Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at, first published .
Serious Games Based on Cognitive Bias Modification and Learned Helplessness Paradigms for the Treatment of Depression: Design and Acceptability Study

Serious Games Based on Cognitive Bias Modification and Learned Helplessness Paradigms for the Treatment of Depression: Design and Acceptability Study

Serious Games Based on Cognitive Bias Modification and Learned Helplessness Paradigms for the Treatment of Depression: Design and Acceptability Study

Original Paper

1Department of Biological Sciences and Bioengineering, Indian Institute of Technology Kanpur, Kanpur, India

2Department of Cognitive Science, Indian Institute of Technology Kanpur, Kanpur, India

3Mehta Family Center for Engineering in Medicine, Indian Institute of Technology Kanpur, Kanpur, India

Corresponding Author:

Nitin Gupta, PhD

Department of Biological Sciences and Bioengineering

Indian Institute of Technology Kanpur


Kanpur, 208016


Phone: 91 5122594384


Background: Depression is a debilitating mental health disorder, with a large treatment gap. Recent years have seen a surge in digital interventions to bridge this treatment gap. Most of these interventions are based on computerized cognitive behavioral therapy. Despite the efficacy of computerized cognitive behavioral therapy–based interventions, their uptake is low and dropout rates are high. Cognitive bias modification (CBM) paradigms provide a complementary approach to digital interventions for depression. However, interventions based on CBM paradigms have been reported to be repetitive and boring.

Objective: In this paper, we described the conceptualization, design, and acceptability of serious games based on CBM paradigms and the learned helplessness paradigm.

Methods: We searched the literature for CBM paradigms that were shown to be effective in reducing depressive symptoms. For each of the CBM paradigms, we ideated how to create a game so that the gameplay was engaging while the active therapeutic component remained unchanged.

Results: We developed 5 serious games based on the CBM paradigms and the learned helplessness paradigm. The games include various core elements of gamification, such as goals, challenges, feedback, rewards, progress, and fun. Overall, the games received positive acceptability ratings from 15 users.

Conclusions: These games may help improve the effectiveness and engagement levels of computerized interventions for depression.

JMIR Serious Games 2023;11:e37105




Depressive disorders are a leading cause of disability worldwide, affecting >264 million people [1]. Antidepressant medications and cognitive behavioral therapy (CBT) are currently the most effective treatment modalities for depression [2-4], but there is a large treatment gap owing to the lack of accessibility, high cost of therapy, and social stigma associated with the visits to a psychiatric clinic [5-7]. In the past 2 decades, digital interventions have been gaining traction. The most widely studied digital intervention for depression is computerized CBT (cCBT). Although cCBT is an effective form of treatment [8-10], a recent meta-analysis has demonstrated that guided cCBT is less acceptable than being on a waiting list [11]. There is a need for other digital treatment modalities.

The cognitive theory of depression posits that information processing—attention, interpretation, and memory—is negatively biased in depression [12,13]. This biased information processing has been implicated in the onset and maintenance of depression [14]. Experimental studies have corroborated the cognitive model by providing empirical support for self-referential information processing, attention bias, interpretation bias, and memory bias [15-19]. Psychological training paradigms, known as cognitive bias modification (CBM) paradigms, have been used to modify these cognitive biases in subthreshold, clinical, and remitted populations [20-28], albeit with mixed results. Despite the mixed results and small effect sizes [29,30], this field promises novel treatment approaches and warrants further research.

The previously mentioned evaluations of CBM paradigms have been mostly performed in laboratory settings; these paradigms have received much less attention than cCBT as a potential treatment approach for depression outside the laboratory [31-33]. CBM paradigms tend to have low user engagement owing to the repetitiveness of the paradigms [34-37] and a lack of credibility in some cases [34,38]. In a digital intervention, in which the user needs to engage with a paradigm without any external supervision, the paradigm’s ability to engage becomes the determining factor for the success of the intervention.

One way to make the CBM paradigms more engaging to users is by developing serious games based on the paradigms [39]. A game serves as an interactive medium that provides game designers with considerable control in creating engaging experiences and can reduce the attrition rate in digital interventions [40]. Serious games have been evaluated for multiple conditions, including posttraumatic stress disorder [41,42], autism spectrum disorder [43-45], attention-deficit/hyperactivity disorder [46], cognitive functioning [47,48], alcohol use disorder [49,50], trait anxiety [51,52], etc. The results of a meta-analysis that evaluated the effectiveness of serious games demonstrated a moderate effect size of serious games for reducing psychiatric disorder–related symptoms compared with no intervention controls [53]. In a review of 4 studies that evaluated CBM interventions based on serious games, only 2 studies reported their gamified interventions to be effective [54].

Serious games have been developed for various aspects of depression. Bespoke serious games have been created to diagnose depression [55,56], treat depression [57-63], and describe the experience of depression either metaphorically [64] or literally [65]. Off-the-shelf commercial games have also been used to target depression [66]. There are multiple serious games based on different therapeutic techniques—CBT [67-69], solution-focused therapy [70], and interpersonal therapy [68]—that do not target depression specifically but can be useful. There is only 1 serious game based on a CBM paradigm targeting depression, but it was found to be ineffective [62]. Serious game–based interventions have been shown to be acceptable to the users overall [57,60,67-69]. A recent review, however, suggests that the effectiveness and acceptability data are not convincing enough yet to warrant clinical adoption [71].


In this study, we selected specific CBM paradigms that had received empirical support for targeting cognitive biases underlying depression and appeared suitable for conversion to games. Then, we described the design and development of these games in detail. Furthermore, we developed 1 serious game based on the learned helplessness theory.

Embedding Training Paradigms Into Serious Games

We searched the literature for known CBM paradigms and selected those that have shown promise in reducing depressive symptoms and were amenable to conversion to games. Our team discussed multiple game ideas for each paradigm. While thinking of the ideas, the primary aim was to make the gameplay engaging while keeping the active therapeutic component unchanged. After multiple sessions on ideations, the team selected the most promising game idea for each paradigm. Once the team agreed on a game idea, minimally viable prototypes were created and tested within the team. These minimally viable prototypes were improved upon to create the final versions by using the feedback obtained from informal tests performed in a larger group of approximately 10 friends and colleagues.

Software Development

We used Angular 8 (Google LLC) and JavaScript (ECMAScript 2018) for creating the front end of the games and Django-rest-framework 3.9.2 (Encode OSS Ltd) and Django 2.2 (Django Software Foundation) for creating the backend of the games. Two games required the detection of the swipe gesture on the screen, for which we used a readily available library, hammer.js. For 1 game that required the simulation of gravity and collision in the game environment, we used the phaser.js framework. The games were optimized for smartphone screens and were also compatible with tablets, laptops, and desktop devices. We created the graphical elements required for the game using Adobe Illustrator (Adobe Inc). Musical elements required for some of the games were collected from open web resources. The negative attention bias training game required the combination of 20 rhymes (Rock a bye baby, Wheels on the bus, etc) and famous compositions (Ode to joy, Für Elise, etc). The musical notations for these rhymes and compositions were collected from various YouTube channels. A few of them were readily available in the scientific pitch notation. For the others, we deduced the musical notations from the simple piano versions of these rhymes and compositions available on YouTube.

Feedback on the Games

To obtain a preliminary sense of the acceptability of the games, we asked 15 pilot users (n=8, 53% male and n=7, 47% female) to provide feedback on the 3 aspects of the games. The users were recruited from the Indian Institute of Technology, Kanpur community, by word of mouth. Potential users who expressed interest were sent an email detailing the procedure to participate in the study and to provide feedback. They were also sent an informed consent form via email. They were required to include their name and signature in the informed consent form and email it back to the study team. These users rated the games on three aspects: (1) The instructions on how to play the game were clear, (2) The game was fun to play, and (3) The purpose of the game was clear. The users rated these aspects on a 5-point scale—(1) strongly agree, (2) agree, (3) neutral, (4) disagree, and (5) strongly disagree. These ratings were mapped to scores of 2, 1, 0, −1, and −2, respectively. For the game for learned helplessness, we asked the users an additional question, In this game, you were presented with some unsolvable puzzles and some solvable puzzles. After you completed the game, the logic of the game was presented to you. After playing the game and reading the explanations, which of the following statements are true (tick all that apply)?

The following options were provided: (1) I have an understanding of learned helplessness; (2) I felt angry or frustrated while I was stuck with the puzzles; (3) After the logic of the game was explained, my frustration or anger reduced; and (4) After the logic of the game was explained, my frustration or anger did not reduce. The feedback was collected as a preliminary pilot for a larger study.

Ethics Approval

Ethical clearance was provided by the Institutional Ethics Committee of the Indian Institute of Technology Kanpur (IITK/IEC/2019-20/II/4).


We calculated the average value of the feedback received on the different aspects of the game. We also checked whether the feedback received was significantly different from 0 using the Wilcoxon signed rank test. Python (version 3.10.5; Python Software Foundation) and MATLAB R2020b (Mathworks) were used for data analysis.

Design Philosophy

Our main design objectives were to make the games effective by using evidence-based paradigms and engaging by incorporating 6 out of the 7 core elements of gamification. The evidence-based paradigm used for the individual games is described in individual sections throughout the paper. CBM paradigms have been reported to be boring and repetitive [34-37]. We hypothesized that making the games fun and engaging would increase the likelihood of spontaneous gameplay and, consequently, increase the CBM dosage without external supervision. Studies have reported that the rationale behind some CBM interventions is not apparent to the users, which can contribute to the lack of engagement [34,38]. To tackle this, we added a brief section called Science behind the game to each game.

Individuals experiencing an episode of depression have decreased cognitive abilities [72]. Considering this, we designed the gameplay to be easy and intuitive, such that anyone with some experience in using smartphone apps and a basic familiarity with the English language could play the games. We also kept the hardware requirements for the games minimal so that they could be played on low-end smartphones. At the beginning of the games, we gave simple in-game instructions or in-game tutorials. To avoid an artificial limit on the practice of CBM, we designed the games to be never-ending (except for the game for learned helplessness, in which the design required a definite ending). The difficulty level of each game adapted to the skill level of the user to create the flow experience [73]. Apart from making the games intrinsically engaging, we also added some extrinsic motivators to play the games, such as badges and scores, or the sensory experience of a familiar musical tune. The badges served as short-term rewards for playing the games, and the scores served as in-game currency, which could be exchanged for lives or hints in the games. We describe how our games are based on the elements of gamification in the later section titled, How game-like are our games?

Game for Automatic Interpretation Bias Modification

People with depression have an automatic negative interpretation bias [74]. Cowden Hindash et al [21,75,76] used a modified word sentence association paradigm for participants with dysphoria to confirm and modify the automatic negative interpretation bias. The bias modification paradigm also showed a near-transfer effect on the Scrambled Sentence Task [77] and a far-transfer effect of increased resiliency on a laboratory stressor [21].

In the task of modified word sentence association paradigm for participants with dysphoria, a self-relevant ambiguous sentence (My mom called me to tell me the news) is shown for a short duration, followed by a positive or negative word. The user is asked whether the word is related to the sentence. The user can answer Yes (related) or No (unrelated). The user is trained, via text-based feedback, to associate positive words with ambiguous sentences; the feedback is Correct if the answer is Yes for a positive word or No for a negative word; otherwise, the feedback is Incorrect. We converted this paradigm into a serious game in the following manner: The game displays an alphabet grid. The user’s goal is to find the words (that can be formed by connecting letters in the grid; Figure 1A) that form the ambiguous sentence. The game screen includes several empty bars, equal to the number of words to be found. As the user finds a word, a bar gets filled to provide the users with a sense of progress in the game and indicate the number of words found. Once the user finds 50% of the words, we reveal the full ambiguous sentence (Figure 1B), and then we show a positive or negative word and ask the user if the word and the sentence are related (Figure 1C). The user can answer by clicking on Yes (related) or No (unrelated) buttons. Quicker answers are given higher rewards to encourage the users to answer with the first thought they have. An incorrect answer receives 0 points. To prevent the users from clicking Yes for all positive words and No for all negative words, we used decoy sentence-word pairs, in which the sentence was unambiguous, and the negative word was related, while the positive word was unrelated [78].

Figure 1. Screenshots of the game for automatic interpretation bias modification. (A) The user finds words that are contained in the sentence by linearly connecting letters in the grid. (B) The ambiguous sentence is shown in full once the user finds 4 words. (C) The user is asked if the word (Bonus in the shown example) is related to the sentence on the previous screen.

The users earn reward points by finding words in the grid. Valid English words that are not parts of the sentence also earn points. The points, apart from being a short-term reward, also serve as an in-game currency to buy extra time or hints. Apart from points, the users also receive other short-term rewards in the form of bronze, silver, and gold badges for completing 4, 10, and 26 levels, respectively.

The game adapts to the user’s level of competence by varying the number of words hidden and allotted time per difficulty level (Figure S1 in Multimedia Appendix 1). To help the user in learning to play the game, the initial 4 levels of the game keep the words of the sentence fully visible in a jumbled order and give the user 150 seconds (in the first 2 levels) or 120 seconds (in the next 2 levels) to find the words in the grid. A bar, ranging from Easy to Hard, indicates the game’s current difficulty level.

There are 42 levels (sentence-word pairs) in the game. The difficulty of each level depends on the number of words to be found and the complexity of the grid. These, in turn, depend on the length of the sentence and the length of the longest word. The levels are arranged to gradually increase the difficulty level. After the completion of all the levels, the game loops back to the first level.

Game for Executive Control Training

Rumination, a core factor in depression, affects the duration [79] and intensity [80] of depressive episodes. Multiple studies have established that depressive rumination is associated with an inability to inhibit the processing of emotional information [81,82]. Executive control is one mechanism that regulates the ability to inhibit emotional information in healthy individuals [83-85]. Cohen et al [86] hypothesized that the difficulty in using executive control might be the factor behind impaired inhibition in ruminators. Cohen et al [86] designed a paradigm to train individuals to exert executive control before exposure to an emotional stimulus, followed by a discrimination task. They observed that individuals trained with this paradigm were less likely to engage in a state of rumination [86] and more likely to use reappraisal—an effective emotion regulation technique—more frequently and efficiently [87]. On the basis of this executive control training paradigm [87], we designed a 2D platform game to resemble the classic video game, Super Mario Bros. (Figure 2). The goal of the user is to keep a running avatar alive by jumping over obstacles (sitting or jumping frogs; Figure 2A) or pits (Figure 2B). The pits are of different types: some requiring a single jump, some requiring a double jump, and some including floating platforms in between (Figure 2C). The floating platforms are also of 2 kinds—some are stationary when the avatar lands on them, whereas others start to fall upon the landing of the avatar. The avatar sometimes passes through an underground tunnel, and on returning to the ground level, the background landscape changes to maintain a diversity of visuals. An in-game tutorial is shown to make the user familiar with the game’s rules and controls. On a keyboard-based device, the arrow keys can be used to play the game. On a touchscreen device, buttons corresponding to the arrow keys are shown on the screen itself.

Figure 2. Screenshots of the game for executive control training. (A) The avatar faces an obstacle, a jumping frog. (B) The avatar faces an obstacle, a pit. (C) The avatar faces a longer pit with floating platforms. (D) The instructions for the cognitive bias modification paradigm. (E) An incongruent flanker task as a part of the cognitive bias modification paradigm. The user must press the button corresponding to the middle arrow in the flanker task. (F) A green circle as a part of the cognitive bias modification paradigm. The user must press the button (green button on the right side) corresponding to the circle in the center.

As time progresses, the speed of the avatar increases to increase the difficulty level. The score in the game increases over time as the avatar continues to run. Intermittently, the game screen presents coins, which can be collected by jumping. The coins serve as an in-game currency. Initially, the user is given 3 lives and 5 double jumps for free. Once the user exhausts the free double jumps, each double jump costs 10 coins. In addition, once the user exhausts the free lives, additional lives can be purchased with coins with gradually increasing difficulty: the first purchase costs 10 coins and each purchase after that costs twice the amount of the last purchase.

At predetermined points in the game, the avatar stops in front of a large pit with floating platforms. At this point, the executive control training task is shown to the user (Figure 2D). An incongruent or a congruent set of flanker arrows (Figure 2E) is shown with a 50:50 probability. The user is required to press an arrow key corresponding to the middle arrow in the set. The flanker arrows remain visible until the user responds or for a maximum of 1000 milliseconds. After the flanker set disappears, an image is shown for 100 milliseconds. The image is neutral or negative with an 80:20 probability following a congruent set and with a 20:80 probability following an incongruent set. After a further gap of 50 milliseconds, during which no stimulus is shown, a green or red circle is shown with a 50:50 probability (Figure 2F). The user is required to respond according to the color of the circle (up arrow for green and down arrow for red). The circle remains visible until the user responds or for a maximum of 2000 milliseconds (Figure S2 in Multimedia Appendix 1). These 3 steps—including the arrows, the image, and the circle—constitute 1 round of training. The next round of similar training steps begins after a delay of 2000 milliseconds. After 3 rounds of training, the gameplay begins again and continues for approximately 30 seconds before the next batch of training begins. The instructions for choosing the correct keys are shown before each round of training. If the user presses the correct keys for both the flanker task and the colored circle task in a round, it is considered a correct response. The users are incentivized to perform the task diligently, as correct choices reward them with double jumps or additional lives. The users can also earn short-term rewards in the form of bronze, silver, and gold badges for 6, 15, and 39 correct responses, respectively.

Game for Negative Attention Bias Modification

The vulnerability model of low self-esteem and depression states that low self-esteem increases the risk of future depressive episodes [88,89]. Accordingly, improving one’s self-esteem should reduce the risk of depression. Individuals with lower self-esteem are more attentive to rejection cues, which in turn increases their tendency to interpret more and more social cues as rejecting, thus perpetuating the cycle of vigilance and low self-esteem [90,91]. Dandeneau et al [92] used an attention-training paradigm to modify this negative attention bias and observed that it led to a more resilient self-esteem against a laboratory-based rejection manipulation.

We designed a game based on the same training paradigm to overcome negative attention bias [92]. Images of human faces, one depicting a positive emotion and the others depicting negative emotions, are shown in a grid (Figure 3). The user is asked to click (or tap, when played on a touchscreen device) on the image with positive emotion as quickly as possible. Once the user clicks on the positive image, the next set of images is displayed in the same grid. To make this process fun and engaging, the game plays a musical note when the user clicks on a positive image. The musical notes, played sequentially, are taken from a popular song (or rhyme), and 1 song constitutes 1 level of the game. A click on a negative image results in an unpleasant beep. Therefore, in effect, the user can play the song by clicking on the faces with positive emotions—the more accurately they select the images with positive emotions, the fewer interruptions they hear during the song.

Figure 3. Screenshots of the game for negative attention bias training, showing (A) a 1 × 2 grid, (B) a 2 × 2 grid, and (C) a 3 × 2 grid of faces with different emotions.

To make the game challenging, the user is given a time limit to finish each level, calculated as TT = N × T, where N is the number of musical notes in the song and T is the time allotted per note (initialized to 5000 milliseconds). The game adapts to the user’s performance level by dynamically varying T between 1000 and 5000 milliseconds and the grid size between 1 × 2 (Figure 3A), 2 × 2 (Figure 3B), and 3 × 2 (Figure 3C) after the completion of each level. The algorithm of this adaptation is summarized in Figure S3 in Multimedia Appendix 1.

A bar, ranging from Easy to Hard, indicates the current difficulty level. To dissuade the user from clicking on images without paying attention, we penalize each click on a negative image by deducting 1 life (in addition to playing the unpleasant beeps). The user is given 5 free lives at the beginning of each game. Once the user runs out of lives, they have the option to replay the same level. Clicks on positive images earn points, which can be used to buy more time if the user runs out of time before the completion of a song. To give the user a sense of progress at each level, a progress bar on the screen indicates the fraction of notes in the current song that has been played.

The users also receive badges as short-term rewards. They earn bronze, silver, and gold badges by clicking on 34, 60, and 156 positive images, respectively. The game has 20 levels (songs). Once the user finishes all the songs, the game loops back to the first song.

Game for Positive Imagery Training

Negative automatic thoughts can be verbal or imaginal [93]. Holmes et al [94] developed an interpretation bias training paradigm based on positive mental imagery. Multiple studies have demonstrated that the training has a positive effect on the participants’ moods [25,94-96], although there are some exceptions [36,97]; the training also helped in targeting anhedonia [97].

We designed a serious game based on the combination of paradigms by Holmes et al [94] and Mathews and Mackintosh [98]. This game was developed as interactive fiction inspired by Zork [99]. At each level, the user is presented with an ambiguous scenario in the form of a paragraph with a blank space (Figure 4A). The user can fill in the blank with one or more words to resolve the sentence positively or negatively (eg, You think you ______ be able to enjoy the meeting can be resolved positively by adding will or negatively by adding will not). The game evaluates the phrase written by the user by comparing it against a comprehensive list of possible positive and negative completions for each sentence (occasionally, if the phrase falls outside the list, the game responds that it could not understand the input and requests the user to write a different phrase). If the user resolves the sentence negatively, it is considered an incorrect response and the user is asked to try again (Figure 4B). If resolved positively, the game moves forward and another ambiguous scenario appears in continuation with the previous one (Figure 4C). Once the user resolves the second part of the ambiguous scenario positively, the level concludes and a new scenario appears at the next level of the game. As vivid imagination is an active element [100], users are urged to imagine the situations vividly in the first person. No hints are provided in the game; however, if the user fails to answer correctly in 3 attempts, a list of potential answers is shown from which the user can select one. To encourage vivid imagination, we did not include a time limit in this game.

Figure 4. Screenshots of the game for positive imagery training. (A) A scenario is shown that can be resolved positively or negatively by providing one or more words to fill in the blank. (B) If the user resolves the scenario negatively, they are asked to try again. (C) If the user resolves the scenario positively, the game moves forward and another scenario is presented.

The game is designed to be never-ending. It includes 20 levels, and after the completion of all the levels, the game loops back to the first level. The user earns 5 points for resolving a scenario positively. The user also earns a bronze, a silver, and a gold badge after positively resolving 4, 10, and 26 scenarios, respectively.

Game for Learned Helplessness

Learned helplessness is a laboratory model of depression that emulates multiple aspects of clinical depression in animals [101,102]. The state of learned helplessness, reached after some experiences of inescapable aversive conditions, involves a generalized self-assumption of powerlessness, thereby reducing the effort to come out of difficult situations in the future. A reformulation of the theory in terms of attribution theory has also been extended to humans: individuals with learned helplessness attribute their failures to personal, pervasive, and persistent lack of abilities and their successes to luck [103].

We designed a puzzle-based game to help the users understand the ideas of learned helplessness and attribution style. We reasoned that an explanation after a game-based transient experience of the phenomenon would be more effective than simply explaining the concept using text or videos and is more likely to help users change their self-defeating attribution bias.

In the original experiments on learned helplessness, dogs failed to escape avoidable shocks after they had unsuccessfully tried to escape unavoidable shocks [104]. Very recently, a paradigm has been proposed to test learned helplessness in humans using loud audio tones as a stressor [105]. To allow the users to appreciate this phenomenon without a physical stressor, we devised the following approach: if a user can solve a puzzle initially but gives up on the same puzzle when it is shown after the failure to solve a hard and unrelated puzzle, the user would be able to see the parallel with learned helplessness and realize that it can happen in real life. At this point, the user is more likely to be receptive to the introspection of their own attribution bias.

We created a suite of 4 puzzle-based mini-games to achieve this objective. The first one, the circle-triangle mini-game, is a genuine puzzle game with multiple difficulty levels. The other 3 mini-games are designed to trick the user: each of them appears like a genuine puzzle game with easy puzzles in the first 1 or 2 levels but has unsolvable levels thereafter.

The user starts by playing the circle-triangle mini-game. The screen presents a pattern of squares, each containing a circle or a triangle (Figure 5A). If the user clicks on one of the squares, it flips (a circle becomes a triangle and vice versa). Simultaneously, the adjacent squares also flip (Figure 5B). The goal of the user is to change all the embedded shapes into circles. Once the user solves the puzzle, a message (Great) and auditory feedback (a pleasant ding) are provided to the user. Next, a harder level of the same mini-game is presented. This stepwise increase in the level continues until the user fails to solve the current level and clicks on a button labeled I give up (Figure 5C). When this happens, 1 of the 3 unsolvable mini-games is displayed to the user.

The 3 unsolvable mini-games are based on different types of puzzles (Figures 6A-C). For example, one is based on the popular 15 puzzle, in which a 4 × 4 grid has 1 empty cell and 15 cells containing tiles numbered 1 to 15 and the goal is to move the tiles to arrange them in increasing order. The first level shown in the mini-game is kept very simple and easily solvable (Figure 6A1), which allows the users to become familiar with the puzzle. However, unbeknownst to the user, the second and third levels are unsolvable—we set the initial configuration of tiles in these levels by slightly reordering the tiles from solvable puzzles in such a way that they could not be solved anymore but looked normal otherwise (Figure 6A2). Thus, at the second level—just after the very easy first level—the user finds it impossible to solve the puzzle and has no choice but to accept failure by clicking on the button I give up. After this, the third level of the same mini-game appears, in which the user again gives up regardless of how hard they try.

Once the user gives up in both the levels of an unsolvable mini-game, the last solved level of the circle-triangle mini-game is shown again (Figure 7 presents the flow of mini-games). If the user gives up on this level, which they have previously solved, we take the opportunity to draw a parallel with learned helplessness and the game ends with the explanation. By relating to the game, we explain the ideas of learned helplessness and attribution bias, with an emphasis on personalization and pervasiveness. We expect that once individuals can appreciate their own susceptibility, they are more likely to engage in the introspection to identify real-life situations where they fall prey to dysfunctional attribution styles. A correct understanding helps one to evaluate each situation independently and not lose motivation in all areas of life upon experiencing failure in some.

Figure 5. Screenshots of the circle-triangle mini-game in the game for learned helplessness. (A) The initial state in level 4. (B) An intermediate state in level 4. (C) An intermediate state in level 6.
Figure 6. The 3 unsolvable mini-games within the game for learned helplessness. (A) The goal in this mini-game is to arrange the tiles in the increasing order of the numbers. Configuration A1 is solvable, and A2 is unsolvable. (B) The goal in this mini-game is to get the butterfly to sit on all the flowers. The butterfly can be moved forward and sideways using the cursor keys on a keyboard or the swipe action on a touchscreen device. Once a butterfly sits on a flower, the flower withers away and the butterfly cannot move to a position without a flower. B1 is solvable, and B2 is unsolvable. (C) The goal in this mini-game is to insert the small red arc into the big blue arc. The user can move the solid black ball using cursor keys or swipe action to the adjacent squares (if the square contains an arc open in the direction of the ball, the ball moves inside the arc). Once the ball is inside an arc, the arc can be moved along with the ball to an adjacent square that is empty or contains a bigger arc with an opening in the direction from which the smaller arc is coming. The ball comes out of the small arc if moved in the direction in which the arc is open. C1 is solvable, and C2 is unsolvable.
Figure 7. Flowchart describing the sequence of mini-games in the game for learned helplessness. CTML: circle-triangle mini-game level.

If the user does not give up on the last solved level of the circle-triangle mini-game, they reach the next level within the same mini-game, and the game continues as normal. Once they give up on a higher level of the circle-triangle mini-game, they are shown a different unsolvable mini-game. This cycle of alternating between the circle-triangle mini-game and a different unsolvable mini-game continues until the user gives up on a previously solved level of the circle-triangle mini-game or completes all levels in it (the difficulty of the higher levels ensures that the latter scenario is unlikely).

The 4 puzzle-based mini-games are designed to be engaging and challenging to play. The difficulty level in the circle-triangle mini-game adapts to the competence level of the users. The screen displays the current level to provide the user with a sense of progress. The user receives a gold badge on finishing the game. Unlike other games in TreadWill, this game was designed to be played for a limited time, until the explanation of learned helplessness and the idea of the game were shown; however, the users are free to play it again if they wish.

How Game-Like Are Our Games?

Cugelman [106] has suggested 7 core elements of gamification. Each of the games we had designed incorporated 6 of the 7 elements, including goals, challenges, feedback, rewards, progress, and fun; the only element not included in our games is social connectivity, as the games were designed to be played individually as part of a mental health intervention. Table 1 describes how the core elements are incorporated into each game.

Table 1. Core game elements incorporated in different games.
Automatic interpretation bias modificationFinding words in the alphabet grid to complete the sentenceFinding words from the grid within the allotted timePoints for finding words and positive interpretationPoints and badges
  • In-level progress using progress bar
  • In-game progress using difficulty bar
Finding words in the alphabet grid
Executive control trainingTo keep the avatar alive as long as possible and collect coinsAvoid the obstacles at an increasingly faster speedPoints for keeping the avatar alivePoints and badges
  • In-game progress via increasing avatar speed
Gameplay similar to Super Mario Bros.
Negative attention bias modificationTo click on positive facesTo complete the song within the allotted time and avoid clicking on negative facesPoint and progress in level for clicking positive face and reduction in life for clicking on negative facePoints and badges
  • In-level progress using progress bar
  • In-game progress using difficulty bar
The music along with the game play
Positive imagery trainingTo progress in the game by providing positive resolutionsFinding the right wordPoints and progress in level for positive resolutionsPoints and badges
  • In-level progress using progress bar
Imagining the self-referent situations
Learned helplessnessSolving the puzzlesSolving the puzzlesPositive feedback for solving a puzzleBadge
  • For the solvable game, levels are shown
Solving the puzzles

Feedback on the Games

The feedback for all games obtained from the 15 pilot users (Methods section) is summarized in Figure 8. In most cases, there was statistically significant positive feedback on the clarity of instructions, fun in gameplay, and clarity of purpose (all P<.05; Table 2), showing that the games were acceptable to the users. According to the user feedback (Figure 8A-E), the games for negative attention bias modification (Figure 8C) and positive imagery training (Figure 8D) had the clearest instructions; the game for learned helplessness (Figure 8E) was the most fun to play; and the game for positive imagery training (Figure 8D) had the clearest purpose. The game for learned helplessness was able to achieve its purpose: 11 (73%) out of 15 users said that they had a better understanding of the idea of learned helplessness after playing the game. The game was able to induce anger or frustration in 6 (40%) out of 15 participants, of which 4 (67%) of the 6 mentioned that their anger or frustration reduced once the logic of the game was explained (overall, 7/15, 47% users reported a reduction in anger or frustration). Only 2 (13%) out of 15 participants reported that their anger or frustration did not reduce once the logic of the game was explained.

Figure 8. Acceptability results of the game for (A) automatic interpretation bias modification, (B) executive control training, (C) negative attention bias modification, (D) positive imagery training, and (E) learned helplessness. Overall (1) the instructions for the games were clear; (2) the games were fun to play; and (3) the purpose of the games was clear.
Table 2. Summary of feedback on the games from 15 pilot users. Each game was rated on 3 parameters on a 5-point Likert scale, in which 2=strongly agree, 1=agree, 0=neutral, −1=disagree, −2=strongly disagree. The P value corresponds to Wilcoxon signed rank test against 0.

Values, mean (SD)P value
Automatic interpretation bias modification

Instructions0.800 (1.014).02

Fun0.867 (0.743).003

Purpose0.733 (0.883).02
Executive control training

Instructions0.800 (1.207).03

Fun1.000 (0.926).004

Purpose0.533 (0.743).04
Negative attention bias modification

Instructions1.533 (0.639)<.001

Fun1.000 (1.195).01

Purpose1.067 (0.961).003
Positive imagery training

Instructions1.533 (0.639)<.001

Fun1.067 (1.032).005

Purpose1.267 (0.798)<.001
Learned helplessness

Instructions1.133 (0.743)<.001

Fun1.133 (0.639)<.001

Purpose1.133 (0.743)<.001

Principal Findings

This paper describes the design of 4 serious games based on CBM paradigms and 1 serious game based on the learned helplessness theory. We expect that delivering the CBM paradigms in the form of serious games will increase the paradigms’ engagement and consequent effectiveness. Currently, cCBT is the predominant digital intervention modality used for depression. Despite some early attempts at combining cCBT and CBM [23,32,33], no well-evaluated and widely available software intervention offers both. One likely reason is that users are not motivated to use the CBM paradigms in their raw forms. Incorporating game-based CBM paradigms in digital interventions might serve the following 2 purposes: increase engagement with the overall interventions and serve as a complementary therapeutic approach to CBT. Overall, all the games received positive feedback on all 3 aspects—whether the instructions were clear, whether the game was fun to play, and whether the purpose of the game was clear (Figure 8). In addition, the learned helplessness game was able to achieve its purpose of explaining learned helplessness via experiential learning.

Optimization of Game Paradigms

Two of the CBM paradigms described in this paper, the negative attention bias training [92] and the positive imagery training [94], were previously converted into serious games. In particular, the negative attention bias training paradigm has inspired many serious games. However, only a few have been evaluated in research studies [62,107,108], whereas the rest are commercially available without evaluation. The Bias Bluster game [109] was developed based on the positive imagery training paradigm.

We made slight modifications to 3 of the CBM paradigms to make them suitable for use in the games while keeping their active ingredients intact. In the original automatic interpretation bias modification paradigm, a sentence was shown for 1000 milliseconds [21]. However, during our internal testing, we observed that 1000 milliseconds was not appropriate for all sentences and, in general, too short for nonnative English speakers. Therefore, we showed the sentence for a duration dependent upon the length of the sentence, computed by 100 + (TC / ARS) milliseconds, where TC denotes the total number of characters in the sentence and ARS denotes the average reading speed (estimated to be approximately 50 characters per 1000 ms).

In the original negative attention bias training paradigm, the images were presented in a 4 × 4 grid [92]. During the internal testing, we observed that a 4 × 4 grid on a smartphone screen makes the individual images very small and the emotions in the images indiscernible. Considering the higher penetration of smartphones than computers or tablets, we presented images in 2 × 1, 2 × 2, or 3 × 2 grids to ensure that the images and emotions could be seen easily.

In some of the previous implementations of the positive imagery training paradigms, the scenarios were presented in an auditory format and the positive resolutions were provided to the user by the program directly [25,94,95,97,100]. We presented the scenarios using a text-based format, similar to Mathews and Mackintosh [98], as the auditory format is less amenable to gameplay (eg, an audio clip is slower to scan back and forth compared with text). Furthermore, we designed the game such that the user was required to come up with a positive resolution to the ambiguous scenario. This modification was inspired by the observation that the training was more effective in changing the mood if the interpretation was actively generated by the user [98].

Limitations and Future Directions

Feedback from the users in this study indicates that serious games based on CBM paradigms are acceptable. However, this study had a small sample size. There is a need for more studies with larger, more diverse, and clinical samples to test the real-world engagement and effectiveness of the games. In the future, games can be made more engaging using virtual reality.


Serious game–based mental health interventions are acceptable to users and have the potential to increase their engagement with digital mental health interventions. The designs we have provided can also be adapted into other interventions for many other disorders in which cognitive biases are involved [110]. We expect that the inclusion of serious games based on the CBM paradigms will help in improving the effectiveness and engagement of digital interventions.


The authors thank the members of the NG laboratory for testing the initial versions of the games and providing feedback on the content and user experience. In addition, the authors thank professor Arjun Ramakrishnan and Abin Thomas for help in recruiting participants for the pilot trial. They also thank Arun Shankar and Ranjeet Kumar for labeling the images used in the game for the negative attention bias modification. Face images used in the game for negative attention bias training were collected from multiple sources: White—Psychological Image Collection at Stirling [111]; African and Asian—tarrlab [112] (courtesy of Michael J Tarr, Carnegie Mellon University; funded by National Science Foundation award 0339122); and Indian—photographed by us. This work was supported by the Cognitive Science Research Initiative (CSRI) of the Department of Science and Technology (DST; grant DST/CSRI/2018/102). The NG laboratory is supported by the DST Science and Engineering Research Board Swarnajayanti Fellowship (grant SB/SJF/2021-22/04-C). The funding agencies had no role in the design or implementation of the study and in the interpretation of the results.

Data Availability

The deidentified data analyzed in the pilot study are available from the corresponding author upon reasonable request.

Authors' Contributions

AG and NG conceptualized the project. AG searched the literature for cognitive bias modification paradigms and suggested the initial game ideas that were refined and finalized after discussion with NG and other authors. AG, JA, SB, BKS, LA, AA, ST, KM, SR, YA, and SG developed the games. AG and NG wrote the paper with inputs from all coauthors.

Conflicts of Interest

None declared.

Multimedia Appendix 1

Flowcharts describing game algorithms.

PDF File (Adobe PDF File), 388 KB

  1. GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018 Nov 10;392(10159):1789-1858 [FREE Full text] [CrossRef] [Medline]
  2. Butler AC, Chapman JE, Forman EM, Beck AT. The empirical status of cognitive-behavioral therapy: a review of meta-analyses. Clin Psychol Rev 2006 Jan;26(1):17-31. [CrossRef] [Medline]
  3. Cipriani A, Furukawa TA, Salanti G, Chaimani A, Atkinson LZ, Ogawa Y, et al. Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. Lancet 2018 Apr 07;391(10128):1357-1366 [FREE Full text] [CrossRef] [Medline]
  4. Hofmann SG, Asnaani A, Vonk IJ, Sawyer AT, Fang A. The efficacy of cognitive behavioral therapy: a review of meta-analyses. Cognit Ther Res 2012 Oct 01;36(5):427-440 [FREE Full text] [CrossRef] [Medline]
  5. Andrade LH, Alonso J, Mneimneh Z, Wells JE, Al-Hamzawi A, Borges G, et al. Barriers to mental health treatment: results from the WHO World Mental Health surveys. Psychol Med 2013 Aug 09;44(6):1303-1317. [CrossRef]
  6. Patel V, Saxena S, Lund C, Thornicroft G, Baingana F, Bolton P, et al. The Lancet Commission on global mental health and sustainable development. Lancet 2018 Oct 27;392(10157):1553-1598. [CrossRef] [Medline]
  7. Saxena S, Thornicroft G, Knapp M, Whiteford H. Resources for mental health: scarcity, inequity, and inefficiency. Lancet 2007 Sep;370(9590):878-889. [CrossRef]
  8. Karyotaki E, Riper H, Twisk J, Hoogendoorn A, Kleiboer A, Mira A, et al. Efficacy of self-guided internet-based cognitive behavioral therapy in the treatment of depressive symptoms: a meta-analysis of individual participant data. JAMA Psychiatry 2017 Apr 01;74(4):351-359 [FREE Full text] [CrossRef] [Medline]
  9. Karyotaki E, Efthimiou O, Miguel C, Bermpohl FM, Furukawa TA, Cuijpers P, Individual Patient Data Meta-Analyses for Depression (IPDMA-DE) Collaboration, et al. Internet-based cognitive behavioral therapy for depression: a systematic review and individual patient data network meta-analysis. JAMA Psychiatry 2021 Apr 01;78(4):361-371 [FREE Full text] [CrossRef] [Medline]
  10. Wright JH, Owen JJ, Richards D, Eells TD, Richardson T, Brown GK, et al. Computer-assisted cognitive-behavior therapy for depression: a systematic review and meta-analysis. J Clin Psychiatry 2019 Mar 19;80(2):18r12188 [FREE Full text] [CrossRef] [Medline]
  11. Cuijpers P, Noma H, Karyotaki E, Cipriani A, Furukawa TA. Effectiveness and acceptability of cognitive behavior therapy delivery formats in adults with depression: a network meta-analysis. JAMA Psychiatry 2019 Jul 01;76(7):700-707 [FREE Full text] [CrossRef] [Medline]
  12. Beck A. Cognitive models of depressio. In: Clinical Advances in Cognitive Psychotherapy: Theory and Application. Cham: Springer Publishing Company; 2002.
  13. Beck AT. The evolution of the cognitive model of depression and its neurobiological correlates. Am J Psychiatry 2008 Aug;165(8):969-977. [CrossRef] [Medline]
  14. Roiser JP, Elliott R, Sahakian BJ. Cognitive mechanisms of treatment in depression. Neuropsychopharmacology 2012 Jan 5;37(1):117-136 [FREE Full text] [CrossRef] [Medline]
  15. Gotlib IH, Joormann J. Cognition and depression: current status and future directions. Annu Rev Clin Psychol 2010;6:285-312 [FREE Full text] [CrossRef] [Medline]
  16. Hsu KJ, Shumake J, Caffey K, Risom S, Labrada J, Smits JA, et al. Efficacy of attention bias modification training for depressed adults: a randomized clinical trial. Psychol Med 2021 Mar 26;52(16):3865-3873. [CrossRef]
  17. LeMoult J, Gotlib IH. Depression: a cognitive perspective. Clin Psychol Rev 2019 Apr;69:51-66. [CrossRef] [Medline]
  18. Mathews A, MacLeod C. Cognitive vulnerability to emotional disorders. Annu Rev Clin Psychol 2005;1:167-195. [CrossRef] [Medline]
  19. Woolridge SM, Harrison GW, Best MW, Bowie CR. Attention bias modification in depression: a randomized trial using a novel, reward-based, eye-tracking approach. J Behav Ther Exp Psychiatry 2021 Jun;71:101621. [CrossRef] [Medline]
  20. Browning M, Holmes EA, Charles M, Cowen PJ, Harmer CJ. Using attentional bias modification as a cognitive vaccine against depression. Biol Psychiatry 2012 Oct 01;72(7):572-579 [FREE Full text] [CrossRef] [Medline]
  21. Cowden Hindash AH, Rottenberg JA. Moving towards the benign: automatic interpretation bias modification in dysphoria. Behav Res Ther 2017 Dec;99:98-107. [CrossRef] [Medline]
  22. Hirsch CR, Krahé C, Whyte J, Loizou S, Bridge L, Norton S, et al. Interpretation training to target repetitive negative thinking in generalized anxiety disorder and depression. J Consult Clin Psychol 2018 Dec;86(12):1017-1030. [CrossRef] [Medline]
  23. Koster EH, Hoorelbeke K. Cognitive bias modification for depression. Current Opinion Psychol 2015 Aug;4:119-123. [CrossRef]
  24. Kraft B, Jonassen R, Heeren A, Harmer C, Stiles T, Landrø NI. Attention bias modification in remitted depression is associated with increased interest and leads to reduced adverse impact of anxiety symptoms and negative cognition. Clin Psychol Sci 2019 Feb 08;7(3):530-544. [CrossRef]
  25. Lang TJ, Blackwell SE, Harmer CJ, Davison P, Holmes EA. Cognitive bias modification using mental imagery for depression: developing a novel computerized intervention to change negative thinking styles. Eur J Pers 2012 Mar 18;26(2):145-157 [FREE Full text] [CrossRef] [Medline]
  26. Pictet A, Jermann F, Ceschi G. When less could be more: investigating the effects of a brief internet-based imagery cognitive bias modification intervention in depression. Behav Res Ther 2016 Sep;84:45-51. [CrossRef] [Medline]
  27. Watkins ER, Baeyens CB, Read R. Concreteness training reduces dysphoria: proof-of-principle for repeated cognitive bias modification in depression. J Abnorm Psychol 2009 Feb;118(1):55-64. [CrossRef] [Medline]
  28. Yiend J, Lee J, Tekes S, Atkins L, Mathews A, Vrinten M, et al. Modifying interpretation in a clinically depressed sample using ‘cognitive bias modification-errors’: a double blind randomised controlled trial. Cogn Ther Res 2013 Jul 23;38(2):146-159. [CrossRef]
  29. Cristea IA, Kok RN, Cuijpers P. Efficacy of cognitive bias modification interventions in anxiety and depression: meta-analysis. Br J Psychiatry 2015 Jan 2;206(1):7-16. [CrossRef] [Medline]
  30. Grafton B, MacLeod C, Rudaizky D, Holmes EA, Salemink E, Fox E, et al. Confusing procedures with process when appraising the impact of cognitive bias modification on emotional vulnerability. Br J Psychiatry 2017 Nov 2;211(5):266-271 [FREE Full text] [CrossRef] [Medline]
  31. Bowler JO, Mackintosh B, Dunn BD, Mathews A, Dalgleish T, Hoppitt L. A comparison of cognitive bias modification for interpretation and computerized cognitive behavior therapy: effects on anxiety, depression, attentional control, and interpretive bias. J Consult Clin Psychol 2012 Dec;80(6):1021-1033 [FREE Full text] [CrossRef] [Medline]
  32. Williams AD, Blackwell SE, Mackenzie A, Holmes EA, Andrews G. Combining imagination and reason in the treatment of depression: a randomized controlled trial of internet-based cognitive-bias modification and internet-CBT for depression. J Consult Clin Psychol 2013 Oct;81(5):793-799 [FREE Full text] [CrossRef] [Medline]
  33. Williams AD, O'Moore K, Blackwell SE, Smith J, Holmes EA, Andrews G. Positive imagery cognitive bias modification (CBM) and internet-based cognitive behavioral therapy (iCBT): a randomized controlled trial. J Affect Disord 2015 Jun 01;178:131-141 [FREE Full text] [CrossRef] [Medline]
  34. Beard C, Weisberg RB, Primack J. Socially anxious primary care patients' attitudes toward cognitive bias modification (CBM): a qualitative study. Behav Cogn Psychother 2012 Oct;40(5):618-633 [FREE Full text] [CrossRef] [Medline]
  35. Brosan L, Hoppitt L, Shelfer L, Sillence A, Mackintosh B. Cognitive bias modification for attention and interpretation reduces trait and state anxiety in anxious patients referred to an out-patient service: results from a pilot study. J Behav Ther Exp Psychiatry 2011 Sep;42(3):258-264. [CrossRef] [Medline]
  36. de Voogd EL, de Hullu E, Burnett Heyes S, Blackwell SE, Wiers RW, Salemink E. Imagine the bright side of life: a randomized controlled trial of two types of interpretation bias modification procedure targeting adolescent anxiety and depression. PLoS One 2017 Jul 17;12(7):e0181147 [FREE Full text] [CrossRef] [Medline]
  37. Zhang M, Ying J, Song G, Fung DS, Smith H. Web-based cognitive bias modification interventions for psychiatric disorders: scoping review. JMIR Ment Health 2019 Oct 24;6(10):e11841 [FREE Full text] [CrossRef] [Medline]
  38. Yang R, Cui L, Li F, Xiao J, Zhang Q, Oei TP. Effects of cognitive bias modification training via smartphones. Front Psychol 2017 Aug 14;8:1370 [FREE Full text] [CrossRef] [Medline]
  39. Boendermaker WJ, Boffo M, Wiers RW. Exploring elements of fun to motivate youth to do cognitive bias modification. Games Health J 2015 Dec;4(6):434-443. [CrossRef] [Medline]
  40. Fleming TM, de Beurs D, Khazaal Y, Gaggioli A, Riva G, Botella C, et al. Maximizing the impact of e-therapy and serious gaming: time for a paradigm shift. Front Psychiatry 2016;7:65 [FREE Full text] [CrossRef] [Medline]
  41. Holmes EA, James EL, Kilford EJ, Deeprose C. Key steps in developing a cognitive vaccine against traumatic flashbacks: visuospatial Tetris versus verbal Pub Quiz. PLoS One 2010 Nov 10;5(11):e13706 [FREE Full text] [CrossRef] [Medline]
  42. Holmes EA, James EL, Coode-Bate T, Deeprose C. Can playing the computer game "Tetris" reduce the build-up of flashbacks for trauma? A proposal from cognitive science. PLoS One 2009;4(1):e4153 [FREE Full text] [CrossRef] [Medline]
  43. Beaumont R, Sofronoff K. A multi-component social skills intervention for children with Asperger syndrome: the Junior Detective Training Program. J Child Psychol Psychiatry 2008 Jul;49(7):743-753. [CrossRef] [Medline]
  44. Tanaka JW, Wolf JM, Klaiman C, Koenig K, Cockburn J, Herlihy L, et al. Using computerized games to teach face recognition skills to children with autism spectrum disorder: the Let's Face It! program. J Child Psychol Psychiatry 2010 Aug;51(8):944-952. [CrossRef] [Medline]
  45. Wagle S, Ghosh A, Karthic P, Ghosh A, Pervaiz T, Kapoor R, et al. Development and testing of a game-based digital intervention for working memory training in autism spectrum disorder. Sci Rep 2021 Jul 05;11(1):13800 [FREE Full text] [CrossRef] [Medline]
  46. Dovis S, Van der Oord S, Wiers RW, Prins PJ. Improving executive functioning in children with ADHD: training multiple executive functions within the context of a computer game. a randomized double-blind placebo controlled trial. PLoS One 2015;10(4):e0121651 [FREE Full text] [CrossRef] [Medline]
  47. Ballesteros S, Prieto A, Mayas J, Toril P, Pita C, Ponce de León L, et al. Brain training with non-action video games enhances aspects of cognition in older adults: a randomized controlled trial. Front Aging Neurosci 2014;6:277 [FREE Full text] [CrossRef] [Medline]
  48. Rezaiyan A, Mohammadi E, Fallah PA. Effect of computer game intervention on the attention capacity of mentally retarded children. Int J Nurs Pract 2007 Oct;13(5):284-288. [CrossRef]
  49. Boendermaker WJ, Sanchez Maceiras S, Boffo M, Wiers RW. Attentional bias modification with serious game elements: evaluating the shots game. JMIR Serious Games 2016 Dec 06;4(2):e20 [FREE Full text] [CrossRef] [Medline]
  50. Verduin ML, LaRowe SD, Myrick H, Cannon-Bowers J, Bowers C. Computer simulation games as an adjunct for treatment in male veterans with alcohol use disorder. J Subst Abuse Treat 2013 Mar;44(3):316-322. [CrossRef] [Medline]
  51. Dennis TA, O'Toole L. Mental health on the go: effects of a gamified attention bias modification mobile application in trait anxious adults. Clin Psychol Sci 2014 Sep 01;2(5):576-590 [FREE Full text] [CrossRef] [Medline]
  52. Dennis-Tiwary TA, Egan LJ, Babkirk S, Denefrio S. For whom the bell tolls: neurocognitive individual differences in the acute stress-reduction effects of an attention bias modification game for anxiety. Behav Res Ther 2016 Feb;77:105-117 [FREE Full text] [CrossRef] [Medline]
  53. Lau HM, Smit JH, Fleming TM, Riper H. Serious games for mental health: are they accessible, feasible, and effective? A systematic review and meta-analysis. Front Psychiatry 2016;7:209 [FREE Full text] [CrossRef] [Medline]
  54. Zhang M, Ying J, Song G, Fung DS, Smith H. Gamified cognitive bias modification interventions for psychiatric disorders: review. JMIR Ment Health 2018 Oct 25;5(4):e11640 [FREE Full text] [CrossRef] [Medline]
  55. Maskeliūnas R, Blažauskas T, Damaševičius R. Depression behavior detection model based on participation in serious games. In: Rough Sets. Cham: Springer; 2017.
  56. Tsionas A, Lazaridis A, Vlahavas I. Serious game development for the diagnosis of major depressive disorder cases using machine learning methods. In: Proceedings of the GAITCS 2020. 2020 Presented at: GAITCS 2020; Sep 2-4, 2020; Athens, Greece   URL:
  57. Fleming T, Dixon R, Frampton C, Merry S. A pragmatic randomized controlled trial of computerized CBT (SPARX) for symptoms of depression among adolescents excluded from mainstream education. Behav Cogn Psychother 2012 Oct;40(5):529-541. [CrossRef] [Medline]
  58. Hookham G, Kay-Lambkin F, Blackmore K, Nesbitt K. Using startle probe to compare affect and engagement between a serious game and an online intervention program. In: Proceedings of the Australasian Computer Science Week Multiconference. 2016 Presented at: ACSW '16: Australasian Computer Science Week; Feb 1 - 5, 2016; Canberra Australia. [CrossRef]
  59. Knox M, Lentini J, Cummings T, McGrady A, Whearty K, Sancrant L. Game-based biofeedback for paediatric anxiety and depression. Ment Health Fam Med 2011 Sep;8(3):195-203 [FREE Full text] [Medline]
  60. Merry SN, Stasiak K, Shepherd M, Frampton C, Fleming T, Lucassen MF. The effectiveness of SPARX, a computerised self help intervention for adolescents seeking help for depression: randomised controlled non-inferiority trial. BMJ 2012 Apr 18;344(apr18 3):e2598 [FREE Full text] [CrossRef] [Medline]
  61. Oliveira E, Gonçalves MM, Caridade R, Rodrigues N. Rumination room: a serious game to deal with disturbing thoughts. In: Proceedings of the 2014 IEEE 3nd International Conference on Serious Games and Applications for Health (SeGAH). 2014 Presented at: 2014 IEEE 3nd International Conference on Serious Games and Applications for Health (SeGAH); May 14-16, 2014; Rio de Janeiro, Brazil. [CrossRef]
  62. Pieters EK, De Raedt R, Enock PM, De Putter LM, Braham H, McNally RJ, et al. Examining a novel gamified approach to attentional retraining: effects of single and multiple session training. Cogn Ther Res 2016 Sep 7;41(1):89-105. [CrossRef]
  63. Stasiak K, Hatcher S, Frampton C, Merry SN. A pilot double blind randomized placebo controlled trial of a prototype computer-based cognitive behavioural therapy program for adolescents with symptoms of depression. Behav Cogn Psychother 2012 Dec 20;42(4):385-401. [CrossRef]
  64. Rusch DC. "Elude": designing depression. In: Proceedings of the International Conference on the Foundations of Digital Games. 2012 Presented at: FDG'12: International Conference on the Foundations of Digital Games; May 29- Jun 1, 2012; Raleigh North Carolina. [CrossRef]
  65. Quinn Z, Lindsey P, Schankler I. Depression Quest [Twine game]. Zoë Quinn Games.   URL: [accessed 2021-05-08]
  66. Kowal M, Conroy E, Ramsbottom N, Smithies T, Toth A, Campbell M. Gaming your mental health: a narrative review on mitigating symptoms of depression and anxiety using commercial video games. JMIR Serious Games 2021 Jun 16;9(2):e26575 [FREE Full text] [CrossRef] [Medline]
  67. Brezinka V. Treasure Hunt - a serious game to support psychotherapeutic treatment of children. Stud Health Technol Inform 2008;136:71-76. [Medline]
  68. Carrasco AE. Acceptability of an adventure video game in the treatment of female adolescents with symptoms of depression. ResPsy 2016 Apr 18;19(1) [FREE Full text] [CrossRef]
  69. Coyle D, McGlade N, Doherty G, O'Reilly G. Exploratory evaluations of a computer game supporting cognitive behavioural therapy for adolescents. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 2011 Presented at: CHI '11: CHI Conference on Human Factors in Computing Systems; May 7 - 12, 2011; Vancouver BC Canada. [CrossRef]
  70. Coyle D, Matthews M, Sharry J, Nisbet A, Doherty G. Personal Investigator: a therapeutic 3D game for adolecscent psychotherapy. Interact Technol Smart Educ 2005 May 31;2(2):73-88. [CrossRef]
  71. Dewhirst A, Laugharne R, Shankar R. Therapeutic use of serious games in mental health: scoping review. BJPsych Open 2022 Feb 02;8(2):e37 [FREE Full text] [CrossRef] [Medline]
  72. Rock PL, Roiser JP, Riedel WJ, Blackwell AD. Cognitive impairment in depression: a systematic review and meta-analysis. Psychol Med 2014 Jul 29;44(10):2029-2040. [CrossRef] [Medline]
  73. Csikszentmihalyi M. Flow: The Classic Work On How To Achieve Happiness: The Psychology of Happiness. London: Random House; 2002.
  74. Beevers CG. Cognitive vulnerability to depression: a dual process model. Clin Psychol Rev 2005 Nov;25(7):975-1002. [CrossRef] [Medline]
  75. Cowden Hindash AH, Rottenberg J. Turning quickly on myself: automatic interpretation biases in dysphoria are self-referent. Cogn Emot 2017 Feb 03;31(2):395-402. [CrossRef] [Medline]
  76. Cowden Hindash AH, Amir N. Negative interpretation bias in individuals with depressive symptoms. Cogn Ther Res 2011 Sep 27;36(5):502-511. [CrossRef]
  77. Wenzlaff RM, Bates DE. Unmasking a cognitive vulnerability to depression: how lapses in mental control reveal depressive thinking. J Personality Social Psychol 1998;75(6):1559-1571. [CrossRef]
  78. Möbius M, Tendolkar I, Lohner V, Baltussen M, Becker ES. Refilling the half-empty glass--Investigating the potential role of the Interpretation Modification Paradigm for Depression (IMP-D). J Behav Ther Exp Psychiatry 2015 Dec;49(Pt A):37-43. [CrossRef] [Medline]
  79. Nolen-Hoeksema S, Morrow J, Fredrickson BL. Response styles and the duration of episodes of depressed mood. J Abnormal Psychol 1993 Feb;102(1):20-28. [CrossRef]
  80. Nolen-Hoeksema S, Davis CG. "Thanks for sharing that": ruminators and their social support networks. J Personality Social Psychol 1999;77(4):801-814. [CrossRef]
  81. De Lissnyder E, Koster EH, Derakshan N, De Raedt R. The association between depressive symptoms and executive control impairments in response to emotional and non-emotional information. Cognit Emotion 2010 Feb;24(2):264-280. [CrossRef]
  82. Joormann J. Differential effects of rumination and dysphoria on the inhibition of irrelevant emotional material: evidence from a negative priming task. Cogn Ther Res 2006 Jun 17;30(2):149-160. [CrossRef]
  83. Cohen N, Henik A, Mor N. Can emotion modulate attention? Evidence for reciprocal links in the attentional network test. Exp Psychol 2011 Nov 01;58(3):171-179. [CrossRef] [Medline]
  84. Cohen N, Henik A, Moyal N. Executive control attenuates emotional effects-For high reappraisers only? Emotion 2012 Oct;12(5):970-979. [CrossRef] [Medline]
  85. Kalanthroff E, Cohen N, Henik A. Stop feeling: inhibition of emotional interference following stop-signal trials. Front Hum Neurosci 2013;7:78 [FREE Full text] [CrossRef] [Medline]
  86. Cohen N, Mor N, Henik A. Linking executive control and emotional response. Clin Psychological Sci 2014 Apr 30;3(1):15-25. [CrossRef]
  87. Cohen N, Mor N. Enhancing reappraisal by linking cognitive control and emotion. Clin Psychological Sci 2017 Oct 27;6(1):155-163. [CrossRef]
  88. Orth U, Robins RW, Meier LL, Conger RD. Refining the vulnerability model of low self-esteem and depression: disentangling the effects of genuine self-esteem and narcissism. J Pers Soc Psychol 2016 Jan;110(1):133-149 [FREE Full text] [CrossRef] [Medline]
  89. Sowislo JF, Orth U. Does low self-esteem predict depression and anxiety? A meta-analysis of longitudinal studies. Psychol Bull 2013 Jan;139(1):213-240. [CrossRef] [Medline]
  90. Dandeneau SD, Baldwin MW, Baccus JR, Sakellaropoulo M, Pruessner JC. Cutting stress off at the pass: reducing vigilance and responsiveness to social threat by manipulating attention. J Pers Soc Psychol 2007 Oct;93(4):651-666. [CrossRef] [Medline]
  91. Dandeneau SD, Baldwin MW. The inhibition of socially rejecting information among people with high versus low self-esteem: the role of attentional bias and the effects of bias reduction training. J Social Clin Psychol 2004 Aug;23(4):584-603. [CrossRef]
  92. Dandeneau SD, Baldwin MW. The buffering effects of rejection-inhibiting attentional training on social and performance threat among adult students. Contemporary Educational Psychol 2009 Jan;34(1):42-50. [CrossRef]
  93. Beck JS. Cognitive therapy. In: The Corsini Encyclopedia of Psychology. Hoboken, New Jersey: Wiley; 2010.
  94. Holmes EA, Mathews A, Dalgleish T, Mackintosh B. Positive interpretation training: effects of mental imagery versus verbal training on positive mood. Behav Ther 2006 Sep;37(3):237-247. [CrossRef] [Medline]
  95. Blackwell SE, Holmes EA. Modifying interpretation and imagination in clinical depression: a single case series using cognitive bias modification. Appl Cognit Psychol 2010 Apr;24(3):338-350. [CrossRef]
  96. Holmes EA, Lang TJ, Shah DM. Developing interpretation bias modification as a "cognitive vaccine" for depressed mood: imagining positive events makes you feel better than thinking about them verbally. J Abnorm Psychol 2009 Feb;118(1):76-88. [CrossRef] [Medline]
  97. Blackwell SE, Browning M, Mathews A, Pictet A, Welch J, Davies J, et al. Positive imagery-based cognitive bias modification as a web-based treatment tool for depressed adults: a randomized controlled trial. Clin Psychol Sci 2015 Jan 06;3(1):91-111 [FREE Full text] [CrossRef] [Medline]
  98. Mathews A, Mackintosh B. Induced emotional interpretation bias and anxiety. J Abnormal Psychol 2000 Nov;109(4):602-615. [CrossRef]
  99. Lebling, Blank, Anderson. Special feature zork: a computerized fantasy simulation game. Computer 1979 Apr;12(4):51-59. [CrossRef]
  100. Nelis S, Vanbrabant K, Holmes EA, Raes F. Greater positive affect change after mental imagery than verbal thinking in a student sample. J Exp Psychopathol 2012 Apr 23;3(2):178-188 [FREE Full text] [CrossRef] [Medline]
  101. Deussing JM. Animal models of depression. Drug Discovery Today Disease Models 2006 Dec;3(4):375-383. [CrossRef]
  102. Seligman ME, Rosellini RA, Kozak MJ. Learned helplessness in the rat: time course, immunization, and reversibility. J Comp Physiol Psychol 1975 Feb;88(2):542-547. [CrossRef] [Medline]
  103. Abramson LY, Seligman ME, Teasdale JD. Learned helplessness in humans: critique and reformulation. J Abnormal Psychol 1978 Feb;87(1):49-74. [CrossRef]
  104. Seligman ME, Maier SF. Failure to escape traumatic shock. J Exp Psychol 1967 May;74(1):1-9. [CrossRef] [Medline]
  105. Song X, Vilares I. Assessing the relationship between the human learned helplessness depression model and anhedonia. PLoS One 2021 Mar 30;16(3):e0249056 [FREE Full text] [CrossRef] [Medline]
  106. Cugelman B. Gamification: what it is and why it matters to digital health behavior change developers. JMIR Serious Games 2013 Dec 12;1(1):e3 [FREE Full text] [CrossRef] [Medline]
  107. Basanovic J, Notebaert L, Clarke PJ, MacLeod C. Emotion-in-motion: an ABM approach that modifies attentional disengagement from, rather than attentional engagement with, negative information. Cogn Ther Res 2020 Nov 19;45(1):90-98. [CrossRef]
  108. Notebaert L, Grafton B, Clarke PJ, Rudaizky D, Chen NT, MacLeod C. Emotion-in-motion, a novel approach for the modification of attentional bias: an experimental proof-of-concept study. JMIR Serious Games 2018 Nov 28;6(4):e10993 [FREE Full text] [CrossRef] [Medline]
  109. van der Krieke L, Boonstra N, Malda A. Bias blaster: a game to beat interpretation bias in psychosis. Psychiatr Serv 2014 Jul;65(7):961. [CrossRef] [Medline]
  110. Macleod C. Cognitive bias modification procedures in the management of mental disorders. Curr Opin Psychiatry 2012 Mar;25(2):114-120. [CrossRef] [Medline]
  111. Psychological Image Collection at Stirling (PICS). University of Stirling.   URL: [accessed 2023-04-23]
  112. tarrlab.   URL: [accessed 2023-04-23]

CBM: cognitive bias modification
CBT: cognitive behavioral therapy
cCBT: computerized cognitive behavioral therapy

Edited by T Rashid Soron; submitted 07.02.22; peer-reviewed by C Beevers, N Chalghaf, V Verma; comments to author 25.03.22; revised version received 11.08.22; accepted 20.03.23; published 03.05.23


©Arka Ghosh, Jagriti Agnihotri, Sradha Bhalotia, Bharat Kumar Sati, Latika Agarwal, Akash A, Swastika Tandon, Komal Meena, Shreyash Raj, Yatin Azad, Silky Gupta, Nitin Gupta. Originally published in JMIR Serious Games (, 03.05.2023.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Serious Games, is properly cited. The complete bibliographic information, a link to the original publication on, as well as this copyright and license information must be included.