Effects of psychiatric symptoms, age, and gender on fear of missing out (FoMO) and problematic smartphone use: A path analysis with clinical-based adolescent sample

Abstract

Background:

Fear of missing out (FoMO) is a kind of anxiety that arises from FoMO on rewarding online social experiences that others might be having. Recent studies demonstrated that there is a strong relationship between FoMO and problematic smartphone use (PSU). In this study, we aimed to address the relationship between age, gender, psychiatric symptoms, PSU, and FoMO among a clinical-based adolescent sample.

Methods:

In total, 197 adolescents (136 boys, 12–18 years) who applied to psychiatry clinics were recruited in the study. Path analysis with observed variables was used to investigate the relationships of PSU and FoMO with each other and with psychiatric symptoms (somatization, obsession–compulsion, interpersonal sensitivity, depression, anxiety, phobic anxiety, paranoid ideation, and psychoticism), age, and gender.

Results:

Path analysis showed that age (B₁ = 2.35, P < 0.001), somatization (B₁ = 1.19, P < 0.001), hostility (B₁ = 0.92, P = 0.001), and paranoid ideation (B₁ = 0.93, P = 0.005) have significant positive effect on PSU, when interpersonal sensitivity has a significant negative effect (B₁ = –1.47, P < 0.001). For FoMO, male gender (B₀ = 0.35, P < 0.001), anxiety (B₁ = 1.37, P < 0.001), and PSU have positive effects, whereas age (B₁ = –1.60, P < 0.001), depression (B₁ = –0.58, P = 0.004), and hostility (B₁ = –0.49, P = 0.001) have a negative effect.

Conclusions:

Our study demonstrated that although PSU and FoMO are closely related to each other in previous studies, they have different associations with age, gender, and psychiatric symptoms among a clinical-based adolescent sample. The positive effects of PSU, anxiety on FoMO are predictable; however, the negative effect of age, hostility, and depression on FoMO was interesting. These relationships could be related to social exclusion-hostility and impulsivity-male gender/younger age associations in adolescence. In addition, we did not find a significant effect of FoMO on PSU, this could be related to the social and non-social use of smartphones, and should be reevaluated in clinical samples in the future.

INTRODUCTION

Mobile phone use increased rapidly after smartphones. Smartphones changed how humans communicate and entertain themselves. Although it is a tool that makes life easier and enjoyable, some vulnerable groups have a higher risk of formal adaptive use, frequently defined as problematic smartphone use (PSU).[1] One of the risky groups for PSU is young adults and adolescents[2,3] and PSU is associated with depression, anxiety, sleep problems, and low self-esteem among this group.[4,5,6]

Fear of missing out (FoMO) is a kind of anxiety that arises from FoMO on rewarding online social experiences that others might be having.[7] Recent studies have shown that there is a strong relationship between FoMO and PSU. Some of them suggest that FoMO play an important role in developing PSU because adolescents with high FoMO feel compelled to check their smartphone to keep up to date on their friends’ activities.[8,9,10] In contrast, some other studies suggested that PSU results in an increased tendency of FoMO due to extensive social media use (the continuous notifications from social media sites/applications on smartphones heighten the need to check on what friends are doing more often).[11,12,13] In addition, a recent study that examined the longitudinal, bi-directional relationships between FoMO and PSU among adolescents suggested that adolescents who report higher FoMO and/or PSU at a given time point are more likely to report higher levels of FoMO and/or PSU from 1 year to the next.[14]

One of the important key points in the PSU–FoMO association is the presence of psychopathologies. Recent studies demonstrated that FoMO is related to both PSU and psychiatric symptoms including depression and anxiety and FoMO mediated the effect of these symptoms on negative consequences of PSU[8,9,13,15] Moreover, the effect of FoMO on the negative consequences of PSU was mediated by the intensity of social network sites (SNSs).[16]

In this study, we aimed to address the relationship between age, gender, psychiatric symptoms, PSU, and FoMO among a clinical-based adolescent sample.

Our hypotheses are:

1. Somatization, obsession–compulsion, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism symptoms have positive effects on both PSU and FoMO.

2. Gender and age have effects on PSU and FoMO.

MATERIALS AND METHODS

Participants and procedure

After ethical approval, 12–18 years old adolescents who were referred to psychiatry/child and adolescent psychiatry clinics and who have their smartphones were invited to the study. If they agreed to participate, written informed consent was obtained. There were 136 boys and 61 girls aged between 12 and 18 (median age: 15 years) years. (median maternal age: 40, median maternal education level: 6 years, median paternal age: 44.5 years, median paternal education level: 8 years) [Table 1].

Table 1.

Demographic characteristics of groups

Characteristics	n (197)	%
Gender
Boys	136	(69)
Girls	61	(31)
Age (years); median (min–max)	15 (12-18)
Education	10 (0-12)
Socioeconomic status
Monthly income (lira); median (min–max)	2000 (0-5000)
Maternal education (years) median (min–max)	6 (3-16)
Paternal education (years) median (min–max)	8 (5-16)
Maternal age (years) median (min–max)	40 (31-58)
Paternal age (years) median (min–max)	44.5 (36-76)

Measurements

Problematic Mobile Phone Usage Scale (PMPUS)

This scale was developed by Augner and Hacker.[17] It is a Likert-type scale that is scored between 0 (no) and 4 (very frequent) points in the addiction and social relations section; 0 to 4 points (0 = strongly disagree, 4 = strongly agree) in the results section. The total score for the entire scale ranges from 0–104 (over 30 points are regarded as problematic use). Taking a high score indicates that someone is having more problematic and addictive mobile phone use. The Turkish validity and reliability study of the scale was made by Tekin and colleagues.[18] For our sample, the value of Cronbach a is = 0.94.

Brief Symptom Inventory (BSI)

The Brief Symptom Inventory was developed by Derogatis (1992) for the purpose of screening various psychological indications. It is the short form of SCL-90-R. Among the 90 items distributed over 9 factors of SCL-90-R, the short form was obtained by selecting 53 items with the highest load in each factor. It is a 4-point Likert-type scale. The high scores on the total scores indicate the frequency of the individual’s symptoms.[19] It has items for somatization, obsession–compulsion, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism. Turkish adaptation studies were made by Sahin and Durak (1994).

Fear of Missing Out Scale (FoMO)

The scale is a 1-factor 10-item self-report measurement (e.g., I get anxious when I do not know what my friends are up to). Each item is rated on a 5-point Likert scale (1 = not at all true to 5 = absolutely true). The total scores of the scale range between 10 and 50 and higher scores indicate a higher level of FoMo. The Cronbach a coefficient of the original version is 0.90.[7] Turkish validity and reliability studies demonstrated that the Cronbach a values were ranged between 0.78 and 0.86 in three different samples.[20]

Statistical analysis

We used IBM SPSS Statistics for Windows 22.0 and IBM AMOS 24.0 for analysis. Pearson, Chi-square, and Fisher’s exact tests were used to compare the differences in categorical variables. Pearson correlation analyzes were used to examine the relationships between scale scores. Path analysis method with observed variables was used to investigate the relationships of PSU and FoMO with each other and with psychiatric symptoms (somatization, obsession–compulsion, interpersonal sensitivity, depression, anxiety, phobic anxiety, paranoid ideation, and psychoticism), age, and gender.

The model fit was assessed using appropriate residual and goodness-of-fit statistics. A 5% type-I error level was used to infer statistical significance.

RESULTS

Results of correlation analysis

There were positive significant correlations between FoMO, PSU, and BSI subscales. For all psychiatric symptoms, PSU’s correlations were stronger than FoMO’s. The relationship between psychiatric symptoms and FoMO is generally weak except the anxiety (for anxiety r = 0.43, moderate) (For others r < 0.40) [Table 2].

Table 2.

Correlations of BSI sub-scales and FoMO (fear of missing out scale)–PSU (problematic mobile phone usage scale) scores

BSI- Subscales	FoMo	PSU
Somatization	0.30**	0.62**
Obsession–Compulsion	0.31**	0.51**
Interpersonal Sensitivity	0.32**	0.41**
Depression	0.35**	0.53**
Anxiety	0.43**	0.49**
Hostility	0.28**	0.57**
Phobic Anxiety	0.32**	0.49**
Paranoid Ideation	0.36**	0.55**
Psychoticism	0.32**	0.52**
FoMO	–	0.46**
PMPUS	0.46**	–

Pearson correlations. **Correlations are significant at 0.01 level (2-tailed). BSI: Brief Symptom Inventory; FOMO: fear of missing out; PMPUS: Problematic Mobile Phone Usage Scale.

Results of path analysis

According to the results of the first step path analysis, we found that some of the variables have statistically insignificant path coefficients (for PSU: gender, obsession–compulsion, depression, anxiety, phobic anxiety, psychoticism, and FoMO; for FoMO: somatization, obsession–compulsion, interpersonal sensitivity, phobic anxiety, paranoid ideation, psychoticism) (you can see the details of β and P values of the first model in Table 3). These variables were removed from the model and the analyses were repeated. As Table 4 and Figures 1 and 2 show, age (B₁ = 2.35, P < 0.001), somatization (B₁ = 1.19, P < 0.001), hostility (B₁ = 0.92, P = 0.001), and paranoid ideation (B₁ = 0.93, P = 0.005) have significant positive effect on PSU, when interpersonal sensitivity has a significant negative effect (B₁ = –1.47, P < 0.001). These results demonstrated that older age, higher somatization, hostility, and paranoid ideation symptoms increase the risk of PSU; however, higher interpersonal sensitivity decreases the PSU. Table 4 and figures also show that male gender (B₀ = 0.35, P < 0.001), anxiety (B₁ = 1.37, P < 0.001), and PSU have positive effects on FoMO, whereas age (B₁ = –1.60, P < 0.001), depression (B₁ = –0.58, P = 0.004), and hostility (B₁ = –0.49, P = 0.001) have negative effect. These results demonstrated that younger age, male gender, and higher anxiety symptoms increase the risk of FoMO; however, higher depression and hostility symptoms decrease the FoMO.

Table 3.

Results of the path analysis-first model

Variables			B0	B1	S.E.	C.R.	P
PSU	<---	Age	0.205	2.376	0.587	4.051	<0.001
PSU	<---	Gender	0.040	1.604	2.038	0.787	0.431
PSU	<---	Somatization	0.409	1.053	0.289	3.650	<0.001
PSU	<---	Obsession–Compulsion	0.155	0.468	0.302	1.548	0.122
PSU	<---	Interpersonal Sensitivity	–0.343	–1.423	0.498	–2.856	0.004
PSU	<---	Depression	0.105	0.264	0.429	0.617	0.537
PSU	<---	Anxiety	–0.221	–0.648	0.495	–1.310	0.190
PSU	<---	Hostility	0.342	1.095	0.307	3.573	<0.001
PSU	<---	Phobic Anxiety	0.014	0.050	0.389	0.129	0.897
PSU	<---	Paranoid Ideation	0.256	0.906	0.395	2.293	0.022
PSU	<---	Psychoticism	–0.031	–0.110	0.376	–0.293	0.769
PSU	<---	FoMO	–0.026	–0.045	0.187	–0.239	0.811
FoMO	<---	Age	–0.259	–1.747	0.329	–5.313	<0.001
FoMO	<---	Gender	0.346	8.100	1.098	7.377	<0.001
FoMO	<---	Somatization	0.086	0.129	0.160	0.803	0.422
FoMO	<---	Obsession-Compulsion	–0.183	–0.320	0.163	–1.960	0.050
FoMO	<---	Interpersonal Sensitivity	–0.060	–0.145	0.274	–0.530	0.596
FoMO	<---	Depression	–0.375	–0.549	0.231	–2.378	0.017
FoMO	<---	Anxiety	0.908	1.550	0.267	5.799	<0.001
FoMO	<---	Hostility	–0.335	–0.623	0.170	–3.661	<0.001
FoMO	<---	Phobic Anxiety	–0.078	–0.159	0.209	–0.759	0.448
FoMO	<---	Paranoid Ideation	0.112	0.230	0.215	1.067	0.286
FoMO	<---	Psychoticism	0.025	0.053	0.202	0.262	0.793
FoMO	<---	PSU	0.533	0.310	0.039	7.988	<0.001

B0, standardized regression coefficient, B1, unstandardized regression coefficient; PSU: Problematic Mobile Phone Usage Scale Score; FoMO: fear of missing out, Gender was coded as 0 for girls, 1 for boys

Table 4.

Results of the path analysis-final model

Variables			B0	B1	S.E.	C.R.	P
PSU	<---	Age	0.206	2.351	0.610	3.855	<0.001
PSU	<---	Somatization	0.459	1.196	0.245	4.890	<0.001
PSU	<---	Interpersonal sensitivity	–0.359	–1.470	0.402	–3.657	<0.001
PSU	<---	Hostility	0.286	0.902	0.276	3.271	0.001
PSU	<---	Paranoid ideation	0.265	0.937	0.334	2.803	0.005
FoMO	<---	Age	–0.245	–1.608	0.336	–4.790	<0.001
FoMO	<---	Gender	0.352	8.005	1.117	7.168	<0.001
FoMO	<---	Depression	–0.413	–0.588	0.204	–2.887	0.004
FoMO	<---	Anxiety	0.826	1.372	0.231	5.943	<0.001
FoMO	<---	Hostility	–0.275	–0.497	0.154	–3.230	0.001
FoMO	<---	PSU	0.533	0.305	0.036	8.420	<0.001

B0, standardized regression coefficient, B1, unstandardized regression coefficient; PSU: Problematic Mobile Phone Usage Scale Score; FoMO: fear of missing out. Gender was coded as 0 for girls, 1 for boys. R2 for PSU=0.483; R2 for FoMO=0.541

Figure 1.

Path diagram with unstandardized regression coefficients

Figure 2.

Path diagram with standardized regression coefficients

Finally, to verify the fitness of the model, indicators of goodness-of-fit were calculated and presented in Table 5. Our model has a good relatively good fit according to the indicators.

Table 5.

Final model goodness of fit

Measure	Good fit	Acceptable fit	Fit index values of final model
c2/sd	≤3	≤4-5	1.98
RMSEA	≤0.05	0.06-0.08	0.07
SRMR	≤0.05	0.06-0.08	0.07
NFI	≥0.98	0.94-0.90	0.98
CFI	≥0.97	≥0.95	0.99
GFI	≥0.90	0.89-0.85	0.96
AGFI	≥0.90	0.89-0.85	0.89
TLI	≥0.95	0.94–0.90	0.97

DISCUSSION

Our study demonstrated that although PSU and FoMO are closely related to each other in previous studies, they have different associations with age, gender, and psychiatric symptoms among adolescents. Hostility symptoms and older age have a negative effect on FoMO; however, a positive effect on PSU. Gender has an effect only on FoMO (male gender is a risk factor for FoMO). In addition, PSU is related to higher somatization, paranoid ideation, and lower interpersonal sensitivity, whereas FoMO is related to higher depression and anxiety.

FoMO is defined as the tendency toward having FoMO on actions/status that others are experiencing and rewarding thus having the desire to constantly stay connected.[7] Wegmann et al. (2017)[15] defined two types of FoMO: 1. trait-FoMO, which refers to a dispositional characteristic such as “fearing that others are having fun without me” and 2. internet-specific FoMO, which has more direct relevance in the context of online use such as “not wanting to miss out on anything online.” Their study indicated that internet-specific FoMO mediated the effect of trait-FoMO and depression-interpersonal sensitivity on internet communication disorder. Furthermore, they showed that the effects of trait and internet-specific FoMO were specific to internet communication disorder, did not predict the internet gaming disorder, which is another type of problematic internet use. These results are supported by other studies, which reported the links between FoMO-SNS addiction[21,22] and FoMO-PSU.[8] Also, recent studies revealed that depression, anxiety, and stress mediated the relationship between FoMO-PSU and the effect of FoMO on the negative consequences of PSU was mediated by the intensity of SNS use.[9,13] Summarizing the results from the above-mentioned studies it appears that FoMO is an important risk factor, particularly in the context of excessive SNS use, not a direct risk factor for PSU. Supporting, we found that PSU has a significant positive effect on FoMO; however, FoMO has no such effect on PSU. This result should be evaluated in further studies with adolescents.

Our study adds to the literature also by examining the psychiatric predictors of FoMO among adolescents. We found that higher levels of PSU and anxiety, lower levels of depression, and hostility increase the risk of FoMO. The relationship between FoMO and anxiety is predictable because FoMO is a type of anxiety to miss out on rewarding experiences that result from people’s desire for interpersonal attachments. This desire is grounded in people’s need to belong and is a fundamental motivation for humans.[23,24] However, the negative effect of hostility on FoMO is interesting. This effect could be related to social exclusion. The fear of being socially excluded plays a role in experiencing FoMO.[23] Social exclusion risk produces fear of losing belongingness and worthlessness[23] and these feelings lead people to compare themselves with others on social media platforms for deciding upon their personal value.[25,26] In contrast, how do socially excluded adolescents feel? Prior research has confirmed a causal path between social rejection/exclusion, and aggression-hostility.[27,28] Although it is not possible to evaluate causality in a cross-sectional study such as the present one, it can be speculated that socially excluded adolescents could have higher hostility and lower FoMO. In other words, a decrease in FoMO could be a consequence of social exclusion.

Another important and interesting result of our study is the negative relationship between depression and FoMO. This result contradicts many previous studies that reported a positive relationship.[7,29,30,31] We speculate that there are two reasons why our results differ from previous studies. First, the vast majority of studies on FOMO are online or with college students. It is expected that the results of these studies will differ from the clinical sample. As a matter of fact, it can be thought that many young people who have low levels of depression symptoms do not feel the need to apply to the psychiatry service will have problematic smartphone use. In addition, symptoms at this level have not yet caused social isolation and may have impaired functionality to a small extent. However, considering that the severity of depression in the clinical sample is at a level that requires seeking treatment, it can be predicted that functionality is more impaired, social isolation increases, and a young person with this condition will have a low FOMO level. A recent study that addressed the PSU-FoMO and depression associations in a new perspective supports these predictions. In this study, results demonstrated that non-social smartphone use was more strongly linked with the severity of PSU compared to social smartphone use. In addition, they found that FoMO mediated the relationship between depression severity and non-social PSU.[32] Considering the results of our study, we can say that the effect of social/non-social smartphone use and psychopathologies in the PSU-FOMO relationship should be reconsidered in the clinical adolescent sample.

Finally, we found both younger age and male gender are the predictors of FoMO. A recent study with young adults found that FoMO is related to younger age but not gender.[33] As known impulsivity is an important psychiatric problem for adolescent boys than girls and impulsivity decrease with age. The relationship between FoMO and young age–male gender could be related to impulsivity among adolescents. The association between impulsivity-FoMO was demonstrated in previous studies with young adults.[34,35] Future studies should examine the impulsivity-FoMO relationship among adolescents, too.

The results of our study seem important to guide our clinical practice but also it has limitations. Firstly, we used self-report scales, so we could not get information from parents and teachers. Some adolescents may have scored lower than they are in reality; thus, the PSU and FoMO rates could be higher than detected. Another problem is the difficulty of comparing the results due to the use of different scales in previous studies. This difficulty, unfortunately, is also a common limitation of studies measuring social media overuse and addiction.[36] Secondly, although there was a valid statistical power analysis, the sample size is relatively small, and the study has a cross-sectional design so it is difficult to determine the sequence of cause-effects—consequences and generalize the findings. In other words, finding such as a high prevalence of PSU and FoMO in a clinical adolescent sample makes us think about the possibility that this could be a consequence of psychiatric symptoms rather than the cause. Thirdly, it would be useful to address the diagnoses of adolescents (e.g., attention deficit hyperactivity disorder, depression, anxiety disorders, and obsessive compulsive disorder) rather than measuring psychiatric symptom scores. We want to underline that large sample sizes and case–control studies are needed to determine multiple relationships between PSU, FoMO, and psychiatric problems. We hope that our study could be a step to increase clinicians’ awareness of the FoMO among adolescents.

Declaration of patient consent

The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.