Skip to main content

Selfie phenomenon among a sample of Egyptian university students: rate and psychiatric correlates

Abstract

Background

The selfie phenomenon is an emanating one, specifically affecting adolescents and young adults. It emerges as a reflection of a wide spectrum of neuropsychiatric disorders. Based on this, the current study aimed to assess the rate of the selfie phenomenon among Egyptian university students and its sociodemographic and psychiatric correlates. During the study procedure, we enrolled 200 undergraduate Egyptian university students from two different faculties and were assessed using the Selfie Behavioral Scale, Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Structured Clinical Interview for DSM-IV-TR Axis II Disorders, and Global Assessment of Functioning Scale.

Results

49.5% of the students being assessed had borderline selfitis with a higher rate among females. We found a highly significant association between the selfie phenomenon and depression, anxiety, obsessive-compulsive disorder, eating disorders, and other psychiatric disorders and personality disorders, and we also found that selfies had a significant negative association with the level of functioning among students.

Conclusions

Results concur with previous existing literature regarding the magnitude of the selfie phenomenon and its relationship with different psychiatric disorders and personality disorders.

Background

Behavioral addictions are addictions to activities or processes such as gambling, eating, tanning, sexuality, and shopping. These types of addiction may be more common in more youthful age group [1].

The primary paper on technological forms of addiction was released in 1995, and there has been a marked increment in research into Internet addictive behavior, online video game addiction, mobile phone addiction, social media addiction, and so on [2]. New technologically related mental well-being disorders, such as nomophobia (no mobile phone phobia) [3], technoference (constant intrusions of technology into everyday life) [4], and cyberchondria (feeling ill with the same symptoms after looking for the symptoms of illnesses) [5], were introduced.

Photo sharing on social network sites and advancements in mobile technologies become ubiquitous which aids dramatically in the development of a novel phenomenon in the form of sharing selfies on social network sites. In 2013 selfie was given the title of *Word of the Year* due to its sudden spreading among social media users and was given a definition by Oxford Dictionaries [6] in 2013 of a photograph that one has taken of oneself, typically with a smartphone or webcam and shared through social network sites. Since the onset of Instagram’s first selfie hashtag, #selfie, emerged in the year 2011, Jang et al. [7] mentioned that selfies have become the most popular photos posted on Instagram.

A survey that was performed in 2019 on The *Mobile Technology and Home Broadband* by the Pew Research Center detailed that 96% in the age range between 18 and 29 years in the USA had a smartphone. Some researchers estimated that 98% of the candidates (aged 18 to 24) took selfies, and 69% tended to share selfies 3 to 20 times day by day as stated by Katz and Crocker [8] in 2015, and in 2016, Dutta et al. [9] reported that the prevalence of *addiction to selfie-taking* was 13% among adolescents in Mumbai.

In the beginning of 2021, there were 4.2 billion more active social media users [10], in agreement with the work done. In 2018, Mascheroni and Ólafsson [11] mentioned that high proportions of adolescents aged from 13 to 14 years (79%) and 15 to 17 years (84%) had active social media profiles reflecting that social media is necessary for adolescents’ social interactions and leisure activities that were mentioned and elaborated earlier by Bryant & Bryant [12] in 2005 and also by Musetti et al. [13] in 2020; the highly visual nature of the interactions conferred by online platforms is the key feature why adolescents favored these platforms.

In several studies, it has been found the presence of gender-related differences in selfie practices which shows a higher involvement in selfie-taking, selfie-posting, and selfie-editing by girls in comparison with boys. In 2019, it was clarified by Masha et al. [14] that girls are frequent users of social networking sites and they also post more pictures of themselves as compared to males.

According to the findings of Feltman and Szymanski [15] in 2018, social network sites appear to promote mounting amounts of digital visual content, transforming contemporary everyday life to a “more photographic” life, and this was also mentioned earlier by d’Aloia and Parisi [16] in 2016 and was replicated by Fox and Vendemia [17] in the same year in which editing, filtering, posting, sharing, tagging, and commenting have become natural daily behaviors. In this regard, starting with Katz and Crocker [8] in 2015 passing through Sung et al. [18] and Fox and Vendemia [17] in 2016 followed by Diefenbach and Christoforakos [19] in 2017 and then Balakrishnan and Griffiths [20] in 2018 and ended with McLean et al. [21] in 2019, all agreed that two of the most popular activities carried out on SNSs are selfie-taking and selfie-sharing, and their use might be defined as a “way of being” that is what Griffiths and Kuss found to be the best explanation in 2017 [22].

Upon looking to understand how the phenomenon of behavioral addiction has overlapping factors through the biopsychosocial model, here are the following: (1) biological (reward/executive function model relies on a theory that alterations in the mesolimbic system and medial frontal cortex perpetuate the initiation of the addictive cycle, by looking to the elaboration of addiction results from vulnerabilities and malfunctions in the decision-making process and cellular memory); (2) psychological (emotional, behavioral, and cognitive factors), this was better explained in 2012 by Essig [23] who asserts that behavioral addict is both trying to avoid something (e.g., negative effect) and is self-deluded into the belief that his or her addictive behavior (for instance; Internet use, online gaming) will fulfill all his\her interpersonal needs. Essig [23] also references the feelings of shame that often inflicts so many individuals struggling with behavioral addictions; upon reaching the behavioral approach of explaining behavioral addiction, this can be understood in terms of impulsivity and compulsivity construct which is a hallmark of several psychiatric conditions and is observed mostly in obsessive-compulsive disorder (OCD). In 2006, Grant et al. [24] discussed other conditions with compulsive features including obsessive-compulsive and related disorders, eating disorders, substance dependence, and together with several impulse control disorders and behavioral addictions, such as compulsive Internet use and the urge for taking a perfect selfie as one of the behavioral addiction-related phenomenon; and (3) sociocultural (by the influences of family, friends, and broader culture). Going back to 2005, Donovan and Marlatt [25] hand in hand with Griffiths highlighted that this model has been widely approved in the chemical addiction field, as well as the developing field of behavioral addictions.

In 2014, it was mentioned that the selfie phenomenon is classed, by the American Psychiatric Association (APA), as a novel mental disorder and characterized as (the obsessive-compulsive need to take self-photos and post them on social network sites as a means to make up for the lack of self-esteem and to fill an intimacy gap) [26], and it was also classified into three levels according to the frequency of taking self-photos and posting on social network sites into borderline selfitis (taking photos of one’s self at least 3 times a day but not posting them on social media), acute selfitis (taking photos of one’s self at least 3 times a day and posting each of the photos on social media), and chronic selfitis (an uncontrollable urge to take photos of one’s self around the clock and sharing the photos on social media more than 6 times a day).

Selfie addiction has been connected to various psychiatric illnesses, for example, in 2016 Kaur and Vig [27] found that selfie addiction was associated with low self-esteem, loneliness, and depression. In the same year, Sunitha et al. [28] concluded similar findings depending on their review of selfie-taking. Moreover, in 2017, a study by Kela et al. [29] examined the more medical effects of excessive selfie-taking. A survey of 250 Indian students aged 18–25 years (56% females) uncovered that 30% reported lower back ache, 15% complained of stress, 20%, complained of cervical spondylitis, 25% complained of headache, and 10% complained of “selfie elbow” (a tendonitis condition).

The work done by Baiocco et al. [30] in 2017 on the frequency and the degree of addiction to selfies found that it may be linked to some personality traits. In 2015, a study done by Fox et al. [31] identified a relationship between narcissistic and psychopathic personalities and the tendency for sharing a large number of selfies online. In 2016, Choi et al. [32] studied the association between the five main personality traits and taking selfies in the upholding of social life on and off. He also showed that agreeableness and openness traits are correlated to only looking at others’ selfies and that agreeableness and extraversion traits are correlated to interacting with others’ selfies on social media. Two years after this work, another research done by Sorokowski et al. [33] in 2018 concluded a significant relationship between sharing selfies and narcissism among men.

Due to the absence of data about this topic in Egypt up to this current date, no study has focused on evaluating the rate of the selfie phenomenon and its impact on functionality, and the relationship between the selfie phenomenon and different psychiatric and personality disorders was not explored; therefore, this research was conducted aiming to find the rates and correlates of selfie phenomenon on different personality related and psychiatric variables in a sample of Egyptian university students.

Methods

Participants

Undergraduate students with age between 18 and 25 years of both genders at Ain Shams University (ASU), Cairo, Egypt, were recruited from two different colleges: one practical faculty (the faculty of medicine was selected) and one theoretical college (the faculty of literary arts) were chosen to detect the impact of the field of study on the selfie phenomenon.

We selected a convenience sample, the sample size was calculated using the EpiInfo® version 7.0 (EPI info 7) program, setting the type-1 error (α) at 0.05, and the power (1-ß) at 0.80 and assuming a 15% prevalence of selfie phenomenon in the university students [34]. With a margin of error 5% and at 95% confidence level, a sample size of 200 students will be needed according to the Community Department in Ain Shams University, 100 students from medical school as representatives of practical colleges, and 100 students from the faculty of arts as a representative of theoretical colleges.

All students in the campus of the study dates were asked to enroll and were invited to complete a traditional paper-and-pencil survey, including their sociodemographic data and questionnaires regarding their selfie behavior and a structured clinical interview of a group of psychiatric and personality disorders was performed. The collection of data took place between July 2020 and March 2021.

Data were collected in an anonymous manner (i.e., no names, identification numbers, or any other personal identifiers were requested except for the phone number) to ensure that the students feel safe to share their information freely, but they were taking a code number. All participants were asked to sign an informed consent explaining the purpose of the study, stating their approval to participate in the study, and ensuring the confidentiality of their information. Those who scored highly upon screening for selfie behavior were contacted via a phone call, and a second interview was set forth after finishing their lectures in the outpatient clinic at ASUIP institute to complete SCID-I and SCI-DII assessment.

The study was approved by the team of Ain-Shams University research and ethical committee and the scientific committee of the neuropsychiatric department. At the same time, all data were stored on a password-protected computer in a locked office of the research team and access was strictly limited to the study investigator.

Procedures

All students in the selected faculties who gave approved consent to participate were assessed by the research team according to the following steps:

Demographics

Sociodemographic data was done through a sheet designed by the research team including age, sex, faculty, and academic year.

The Selfie Behavioral Scale (SBS) (Arabic version)

In 2018, Balakrishnan and Griffiths [20] developed a validated tool for the assessment of selfie behavior. They divided the scale into 6 items: the first one being environmental enhancement followed by social competition, attention-seeking, mood modification, self-confidence, and the last one was social conformity. The first 2 zones of environmental enhancement and social competition each of which consists of 4 items, and the last 4 zones of attention-seeking, mood modification, self-confidence, and subjective conformity each consists of 3 items. The total scale consists of twenty items. Response to each item by participants was scored on a five point Likert scale (1–strongly disagree; 2–disagree; 3–neither agree nor disagree; 4–agree; and 5–strongly agree). The total scores ranged from 20 to 100. The behavior was categorized into 4 categories normal, borderline, acute, and chronic selfitis with scores ranging from 20–40, 40–60, 60–80, and 80–100, respectively. An Arabic version of the scale was used in the current study as it was translated and validated by our study,

The translation was conducted in two stages. In the first stage, the scale was translated into Arabic. In the second stage, it was tested among university studies to assess the reliability and internal consistency of the Arabic version.

The initial translation into Arabic was performed independently by two bilingual native speakers from Egypt, both are official translation centers. They were assisted by the researcher if they had any questions about the scale’s content. The two translators combined the translations into a consensus version based on the original scale.

The common translated/adapted version was then back-translated into English by two bilingual different official translators.

The scale was applied in a pilot study of 30 students in Arabic and then applied to the same group after 1 week, and it shows similar results. None of the students reported difficulty in understanding or interpreting the questions. The Arabic version of the scale shows excellent reliability. The scale also showed good internal consistency considering all 6 items (Cronbach’s alpha = 0.94). Whenever one item was excluded, alpha values did not reveal changes in scale homogeneity. No other instrument was used for construct validity analysis due to the absence of Arabic questionnaires assessing the selfie phenomenon.

The Structured Clinical Interview for DSM-IV-TR Axis I Disorders (SCID-I)

In 1997, First et al. [35] designed a diagnostic exam used to determine DSM-IV-TR Axis I Disorder after 6 years of his work. Missery et al. [36] introduced the Arabic version of SCID-I which is a diagnostic exam used to define DSM-IV-TR Axis I Disorder. It is composed of separate modules, which correlate to categories of diagnoses. Most sections initiate with a leading question that allows the interviewer to *skip* the subsequent questions if not met. All diagnosed symptoms are coded as present, subthreshold, or absent. The interview is designed to be performed by a clinician or trained mental health professional. It is divided into 7 diagnostic modules: psychotic, mood, anxiety, somatoform, substance abuse, eating, and adjustment disorders.

In this research, we used the Arabic version that was translated and used in previous Egyptian studies [36].

The Structured Clinical Interview for DSM-IV-TR Axis II Disorders (SCID-II)

In 2003, Hatata et al. [37] translated this instrument into Arabic, but it was first designed by First et al. [35] in 1997. SCID-II is a semi-structured interview that was developed to categorically and/or dimensionally determine the DSM-IV personality disorders. It could be used in both clinical as well as research settings. Items are organized by personality disorder. A 119-item yes/or no screening questionnaire is available to reduce interview time by identifying personality disorders that are unlikely to be present. Each criterion is scored as (1) absent or false, (2) sub-threshold, (3) threshold or true, or (?) inadequate information. Specific guidelines for a score of three (threshold) are provided. The average administration time is just less than 1 h for the SCID-II interview. In the current research, we used the Arabic version that was translated and used in a previous Egyptian study by Hatata et al. [37].

Global Assessment of Functioning (GAF)

A numeric scale (1–100) was first designed and introduced by Hall et al. to be used by mental health clinicians and physicians to grade the social, occupational, and psychological functioning of adults in a subjective manner and assess if the patient’s psychiatric symptoms affect his life. The score is given as a range and is presented in DSM-IV-TR.

Statistical analysis

Descriptive statistics for the total sample were performed. Quantitative and qualitative measurements were summarized as mean ± standard deviation and n (%), respectively. We performed comparisons of continuous and categorical variables by using chi-square and T test, and Spearman correlation coefficients were used to evaluate the association among the different variables. The statistical analyses were performed using the Statistical Package for Social Sciences (SPSS) version 22 for Windows. A p value less than 0.05 was considered statistically significant

Results

The study included a total number of 200 undergraduate students, and those who refused to complete the questionnaire or refused to come to the second interview were excluded and replaced by others to complete the predetermined sample number, so statistically, no dropout as we reached the whole sample size number.

In the current study, 41% were males and 59% were females, and the distribution of different universities and academic years is shown in Table 1.

Table 1 Descriptive data of the sample

Of the students in the literature group, 23% (n=23) were positive for mood disorder and 17% of them were diagnosed with major depressive disorder (MDD) that was higher in comparison with the students in the medical group, 17% (n=17) only were positive out of which 11% (n=11) were diagnosed with major depressive disorder (MDD). However, there was no significant difference found between both groups with a p value of 0.289.

Anxiety disorders were positive in 44% (n=44) of the literature group, out of which 25% (n=25) were diagnosed with panic disorder, 15% (n=15) with a generalized anxiety disorder (GAD), and 14% (n=14) with social phobia that was also higher than that of the medical group as the results showed that 31% (n=31) of the medical students were found to be positive out of which 18% (n=18) were diagnosed with panic disorder, 16% (n=16) with a generalized anxiety disorder (GAD), and 11% (n=11) with social phobia. Yet, there was no significant difference found between both groups with a p value of 0.058

None of the students was diagnosed with schizophrenia nor substance use disorder or hypochondriasis in both groups.

A significant difference was found between both groups, where 12% (n=12) of the literature group more diagnosed as having OCD, 8% (n=8) with posttraumatic stress disorder (PTSD), 12% (n=12) were diagnosed with eating disorder, and 9%(n=9) were diagnosed with body dysmorphic disorders with a p value of 0.016, 0.052, 0.006, and 0.030, respectively, as shown in Table 2.

Table 2 Descriptive data for all psychiatric disorders using SCID-I

Regarding personality disorders, the results showed a significant difference between both groups as the literature group tends to belong to be diagnosed with cluster B personality as 47% (n=47) of the literature group were diagnosed with cluster B personality disorder, 27% (n=27) diagnosed with narcissistic, 14% (n=14) with histrionic personality disorder, 6% (n=6) diagnosed with borderline personality disorder with a p value of 0.007, <0.001, and 0.05, respectively. Also, 11% of the literature group were diagnosed as obsessive-compulsive personality which was significantly higher than the medical group of 3% (n=3) with a p value of 0.027 as shown in Table 3.

Table 3 Descriptive data for all personality disorders using SCID-II

The prevalence of SELFIE among the college of literature group using SBS showed a significantly higher percentage where 1% had normal selfie behavior (score ranging from 20 to 40), 42% were borderline (score ranging from 41 to 60), 41% had acute (score ranging from 61 to 80), and 16% have chronic (score ranging from 81 to 100) on the other hand medical college group showed that 14% had normal selfie behavior, 57% had borderline, 26% had acute, and 3% had chronic selfie behavior, pointing to the fact that the prevalence of selfie phenomenon was higher in the literature group as illustrated in Table 4. The current study results also showed that there was a significant relation between age and the selfie phenomenon.

Table 4 Prevalence of the selfie phenomenon using the Selfie Behavioral Scale (SBS) between both groups

There was a highly significant association between having a chronic and acute selfie behavior and having positive results on SCID-I & II. Our results showed that the higher the selfie behavioral score, the more likely diagnosis of a mood disorder, anxiety disorder, eating disorder, obsessive-compulsive disorder, and body dysmorphic disorder as detailed in Table 5.

Table 5 Relationship between the prevalence of different psychiatric disorders and the prevalence of the selfie phenomenon

Also, there was a highly statistically significant association between chronic selfie behavior and cluster B personality disorder shown in Table 6.

Table 6 relationship between personality disorders and levels of SELFIE behavior

In the current study, we reported a statistically significant negative correlation between individual subscales of the Selfie Behavioral Scale and its total score on the one hand and the GAF score scale, i.e., a higher score on the Selfie Behavioral Scale was associated with less functioning, detailed in Table 7.

Table 7 correlation between items of Selfie Behavioral Scale (SBS), total score, Age and general assessment of functioning (GAF)

Discussion

This study is considered to be one of the first studies to investigate the search for the problem of the selfie phenomenon in Egypt. The past years have witnessed a staggering increase in empirical studies into the effects of social media use (SMU) on adolescents’ mental health worldwide [38,39,40]. One specific behavior of interest is the “selfie,” an act of taking and posting digital photos of oneself online [41]. Due to the significant rise in the use of social networking, behaviors related to social media, particularly selfie behavior, were found to be one of the most popular online engagements, particularly among adolescent and emerging adult social media users [41, 42].

Studies reported that SELFIES have become an addiction among college students [43]. The most dynamic development in this phenomenon was its extreme and recent increase in the usage of social media [33, 44]. Both age and gender are likely factors linked with taking selfies as well as the experience and exposure to social media. Consistent with our results, a clear gender disparity is observed with a larger percentage of younger girls clicking selfies when compared to boys [45,46,47,48].

In addition to the previous sociodemographic findings in the current study sample, it was found that there was a significant prevalence of the obsessive-compulsive disorder, post-traumatic stress disorder, eating disorders, and body dysmorphic disorder regarding SCID-I findings and it was also found that there was a significant prevalence of cluster B personality disorder (histrionic, borderline, and narcissistic) and obsessive-compulsive personality disorder regarding SCID-II findings. These go in line with the association found between higher Selfie Behavioral Scale scores and the above disorders being higher among adolescents who are the target for social media use.

The study results showed that 49.5% of the sample had borderline selfitis and 33% acute selfitis which is consistent with the results showing that selfies are very popular among college-attending young adults [8] and adolescents [42, 49]. Evidence was presented from the fact that 96% of young adults had taken a selfie in the past, and 25% had taken a selfie on the previous day [8].

According to a study done in the USA, 98% of participants (aged 18 to 24) took selfies which is consistent with the age range of our study, 46% had shared SELFIES within the past day, and 69% tended to share selfies three to 20 times daily [8].

Bhattacharyya [50], Gupta and Pooja [51], Kaur and Vig [27], and Singh and Tripathi [52] believed that excessive selfie-taking could result in some psychological problems on the part of the selfie-taker who has crossed from the borderline and acute stages to the chronic stage in their respective studies. This is supported by the current study results showing that chronic selfitis has a significant association with mood disorders, anxiety disorders, obsessive-compulsive disorder, eating disorders, and personality disorders more than the borderline and acute stages.

Consistent with the current study results, Nagaraju and Chikkegowda [53] found that 35.4% of the sample took >3 selfies/day, similar to a study done by Priya et al. [54] that was 31%. Borderline selfitis was seen in 23.9% of the sample, acute selfitis was seen in 8.4%, and chronic selfitis was seen in 3.2%. In the current study, we found that 49.5% of our sample exhibited borderline selfitis, 33.5% acute, and 9.5% chronic.

Consistency in the rate of selfie behavior was seen in the current study results and previous studies, as a study in the eastern part of India revealed that none of the students had acute or chronic selfitis. Almost one in every three students had borderline selfitis [55]. Similarly, studies that examined the negative consequences associated with social media use include engaging in social comparison, low self-esteem, and self-objectification [56]. Perhaps one of the most noted risks associated with social media use is depression, which is more common for those who report spending increased time on social networking sites across platforms [57], and we found that 31% of our sample diagnosed with major depressive disorder is having a chronic selfie behavior.

Although some scholars have claimed that the obsessive taking of selfies can be an addiction [27, 29, 58, 59] and that selfitis might be more common among those with a “selfie addiction” [60], little empirical research has been carried out. To date, only a few studies, mainly in Asia, have examined the negative effects of habitual selfie-taking on mental and physical health [61, 62]. These studies have revealed that selfie addiction is most commonly associated with narcissism, self-centered behavior, low self-esteem, loneliness, and depression [62]. Consistent with this study results, studies revealed that it is how one uses social media that gave an idea of whether one suffers or benefits from its use. For example, passive use, such as looking at the content others have shared (like selfies, that is, photographs one takes of oneself) or reading and not interacting with others, has been identified as particularly problematic; this use has been linked to increased anxiety, feelings of envy, and decreased well-being [63,64,65].

Regarding obsessive-compulsive disorder (OCD) and the excessive selfie behavior, a Malaysian study indicated that selfie might bring negative effects other than positive such as obsessive-compulsive disorder or body dysmorphic disorder and selfie obsession. The more women are exposed to *selfies* and other photos on social media, the more they compare themselves negatively. Researchers concluded that the phenomenon of a selfie is more on involving self-image, self-confidence, and self-esteem of oneself as stated by Tajuddin et al. [66] in 2013.

Introductory cross-sectional studies on the relationship between disordered eating and body image found that adolescent girls who reported greater photo investment (effort in choosing a selfie and monitoring likes/comments) and photo manipulation (digital editing of a selfie) reported greater eating and body image concerns which McLean et al. [21] introduced in 2015. This is particularly relevant as eating disorder risk is elevated during adolescence, and they are the most prolific users of photo-based social network sites based on a paper done by Smith and Anderson [67] in 2018. Goldenberg et al. [68] and Gupta [69] also found that body image dissatisfaction is closely linked to depression, eating disorders, and low self-esteem. This goes in line with our results showing that excessive involvement in selfie behavior had a significant relationship with eating disorders and depression as mentioned.

It was found in a significant amount of selfie researches done by Barry et al. [70], Weiser [71], Sorokowski et al. [33, 72], and Halpern et al. [73] that there is a link between narcissism and selfie-sharing behavior on social network sites, as selfie-sharing behavior increased one’s narcissism or vice versa. Other selfie studies as mentioned by Qiu et al. [74] in 2015 proposed that selfie content reflected people’s personality.

Katz and Crocker in [8] mentioned that selfies allow users novel opportunities to customize their self-presentation by giving picture takers a wide range of ways to portray themselves. Interestingly, in 2016, Halpern et al.’s [73] research has shown that this individualistic form of SNS usage, where users focus on how they want to be seen by others from their perspective, is highly related to narcissism.

Although several studies have burrowed into trait predictors of selfie-related behavior, existing research has largely investigated narcissism, where Choi et al. [75] in 2017 pointed to the idea that other traits relevant to selfies on SNSs remain unexamined.

This study may show the impact of social media and globalization on cultural phenomena and mental health and show how similar human beings are among all cultures that we share the same interests and the same pathology.

The work done in this study includes more than a narcissistic personality disorder. It showed that the diagnosis of borderline and histrionic personality disorders was more likely associated with higher scores on the SBS scale being more significant with chronic selfie behavior. This was supported by the results in the current study that 84.21% of the sample was more likely to have cluster B personality disorder with chronic selfie behavior. This needs to be supported by further studies on the effect of selfies on personality in adolescents and vice versa.

Conclusions

In summary, the study shows that selfie behavior was significant among females (59%), and in the literature group, 16% have chronic behavior, which significantly affects the personality development and increases the likelihood of occurrence of psychiatric disorder. A significant negative correlation between the Selfie Behavioral Scale total score and GAF score scale, i.e., a higher score on selfie is associated with less functioning among college students, is that chronic selfie behavior as categorized by the Selfie Behavioral Scale is associated with more likelihood development of MDD. In the current study, chronic selfie behavior is associated with more anxiety disorders, eating disorders, obsessive-compulsive disorder (OCD), and body dysmorphic disorder. Also, there was more chronic selfie-taking behavior among cluster B personality disorders being more significantly with narcissistic personality disorder (42%).

Clinical implications

It is important for mental health professionals to explore the adolescent’s purpose in taking selfies as it opens the door for discussions about self-esteem, body image, healthy relationships, and digital safety. Also, health professionals need to provide screen-free ways to show such individuals how to spend their time.

Limitations

The study sample size was not large enough, and students at 2 different faculties were assessed as a representative of the practical and theoretical colleges. This study was confined to a single governmental university in Cairo, Egypt, and cannot be generalized to other universities in smaller cities or private universities, so further research is still needed in this area.

Availability of data and materials

The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.

Abbreviations

APA:

American Psychiatric Association

GAF:

Global Assessment of Functioning

MDD:

Major depressive disorder

OCD:

Obsessive-compulsive disorder

SBS:

Selfie Behavioral Scale

SCID-I:

Structured Clinical Interview for DSM-IV-TR Axis I Disorders

SCID-II:

Structured Clinical Interview for DSM-IV-TR Axis II Disorders

SMU:

Social media use

SNSs:

Social network sites

SPSS:

Statistical Package for Social Sciences

References

  1. Dutta E, Sharma P, Shah N, Bharati A, Sonavane S, Desousa A (2018) Attitude toward selfie taking and it’s relation to image and narcissism in medical students. Indian J Psychol Med 40:17–21

    Article  Google Scholar 

  2. Griffiths MD (1995) Technological addictions.  Clin Psychol Forum 76:14–19

    Google Scholar 

  3. King ALS, Valença AM, Nardi AE (2010) Nomophobia: the mobile phone in panic disorder with agoraphobia: reducing phobias or worsening of dependence? Cogn Behav Neurol 23(1):52–54

    Article  Google Scholar 

  4. McDaniel BT (2015) “Technoference”: everyday intrusions and interruptions of technology in couple and family relationships. In: Bruess CJ (ed) Family communication in the age of digital and social media. Peter Lang Publishing, New York, pp 228–244

    Google Scholar 

  5. Lewis T (2006) Seeking health information on the internet: Lifestyle choice or bad attack of cyberchondria? Media Cult Soc 28(4):521–539

    Article  Google Scholar 

  6. Oxford Dictionaries (2013) http://www.oxforddictionaries.com/definition/english/selfie. Accessed 23 July 2015

  7. Jang JY, Han K, Shih PC, Lee D (2015) Generation like: comparative characteristics in instagram. In: Paper presented at theACM Conference on Human Factors in Computing Systems

    Google Scholar 

  8. Katz JE, Crocker ET (2015) Selfies and photo messaging as visual conversation: reports from the United States, United Kingdom and China. Int J Commun 9(12):1861–1872

    Google Scholar 

  9. Dutta E, Sharma P, Dikshit R, Shah N, Sonavane S, Bharati A et al (2016) Attitudes toward selfie taking in school-going adolescents: an exploratory study. Indian J Psychol Med 38(3):242–245

    Article  Google Scholar 

  10. We Are Social (2021) Digital in 2020 global overview. Retrieved February 08, 2020

  11. Mascheroni G, Ólafsson K (2018) Accesso, usi, rischi e opportunità di internet per i ragazzi Italiani. I primi risultati di EU Kids Online 2017. EU Kids Online and OssCom

  12. Bryant P, Bryant JA (2005) Adolescents and the internet. Adolesc Med Clin 16(2):413–426. https://doi.org/10.1016/j.admecli.2005.03.001

    Article  Google Scholar 

  13. Musetti A, Corsano P, Boursier V, Schimmenti A (2020) Problematic Internet use in lonely adolescents: the mediating role of detachment from parents. Clin Neuropsychiatry 17:3–10

    Google Scholar 

  14. Masha et al (2019) J Res Rev Soc Sci Pak 2(2):424–439 mashable.com/2014/11/07/first-selfie. Accessed 28 Sept 2019

    Google Scholar 

  15. Feltman CE, Szymanski DM (2018) Instagram use and self-objectification: the roles of internalization, comparison, appearance commentary, and feminism. Sex Roles 78(5–6):311–324

    Article  Google Scholar 

  16. d’Aloia A, Parisi F (2016) Snapshot culture: the photographic experience in the post-medium age. Comun Soc 1:3–14

    Google Scholar 

  17. Fox J, Vendemia MA (2016) Selective self-presentation and social comparison through photographs on social networking sites. Cyberpsychol Behav Soc Netw 19(10):593–600

    Article  Google Scholar 

  18. Sung Y, Lee J-A, Kim E, Choi SM (2016) Why we post selfies: understanding motivations for posting pictures of oneself. Pers Individ Differ 97:260–265

    Article  Google Scholar 

  19. Diefenbach S, Christoforakos L (2017) The selfie paradox: nobody seems to like them yet everyone has reasons to take them. An exploration of psychological functions of selfies in self-presentation. Front Psychol 8:7

    Article  Google Scholar 

  20. Balakrishnan J, Griffiths MD (2018) An exploratory study of “selfitis” and the development of the selfitis behaviour scale. Int J Ment Health Addict 16(3):722–736

    Article  Google Scholar 

  21. McLean SA, Paxton SJ, Wertheim EH, Masters J (2015) Photoshopping the selfie: self photo editing and photo investment are associated with body dissatisfaction in adolescent girls. Int J Eat Disord 48(8):1132–1140

    Article  Google Scholar 

  22. Griffiths D, Kuss D (2017) adolescent social media addiction (revisited). Educ Health 35(3):49–52

    Google Scholar 

  23. Essig T (2012) The addiction concept and technology: diagnosis, metaphor, or something else? A psychodynamic point of view. J Clin Psychol 68(11):1175–1184

    Article  Google Scholar 

  24. Grant JE, Brewer JA, Potenza MN (2006) The neurobiology of substance and behavioral addictions. CNS Spectr 11(12):924–930

    Article  Google Scholar 

  25. Donovan DM, Marlatt GA (eds) (2005) Assessment of addictive behaviors, 2nd edn. The Guilford Press, New York

    Google Scholar 

  26. Vincent J (2014) American Psychiatric Association makes it official: ‘selfie’ a mental disorder. In: Adobo chronicles, March 31 Retrieved September 6, 2017, from: https://adobochronicles.com/2014/03/31/american-psychiatric-association-makes-it-official-selfie-a-mental-disorder/

    Google Scholar 

  27. Kaur S, Vig D (2016) Selfie and mental health issues: an overview. Indian J Health Wellbeing 7(12):1149–1152

    Google Scholar 

  28. Sunitha PS, Vidya M, Rashmi P, Mamatha M (2016) Selfy [sic] as a mental disorder - a review. Int J Adv Nurs Manag 4(2):169–172

    Article  Google Scholar 

  29. Kela R, Khan N, Saraswat R, Amin B (2017) Selfie: enjoyment or addiction? J Med Sci Clin Res 5:15836–15840

    Article  Google Scholar 

  30. Baiocco R, Chirumbolo A, Bianchi D, Ioverno S, Morelli M, Nappa MR (2017) How hexaco personality traits predict different selfie-posting behaviors among adolescents and young adults. Front Psychol 7:2080

    Article  Google Scholar 

  31. Fox J, Rooney MC (2015) The dark triad and trait self-objectification as predictors of men’s use and self-presentation behaviors on social networking sites. Pers Individ Differ 76:161–165

    Article  Google Scholar 

  32. Choi J, Flaherty GT (2016) The ‘selfie’phenomenon: reducing the risk of harm while using smartphones during international travel. J Travel Med 23(2):1–3

  33. Sorokowski P, Sorokowska A, Oleszkiewicz A, Frackowiak T, Huk A, Pisanski K (2015) Selfie posting behaviors are associated with narcissism among men. Pers Individ Differ 85:123–127

    Article  Google Scholar 

  34. Varma R, Sarada K, Radha SR (2020) A study on “selfitis”: selfie addiction among medical students. IOSR J Dent Med Sci 21(25):24

    Google Scholar 

  35. First MB, Spitzer RL, Gibbon M, Williams JBW (eds) (1997) Structured Clinical Interview for DSM-IV Axis I Disorders-Clinical Version (SCID-CV). APA Press, Washington

    Google Scholar 

  36. El Missiry A, Sorour A, Sadek A, Fahy T, Abdel Mawgoud M, Asaad T (2004) Homicide and psychiatric illness: an Egyptian study [MD thesis]. Faculty of Medicine, Ain Shams University, Cairo

    Google Scholar 

  37. Hatata H, Khalil A, Asaad T, AboZeid M, Okasha T (2003) Dual diagnosis in substance use disorders. A study in an Egyptian sample. Unpublished MD Thesis. Institute of Psychiatry, Ain Shams University, Cairo

    Google Scholar 

  38. Beyens I, Pouwels JL, van Driel II, Keijsers L, Valkenburg PM (2020) The effect of social media on well-being differs from adolescent to adolescent. Sci Rep 10:10763

    Article  CAS  Google Scholar 

  39. Jensen M, George MJ, Russell MR, Odgers CL (2019) Young adolescents’ digital technology use and mental health symptoms: little evidence of longitudinal or daily linkages. Clin Psychol Sci 7:1416–1433

    Article  Google Scholar 

  40. Orben A, Przybylski AK (2019) The association between adolescent well-being and digital technology use. Nat Hum Behav 3:173–182

    Article  Google Scholar 

  41. Monacis L, Griffiths M, Limone P, Sinatra M, Servidio R (2020) Selfitis behavior: assessing the Italian version of the Selfitis Behavior Scale and its mediating role in the relationship of dark traits with social media addiction. Int J Environ Res Public Health 17:5738. https://doi.org/10.3390/ijerph17165738

    Article  Google Scholar 

  42. Senft TM, Baym NK (2015) What does the selfie say? Investigating a global phenomenon. Int J Commun 9:1588e1606

    Google Scholar 

  43. Joy D, Venkatachalam J (2019) Personality and selfie-liking behaviour among college students. Res J Soc Sci 10:6 https://www.researchgate.net/profile/Dom-Joy/publication/333802385

    Google Scholar 

  44. Wild C. The first selfie ever was taken in 1839. 2019. Available from: https://mashable.com/2014/11/07/first-selfie. Accessed 28 Sept 2019

    Google Scholar 

  45. Amandeep D, Ståle P, Torbjørn T, Cecilie SA (2016) Do age and gender differences exist in selfie related behaviors? Comput Hum Behav 63(2016):549–555

    Google Scholar 

  46. Clay D, Vignoles VL, Dittmar H (2005) Body image and self-esteem among adolescent girls: testing the influence of sociocultural factors. J Res Adolesc 15:451–477

    Article  Google Scholar 

  47. Richard K, Douglas EA (2016) From liberation to control: understanding the selfie experience. Eur J Mark 50(9/10):1893–1902

    Article  Google Scholar 

  48. Richard K, Douglas EA, Jonathan S (2016) The selfie phenomenon – consumer identities in the social media marketplace. Eur J Mark 50(9/10):1767–1772

    Article  Google Scholar 

  49. Kiprin, B. (2013). Go selfie yourself. http://borislavkiprin.com/2013/12/13/go-selfieyourself/

  50. Bhattacharyya R (2017) Addiction to modern gadgets and technologies across generations. East J Psychiatry 18(2):27–37

    Article  Google Scholar 

  51. Gupta R, Pooja M (2016) Selfie an infectious gift of IT to modern society. Glob J Res Anal 5(1):278–280

    Google Scholar 

  52. Singh, S., & Tripathi, K.M. (2017). Selfie: a new obsession. SSRN, 1–3. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2920945

    Google Scholar 

  53. Nagaraju R, Chikkegowda LK (2019) Selfie: a rising culture. Assessment of selfitis and its relation with self-esteem among medical and nursing students: a cross-sectional study. Natl J Community Med 10(5):285–289

    Google Scholar 

  54. Mohan P, Sunda S, Dubey P (2017) Selfitis: selfie craze and addiction. Res J Manag Sci 6(6):12–21

    Google Scholar 

  55. Ray S, Panja TK, Mukhopadhyay DK (2020) Selfitis, narcissism, and emotional intelligence: eliciting the interrelation among medical students in Kolkata, West Bengal. Acta Med Int 7:81–85

    Article  Google Scholar 

  56. Hanna E, Ward LM, Seabrook RC, Jerald M, Reed L, Giaccardi S, Lippman JR (2017) Contributions of social comparison and self-objectification in mediating associations between Facebook use and emergent adults’ psychological well-being. Cyberpsychol Behav Soc Netw 20:172–179

    Article  Google Scholar 

  57. Lin L, Sidani JE, Shensa A, Radovic A, Miller E, Colditz JB, Primack BA (2016) Association between social media use and depression among US young adults. Depress Anxiety 33:323–331

    Article  Google Scholar 

  58. Shah PM (2015) Selfie—a new generation addiction disorder—literature review and updates. Int J Emerg Ment Health Hum Resilience 17:602

    Article  Google Scholar 

  59. Singh D, Lippmann S (2017) Selfie addiction. Internet and Psychiatry https://www.internetandpsychiatry.com/wp/editorials/selfie-addiction. Accessed 6 June 2019

    Google Scholar 

  60. Balakrishnan J, Griffiths MD (2018) An exploratory study of “selfitis” and the development of the selfitis behavior scale. Int J Ment Health Addict 16(3):722–736

  61. Dokur M, Petekkaya E, Karadag M (2018) Media-based clinical research on selfie-related injuries and deaths. Ulus Travma Acil Cerrahi Derg [Turk J Trauma Emerg Surg] 24(2):129–135

    Google Scholar 

  62. Pantic I, Milanovic A, Loboda B, Błachnio A, Przepiorka A, Nesic D, Mazic S, Dugalic S, Ristic S (2017) Association between physiological oscillations in self-esteem, narcissism and internet addiction: a cross-sectional study. Psychiatry Res 258:239–243. https://doi.org/10.1016/j.psychres.2017.08.044

    Article  Google Scholar 

  63. Shaw AM, Timpano KR, Tran TB, Joormann J (2015) Correlates of Facebook usage patterns: the relationship between passive Facebook use, social anxiety symptoms, and brooding. Comput Hum Behav 48:575–580

    Article  Google Scholar 

  64. Verduyn P, Lee DS, Park J, Shablack H, Orvell A, Bayer J et al (2015) Passive Facebook usage undermines affective well-being: experimental and longitudinal evidence. J Exp Psychol Gen 144:480–488

    Article  Google Scholar 

  65. Verduyn P, Ybarra O, Résibois M, Jonides J, Kross E (2017) Do social network sites enhance or undermine subjective well-being? A critical review. Soc Issues Policy Rev 11:274–302

    Article  Google Scholar 

  66. Tajuddin JM, Hassan NA, Ahmad R (2013) Social media usage among university students: a study on selfie and its impacts (January 19, 2013). Glob J Bus Soc Sci Rev 1(1):124–132 Available at SSRN: https://ssrn.com/abstract=3000802

    Article  Google Scholar 

  67. Smith, A., & Anderson, M. (2018). Social media use in 2018: a majority of Americans use Facebook and YouTube, but young adults are especially heavy users of Snapchat and Instagram. Retrieved from https://www.pewinternet.org

    Google Scholar 

  68. Goldenberg JL, Cooper DP, Heflick NA, Routledge C, Arndt J (2011) Is objectification always harmful? Reactions to objectifying images and feedback as a function of self-objectification and mortality salience. J Exp Soc Psychol 47(2):443–448

    Article  Google Scholar 

  69. Gupta C (2013) The relation between body image satisfaction and selfesteem to academic behaviour in pre-adolescent and adolescent girls and boys. ProQuest Dissertations Publishing, University of Manitoba, Canada, p pMR95654

    Google Scholar 

  70. Barry CT, Doucette H, Loflin DC, Rivera-Hudson N, Herrington LL (2017) “Let me take a selfie”: associations between selfphotography, narcissism, and self-esteem. Psychol Pop Media Cult 6(1):48

    Article  Google Scholar 

  71. Weiser EB (2015) #Me: narcissism and its facets as predictors of selfie-posting frequency. Pers Individ Differ 86:477–481

    Article  Google Scholar 

  72. Sorokowski P, Sorokowska A, Frackowiak T, Karwowski M, Rusicka I, Oleszkiewicz A (2016) Sex differences in online selfie posting behaviors predict histrionic personality scores among men but not women. Comput Hum Behav 59:368–373

    Article  Google Scholar 

  73. Halpern D, Valenzuela S, Katz JE (2016) “Selfie-ists” or “narciselfiers”?: a cross-lagged panel analysis of selfie-taking and narcissism. Pers Individ Differ 97:98–101

    Article  Google Scholar 

  74. Qiu L, Lu J, Yang S, Qu W, Zhu T (2015) What does your selfie say about you? Comput Hum Behav 52:443–449

    Article  Google Scholar 

  75. Choi TR, Sung Y, Lee JA, Choi SM (2017) Get behind my selfies: the big five traits and social networking behaviors through selfies. Pers Individ Dif 109:98–101

    Article  Google Scholar 

Download references

Acknowledgements

The authors want to thank all students who participated in this study; they have provided valuable information that might be an initial probe about the magnitude of the problem of the selfie phenomenon among college students in Egypt.

Funding

This research received no specific grant from any funding agency.

Author information

Authors and Affiliations

Authors

Contributions

Reem Hashem, Ghada Abdelrazik and Mona El-Sheikh are joint first authors. Mona El-Sheikh, Ghada Abdelrazik, and Hadeer Hassan contributed to the conception, design, and supervision of the data collection process. Hadeer Hassan and Reem Hashem participated in analyzing and interpreting the data. Hadeer Hassan and Lobna Bakr contributed to the writing of the original manuscript, and Ghada Abdelrazik and Mona El-Sheikh revised the manuscript. Ghada Abdelrazik, Mona El-Sheikh, Reem Hashem, and Lobna Bakr participated in reviewing the methods and provided critical revision. The authors have read and approved the final manuscript.

Corresponding author

Correspondence to Hadeer Hassan.

Ethics declarations

Ethics approval and consent to participate

All subjects enrolled in the study signed an informed consent prior to completing the questionnaire, and the participation was voluntary. All methods were carried out in accordance with relevant guidelines and regulations. The study protocol for data collection was approved by the Ain-Shams University research and ethical committee and the scientific committee of the Neuropsychiatric Department.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hashem, R.E.S.M., Hassan, G.A.M., El-Sheikh, M.M. et al. Selfie phenomenon among a sample of Egyptian university students: rate and psychiatric correlates. Middle East Curr Psychiatry 29, 103 (2022). https://doi.org/10.1186/s43045-022-00254-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s43045-022-00254-5

Keywords

  • Selfie phenomenon
  • University students
  • Depression
  • Anxiety
  • Body dysmorphic
  • Obsessive compulsive
  • Narcissistic
  • Histrionic
  • Egypt