The impact of time spent playing video games on well-being is probably too small to be subjectively noticeable and not credibly different from zero

Time spent playing video games is unlikely to impact well-being. Matti Vuorre et al. Royal Society Open Science. July 27 2022. https://doi.org/10.1098/rsos.220411

Abstract: Video games are a massively popular form of entertainment, socializing, cooperation and competition. Games' ubiquity fuels fears that they cause poor mental health, and major health bodies and national governments have made far-reaching policy decisions to address games’ potential risks, despite lacking adequate supporting data. The concern–evidence mismatch underscores that we know too little about games' impacts on well-being. We addressed this disconnect by linking six weeks of 38 935 players’ objective game-behaviour data, provided by seven global game publishers, with three waves of their self-reported well-being that we collected. We found little to no evidence for a causal connection between game play and well-being. However, results suggested that motivations play a role in players' well-being. For good or ill, the average effects of time spent playing video games on players’ well-being are probably very small, and further industry data are required to determine potential risks and supportive factors to health.

3.1. Effects between play and well-being over time

We then focused on our first research objective: determining the extent to which game play affects well-being. Scatterplots describing the associations between (lagged) hours played and well-being are shown in figure 3. The meta-analysis of play time and affect indicated that, on average, video game play had little to no effect on affect, with 68% posterior probability of a positive effect (figure 4, top left). The 95% most likely effect sizes of a one-hour daily increase in play on the 13-point SPANE scale ([−0.09, 0.16]) indicated that the effect was not credibly different from zero: the magnitude and associated uncertainty of this effect suggests that there is little to no practical causal connection (given our assumptions described above) between game play in the preceding two weeks and current affect.

4. Discussion

Evidence about video games' potential impacts so far has suffered from several limitations, most notably inaccurate measurement and a lack of explicit, testable causal models. We aimed to remedy these shortcomings by pairing objective behavioural data with self-reports of psychological states. Across six weeks, seven games and 38 935 players, our results suggest that the most pronounced hopes and fears surrounding video games may be unfounded: time spent playing video games had limited if any impact on well-being. Similarly, well-being had little to no effect on time spent playing.

We conclude the effects of playing are negligible because they are very unlikely to be large enough to be subjectively noticed. Anvari & Lakens [55] demonstrated that the smallest perceptible difference on PANAS, a scale similar to SPANE, was 0.20 (2%) on a 5-point Likert scale. In our study, 1 h day−1 increase in play resulted in 0.03 unit increase in well-being: assuming linearity and equidistant response categories, the average player would have to play 10 h more per day than typical to notice changes (i.e. 2% [0.26 units]) in well-being. Moreover, our model indicated 99% probability that the effect of increasing daily play time by one hour on well-being is too small to be subjectively noticeable. Even if effects steadily accumulated over time—an unrealistic assumption—players would notice a difference only after 17 weeks.

We also studied the roles of motivational experiences during play. Conceptually replicating previous cross-sectional findings [21], our results suggested that intrinsic motivation positively and extrinsic motivation negatively affects well-being. Motivations’ suggested effects were larger, and we can be more confident in them, than those of play time. However, the effect of a 1-point deviation from a player's typical intrinsic motivation on affect did not reach the threshold of being subjectively noticeable (0.10 estimate versus 0.26 threshold). Similarly: we cannot be certain a 1-point increase is a large or a small shift—participants' average range on the 7-point intrinsic motivation scale was 0.36. Until future work determines what constitutes an adequate ‘treatment’, these conclusions remain open to future investigation and interpretation. Our findings, therefore, suggest that amount of play does not, on balance, undermine well-being. Instead, our results align with a perspective that the motivational experiences during play may influence well-being [23]. Simply put, the subjective qualities of play may be more important than its quantity. The extent to which this effect generalizes or is practically significant remains an open question.

4.1. Limitations

Although we studied the play and well-being of thousands of people across diverse games, our study barely scratched the surface of video game play more broadly. Hundreds of millions of players play tens of thousands of games on online platforms. We were only able to study seven games, and thus the generalizability of our findings is limited [29]. To truly understand why people play and to what effect, we need to study a broader variety of games, genres and players. Moreover, we analysed total game time, which is the broadest possible measure of play. Although it is necessary to begin at a broad level [12,56], future work must account for the situations, motivations and contexts in which people play [57]. Additionally, play time is a skewed variable because a minority of players spend a great amount of time playing. This means that the Gaussian assumptions of the RICLPM might be threatened, and future simulation work should investigate how the RICLPM deals with skewed data. We also emphasize that our conclusions regarding the causal nature of the observed associations are tentative: without theoretical and empirical identification of confounds, our and future studies will probably produce biased estimates. Finally, industry-provided behavioural data have their own measurement error and there are differences between publishers. Independent researchers must continue working with industry to better understand behavioural data and their limitations.