral, or positive) and participant gender. While participants were randomly assigned to a comment condition, gender served as a quasi-experimental factor. This design aims to investigate how the two variables affected participants' mood states and anxious levels, examining their individual effects and interactions.\u003c/p\u003e \u003cp\u003eWe used AI-generated blogs to maintain better experimental control over content length and quality rather than having participants write their own blogs. This approach also minimized variability due to differences in individual writing ability and effort. There were eight blogs (short texts of 75\u0026ndash;100 words), each underlined by a picture that matched the blog's theme. The blogs were presented in pairs, and participants had to choose each time one topic for their blog. The option to choose was primarily introduced to enhance participants\u0026rsquo; motivation and engagement with the material (e.g., Deci \u0026amp; Ryan, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The topics included the following pairs: shopping/building Lego, gaming/drinking, gardening/baking, and upscale dinner/trip. The eight pictures were sourced from an internet source of freely usable images (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.unsplash.com\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.unsplash.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). They showed people walking in an antique shopping arcade (Fin, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), buildings built in Lego (Alphacolor, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), two people playing on videogame consoles (Jeshoots, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), a close-up image of a cocktail drink (Tai, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), a person watering garden plants (Spiske, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), a raspberry cake (Tukhfatullina, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), a salmon and vegetable dish (Lee, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), or people walking in an alleyway (Ib\u0026aacute;\u0026ntilde;ez, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Each blog was followed by ten comments, which were either negative, neutral, or positive. For example, a negative comment would be, \u0026ldquo;These Lego models look really childish; don't you think you're too old for this?\u0026rdquo;, a neutral comment would be, \u0026ldquo;Hi, where do you usually buy your Lego sets?\u0026rdquo;, and a positive comment would be, \u0026ldquo;You're so talented with Lego, it's truly impressive!\u0026rdquo;. Thus, each participant saw 40 comments out of a total of 240 (i.e., 8 x 3 x 10) comments. The content of the blog posts and comments generated using ChatGPT (OpenAI, 2024) are fully available on the Open Science Framework (Ai \u0026amp; von M\u0026uuml;hlenen, 2025; see file \u0026ldquo;Procedure.docx\u0026rdquo;).\u003c/p\u003e \u003cp\u003eThe participants\u0026rsquo; mood states were measured using Mayer and Gaschke\u0026rsquo;s (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1988\u003c/span\u003e) Brief Mood Introspection Scale (BMIS). The scale includes 16 adjectives describing different moods, such as \u0026rdquo;lively\u0026rdquo;, \u0026rdquo;happy\u0026rdquo;, or \u0026rdquo;gloomy\u0026rdquo;. Participants were asked to rate each word on a scale from 1 (\u0026ldquo;definitely do not feel\u0026rdquo;) to 4 (\u0026ldquo;definitely feel\u0026rdquo;) to indicate how well the words described their current mood. Anxiety level was measured with Spielberger et al.\u0026rsquo;s (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1970\u003c/span\u003e) State-Trait Anxiety Inventory (STAI original Form X-1), which is suitable for measuring anxiety across different cultures (see Spielberger et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1971\u003c/span\u003e). Only the state scale (STAI-S) was used, which contains 20 short statements, such as \u0026ldquo;I feel calm\u0026rdquo;, \u0026rdquo;I feel secure\u0026rdquo;, or \u0026rdquo;I am tense\u0026rdquo;. Participants had to rate each statement on a four-point scale from 1 (\u0026ldquo;not at all\u0026rdquo;) to 4 (\u0026ldquo;very much\u0026rdquo;) to indicate how they felt right at this moment.\u003c/p\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eThe experiment started by explaining the purpose of the study, the data handling, and the participant rights, followed by the consent form and questions about age and gender. In the first part of the experiment, participants were asked to imagine that they were a blogger with a hundred thousand followers who would update their blog regularly every day. They further had to imagine that they were sitting in front of their computer and that they would, with a happy heart, share something exciting. Participants then pressed \u0026ldquo;continue\u0026rdquo; before seeing the first two topics with the corresponding blogs and images. They were told they did not need to write anything; they just had to select the topic that interested them more, and the chosen blog would be automatically shared. Please note that participants were unaware that their choice had no effect whatsoever; its purpose was only to make them feel more immersed. Participants were then asked to wait while other users (apparently) were viewing and commenting on their blog. After a few seconds, a new page appeared showing the comments on their blog, which were either all negative, neutral, or positive, depending on their condition. They were asked to read the comments carefully, as they may get questions related to them later. This procedure of choosing and reading comments was repeated four times.\u003c/p\u003e \u003cp\u003eIn the second part of the experiment, participants completed the BMIS and the STAI-S. Both questionnaires contained two attention checks, where participants were asked to select a particular answer (e.g., \u0026ldquo;select 3\u0026rdquo;). After completing the questionnaires, to neutralize any negative emotions potentially caused by the comments, participants were shown a funny 90-second video on YouTube (Masefield, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). At the end, participants were debriefed and redirected to Prolific to be compensated for their participation.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eBMIS mood scores were calculated separately for each participant by adding the responses of all pleasant items (e.g., \u0026ldquo;happy\u0026rdquo;) and the reversed responses of all unpleasant items (e.g., \u0026ldquo;gloomy\u0026rdquo;; for item coding, see Mayer \u0026amp; Gaschke, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). The sums were then divided by sixteen, the number of items, to have the final scores again ranging from 1 to 4. Mean scores were calculated instead of sum scores, as they more clearly reflect the response scale, where 1 indicates \u0026ldquo;not at all\u0026rdquo; and 4 indicates \u0026ldquo;very much\u0026rdquo;. Individual STAI-S anxiety scores were calculated by adding all negative items (e.g., \u0026ldquo;I am tense\u0026rdquo;) and reversed positive items (e.g., \u0026ldquo;I feel calm\u0026rdquo;, for item coding, see Skapinakis, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The sums were again divided by the number of items to have the final scores ranging from 1 to 4. The data was analyzed using JASP (JASP Team \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eState-Trait Anxiety Inventory (STAI)\u003c/h2\u003e \u003cp\u003eParticipants selecting \u0026ldquo;prefer not to say\u0026rdquo; in one or more responses (7) were excluded from the following analysis. The data from one participant who selected \u0026ldquo;other\u0026rdquo; for gender was excluded because the group size was too small for meaningful analysis. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA shows the anxiety scores averaged across participants for each combination of Gender and Comment Type.\u003c/p\u003e \u003cp\u003eA 2x3-way univariate ANOVA with the between-subject factors Gender (male, female) and Comment Type (negative, neutral, positive) revealed a significant main effect of Comment Type, F(2, 115)\u0026thinsp;=\u0026thinsp;19.74, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.256. Two-tailed post-hoc tests (Holm, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1979\u003c/span\u003e) revealed that negative comments lead to significantly higher anxiety scores than neutral or positive comments (2.42 vs. 1.77 and 1.55, respectively; both p\u0026thinsp;\u0026lt;\u0026thinsp;.001, the difference between the latter two was not significant). Because Levene\u0026rsquo;s test revealed an unequal variance between groups, F(5, 115)\u0026thinsp;=\u0026thinsp;5.45, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, the significant Comment Type effect was confirmed with a Kruskal-Wallis test, H(2)\u0026thinsp;=\u0026thinsp;26.83, p\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA suggests that male participants receiving negative or neutral comments were more anxious than female participants. However, the Gender main effect, F(1, 115)\u0026thinsp;=\u0026thinsp;2.77, p\u0026thinsp;=\u0026thinsp;.099, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.024, and the interaction between Gender and Comment Type, F(2, 115)\u0026thinsp;=\u0026thinsp;2.37, p\u0026thinsp;=\u0026thinsp;.098, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.040, were both only marginally significant. During a preliminary inspection of the data, it was discovered that the Prolific sample had an unexpectedly widespread age range (18 to 73 years). Given the evidence that older and younger adults differ in their social media use, such as frequency, purpose, and preferred platforms (Gottfried, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), we decided to conduct further exploratory analyses to examine age-related effects (note that these were not pre-registered). Participants were split by the median (Mdn\u0026thinsp;=\u0026thinsp;35 years) into a younger age group (N\u0026thinsp;=\u0026thinsp;61, M\u0026thinsp;=\u0026thinsp;26.72, SD\u0026thinsp;=\u0026thinsp;4.23) and an older age group (N\u0026thinsp;=\u0026thinsp;60, M\u0026thinsp;=\u0026thinsp;48.13, SD\u0026thinsp;=\u0026thinsp;9.37). Age Group (younger, older) was then added as an additional factor to the current design to test whether anxiety levels differed with age. The 2x2x3-way ANOVA with the factors Age Group, Gender, and Comment Type revealed a significant main effect of Age Group, F(1, 109)\u0026thinsp;=\u0026thinsp;6.73, p\u0026thinsp;=\u0026thinsp;.011, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.058, due to younger participants reporting to be more anxious than older participants (2.07 vs. 1.77, respectively). None of the other effects involving Age Group reached significance (all p\u0026thinsp;\u0026gt;\u0026thinsp;.20).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBrief Mood Introspection Scale (BMIS)\u003c/h3\u003e\n\u003cp\u003e Participants selecting \u0026ldquo;prefer not to say\u0026rdquo; in one or more responses (5) were excluded from the analysis. The data from the participant selecting \u0026ldquo;other\u0026rdquo; for gender (1) was not included. The mood scores averaged across the remaining 123 participants are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB.\u003c/p\u003e \u003cp\u003eA 2x3-way ANOVA with the between-subject factors Gender and Comment Type revealed a significant main effect of Comment Type, F(2, 117)\u0026thinsp;=\u0026thinsp;28.13, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.325: Two-tailed post-hoc tests revealed that negative comments lead to significantly lower mood scores than neutral or positive comments (2.37 vs. 3.05 and 3.25, respectively), mirroring the reversed pattern of the anxiety scores (compare Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Note that Levene\u0026rsquo;s test was nonsignificant for mood (p\u0026thinsp;=\u0026thinsp;.103), indicating sufficient equality of variance between groups. Gender effects were not significant (all p\u0026thinsp;\u0026gt;\u0026thinsp;.182). Adding Age Group as an additional factor to the ANOVA revealed a significant Age main effect, F(2, 111)\u0026thinsp;=\u0026thinsp;5.10, p\u0026thinsp;=\u0026thinsp;.026, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.044, due to younger participants reporting less pleasant mood than older participants (2.79 vs. 3.01, respectively). None of the interactions involving Age Group reached significance (all p\u0026thinsp;\u0026gt;\u0026thinsp;.090).\u003c/p\u003e \u003cp\u003eMayer and Gaschke (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1988\u003c/span\u003e) proposed that three other sub-scores can be computed from the BMIS (in addition to pleasant versus unpleasant mood). For example, twelve of the 16 BMIS items can also be used to represent arousal (10 items, e.g., \u0026ldquo;lively\u0026rdquo;, \u0026ldquo;sad\u0026rdquo;) versus calm mood (2 items: \u0026ldquo;tired\u0026rdquo;, \u0026ldquo;calm\u0026rdquo;). Although these sub-scores were not included in the pre-registered analysis plan, they were explored in a post-hoc analysis. Individual arousal scores were calculated by summing up arousal items and reversing calm items, and by dividing the sum by the number of items. The 2 x 3 ANOVA with Gender and Comment Type revealed significant main effects for Gender, F(1, 117)\u0026thinsp;=\u0026thinsp;6.15, p\u0026thinsp;=\u0026thinsp;.015, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.050, and Comment Type, F(1, 117)\u0026thinsp;=\u0026thinsp;4.69, p\u0026thinsp;=\u0026thinsp;.012, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.073: Male participants reported overall more arousal than female participants (2.39 vs. 2.26, respectively), and negative comments lead to more arousal than neutral comments (2.44 vs. 2.24). Adding Age Group to the ANOVA revealed a significant interaction between Age Group and Condition, F(1, 111)\u0026thinsp;=\u0026thinsp;4.11, p\u0026thinsp;=\u0026thinsp;.019, η\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.069: Older participants were overall less aroused by negative or positive comments (compared to neutral comments) than younger participants (0.03 or -0.05 vs. 0.29 or 0.18, respectively).\u003c/p\u003e \u003cp\u003eThe BMIS can also represent positive versus tired mood (7 items) and negative versus relaxed mood (6 items). For positive versus tired mood, the pattern mirrored that of pleasant mood, with significant main effects for both Comment Type and Age Group. In contrast, the negative versus relaxed mood pattern resembled the inverse of pleasant mood.\u003c/p\u003e\n\u003ch3\u003eBlog Choices\u003c/h3\u003e\n\u003cp\u003eThe primary purpose of allowing participants to choose blog topics was to enhance their engagement with the material. The number of participants selecting each option was as follows: shopping (n\u0026thinsp;=\u0026thinsp;49) versus building Lego (n\u0026thinsp;=\u0026thinsp;80), gaming (n\u0026thinsp;=\u0026thinsp;63) versus drinking (n\u0026thinsp;=\u0026thinsp;66), gardening (n\u0026thinsp;=\u0026thinsp;60) versus baking (n\u0026thinsp;=\u0026thinsp;69), and upscale dinner (n\u0026thinsp;=\u0026thinsp;23) versus trip (n\u0026thinsp;=\u0026thinsp;106). Independent-samples t-tests conducted for each pair revealed no significant effects on anxiety (all p\u0026thinsp;\u0026gt;\u0026thinsp;.078), pleasant mood, or the other three mood sub-scores (all p\u0026thinsp;\u0026gt;\u0026thinsp;.062), indicating that anxiety and mood were not influenced by participants\u0026rsquo; specific topic choices.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study was designed to explore how negative comments on social media affect the mood state and anxiety levels of adults of different genders. The results showed that negative comments significantly increased anxiety and caused more unpleasant moods compared with positive or neutral comments, with gender showing only a marginal effect on anxiety and no significant influence on unpleasant moods. What we didn't expect was a wide range of ages, so we included age as a factor and found that younger people were more likely to have anxiety and negative moods than older people. These results align with previous findings on adolescents (O'Reilly et al., 2018), but extend the evidence to adults, underscoring the potential psychological impacts of negative social media interactions across age groups. Arousal levels were also affected by age, gender, and comment type. Male participants reported greater overall arousal than females, and younger participants exhibited stronger arousal responses to both negative comments. These findings mirror those of anxiety, which fits with the well-established concept that anxiety is associated with increased arousal, both subjectively and physiologically (e.g., Barlow, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSubdividing the adult sample revealed that the adverse psychological effects of social media persisted among younger adults but appeared to diminish in older adults. Younger adults may still form their self-identity and social roles (Bonnie et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Hatano et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), emphasising their online image and perceived social attractiveness. This heightened concern can make them more vulnerable to negative emotions in response to criticism or competitive interactions (Callan et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Chou \u0026amp; Edge, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Another possible explanation is that younger adults may be more affected by the psychological construct of Fear of Missing Out (FOMO), which can intensify stress responses to social comparisons and critical feedback (Przybylski et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and increase feelings of jealousy (Sharifian et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For example, when they see comments like \"The products I purchase are more luxurious than yours,\" they experience increased jealousy. Jealous emotion can lead to anxiety (Irshad et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Another possible explanation is that younger adults may be more affected by the psychological construct of Fear of Missing Out (FOMO), which can heighten stress reactions to social comparisons and negative feedback (Przybylski et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and may also increase feelings of jealousy (Sharifian et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For instance, encountering comments like \u0026ldquo;The products I purchase are more luxurious than yours\u0026rdquo; could provoke stronger jealousy responses, which in turn can fuel anxiety (Irshad et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe subdivision of age in our study aligns with prior research suggesting that adults tend to be more psychologically resilient than adolescents (Gomez et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Hu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This may reflect a gradual, linear increase in mental toughness across the lifespan, supporting the need for future studies to examine age-related effects in greater detail (Gooding et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). These findings suggest that intervention strategies should be tailored to specific age groups. For example, younger adults may benefit from cognitive reappraisal training to better manage social comparisons and reinterpret negative evaluations on social media (Denny \u0026amp; Ochsner, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). For older adults (35\u0026thinsp;+\u0026thinsp;years), enhancing digital literacy could reduce the risk of misinterpreting online interactions, particularly through an improved understanding of algorithmic filtering and content presentation (Carrasco-Dajer et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough prior research has found gender differences in anxiety responses, with women generally reporting higher anxiety levels (Bahrami \u0026amp; Yousefi, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Stumpf et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), our study observed slightly higher anxiety ratings among men in response to negative social media comments. This result may reflect gender-specific pressures within the context of online environments. One possible explanation is that men may experience greater pressure to conform to social expectations around emotional restraint and interpersonal conduct, particularly when attempting to maintain traditional markers of masculinity, such as projecting a positive body image (Brasil et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Lonergan et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Warren, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). As a result, negative evaluations may pose a stronger threat to men\u0026rsquo;s self-esteem, leading to elevated anxiety. Furthermore, men may interpret such evaluations as a challenge to their social standing, increasing the perceived risk of exclusion and triggering heightened social stress (Lamarche et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn contrast to the STAI, which explicitly measures anxiety, the BMIS provides a composite assessment of the overall mood state by aggregating multiple mood components. However, this aggregation can produce a \"cancellation effect\" that may obscure underlying gender differences. When facing negative evaluations, individuals may experience a mix of emotional responses\u0026mdash;such as anxiety, anger, and disappointment\u0026mdash;whose intensity and dominance may differ by gender. For instance, women may be more likely than men to experience sadness in such situations (Samra et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). If one participant reports high anxiety and low sadness, and another the reverse, their overall mood scores may converge, masking actual emotional differences.\u003c/p\u003e \u003cp\u003eMoreover, our experiment did not record individual differences among participants. For example, having prior social support and having high self-efficacy can lead to better mood and less anxiety (Rohde et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Williamson et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Personality traits and emotional intelligence, to a certain extent, determine individuals' coping abilities and strategies (DeLongis \u0026amp; Holtzman, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Y\u0026ouml;ney, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). If men and women had similar levels in these areas, the gender difference might be cancelled out, which in line with overall explains why gender has only a very subtle effect.\u003c/p\u003e \u003cp\u003eAlthough we employed a highly realistic experimental design, enhancing the external validity of the results\u0026mdash;meaning that most people would react similarly to negative comments as the sample in our experiment (Findley et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). There are still many designs that need improvement. Firstly, participants may have realized they were part of an experiment, which could have led to the observer effect, where participants were aware that the experimenter would observe their data and change their responses (Sykes, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1978\u003c/span\u003e). Secondly, the comments received by participants were all generated by ChatGPT. Although these comments were designed to be negative, neutral, or positive, they may not fully reflect the complexity and diversity of comments in real social media environments. Real online comments also include non-text elements like emojis (Park et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Thirdly, our participants were mainly adult native English speakers, likely from Western cultural backgrounds. Different cultures use social media differently (Kim et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Individuals from specific cultural backgrounds may be more inclined to gain confidence through social media, making them more sensitive to the influence of negative comments.\u003c/p\u003e \u003cp\u003eThis study\u0026rsquo;s reliance on simulated social media comments, while valuable for experimental control, may not fully capture the complex dynamics of real-world interactions. Future studies could utilize actual social media platforms to increase ecological validity. For example, researchers could ask participants to post something during the experiment on their real Instagram account. More objective data on mood state and anxiety levels could be obtained with physiological indicators or behavioral measurements, such as heart rate, skin conductance responses, and facial expression analysis, combined with self-report measures. To more accurately reflect the social media environment, researchers can collect user comments from real media like Twitter or construct a diverse comment library that includes elements like metaphors and emojis to simulate the complexity of real comments. Furthermore, recruiting a culturally diverse sample would provide a more comprehensive understanding of how different populations are affected by social media negativity. Finally, the current findings underscore the need for social media platforms and mental health organizations to provide resources for managing negative online interactions, potentially through digital literacy programs or features that allow users to moderate their exposure to certain content.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eThe datasets generated and analyzed during the current study, along with the corresponding R scripts, are available in the OSF repository at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.17605/OSF.IO/EF4ND\u003c/span\u003e\u003cspan address=\"10.17605/OSF.IO/EF4ND\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study, along with the corresponding R scripts, are available in the OSF repository at https://doi.org/10.17605/OSF.IO/EF4ND\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Undergraduate Research Support Scheme of the University of Warwick awarded to the first author (YA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Psychology, University of Warwick, Coventry, CV4 7AL, United Kingdom\u003c/p\u003e\n\u003cp\u003eYuetong Ai \u0026amp; Adrian von M\u0026uuml;hlenen\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYA: Conceptualization, Data curation, Funding acquisition, Methodology, Formal analysis, \u0026nbsp;Writing \u0026ndash; Original Draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAM: Conceptualization, Data curation, Formal analysis, Methodology, Writing \u0026ndash; Review and Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Adrian von M\u0026uuml;hlenen\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAcar, I. H., Avcılar, G., Yazıcı, G. \u0026amp; Bostancı, S. The roles of adolescents\u0026rsquo; emotional problems and social media addiction on their self-esteem. \u003cem\u003eCurr. Psychol.\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e (10), 6838\u0026ndash;6847. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12144-020-01174-5\u003c/span\u003e\u003cspan address=\"10.1007/s12144-020-01174-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAi, Y. \u0026amp; von Muhlenen, A. How Do Negative Comments Directed at Adults on Social Media Affect Their Anxious Level and Mood State. (2025)., April 3 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.17605/OSF.IO/EF4ND\u003c/span\u003e\u003cspan address=\"10.17605/OSF.IO/EF4ND\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAimeur, E., Amri, S. \u0026amp; Brassard, G. Fake news, disinformation and misinformation in social media: a review. \u003cem\u003eSocial Netw. Anal. Min.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e (1), 30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s13278-023-01028-5\u003c/span\u003e\u003cspan address=\"10.1007/s13278-023-01028-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlipan, A., Skues, J. L. \u0026amp; Theiler, S. They will find another way to hurt you: Emerging adults\u0026rsquo; perceptions of coping with cyberbullying. \u003cem\u003eEmerg. Adulthood\u003c/em\u003e. \u003cb\u003e9\u003c/b\u003e (1), 22\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/2167696818816896\u003c/span\u003e\u003cspan address=\"10.1177/2167696818816896\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlipan, A., Skues, J. L., Theiler, S. \u0026amp; Wise, L. Defining cyberbullying: A multifaceted definition based on the perspectives of emerging adults. \u003cem\u003eInt. J. Bullying Prev.\u003c/em\u003e \u003cb\u003e2\u003c/b\u003e, 79\u0026ndash;92. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s42380-019-00018-6\u003c/span\u003e\u003cspan address=\"10.1007/s42380-019-00018-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlphacolor. \u003cem\u003e[White and multicolored building scale mode]. Unsplash.\u003c/em\u003e (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://unsplash.com/photos/ipmwlGIXzcw\u003c/span\u003e\u003cspan address=\"https://unsplash.com/photos/ipmwlGIXzcw\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBahrami, F. \u0026amp; Yousefi, N. Females are more anxious than males: a metacognitive perspective. \u003cem\u003eIran. J. Psychiatry Behav. Sci.\u003c/em\u003e \u003cb\u003e5\u003c/b\u003e (2), 83\u0026ndash;90 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarlett, C. P., DeWitt, C. C., Maronna, B. \u0026amp; Johnson, K. Social media use as a tool to facilitate or reduce cyberbullying perpetration: A review focusing on anonymous and nonanonymous social media platforms. \u003cem\u003eViolence Gend.\u003c/em\u003e \u003cb\u003e5\u003c/b\u003e (3), 147\u0026ndash;152. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1089/vio.2017.0057\u003c/span\u003e\u003cspan address=\"10.1089/vio.2017.0057\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarlow, D. H. \u003cem\u003eAnxiety and its disorders: The nature and treatment of anxiety and panic\u003c/em\u003e (Guilford Press, 2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBonnie, R. J., Stroud, C., Breiner, H. \u0026amp; National Research Council., \u0026amp; Young adults in the 21st century. In Investing in the health and wellbeing of young adults. National Academies Press (US). (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBraghieri, L., Levy, R. E. \u0026amp; Makarin, A. Social media and mental health. \u003cem\u003eAm. Econ. Rev.\u003c/em\u003e \u003cb\u003e112\u003c/b\u003e (11), 3660\u0026ndash;3693. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1257/aer.20211218\u003c/span\u003e\u003cspan address=\"10.1257/aer.20211218\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrasil, K. M., Mims, C. E., Pritchard, M. E. \u0026amp; McDermott, R. C. Social media and body image: Relationships between social media appearance preoccupation, self-objectification, and body image. \u003cem\u003eBody Image\u003c/em\u003e. \u003cb\u003e51\u003c/b\u003e, 101767. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.bodyim.2024.101767\u003c/span\u003e\u003cspan address=\"10.1016/j.bodyim.2024.101767\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCalancie, O., Ewing, L., Narducci, L. D., Horgan, S. \u0026amp; Khalid-Khan, S. Exploring how social networking sites impact youth with anxiety: A qualitative study of Facebook stressors among adolescents with an anxiety disorder diagnosis. \u003cem\u003eCyberpsychology: J. Psychosocial Res. Cyberspace\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e (4). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5817/CP2017-4-2\u003c/span\u003e\u003cspan address=\"10.5817/CP2017-4-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCallan, M. J., Kim, H. \u0026amp; Matthews, W. J. Age differences in social comparison tendency and personal relative deprivation. \u003cem\u003ePers. Indiv. Differ.\u003c/em\u003e \u003cb\u003e87\u003c/b\u003e, 196\u0026ndash;199. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.paid.2015.08.003\u003c/span\u003e\u003cspan address=\"10.1016/j.paid.2015.08.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarrasco-Dajer, C. M., Vera-Calzaretta, A. R., Ubillos-Landa, S., Oyanedel, J. C. \u0026amp; D\u0026iacute;az-Gorriti, V. Impact of a culturally adapted digital literacy intervention on older people and its relationship with health literacy, quality of life, and wellbeing. \u003cem\u003eFront. Psychol.\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e, 1305569. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fpsyg.2024.1305569\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2024.1305569\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen, G. M. \u0026amp; Ng, Y. M. M. Nasty online comments anger you more than me, but nice ones make me as happy as you. \u003cem\u003eComput. Hum. Behav.\u003c/em\u003e \u003cb\u003e71\u003c/b\u003e, 181\u0026ndash;188. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.chb.2017.02.010\u003c/span\u003e\u003cspan address=\"10.1016/j.chb.2017.02.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChou, H. T. G. \u0026amp; Edge, N. They are happier and having better lives than I am: The impact of using Facebook on perceptions of others' lives. \u003cem\u003eCyberpsychology Behav. Social Netw.\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e (2), 117\u0026ndash;120. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1089/cyber.2011.0324\u003c/span\u003e\u003cspan address=\"10.1089/cyber.2011.0324\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeci, E. L. \u0026amp; Ryan, R. M. \u003cem\u003eIntrinsic motivation and self-determination in human behavior\u003c/em\u003e (Springer Science \u0026amp; Business Media, 2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeLongis, A. \u0026amp; Holtzman, S. Coping in context: The role of stress, social support, and personality in coping. \u003cem\u003eJ. Pers.\u003c/em\u003e \u003cb\u003e73\u003c/b\u003e (6), 1633\u0026ndash;1656. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1467-6494.2005.00361.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1467-6494.2005.00361.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDenny, B. T. \u0026amp; Ochsner, K. N. Behavioral effects of longitudinal training in cognitive reappraisal. \u003cem\u003eEmotion\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e (2), 425\u0026ndash;433. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/a0035276\u003c/span\u003e\u003cspan address=\"10.1037/a0035276\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFaul, F., Erdfelder, E., Lang, A. G. \u0026amp; Buchner, A. G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. \u003cem\u003eBehav. Res. Methods\u003c/em\u003e. \u003cb\u003e39\u003c/b\u003e (2), 175\u0026ndash;191. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3758/BF03193146\u003c/span\u003e\u003cspan address=\"10.3758/BF03193146\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFin, H. \u003cem\u003e[Person walking inside building near glass]. Unsplash.\u003c/em\u003e (2016). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://unsplash.com/photos/2TLREZi7BUg\u003c/span\u003e\u003cspan address=\"https://unsplash.com/photos/2TLREZi7BUg\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFindley, M. G., Kikuta, K. \u0026amp; Denly, M. External validity. \u003cem\u003eAnnu. Rev. Polit. Sci.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e (1), 365\u0026ndash;393. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1146/annurev-polisci-041719-102556\u003c/span\u003e\u003cspan address=\"10.1146/annurev-polisci-041719-102556\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGe, X. Social media reduce users' moral sensitivity: Online shaming as a possible consequence. \u003cem\u003eAggressive Behav.\u003c/em\u003e \u003cb\u003e46\u003c/b\u003e (5), 359\u0026ndash;369. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ab.21904\u003c/span\u003e\u003cspan address=\"10.1002/ab.21904\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGomez, M., Vincent, A. \u0026amp; Toussaint, L. L. Correlates of resilience in adolescents and adults. \u003cem\u003eInt. J. Clin. Psychiatry Mental Health\u003c/em\u003e. \u003cb\u003e1\u003c/b\u003e (1), 18\u0026ndash;24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.12970/2310-8231.2013.01.01.2\u003c/span\u003e\u003cspan address=\"10.12970/2310-8231.2013.01.01.2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGooding, P. A., Hurst, A., Johnson, J. \u0026amp; Tarrier, N. Psychological resilience in young and older adults. \u003cem\u003eInt. J. Geriatr. Psychiatry\u003c/em\u003e. \u003cb\u003e27\u003c/b\u003e (3), 262\u0026ndash;270. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/gps.2712\u003c/span\u003e\u003cspan address=\"10.1002/gps.2712\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGottfried, J. Americans\u0026rsquo; social media use. \u003cem\u003ePew Res. Cent.\u003c/em\u003e, 31. (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.jstor.org/stable/resrep63512\u003c/span\u003e\u003cspan address=\"https://www.jstor.org/stable/resrep63512\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHatano, K., Luyckx, K., Hihara, S., Sugimura, K., Becht, I. \u0026amp; A Daily identity processes and emotions in young adulthood: a five-day daily-diary method. \u003cem\u003eJ. Youth Adolesc.\u003c/em\u003e \u003cb\u003e51\u003c/b\u003e (9), 1815\u0026ndash;1828. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10964-022-01629-x\u003c/span\u003e\u003cspan address=\"10.1007/s10964-022-01629-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHolm, S. A simple sequentially rejective multiple test procedure. \u003cem\u003eScand. J. Stat.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e (2), 65\u0026ndash;70 (1979). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.jstor.org/stable/4615733\u003c/span\u003e\u003cspan address=\"http://www.jstor.org/stable/4615733\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu, T., Zhang, D. \u0026amp; Wang, J. A meta-analysis of the trait resilience and mental health. \u003cem\u003ePers. Indiv. Differ.\u003c/em\u003e \u003cb\u003e76\u003c/b\u003e, 18\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.paid.2014.11.039\u003c/span\u003e\u003cspan address=\"10.1016/j.paid.2014.11.039\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHunt, M. G., Marx, R., Lipson, C. \u0026amp; Young, J. No more FOMO: Limiting social media decreases loneliness and depression. \u003cem\u003eJ. Soc. Clin. Psychol.\u003c/em\u003e \u003cb\u003e37\u003c/b\u003e (10), 751\u0026ndash;768. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1521/jscp.2018.37.10.751\u003c/span\u003e\u003cspan address=\"10.1521/jscp.2018.37.10.751\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIb\u0026aacute;\u0026ntilde;ez, C. \u003cem\u003e[Few people walking on pathway between buildings]. Unsplash.\u003c/em\u003e (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://unsplash.com/photos/ZmqBWZoWpsI\u003c/span\u003e\u003cspan address=\"https://unsplash.com/photos/ZmqBWZoWpsI\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIdachaba, A. A., Ejime, O. S. \u0026amp; Terneng, K. \u003cem\u003eSocial media and the promotion of national integration in Nigeria in communication, media and power relations in a multicultural society: Context, issues and perspectives for development.\u003c/em\u003e ACSPN Book Series 8. (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.acspn.com.ng\u003c/span\u003e\u003cspan address=\"http://www.acspn.com.ng\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIrshad, M. et al. Impact of psychological entitlement on engagement in learning activities and psychological anxiety: the mediating role of envy. \u003cem\u003eBMC Psychol.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e (1), 477. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s40359-024-01961-w\u003c/span\u003e\u003cspan address=\"10.1186/s40359-024-01961-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJASP Team. \u003cem\u003eJASP (Version 0.18.3)\u003c/em\u003e[Computer software]. (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJackson, B. F. Censorship and freedom of expression in the age of Facebook. \u003cem\u003eNew. Mexico Law Rev.\u003c/em\u003e \u003cb\u003e44\u003c/b\u003e (1), 121\u0026ndash;167 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJeshoots \u003cem\u003e[Two people playing Sony PS4 game console]. Unsplash.\u003c/em\u003e (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://unsplash.com/photos/eCktzGjC-iU\u003c/span\u003e\u003cspan address=\"https://unsplash.com/photos/eCktzGjC-iU\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim, Y., Sohn, D. \u0026amp; Choi, S. M. Cultural difference in motivations for using social network sites: A comparative study of American and Korean college students. \u003cem\u003eComput. Hum. Behav.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e (1), 365\u0026ndash;372. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.chb.2010.08.015\u003c/span\u003e\u003cspan address=\"10.1016/j.chb.2010.08.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKolas, J. \u0026amp; Von M\u0026uuml;hlenen, A. Addicted to socialising and still lonely: A comparative, corpus-driven analysis of problematic social networking site use. \u003cem\u003eJ. Behav. Addictions\u003c/em\u003e. \u003cb\u003e13\u003c/b\u003e (1), 163\u0026ndash;176. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1556/2006.2023.00061\u003c/span\u003e\u003cspan address=\"10.1556/2006.2023.00061\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024a).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKolas, J. \u0026amp; Von M\u0026uuml;hlenen, A. Checking in to check out? The effect of boredom on craving, behavioural inhibition and social networking site use. \u003cem\u003eInt. J. Mental Health Addict.\u003c/em\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11469-024-01349-2\u003c/span\u003e\u003cspan address=\"10.1007/s11469-024-01349-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024b).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLamarche, L., Ozimok, B., Gammage, K. L. \u0026amp; Muir, C. Men respond too: The effects of a social-evaluative body image threat on shame and cortisol in university men. \u003cem\u003eAm. J. Men's Health\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e (6), 1791\u0026ndash;1803. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/1557988317723406\u003c/span\u003e\u003cspan address=\"10.1177/1557988317723406\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaroche, M., Habibi, M. R. \u0026amp; Richard, M. O. To be or not to be in social media: How brand loyalty is affected by social media? \u003cem\u003eInt. J. Inf. Manag.\u003c/em\u003e \u003cb\u003e33\u003c/b\u003e (1), 76\u0026ndash;82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijinfomgt.2012.07.003\u003c/span\u003e\u003cspan address=\"10.1016/j.ijinfomgt.2012.07.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee, C. \u003cem\u003e[Cooked food]. Unsplash\u003c/em\u003e. (2016). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://unsplash.com/photos/awj7sRviVXo\u003c/span\u003e\u003cspan address=\"https://unsplash.com/photos/awj7sRviVXo\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi, W., Lin, X., Wu, J., Xue, W. \u0026amp; Zhang, J. Impacts social media have on young generation and older adults. In \u003cem\u003e4th International Conference on Humanities Education and Social Sciences\u003c/em\u003e (pp. 294\u0026ndash;300). Atlantis Press. (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2991/assehr.k.211220.051\u003c/span\u003e\u003cspan address=\"10.2991/assehr.k.211220.051\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLonergan, A. R., Mitchison, D., Bussey, K. \u0026amp; Fardouly, J. Social media and eating and body image concerns among men and boys. In J. M. Nagata, T. A. Brown, S. B. Murray, \u0026amp; J. M. Lavender (Eds.), \u003cem\u003eEating disorders in boys and men\u003c/em\u003e (pp. 307\u0026ndash;316). Springer Nature Switzerland AG. (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-3-030-67127-3_20\u003c/span\u003e\u003cspan address=\"10.1007/978-3-030-67127-3_20\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMasefield, S. \u003cem\u003eFunny Xmas Communication\u003c/em\u003e [Video]. YouTube. (2014)., 4 December \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.youtube.com/watch?v=YQ3qgIMURgI\u003c/span\u003e\u003cspan address=\"https://www.youtube.com/watch?v=YQ3qgIMURgI\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMayer, J. D. \u0026amp; Gaschke, Y. N. The experience and meta-experience of mood. \u003cem\u003eJ. Personal. Soc. Psychol.\u003c/em\u003e \u003cb\u003e55\u003c/b\u003e (1), 102\u0026ndash;111. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0022-3514.55.1.102\u003c/span\u003e\u003cspan address=\"10.1037/0022-3514.55.1.102\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1988).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Byrne, W. I. Educate, empower, advocate: Amplifying marginalized voices in a digital society. \u003cem\u003eContemp. Issues Technol. Teacher Educ.\u003c/em\u003e \u003cb\u003e19\u003c/b\u003e (4), 640\u0026ndash;669 (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.learntechlib.org/primary/p/188279/\u003c/span\u003e\u003cspan address=\"https://www.learntechlib.org/primary/p/188279/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO\u0026rsquo;Reilly, M. et al. Is social media bad for mental health and wellbeing? Exploring the perspectives of adolescents. \u003cem\u003eClin. Child Psychol. Psychiatry\u003c/em\u003e. \u003cb\u003e23\u003c/b\u003e (4), 601\u0026ndash;613. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/1359104518775154\u003c/span\u003e\u003cspan address=\"10.1177/1359104518775154\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOpenAI. ChatGPT (Mar 14 version) [Large language model]. (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://chat.openai.com/chat\u003c/span\u003e\u003cspan address=\"https://chat.openai.com/chat\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOssiannilsson, E. Open educational resources: A catalyst for social justice and equality. In (eds Olivier, J. \u0026amp; Rambow, A.) Open educational resources in higher education (15\u0026ndash;33). Springer, Singapore. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-981-19-8590-4_2\u003c/span\u003e\u003cspan address=\"10.1007/978-981-19-8590-4_2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark, J., Barash, V., Fink, C. \u0026amp; Cha, M. Emoticon style: Interpreting differences in emoticons across cultures. \u003cem\u003eIn Proceedings of the International AAAI Conference on Web and Social Media, 7\u003c/em\u003e(1), 466\u0026ndash;475. (2013). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1609/icwsm.v7i1.14437\u003c/span\u003e\u003cspan address=\"10.1609/icwsm.v7i1.14437\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetrosyan, A. \u003cem\u003eNumber of internet and social media users worldwide as of July 2024\u003c/em\u003e [Chart]. Statista. (2024)., Aug 19 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.statista.com/statistics/617136/digital-population-worldwide/#statisticContainer\u003c/span\u003e\u003cspan address=\"https://www.statista.com/statistics/617136/digital-population-worldwide/#statisticContainer\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrzybylski, A. K., Murayama, K., DeHaan, C. R. \u0026amp; Gladwell, V. Motivational, emotional, and behavioral correlates of fear of missing out. \u003cem\u003eComput. Hum. Behav.\u003c/em\u003e \u003cb\u003e29\u003c/b\u003e (4), 1841\u0026ndash;1848. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.chb.2013.02.014\u003c/span\u003e\u003cspan address=\"10.1016/j.chb.2013.02.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRadovic, A., Gmelin, T., Stein, B. D. \u0026amp; Miller, E. Depressed adolescents' positive and negative use of social media. \u003cem\u003eJ. Adolesc.\u003c/em\u003e \u003cb\u003e55\u003c/b\u003e, 5\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.adolescence.2016.12.002\u003c/span\u003e\u003cspan address=\"10.1016/j.adolescence.2016.12.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRohde, J. et al. Investigating relationships among self-efficacy, mood, and anxiety using digital technologies: Randomized controlled trial. \u003cem\u003eJMIR Formative Res.\u003c/em\u003e \u003cb\u003e7\u003c/b\u003e (1), e45749. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2196/45749\u003c/span\u003e\u003cspan address=\"10.2196/45749\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSamra, A., Warburton, W. A. \u0026amp; Collins, A. M. Social comparisons: A potential mechanism linking problematic social media use with depression. \u003cem\u003eJ. Behav. Addictions\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e (2), 607\u0026ndash;614. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1556/2006.2022.00023\u003c/span\u003e\u003cspan address=\"10.1556/2006.2022.00023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharifian, N. et al. Measurement invariance of social media use in younger and older adults and links to socioemotional health. \u003cem\u003eInnov. Aging\u003c/em\u003e. \u003cb\u003e5\u003c/b\u003e (2), igab009. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/geroni/igab009\u003c/span\u003e\u003cspan address=\"10.1093/geroni/igab009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShu, K., Sliva, A., Wang, S., Tang, J. \u0026amp; Liu, H. Fake news detection on social media: A data mining perspective. \u003cem\u003eACM SIGKDD Explorations Newsl.\u003c/em\u003e \u003cb\u003e19\u003c/b\u003e (1), 22\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1145/3137597.3137600\u003c/span\u003e\u003cspan address=\"10.1145/3137597.3137600\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSkapinakis, P. Spielberger state-trait anxiety inventory. In (ed Maggino, F.) Encyclopedia of quality of life and wellbeing research. Springer, Cham. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-3-031-17299-1_2825\u003c/span\u003e\u003cspan address=\"10.1007/978-3-031-17299-1_2825\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpielberger, C. D., Gonzalez-Reigosa, F., Martinez-Urrutia, A., Natalicio, L. F. \u0026amp; Natalicio, D. S. The state-trait anxiety inventory. \u003cem\u003eInteramerican J. Psychol.\u003c/em\u003e \u003cb\u003e5\u003c/b\u003e, 145\u0026ndash;158 (1971).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpielberger, C. D., Gorsuch, R. L. \u0026amp; Lushene, R. E. \u003cem\u003eSTAI: Manual for the state-trait anxiety inventory\u003c/em\u003e (Consulting Psychologists, 1970).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpiske, M. \u003cem\u003e[Person watering plant]. Unsplash.\u003c/em\u003e (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://unsplash.com/photos/sFydXGrt5OA\u003c/span\u003e\u003cspan address=\"https://unsplash.com/photos/sFydXGrt5OA\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStumpf, A. et al. Relations between the characteristics and psychological comorbidities of chronic pruritus differ between men and women: women are more anxious than men. \u003cem\u003eBr. J. Dermatol.\u003c/em\u003e \u003cb\u003e172\u003c/b\u003e (5), 1323\u0026ndash;1328. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/bjd.13492\u003c/span\u003e\u003cspan address=\"10.1111/bjd.13492\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSykes, R. E. Toward a theory of observer effect in systematic field observation. \u003cem\u003eHum. Organ.\u003c/em\u003e \u003cb\u003e37\u003c/b\u003e (2), 148\u0026ndash;156. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.17730/humo.37.2.g663443211026724\u003c/span\u003e\u003cspan address=\"10.17730/humo.37.2.g663443211026724\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1978).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTai. \u003cem\u003e[Clear margarita glass on selective focus photography]\u003c/em\u003e. Unsplash. (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://unsplash.com/photos/2EBTwzczg2A\u003c/span\u003e\u003cspan address=\"https://unsplash.com/photos/2EBTwzczg2A\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTran, R. Technology and the Arab spring: Catalyst not cause. \u003cem\u003eLiberated Arts: J. Undergrad. Res.\u003c/em\u003e, \u003cb\u003e11\u003c/b\u003e(1). (2024). Article 10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTukhfatullina, A. \u003cem\u003e[Raspberry cake]. Unsplash.\u003c/em\u003e (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://unsplash.com/photos/Mzy-OjtCI70\u003c/span\u003e\u003cspan address=\"https://unsplash.com/photos/Mzy-OjtCI70\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, X., Qiao, Y., Li, W. \u0026amp; Dong, W. How is online disinhibition related to adolescents\u0026rsquo; cyberbullying perpetration? Empathy and gender as moderators. \u003cem\u003eJ. Early Adolescence\u003c/em\u003e. \u003cb\u003e42\u003c/b\u003e (5), 704\u0026ndash;732. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/02724316211064515\u003c/span\u003e\u003cspan address=\"10.1177/02724316211064515\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWarren, A. \u003cem\u003eThe association between social media, toxic masculinity, and depression in young adult males\u003c/em\u003e [Doctoral dissertation, National Louis University]. Digital Commons at NLU. (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://digitalcommons.nl.edu/diss/852\u003c/span\u003e\u003cspan address=\"https://digitalcommons.nl.edu/diss/852\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilliamson, J. A., Oliger, C., Wheeler, A. \u0026amp; O\u0026rsquo;Hara, M. W. More social support is associated with more positive mood but excess support is associated with more negative mood. \u003cem\u003eJ. Social Personal Relationships\u003c/em\u003e. \u003cb\u003e36\u003c/b\u003e (11\u0026ndash;12), 3588\u0026ndash;3610. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0265407519831771\u003c/span\u003e\u003cspan address=\"10.1177/0265407519831771\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eY\u0026ouml;ney, H. Emotional intelligence. \u003cem\u003eMarmara Med. J.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e (1), 47\u0026ndash;52 (2001).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"social media, anxiety, negative comment, mood state, cyberpsychology","lastPublishedDoi":"10.21203/rs.3.rs-5448411/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5448411/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSocial media has become the mainstream communication platform, offering unprecedented convenience, but its anonymity can also encourage negative interactions. This study investigates how negative comments on social media affect adults\u0026rsquo; anxiety and mood. In an experimental study involving 128 adult participants (85 female, 43 male), individuals were asked to share blog posts on a simulated internet forum. Subsequently, they were exposed to either negative, neutral, or positive comments, and their mood and anxiety levels were measured using validated scales. Results showed that negative comments significantly increased anxiety and decreased mood compared to neutral or positive comments, while gender did not show any significant effects. Younger adults reported stronger anxiety responses to negative comments than older adults, suggesting heightened sensitivity among younger users. These findings highlight the psychological impact of negative social media comments on adults and underscore the importance of strategies for managing online negativity. This research expands our understanding of social media's effects on adult mental health.\u003c/p\u003e","manuscriptTitle":"An experimental online study on the impact of negative social media comments on anxiety and mood","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-06 07:14:52","doi":"10.21203/rs.3.rs-5448411/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-29T09:07:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-09T07:01:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"257556012810349174611212034254883945667","date":"2025-04-29T00:40:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-28T23:51:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-25T12:52:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-04-09T16:27:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cf39cd4c-506b-4b9d-be27-1c14024beedf","owner":[],"postedDate":"May 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47818495,"name":"Biological sciences/Psychology"},{"id":47818496,"name":"Health sciences/Health care/Quality of life"}],"tags":[],"updatedAt":"2025-07-28T15:58:50+00:00","versionOfRecord":{"articleIdentity":"rs-5448411","link":"https://doi.org/10.1038/s41598-025-10810-8","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-07-22 15:56:52","publishedOnDateReadable":"July 22nd, 2025"},"versionCreatedAt":"2025-05-06 07:14:52","video":"","vorDoi":"10.1038/s41598-025-10810-8","vorDoiUrl":"https://doi.org/10.1038/s41598-025-10810-8","workflowStages":[]},"version":"v1","identity":"rs-5448411","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5448411","identity":"rs-5448411","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}