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Designers of digital interventions for mental health often leverage interactions from games because the intrinsic motivation that results from game-based interventions may increase participation and translate into improved treatment efficacy. However, there are outstanding questions about the suitability (eg, are desktop or mobile interventions more appropriate?) and intervention potential (eg, do people with depression activate enough to play?) of games for mental health.
In this paper, we aimed to describe the presently unknown relationship between gaming activity and indicators of well-being so that designers make informed choices when designing game-based interventions for mental health.
We gathered validated scales of well-being (Beck’s Depression Inventory [BDI-II], Patient Health Questionnaire [PHQ-9], trait anxiety [TA], and basic psychological needs satisfaction [BPNS]), play importance (control over game behavior: control; gamer identity: identity), and play behavior (play frequency, platform preferences, and genre preferences) in a Web-based survey (N=491).
The majority of our participants played games a few times a week (45.3%, 222/490) or daily (34.3%, 168/490). In terms of depression, play frequency was associated with PHQ-9 (
Our results suggest that games are a suitable approach for mental health interventions as they are played broadly by people across a range of indicators of mental health. We further unpack the platform preferences and genre preferences of players with varying levels of well-being.
The prevalence of mental illness is on the rise [
There are several reasons why treatment of mental illness has not evolved to meet the growing demand. First, health care systems cannot handle the burden—there are not enough trained professionals to provide treatment to those in need [
These limitations in access to treatment cannot be addressed solely by growing the existing mental health system [
Results such as these demonstrate that technology-based mental health interventions offer promise for use in self-help or as an adjunct to clinical treatment [
One solution is to introduce external regulation into digital interventions. For example, we could design systems that require check-ins or provide tangible benefits for daily participation [
One common approach to increasing intrinsic motivation with a digital system is to increase the inherent enjoyment of the activity itself by leveraging the motivational pull of digital games [
For example, a common technique used in CBT is attentional retraining of a participant’s attention away from maladaptive cognitive processes [
In an even broader context, games offer an opportunity for improving mental health at a large-scale as it is known that people use games to recover from noxious moods—a process known as mood management. Mood repair through escapism is included in validated scales on both motivations for play [
It is clear that there are potential benefits of motivating participation in digital interventions for mental health by introducing game-based elements; however, there are several outstanding questions about the whether or not games are really appropriate in this context and how great their intervention potential truly is in this domain. For example, we may argue that games have a high intervention potential because people who have low need satisfaction experience greater compulsion to play games [
Taken together, these questions highlight a problem in our understanding of how games can be used to create digital interventions in mental health:
To investigate the intervention potential of digital games, we gathered survey data from 491 online participants who completed validated scales related to their well-being, including on their levels of depression (Beck’s Depression Inventory [BDI-II], Patient Health Questionnaire [PHQ-9], their trait anxiety [TA]), and their satisfaction of their basic psychological needs satisfaction (BPNS). We also asked questions about the importance of play in their lives, including about the control they felt over their gaming behavior and how much they identified as a gamer. Finally, we asked questions about play behavior, including their frequency of play, platform preferences, and genre preferences. Our results suggest that games are a suitable approach for mental health interventions as they are played broadly by people across all indicators of mental health. Throughout the remainder of this paper, we further unpack the play frequency, platform preferences, and genre preferences of players with varying levels of well-being.
Our study was designed to answer several research questions about the intervention potential and suitability of games for mental health interventions. Specifically:
RQ1: Are people with depression or anxiety activating enough to play games? How frequently do they play?
RQ2: Are gamers with depression or anxiety part of the growing group who play games on a mobile platform or are they more likely to play in the comfort of their homes on a desktop or console platform?
RQ3: Do players with depression or anxiety play casual games, or do they prefer more complex and immersive genres of games?
We recruited 491 participants through Amazon Mechanical Turk (AMT), which acts as a broker between requesters who offer Human Intelligence Tasks (HITs) and paid workers who complete them. Participants received compensation of US $2.5 for their participation, which took approximately 15 min. Ethical approval was obtained from the University of Saskatchewan Behavioral Research Ethics Board, and participants were asked to provide informed consent at the beginning of the task. To comply with ethical guidelines, the task was only available to workers from the United States who were older than 18 years. Additionally, only workers with an approval rate above 90% were offered the task as a means of quality control.
We gathered indicators of well-being, indicators of the importance of play, and information regarding gaming behaviors.
The BDI-II is a psychometric test that measures depression using 21 questions that address categories of behavior that are associated with depression, including pessimism, past failure, self-dislike, suicidal thoughts, crying, agitation, and loss of interest in sex. For each question, participants were asked how they have been feeling over the last two weeks, including today. Responses range from not experiencing a feeling or displaying a behavior, for example, “I do not feel sad,” or to an extreme expression of the same feeling or behavior, for example, “I am so sad or unhappy that I can’t stand it.” Responses are then mapped to a severity rating between 0 and 3. Responses are added into a total score (Cronbach alpha=.947); the BDI-II also provides threshold values that indicate categories of depression.
The PHQ-9 asks participants to rate the frequency of negative experiences, over the last two weeks (eg, “Little interest or pleasure in doing things,” “Feeling bad about yourself or that you’re a failure or have let yourself or your family down”) on a scale from “Not at all” to “Nearly every day.” Each rating was assigned a value from 0 to 3. All items were added to create a single score reflecting an overall level of depression (Cronbach alpha=.903).
TA was measured using the 20-item trait scale from the State-Trait Anxiety Scale (STAI; [
To measure how much importance gaming has in a person’s life, we measured
Additionally, we measured
We gathered subjective measures of play habits and preferences.
Participants indicated their
Participants indicated their
Clusters of genre preferences from the K-means clustering.
Although AMT has been shown to be reliable as a recruitment tool for research [
BDI-II, PHQ-9, and TA data were summed into a single score reflecting level of depression, and TA respectively. As shown in
To investigate the relationship between mental health and play behavior, we performed multivariate analysis of variance (MANOVA), with play behavior variables (play frequency, platform preference cluster, genre preference cluster) as factors, and indicators of well-being (BDI-II, PHQ-9, STAI trait, BPNS) and importance of play (control, identity) as dependent measures, controlling for sex and age. It is important to note that the predictor variables are not randomly assigned, but reflect the choices of participants. Therefore, our results cannot be interpreted as a causal relationship between the factor and the measure (as is common with ANOVA interpretation), but rather as an indicator of a statistically significant relationship between a categorical variable and a continuous variable. All analyses were performed using SPSS 24 (IBM Corp).
Bar charts of the constructs of well-being (Beck’s Depression Inventory [BDI-II], Patient Health Questionnaire [PHQ-9], Trait Anxiety, and Need Satisfaction) displayed for each level of time spent (less, a few times per week, every day). For each construct, the chart shows the count per bin on the x-axis, represented as a percentage of participants in that level of time spent.
The age of our sample ranged between 18 and 73 years (mean 34.1, SD 9.8); furthermore, as
Stacked bar chart of frequency of play and gender.
Bar charts of the constructs of age, loss of control, and identity displayed for each level of time spent (less, a few times per week, every day). For each construct, the chart shows the count per bin on the x-axis, represented as a percentage of participants in that level of time spent.
Means and standard deviations (SD) for the indicators of well-being and importance of play for: (Top) frequency of play groups, (Middle) platform clusters, and (Bottom) genre clusters.
There were significant correlations between the dependent measures. As expected, CPB was correlated with gamer identity (
Frequency of play showed a significant relationship with CPB (
In terms of genre preference, we found significant relationships with CPB (
Platform preference showed a significant effect on gamer identity (
Frequency of play showed a significant relationship with PHQ-9 (
Furthermore, when we consider just those players who are classified as having significant depression (n=35) according to the BDI-II [
Platform preferences showed a significant relationship with PHQ-9 (
TA shows no significant relationship with frequency of play (
Need satisfaction showed no significant relationship with frequency of play (
In summary, our results for importance of play showed that people who play frequently identify more as a gamer and feel less in control over their play behavior. It is not a surprise that investing more in an activity makes this activity a bigger part of our life and is integrated more into our identity [
In terms of the effects on indicators of well-being, we showed that playing every day was associated with higher scores on the BDI-II and PHQ-9, but did not affect TA or need satisfaction. It is not surprising that playing every day is associated with indicators of poorer mental health, as research on pathological gaming has found that low need satisfaction is associated with the experience of game addiction [
Furthermore, desktop-only players scored higher on the PHQ-9 and lower on need satisfaction; however, genre preference was not significantly related to any indicator of well-being. This last result bodes well for intervention designers who wish to incorporate game-based elements into their digital interventions, as it appears that they are not limited in terms of the appeal of different game mechanics or genres and can use what works best for their particular intervention design. However, the finding that playing on desktop computers alone (as opposed to consoles, mobile devices, or all three) is associated with indicators of poorer mental health suggests that intervention designers might want to account for this preference when deciding on a platform for delivery.
In terms of the research questions that we set out to answer:
RQ1. Are people with depression or anxiety activating enough to play games? How frequently do they play?
The majority of our participants played games a few times a week or daily. In addition, PHQ-9 scores were higher for those who played daily than for those who played a few times a week or less, and BDI-II scores were higher for those who played daily than for those who played once a week or less.
RQ2. Are gamers with depression or anxiety part of the growing group who play games on a mobile platform or are they more likely to play in the comfort of their homes on a desktop or console platform?
Depression and low need satisfaction were both significantly associated with desktop-only play.
RQ3. Do players with depression or anxiety play casual games, or do they prefer more complex and immersive genres of games?
Genre preferences were not associated with any indicators of mental health.
Our results suggest that games may be a valuable approach for the design of digital mental health interventions. Here, we discuss three main advantages of game-based intervention design for mental health based on our results and previous work [
We motivated the contribution of this paper by arguing that leveraging the motivational pull of games [
Although people from different demographics may be more susceptible to mental health issues (eg, adolescents [
Our previous research on computer games spans various ages of players, ranging from a focus on children with developmental disabilities [
Because mental health issues are prevalent across demographic groups, it is important to ensure that people have access to treatment, independent of their work schedule, geographic location, or the capacity of the health care system. Games are generally accessible, independent of time of the day or location (thanks to the increased prevalence of mobile games). Because digital content can be delivered to any place that has Internet access, games are accessible in most geographical locations, which gives them advantages over traditional psychotherapy for countries with distributed and remote populations, such as in Nunavut—the territory in northern Canada that has a suicide rate 10 times greater than the rest of the country [
Our results demonstrate several important relationships between the habits and preferences of players and indicators of their mental health. However, there are several limitations that should be addressed through future work. First, the survey uses self-report measures of play behavior and is subject to all the biases present in self-report. Although the indicators of mental health also use self-report, the measures that we used are standard in terms of diagnosing depression (ie, BDI-II) and are recommended by the World Health Organization for assessing mental health (ie, the PHQ-9). Second, the survey was only available to be taken by the US residents, and thus our results are not generalizable beyond this particular context. Third, our results provide information on the play habits and preferences of people with varying levels of depression, anxiety, and need satisfaction to provide guidance to developers of digital interventions for mental health. Because we do not randomly assign people to experimental conditions, there is no intention in this paper of claiming causal links between game play habits and mental health. Research on pathological gaming [
In this paper, we use data from a Web-based survey (N=491) to describe the relationships between gameplay habits, gameplay preferences, and indicators of mental health by answering research questions about the differential gameplay habits of people with varying levels of depression, anxiety, and need satisfaction. In general, we reveal that the vast majority of people in our sample play games a few times a week or more, and that playing daily is associated with indicators of depression. Desktop play was also associated with higher indicators of depression and lower need satisfaction. As expected, those who played more had identified more as a gamer and had less control over their gameplay.
Our results suggest that games are a suitable approach for mental health interventions as they are played broadly by people across a range of indicators of mental health, have strong motivational pull, and are accessible to players from a broad range of demographics. Our contribution is of interest to the community as we establish that games are an approach with great potential to add to the growing literature on digital interventions for improving mental health.
Description of one-item measure of gamer identity.
attention-bias modification training
Amazon Mechanical Turk
analysis of variance
Beck’s Depression Inventory
basic psychological needs satisfaction
cognitive behavioral therapy
control over play behavior
Entertainment Software Association
first-person shooter
Human Intelligence Task
multivariate analysis of variance
massively multiplayer online role-playing game
Multiplayer online battle arena
Patient Health Questionnaire
post-traumatic stress disorder
randomized controlled trial
role-playing game
self-determination theory
State-Trait Anxiety Scale
trait anxiety
United States
We thank NSERC and SWaGUR for funding, members of the Interaction Lab for support (in particular Colby Johannson for his efforts in creating BOF), and our participants for contributing data.
None declared.