Addictive Behaviors Reports, volume 14, article 100391, December 2021 (online 1 November 2021)
- Open access
- 2,768 German-speaking gamers
- Online survey
- MANCOVA
- Germany, Austria, Switzerland
- Open data (OSF)
Free full text: the open access article (CC BY 4.0), re-typeset as a clean PDF with the same content as the published version. Please cite the published version.
- gaming disorder
- internet gaming disorder
- gaming mode
- offline gaming
- online gaming
- gaming device
- ICD-11
- DSM-5
- structural characteristics of video games
- multiplayer games
- desktop computer gaming
- console gaming
- mobile gaming
- loneliness
- attention problems
- depression
- Gaming Disorder Test (GDT)
- Internet Gaming Disorder Scale–Short-Form (IGDS9-SF)
- UCLA Loneliness Scale
- PHQ-8
- online survey
- MANCOVA
- open data
- German-speaking countries
The WHO’s split of gaming disorder into a mainly online and a mainly offline form makes sense: in 2,768 German-speaking gamers, those who played mostly online had the most symptoms, followed by mixed and then offline gamers. Gamers who mostly played on a desktop computer also had the highest symptom scores and played the longest.
Key findings
- Online gamers show the most gaming disorder symptoms. Gaming Disorder Test scores were highest for gamers who mainly played online (9.27), lower for those playing online and offline equally (8.51) and lowest for offline gamers (7.32); all three groups differed significantly (Montag et al., 2021).
- Online gamers also play the longest. Online gamers played 23.0 hours a week on average, against 20.7 for mixed and 12.7 for offline gamers; gaming mode explained about 4% of the variance in gaming time and about 2% in disorder scores (Montag et al., 2021).
- Desktop computer gamers score highest. Gamers who mostly used a desktop computer reported the most weekly gaming (24.2 hours) and the highest gaming disorder scores under both the WHO and APA frameworks, compared with console, laptop and mobile gamers (Montag et al., 2021).
- Online play dominates on every device. 54% of participants mainly played online, 27% online and offline, and 19% offline; online gaming was the most common mode for every device (Montag et al., 2021).
At a glance
- Design
- Cross-sectional online survey on the team’s German-language gaming disorder self-test platform, promoted via radio, TV and social media, May 2019 to August 2020
- Participants
- 2,768 gamers (2,356 men, 412 women; mean age 28.7, SD 11.9) from Germany (2,126), Switzerland (475), Austria (126), Luxembourg (10) and other countries (31); 13 professional gamers
- Gaming mode
- Mainly online (n = 1,490), mixed online and offline (n = 740) or mainly offline (n = 538)
- Gaming device
- Console (n = 772), desktop computer (n = 1,441), laptop (n = 278) or mobile device (n = 277)
- Measures
- Gaming Disorder Test (WHO framework), IGDS9-SF (APA framework), three-item UCLA Loneliness Scale, attention problems scale (Swing et al., 2010) and PHQ-8 depression; weekly time spent gaming
- Analysis
- t-tests by gender, Pearson correlations, χ² test of mode by device, and MANCOVAs with gender and gaming mode (or device) as factors and age as covariate
- Ethics
- University ethics committee approval (2018/95)
- Data
- Full data set on the Open Science Framework (osf.io/ntyhr)
Figure 1. Gaming mode by gaming device
Gaming Disorder Test scores by gaming mode and device
Tables
Table 1. Descriptive statistics and differences between scores of males and females
| Variable | Total (n = 2,768) | Men (n = 2,356) | Women (n = 412) | t | df | p |
|---|---|---|---|---|---|---|
| Weekly time spent gaming | 20.39 (15.73) [16] | 20.99 (15.80) [18] | 16.97 (14.85) [14] | 4.81 | 2766 | <.001 |
| Gaming Disorder | 8.69 (3.62) [8] | 8.85 (3.66) [8] | 7.79 (3.20) [7] | 6.05 | 614,904 | <.001 |
| Internet Gaming Disorder | 17.44 (7.03) [15] | 17.72 (7.15) [16] | 15.89 (6.07) [14] | 5.49 | 628,071 | <.001 |
| Attention Problems | 6.53 (2.56) [6] | 6.48 (2.56) [6] | 6.81 (2.56) [7] | −2.44 | 2766 | <.05 |
| Loneliness | 6.22 (3.04) [6] | 6.16 (3.01) [6] | 6.53 (3.19) [6] | −2.20 | 546,660 | <.05 |
| Depression | 13.78 (4.35) [13] | 13.62 (4.32) [13] | 14.69 (4.39) [14] | −4.63 | 2766 | <.001 |
Mean (SD) [median]. Degrees of freedom as printed (the article uses decimal commas for Welch-corrected df, e.g. 614,904 = 614.904).
Table 2. Correlation analysis between metric variables of interest
| Gaming time | GD | IGD | Attention | Loneliness | Depression | Age | |
|---|---|---|---|---|---|---|---|
| Gaming time | 0.38 | 0.43 | 0.10 | 0.21 | 0.26 | −0.14 | |
| GD | 0.84 | 0.50 | 0.41 | 0.54 | −0.13 | ||
| IGD | 0.47 | 0.45 | 0.58 | −0.15 | |||
| Attention | 0.37 | 0.53 | −0.04* | ||||
| Loneliness | 0.53 | 0.03 (n.s.) | |||||
| Depression | 0.002 (n.s.) |
Gaming time = weekly time spent gaming; GD = Gaming Disorder (GDT); IGD = Internet Gaming Disorder (IGDS9-SF); Attention = attention problems. Pearson correlations, two-tailed; all p < .001 except *p < .05 and n.s. = not significant. Spearman correlations are with the data on the OSF.
Table 3. Associations between different gaming modes (predominantly online, both online and offline, predominantly offline) and gaming variables, attentional problems, loneliness, and depressive tendencies
| Variable | Online (1,490) | Mixed (740) | Offline (538) | F(2,2761) | p | η² |
|---|---|---|---|---|---|---|
| Weekly time spent gaming | 23.02 (16.44) | 20.66 (15.18) | 12.73 (11.38) | 58.59 | <.001 | 0.041 |
| Gaming Disorder | 9.27 (3.74) | 8.51 (3.47) | 7.32 (3.04) | 27.49 | <.001 | 0.020 |
| Internet Gaming Disorder | 18.68 (7.31) | 17.00 (6.70) | 14.63 (5.66) | 31.40 | <.001 | 0.022 |
| Attention Problems | 6.64 (2.61) | 6.35 (2.47) | 6.45 (2.57) | 0.76 | n.s. | 0.001 |
| Loneliness | 6.15 (3.08) | 6.25 (2.95) | 6.36 (3.05) | 0.04 | n.s. | 0.000 |
| Depression | 13.91 (4.46) | 13.69 (4.38) | 13.53 (3.98) | 1.32 | n.s. | 0.001 |
Mean (SD); group sizes in brackets in the header. Results from MANCOVA with gender as a further factor and age as covariate. Score ranges: Gaming Disorder 4–20; Internet Gaming Disorder 9–45; attention problems 3–15; loneliness 3–15; depression 8–32.
Table 4. Associations between different gaming devices and gaming variables, attention problems, loneliness, and depressive tendencies
| Variable | Console (772) | Desktop (1,441) | Laptop (278) | Mobile (277) | F(3,2759) | p | η² |
|---|---|---|---|---|---|---|---|
| Weekly time spent gaming | 17.11 (13.04) | 24.15 (16.89) | 16.50 (13.77) | 13.91 (12.81) | 27.86 | <.001 | 0.029 |
| Gaming Disorder | 8.29 (3.43) | 8.99 (3.68) | 8.47 (3.65) | 8.45 (3.66) | 4.88 | .002 | 0.005 |
| Internet Gaming Disorder | 16.98 (6.87) | 17.99 (7.07) | 16.68 (6.97) | 16.65 (7.12) | 2.68 | <.05 | 0.003 |
| Attention Problems | 6.48 (2.63) | 6.44 (2.51) | 6.68 (2.48) | 6.97 (2.70) | 5.64 | <.001 | 0.006 |
| Loneliness | 5.90 (2.92) | 6.32 (3.05) | 6.59 (3.27) | 6.19 (3.04) | 1.91 | n.s. | 0.002 |
| Depression | 13.65 (4.25) | 13.71 (4.41) | 13.99 (4.43) | 14.25 (4.25) | 1.30 | n.s. | 0.001 |
Mean (SD); group sizes in brackets in the header. Results from MANCOVA with gender as a further factor and age as covariate. Score ranges: Gaming Disorder 4–20; Internet Gaming Disorder 9–45; attention problems 3–15; loneliness 3–15; depression 8–32.
The question
The World Health Organization’s ICD-11 distinguishes gaming disorder that is predominantly online from gaming disorder that is predominantly offline, but no study had tested whether the distinction is meaningful. We compared gamers who play mainly online, mainly offline or both on gaming disorder symptoms, gaming time, loneliness, attention problems and depression, and examined whether the device people play on matters too.
Implications
Practical implications
Gaming mode and device can help clinicians and researchers judge who may be more vulnerable to disordered gaming: online play, and play on desktop computers, went with more symptoms and more hours. Because the industry holds much of the relevant data, for example on freemium games designed to prolong play, cooperation with independent researchers is needed.
Theoretical implications
The study provides the first empirical support for the ICD-11 distinction between predominantly online and offline gaming disorder, and suggests that structural characteristics such as online multiplayer features and the gaming device should be considered in the study of disordered gaming.
Limitations and future research
- All data are self-reported; structured interviews and clinical samples are needed to validate the findings.
- The sample is large but not representative of German-speaking gamers, and few women took part.
- The design is cross-sectional and correlational, so causal conclusions cannot be drawn.
Questions this paper answers
Is online gaming more addictive than offline gaming?
In 2,768 German-speaking gamers, those who played mainly online had higher gaming disorder scores than mixed and offline gamers, though gaming mode explained only about 2% of the variance (Montag et al., 2021).
Does the gaming device matter for gaming disorder?
Yes, modestly. Desktop computer gamers reported the most gaming time and the highest gaming disorder scores of all device groups (Montag et al., 2021).
What does ICD-11 say about online and offline gaming disorder?
ICD-11 distinguishes gaming disorder that is predominantly online (6C51.0), predominantly offline (6C51.1) and unspecified.
Is gaming disorder linked to loneliness and depression?
Yes. Gaming disorder scores correlated with loneliness (r = .41), attention problems (.50) and depression (.54) in this sample, but these did not differ by gaming mode (Montag et al., 2021).
Key concepts
- Gaming disorder (WHO)
- An ICD-11 diagnosis marked by impaired control over gaming, increasing priority given to gaming and continued gaming despite negative consequences, with significant impairment.
- Internet gaming disorder (APA)
- A DSM-5 condition for further study, defined by at least five of nine criteria within 12 months.
- Gaming mode
- Whether a person plays predominantly online, predominantly offline or both equally.
- Structural characteristics
- Design features of games, such as multiplayer functions and reward schedules, that may influence playing behaviour and addictive potential.
Open science and materials
- Full text (PDF) Open access article re-typeset as a clean PDF, including all tables and figures
- Data (OSF) Open Science Framework project with the data set
- Published version Addictive Behaviors Reports (open access)
Study materials
- Measures
- GDT and IGDS9-SF rated from 1 = ‘never’ to 5 = ‘very often’; UCLA loneliness (3 items) and attention problems (3 items) rated from 1 = ‘strongly disagree’ to 5 = ‘strongly agree’; PHQ-8 rated from 1 = ‘not at all’ to 4 = ‘nearly every day’.
- Questions on gaming
- Participants reported whether they mainly played online, offline or both equally, and whether they mainly used a console, desktop computer, laptop or mobile device such as a smartphone.
How to cite
Montag, C., Schivinski, B., & Pontes, H. M. (2021). Is the proposed distinction of gaming disorder into a predominantly online vs. offline form meaningful? Empirical evidence from a large German speaking gamer sample. Addictive Behaviors Reports, 14, Article 100391. https://doi.org/10.1016/j.abrep.2021.100391
Open access under a Creative Commons CC BY 4.0 licence.