Game playbooks: tools to guide multidisciplinary teams in developing videogame-based behavior change interventions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As mobile technologies and videogaming platforms are becoming increasingly prevalent in the realm of health and healthcare, so are the opportunities to use these resources to conduct behavioral interventions. The creation and empirical testing of game style interventions, however, is challenged by the requisite collaboration of multidisciplinary teams, including researchers and game developers who have different cultures, terminologies, and standards of evidence. Thus, traditional intervention development tools such as logic models and intervention manuals may need to be augmented by creating what we have termed "Game Playbooks" which are intervention guidebooks that are created by, understood by, and acceptable to all members of the multidisciplinary game development team. The purpose of this paper is to describe the importance and content of a Game Playbook created to aide in the development of a videogame intervention designed specifically for health behavior change in young teens as well as the process for creating such a tool. We draw on the experience of our research and game design team to describe the critical components of the Game Playbook and the necessity of creating such a tool.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it