The Spanish Version of the Video Game Functional Assessment-Revised

Abstract

It is estimated that 16.8 million in Spain (41% female) are involved in gaming, and approximately 8.3% of Spanish gamers are problematic gamers (i.e., endorsing five or more of the nine criteria for Internet Gaming Disorder [IGD]). Given the high prevalence of IGD in Spain, this study evaluated construct validity and concurrent validity of the Spanish Version of the Video Game Functional Assessment—Revised (SP-VGFA-R), by examining the correlational coefficients with the nine-item Internet Gaming Disorder Scale-Short-Form (IGDS9-SF). A total of 434 adults 18 years of age or older participated in the study (15.1% female). Results showed that the SP-VGFA-R was positively and significantly associated with the IGDS9-SF (bivariate coefficients ranging from 0.411 to 0.610). Four distinct factors in the SP-VGFA-R were identified in confirmatory factor analysis, including (a) social attention, (b) tangible/intangible rewards, (c) escape/avoidance of demands or pain, and (d) sensory stimulation. Other findings showed that IGDS9-SF scores increased as (a) the escape/avoidance of demands or pain function increased and (b) two or more function scores increased. The SP-VGFA-R can be used in combination with the IGDS9-SF to assess Spanish gamers with IGD internationally, and to develop evidence-based behavioral interventions.

Introduction

The prevalence of internet gaming disorder (IGD) internationally ranges from 0.7% to 27.5%, with higher prevalence among males than females in the vast majority of studies.¹ A systematic review and meta-analysis were performed for studies (n = 53) conducted between 2009 and 2019 and showed worldwide prevalence estimates of 3.05%.² However, it should be noted that the prevalence rates may differ depending on the screening instrument used and interpretation of those findings.³ In European countries, the rate of prevalence is largely based on categorical demographics,⁴ and some evidence suggests that IGD increased during the COVID-19 pandemic.^5,6

Despite IGD being problematic across several cultures, this study focused on the Spanish culture, as the Spanish Video Game Association (2018) reported that, in Spain, 16.8 million are involved in gaming (41% female), indicating that an estimated 35% of the total Spanish population has engaged in playing video games.^7,8

Furthermore, an estimated 480 million people are native Spanish speakers,^9,10 and this language is spoken in 31 different countries. Among young adults (18–28 years), only a few studies have assessed prevalence and diagnosis of IGD in Spain.^11,12 Given this, it is critical to understand what functionally maintains this behavior at such a relatively high rate, in attempts to treat this clinically.

Although there has been ongoing debate about whether problematic gaming is a genuine disorder, it has now received formal recognition in both the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders (DSM-5),¹³ which included IGD in Internet Gaming Disorder, and the World Health Organization's International Classification of Diseases (ICD-11),¹⁴ which included “gaming disorder.” Subsequently, validated psychometric instruments like the nine-item Internet Gaming Disorder Scale-Short-Form (IGDS9-SF)¹⁵ were constructed and validated in several languages (e.g., Spanish,¹¹ Chinese,¹⁶ Turkish,¹⁷ Italian¹⁸).

A study of Spanish adolescents was conducted by Buiza-Aguado et al.⁷ and reported that in a sample of 708 students in large urban areas across low, medium, and high socioeconomic status reported, 72.8% were online gamers. Of this sample, 8.3% met five or more of the DSM-5's nine criteria for IGD. Other studies such as Lopez-Fernandez et al.¹⁹ reported that 7.7% of equally sampled male and female Spanish adolescents gamers (n = 1132) between the ages of 11 and 18 years were classified as pathological gamers. Moreover, Fumero et al.²⁰ found that, among 946 Spanish adolescents 11 to 18 years of age, (a) anxiety and time spent playing predicted IGD, (b) social skills and family functioning indirectly predicted IGD, (c) lower family functioning was related with IGD among females, and (d) hostility and social skill deficits were associated among males.

Despite the known problems, variables, and consequences related to IGD in the Spanish population, few studies have examined methodologies to best treat this disorder, or reduce the duration and frequency of problematic gaming among those who meet criteria for IGD.²¹ Similar to other addictive behaviors, there are several behavioral interventions that may be applicable to the treatment of IGD. One such approach is by conducting a functional behavioral assessment to determine the antecedents that follow a type of behavior and the consequences related to maintaining the behavior.²²

The Video Game Functional Assessment—Revised (VGFA-R) is a functional behavioral assessment instrument designed to assess the motivation to engage in video gaming that contributes to IGD and comprises items relating to (a) social attention, (b) tangible/intangible rewards, (c) escape/avoidance of demands or pain, and (d) sensory stimulation.²³

Social attention involves seeking a response from others by drawing the attention to an individual's behavior, through positive or negatively maintained behavior.²⁴ The escape/avoidance function is divided into two related functions, including escape (termination of the demand made on the individual) and avoidance (temporary removal of the demand). The tangible/intangible reward function is the desire for an item or commodity within a game, such as earning in-game items like improved equipment or cosmetic items.^25,26

Finally, the sensory stimulation function is maintained by two aspects, including visual characteristics (e.g., lights and graphics that are esthetically pleasing) and auditory characteristics (e.g., music, sound effects). The sensory stimulation function can lead to a gamer becoming so intensely immersed in the video game, that they become disconnected from other aspects of their environment and life.^27–29 Theoretical support for the VGFA-R is now well established in the literature.^{23,24,29–32}

There have also been recommendations to assess the functions that reinforce video gaming among gamers who meet criteria for IGD.³² Although prior research has shown that identifying severity level^4,10 is necessary when developing interventions, understanding the reinforcing functions that maintain the detrimental behavior is essential in the development of actual treatment interventions.¹⁸ Since there is a large Spanish population worldwide, the IGD has been cross-culturally validated,^4,11–13 and identifying the function that maintains/reinforces a behavior is vital in implementing treatment interventions²³; the VGFA-R must also be validated among these populations to conduct functional assessments that lead to the development of effective interventions.

Since the Spanish Version of the Video Game Functional Assessment—Revised (SP-VGFA-R) has already been validated in English, it is possible to make comparisons between samples from other cultures. Consequently, the purpose of this study was to psychometrically evaluate the SP-VGFA-R, as well as establish concurrent validity with one of the most used instruments assessing IGD, namely IGDS9-SF.

Methods

Participants

Initially, a total of 434 gamers participated in the study. Potential participants were recruited at the Universitat Autonoma de Barcelona Universita or were contacted online through approved Spanish social networking sites,³³ or through e-mails within social networks. Inclusion criteria were similar to that of Buono et al.²⁴

Participants (a) were required to be 18 years of age or older, (b) were required to play at least 1 hour of video games per week, (c) had to speak and read Spanish, and (d) had to access the survey by mobile phone, tablet, or computer. Exclusion criteria included (a) being younger than 18 years, (b) having no access to the internet through laptop/desktop computer, and (c) submitting incomplete data (e.g., exiting the survey before completion, providing demographics, but no answers to outcome measures). Of the 434 initial gamers, 66 were eliminated because they were either underage (n = 18) or provided incomplete data (n = 48), resulting in a final sample size of 368 gamers. Of these, 284 identified as male (77.20%) and 84 identified as female (22.80%). The mean age of the total sample was 25.1 years (53.9%).

Materials

The Spanish VGFA-R (SP-VGFA-R), assesses 24-items across four functions (six questions per function) that reinforce/maintain video gaming: (a) social attention, (b) tangible/intangible rewards, (c) escape/avoidance of demands or pain, and (d) sensory stimulation.²³ Individuals are presented with an item (e.g., “I choose to play video games when I am upset or depressed”) and then select their response based on a seven-item scale (never, almost never, seldom, half the time, usually, almost always, and always). Items associated with each function are summed and the function with the highest rating is the function that maintains video gaming (note: participants may have more than one function that maintains gaming). The psychometric properties of the Spanish SP-VGFA-R are presented in the Results section.

The Spanish version of the IGDS9-SF was used to assess the risk of IGD and is based on the nine DSM-5 criteria for IGD.^11,15 Factor analysis from the original scale development study identified six components comprising salience, mood modification, tolerance, withdrawal symptoms, conflict, and relapse.

Individuals are presented with an item (e.g., Do you feel the need to spend increasing amount of time engaged gaming to achieve satisfaction or pleasure; ¿Sientes la necesidad de pasar cada vez más tiempo jugando para lograr satisfacción o placer?) and select one of five responses indicating their level of agreement/disagreement with the statement (1 = never, 2 = rarely, 3 = sometimes, 4 = often, and 5 = very often). The total score is obtained (ranging from 9 to 45) and higher scores indicate a higher level of IGD symptom severity. The Spanish IGDS9-SF showed very good overall internal consistency using Cronbach's alpha (α = 0.857).

Procedure

The translation of the VGFA-R was carried out using standardized international protocols.³⁴ Participants included undergraduates at Universitat Autonoma de Barcelona Universita, and were contacted through online social networks and answered an online questionnaire (SP-VGFA-R) with informed consent. An independent samples t-test was performed and showed no significant difference between the datasets (undergraduates recruited at the Universitat Autonoma de Barcelona Universita and participants recruited online).

Therefore, they were combined to create one dataset. Participants who agreed to take part in the study were instructed to click on the link at the bottom of the recruitment e-mail. The link relocated the study participants to the study materials within Qualtrics. The SP-VGFA-R was completed first by study participants, followed by demographic information (e.g., participants were asked about their preferred gaming platforms), and then the Spanish IGDS9-SF. The materials were administered in this manner to provide a break between answering questions that had some similarity in phrasing. Once participants completed all the study materials, a debriefing statement was provided.

Ethics

Approval from the second author's institutional review board was requested and obtained before recruiting participants or the study. The study procedures were carried out in accordance with the Declaration of Helsinki. All participants were informed about the study, and all provided informed consent.

Data analysis

Values of the SP-VGFA-R within each function are summed for their total score. If the total highest score is equal to another function (e.g., attention and tangible), the highest motivating function is then maintained by automatic reinforcement, because of two functions interplaying with each other. This is common practice for functional assessment.³⁵ However, for the current dataset, no participant had equal maintaining functions.

Statistical analyses were performed using Statistical Package for the Social Sciences (SPSS) version 27. There were three analyses used for the study, comprising a principal components analysis (PCA), a correlational analysis, and a multinomial logistic regression analysis. A PCA was used to compute scores for the factors underlying the VGFA-R. The four-factor solution was preferred because of prior theoretical support,³⁶ and internal consistency for the entire scale was examined using Cronbach's alpha and resulted in good overall consistency, α = 0.938. Each subscale had the following Cronbach's alpha scores: social attention (α = 0.874), escape/avoidance (α = 0.875), tangible/intangible (α = 0.827), and sensory stimulation (α = 0.747).

The comparison between a new scale and an established scale is a method to evaluate concurrent validity. This is accomplished by examining the correlation coefficient between the items of the two scales.³⁷ The correlational analysis was performed to examine the relationship between the SP-VGFA-R and the IGDS9-SF and to determine concurrent validity.

A multinomial logistic regression analysis was performed to determine how scores on the IGDS9-SF (i.e., risk of IGD) predicted each function of the VGFA-R (social attention, tangible/intangible rewards, escape/avoidance of demands or pain, and sensory stimulation). This analysis was used because the four levels of the VGFA-R (outcome variable) have no magnitude as found in ordinal, interval, and ratio scales of measurement,³⁸ and there are more than two levels found in traditional binomial logistic regressions. All assumptions were met before running the analysis. Multicollinearity did not appear to be an issue given that all significant correlational coefficients (<0.07) were below the typical cutoff value of (≥) 0.80.³⁹

Participant data were removed and placed into the two or more function category if they had more than one function that maintained a behavior, as defined by a functioning being within 3 points (≤) of the highest scored function.

Results

Descriptive information is shown in Table 1. A frequency distribution analysis showed that 14.6% played video games for 24 hours or more per week and 10.6% played video games for 18 to 23 hours per week and preferred gaming consoles (29.5%) or mobile game devices (16.6%). Concurrent validity of the SP-VGFA-R was established by examining the correlation coefficients to the Spanish version of the IGDS9-SF (total score). As presented in Table 2, the correlation analysis showed significant, positive correlations between the two scales (bivariate coefficients ranging from 0.411 to 0.610).

Table 1.

Demographic Information of Gamers (N = 304)

	N	% of population
Platform(s) used
Computer games	195	53.0
Gaming consoles	105	28.5
Mobile games	61	16.6
Tablet/iPad	5	1.4
Hours played/week
0–5	58	15.8
6–11	101	27.4
12–17	102	27.7
18–23	42	11.4
24+	65	17.7

Table 2.

Principal Component Analysis of the Total Variance of the Spanish Version of the Video Game Functional Assessment—Revised

Total variance explained
Component	Extraction sums of squared loadings			Rotation sums of squared loadings^a
Component	Total	% of variance	Cumulative %	Total
1	9.083	37.844	37.844	6.592
2	1.902	7.925	45.769	6.481
3	1.694	7.058	52.828	6.520
4	1.262	5.258	58.086	5.180

Extraction method: principal component analysis.

When components are correlated, sums of squared loadings cannot be added to obtain total variance.

Spanish VGFA-R construct validity

A four-factor confirmatory analysis was utilized to examine the factorability of 24 items of the VGFA-R. The data were screened for univariate outliers, and the minimum amount of data for factor analysis was satisfied. Initially, factorability of the 24-item VGFA-R was examined using several well-recognized criteria. All 24 items correlated at a minimum of 0.30 with at least one other item. Kaiser-Meyer-Olkin measure of sampling adequacy was 0.920, above the recommended value of 0.60.⁴⁰ Bartlett's test of sphericity was significant (χ² = (276) = 4497.617, p < 0.001). Diagonals of the anti-image correlation matrix exceeded 0.3, supporting inclusion of each item in the factor analysis.⁴¹ Communalities ranged between 0.435 and 0.764, confirming all other items shared some common variance.

Therefore, factor analysis was conducted with all 24 items. PCA with promax rotation was utilized because the primary purpose was to identify and compute scores for the correlated factors underlying the VGFA-R. The first factor explained 37.84% of the variance, the second factor explained 7.92% of the variance, the third factor explained 7.06% of the variance, and the fourth factor explained 5.26% of the variance. A promax rotation provided the best-defined factor structure. The summary of the confirmatory factor analysis is presented in Table 3.

Table 3.

Correlation Matrix of Spanish Video Game Functional Assessment—Revised and Spanish Internet Gaming Disorder Scale-Short Form

	1	2	3	4	5
SP-VGFA-R attention (1)	—	—	—	—	—
SP-VGFA-R escape (2)	0.534^a	—	—	—	—
SP-VGFA-R tangible (3)	0.558^a	0.575^a	—	—	—
SP-VGFA-R sensory (4)	0.587^a	0.577^a	0.610^a	—	—
Total Spanish IGDS9-SF (5)	0.411^a	0.635^a	0.467^a	0.474^a	—

Coefficients are significant at <0.001.

IGDS9-SF, nine-item Internet Gaming Disorder Scale-Short-Form; SP-VGFA-R, Spanish video game functional assessment—revised.

Comparison of Spanish IGDS9-SF and Spanish VGFA-R

A multinomial logistic regression analysis was performed to determine how scores on the IGDS9-SF predicted each function of the VGFA-R (social attention, tangible/intangible rewards, escape/avoidance of demands or pain, and sensory stimulation). The social attention function served as the comparison group and findings showed that the IGDS9-SF score increased as the escape/avoidance of demands or pain function increased (β = 0.112, χ²₍₁₎ = 13.08, p < 0.0001), and two or more function scores increased (β = 0.057, χ²₍₁₎ = 5.029, p = 0.025). Results also showed that age was a significant predictor of escape/avoidance of demands or pain function (β = 0.079, χ²₍₁₎ = 7.71, p = 0.006), tangible/intangible rewards (β = 0.073, χ²₍₁₎ = 9.16, p = 0.002), sensory stimulation (β = 0.129, χ²₍₁₎ = 15.832, p < 0.001), and two or more functions (β = 0.057, χ²₍₁₎ = 6.201, p = 0.013).

Discussion

The goal of this study was to establish construct validity of the SP-VGFA-R, and to establish concurrent validity by examining the correlational coefficients with the Spanish IGDS9-SF. Prior research has shown high reliability and validity of the VGFA-R,²³ and this translated well within the Spanish population used in this study. The scale showed positive correlations (bivariate coefficients ranging from 0.411 to 0.610). The initial English validation of the VGFA-R showed that the sensory stimulation function did not load well among participants. However, the Spanish version showed that four distinct functions were identified from the confirmatory factor analysis, including (a) social attention, (b) tangible/intangible rewards, (c) escape/avoidance of demands or pain, and (d) sensory stimulation.

Findings also showed that IGDS9-SF scores increased as the escape/avoidance of demands or pain function increased and two or more function scores increased when social attention was used as the comparison group, reinforcing the findings of previous research.²⁹ Prior research has shown that some gamers spend a significant investment in terms of time and energy toward gaming because it allows the opportunity to escape their real-life problems.^42,43 In addition, much of the research has focused on the occurrence of different gamer profiles,⁴⁴ or the development of diagnostic materials to identify the relationships between IGD and other psychopathologies.^45,46

Tullett-Prado et al.⁴⁴ indicated that identifying gamer profiles would be of “high clinical value” because latent class analyses showed four IGD classes comprising (a) IGD aversive, (a) normative, (c) moderate IGD risk, and (d) high IGD risk, and recommended that social engagement and participation should be particularly targeted by IGD immunization and treatment protocols. However, identifying gamer profiles is not sufficient in conducting functional assessments. Moreover, as indicated in the Results section, the tangible/intangible rewards and sensory stimulation functions had no difference compared to social attention when examining how IGD predicted these functions. This indicates that the identification of severity alone may not be adequate in identifying the function that maintains the behavior, or enough information to develop treatment interventions.

Given the empirical support demonstrating the SP-VGFA-R is an appropriate tool to assess behavioral functions that reinforce video gaming, clinicians internationally can use this functional assessment to treat IGD among the Spanish populations. Furthermore, Spanish-speaking researchers can now use the IGDS9-SF to identify the severity of IGD and the SP-VGFA-R to further develop behavioral interventions to target the function that maintains the gaming behavior. More specifically, for gamers who show IGD severity levels that are consistent with problematic gaming, the functional behavioral assessment instrument will help determine the antecedents that follow a type of behavior and the consequences related to maintaining the behavior.^47,48 However, cultural influences must also be considered when identifying if the severity level of IGD is considered an issue.

Cultural effects and behavioral decision making

Previous research has shown that there are cultural influences on judgment and decision-making,⁴⁹ and this might deem what is socially acceptable in terms of video game playing. For example, in some cultures, what constitutes excessive gaming may be viewed differently, and even if the IGDS9-SF identifies severe IGD, this might not be an issue culturally, as problematic dimensions are seemed to be shaped by culture-specific expressions. For example, in some cultures, what constitutes excessive gaming may be viewed differently, and even if the IGDS9-SF identifies more severe IGD, this might not be an issue culturally, as problematic dimensions appear to be shaped by culture-specific expressions.⁴⁵ The relationship between values and decision-making styles is higher and numerous in younger adolescents.⁵⁰

Furthermore, studies have shown slight cultural differences when examining British versus Spanish gamers.¹⁹ This was slightly lower than what was reported in Lopez-Fernandez et al.,¹⁹ which showed that 7.7% of gamers in Spain could be classified as pathological gamers. Irrespective of the exact prevalence of IGD, having a complimentary functional assessment can result in the development in effective treatment interventions to alleviate IGD.

In addition, functional assessments should be developed in several languages and validated among different cultural populations. This will assist clinicians and treatment providers in identifying the correct function, and then interventions that target each function can be developed. However, the invariance of English to Spanish or inclusion of other cultures should be taken into account, as this may limit the findings of this study.

Limitations and future research

This study is not without its limitations. One limitation is that both psychometric instruments used involved self-report responses (indirect assessment), rather than using direct behavioral assessment. There are limitations to both direct and indirect assessments (e.g., interfering in the natural environment versus participants incorrectly marking their responses or exaggerating or underestimating their responses to each item), and the sample utilized was not representative of all Spanish gamers, given its cross-sectional design, its use of university students as the target population, and the method of data collection (i.e., convenience sampling). Future research should consider more representative methodologies to enhance true sampling across different international Spanish populations, although this would be difficult and costly in terms of both time and money.

Future research should utilize both the Spanish IGDS9-SF and Spanish VGFA-R to gather information concerning the antecedent stimuli and consequences that are functional to the problem behavior.^23,51

Conducting video game playing functional assessments will help clinicians identify why the problem behavior occurs, and further understanding this concept will allow the development of evidence-based treatments and interventions. Furthermore, validating the SP-VGFA-R into other cultural populations would allow clinicians to conduct functional assessments and can be used with the IGDS9-SF to identify gamers with severe IGD. Finally, future studies should use an approach to where the IGD scales and the SP-VGFA-R are administered in different orders for participants within the same study. Having one scale administered before the other, one may influence or prime the participant in their responses to the other scale.

Authors' Contributions

All authors contributed to the preparation of this article.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

Supplementary Material

References

Mihara

, Higuchi

. Cross-sectional and longitudinal epidemiological studies of internet gaming disorder: a systematic review of the literature. Psychiatry and Clinical Neurosciences, 2017; 71:425–444.

Stevens

, Dorstyn

, Delfabbro

, et al. Global prevalence of gaming disorder: a systematic review and meta-analysis. The Australian and New Zealand Journal of Psychiatry, 2021; 55:553–568.

King

, Billieux

, Carragher

, et al. Face validity evaluation of screening tools for gaming disorder: scope, language, and overpathologizing issues. Journal of Behavioral Addictions, 2020; 9:1–13.

Europe's Video Games Industry/European Games Developer Federation. (2021) Key facts 2020: the year we played together. https://www.isfe.eu/wp-content/uploads/2021/10/2021-ISFE-EGDF-Key-Facts-European-video-games-sector-FINAL.pdf (accessed Nov. 15, 2021).

Blake

, Sauermilch

. Reconsidering internet gaming disorder during the COVID-19 pandemic. Journal of Technology in Behavioral Science, 2021; 6:348–351.

Masaeli

, Farhadi

. Prevalence of internet-based addictive behaviors during COVID-19 pandemic: a systematic review. Journal of Addictive Disease, 2021; 39:468–488.

Buiza-Aguado

, Alonso-Canovas

, Conde-Mateos

, et al. Problematic video gaming in a young Spanish population: association with psychosocial health. Cyberpsychology & Behavior and Social Network, 2018; 21:388–394.

Asociación Española de Videojuegos. (2018) The video game industry in Spain [in Spanish]. Madrid, Spain: Asociación Española de Videojuegos.

Ardila

. Who are the Spanish speakers? An examination of their linguistic, cultural, and societal commonalities and differences. Hispanic Journal of Behavioral Sciences, 2020; 42:41–61.

10.

Fernández-Vítores

. (2020) Spanish: a living language [in Spanish]. Report, 2020. Instituto Cervantes. https://cvc.cervantes.es/lengua/espanol_lengua_viva/pdf/espanol_lengua_viva_2020.pdf (accessed Nov. 15, 2021).

11.

Beranuy

, Machimbarrena

, Vega-Oses

, et al. Spanish validation of the internet gaming disorder scale-short form (IGDS9-SF): prevalence and relationship with online gambling and quality of life. International Journal of Environmental Research and Public Health, 2020; 17.

12.

Sanchez-Iglesias

, Bernaldo-de-Quiros

, Labrador

, et al. Spanish validation and scoring of the internet gaming disorder scale—short-form (IGDS9-SF). Spanish Journal of Psychology, 2020; 23:e22.

13.

American Psychiatric Association. (2013) Diagnostic and statistical manual of mental disorders: DSM-5. 5th ed. Washington, DC: American Psychiatric Association.

14.

World Health Organization. (2018) The ICD-11 classification of mental and behavioural disorders. Geneva, Switzerland: WHO. https://icd.who.int/browse11/l-m/en (accessed Nov. 5, 2021).

15.

Pontes

, Kiraly

, Demetrovics

, et al. The conceptualisation and measurement of DSM-5 internet gaming disorder: the development of the IGD-20 test. PLoS One, 2014; 9:e110137.

16.

Yam

, Pakpour

, Griffiths

, et al. Psychometric testing of three Chinese online-related addictive behavior instruments among Hong Kong University students. Psychiatric Quarterly, 2019; 90:117–128.

17.

Evren

, Dalbudak

, Topcu

, et al. Psychometric validation of the Turkish nine-item internet gaming disorder scale-short form (IGDS9-SF). Psychiatry Research, 2018; 265:349–354.

18.

Monacis

, Palo

, Griffiths

, et al. Validation of the internet gaming disorder scale—short-form (IGDS9-SF) in an Italian-speaking sample. Journal of Behavioral Addictions, 2016; 5:683–690.

19.

Lopez-Fernandez

, Honrubia-Serrano

, Baguley

, et al. Pathological video game playing in Spanish and British adolescents: towards the exploration of internet gaming disorder symptomatology. Computers in Human Behavior, 2014; 41:304–312.

20.

Fumero

, Marrero

, Bethencourt

, et al. Risk factors of internet gaming disorder symptoms in Spanish adolescents. Computers in Human Behavior, 2020; 111:106416.

21.

Zajac

, Ginley

, Chang

, et al. Treatments for internet gaming disorder and internet addiction: a systematic review. Psychology of Addictive Behaviors, 2017; 31:979–994.

22.

Schlinger

Jr. , Normand

. On the origin and functions of the term functional analysis. Journal of Applied Behavior Analysis, 2013; 46:285–288.

23.

Buono

, Upton

, Griffiths

, et al. Demonstrating the validity of the video game functional assessment-revised (VGFA-R). Computers in Human Behavior, 2016; 54:501–510.

24.

Buono

, Griffiths

, Sprong

, et al. Measures of behavioral function predict duration of video game play: utilization of the video game functional assessment—revised. Journal of Behavioral Addictions, 2017; 6:572–578.

25.

King

, Delfabbro

. Understanding and assisting excessive players of video games: a community psychology perspective. The Australian Community Psychologist, 2009; 21:62–74.

26.

King

, Delfabbro

, Griffiths

. The role of structural characteristics in problematic video game play: an empirical study. International Journal of Mental Health and Addiction, 2010; 9:320–333.

27.

Griffiths

. Diagnosis and management of video game addiction. New Directions in Addiction Treatment and Prevention, 2008; 12:27–41.

28.

Gros

, Debue

, Lete

, et al. Video game addiction and emotional states: possible confusion between pleasure and happiness?. Frontiers in Psychology, 2019; 10:2894.

29.

Sprong

, Buono

, Kaiser

, et al. The mediation effects of behavioral motivations between age of gaming onset and internet gaming disorder. Journal of Addictive Behaviors, Therapy & Rehabilitation, 2021; 10:1–5.

30.

Buono

, Paul

, Sprong

, et al. Gaming and gaming disorder: a mediation model gender, salience, age of gaming onset, and time spent gaming. Cyberpsychology, Behavior and Social Networking, 2020; 23:647–651.

31.

Sprong

, Buono

, Bordieri

, et al. Establishing the behavioral function of video game use: development of the video game functional assessment. Journal of Addictive Behaviors, Therapy & Rehabilitation, 2014; 3:1–6.

32.

Sprong

, Griffiths

, Lloyd

, et al. Comparison of the video game functional assessment-revised (VGFA-R) and internet gaming disorder test (IGD-20). Frontiers in Psychology, 2019; 10:310.

33.

Panova

, Carbonell

, Chamarro

, et al. Internet addiction test research through a cross-cultural perspective: Spain, USA and Colombia. Adicciones, 2021; 33:307–318.

34.

Beaton

, Bombardier

, Guillemin

, Ferraz

. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine (Phila Pa 1976), 2000; 25:3186–3191.

35.

Iwata

, Deleon

, Roscoe

. Reliability and validity of the functional analysis screening tool. Journal of Applied Behavior Analysis, 2013; 46:271–284.

36.

Hancock

, Stapleton

, Mueller

. (2019) The reviewer's guide to quantitative methods in the social sciences. 2nd ed. New York City, NY: Routledge.

37.

Murphy

, Davidshofer

. (2005) Psychological testing: priniciples and applications. 6th ed. Englewood Cliffs, NJ: Prentice-Hall.

38.

Sheperis

, Drummond

, Jones

. (2019) Assessment procedures for counselors and helping professionals. 9th ed. London, England: Pearson.

39.

Berry

, Feldman

. (1985) Multiple regression in practice (quantitative applications in the social sciences). Newbury Park, CA: Sage Publications.

40.

Garson

. (2013) Factor analysis. Asheboro, NC: Statistical Associates Blue Book Series.

41.

Cerny

, Kaiser

. A study of a measure of sampling adequacy for factor-analytic correlation matrices. Multivariate Behavioral Research, 1977; 12:43–47.

42.

Kuss

, Griffiths

. Internet gaming addiction: a systematic review of empirical research. International Journal of Mental Health and Addiction, 2011; 10:278–296.

43.

Kuss

, Pontes

, Griffiths

. Neurobiological correlates in internet gaming disorder: a systematic literature review. Frontiers in Psychiatry, 2018; 9:166.

44.

Tullett-Prado

, Stavropoulos

, Mueller

, et al. Internet gaming disorder profiles and their associations with social engagement behaviours. Journal of Psychiatric Research, 2021; 138:393–403.

45.

Kircaburun

, Pontes

, Stavropoulos

, et al. A brief psychological overview of disordered gaming. Current Opinion in Psychology, 2020; 36:38–43.

46.

Stavropoulos

, Gomez

, Mueller

, et al. User-avatar bond profiles: how do they associate with disordered gaming?. Addictive Behaviors, 2020; 103:106245.

47.

Hanley

, Iwata

, McCord

. Functional analysis of problem behavior: a review. Journal of Applied Behavior Analysis, 2003; 36:147–185.

48.

Oka

, Hamamura

, Miyake

, et al. Prevalence and risk factors of internet gaming disorder and problematic internet use before and during the COVID-19 pandemic: a large online survey of Japanese adults. Journal of Psychiatric Research, 2021; 142:218–225.

49.

Weber

, Morris

. Culture and judgment and decision making: the constructivist turn. Perspectives on Psychological Science, 2010; 5:410–419.

50.

Gallego

, Perich

, Chowdhury

, et al. Long-term stability of cortical population dynamics underlying consistent behavior. Nature Neuroscience, 2020; 23:260–270.

51.

Sprong

, Dallas

, Upton

, et al. The influence of race, causal attribution, and in-group favoritism on recommendations for rehabilitation services. Rehabilitation Counseling Bulletin, 2014; 58:227–239.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB