Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-25T07:01:52.335Z Has data issue: false hasContentIssue false

The relationship between social media addiction and emotional appetite: a cross-sectional study among young adults in Turkey

Published online by Cambridge University Press:  15 February 2024

Sumeyra Sevim
Affiliation:
Ankara Medipol University, Faculty of Health Sciences, Department of Nutrition and Dietetics, Altindag, Ankara, Turkey
Damla Gumus
Affiliation:
Hacettepe University, Faculty of Health Sciences, Department of Nutrition and Dietetics, Sıhhiye, Ankara, Turkey
Mevlude Kizil*
Affiliation:
Hacettepe University, Faculty of Health Sciences, Department of Nutrition and Dietetics, Sıhhiye, Ankara, Turkey
*
*Corresponding author: Email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Objective:

The present study focused on the relationship between addiction to social media (SM) and emotional appetite in young adults.

Design:

Cross-sectional online survey.

Setting:

The Bergen Social Media Addiction Scale (BSMAS) and Emotional Appetite Questionnaire (EMAQ) were used, and the duration and frequency of SM tools usage were analysed.

Participants:

Five hundred and twenty-four participants (144 men and 380 women) aged between 18 and 25 years.

Results:

The mean of SM usage duration of participants was 3·2 ± 2·2 h per d along with a mean of BSMAS score of 16·1 ± 5·9. Concerning emotional appetite, the mean scores for positive and negative aspects of EMAQ were 4·4 ± 1·9 and 3·1 ± 1·2, respectively. The predominant SM tools were YouTube (92·6 %) and Instagram (90·3 %). Notably, a significant association was observed between SM addiction and the frequency of access to YouTube, Instagram, and Twitter, with addiction levels increasing as access frequency rose (P < 0·01).

Conclusion:

This study demonstrated a possible relationship between SM addiction and emotional appetite among young adults. However, further research with more prominent participants and a lengthier follow-up duration is necessary to elucidate how SM tools affect eating behaviour.

Type
Short Communication
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of The Nutrition Society

The escalating global use of social media (SM), an Internet-based communication tool, is a prevalent trend. Reports indicate that SM users exceeded 3·6 billion in 2020 and are projected to reach 4·41 billion by 2025. SM serves various functions, including communication, social interaction and image sharing(Reference Frith1,Reference Third, Bellerose and Oliveira2) . While SM facilitates vital aspects like social connectivity and information access, it also entails inherent risks such as addiction and cognitive impairment. Research has extensively explored SM addiction, characterised by excessive or problematic usage, from diverse perspectives including mental, biological and social dimensions(Reference Tateno, Teo and Ukai3,Reference Ghaedrahmati, Kazemi and Kheirabadi4) .

Young adults are the primary active users of SM. They experience continuous exposure to diverse content and images(Reference Aparicio-Martinez, Perea-Moreno and Martinez-Jimenez5), which raises concerns about their susceptibility to eating and body perception disorders induced by media influences, making them a potentially vulnerable demographic in this context(Reference Rounsefell, Gibson and McLean6).

Although existing research has highlighted connections between SM and eating disorders, such as restrained eating and eating-related concerns, there is a gap in the literature regarding the exploration of the interplay between SM addiction and emotional appetite. To address this void, the present study was conducted to assess the associations among SM usage, SM addiction and emotional appetite among young individuals.

Materials and methods

Study design and participants

The study was conducted through an online survey targeting individuals aged 19–25 years residing in Turkey. The online questionnaire was designed via Google.form, accessible via smartphones or computers. Exclusion criteria encompassed drug use, psychiatric disorders, undergoing eating behaviour therapy, pregnancy and lactation. Over a span of 2 months, a total of 588 participants were engaged. After addressing issues such as missing data (e.g. weight and height), incomplete responses to scales, and inconsistencies with inclusion criteria, sixty-four participants were excluded. Thus, the study ultimately focused on 524 subjects (144 men and 380 women).

Measures

The questionnaire form consisting of four parts was used to evaluate the relationship between SM use and eating behaviour. The initial section of the questionnaire consisted of demographic characteristics. Subsequently, the second section explored participants’ dietary practices, including meal frequency, meal skipping tendencies, appetite status, dietary preferences and anthropometric measurements. This section also entailed participants’ self-reported body weight and height. The third section delved into participants’ SM usage patterns and their potential tendencies towards addiction. Finally, the fourth section of the questionnaire was dedicated to evaluating participants’ emotional appetite.

Social media usage and social media addiction

The inquiry concerning SM usage encompassed various dimensions, including the extent and frequency of Internet and SM engagement within a given day, preferred SM tools, and the frequency and duration of interactions with distinct SM tools. Bergen Social Media Addiction Scale (BSMAS) which was developed by Andreassen et al.(Reference Andreassen, Pallesen and Griffiths7) was used to measure SM addiction. A high score in this questionnaire indicates high SM addiction, while a low score indicates low addiction. Turkish validation of the scale was conducted by Demirci(Reference Demirci8). Within the present study’s sample, the BSMAS demonstrated high internal consistency, indicated by a Cronbach’s α coefficient of 0·82.

Emotional appetite assessments

Emotional Appetite Questionnaire (EMAQ) was used to evaluate the emotional appetite of the participants. The EMAQ shows the propensity to eating as a response to positive and negative emotions and situations, developed by Nolan et al.(Reference Nolan, Halperin and Geliebter9). Demirel et al.(Reference Demirel, Yavuz and Karadere10) conducted the validity and reliability of the scale in Turkish. The presence of emotional eating is evaluated with fourteen items in negative/positive emotions and eight items in negative/positive situations. The total positive EMAQ score (EMAQ-P) was obtained by averaging positive emotion and situation scores. Likewise, the total negative emotion and situation scores were averaged to obtain total negative EMAQ score (EMAQ-N). Higher scores were representer of increased emotional eating(Reference Nolan, Halperin and Geliebter9). Cronbach’s αs were 0·92 for EMAQ-N and 0·93 for EMAQ-P, indicating high internal consistency in present study.

Statistical analyses

All statistical analyses were performed using SPSS 25. Data were screened for normality according to Kolmogorov–Smirnov test. All dependent variables were normally distributed. The differences in BMI, BSMAS and EMAQ by SM access frequency were analysed by performing ANOVA, and the significance of the difference between groups was determined by Tukey’s multiple comparison test. To examine the relationship between the duration of SM use, BSMAS, BMI and EMAQ, multiple regression was performed after it was checked whether the statistical assumptions for regression were met. Statistically, the lowest level of significance was accepted as P < 0·05.

Results

Participant characteristics and Internet, social media usage duration, Bergen Social Media Addiction Scale and Emotional Appetite Questionnaire score

Characteristics of the subjects are presented in Table 1. The mean BMI was 22·2 ± 3·8 kg/m2, and most participants (67·4 %) had normal BMI (18·5–24·9 kg/m2). While the mean Internet usage duration was 6·6 ± 3·4 h, the mean SM usage duration was 3·2 ± 2·2 h in a day. Moreover, the mean of BSMAS and EMAQ of participants are presented in Table 1.

Table 1 Sample descriptives

SM, social media; BSMAS, Bergen Social Media Addiction Scale; EMAQ, Emotional Appetite Questionnaire; EMAQ-P, positive EMAQ score; EMAQ-N, negative EMAQ score.

The differences between BMI, social media addiction and emotional appetite according to the frequency of the most accessed social media tools

YouTube (92·6 %), Instagram (90·3 %), Google+ (56·7 %) and Twitter (54·8 %) emerged as the predominant SM tools, each accessed at least once a week, as depicted in online supplementary material, Supplementary Figure 1. Table 2 presents variations in BMI, BSMAS and EMAQ scores based on the frequency of SM access across four commonly used SM platforms. Notably, individuals who primarily used YouTube had the highest averages for BMI, BSMAS and EMAQ-P scores. BSMAS scores increased with higher frequency of Instagram access, but no significant variations were observed in EMAQ-P or EMAQ-N scores. Participants accessing Twitter less than once a week or not at all had significantly lower mean BSMAS scores compared with others. However, no significant differences were found in other scales based on the frequency of accessing Twitter or Google+.

Table 2 Differences in BMI, BSMAS and EMAQ by SM accessed frequency

BSMAS, Bergen Social Media Addiction Scale; EMAQ, Emotional Appetite Questionnaire; SM, social media; EMAQ-P, positive EMAQ score; EMAQ-N, negative EMAQ score.

P values were calculated by ANOVA. Bold indicates statistically significant difference (P < 0.05).

* Different lower case (*-†) in the same row means the statistically significant difference among the values, according to the post hoc Tukey’s test (P < 0·05), the same lower case (*-†) means that there was not statistically difference (P > 0·05).

Different lower case (*-†) in the same row means the statistically significant difference among the values, according to the post hoc Tukey’s test (P < 0·05), the same lower case (*-†) means that there was not statistically difference (P > 0·05).

A multiple linear regression analysis was conducted to assess whether certain independent variables could predict the EMAQ scores (Table 3). For EMAQ-P, the overall model was statistically significant, indicating that the predictor variables explained about 1 % of the variance in EMAQ-P scores. Specifically, the BSMAS variable significantly contributed to the model, while SM usage duration and BMI did not. Similarly, for EMAQ-N, the regression equation was significant, with the predictor variables explaining about 5 % of the variance. In this case, both BSMAS and BMI were found to contribute to the model, whereas SM usage duration did not.

Table 3 Multiple regression analysis results for predicting EMAQ-P and EMAQ-N

EMAQ, Emotional Appetite Questionnaire; EMAQ-P, positive EMAQ score; EMAQ-N, negative EMAQ score; B, unstandardised regression coefficient; se, unstandardised standard error; β, standardised regression coefficient; t, t-test value; SM, social media; BSMAS, Bergen Social Media Addiction Scale. Bold indicates statistically significant difference (P < 0.05).

Discussion

The global daily engagement with SM platforms is continually expanding. This aligns with our findings, which parallel those of Statista(11) indicating that Internet users devoted an average of 2 hours and 24 min per d to SM in 2020. The escalating online activity is often associated with problematic SM usage, potentially indicative of incipient addiction. Such an inclination can contribute to challenges in emotion regulation(Reference Bourdier, Morvan and Kotbagi12,Reference Leunga, Pakpour and Strong13) .

Various studies have posited a potential link between SM addiction and disruptions in emotional regulation(Reference Hormes, Kearns and Timko14,Reference Andreassen and Pallesen15) . In the present study, emotional appetite was assessed using the EMAQ, revealing a mean EMAQ-P score of 4·4 ± 1·9 and an EMAQ-N score of 3·1 ± 1·2. These findings corroborate earlier reports(Reference Bourdier, Morvan and Kotbagi12,Reference Barnhart, Braden and Price16) .

The relationship between SM addiction and emotional appetite remains relatively underexplored within the existing literature. Solely, one study reported the association between addictive phone use and dysregulated eating and food addiction(Reference Domoff, Sutherland and Yokum17). Positive relations between SM addiction and emotional dysregulation were observed previously(Reference Quaglieri, Biondi and Roma18,Reference Kardefelt-Winther19) . Given the common phenomenon of altered eating behaviours serving as coping mechanisms among young adults, it is plausible that both SM addiction and heightened emotional appetite could be precipitated by emotional dysregulation and evolving coping strategies within this demographic.

Statista(20) reported that Facebook was the most popular social network worldwide in 2020, while YouTube was the second. Interestingly, YouTube and Instagram were found as the most frequently used SM tools among the participants of the current study. However, Nelson and Fleming(Reference Nelson and Fleming21) reported that the most frequently used SM tools of young participants in the USA were Facebook, Snapchat, Instagram, and YouTube, while according to Jairoun and Shahwan’s study(Reference Jairoun and Shahwan22) Instagram and Snapchat were the most popular in the UAE.

Researchers point out that the associations between SM and worse well-being were associated with the exposure to visual and image-oriented SM rather than the general use of SM tools(Reference Cohen, Newton-John and Slater23,Reference Saiphoo and Vahedi24) . Likewise, within this study, participants who primarily accessed YouTube demonstrated elevated scores in BMI, BSMAS and EMAQ-P. A plausible rationale for these findings could be attributed to the potential impact of YouTube video content on eating behaviours. For example, recent research highlighted a positive link between watching mukbang videos on SM and disordered eating as well as Internet addiction among young adults(Reference Kircaburun, Yurdagül and Kuss25). In the current study, a positive correlation was observed between SM addiction and the frequency of participants’ Instagram use, while no significant variance was found in emotional appetite scores based on Instagram access. Notably, these findings diverge from certain research that has suggested a connection between Instagram and eating disorders(Reference Lee-Won, Joo and Baek26,Reference Saunders and Eaton27) , although a recent systematic review noted an inconclusive relationship(Reference Faelens, Hoorelbeke and Cambier28).

The study found no significant differences in BMI, SM addiction or emotional appetite based on the frequency of accessing Twitter or Google+. Notably, participants accessing Twitter less than once a week or not at all had significantly lower BSMAS scores. While there is no direct literature linking Twitter to eating behaviour or disorders, some studies suggest a correlation between posting food-related content on Twitter and problematic eating behaviours(Reference Vidal, Ares and Machín29,Reference Arseniev-Koehler, Lee and McCormick30) .

BSMAS was found as a predictor for EMAQ-P, whereas SM usage and BMI were found not to be significant predictors. Considering EMAQ-N, it was found that BSMAS and BMI were significant predictors while SM usage duration was not a predictor for EMAQ-N. This study provides preliminary evidence demonstrating the emotional appetite risks associated with SM addiction. Problematic SM usage and being addicted to SM might have complicated effects on emotional appetite.

Strengths and limitations

To our knowledge, this research provides the first report on the association between SM addiction and emotional appetite. This study has several strengths. To start, the BSMAS has not been previously used in studies investigating SM use and emotional appetite. Additionally, the incorporation of validated and reliable scales to gauge emotional appetite enhances the study’s methodological robustness. However, the online modality employed for data collection presents a limitation, as it contrasts with traditional face-to-face interactions. Furthermore, a gender imbalance in the participant pool affects the study’s generalisability. Additionally, the absence of dietary intake and food choice data precludes the evaluation of participants’ energy and nutrient intake as well as their dietary preferences.

Conclusion

The results of the present study provide initial evidence for the interaction between negative and positive emotional eating and SM engagement and addiction. Notably, having SM addiction and extended SM usage duration had the effect on both negative and positive emotional appetite. Considering the widespread use of SM and its potential impact, further research is required for comprehensive investigations to examine the influences of SM addiction on eating behaviours.

Acknowledgements

This work did not receive any financial support. The authors thank the participants for their valuable time and responses.

Financial support

This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.

Conflict of interest

There are no conflicts of interest.

Authorship

S.S.: Conceptualisation, Investigation, Formal analysis, and Writing – original draft; D.G.: Conceptualisation, Investigation, Formal analysis, and Writing – original draft; M.K.: Conceptualisation, Methodology, and Writing – review and editing.

Ethics of human subject participation

This study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures involving research study participants were approved by the Hacettepe University Ethics Committee (document number: E-35853172-000-00001515083). Informed consent was obtained from all participants.

Supplementary material

For supplementary material accompanying this paper visit https://doi.org/10.1017/S1368980024000466.

Footnotes

Sumeyra Sevim and Damla Gumus contributed equally to this work.

References

Frith, E (2017) Social media and children’s mental health: A review of the evidence; June 2017. Available at https://epi.org.uk/wp-content/uploads/2018/01/Social-Media_Mental-Health_EPI-Report.pdf (accessed October 2021).Google Scholar
Third, A, Bellerose, D, Oliveira, JD et al. (2017) Young, Online: Children’s Perspectives on Life in the Digital Age (The State of the World’s Children 2017 Companion Report). Sydney: Western Sydney University. Available at https://www.westernsydney.edu.au/__data/assets/pdf_file/0006/1334805/Young_and_Online_Report.pdf (accessed October 2021).Google Scholar
Tateno, M, Teo, AR, Ukai, W et al. (2019) Internet addiction, smartphone addiction, and Hikikomori trait in Japanese young adult: social isolation and social network. Front Psychiatry 10, 455.CrossRefGoogle ScholarPubMed
Ghaedrahmati, M, Kazemi, A, Kheirabadi, G et al. (2018) Examining the relationship between mothers’ prenatal mental health and demographic factors with postpartum depression. J Educ Health Promot 7, 146.Google ScholarPubMed
Aparicio-Martinez, P, Perea-Moreno, A-J & Martinez-Jimenez, MP (2019) Social media, thin-ideal, body dissatisfaction and disordered eating attitudes: an exploratory analysis. Int J Environ Res Public Health 16, 4177.CrossRefGoogle ScholarPubMed
Rounsefell, K, Gibson, S, McLean, S et al. (2020) Social media, body image and food choices in healthy young adults: a mixed methods systematic review. Nutr Diet 77, 1940.CrossRefGoogle ScholarPubMed
Andreassen, CS, Pallesen, S & Griffiths, MD (2017) The relationship between addictive use of social media, narcissism, and self-esteem: findings from a large national survey. Addict Behav 64, 287293.CrossRefGoogle ScholarPubMed
Demirci, İ (2019) Bergen sosyal medya bağimliliği ölçeğinin Türkçeye uyarlanması, depresyon ve anksiyete belirtileriyle ilişkisinin değerlendirilmesi. Anatolian J Psychiatry/Anadolu Psikiyatri Dergisi 20, 1522.Google Scholar
Nolan, LJ, Halperin, LB & Geliebter, A (2010) Emotional appetite questionnaire. Construct validity and relationship with BMI. Appetite 54, 314319.CrossRefGoogle ScholarPubMed
Demirel, B, Yavuz, KF, Karadere, ME et al. (2014) Duygusal İştah Anketi’nin Türkçe geçerlik ve güvenilirliği, beden kitle indeksi ve duygusal şemalarla İlişkisi. Bilişsel Davranışcı Psikoterapi ve Arastırmalar Dergisi 3, 171181.Google Scholar
Statista (2021) Number of social network users worldwide from 2017 to 2025 (in billions). Available at https://www.statista.com/statistics/278414/number-of-worldwide-social-network-users/ (accessed October 2021).Google Scholar
Bourdier, L, Morvan, Y, Kotbagi, G et al. (2018) Examination of emotion-induced changes in eating: a latent profile analysis of the emotional appetite questionnaire. Appetite 123, 7281.CrossRefGoogle ScholarPubMed
Leunga, H, Pakpour, AH, Strong, C et al. (2020) Measurement invariance across young adults from Hong Kong and Taiwan among three internet-related addiction scales: Bergen social media addiction scale (BSMAS), smartphone application-based addiction scale (SABAS), and internet gaming disorder scale-short form (IGDS-SF9) (study part A). Addict Behav 101, 105969.CrossRefGoogle Scholar
Hormes, JM, Kearns, B & Timko, CA (2014) Craving facebook? Behavioral addiction to online social networking and its association with emotion regulation deficits. Addict 109, 20792088.CrossRefGoogle ScholarPubMed
Andreassen, CS & Pallesen, S (2014) Social network site addiction-an overview. Curr Pharm 20, 40534061.CrossRefGoogle Scholar
Barnhart, WR, Braden, AL & Price, E (2021) Emotion regulation difficulties interact with negative, not positive, emotional eating to strengthen relationships with disordered eating: an exploratory study. Appetite 158, 105038.CrossRefGoogle Scholar
Domoff, SE, Sutherland, EQ & Yokum, S (2020) Adolescents’ addictive phone use: associations with eating behaviors and adiposity. Int J Environ Res Public Health 17, 2861.Google Scholar
Quaglieri, A, Biondi, S, Roma, P et al. (2021) From emotional (Dys) regulation to internet addiction: a mediation model of problematic social media use among Italian young adults. J Clin Med 11, 188.Google Scholar
Kardefelt-Winther, DA (2014) Conceptual and methodological critique of internet addiction research: towards a model of compensatory internet use. Comput Hum Behav 31, 351–4.CrossRefGoogle Scholar
Statista (2021) Global active usage penetration of leading social networks as of February 2020. Available at https://www.statista.com/statistics/274773/global-penetration-of-selected-social-media-sites/ (accessed November 2021).Google Scholar
Nelson, AM & Fleming, R (2019) Gender differences in diet and social media: an explorative study. Appetite 142, 104383.CrossRefGoogle ScholarPubMed
Jairoun, A & Shahwan, M (2020) Assessment of university students’ suboptimal health and social media use: implications for health regulatory authorities. J Community Health 46, 653659.CrossRefGoogle ScholarPubMed
Cohen, R, Newton-John, T & Slater, A (2017) The relationship between facebook and instagram appearance-focused activities and body image concerns in young women. Body Image 23, 183187.Google Scholar
Saiphoo, AN & Vahedi, ZA (2019) A meta-analytic review of the relationship between social media use and body image disturbance. Comput Hum Behav 101, 259275.Google Scholar
Kircaburun, K, Yurdagül, C, Kuss, D et al. (2021) Problematic mukbang watching and its relationship to disordered eating and internet addiction: a pilot study among emerging adult mukbang watchers. Int J Ment Health Addict 19, 21602169.Google Scholar
Lee-Won, RJ, Joo, YK, Baek, YM et al. (2020) “Obsessed with retouching your selfies? Check your mindset!”: female instagram users with a fixed mindset are at greater risk of disordered eating. Pers Individ Differ 167, 110223.CrossRefGoogle Scholar
Saunders, JF & Eaton, AA (2018) Snaps, selfies, and shares: how three popular social media platforms contribute to the sociocultural model of disordered eating among young women. Cyberpsychol Behav Soc Netw 21, 343–54.CrossRefGoogle Scholar
Faelens, L, Hoorelbeke, K, Cambier, R et al. (2021) The relationship between Instagram use and indicators of mental health: a systematic review. Comput Hum Behav 4, 100121.Google Scholar
Vidal, L, Ares, G, Machín, L et al. (2015) Using twitter data for food-related consumer research: a case study on “what people say when tweeting about different eating situations”. Food Qual Prefer 45, 5869.CrossRefGoogle Scholar
Arseniev-Koehler, A, Lee, H, McCormick, T et al. (2016) #Proana: pro-eating disorder socialization on twitter. J Adolesc Health 58, 659–64.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Sample descriptives

Figure 1

Table 2 Differences in BMI, BSMAS and EMAQ by SM accessed frequency

Figure 2

Table 3 Multiple regression analysis results for predicting EMAQ-P and EMAQ-N

Supplementary material: File

Sevim et al. supplementary material

Sevim et al. supplementary material
Download Sevim et al. supplementary material(File)
File 16.9 KB