Background A lack of ability to inhibit prepotent responses, or more generally a lack of impulse control, is associated with several disorders such as attention-deficit/hyperactivity disorder and schizophrenia as well as general damage to the prefrontal cortex. A stop-signal task (SST) is a reliable and established measure of response inhibition. However, using the SST as an objective assessment in diagnostic or research-focused settings places significant stress on participants as the task itself requires concentration and cognitive effort and is not particularly engaging. This can lead to decreased motivation to follow task instructions and poor data quality, which can affect assessment efficacy and might increase drop-out rates. Gamification—the application of game-based elements in nongame settings—has shown to improve engaged attention to a cognitive task, thus increasing participant motivation and data quality. Objective This study aims to design a gamified SST that improves participants’ engagement and validate this gamified SST against a standard SST. Methods We described the design of our gamified SST and reported on 2 separate studies that aim to validate the gamified SST relative to a standard SST. In study 1, a within-subject design was used to compare the performance of the SST and a stop-signal game (SSG). In study 2, we added eye tracking to the procedure to determine if overt attention was affected and aimed to replicate the findings from study 1 in a between-subjects design. Furthermore, in both studies, flow and motivational experiences were measured. Results In contrast, the behavioral performance was comparable between the tasks (P<.87; BF01=2.87), and the experience of flow and intrinsic motivation were rated higher in the SSG group, although this difference was not significant. Conclusions Overall, our findings provide evidence that the gamification of SST is possible and that the SSG is enjoyed more. Thus, when participant engagement is critical, we recommend using the SSG instead of the SST.

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We describe the design and evaluation of a sub-clinical digital assessment tool that integrates digital biomarkers of depression. Based on three standard cognitive tasks (D2 Test of Attention, Delayed Matching to Sample Task, Spatial Working Memory Task) on which people with depression have been known to perform differently than a control group, we iteratively designed a digital assessment tool that could be deployed outside of laboratory contexts, in uncontrolled home environments on computer systems with widely varying system characteristics (e.g., displays resolution, input devices). We conducted two online studies, in which participants used the assessment tool in their own homes, and completed subjective questionnaires including the Patient Health Questionnaire (PHQ-9)—a standard self-report tool for assessing depression in clinical contexts. In a first study (n = 269), we demonstrate that each task can be used in isolation to significantly predict PHQ-9 scores. In a second study (n = 90), we replicate these results and further demonstrate that when used in combination, behavioral metrics from the three tasks significantly predicted PHQ-9 scores, even when taking into account demographic factors known to influence depression such as age and gender. A multiple regression model explained 34.4% of variance in PHQ-9 scores with behavioral metrics from each task providing unique and significant contributions to the prediction.

BACKGROUND A lack in the ability to inhibit prepotent responses, or, more generally, a lack of impulse control, is associated with several disorders such as attention-deficit/hyperactivity disorder (ADHD) and schizophrenia as well as general damage to the prefrontal cortex. The Stop-Signal Task (SST) is a reliable and established measure of response inhibition. However, using the SST as an objective assessment in diagnostic or research focused settings places significant stress on participants as the task itself requires concentration and cognitive effort and is not particularly engaging. This can lead to decreased motivation to follow task instructions and poor data quality, which can affect assessment efficacy and might increase drop-out rates. Gamification—the application of game-based elements in non-game settings—has been shown to improve engaged attention to a cognitive task, which can improve participant motivation and data quality. OBJECTIVE Design a gamified SST that improves participants’ engagement and validate this gamified SST against a standard SST task. METHODS We describe the design of our gamified SST task and report on two separate studies that aim to validate it relative to a standard SST task. In study 1, a within-subject design was used to compare performance between the SST and Stop-Signal Game (SSG). In study 2, we added eye-tracking to the procedure to determine if overt attention was affected and aimed to replicate the findings from study 1 in a between-subjects design. Furthermore, in both studies, flow and motivational experiences were measured. RESULTS Study 1 showed that response inhibition was comparable between the tasks as evidenced by frequentist (p = .86) and Bayesian (BF01 = 4.60) analysis. But the subjective experience was rated higher for the SSG as compared to the SST. Specifically results showed higher interest-enjoyment (p < .01, BF10 = 168.11) and higher flow (p < .05, BF10 = 4.92) experience. Study 2 produces similar results. While the behavioral performance was comparable between tasks (p < .87, BF01 = 2.87), the experience of flow and intrinsic motivation were rated higher in the SSG group although this difference was not significant. CONCLUSIONS Overall, our findings provide evidence that gamification of the SST is possible and that the SSG is enjoyed more. Thus, when participant engagement is critical, we recommend using the SSG instead of the SST. CLINICALTRIAL