Internet Gaming Disorder Scale – Short Form (IGDS9-SF)

1. Abstract

The Internet Gaming Disorder Scale – Short Form (IGDS9-SF) is a standardized, psychometrically validated, self-report instrument engineered to evaluate the severity and symptomatology of Internet Gaming Disorder (IGD). Developed by Halley M. Pontes and Mark D. Griffiths in 2015, the instrument directly translates the nine clinical diagnostic criteria outlined in Section III of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) into a brief, psychometrically robust psychometric tool. The IGDS9-SF comprises exactly 9 items, each operationalizing a distinct DSM-5 criterion: preoccupation, withdrawal symptoms, tolerance, unsuccessful attempts to control or curtail gaming, loss of other recreational interests, continued excessive gaming despite negative psychosocial consequences, deception regarding gaming engagement, gaming to escape negative psychological states or modify mood, and jeopardizing or sacrificing significant educational, occupational, or interpersonal relationships.

Administered via a 5-point Likert scale ranging from 1 (Never) to 5 (Very Often), the total composite score ranges from 9 to 45, with higher values denoting greater IGD severity. Extensive cross-cultural investigations have demonstrated that the IGDS9-SF exhibits exemplary psychometric properties, consistently displaying high internal consistency reliability (Cronbach’s alpha values typically ranging between .87 and .94; McDonald’s omega exceeding .88), solid test-retest reliability, and robust unidimensional construct validity verified across diverse linguistic populations via rigorous exploratory and confirmatory factor analyses. Furthermore, the instrument demonstrates robust convergent validity through moderate-to-strong correlations with maladaptive gaming behaviors, weekly hours spent playing video games, psychological distress (depression, anxiety, stress), and loneliness, while maintaining strict discriminant validity from adaptive gaming engagement. The scale serves as an internationally recognized gold standard for epidemiological screening, psychopathological modeling, and clinical assessment of disordered gaming.

2. Keywords

Internet Gaming Disorder, IGDS9-SF, behavioral addiction, DSM-5 criteria, psychometrics, video game addiction, confirmatory factor analysis, measurement invariance, clinical assessment, psychological screening

3. Authors

The Internet Gaming Disorder Scale – Short Form was conceptualized, developed, and validated through collaborative clinical and psychometric research conducted by:

• Dr. Halley M. Pontes, Ph.D. — Department of Psychological Sciences, Birkbeck, University of London, United Kingdom; previously associated with the International Gaming Research Unit, Psychology Division, Nottingham Trent University, United Kingdom. Dr. Pontes is a recognized expert in behavioral addictions, cyberpsychology, and advanced psychometrics.
• Professor Mark D. Griffiths, Ph.D. — Distinguished Professor of Behavioural Addiction, International Gaming Research Unit, Psychology Department, Nottingham Trent University, United Kingdom. Professor Griffiths is a world-renowned pioneer in the investigation of technological addictions, pathological gambling, and behavioral addictions.

Correspondence regarding original psychometric validation of the IGDS9-SF can be directed to the corresponding authors via Nottingham Trent University ([email protected]) or Birkbeck College, University of London ([email protected]).

4. Purpose

The primary purpose of the Internet Gaming Disorder Scale – Short Form (IGDS9-SF) is to provide a brief, psychometrically sound, standardized self-report instrument capable of assessing both the continuous severity of Internet Gaming Disorder (IGD) and the categorical presence of clinically relevant gaming addiction symptoms in adolescents, emerging adults, and adult populations. Prior to the formal publication of the DSM-5 by the American Psychiatric Association (APA) in 2013, the field of behavioral addiction was plagued by significant conceptual fragmentation. Over two decades of empirical inquiry had yielded dozens of non-standardized assessment tools adapted arbitrarily from pathological gambling or substance-related disorders, lacking consensus regarding operational thresholds, underlying constructs, or psychopathological boundaries.

With the inclusion of Internet Gaming Disorder in Section III of DSM-5 as a condition requiring further research, the scientific community obtained an authoritatively consolidated framework consisting of nine distinct clinical criteria. Pontes and Griffiths designed the IGDS9-SF to operationalize these exact nine criteria within a minimalist, nine-item instrument that minimizes participant response burden while maintaining full clinical coverage. The instrument is engineered to distinguish genuine behavioral pathology from benign, high-engagement gaming, addressing a common critique in digital cyberpsychology that pathologizes normative, non-problematic immersion in video games.

From a research perspective, the IGDS9-SF facilitates epidemiological surveillance, transnational comparisons, structural equation modeling, and longitudinal tracking of risk and protective factors associated with disordered gaming. Clinically, the scale functions as an efficient diagnostic screener in outpatient psychiatric clinics, university counseling centers, school psychological services, and specialized behavioral addiction units. It enables clinicians to rapidly identify clients who endorse clinically significant thresholds of gaming-related impairment, capture symptom severity along a dimensional spectrum, and monitor therapeutic outcomes across evidence-based interventions such as Cognitive Behavioral Therapy (CBT).

5. Psychological Construct

The IGDS9-SF operationalizes Internet Gaming Disorder as a multidimensional, behavioral addiction construct captured parsimoniously within a single overarching latent dimension. In accordance with the DSM-5 framework, disordered gaming represents persistent and recurrent engagement with video games—whether played online or offline, on computers, consoles, smartphones, or dedicated devices—leading to clinically significant impairment or distress over a 12-month period. The nine items of the IGDS9-SF operationalize the following specific clinical dimensions:

5.1. Preoccupation (Cognitive Salience)

Preoccupation refers to an obsessive cognitive absorption with gaming activities. Individuals experiencing cognitive salience spend excessive amounts of mental energy reflecting on past gaming experiences, strategizing for upcoming gameplay, or continually anticipating their next gaming session throughout daily life. Even when physically disconnected from gaming hardware, their attentional focus is dominated by thoughts of the virtual environment, impairing concentration on educational, occupational, or social tasks.

5.2. Withdrawal Symptoms

Withdrawal manifests when gaming is interrupted, restricted, or rendered impossible due to environmental constraints. Disordered gamers experience acute emotional and affective dysregulation characterized by irritability, generalized anxiety, restlessness, moodiness, or profound sadness. Unlike physiological substance withdrawal, behavioral withdrawal in IGD is primarily marked by psychological distress stemming from the abrupt loss of the rewarding or mood-regulating digital stimuli.

5.3. Tolerance

Tolerance denotes the progressive neurobehavioral need to spend increasingly longer durations immersed in gaming activities or to engage in increasingly complex, challenging, or stimulating gaming scenarios to attain the desired level of satisfaction, emotional relief, or neurochemical arousal. Over time, baseline gaming durations that previously induced positive affect or euphoric engagement become insufficient, compelling the individual to escalate their time commitment.

5.4. Loss of Control (Inability to Reduce Use)

Loss of control represents repeated, unsuccessful executive efforts to regulate, restrict, delay, or cease gaming activity. Disordered gamers frequently form explicit intentions to play for a limited timeframe (e.g., 30 minutes), yet repeatedly fail to adhere to these self-imposed boundaries, playing for multiple unplanned hours. This executive dysfunction reflects diminished inhibitory control and compromised self-monitoring capabilities.

5.5. Loss of Other Interests (Displacement of Hobbies)

This dimension captures the systematic displacement and abandonment of previously enjoyed recreational pursuits, hobbies, sports, social engagements, and alternative pastimes as a direct consequence of gaming. The individual’s motivational sphere narrows dramatically, such that non-gaming activities are perceived as unrewarding, boring, or burdensome, leaving gaming as the virtually exclusive source of positive reinforcement.

5.6. Continued Excessive Use Despite Psychosocial Problems

Disordered gamers continue their intensive gaming habits despite having clear conscious awareness and explicit knowledge of the psychological, physical, or interpersonal problems provoked or exacerbated by the behavior. These consequences may include chronic sleep deprivation, severe daytime fatigue, migraine headaches, musculoskeletal pain, declining academic transcripts, deteriorating occupational performance, or persistent family friction.

5.7. Deception and Concealment

Deception involves intentionally concealing, disguising, or lying about the true extent, duration, and frequency of video game engagement to family members, romantic partners, therapists, employers, or peers. Disordered gamers actively minimize their play hours, manipulate parental tracking software, or covertly play late at night to avoid interpersonal conflict and external regulation.

5.8. Escape and Mood Modification

This dimension operationalizes negative reinforcement mechanisms, wherein gaming is utilized primarily as a maladaptive psychological coping strategy to avoid, escape, or neutralize adverse psychological states, such as chronic stress, depression, generalized anxiety, feelings of inadequacy, guilt, or interpersonal alienation. Gaming provides an immersive digital refuge that distracts the individual from real-world distress.

5.9. Jeopardizing or Sacrificing Significant Relationships and Opportunities

The ultimate hallmark of functional impairment occurs when the individual risks, damages, or completely loses meaningful interpersonal relationships (e.g., divorce, separation, familial estrangement), educational advancements (e.g., academic suspension, dropping out of school or university), or occupational opportunities (e.g., job termination, demotion) directly attributable to prioritized and uncontrollable gaming behaviors.

6. Theoretical Framework

The conceptual foundation of the IGDS9-SF integrates several seminal psychological and neurobiological theories of addiction, bridging classic behavioral addiction formulations with modern neurocognitive architectures.

6.1. The Component Model of Addiction (Griffiths, 2005)

The operational framework of the IGDS9-SF is grounded in Mark Griffiths’ Component Model of Addiction, which posits that all addictions—whether chemical or behavioral—share six essential core components:

• Salience: Gaming becomes the single most important activity in the person’s life, dominating thinking (preoccupations and cognitive distortions), feelings (cravings), and behavior.
• Mood Modification: The subjective emotional experience reported by individuals as a consequence of engaging in gaming (e.g., experiencing a tranquilizing escape or an arousing buzz).
• Tolerance: The process whereby increasing amounts of gaming are required to achieve the former mood-modifying effects.
• Withdrawal Symptoms: Unpleasant emotional states and physical effects that occur when gaming is suddenly discontinued or restricted.
• Conflict: Interpersonal conflict between the gamer and those around them, as well as intrapersonal conflict within the individual arising from feelings of loss of control.
• Relapse: The tendency for repeated reversions to earlier patterns of excessive gaming following periods of abstinence or control.

The IGDS9-SF maps the nine DSM-5 criteria directly onto these overarching theoretical components, providing a theoretically unified representation of behavioral addiction pathology.

6.2. The I-PACE Model (Interaction of Person-Affect-Cognition-Execution)

The contemporary theoretical underpinnings of the IGDS9-SF are further elucidated by the I-PACE model developed by Matthias Brand and colleagues (2016, 2019). The I-PACE framework views Internet-use disorders as emerging from complex, dynamic interactions between predisposing core person characteristics (P: genetics, neurobiology, psychopathology, personality traits such as high impulsivity or low self-esteem), subjective cognitive and affective perceptions of external/internal triggers (A: cue reactivity, craving, negative mood states), cognitive processing styles (C: cognitive biases, implicit associations, expectancies), and executive control mechanisms (E: inhibitory control, decision-making deficits).

Within this framework, the IGDS9-SF captures symptoms across both early and late stages of the addiction trajectory. In early stages, gaming is driven largely by positive reinforcement (gratification, mood enhancement, social bonding). Over time, as neurobiological sensitization and prefrontal executive control weaken, the behavior shifts toward habit formation and negative reinforcement (compulsive gaming to alleviate withdrawal-induced negative affect, automatic cue-reactivity, and severe behavioral preservation despite functional catastrophic outcomes).

6.3. Compensatory Internet Use Theory (Kardefelt-Winther, 2014)

Complementing addiction-based models, the Compensatory Internet Use Theory (CIUT) posits that excessive engagement in online gaming frequently emerges as a compensatory coping mechanism to satisfy unmet psychosocial needs or regulate negative real-life emotionality. Disordered gaming arises when individuals lack alternative, adaptive coping repertoires, leading to over-reliance on virtual worlds for social belonging, achievement, autonomy, and emotional stabilization. Item 8 of the IGDS9-SF specifically operationalizes this compensatory mechanism.

7. Validity

The psychometric validity of the IGDS9-SF has been subjected to rigorous empirical evaluation across global populations, consistently establishing robust content, construct, convergent, discriminant, and criterion-related validity.

7.1. Content and Face Validity

Because each of the nine items in the IGDS9-SF was crafted to map directly onto one of the nine DSM-5 criteria without omissions or structural redundancies, content validity is structurally intrinsic to the scale. Expert psychometric panels, clinicians, and researchers have repeatedly corroborated that the items comprehensively cover the intended diagnostic spectrum while remaining concise and accessible to both youth and adult respondents.

7.2. Convergent and Concurrent Validity

Extensive studies worldwide have corroborated the convergent validity of the IGDS9-SF by assessing its correlations with established measures of gaming pathology, general internet addiction, gaming habits, and psychological distress:

• Other Gaming Addiction Scales: The IGDS9-SF shows large positive correlations with established behavioral measures, such as the Game Addiction Scale (GAS) (r ≈ .70 to .84) and the Internet Gaming Disorder Test (IGD-20) (r ≈ .80 to .91).
• Time Spent Gaming: Statistically significant moderate positive correlations have been consistently documented between IGDS9-SF scores and total hours spent playing video games per week, both on weekdays (r ≈ .30 to .45) and weekends (r ≈ .35 to .52).
• Psychological Distress: Disordered gaming scores correlate positively with validated measures of depression (e.g., BDI-II, PHQ-9, r ≈ .35 to .55), generalized anxiety (e.g., GAD-7, r ≈ .30 to .48), stress (e.g., DASS-21, r ≈ .38 to .50), and loneliness (UCLA Loneliness Scale, r ≈ .28 to .42).
• Self-Esteem and Life Satisfaction: Significant negative correlations are observed between IGDS9-SF scores and global self-esteem (Rosenberg Self-Esteem Scale, r ≈ -.25 to -.40) and life satisfaction (SWLS, r ≈ -.28 to -.45).

7.3. Discriminant Validity

Crucially, the IGDS9-SF effectively discriminates between excessive, highly passionate engagement and genuine clinical pathology. Highly engaged non-problematic gamers frequently score high on weekly gaming time and cognitive preoccupation without endorsing negative consequences, deception, or relationship loss. Receiver Operating Characteristic (ROC) curve analyses and latent profile analyses consistently demonstrate that the IGDS9-SF distinguishes clinical IGD cases from healthy gamers with high sensitivity (> 90%) and specificity (> 85%).

7.4. Cross-Cultural Invariance

The IGDS9-SF has been translated, adapted, and validated in more than 20 languages across Asia, Europe, North America, South America, and the Middle East, including Portuguese, Spanish, Italian, German, French, Turkish, Persian, Chinese, Japanese, Korean, Polish, and Arabic. Multigroup Confirmatory Factor Analysis (MGCFA) consistently establishes configural, metric (weak), and scalar (strong) measurement invariance across genders (male vs. female), age groups (adolescents vs. adults), and cultural contexts, confirming that the underlying construct is measured equivalently across disparate demographic groups.

8. Reliability

The IGDS9-SF has demonstrated outstanding psychometric reliability across numerous independent empirical investigations spanning diverse clinical and non-clinical cohorts.

8.1. Internal Consistency

In the original seminal validation study by Pontes and Griffiths (2015) involving two distinct online gamer samples (Sample 1: N = 1,060; Sample 2: N = 337), the scale demonstrated high internal consistency reliability, with Cronbach’s alpha coefficients of α = .87 and α = .88, respectively. Subsequent worldwide validation studies have consistently confirmed strong internal reliability, frequently reporting coefficients exceeding the recommended .80 benchmark:

• Italian Validation (Monacis et al., 2016): Cronbach’s α = .91, McDonald’s ω = .92.
• Portuguese Validation (Pontes et al., 2016): Cronbach’s α = .87, McDonald’s ω = .88.
• Spanish Validation (Beranuy et al., 2020): Cronbach’s α = .85 to .88.
• Turkish Validation (Evren et al., 2018): Cronbach’s α = .89, item-total correlations ranging from .51 to .72.
• Persian Validation (Wu et al., 2017): Cronbach’s α = .90.
• Chinese Validation (Yamasaki et al., 2020): Cronbach’s α = .90, composite reliability (CR) = .91.
• German Validation (Montag et al., 2019): Cronbach’s α = .86.

8.2. Test-Retest Reliability and Temporal Stability

Longitudinal studies and test-retest investigations assessing intervals ranging from two weeks to six months have documented substantial temporal stability. Intraclass Correlation Coefficients (ICC) typically range between .80 and .89 across short intervals (2 to 4 weeks), indicating that while IGD symptoms can fluctuate with therapeutic intervention or life transitions, the scale measures a stable psychological trait-like behavioral pattern over time.

9. Factor Analysis

Extensive exploratory and confirmatory psychometric evaluations have rigorously scrutinized the latent structure of the IGDS9-SF, establishing its empirical dimensionality.

9.1. Exploratory Factor Analysis (EFA)

During preliminary structural testing, exploratory factor analyses (utilizing principal axis factoring and maximum likelihood estimation with both orthogonal and oblique rotations) consistently yield an unambiguous single-factor solution. Scree plot inspections, parallel analyses, and Kaiser-Guttman eigenvalues (> 1.0) unambiguously support unidimensionality, with the primary factor accounting for between 48% and 62% of the total variance across diverse datasets.

9.2. Confirmatory Factor Analysis (CFA)

Confirmatory Factor Analyses across both original and international adaptation studies have verified the unidimensional model’s superior fit to empirical data. In Pontes and Griffiths’ (2015) initial validation, CFA fit indices confirmed excellent model fit:

• Sample 1: χ²(27) = 117.84, p < .001; Comparative Fit Index (CFI) = .970; Tucker-Lewis Index (TLI) = .960; Root Mean Square Error of Approximation (RMSEA) = .056 (90% CI: .046–.067); Standardized Root Mean Square Residual (SRMR) = .038.
• Sample 2: χ²(27) = 54.49, p = .001; CFI = .967; TLI = .956; RMSEA = .055 (90% CI: .034–.076); SRMR = .042.

Standardized factor loadings across all nine items are consistently robust and statistically significant (p < .001). In published literature, factor loadings generally span between .56 and .84:

• Item 1 (Preoccupation): λ = .56 to .72
• Item 2 (Withdrawal): λ = .62 to .78
• Item 3 (Tolerance): λ = .64 to .79
• Item 4 (Loss of Control): λ = .68 to .83
• Item 5 (Loss of Other Interests): λ = .65 to .80
• Item 6 (Continued Use): λ = .70 to .84
• Item 7 (Deception): λ = .60 to .75
• Item 8 (Escape / Mood Modification): λ = .55 to .71
• Item 9 (Jeopardizing Opportunities): λ = .66 to .82

9.3. Item Response Theory (IRT) Analysis

Modern psychometric evaluations employing two-parameter logistic (2PL) and Graded Response Models (GRM) have provided deeper insight into item-level performance. GRM parameters demonstrate high discrimination parameters (α > 1.35 across all items), indicating that all items effectively differentiate individuals with varying degrees of latent IGD severity (θ). Threshold parameters (β) indicate that items such as Item 9 (jeopardizing relationships/opportunities) and Item 7 (deception) provide high information at elevated levels of latent trait severity, functioning as markers for severe, clinical manifestation. Conversely, Item 1 (preoccupation) and Item 8 (mood modification) capture lower thresholds of the continuum, reflecting symptoms common even in borderline or highly involved non-disordered gamers.

10. Instrument / Measurement Tool

• Full Instrument Name: Internet Gaming Disorder Scale – Short Form (IGDS9-SF)
• Construct Assessed: Severity of Internet Gaming Disorder (IGD) and operational presence of the 9 DSM-5 criteria
• Administration Format: Paper-and-pencil self-report or computer-administered digital questionnaire
• Completion Time: Approximately 2 to 4 minutes
• Target Population: Adolescents (ages 11+) and adults engaging in video game activities across any gaming platform
• Number of Items: 9 single-statement items
• Item Structure: Each item operationalizes exactly one of the nine DSM-5 proposed criteria: (1) Preoccupation, (2) Withdrawal, (3) Tolerance, (4) Loss of control, (5) Reduced other interests, (6) Continued use despite problems, (7) Deception, (8) Escape/mood modification, and (9) Jeopardizing relationships/opportunities.
• Authentic Response Scale: 5-point Likert scale:
  • 1 = Never
  • 2 = Rarely
  • 3 = Sometimes
  • 4 = Often
  • 5 = Very Often
• Scoring and Quantification Rules:
  • Total Score Calculation: Items are summed across all 9 questions to produce a continuous composite score ranging from 9 to 45. There are no reverse-scored items.
  • Dimensional Interpretation: Higher total scores reflect greater severity of gaming-related problems, functional impairment, and psychopathological symptom burden.
  • Diagnostic / Screening Thresholds: In alignment with DSM-5 diagnostic guidelines requiring the presence of at least 5 out of 9 criteria, two primary operational approaches are utilized in research and clinical practice:
    • Liberal/Moderate Threshold: Endorsement of an item as present is operationalized as a response of 4 (“Often”) or 5 (“Very Often”). Individuals endorsing at least 5 of the 9 items at this level meet the screening threshold for disordered gaming.
    • Conservative Threshold: Endorsement of an item as present is operationalized strictly as answering 5 (“Very Often”) across at least 5 criteria, significantly minimizing false-positive classifications in non-clinical epidemiological surveys.
    • Empirical Cutoff Scores: Various ROC and latent class studies suggest continuous cutoff scores ranging between 32 and 36 out of 45 as optimal benchmarks for identifying individuals at high risk for clinical IGD.

11. Permissions & Fee and Test Year

The Internet Gaming Disorder Scale – Short Form (IGDS9-SF) was formally published in 2015 in the peer-reviewed journal Computers in Human Behavior by Elsevier. Under standard academic fair use and the authors’ publication terms:

• Research and Non-Commercial Academic Use: The IGDS9-SF is an open-access, free-to-use psychometric instrument for academic, empirical, educational, and clinical research purposes without requiring royalty fees. Researchers and clinicians may utilize the scale in study protocols provided that proper citation and attribution to Pontes and Griffiths (2015) are maintained.
• Commercial and Proprietary Use: Commercial deployment, integration into proprietary healthcare software, digital diagnostic platforms, or commercial health assessments may require formal permissions or licensing from the authors and/or the original copyright holder (Elsevier).
• Contact and Translations: Researchers wishing to produce new formal cross-cultural adaptations or register language translations are encouraged to contact Dr. Halley M. Pontes or Professor Mark D. Griffiths to ensure translational consistency and prevent duplicate efforts.

12. References

• American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing. https://doi.org/10.1176/appi.books.9780890425596
• Beranuy, M., Machimbarrena, J. M., Vega-Flores, M. G., Rivera-Flores, G. W., Griffiths, M. D., & Pontes, H. M. (2020). Spanish validation of the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF): Prevalence and psychometric properties. International Journal of Mental Health and Addiction, 18(5), 1369–1384. https://doi.org/10.1007/s11469-019-00161-0
• Brand, M., Young, K. S., Laier, C., Wölfling, K., & Potenza, M. N. (2016). Integrating psychological and neurobiological considerations regarding Internet-use disorders based on the I-PACE model. Neuroscience & Biobehavioral Reviews, 71, 252–266. https://doi.org/10.1016/j.neubiorev.2016.08.018
• Brand, M., Wegmann, E., Stark, R., Müller, A., Wölfling, K., Robbins, T. W., & Potenza, M. N. (2019). The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: Update, generalization to specific Internet-use disorders, and specification. Neuroscience & Biobehavioral Reviews, 104, 1–10. https://doi.org/10.1016/j.neubiorev.2019.06.032
• Evren, C., Evren, B., Dalbudak, E., Topcu, M., & Kutlu, N. (2018). Psychometric properties of the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF) in a Turkish sample of university students. Dusunen Adam: The Journal of Psychiatry and Neurological Sciences, 31(3), 263–271. https://doi.org/10.5350/DAJPN2018310304
• Griffiths, M. D. (2005). A ‘components’ model of addiction within a biopsychosocial framework. Journal of Substance Use, 10(4), 191–197. https://doi.org/10.1080/14659890500114359
• Kardefelt-Winther, D. (2014). A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use. Computers in Human Behavior, 31, 351–354. https://doi.org/10.1016/j.chb.2013.10.059
• Monacis, L., Palo, V. D., Griffiths, M. D., & Sinatra, M. (2016). Validation of the Internet Gaming Disorder Scale – Short-Form (IGDS9-SF) in an Italian-speaking sample. Journal of Behavioral Addictions, 5(4), 683–690. https://doi.org/10.1556/2006.5.2016.083
• Montag, C., Schivinski, B., Sariyska, R., Kothgassner, O. D., & Pontes, H. M. (2019). Psychometric evaluation of the German version of the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF). Addictive Behaviors, 98, 106037. https://doi.org/10.1016/j.addbeh.2019.106037
• Pontes, H. M., & Griffiths, M. D. (2015). Measuring DSM-5 internet gaming disorder: Development and validation of a short psychometric scale. Computers in Human Behavior, 45, 137–143. https://doi.org/10.1016/j.chb.2014.12.006
• Pontes, H. M., Király, O., Demetrovics, Z., & Griffiths, M. D. (2014). The conceptualisation and measurement of DSM-5 Internet Gaming Disorder: The development of the IGD-20 Test. PLOS ONE, 9(10), e110137. https://doi.org/10.1371/journal.pone.0110137
• Pontes, H. M., Stavropoulos, V., & Griffiths, M. D. (2017). Measurement invariance of the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF) across the United States, the United Kingdom, and India. Cyberpsychology, Behavior, and Social Networking, 20(11), 693–701. https://doi.org/10.1089/cyber.2017.0252
• Wu, T. Y., Lin, C. Y., AÅŸun, S., Griffiths, M. D., & Pontes, H. M. (2017). Investigating the factor structure, measurement invariance, and structural validity of the Persian Internet Gaming Disorder Scale–Short-Form (IGDS9-SF) among Iranian adolescents. International Journal of Mental Health and Addiction, 16(5), 1279–1293. https://doi.org/10.1007/s11469-017-9844-3
• Yamasaki, S., Pontes, H. M., Tsuboi, S., & Griffiths, M. D. (2020). Cross-cultural psychometric evaluation of the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF) among Japanese and Taiwanese university students. Frontiers in Psychiatry, 11, 563. https://doi.org/10.3389/fpsyt.2020.00563

13. Items of the Scale