Gamifying Cognitive Behavioral Therapy Techniques on Smartphones for Bangkok’s Millennials With Depressive Symptoms: Interdisciplinary Game Development
Bibliographic record
Abstract
BACKGROUND: There is serious concern over the annual increase in depressive symptoms among millennials in Bangkok, Thailand. Their daily routine revolves around the use of their smartphones for work and leisure. Although accessibility to mental health care is expanding, it cannot keep up with the demand for mental health treatment. Outside Thailand, multiple projects and studies have attempted to merge gamification mechanisms and cognitive behavioral therapy (CBT) to create mobile health intervention apps and serious games with positive feedback. This presents an opportunity to explore the same approach in Thailand. OBJECTIVE: This study investigated the development process of gamifying CBT techniques to support game mechanics in a visual narrative serious game, BlueLine. The primary target of this research is Bangkok's millennials. In the game, players play as Blue, a Bangkok millennial who struggles to live through societal norms that influence his digital life and relationships. Through in-game scenarios, players will learn and understand how to lessen the impact of depressive symptoms via gamified interactions on their smartphones. METHODS: First, this paper follows each development step of solidifying BlueLine's game structure by integrating the Activating Events, Beliefs, Consequences, Disputation of Beliefs and Effective New Approaches (ABCDE) model and narrative in games. Second, the approach to select CBT and related therapeutic elements for gamification is based on suitability to the game structure. Throughout the process, CBT experts in Thailand have reviewed these scenarios. The approach forms the base of the player's interactions throughout the scenarios in BlueLine, broken down into 4 types of gamified mechanisms: narrative, verbal interactions, physical interactions, and social media interactions. RESULTS: With the game structure based on the ABCDE model, BlueLine scenarios implement gamified mechanisms in conjunction with the following CBT and related therapeutic elements: behavioral activation, self-monitoring, interpersonal skills, positive psychology, relaxation and mindful activities, and problem-solving. In each scenario, players guide Blue to overcome his triggered dysfunctional beliefs. During this process, players can learn and understand how to lessen the impact of depressive symptoms through gamified interactions. CONCLUSIONS: This paper presents the development process of gamifying CBT and related therapeutic techniques in BlueLine game scenarios. A scenario can harbor multiple techniques, including behavioral activation, self-monitoring, interpersonal skills, positive psychology, relaxation and mindful activities, and problem-solving. BlueLine's game structure does not limit the fact that the same combination of CBT elements ties each gamified mechanism.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".