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Xinyu Zheng Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, People's Republic of China

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Yuwei Yang Guangdong Provincial Center for Disease Control and Prevention, People's Republic of China

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Weiqing Jiang Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, People's Republic of China

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Yitong He Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, People's Republic of China

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Cuihong Huang Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, People's Republic of China

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Yilin Hua Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, People's Republic of China

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Ciyong Lu Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, People's Republic of China

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Lan Guo Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, People's Republic of China

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Open access

Abstract

Background and aims

Gender nonconformity (GNC), which refers to an individual's expression of gender that does not align with the socially prescribed norms for their biological sex, may be associated with adverse behavioral problems, such as problematic smartphone use (PSU) and problematic internet use (PIU). This study examined the associations between GNC and PSU and GNC and PIU among Chinese adolescents.

Methods

This cross-sectional study utilized data from the 2021 School-based Chinese Adolescents Health Survey, recruiting 23,054 eligible adolescents aged 11 to 21, with an average age of 14.9 (SD: 1.7) years from 504 classes in 84 public high schools across 7 cities in China. Gender nonconformity, PSU/PIU, and demographics were measured. Mixed-effect linear regression models were performed.

Results

Among the participants (51.0% male), 5.3% reported high GNC and 26.9% reported moderate GNC. After adjusting for covariates, high GNC was significantly and positively associated with PSU (Β = 1.11, 95% CI = 0.49–1.72) and PIU severity (Β = 2.16, 95% CI = 1.40–2.93). Stratified analyses indicated that the associations between GNC and PSU differed between males and females, with a significant association observed only among male students (Β = 1.91, 95% CI = 0.97–2.86).

Discussion and conclusions

GNC is positively associated with the severity of PSU and PIU among Chinese adolescents, with male gender-nonconforming adolescents being more vulnerable to PSU. These results highlight the importance of implementing education on gender expression diversity in schools to create an inclusive school environment, which may potentially help prevent PSU and PIU among gender-nonconforming adolescents.

Abstract

Background and aims

Gender nonconformity (GNC), which refers to an individual's expression of gender that does not align with the socially prescribed norms for their biological sex, may be associated with adverse behavioral problems, such as problematic smartphone use (PSU) and problematic internet use (PIU). This study examined the associations between GNC and PSU and GNC and PIU among Chinese adolescents.

Methods

This cross-sectional study utilized data from the 2021 School-based Chinese Adolescents Health Survey, recruiting 23,054 eligible adolescents aged 11 to 21, with an average age of 14.9 (SD: 1.7) years from 504 classes in 84 public high schools across 7 cities in China. Gender nonconformity, PSU/PIU, and demographics were measured. Mixed-effect linear regression models were performed.

Results

Among the participants (51.0% male), 5.3% reported high GNC and 26.9% reported moderate GNC. After adjusting for covariates, high GNC was significantly and positively associated with PSU (Β = 1.11, 95% CI = 0.49–1.72) and PIU severity (Β = 2.16, 95% CI = 1.40–2.93). Stratified analyses indicated that the associations between GNC and PSU differed between males and females, with a significant association observed only among male students (Β = 1.91, 95% CI = 0.97–2.86).

Discussion and conclusions

GNC is positively associated with the severity of PSU and PIU among Chinese adolescents, with male gender-nonconforming adolescents being more vulnerable to PSU. These results highlight the importance of implementing education on gender expression diversity in schools to create an inclusive school environment, which may potentially help prevent PSU and PIU among gender-nonconforming adolescents.

Introduction

The use of smartphones and the internet has become increasingly popular among adolescents worldwide, with widespread access to digital devices and high-speed internet (Ricoy, Martínez-Carrera, & Martínez-Carrera, 2022). In China alone, there were over 191 million adolescent internet users in 2021, with the majority accessing the web through their personal devices (China Internet Network Information Center, 2022). While these technologies offer numerous benefits, excessive use and dependency among young people are growing public concerns (Meng et al., 2022; Pan, Chiu, & Lin, 2020). Two forms of problematic digital use that are common among adolescents are problematic smartphone use (PSU) and problematic internet use (PIU) (Christakis, 2019). Evidence has shown that adolescents who engage in PSU and PIU are at increased risk of physical discomfort (e.g., back, neck, and wrist pain), lower academic performance, and mental health issues (e.g., anxiety, depression, and suicidal behavior) (Shinetsetseg, Jung, Park, Park, & Jang, 2022; van den Eijnden, Koning, Doornwaard, van Gurp, & TerBogt, 2018). Given the high occurrence and harmful effects of PSU and PIU among adolescents, it is crucial to identify those who are most vulnerable and more likely to engage in high levels of problematic digital use.

Gender, in this context, refers to the cultural roles and expectations assigned to individuals based on their biological sex. It is an organizing feature in most societies that shapes norms of socialization (Bewley, McCartney, Meads, & Rogers, 2021). Gender expression, on the other hand, pertains to how individuals display their gender through their physical appearance or behavior (American Psychological Association, 2023). Gender nonconformity (GNC), also known as non-conforming gender expression, occurs when an individual's gender expression deviates from the socially accepted norms associated with their biological sex (Lowry, Johns, & Robin, 2020). It is important to note that gender expression represents the external presentation of one's gender and is distinct from gender identity, which refers to an individual's internal sense of their gender (Loso et al., 2023).

A recent cross-sectional study conducted in Shanghai reported that approximately 30% of Chinese adolescents exhibit moderate or high levels of GNC (Lian & Lou et al., 2022), indicating that the presence of this phenomenon among Chinese adolescents cannot be neglected. Previous evidence has shown that adolescents with GNC expressions usually experience more bullying, victimization, and childhood abuse than their gender-conforming peers (Brown & Stone, 2016; Feijóo & Rodríguez-Fernández, 2021). Moreover, these gender non-conforming adolescents are at an increased risk of developing mental health problems, including depressive and anxiety symptoms (Lin et al., 2021). According to the minority stress theory and the compensatory internet use theory (Kardefelt-Winther, 2014; Meyer, 2003), adolescents with GNC tend to adopt avoidant and inflexible coping styles, such as PSU and PIU, when faced with the aforementioned negative experiences and mental health issues (Brand, 2022; Elhai, Levine, & Hall, 2019).

Despite the growing evidence indicating that adolescents with GNC expressions are more likely to engage in PSU and PIU (Huang, Chang, Lu, & Yen, 2022; Lowry et al., 2018), there is limited research exploring the relationship between GNC and PSU/PIU among school-based Chinese adolescents (Huang et al., 2022). Additionally, previous studies examining these associations have not adequately accounted for important covariates, such as adolescents' depressive and anxiety symptoms, social support status, and school bullying experiences (Long et al., 2016). Furthermore, it remains unclear whether these findings hold true across different biological sexes within the population. Therefore, the present study examined the associations between both GNC and PSU and GNC and PIU among Chinese adolescents.

Methods

Participants and procedure

This cross-sectional study utilized data from the 2021 School-based Chinese Adolescents Health Survey (SCAHS), an ongoing survey of health-related behaviors among Chinese adolescents in grades 7 to 12. The detailed study design and sampling methods have been previously reported (Lai et al., 2023). In brief, a multi-stage, random cluster sampling approach was used to select participants. Initially, a convenience sample of 7 cities was selected with the assistance of local education bureaus. Subsequently, the number of junior, senior, and vocational high schools was randomly determined based on the proportion of different school types. In each selected school, two classes were randomly chosen from each grade, and all students in these classes were invited to participate in the study, except for those who suffered from severe mental or physical disorders as identified by the head teacher and/or health care physicians. The survey was conducted by trained investigators who were available to address any queries or confusion the participants might have had regarding the structured questionnaire. Participants completed the survey within a single session at school after being informed of the study's objectives and procedures. All participants were expected to independently complete the anonymous questionnaire within 45 min, and the investigators reviewed the completeness of the questionnaires before the participants left the site. Of the total 23,409 students from 504 classes in 84 public high schools (42 junior high schools, 28 senior high schools, and 14 vocational high schools) who were invited to participate, 23,054 completed and submitted the questionnaire, yielding a response rate of 98.5%. Among the included 23,054 adolescents (age range: 11–21 years; mean [SD] age: 14.9 [1.7] years), 51.0% were males.

Measures

PSU and PIU

PSU severity was assessed using the 10-item smartphone addiction scale-short version (SAS-SV) (Kwon, Kim, Cho, & Yang, 2013), and PIU severity was measured using Young's 20-item internet addiction test (IAT) (Young, 1998). SAS-SV and IAT are widely used instruments to assess PSU and PIU with good reliability and validity in the Chinese population (Guo et al., 2020; Luk et al., 2018). Further details are available in the Methods in the Supplementary material.

Gender nonconformity

To assess GNC or gender non-conforming gender expression, we employed a validated measure for gender expression that has been utilized in previous studies (Greytak, 2016; Wylie, Corliss, Boulanger, Prokop, & Austin, 2010), including research conducted among Chinese adolescents (Zhao et al., 2021). Participants were presented with the following statement and question: “A person's appearance, style, dress, or the way they walk or talk may affect how people describe them. How do you think people at school would describe you?” The response options were “very feminine,” “mostly feminine,” “somewhat feminine,” “equally feminine and masculine,” “somewhat masculine,” “mostly masculine,” and “very masculine.” By considering a student's response to this question and their biological sex, a 7-point GNC scale was established (Lowry et al., 2018). The scale ranged from 1, indicating very feminine female students and very masculine male students (representing the most gender conforming individuals), to 7, representing very masculine female students and very feminine male students (representing the most gender non-conforming individuals) (Table S2 in the Supplementary material). However, due to the limited number of mostly or very masculine female students, and the limited number of mostly or very feminine male students, we created a 3-level GNC variable based on previous studies (Lowry et al., 2018, 2020): (1) high GNC (somewhat, mostly, and very masculine female students and somewhat, mostly, and very feminine male students), (2) moderate GNC (equally feminine and masculine female and male students), and (3) low GNC (somewhat, mostly, and very feminine female students and somewhat, mostly, and very masculine male students).

Covariates

Several covariates were also measured, including demographic characteristics (sex, age, household socioeconomic status, family relationship, classmate relationship, teacher-classmate relationship, and academic performance), sexual orientation (heterosexual, lesbian/gay, bisexual, and unsure), depressive symptoms, anxiety symptoms, social support, and being bullied at school the students were attending. Further details on these covariables are available in the Methods and Table S1 in the Supplementary material.

Statistical analysis

Data were described as means (standard deviations, SDs) for continuous variables and as frequencies with percentages for categorical variables. Chi-square and analysis of variance tests were performed to test associations or differences among various GNC and PSU/PIU groups. Univariable mixed-effect linear regression models were employed to estimate the potential associations between GNC and PSU/PIU, with the school unit as the random-effect unit. Unstandardized regression coefficients with 95% confidence intervals (CIs) were reported. Additionally, three adjusted models were developed, each including a different set of covariates. Model 1 included age, sex, household socioeconomic status, family relationship, classmate relationship, teacher-classmate relationship, academic performance, and sexual orientation. Model 2 included the variables in Model 1 plus depressive symptoms scores and anxiety symptoms scores. Model 3 included the variables in Model 2 and additionally added social support and being bullied at school. Biological sex was also tested as an effect modifier in Models 1 through 3, using a product interaction term (biological sex × gender expression). Subgroup analyses were conducted by sex (males and females) to examine potential variations in different subgroups.

To test the robustness of the findings, two sensitivity analyses were also performed: (1) all analyses were repeated using imputed data sets generated through the multiple imputation method by chained equations to address missing data. Ten imputed data sets were created (Lin et al., 2022; Lu, 2017; Y. Zhang et al., 2021); (2) the regression analyses examining the associations between GNC and PSU/PIU were repeated using a binary GNC variable called gender conformity (GC) (GNC score: 1–3) and GNC (GNC score: 4–7) (Lian & Li et al., 2022).

All analyses were performed using Stata, version 17 (StataCrop), from December 2022 to January 2023. All statistical tests were two-sided, and a significance level of p ≤ 0.05 was considered statistically significant.

Ethics

The study procedures were carried out in accordance with the Declaration of Helsinki. This study received ethical approval from the Sun Yat-Sen University School of Public Health Institutional Review Board. Written informed consent explaining the study purposes, processes, benefits, and risks was obtained from each participant and one of their legal guardians.

Results

Characteristics of the study population

Table 1 presents the characteristics of the study population stratified by GNC, while Table S3 presents the characteristics stratified by PSU and PIU. Among all participants, 26.9% reported moderate GNC, while 5.3% reported high GNC. Additionally, 39.8% of students were identified as problematic smartphone users, 32.5% were categorized as internet at-risk users, and 652 (2.8%) were identified as problematic internet users. High GNC was found to be more prevalent among female students (6.0%) than male students (4.7%). Moreover, high GNC was more common among lesbian/gay students (25.3%), bisexual students (9.2%), and unsure students (6.4%) compared to heterosexual students (4.2%). High GNC was also more common among adolescents with PSU (6.4%) and those with PIU (problematic internet users: 12.4%; internet at-risk users: 6.8%) than their counterparts.

Table 1.

Characteristics of the study population among different gender expression groups

CharacteristicTotalGender Nonconformity, (N = 23,054)χ2/Fp valuee
LowaModeratebHighc
Total population, n (%)23,054 (100.0)15,618 (67.7)6,213 (26.9)1,223 (5.3)NA
Age, mean (SD)14.9 (1.7)14.9 (1.7)14.7 (1.7)14.6 (1.7)81.5<0.001
Sex, n (%)427.5
 Male11,761 (51.0)8,695 (73.9)2,519 (21.4)547 (4.7)<0.001
 Female11,293 (49.0)6,923 (61.3)3,694 (32.7)676 (6.0)
Household socioeconomic statusd, n (%)
 High7,305 (31.7)5,070 (69.4)1,848 (25.3)387 (5.3)47.1<0.001
 Middle13,718 (59.6)9,241 (67.4)3,803 (27.7)674 (4.9)
 Low1,990 (8.6)1,284 (64.5)548 (27.5)158 (7.9)
Family relationshipd, n (%)
 Good19,121 (83.1)13,328 (70.0)4,910 (25.7)883 (4.6)256.2<0.001
 Average3,053 (13.3)1,795 (58.8)1,022 (33.5)236 (7.7)
 Poor825 (3.6)462 (56.0)262 (31.8)101 (12.2)
Classmate relationshipd, n (%)
 Good18,351 (80.0)12,915 (70.4)4,577 (24.9)859 (4.7)348.8<0.001
 Average4,258 (18.6)2,482 (58.3)1,475 (34.6)301 (7.1)
 Poor335 (1.5)155 (46.3)125 (37.3)55 (16.4)
Teacher-classmate relationshipd, n (%)
 Good16,017 (70.0)11,233 (70.1)4,032 (25.2)752 (4.7)179.5<0.001
 Average6,528 (28.5)4,076 (62.4)2,039 (31.2)413 (6.3)
 Poor345 (1.5)206 (59.7)91 (26.4)48 (13.9)
Academic performanced, n (%)
 Above average8,707 (37.9)6,059 (69.6)2,230 (25.6)418 (4.8)54.5<0.001
 Average7,687 (33.4)5,225 (68.0)2,101 (27.3)361 (4.7)
 Below average6,590 (28.7)4,287 (65.1)1,864 (28.3)439 (6.7)
Sexual orientationd, n (%)
 Heterosexual16,091 (69.8)11,919 (74.1)3,495 (21.7)677 (4.2)1,091.9<0.001
 Lesbian/Gay379 (1.6)137 (36.1)146 (38.5)96 (25.3)
 Bisexual2,040 (8.8)1,011 (49.6)841 (41.2)188 (9.2)
 Unsure1,292 (5.6)687 (53.2)522 (40.4)83 (6.4)
Being bullied at schoold, n (%)
 No20,222 (87.8)13,912 (68.8)5,365 (26.5)945 (4.7)162.8<0.001
 Yes2,815 (12.2)1,693 (60.1)845 (30.0)277 (9.8)
Social support score, mean (SD)67.9 (15.0)69.1 (14.4)65.9 (15.6)62.8 (17.3)181.1<0.001
Depressive symptoms scored, mean (SD)15.2 (7.9)14.9 (7.5)15.6 (8.2)17.7 (9.6)84.2<0.001
Anxiety symptoms score, mean (SD)3.8 (4.4)3.5 (4.1)4.1 (4.6)5.3 (5.4)80.6<0.001
PSU, n (%)
 Non-PSU13,884 (60.2)9,510 (68.5)3,740 (26.9)634 (4.6)38.8<0.001
 PSU9,170 (39.8)6,108 (66.6)2,473 (27.0)589 (6.4)
PIU, n (%)
 Non-PIU14,908 (64.7)10,251 (68.8)4,022 (27.0)635 (4.3)139.0<0.001
 At-risk users7,494 (32.5)4,991 (66.6)1,996 (26.6)507 (6.8)
 PIU652 (2.8)376 (57.7)195 (30.0)81 (12.4)

Abbreviations: PSU, Problematic Smartphone Use; PIU, Problematic Internet Use; SAS-SV, Smartphone Addiction Scale Short Version; IAT, Internet Addiction Test.

a Female students who describe themselves as very/mostly/somewhat feminine; male students who describe themselves as very/mostly/somewhat masculine.

b Students who describe themselves as equally feminine and masculine.

c Female students who describe themselves as very/mostly/somewhat masculine; male students who describe themselves as very/mostly/somewhat feminine.

d Missing data: 41 for household socioeconomic status, 55 for family relationship, 110 for classmate relationship, 164 for teacher-classmate relationship, 70 for academic performance, 3,252 for sexual orientation (2,905 chose “unwilling to answer” and 347 chose “neither men nor women”), 17 for being bullied, 55 for depressive symptoms scores.

e p value was based on the Chi-square test for categorical variables and analysis of variance for continuous variables as appropriate.

Associations of GNC with PSU and PIU

The unadjusted mixed-effect linear regression models demonstrated that moderate and high GNC was associated with the severity of PSU (moderate GNC: Β = 0.71, 95% CI = 0.41–1.01; high GNC: Β = 2.84, 95% CI = 2.25–3.43) and PIU (moderate GNC: Β = 0.93, 95% CI = 0.54–1.32; high GNC: Β = 5.50, 95% CI = 4.73–6.28) (Table S4 in the Supplementary material). As shown in Table 2, after adjusting for covariates in Model 3, students with high GNC were more likely to have a higher level of PSU/PIU severity (PSU: Β = 1.11, 95% CI = 0.49–1.72; PIU: Β = 2.16, 95% CI = 1.40–2.93), compared with those with low GNC.

Table 2.

Associations of gender nonconformity with PSU and PIUa

PSUPIU
Β (95% CI)Β (95% CI)
Model 1Model2Model3Model 1Model2Model3
Gender nonconformity
 LowRefRefRefRefRefRef
 Moderate0.26 (−0.71, 0.59)0.11 (−0.21, 0.43)0.04 (−0.27, 0.36)0.20 (−0.24, 0.63)−0.07 (−0.41, 0.39)−0.16 (−0.55, 0.24)
 High1.82 (1.04, 2.32)b1.27 (0.65, 1.89)b1.11 (0.49, 1.72)b3.45 (2.61, 4.28)b2.46 (1.69, 3.23)b2.16 (1.40, 2.93)b
R20.100.180.190.100.260.27

Abbreviations: Β, unstandardized regression coefficient; 95% CI, 95% confidence interval; Ref, Reference; R2: coefficients of determination, R square.

a PSU was measured by the SAS-SV scores, ranging from 10 to 60, with higher scores indicating the severity of PSU; PIU was measured by the IAT scores, ranging from 20 to 100, with higher scores indicating the severity of PIU.

Model 1 adjusted for sex, age, household socioeconomic status, family relationship, classmate relationship, teacher-classmate relationship, academic performance, and sexual orientation.

Model 2 adjusted for the covariates in Model 1, plus depressive symptoms scores and anxiety symptoms scores.

Model 3 adjusted for the covariates in Model 2, plus social support scores and being bullied.

b p < 0.001.

Associations of GNC with PSU/PIU stratified by sex

The associations between interaction items (biological sex × gender expression) and PSU/PIU were found to be statistically significant (Table S5 in the Supplementary material). Therefore, separate sex-stratified analyses were conducted for male and female adolescents. Among male students, a significant association was observed between high GNC and PSU severity (Fig. 1). Male students with high GNC reported a significantly higher level of PSU (Β = 1.91, 95% CI = 0.97–2.86 in Model 3) than those with low GNC (Table 3). Table 4 demonstrated that the associations between high GNC and PIU were significant for both female students (Β = 2.03, 95% CI = 1.00–3.07 in Model 3) and male students (Β = 2.33, 95% CI = 1.19–3.50 in Model 3).

Fig. 1.
Fig. 1.

Sex and gender expression interaction with the severity of problematic smartphone use (PSU).

Note: The PSU severity was measured by the SAS-SV scale. Based on the mean value of SAS-SV scores in this population, the ordinate starts at 28. Highly gender conforming refers to male adolescents who reported very, mostly, and somewhat masculine or female adolescents who reported very, mostly, and somewhat feminine. Gender nonconforming refers to male adolescents who reported very, mostly, and somewhat feminine or female adolescents who reported very, mostly, and somewhat masculine. The mixed-effect linear regression model was adjusted for age, household socioeconomic status, family relationship, classmate relationship, teacher-classmate relationship, academic performance, and sexual orientation

Citation: Journal of Behavioral Addictions 12, 3; 10.1556/2006.2023.00040

Table 3.

Associations of gender nonconformity with PSUa stratified by sex

Male (n = 9,837)Female (n = 9,704)
Β (95% CI)Β (95% CI)
Model 1Model2Model3Model 1Model2Model3
Gender nonconformity
 LowRefRefRefRefRefRef
 Moderate0.75 (0.23, 1.26)b0.39 (−0.11, 0.89)0.32 (−0.18, 0.81)−0.17 (−0.60, 0.26)−0.15 (−0.56, 0.26)−0.21 (−0.62, 0.20)
 High2.81 (1.82, 3.80)c2.10 (1.15, 3.05)c1.91 (0.97, 2.86)c0.82 (−0.18, 1.67)0.41 (−0.40, 1.21)0.28 (−0.53, 1.09)
R20.100.170.180.100.190.19

Abbreviations: Β, unstandardized regression coefficient; 95% CI, 95% confidence interval; Ref, Reference; R2: coefficients of determination, R square.

a PSU was measured by the SAS-SV scores, ranging from 10 to 60, with higher scores indicating the severity of PSU.

Model 1 adjusted for age, household socioeconomic status, family relationship, classmate relationship, teacher-classmate relationship, academic performance, and sexual orientation.

Model 2 adjusted for the covariates in Model 1, plus depressive symptoms scores and anxiety symptoms scores.

Model 3 adjusted for the covariates in Model 2, plus social support scores and being bullied.

b p < 0.05.

c p < 0.001.

Table 4.

Associations of gender nonconformity with PIUa stratified by sex

Male (n = 9,837)Female (n = 9,704)
Β (95% CI)Β (95% CI)
Model 1Model2Model3Model 1Model2Model3
Gender nonconformity
 LowRefRefRefRefRefRef
 Moderate0.76 (0.10, 1.42)c0.18 (−0.42, 0.79)0.44 (−0.56, 0.64)−0.35 (−0.93, 0.22)−0.27 (−0.80, 0.25)0.41 (−0.94, 0.12)
 High3.88 (2.63, 5.13)b2.61 (1.45, 3.77)b2.33 (1.19, 3.50)b3.09 (1.97, 4.22)b2.33 (1.29, 3.37)b2.03 (1.00, 3.07)b
R20.100.250.270.110.260.27

Abbreviations: Β, unstandardized regression coefficient; 95% CI, 95% confidence interval; Ref, Reference; R2: coefficients of determination, R square.

a PIU was measured by the IAT scores, ranging from 20 to 100, with higher scores indicating the severity of PIU.

Model 1 adjusted for age, household socioeconomic status, family relationship, classmate relationship, teacher-classmate relationship, academic performance, and sexual orientation.

Model 2 adjusted for the covariates in Model 1, plus depressive symptoms scores and anxiety symptoms scores.

Model 3 adjusted for the covariates in Model 2, plus social support scores and being bullied.

b p < 0.001

c p < 0.05

Sensitivity analyses

The results from the imputed data analyses yielded similar findings, further supporting the positive association between high GNC and the severity of PSU and PIU (Table S6 in the Supplementary material). Additionally, significant associations were observed between the interaction items (biological sex × gender expression) and PSU/PIU (Table S7 in the Supplementary material). Furthermore, high GNC was associated with elevated PSU and PIU levels in both male and female students (Tables S8 and S9 in the Supplementary material). In the sensitivity analysis using the binary variable of GNC, the associations of GNC with PSU and PIU remained significant in Model 1 and Model 2, except when adjusting for social support scores and experiences of being bullied in Model 3, where the associations were no longer significant (Table S10 in the Supplementary material).

Discussion

This study represents one of the initial investigations into the associations between GNC and the severity of PSU/PIU in a sizable school-based sample of adolescent students in mainland China. Among the participants, 39.8% of adolescents reported experiencing PSU, while 35.3% reported being either internet at-risk users (32.5%) or problematic internet users (2.8%). These occurrence rates of PSU and PIU were consistent with a recent report on Chinese adolescents (M. X. Zhang, Chen, Tong, Yu, & Wu, 2021), but higher than the pooled rate (21.6%) from a meta-analysis covering adolescents from 64 countries (Meng et al., 2022). These findings indicate that excessive smartphone and internet use is a prevalent issue among Chinese adolescents, highlighting the need for effective interventions. Moreover, among the participants in this study, 26.9% of adolescents reported moderate levels of GNC, while 5.3% reported high levels. These findings are consistent with a recent study conducted in Shanghai, which suggested that 3 out of 10 adolescents experience moderate or high levels of GNC (Lian & Lou et al., 2022). These results highlight the importance of paying attention to GNC among Chinese adolescents. Furthermore, consistent with previous research (Becker, Ravens-Sieberer, Ottová-Jordan, & Schulte-Markwort, 2017; Kawabe, Horiuchi, Ochi, Oka, & Ueno, 2016; Méndez, Jorquera, & Ruiz-Esteban, 2020), the presence of GNC/PSU/PIU varied based on demographic characteristics (e.g., sex, age, household socioeconomic status, and academic performance), sexual orientation (heterosexual, lesbian/gay, bisexual, and unsure), depressive symptoms, anxiety symptoms, social support, and experiences of bullying at school. Therefore, it is important to consider these variables as covariates when examining the association between GNC and PSU/PIU. To the best of our knowledge, this study is the first to comprehensively explore the associations between GNC and PSU/PIU among school-based Chinese adolescents while considering a series of covariates.

Previous research has suggested that mental health problems, such as depressive symptoms and anxiety symptoms (Arrivillaga, Rey, & Extremera, 2022; Kósa et al., 2022; Ueno, Ito, Murai, & Fujiwara, 2020), as well as adverse social environments (e.g., low social support status and being bullied at school) (Gong et al., 2022; Liu, Liu, & Yuan, 2021; Vessey, Difazio, Neil, & Dorste, 2022), may contribute to the occurrence of PSU and PIU among adolescents. A recent study conducted among young sexual minorities demonstrated a positive association between GNC and PSU, even after adjusting for internalized sexual stigma and sexual orientation (Huang et al., 2022). Similarly, our study observed that, after accounting for covariates, moderate GNC did not show a significant association with PSU and PIU. However, high GNC was found to be independently and strongly associated with increased severity of PSU and PIU among general Chinese adolescents. These associations remained significant even after adjusting for covariates such as mental health status and social environment. It is worth noting that the association between high GNC and PIU was more pronounced compared to PSU. Furthermore, when considering covariates such as mental health status and social environment in the models, the unstandardized regression coefficient between GNC and PSU/PIU was slightly attenuated, suggesting that depressive symptoms, anxiety symptoms, low social support status, and experiences of being bullied may also contribute to the severity of PSU and PIU among Chinese adolescents. Moreover, it is also important to highlight that high GNC students with mental health problems or adverse social environments may also exhibit higher levels of PSU and PIU.

Several potential explanations can account for the observed association between high GNC and the severity of PSU and PIU among adolescents. Although all students may experience social and psychological stressors, high GNC adolescents face even greater challenges. First, high gender-nonconforming adolescents may encounter prejudice and stigma due to their gender presentation not aligning with socially expected gender norms, including physical appearance, clothing and accessories choice, and communication style (Hong & Garbarino, 2012; Reisner, Greytak, Parsons, & Ybarra, 2015). When subjected to gender-based bullying, they are more likely to turn to smartphones and the internet to seek online social support and escape from unfriendly social environments in reality. Consequently, smartphone and internet use may play a crucial role in their daily lives. On the one hand, the online world provides a relatively inclusive environment for gender expression diversity (Vessey et al., 2022). Adolescents may seek acceptance and recognition for their gender expression, as well as form new friendships or engage in social interactions with strangers. On the other hand, smartphones and internet activities can provide them with pleasurable experiences, which help them escape negative moods they may face in the real world (Meng et al., 2020). The observed stronger association with PIU may be attributed to the higher occurrence rate of PIU among the gender-nonconforming participants. These findings highlight that gender-nonconforming students may experience elevated levels of stress related to GNC, leading them to PSU/PIU as a coping strategy, similar to how increased PSU/PIU among sexual minority youths may occur as a coping mechanism in response to social and minority stress (Huang et al., 2022).

Additionally, as previous research suggests (Huang et al., 2022), while there were some similarities in the associations between GNC and PSU/PIU among female and male students, there are also differences. This study found that GNC was not significantly associated with PSU among female students, while high GNC was positively associated with severe PSU among male students. These results may be related to the fact that gender-nonconforming male students may experience more severe minority stressors than gender-nonconforming female students. In Chinese culture, masculine gender role expectations and the stigma towards feminine males are deeply embedded (Wang, Yu, Yang, Drescher, & Chen, 2020), resulting in greater societal tolerance towards girls behaving in a “boyish” manner compared to boys behaving in a “girly” manner (Zucker, 2019). These findings suggest that gender-nonconforming male students may face more social stress and may be more likely to turn to digital technologies as a compensatory coping behavior for the relief of their real-life stress compared with gender-nonconforming female students (Lowry et al., 2018). Further research is needed to better understand the links between gender norms, biological sex, social stressors, and PSU/PIU across the spectrum of gender conformity.

Some limitations of our study should be acknowledged. First, due to the nature of the cross-sectional design, we cannot establish a definite causal relationship between GNC and PSU/PIU among Chinese adolescents. Therefore, further longitudinal studies are needed to explore this issue. Second, our study sample was limited to middle and high school students, so our findings cannot be generalized to other populations, such as young adults in university. Third, since we collected data from schools, gender-nonconforming adolescents not attending school were not included in this study. These individuals may have more severe issues with problematic digital use than the school-based sample. Fourth, self-report questionnaires were used to collect data, which may have resulted in ambiguity in interpreting the gender expression questions, and reporting of PSU and PIU behaviors could be influenced by peer pressure, leading to information bias. Future studies should consider using digital trace data to capture smartphone and internet usage patterns more accurately. Fifth, although participants with high GNC scores might be the transgender population, there were no transgender individuals in our study sample of Chinese adolescents.

Conclusions

In summary, our study found a significant association between GNC and the severity of PSU and PIU among Chinese adolescents in school settings. Moreover, our results revealed that high levels of GNC were associated with more severe PSU/PIU, particularly among male students. Accordingly, our findings highlight the need to pay greater attention to GNC in schools and promote educational initiatives that support gender expression diversity. To foster a nondiscriminatory and inclusive school environment, addressing the vulnerabilities of gender-nonconforming adolescents, particularly male students who are more likely to exhibit higher levels of PSU, is essential. As such, school psychologists and specialized support services should play a vital role in facilitating real-life interactions among gender-nonconforming students, their families, classmates, and teachers, thereby effectively preventing PSU and PIU in this vulnerable population.

Funding sources

This research was supported by a grant from the Natural Science Foundation of China Natural Science Foundation of Guangdong Province (Dr. Guo, 2022A1515012333) and the Science and Technology Planning Project of Guangzhou (Dr. Guo, 202102020136).

Authors’ contribution

LG contributed to the conception and design of the work. XYZ, YWY, and LG performed the analysis. All authors contributed to the interpretation of data. WQJ, YTH, CHH, YLH, and CYL accessed and verified the underlying data reported. XYZ and YWY wrote the initial draft of the manuscript. All authors critically revised the manuscript. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Conflict of interest

We declare no competing interests.

Acknowledgment

We appreciate all participants and schools who participated in the School-based Chinese Adolescents Health Survey.

Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1556/2006.2023.00040.

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Supplementary Materials

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    • Search Google Scholar
    • Export Citation
  • Becker, I., Ravens-Sieberer, U., Ottová-Jordan, V., & Schulte-Markwort, M. (2017). Prevalence of adolescent gender experiences and gender expression in Germany [Journal Article]. Journal of Adolescent Health, 61(1), 8390. http://doi.org/10.1016/j.jadohealth.2017.02.001.

    • Search Google Scholar
    • Export Citation
  • Bewley, S., McCartney, M., Meads, C., & Rogers, A. (2021). Sex, gender, and medical data [Editorial]. Bmj-British Medical Journal, 372, n735. http://doi.org/10.1136/bmj.n735.

    • Search Google Scholar
    • Export Citation
  • Brand, M. (2022). Can internet use become addictive? [Journal Article]. Science, 376(6595), 798799. http://doi.org/10.1126/science.abn4189.

    • Search Google Scholar
    • Export Citation
  • Brown, C. S., & Stone, E. A. (2016). Gender stereotypes and discrimination: How sexism impacts development [Journal Article; Review]. Advances in Child Development and Behavior, 50, 105133. http://doi.org/10.1016/bs.acdb.2015.11.001.

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    • Export Citation
  • China Internet Network Information Center. (2022, 2022-12-1). The 2021 national underage internet use research report. Retreved 2023.6.18 from https://www.cnnic.net.cn/6/86/116/index.html.

    • Search Google Scholar
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  • Christakis, D. A. (2019). The challenges of defining and studying “digital addiction” in children [Journal Article]. Jama-Journal of the American Medical Association, 321(23), 22772278. http://doi.org/10.1001/jama.2019.4690.

    • Search Google Scholar
    • Export Citation
  • van den Eijnden, R., Koning, I., Doornwaard, S., van Gurp, F., & Ter Bogt, T. (2018). The impact of heavy and disordered use of games and social media on adolescents’ psychological, social, and school functioning [Journal Article]. Journal of Behavioral Addictions, 7(3), 697706. http://doi.org/10.1556/2006.7.2018.65.

    • Search Google Scholar
    • Export Citation
  • Elhai, J. D., Levine, J. C., & Hall, B. J. (2019). The relationship between anxiety symptom severity and problematic smartphone use: A review of the literature and conceptual frameworks [Journal Article; Systematic Review]. Journal of Anxiety Disorders, 62, 4552. http://doi.org/10.1016/j.janxdis.2018.11.005.

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  • Feijóo, S., & Rodríguez-Fernández, R. (2021). A meta-analytical review of gender-based school bullying in Spain [Introductory Journal Article; Journal Article; Meta-Analysis; Review]. International Journal of Environmental Research and Public Health, 18(23) http://doi.org/10.3390/ijerph182312687.

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  • Lian, Q., Lou, C., Zhong, X., Zhang, J., Tu, X., Fang, Y., … Zuo, X. (2022). Nonconforming gender expression and insufficient sleep among adolescents during COVID-19 school closure and after school reopening [Journal Article; Research Support, Non-U.S. Gov’t]. Bmc Public Health, 22(1), 2037. http://doi.org/10.1186/s12889-022-14463-4.

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The author instruction is available in PDF.
Please, download the file from HERE

Dr. Zsolt Demetrovics
Institute of Psychology, ELTE Eötvös Loránd University
Address: Izabella u. 46. H-1064 Budapest, Hungary
Phone: +36-1-461-2681
E-mail: jba@ppk.elte.hu

Indexing and Abstracting Services:

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  • Journal Citation Reports/Science Edition
  • Social Sciences Citation Index®
  • Journal Citation Reports/ Social Sciences Edition
  • Current Contents®/Social and Behavioral Sciences
  • EBSCO
  • GoogleScholar
  • PsycINFO
  • PubMed Central
  • SCOPUS
  • Medline
  • CABI
  • CABELLS Journalytics

2022  
Web of Science  
Total Cites
WoS
5713
Journal Impact Factor 7.8
Rank by Impact Factor

Psychiatry (SCIE) 18/155
Psychiatry (SSCI) 13/144

Impact Factor
without
Journal Self Cites
7.2
5 Year
Impact Factor
8.9
Journal Citation Indicator 1.42
Rank by Journal Citation Indicator

Psychiatry 35/264

Scimago  
Scimago
H-index
69
Scimago
Journal Rank
1.918
Scimago Quartile Score Clinical Psychology Q1
Medicine (miscellaneous) Q1
Psychiatry and Mental Health Q1
Scopus  
Scopus
Cite Score
11.1
Scopus
Cite Score Rank
Clinical Psychology 10/292 (96th PCTL)
Psychiatry and Mental Health 30/531 (94th PCTL)
Medicine (miscellaneous) 25/309 (92th PCTL)
Scopus
SNIP
1.966

 

 
2021  
Web of Science  
Total Cites
WoS
5223
Journal Impact Factor 7,772
Rank by Impact Factor Psychiatry SCIE 26/155
Psychiatry SSCI 19/142
Impact Factor
without
Journal Self Cites
7,130
5 Year
Impact Factor
9,026
Journal Citation Indicator 1,39
Rank by Journal Citation Indicator

Psychiatry 34/257

Scimago  
Scimago
H-index
56
Scimago
Journal Rank
1,951
Scimago Quartile Score Clinical Psychology (Q1)
Medicine (miscellaneous) (Q1)
Psychiatry and Mental Health (Q1)
Scopus  
Scopus
Cite Score
11,5
Scopus
CIte Score Rank
Clinical Psychology 5/292 (D1)
Psychiatry and Mental Health 20/529 (D1)
Medicine (miscellaneous) 17/276 (D1)
Scopus
SNIP
2,184

2020  
Total Cites 4024
WoS
Journal
Impact Factor
6,756
Rank by Psychiatry (SSCI) 12/143 (Q1)
Impact Factor Psychiatry 19/156 (Q1)
Impact Factor 6,052
without
Journal Self Cites
5 Year 8,735
Impact Factor
Journal  1,48
Citation Indicator  
Rank by Journal  Psychiatry 24/250 (Q1)
Citation Indicator   
Citable 86
Items
Total 74
Articles
Total 12
Reviews
Scimago 47
H-index
Scimago 2,265
Journal Rank
Scimago Clinical Psychology Q1
Quartile Score Psychiatry and Mental Health Q1
  Medicine (miscellaneous) Q1
Scopus 3593/367=9,8
Scite Score  
Scopus Clinical Psychology 7/283 (Q1)
Scite Score Rank Psychiatry and Mental Health 22/502 (Q1)
Scopus 2,026
SNIP  
Days from  38
submission  
to 1st decision  
Days from  37
acceptance  
to publication  
Acceptance 31%
Rate  

2019  
Total Cites
WoS
2 184
Impact Factor 5,143
Impact Factor
without
Journal Self Cites
4,346
5 Year
Impact Factor
5,758
Immediacy
Index
0,587
Citable
Items
75
Total
Articles
67
Total
Reviews
8
Cited
Half-Life
3,3
Citing
Half-Life
6,8
Eigenfactor
Score
0,00597
Article Influence
Score
1,447
% Articles
in
Citable Items
89,33
Normalized
Eigenfactor
0,7294
Average
IF
Percentile
87,923
Scimago
H-index
37
Scimago
Journal Rank
1,767
Scopus
Scite Score
2540/376=6,8
Scopus
Scite Score Rank
Cllinical Psychology 16/275 (Q1)
Medicine (miscellenous) 31/219 (Q1)
Psychiatry and Mental Health 47/506 (Q1)
Scopus
SNIP
1,441
Acceptance
Rate
32%

 

Journal of Behavioral Addictions
Publication Model Gold Open Access
Submission Fee none
Article Processing Charge 990 EUR/article for articles submitted after 30 April 2023 (850 EUR for articles submitted prior to this date)
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%.
Subscription Information Gold Open Access

Journal of Behavioral Addictions
Language English
Size A4
Year of
Foundation
2011
Volumes
per Year
1
Issues
per Year
4
Founder Eötvös Loránd Tudományegyetem
Founder's
Address
H-1053 Budapest, Hungary Egyetem tér 1-3.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2062-5871 (Print)
ISSN 2063-5303 (Online)

Senior editors

Editor(s)-in-Chief: Zsolt DEMETROVICS

Assistant Editor(s): Csilla ÁGOSTON

Associate Editors

  • Stephanie ANTONS (Universitat Duisburg-Essen, Germany)
  • Joel BILLIEUX (University of Lausanne, Switzerland)
  • Beáta BŐTHE (University of Montreal, Canada)
  • Matthias BRAND (University of Duisburg-Essen, Germany)
  • Ruth J. van HOLST (Amsterdam UMC, The Netherlands)
  • Daniel KING (Flinders University, Australia)
  • Gyöngyi KÖKÖNYEI (ELTE Eötvös Loránd University, Hungary)
  • Ludwig KRAUS (IFT Institute for Therapy Research, Germany)
  • Marc N. POTENZA (Yale University, USA)
  • Hans-Jurgen RUMPF (University of Lübeck, Germany)

Editorial Board

  • Max W. ABBOTT (Auckland University of Technology, New Zealand)
  • Elias N. ABOUJAOUDE (Stanford University School of Medicine, USA)
  • Hojjat ADELI (Ohio State University, USA)
  • Alex BALDACCHINO (University of Dundee, United Kingdom)
  • Alex BLASZCZYNSKI (University of Sidney, Australia)
  • Judit BALÁZS (ELTE Eötvös Loránd University, Hungary)
  • Kenneth BLUM (University of Florida, USA)
  • Henrietta BOWDEN-JONES (Imperial College, United Kingdom)
  • Wim VAN DEN BRINK (University of Amsterdam, The Netherlands)
  • Gerhard BÜHRINGER (Technische Universität Dresden, Germany)
  • Sam-Wook CHOI (Eulji University, Republic of Korea)
  • Damiaan DENYS (University of Amsterdam, The Netherlands)
  • Jeffrey L. DEREVENSKY (McGill University, Canada)
  • Naomi FINEBERG (University of Hertfordshire, United Kingdom)
  • Marie GRALL-BRONNEC (University Hospital of Nantes, France)
  • Jon E. GRANT (University of Minnesota, USA)
  • Mark GRIFFITHS (Nottingham Trent University, United Kingdom)
  • Anneke GOUDRIAAN (University of Amsterdam, The Netherlands)
  • Heather HAUSENBLAS (Jacksonville University, USA)
  • Tobias HAYER (University of Bremen, Germany)
  • Susumu HIGUCHI (National Hospital Organization Kurihama Medical and Addiction Center, Japan)
  • David HODGINS (University of Calgary, Canada)
  • Eric HOLLANDER (Albert Einstein College of Medicine, USA)
  • Jaeseung JEONG (Korea Advanced Institute of Science and Technology, Republic of Korea)
  • Yasser KHAZAAL (Geneva University Hospital, Switzerland)
  • Orsolya KIRÁLY (Eötvös Loránd University, Hungary)
  • Emmanuel KUNTSCHE (La Trobe University, Australia)
  • Hae Kook LEE (The Catholic University of Korea, Republic of Korea)
  • Michel LEJOXEUX (Paris University, France)
  • Anikó MARÁZ (Humboldt-Universität zu Berlin, Germany)
  • Giovanni MARTINOTTI (‘Gabriele d’Annunzio’ University of Chieti-Pescara, Italy)
  • Astrid MÜLLER  (Hannover Medical School, Germany)
  • Frederick GERARD MOELLER (University of Texas, USA)
  • Daniel Thor OLASON (University of Iceland, Iceland)
  • Nancy PETRY (University of Connecticut, USA)
  • Bettina PIKÓ (University of Szeged, Hungary)
  • Afarin RAHIMI-MOVAGHAR (Teheran University of Medical Sciences, Iran)
  • József RÁCZ (Hungarian Academy of Sciences, Hungary)
  • Rory C. REID (University of California Los Angeles, USA)
  • Marcantanio M. SPADA (London South Bank University, United Kingdom)
  • Daniel SPRITZER (Study Group on Technological Addictions, Brazil)
  • Dan J. STEIN (University of Cape Town, South Africa)
  • Sherry H. STEWART (Dalhousie University, Canada)
  • Attila SZABÓ (Eötvös Loránd University, Hungary)
  • Ferenc TÚRY (Semmelweis University, Hungary)
  • Alfred UHL (Austrian Federal Health Institute, Austria)
  • Róbert URBÁN  (ELTE Eötvös Loránd University, Hungary)
  • Johan VANDERLINDEN (University Psychiatric Center K.U.Leuven, Belgium)
  • Alexander E. VOISKOUNSKY (Moscow State University, Russia)
  • Aviv M. WEINSTEIN  (Ariel University, Israel)
  • Kimberly YOUNG (Center for Internet Addiction, USA)

 

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