Integrating Health Behavior Theory and Design Elements in Serious Games
Bibliographic record
Abstract
BACKGROUND: Internet interventions for improving health and well-being have the potential to reach many people and fill gaps in service provision. Serious gaming interfaces provide opportunities to optimize user adherence and impact. Health interventions based in theory and evidence and tailored to psychological constructs have been found to be more effective to promote behavior change. Defining the design elements which engage users and help them to meet their goals can contribute to better informed serious games. OBJECTIVE: To elucidate design elements important in SPARX, a serious game for adolescents with depression, from a user-centered perspective. METHODS: We proposed a model based on an established theory of health behavior change and practical features of serious game design to organize ideas and rationale. We analyzed data from 5 studies comprising a total of 22 focus groups and 66 semistructured interviews conducted with youth and families in New Zealand and Australia who had viewed or used SPARX. User perceptions of the game were applied to this framework. RESULTS: A coherent framework was established using the three constructs of self-determination theory (SDT), autonomy, competence, and relatedness, to organize user perceptions and design elements within four areas important in design: computer game, accessibility, working alliance, and learning in immersion. User perceptions mapped well to the framework, which may assist developers in understanding the context of user needs. By mapping these elements against the constructs of SDT, we were able to propose a sound theoretical base for the model. CONCLUSIONS: This study's method allowed for the articulation of design elements in a serious game from a user-centered perspective within a coherent overarching framework. The framework can be used to deliberately incorporate serious game design elements that support a user's sense of autonomy, competence, and relatedness, key constructs which have been found to mediate motivation at all stages of the change process. The resulting model introduces promising avenues for future exploration. Involving users in program design remains an imperative if serious games are to be fit for purpose.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".