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  • 1 Nottingham Centre for Transgender Health, Nottingham, UK
  • | 2 Institute of Mental Health, Faculty of Medicine & Health Sciences, University of Nottingham, Nottingham, UK
  • | 3 School of Sport, Exercise, and Health Sciences, Loughborough University, Loughborough, UK
  • | 4 Department of Psychiatry, University Hospital of Bellvitge-IDIBELL, Barcelona, Spain
  • | 5 International Gaming Research Unit, Psychology Division, Nottingham Trent University, Nottingham, UK
Open access

Background

There is anecdotal clinical evidence that transgender people use the online world – such as forums and online video gaming – for the purpose of experiencing their gender identity in a safe, non-threatening, non-alienating, non-stigmatizing, and non-critical environment.

Aims

To describe gaming behavior, degree of problematic gaming behavior and associated factors with problematic gaming in a comparatively large group of transgender people accessing transgender health services.

Methods

Every individual referred to a national transgender health service in the United Kingdom during a 12-month period was invited to complete a series of questionnaires to measure gaming behavior, interpersonal functioning, severity of autistic features, and anxiety and depressive symptoms.

Results

A total of 245 people agreed to participate in the study with 154 (62.9%) describing themselves as current gamers. Gaming behavior in the transgender population attending transgender health services was prevalent, but less than 1% of them presented with clinical scores for Internet Gaming Disorder, with no differences according to gender. Problematic gaming behavior was associated with general interpersonal problems, depression, and young age.

Discussion and conclusions

Transgender people who engage in problematic gaming behavior are younger, and present with high interpersonal problems, and depression, which can affect a successful transition. In view of the high levels of gaming activity in this population games that are designed to address these psychological problems may be well received by transgender people.

Abstract

Background

There is anecdotal clinical evidence that transgender people use the online world – such as forums and online video gaming – for the purpose of experiencing their gender identity in a safe, non-threatening, non-alienating, non-stigmatizing, and non-critical environment.

Aims

To describe gaming behavior, degree of problematic gaming behavior and associated factors with problematic gaming in a comparatively large group of transgender people accessing transgender health services.

Methods

Every individual referred to a national transgender health service in the United Kingdom during a 12-month period was invited to complete a series of questionnaires to measure gaming behavior, interpersonal functioning, severity of autistic features, and anxiety and depressive symptoms.

Results

A total of 245 people agreed to participate in the study with 154 (62.9%) describing themselves as current gamers. Gaming behavior in the transgender population attending transgender health services was prevalent, but less than 1% of them presented with clinical scores for Internet Gaming Disorder, with no differences according to gender. Problematic gaming behavior was associated with general interpersonal problems, depression, and young age.

Discussion and conclusions

Transgender people who engage in problematic gaming behavior are younger, and present with high interpersonal problems, and depression, which can affect a successful transition. In view of the high levels of gaming activity in this population games that are designed to address these psychological problems may be well received by transgender people.

Introduction

Transgender people are individuals whose gender identity does not match the gender assigned at birth based on their sexual characteristics. Transgender women are those assigned male at birth but whose gender identity is female; and transgender men are those assigned female at birth with a male gender identity (Ahmad et al., 2013). Some transgender people may decide not to transition to their experienced gender, and others choose to transition socially without the need of gender confirming medical interventions (GCMI) [cross-sex hormones (CSH) and/or genital surgeries] (Beek, Kreukels, Cohen-Kettenis, & Steensma, 2015). However, many access transgender health services in order to access GCMI (Bockting, Coleman, & De Cuypere, 2011). Although previous epidemiological studies examining the numbers of transgender people accessing transgender health services suggest low prevalence rates (Arcelus et al., 2015), reality is rather different. Transgender health services around the world (in places where they are available) have shown an increase rate of demand (De Vries, Kreukels, T’Sjoen, Ålgars, & Mattila, 2015), which may be a reflection of the high number of people with a self-identified transgender identity (Van Caenegem et al., 2015).

When people do wish GCMI, many (but not all) transgender health services require their patients to socially transition before such potentially irreversible interventions are considered. For many transgender people, living as their experienced gender without the aid of GCMI, can be a challenge. However, it is the view of many clinicians working in the field – including some of whom are transgender themselves – that living as their experienced gender allows individuals to test their gender identity in the real world before the initiation of potentially irreversible treatments (Wylie et al., 2014). Real life experience of gender identity might include considerable social and interpersonal challenges (e.g., Budge, 2013), such as disclosing one’s gender identity to others (Gagne, Tewksbury, & McGaughey, 1997; Wylie et al., 2014); facing rejection (Koken, Bimbi, & Parsons, 2009); managing social gender role transition (Budge, 2013; Rowniak & Chesla, 2013) including the occupational and personal arenas; and coping with discrimination and stigma (Adams, Nagoshi, Filip-Crawford, Terrell, & Nagoshi, 2016; Clements-Nolle, Marx, & Katz, 2006). As a consequence, transgender people who have poor social and interpersonal skills may be more likely to encounter difficulties when socially transitioning.

Cross-sectional studies investigating mental health problems of people attending transgender health services have found high rates of depression and anxiety in this population (Bouman, Claes, Marshall, et al., 2016; Dhejne, Van Vlerken, Heylens, & Arcelus, 2016; Millet, Longworth, & Arcelus, 2016). Research has provided evidence that psychopathology in transgender people is predicted by interpersonal skills (Arcelus, Claes, Witcomb, Marshall, & Bouman, 2016). High levels of anxiety, low mood and poor interpersonal skills may hinder social gender role transition, and as a consequence some individuals may hide themselves from the real world (Jones, Arcelus, Bouman, & Haycraft, 2017), and only explore their gender identity in online environments.

There is anecdotal clinical evidence that transgender people use the online world – such as forums and online video gaming – for the purpose of experiencing their gender identity in a safe, non-threatening, non-alienating, non-stigmatizing, and non-critical environment (Griffiths, Bouman, & Arcelus, 2016). The online world (including online gaming) may be used by transgender individuals as a preliminary, complementary, and/or alternative medium for helping them to negotiate their gendered status. Such online games and forums may typically involve creating an avatar that aligns with the gender they are experiencing. This could be so for transgender men and women in the same way as both may benefit from experiencing their gender in a safe environment. Although video gaming activities may be useful for transgender people to express their gender, it may also encourage isolation and a minimum contact with the outside world. Particularly, people with social difficulties or those with some level of depression may be presenting with high levels of gaming behavior.

Case studies exploring gaming activity in the transgender population have found that the use of video gaming among this population is not unusual (Griffiths et al., 2016). However, to date no empirical study has explored the degree of gaming behavior in the transgender population or the social and interpersonal factors associated with gaming behavior. If the psychosocial characteristics of transgender people who engage in gaming can be established, perhaps gaming can be used therapeutically to address psychosocial vulnerabilities (i.e., social and interpersonal difficulties) and facilitate the person through their social transition if the person is having difficult negotiating this in the real world.

In cisgender populations, online gaming has been found to be an alternative way of coping with distress, as it provides psychological benefits such as measured goal attainment, community connection, and a sense of escapism (Granic, Lobel, & Engels, 2014). Gaming also has the potential to increase physical and psychological wellbeing (Griffiths, Kuss, & Ortiz de Gortari, 2013). Gaming has already been successfully used to tackle anxiety and improve socialization (Rothbaum, Hodges, Smith, Lee, & Price, 2000; Wilkinson, Ang, & Goh, 2008), including in people on the autistic spectrum (Charlop-Christy, Le, & Freeman, 2000). In light of these benefits, gaming could also be particularly beneficial in the transgender population.

In summary, there is good clinical evidence of high levels of gaming behavior in transgender people attending gender services, which has not been reported in the literature, apart from a case series study. As gaming can help people deal with psychopathology, in view of the high levels of psychopathology among this population, gaming can also be used for transgender people. However, the levels of gaming activity need to be explored first in order to evaluate whether this method is feasible to be used among this population. In view of this, the aims of the present study were exploratory. The first aim is to describe gaming behavior and levels of problematic gaming behavior in a comparatively large group of transgender people accessing transgender health services. Among this self-selected group of transgender people, the second aim was to examine the characteristics that are associated with problematic gaming behavior. In view of the high levels of anxiety and depression levels reported in this particular population (Dhejne et al., 2016), the high numbers of people on the autistic spectrum who also have transgender identities (Glidden, Bouman, Jones, & Arcelus, 2016), and the high levels of interpersonal problems already found in these populations (Davey, Bouman, Meyer, & Arcelus, 2015), the present study explored whether these four factors were associated with the degree of gaming activity found among transgender gamers.

Methods

Participants and procedure

Every individual referred to a national transgender health service in the United Kingdom and accepted for assessment during a 12-month period (from June 2015 to June 2016), was invited to participate in the study. Individuals referred to the service are offered assessment, and possibly GCMI (e.g., CSH, and a referral for chest reconstructive surgery, and gender confirming genital surgery) if required. In order for an individual to be accepted for treatment, they need to socially transition first, which includes not only living as their experienced gender but also changing their name and most legal documents. Prior to the clinical assessment at the service, patients were invited to participate in the study. If they agreed, they completed a series of self-report psychometric measurements (detailed below) and signed a consent form.

Materials

Sociodemographics characteristics

Questions were asked relating to age, birth assigned gender, gender description (male; female; non-male or female; male and female; other; and not sure), and information about social transitional status (socially transitioned – yes or no). All sociodemographic information, including social gender role transition status, was self-reported. No evidence (e.g., legal documents) of social transition was collected at this stage.

Information about gaming behavior

Participants were asked to self-report information about whether or not they engage in gaming behaviors (yes or no) and whether they have engaged in gaming behavior in the past (yes or no). This information was used to categorize the participants as “current gamers” or as “non-gamers.” For the purpose of this study, people who indicated they had previously engaged in gaming behavior were categorized as non-gamers.

Internet Gaming Disorder Scale – Short-Form (IGDS9-SF) (Pontes & Griffiths, 2015)

The IGDS9-SF is a short psychometric tool adapted from the DSM-5 criteria for Internet Gaming Disorder (American Psychiatric Association, 2013). The aim of the instrument is to assess the degree of problematic gaming behavior. It has nine questions that are answered using a 5-point Likert scale: 1 (“Never”), 2 (“Rarely”), 3 (“Sometimes”), 4 (“Often”), and 5 (“Very Often”). The scores are obtained by summing the gamer’s answers and total scores can range from 9 to 45, with higher scores being indicative of higher degrees of gaming disorder. Although it is not diagnostic for the purposes of this research, it may be possible to classify disordered gamers as those gamers that obtain a minimum of 36 out of 45 points (Pontes & Griffiths, 2015). The measure has excellent validity and reliability (Pontes & Griffiths, 2015) and has previously been used (e.g., Kim et al., 2016). The Cronbach’s α for the IGDS9-SF in the present study was 0.92.

Inventory of Interpersonal Problems (IIP-32; Barkham, Hardy, & Startup, 1996)

The IIP-32 assesses common interpersonal problems, across eight subscales: hard to be assertive; hard to be sociable; hard to be supportive; hard to be involved; too dependent; too caring; too aggressive; and too open. The subscales are grouped into four: problems with competition; problems with socializing; problems with nurturance; and problems with independence. A global score provides an indication of overall interpersonal problems and higher scores indicate greater interpersonal problems. The IIP-32 is a shortened version of the original IIP, yet the psychometric properties are retained. A confirmatory factor analysis demonstrated high reliability with α coefficients of 0.70–0.88 (Barkham et al., 1996). The IIP-32 has been used successfully in both non-clinical (e.g., Berry, Wearden, Barrowclough, & Liversidge, 2006) and clinical samples (e.g., Arcelus et al., 2009; Paley et al., 2008), including a transgender population (Davey et al., 2015). For the present study, the problem with socializing scale (which can provide negative values) and the global IIP-32 were used. In the present study, the Cronbach’s α for the global IIP-32 was 0.90, and for the scales measuring problems socializing it was 0.82.

Hospital Anxiety and Depression Scale (HADS) (Zigmond & Snaith, 1983)

The HADS is a commonly used instrument to assess levels of anxiety and depression. It has 14 items and generates an overall score for depression and for anxiety separately. Seven of the items relate to anxiety and seven relate to depression. The HADS has been used in clinical studies, including several with transgender people (e.g., Bouman, Claes, Brewin, et al., 2016; Dhejne et al., 2016). It has shown to have good test–retest and inter-rater reliability (Zigmond & Snaith, 1983). For the present study, both the anxiety and depression subscales were used. The Cronbach’s α for the HADS-anxiety in the present study was 0.85 and 0.76 for HADS-depression.

Autistic Spectrum Quotient 28 (AQ-28) (Hoekstra, Bartels, Cath, & Boosman, 2008)

The AQ-28 is a 28-item instrument that was developed from the AQ-50 (Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001). The AQ is a valuable instrument for rapidly quantifying where any given individual is situated on the continuum from autism to normality. The higher the score the more autistic characteristics the individual presents with. Both the AQ-50 and AQ-28 have shown good test–retest and inter-rater reliability (Baron-Cohen et al., 2001; Hoekstra et al., 2008). For the present study, the total scores of the AQ-28 were used. The Cronbach’s α for the AQ-28 in the present study was 0.87.

Analyses

All gaming questionnaire data were positively skewed in both groups and non-normally distributed, as demonstrated by significant (p < .002) Kolmogorov–Smirnov tests and Shapiro–Wilk tests. Similarly, the rest of the data were mostly non-normally distributed but negatively skewed in both groups (gamers and non-gamers). Therefore, non-parametric tests were selected where possible and regression analyses were interpreted with caution, as there are no non-parametric equivalents available. For the first aim of the study, descriptive data are presented as well as mean scores of the individual psychometric instruments. For comparison between groups, Mann–Whitney U tests and Chi-square tests were conducted. For the second aim of the study, a series of one-tailed Spearman’s rho correlations were performed. The function of this preliminary analysis was to identify which predictor variables significantly correlated with problematic gaming behavior and to subsequently only include these variables in a multiple linear regression model to increase its robustness. The enter method was used. According to Cohen (1992) between 91 and 126 participants are required to meet a power of 0.80 (for a medium effect size, with an α of 0.05 or 0.01) for a five-factor regression model. Statistical significance (α) was set at p < .05. All data analyses were performed using SPSS 22 (IBM Corporation, 2013).

Ethics

The study received ethical approval from the NHS Ethics committee and from the Research and Development Department of the Nottinghamshire Healthcare NHS Foundation Trust in line with Health Research Authority guidance (HRA, 2013).

Results

Descriptive data

During the period of the study, 257 people were accepted for the assessment at the center. Of these, 245 (95.3%) people agreed to participate in the study. One hundred and forty-five individuals self-identified as assigned male gender at birth (59.2%) and 99 as assigned female gender at birth (40.4%). One person did not identify their birth assigned gender. Regarding gender identity, the majority of participants self-identified as being in the binary of male and female. People, who identified as “non-male or female” and those identified as “male and female” were grouped into one category (non-binary) in Table 1. The mean age of the total group was 27.34 years (SD = 12.48). Out of the 245 participants, 154 (62.9%) described themselves as currently using video games (categorized as gamers), and 40 (37.1%) as using video games in the past, but not any longer (categorized as non-gamers for the purposes of the present study). The remaining participants did not, and had never played video games at all (categorized as non-gamers). In the group categorized as gamers, on average participants would play 9.42 times a week, 1.77 times a day and spent an average of 2.80 hr playing on each occasion.

Table 1.

Sociodemographic characteristics, psychopathology related to social problems, gaming activity, and information regarding transition for the whole sample, current gamers, and non-current gamers (N = 245)

TotalCurrent players (n = 154)Non-current players (n = 91)Mann–Whitney UChi-square
zrpχ2dfPhip
Birth assigned gender: N (%)Female: 99 (40.4)Female: 69 (44.8)Female: 30 (33.1)3.101−0.11.08
Male: 145 (59.2)Male: 85 (55.2)Male: 60 (65.9)
Mean age (SD)27.41 (12.4)24.21 (9.9)32.63 (14.4)−5.14−.33.001**
Civil status: N (%)Single: 150 (61.2)Single: 107 (69.5)Single: 43 (47.3)16.1730.26.01**
Married: 56 (22.9)Married: 33 (21.4)Married: 23 (25.3)
Divorced: 12 (4.9)Divorced: 2 (1.3)Divorced: 10 (11.0)
Other: 14 (5.7)Other: 8 (5.2)Other: 6 (6.6)
Self-description: N (%)Man: 86 (35.1)Man: 55 (35.1)Man: 31 (34.9)0.8430.06.84
Woman: 122 (44.8)Woman: 72 (46.8)Woman: 50 (54.9)
Non-binary: 18 (7.3)Non-binary: 12 (7.8)Non-binary: 6 (6.6)
Not sure: 9 (3.7)Not sure: 6 (3.9)Not sure: 3 (3.3)
Socially transitioned: N (%)Yes: 115 (46.9)Yes: 63 (40.99)Yes: 52 (57.1)6.051−0.16.01**
No: 130 (53.1)No: 91 (59.1)No: 39 (42.9)
Occasions playing each day1.77 (0.99)
Occasions playing each week9.42 (7.39)
Amount of time that each session last (hr)2.80 (1.48)
Preferred way to playComputers: 77 (50%)
Game console: 66 (42.9%)
Smart phone or tablets: 4 (2.6%)
Other: 7 (4.5%)
Mean score of IGDS9-SF17 (5.64)
Mean problems socializing (IIP-32) (%)−0.8 (1.1)−0.67 (1.0)−1.12 (1.08)−3.86−.25.001**
Global IIP-32, mean (%)1.37 (0.66)1.40 (0.64)1.32 (0.69)−0.64−.04.52
Mean AQ-28 (%)56.01 (12.93)57.55 (11.89)53.39 (14.22)−2.32−.15.001**
Mean HADS-anxiety (%)10.34 (3.41)10.62 (3.27)9.86 (3.60)−1.97−.13.05**
Mean HADS-depression (%)7.33 (2.9)7.35 (2.9)7.3 (3.0)−0.51−.03.61

Note. IGDS9-SF: Internet Gaming Disorder Scale – Short-Form; IIP-32: Inventory of Interpersonal Problems; HADS: Hospital Anxiety and Depression Scale; AQ-28: Autistic Spectrum Quotient 28.

Statistically significant at p < .05.

When comparing gamers and non-gamers, no statistical difference was found regarding assigned gender. Gamers were younger, single, had not socially transitioned, had more problems socializing, higher anxiety levels, and higher scores in the AQ-28. All the effect sizes of the between group comparisons were considered small, apart from the age difference between gamers and non-gamers which was considered moderate. Only two people (0.7%) presented with scores above 36 in the IGDS-9-SF. See Table 1 for sociodemographics and clinical variables between gamers and non-gamers.

Predictor data

In order to investigate predictors of problematic gaming behavior based on the scores of the (IGDS9-SF), only the gamers group was selected (n = 154). Spearman’s correlation analysis showed a positive correlation, which was statistically significant, between problematic gaming and age (r = −.27, p < .001), global IIP-32 scores (interpersonal problems) (r = .45, p < .001), problems socializing (r = .19, p < .001), total AQ-28 (r = .37, p < .007), anxiety scale (r = .34, p < .001), and depression (r = .31, p < .001) (see Table 2 for all correlations).

Table 2.

Spearman’s rho correlations between gaming behavior and all other variables

Problematic gaming behavior
Age−0.13
Problems socializing0.18*
Global IIP-320.44**
AQ-280.38**
HADS-anxiety0.35**
HADS-depression0.32**

Note. IIP-32: Inventory of Interpersonal Problems; HADS: Hospital Anxiety and Depression Scale; AQ-28: Autistic Spectrum Quotient 28.

p < .05.

p < .001.

A multiple linear regression model was calculated to predict problematic gaming behavior based upon the variables found to be significant (age, general interpersonal problems, problems socializing, AQ-28 total, anxiety, and depression). Preliminary analyses were performed to ensure there was no violation of the assumption of linearity and multicollinearity. The regression model for problematic gaming behavior was found to be statistically significant [R2 = .29, F(6) = 13.30, p < .001]. The model explained 56% of the variance in problematic gaming behavior. Age, global IIP-32, and depression all significantly predicted problematic gaming behavior. The main predictor of gaming behavior was interpersonal problems. Out of the three variables that significantly predicted problematic gaming behavior, global IIP-32 made the largest contribution (see Table 3).

Table 3.

Regression models and significant individual predictors of problematic gaming among transgendered gamers

Unstandardized B (95% CI)SEBStandardized Bp
(Constant)−3.370.4872.248.177
IIP-32 problems socializing−0.7300.435−0.125.95
Global IIP-32 score3.1780.9020.349.001*
HADS-anxiety total0.0140.1190.010.909
HASD-depression total0.3270.1440.200.024*
Total AQ-280.0400.0400.081.329
Age−0.1000.38−0.176.01*

Note. IIP-32: Inventory of Interpersonal Problems; HADS: Hospital Anxiety and Depression Scale; AQ-28: Autistic Spectrum Quotient 28. Adj R2 = .27.

p < .05.

Discussion

This study aimed to examine whether transgender people attending transgender health services engage in gaming activities, the degree of problematic behavior, and factors associated with problematic gaming behavior. The present study found that contrary to previous studies, video gaming behavior was not related to assigned gender. The prevalence of IGD (0.7%) was much lower than in previous studies that have examined the prevalence of online gaming problems in nationally representative populations such as adolescents (1.2%–8.5%) and adults (1.4%–5.4%) (Pontes, Macur, & Griffiths, 2016). This may be because transgender gamers use online gaming in a more functional and non-problematic way to explore their gender identity in a safe and non-stigmatizing environment (Griffiths et al., 2016). Additionally, the population selected were those attending transgender health services and therefore able to prioritize their needs above their gaming activity to ask for help. It may be the case that there is still a population of transgender people who suffer from IGD, but who are not in contact with clinical services. The results of this study, therefore, are only generalizable to the population of transgender people attending clinical services and wishing to transition.

Furthermore, differences between assigned males and females in relation to their gaming behavior were not found. This is contrary to previous studies among the cisgender population which have found that being male-assigned (vs. female) is significantly associated with both frequent and problematic/addictive use of video games (Andreassen et al., 2016). There are two hypotheses that present themselves relating to transgender individuals as a result of this study: (a) the sex assigned at birth (and some degree of childhood socialization) is important, and therefore birth-assigned males would play games more frequently and have higher levels of gaming problems than birth-assigned females; or (b) the gender of identity is important due to later socialization and possibly neuronal features in line with the gender of identity and not of birth gender (e.g., Chung et al., 2002; Zhou, Hofman, Gooren, & Swaab, 1995). Therefore birth-assigned females would play more games and have higher levels of gaming problems than birth-assigned males. Further research using larger samples is needed to further explore these hypotheses, as in the present study only two individuals in the whole sample were operationally defined as having a gaming addiction.

As expected, the present study also found that gaming was more prevalent in younger groups. Although gaming behavior in the transgender population attending transgender health services appeared to be prevalent, the degree was not high and less than 1% of them presented with clinical scores for Internet Gaming Disorder as assessed with the IGDS9-SF.

Problematic gaming behavior was associated with high levels of depression, and interpersonal problems. These psychological characteristics may explain why less than 50% of the gamers had socially transitioned by the time they were assessed at the clinic (i.e., people with interpersonal problems are less likely to be able to negotiate their social transition successfully in the real world). The high levels of interpersonal problems found, and the association and predictive capacity of problematic gaming may indicate that tackling interpersonal problems through gaming could be considered beneficial for transgender individuals who have interpersonal difficulties. Although gaming appears (at least initially) to be a positive and beneficial activity for many transgender people, coping strategies developed in the safe virtual reality world may serve as inadequate in “real life” settings due to the diversity in virtual and “real life” social constructs.

The association between problematic gaming behavior and depression is not unique to the transgender population. A large study with more than 8,000 young people found problematic gaming behavior to be associated with an increased risk for emotionally related symptoms, conduct disorder, hyperactivity/inattention, self-injurious behaviors, and problems with peers (Strittmatter et al., 2015). For transgender people, the use of gaming as a coping mechanism and as a way to avoid interpersonal interaction may create a vicious circle where the transgender person does not wish to move out of the secure online world, and back into the real world, thereby making transitioning impossible for those who wish to do so.

Some studies have also identified relationship difficulties among the general population to be associated with high levels of gaming behavior (Suissa, 2015). Furthermore, spending an increasing amount of time in online gaming carries the risk of developing a gaming dependence or addiction (Hellman, Schoenmakers, Nordstrom, & van Holst, 2013). This may affect one’s personal relationships, work and/or study, and reduce the social support that can be vital for a successful transition (Davey, Bouman, Arcelus, & Meyer, 2014; Richards & Barker, 2013).

Transgender people have been found to present with high levels of social anxiety (Millet et al., 2016) and anxiety disorders (Bouman, Claes, Brewin, et al., 2016). New technologies, such as VR, which have been found to be useful for social anxiety disorders (Kampmann, Emmelkamp, & Morina, 2016), could be well received by this population; these could also improve interpersonal skills and reduce anxiety. Video games have proved to be realistic enough to generate successful graded exposure trials against phobias of spiders (Bouchard, Côté, St-Jacques, Robillard, & Renaud, 2006) and heights or enclosed spaces (Robillard, Bouchard, Fournier, & Renaud, 2003) and social anxiety (Kampmann et al., 2016). Older studies (e.g., Dewis et al., 2001) demonstrate that while computer-aided vicarious exposure is superior to the control, live-graded exposure remains superior to both. However, in the last few years VR has improved considerably.

The study also found that autistic traits were not associated to gaming behavior, which is surprising, as video games have been found to be of special interest to people with autistic features (Mazurek, Shattuck, Wagner, & Cooper, 2012; Parsons, Leonard, & Mitchell, 2006).

The nature of the population selected (transgender people accessing transgender health services) and the tools used may limit the results of the present study. The findings could not be generalized to all transgender people. Additionally, due to the cross-sectional nature of the study, causality cannot be determined conclusively. The strength of the study is that it consists of a large number of transgender people, which is unusual in most studies in the field of transgender health. The study cannot conclude that spending too much time gaming in accordance with experienced gender will prevent people testing their experienced gender in the real world, as the number of transgender participants who initiated social gender role transition was higher among participants currently engaged in gaming compared to participants not currently engaged in gaming. However, the study provides an indication that problematic gaming behavior is associated with several psychological symptoms, some of which (depression and interpersonal problems) may affect a successful transition. The findings from this study suggest that games that are designed to help transgender people manage these psychological symptoms may be well received by the transgender population accessing clinical services.

Authors’ contribution

JA: study concept and design, analysis and interpretation of data, responsibility of data, ethics application, statistical analysis, and drafting of manuscript. WPB: study concept and design, responsibility of data, ethics application, and drafting of manuscript. BAJ: drafting of manuscript. CR and SJ-M: study design and drafting of manuscript. MDG: study concept and design, interpretation of data, supervision, and drafting of manuscript.

Conflict of interest

None.

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  • Beek, T. F., Kreukels, B. P., Cohen-Kettenis, P. T., & Steensma, T. D. (2015). Partial treatment requests and underlying motives of applicants for gender affirming interventions. The Journal of Sexual Medicine, 12(11), 22012205. doi:10.1111/jsm.13033

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  • Berry, K., Wearden, A., Barrowclough, C., & Liversidge, T. (2006). Attachment styles, interpersonal relationships and psychotic phenomena in a non-clinical student sample. Personality and Individual Differences, 41(4), 707718. doi:10.1016/j.paid.2006.03.009

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  • Bockting, W., Coleman, E., & De Cuypere, G. (2011). Care of transsexual persons. The New England Journal of Medicine, 364(26), 25592560. doi:10.1056/NEJMc1104884

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  • Bouchard, S., Côté, S., St-Jacques, J., Robillard, G., & Renaud, P. (2006). Effectiveness of virtual reality exposure in the treatment of arachnophobia using 3D games. Technology and Health Care, 14(1), 1927.

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  • Clements-Nolle, K., Marx, R., & Katz, M. (2006). Attempted suicide among transgender persons. Journal of Homosexuality, 51(3), 5369. doi:10.1300/J082v51n03_04

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  • Davey, A., Bouman, W. P., Arcelus, J., & Meyer, C. (2014). Social support and psychological well-being in gender dysphoria: A comparison of patients with matched controls. The Journal of Sexual Medicine, 11(12), 29762985. doi:10.1111/jsm.12681

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  • Davey, A., Bouman, W. P., Meyer, C., & Arcelus, J. (2015). Interpersonal functioning among treatment-seeking trans individuals. Journal of Clinical Psychology, 71(12), 11731185. doi:10.1002/jclp.22209

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  • De Vries, A. L. C., Kreukels, B. P. C., T’sjoen, G., Ålgars, M., & Mattila, A. (2015). Increase of referrals to gender identity clinics: A European trend? In Transgender healthcare in Europe. Book of abstracts (p. 10). Ghent, Belgium: European Professional Association of Transgender Health.

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  • Dhejne, C., Van Vlerken, R., Heylens, G., & Arcelus, J. (2016). Mental health and gender dysphoria: A review of the literature. International Review of Psychiatry, 28(1), 4457. doi:10.3109/09540261.2015.1115753

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  • Glidden, D., Bouman, W. P., Jones, B. A., & Arcelus, J. (2016). Gender dysphoria and autism spectrum disorder: A systematic review of the literature. Sexual Medicine Reviews, 4(1), 314. doi:10.1016/j.sxmr.2015.10.003

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  • Griffiths, M. D., Bouman, W. P., & Arcelus, J. (2016). Video gaming and gender dysphoria: Some case study evidence. Aloma: Revista de Psicologia, Ciències de l’Educació i de l’Esport, 34(2), 5966.

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    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., & Clubley, E. (2001). The autism-spectrum quotient (AQ): Evidence from Asperger syndrome/high-functioning autism, males and females, scientists and mathematicians. Journal of Autism and Developmental Disorders, 31(1), 517. doi:10.1023/A:1005653411471

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Beek, T. F., Kreukels, B. P., Cohen-Kettenis, P. T., & Steensma, T. D. (2015). Partial treatment requests and underlying motives of applicants for gender affirming interventions. The Journal of Sexual Medicine, 12(11), 22012205. doi:10.1111/jsm.13033

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berry, K., Wearden, A., Barrowclough, C., & Liversidge, T. (2006). Attachment styles, interpersonal relationships and psychotic phenomena in a non-clinical student sample. Personality and Individual Differences, 41(4), 707718. doi:10.1016/j.paid.2006.03.009

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bockting, W., Coleman, E., & De Cuypere, G. (2011). Care of transsexual persons. The New England Journal of Medicine, 364(26), 25592560. doi:10.1056/NEJMc1104884

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bouchard, S., Côté, S., St-Jacques, J., Robillard, G., & Renaud, P. (2006). Effectiveness of virtual reality exposure in the treatment of arachnophobia using 3D games. Technology and Health Care, 14(1), 1927.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bouman, W. P., Claes, L., Brewin, N., Crawford, J. R., Millet, N., Fernandez-Aranda, F., & Arcelus, J. (2016). Transgender and anxiety: A comparative study between transgender people and the general population. International Journal of Transgenderism, Epub ahead of print. doi:10.1080/15532739.2016.1258352

    • Search Google Scholar
    • Export Citation
  • Bouman, W. P., Claes, L., Marshall, E., Pinner, G. T., Longworth, J., Maddox, V., Witcomb, G., Jimenez-Murcia, S., Fernandez-Aranda, F., & Arcelus, J. (2016). Socio-demographic variables, clinical features and the role of pre-assessment cross-sex Hormones in older trans people. The Journal of Sexual Medicine, 13(4), 711719. doi:10.1016/j.jsxm.2016.01.009

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Budge, S. L. (2013). Interpersonal psychotherapy with transgender clients. Psychotherapy, 50(3), 356359. doi:10.1037/a0032194

  • Charlop-Christy, M. H., Le, L., & Freeman, K. A. (2000). A comparison of video modeling with in vivo modeling for teaching children with autism. Journal of Autism and Developmental Disorders, 30(6), 537552. doi:10.1023/A:1005635326276

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chung, C. J., De Vries, G. J., & Swaab, D. F. (2002). Sexual differentiation of the bed nucleus of the stria terminalis in humans may extend into adulthood. Journal of Neuroscience, 22(3), 10271033.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clements-Nolle, K., Marx, R., & Katz, M. (2006). Attempted suicide among transgender persons. Journal of Homosexuality, 51(3), 5369. doi:10.1300/J082v51n03_04

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155159. doi:10.1037/0033-2909.112.1.155

  • Davey, A., Bouman, W. P., Arcelus, J., & Meyer, C. (2014). Social support and psychological well-being in gender dysphoria: A comparison of patients with matched controls. The Journal of Sexual Medicine, 11(12), 29762985. doi:10.1111/jsm.12681

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davey, A., Bouman, W. P., Meyer, C., & Arcelus, J. (2015). Interpersonal functioning among treatment-seeking trans individuals. Journal of Clinical Psychology, 71(12), 11731185. doi:10.1002/jclp.22209

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dewis, L. M., Kirkby, K. C., Martin, F., Daniels, B. A., Gilroy, L. J., & Menzies, R. G. (2001). Computer-aided vicarious exposure versus live graded exposure for spider phobia in children. Journal of Behavior Therapy and Experimental Psychiatry, 32(1), 1727. doi:10.1016/S0005-7916(01)00019-2

    • Crossref
    • Search Google Scholar
    • Export Citation
  • De Vries, A. L. C., Kreukels, B. P. C., T’sjoen, G., Ålgars, M., & Mattila, A. (2015). Increase of referrals to gender identity clinics: A European trend? In Transgender healthcare in Europe. Book of abstracts (p. 10). Ghent, Belgium: European Professional Association of Transgender Health.

    • Search Google Scholar
    • Export Citation
  • Dhejne, C., Van Vlerken, R., Heylens, G., & Arcelus, J. (2016). Mental health and gender dysphoria: A review of the literature. International Review of Psychiatry, 28(1), 4457. doi:10.3109/09540261.2015.1115753

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gagne, P., Tewksbury, R., & McGaughey, D. (1997). Coming out and crossing over: Identity formation and proclamation in a transgender community. Gender & Society, 11(4), 478508. doi:10.1177/089124397011004006

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Glidden, D., Bouman, W. P., Jones, B. A., & Arcelus, J. (2016). Gender dysphoria and autism spectrum disorder: A systematic review of the literature. Sexual Medicine Reviews, 4(1), 314. doi:10.1016/j.sxmr.2015.10.003

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Granic, I., Lobel, A., & Engels, R. C. (2014). The benefits of playing video games. American Psychologist, 69(1), 6678. doi:10.1037/a0034857

  • Griffiths, M. D., Bouman, W. P., & Arcelus, J. (2016). Video gaming and gender dysphoria: Some case study evidence. Aloma: Revista de Psicologia, Ciències de l’Educació i de l’Esport, 34(2), 5966.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffiths, M. D., Kuss, D. J., & Ortiz de Gortari, A. (2013). Videogames as therapy: A review of the medical and psychological literature. In Miranda I. M. & Cruz-Cunha M. M. (Eds.), Handbook of research on ICTs for healthcare and social services: Developments and applications (pp. 4368). Pennsylvania, USA: IGI Global.

    • Search Google Scholar
    • Export Citation
  • Health Research Authority (HRA). (2013). Guidance for NHS research studies. London, UK: Health Research Authority.

  • Hellman, M., Schoenmakers, T. M., Nordstrom, B. R., & van Holst, R. J. (2013). Is there such a thing as online video game addiction? A cross-disciplinary review. Addiction Research & Theory, 21(2), 102112. doi:10.3109/16066359.2012.693222

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoekstra, R. A., Bartels, M., Cath, D. C., & Boomsma, D. I. (2008). Factor structure, reliability and criterion validity of the autism-spectrum quotient (AQ): A study in Dutch population and patient groups. Journal of Autism and Developmental Disorders, 38(8), 15551566. doi:10.1007/s10803-008-0538-x

    • Crossref
    • Search Google Scholar
    • Export Citation
  • IBM Corporation. (2013). IBM SPSS statistics for windows, version 22.0. Armonk, NY, USA: IBM Corporation.

  • Jones, B. A., Arcelus, J., Bouman, W. P., & Haycraft, E. (2017). A systematic review of the literature relating to sport participation and competitive sport policies. Sports Medicine. doi:10.1007/s40279-016-0621-y

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kampmann, I. L., Emmelkamp, P. M., & Morina, N. (2016). Meta-analysis of technology-assisted interventions for social anxiety disorder. Journal of Anxiety Disorders, 42, 7184. doi:10.1016/j.janxdis.2016.06.007

    • Crossref
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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

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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
sumbission  
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 850 EUR/article
Printed Color Illustrations 40 EUR (or 10 000 HUF) + VAT / piece
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Editorial Board / Advisory Board members: 50%
Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription Information Gold Open Access
Purchase per Title  

Journal of Behavioral Addictions
Language English
Size A4
Year of
Foundation
2011
Publication
Programme
2021 Volume 10
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

  • Judit BALÁZS (ELTE Eötvös Loránd University, Hungary)
  • Joel BILLIEUX (University of Lausanne, Switzerland)
  • Matthias BRAND (University of Duisburg-Essen, Germany)
  • Anneke GOUDRIAAN (University of Amsterdam, The Netherlands)
  • Daniel KING (Flinders University, Australia)
  • Ludwig KRAUS (IFT Institute for Therapy Research, Germany)
  • H. N. Alexander LOGEMANN (ELTE Eötvös Loránd University, Hungary)
  • Anikó MARÁZ (Humboldt University of Berlin, Germany)
  • Astrid MÜLLER (Hannover Medical School, Germany)
  • Marc N. POTENZA (Yale University, USA)
  • Hans-Jurgen RUMPF (University of Lübeck, Germany)
  • Attila SZABÓ (ELTE Eötvös Loránd University, Hungary)
  • Róbert URBÁN (ELTE Eötvös Loránd University, Hungary)
  • Aviv M. WEINSTEIN (Ariel University, Israel)

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)
  • Kenneth BLUM (University of Florida, USA)
  • Henrietta BOWDEN-JONES (Imperial College, United Kingdom)
  • Beáta BÖTHE (University of Montreal, Canada)
  • 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)
  • 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 (Eötvös Loránd University, Hungary)
  • Giovanni MARTINOTTI (‘Gabriele d’Annunzio’ University of Chieti-Pescara, Italy)
  • 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)
  • Johan VANDERLINDEN (University Psychiatric Center K.U.Leuven, Belgium)
  • Alexander E. VOISKOUNSKY (Moscow State University, Russia)
  • Kimberly YOUNG (Center for Internet Addiction, USA)

 

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