Influence of game features on attention in adults

Abstract

Introduction: The incorporation of game features into cognitive tasks can inform us about the influence of reward and motivation on attention. Continuous performance tasks (CPTs), designed to assess attention abilities, are examples of cognitive tasks that have been targeted for the addition of game features. However, previous results have been mixed regarding how game elements affect attention abilities and task performance.

Methods: Here, we studied if there were factors that predict which individuals exhibit changes in attention from game features added to a CPT. Participants (N = 94, aged 21-71) played a traditional CPT and a game CPT with identical mechanics, but featured engaging game elements (aesthetics, storyline, competition, feedback, and reward).

Results: We first found corroborating evidence that game features have mixed effects on attention performance: most attention metrics of interest exhibited no overall difference between the traditional and game CPT, while game elements reduced performance for a few metrics. Importantly, we also found that specific behavioral and demographic profiles predicted individual differences in performance on the game CPT compared to the traditional CPT. Those with more attention difficulties (ADHD symptoms), more reward responsiveness, and younger adults performed better on the game CPT while, conversely, those with fewer ADHD symptoms, less reward responsiveness, and older adults performed better on the traditional CPT.

Discussion: These findings provide insights into how game features can influence attention in different individuals and have important implications for the use of game elements in cognitive tasks and training interventions.

Keywords: ADHD symptoms; attention; continuous performance task; game features; reward responsiveness.

Figure 1

CONSORT flow diagram. We collected data from 149 adults (age 18 or older) through Amazon Mechanical Turk (MTurk). We first excluded 55 participants from all analyses because they did not meet our inclusion criteria (e.g., incomplete datasets, self-reported psychiatric or neurological disorders; N = 39) or had chance or below chance performance on either the traditional or game CPT (defined as d-prime ≤0; N = 16). The final dataset for analysis included 94 adults aged 21–71 years old (N = 43 female), where 46 played the inhibitory control CPT condition (frequent target stimuli; orange) and 48 played the sustained attention CPT condition (infrequent target stimuli; blue).

Figure 2

Traditional and game CPTs. (A) In the traditional CPT, participants were instructed to respond to white squares appearing at the top of the screen (targets) and withhold responses to those appearing at the bottom of the screen (non-targets), while maintaining fixation on a white cross in the center of the screen. (B) In the game CPT, participants instead responded to fishing lures at the top of the screen (targets) and withheld responses to lures at the bottom of the screen (non-targets). The mechanics of the game CPT were identical to the traditional CPT; however, we added several game elements, such as game aesthetics (background music and visuals), reward and feedback (catching fish and associated points), as well as storyline and competition (participants were participating in a fishing competition).

Figure 3

Effects of game features on CPT performance. (A) Relationship between traditional and game CPT performance for RT (left), RTV (middle), and d-prime (right) for the inhibitory control and sustained attention conditions (orange and blue, respectively). Note that statistical values represent Spearman correlations (r_s), while the line represents the linear fit between the two variables (for visual purposes only). (B) Differences in performance between traditional and game CPT performance for RT (left), RTV (middle), and d-prime (right) for the inhibitory control and sustained attention conditions (orange and blue, respectively). Points represent the mean and error bars represent 95% bootstrapped confidence intervals. p-values reflect uncorrected values.

Figure 4

Effects of individual differences on the game CPT performance change. (A) ADHD symptoms. Relationship between ADHD symptoms and the game change score for RTV in the inhibitory control condition (left). Spearman correlations between ADHD symptoms and all performance metrics for the inhibitory control (orange) and sustained attention (blue) conditions (right). (B) BAS reward responsiveness. Relationship between reward responsiveness and the game change score for RTV in the inhibitory control condition (left). Spearman correlations between reward responsiveness and all performance metrics for the inhibitory control (orange) and sustained attention (blue) conditions (right). (C) Age. Relationship between age and the game change score for RTV in the sustained attention condition (left). Spearman correlations between age and all performance metrics for the inhibitory control (orange) and sustained attention (blue) conditions (right). In the scatter plots (left), statistical values represent Spearman correlations (r_s), while the line represents the linear fit between the two variables (for visual purposes only). Shaded areas in the scatter plots represent 95% bootstrapped confidence intervals. Black boxes around elements in the correlation matrices (right) denote that its representative scatter plot is shown to the left. *p_corrected ≤ 0.05; **p_corrected ≤ 0.01.