SCH: INT: Collaborative Research: A Self-Adaptive Personalized Behavior Change System for Adolescent Preventive Healthcare

青少年期间的大多数发病和死亡是可以预防的，与药物使用和车辆相关伤害等行为有关。大多数青少年每年去一次医疗保健提供者，提供了一个理想的机会，将行为健康筛查纳入临床护理。虽然大多数青少年健康问题可以通过行为干预来解决，但很少有健康信息技术干预措施被纳入青少年护理。随着互补的理论进步（行为改变的社会认知理论）和技术进步（以智能叙事为中心的学习环境、用户建模和机器学习），该领域现在已经能够很好地设计健康行为改变系统，这些系统可以对青少年预防性健康的行为改变产生重大影响。行为改变的计算模型为青少年医疗保健带来了巨大的希望。本研究的目的是设计、实施和调查青少年预防健康的自适应个性化行为改变系统INSPIRE。INSPIRE将利用行为改变的社会认知理论，建立一个紧密的反馈循环，在这个循环中，以叙事为中心的行为改变环境将产生改善的患者行为，由此产生的患者结果数据将被强化学习优化系统用于学习精细的计算行为改变模型。青少年将与INSPIRE互动，重点关注危险行为，强调物质使用，以发展对其物质使用决定的动态和后果的经验理解。机器学习的最新进展为INSPIRE提供了一个独特的功能，即它能够在个人和群体层面上优化健康行为改变。在个人层面上，INSPIRE将利用患者行为模型来个性化青少年个体的行为改变叙述。它将根据青少年的目标和情感模式定制互动。在人口层面，INSPIRE将利用强化学习来调整其叙事生成系统，以系统地提高其改善两种结果的能力：行为改变和自我效能。该项目最终将在加州大学旧金山分校贝尼奥夫儿童医院儿科门诊诊所全面实施INSPIRE版本的实验。预计INSPIRE干预措施将产生两类结果：1)相对于标准护理而言，通过显著减少青少年危险行为来改善健康行为；2)相对于护理标准而言，青少年在健康行为方面做出正确决定的能力提高了自我效能感。INSPIRE专为自然集成到诊所工作流程、与EHR和患者门户系统的互操作性以及安全和隐私要求而设计，它将向医疗保健提供商报告患者行为变化摘要。通过支持笔记本电脑、台式电脑、平板电脑和移动计算设备的多平台部署，INSPIRE将成为青少年的赋权工具，使他们充分参与自己的幸福生活。它还将使研究人员能够进行行为分析，以调查替代干预措施的哪些特性最有效地促进了行为改变的结果。展望未来，预计INSPIRE将为广泛的行为改变研究提供一个测试平台，并通过计算支持的行为改变作为下一代个性化预防性医疗保健的基础。

The majority of morbidity and mortality during adolescence is preventable and related to behaviors such as substance use and vehicle-related injuries. Most adolescents visit a healthcare provider once a year, providing an ideal opportunity to integrate behavioral health screening into clinical care. Although the majority of adolescent health problems are amenable to behavioral intervention, few health information technology interventions have been integrated into adolescent care. With complementary theoretical advances (social-cognitive theories of behavior change) and technology advances (intelligent narrative-centered learning environments, user modeling, and machine learning), the field is now well positioned to design health behavior change systems that can realize significant impacts on behavior change for adolescent preventive health. Computationally-enabled models of behavior change hold significant promise for adolescent healthcare. The objective of the proposed research is to design, implement, and investigate INSPIRE, a self-adaptive personalized behavior change system for adolescent preventive health. INSPIRE will utilize a social-cognitive theory of behavior change built around a tight feedback loop in which a narrative-centered behavior change environment will produce improved behaviors in patients, and the resulting patient outcome data will be used by a reinforcement learning optimization system to learn refined computational behavior change models. With a focus on risky behaviors and an emphasis on substance use, adolescents will interact with INSPIRE to develop an experiential understanding of the dynamics and consequences of their substance use decisions. A unique feature of INSPIRE afforded by recent advances in machine learning will be its ability to optimize health behavior change at both the individual and population levels. At the individual level, INSPIRE will utilize a patient behavior model to personalize its behavior change narratives for individual adolescents. It will customize interactions based on an adolescent's goals and affective models. At the population level, INSPIRE will utilize reinforcement learning to adapt its narrative generation system to systematically increase its ability to improve two types of outcomes: behavior change and self-efficacy. The project will culminate with an experiment conducted with a fully implemented version of INSPIRE at outpatient clinics within the UC San Francisco Department of Pediatrics, Benioff Children's Hospital. It is anticipated that INSPIRE interventions will yield two types of outcomes: 1) improved health behavior through significant reductions in adolescent risky behavior, relative to standard of care; and 2) increased self-efficacy with respect to adolescents' ability to make good decisions about their health behaviors, relative to standard of care. Designed for natural integration into clinic workflow, interoperability with EHR and patient portal systems, and security and privacy requirements, INSPIRE will report patient behavior change summaries to healthcare providers. Through multi-platform deployments supporting laptop, desktop, tablet, and mobile computing devices, INSPIRE will serve as an empowering tool for adolescents, making them full participants in their own wellbeing. It will also enable researchers to run behavior analytics to investigate which properties of alternate interventions contribute most effectively to behavior change outcomes. Going forward, it is anticipated that INSPIRE will provide a testbed for a broad range of behavior change research and serve as the foundation for next-generation personalized preventive healthcare through computationally-enabled behavior change.