Game design + features
Datasets and empirical evidence on predictors of opioid misuse (e.g., National Survey on Drug Use and Health, Adverse Childhood Experiences) informed the creation of a tailored digital serious game. Digital game was programmed utilizing Unity. Dissemination and data collection via mTurk, Amazon Web Services, and Qualtrics. LifePath is housed on a password-protected, internet-based platform. Specific mechanisms were incorporated to reduce message reactance while stimulating elaboration.
Upon entering the digital game (screen 1), individuals answer questions regarding three main areas of health affected by opioid misuse/abuse: physical (i.e., perceived personal health), mental (i.e., ACE, resilience), and social (i.e., social desirability). Based on their answers and secondary data sets, a unique life path is generated along with a Risk Dependency Score (RDS). The goal being to develop algorithms and predictive patterns based on existing data sets (programmed into the game) and answers collected by participants (during game sessions). All choices made throughout the game are tracked and stored as data points. Unique to this study is the use of user-generated health data (demographics, risk/protective factors) combined with large-scale data in a personalized platform.
The game leads individuals through a personalized (individual-level tailoring) health journey, with 2-3 events per life stage (e.g., 18-25, 26-35). In-game choices generate consequences on wellbeing (in three main areas: physical, mental, and social) based on the most recent data on opioid misuse and the results of previous peer-reviewed studies. Each participant response (selected by swiping left or right at each scenario) will affect one or more of the three areas of life either positively or negatively. For example, choosing to stay home from a party may increase mental health but will decrease social health. The goal is for players to achieve equilibrium. As such, throughout the game the RDS will be hidden, only shown at the end. This is to motivate individuals to make choices based on scenarios presented (e.g., current normative beliefs, social capital) and not merely trying to reduce the RDS (“win the game”). Once the game ends individuals will be able to evaluate their choices based on the entirety of their life path (summary presented) and their RDS.
Current Status: pilot testing digital game