Focus Cat: Designing Idle Games to Promote Intermittent Practice and On-Going Adherence of Breathing Exercise for ADHD
Bibliographic record
Abstract
Adherence and frequency of play are well-established challenges for serious games that target breathing exercises, because exercises are most effective when practiced in short and frequent sessions. Researchers have recognized that elements of idle games ideally align with many therapeutic use cases because idle games have a frequently repeating gameplay cycle that draws people in for short play sessions. However, there is little research about how idle games can be used to motivate consistent, frequent practice of therapies like breathing exercises that are often recommended for chronic conditions like ADHD. This paper describes the design and implementation of a therapeutic idle game, Focus Cat. This game is designed to help people with ADHD incorporate breathing exercises into their symptom management routine. Our work demonstrates how the unique qualities of idle game design—including short, frequent gameplay sessions, simple mechanics that make mundane tasks engaging and mechanics that pull and push players into and out of active gameplay—can be used for ADHD breathing exercises to improve adherence and frequency of practice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".