Automated Coding of eCoaching Exchanges to Promote Healthier Eating

电子教练交流的自动编码以促进健康饮食

• 批准号: 9181203
• 负责人: April Marie Idalski Carcone
• 金额: $ 23.74万
• 依托单位: WAYNE STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9181203
• 关键词: 21 year old; Adolescent; Adult; Alcohol consumption; Artificial Intelligence; Automation; Behavior; Caring; Child; Chronic; Chronic Disease; Classification; Clinical; Clinical Services; Code; Communication; Communication Research; Computer software; Computers; Counseling; Data; Data Analyses; Development; Diet; Diet Habits; Dietary Practices; Eating; Effectiveness; Electronic Mail; Food; Future Generations; Gender; Generations; Goals; Health Promotion; Health Status; Health behavior; Healthy Eating; Human; Image; Individual; Intake; Intervention; Investigator-Initiated Research; Judgment; Lead; Life; Life Expectancy; Link; Machine Learning; Manuals; Mediator of activation protein; Medical; Modeling; Motivation; National Institute of Child Health and Human Development; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Outcome; Outcome Measure; Parents; Patients; Pattern; Pennsylvania; Performance; Pharmacy facility; Physical activity; Population; Process; Professional counselor; Provider; Public Health; Qualitative Methods; Randomized Clinical Trials; Research; Research Methodology; Research Project Grants; Resources; Rural; Sampling; Scheme; Self Efficacy; Smoking; Social Work; Son; Specific qualifier value; Substance abuse problem; Techniques; Technology; Testing; Text; Time; Visit; Work; age group; base; behavior change; clinical practice; cognitive task; communication behavior; computer science; data mining; digital; effective intervention; emerging adulthood; evidence base; fruits and vegetables; good diet; improved; inner city; innovation; interest; intrinsic motivation; member; metropolitan; motivational enhancement therapy; new technology; point of care; primary outcome; public health intervention; rural area; satisfaction; sugar; sweetened beverage; young adult

Poor eating habits, particularly low fruit and vegetable intake, is a growing, serious public health concern, particularly among young adults age 21-30, referred to as Generation Y (GenY). GenY's poor dietary practices are associated with the onset of obesity and many chronic diseases, such as type 2 diabetes, as well as declines in predicted health status and life expectancy. Thus, there is a need to develop effective interventions to improve GenY's eating habits. MENU GenY is a computer-based intervention to encourage increased fruit and vegetable intake among GenY. A critical component of MENU GenY is personalized eCoaching. eCoaches use email to deliver motivation-enhancing coaching to encourage healthy eating, grounded in the principles of Motivational Interviewing (MI), an evidence-based communication technique to increase intrinsic motivation and self-efficacy for behavior change. The MI model posits that counselor's use of “MI-consistent” communication techniques are responsible for eliciting behavior change through patient “change talk” (i.e., statements about one's own desire, ability, reasons, need for or commitment to behavior change). A growing body of empirical evidence links change talk to behavior change, but research identifying the specific provider behaviors that elicit patient change talk is limited to specific populations (mainly adults who abuse substances and a couple studies of adolescents). Identifying specific communication strategies linked to behavior change and integrating these strategies into communication-based interventions (e.g., brief, motivation-enhancing interventions delivered in a variety of settings or public health initiatives) can increase these interventions' potency. However, a significant barrier to this research is the qualitative methods traditionally used to analyze the communication process which are resource-intensive, requiring an iterative process of human (subjective) interpretation of text. Rapidly developing computational technologies, specifically machine learning combined with classification models, offer a unique opportunity to accelerate this process. Our research group has recently applied machine learning-based data mining models to similar communication data. We automated a simple communication code scheme to characterize patient communication and achieved accuracy comparable to human coders. The goals of this study are to leverage innovative computer science machine learning and classification models to fully automate the communication coding process and link patterns in eCoach-patient communication to increases in fruit and vegetable intake. We propose a secondary analysis of data collected for a NICHD randomized clinical trial (R01 HD067314). The sample is 160 members of GenY drawn from both urban and rural settings (Detroit metropolitan area and rural Pennsylvania) with outcomes measured at baseline and 3 months. Our validated approach will accelerate the pace of outcomes-oriented communication research and identify effective communication strategies linked to healthy eating. These findings will be used to tailor interventions and public health messages and develop automated eCoaching.

不良的饮食习惯，特别是水果和蔬菜的摄入量不足，是一个日益严重的公共卫生问题， 特别是在21-30岁的年轻人中，他们被称为Y世代(GenY)。GenY的不良饮食习惯 与肥胖和许多慢性疾病(如2型糖尿病)的发病有关，以及 预测的健康状况和预期寿命。因此，需要制定有效的干预措施，以 改善GenY的饮食习惯。Menu GenY是一种基于计算机的干预措施，旨在鼓励增加水果和 青少年儿童蔬菜摄入量。Menu Geny的一个关键组成部分是个性化的电子教练。ECoach使用 电子邮件旨在提供增强动力的指导，以鼓励健康饮食，基于 动机访谈(MI)，一种以证据为基础的沟通技术，以提高内在动机 和行为改变的自我效能感。MI模型假设辅导员使用“MI-一致性” 通信技术负责通过患者的“改变谈话”引起行为改变(即， 关于自己的愿望、能力、理由、改变行为的需要或承诺的声明)。一个不断增长的 大量经验证据将改变谈话与行为改变联系在一起，但研究确定了具体的提供者 引发患者改变谈话的行为仅限于特定人群(主要是滥用药物的成年人 以及对青少年的几项研究)。确定与行为改变相关的特定沟通策略 并将这些战略纳入以沟通为基础的干预措施(例如，简短、增强动力 在各种环境或公共卫生倡议中提供的干预措施)可以增加这些干预措施 威力。然而，这项研究的一个重大障碍是传统上用于分析的定性方法 沟通过程是资源密集型的，需要人(主观)的迭代过程 对文本的解读。快速发展的计算技术，特别是结合了机器学习 通过分类模型，可以提供一个独特的机会来加速这一过程。我们的研究小组已经 最近将基于机器学习的数据挖掘模型应用于类似的通信数据。我们自动化了一个 简单的通信编码方案，以表征患者的交流，并达到可比的准确性 给人类编码员。这项研究的目标是利用创新的计算机科学机器学习和 用于完全自动化eCoach-Patient中通信编码过程和链接模式的分类模型 沟通与水果和蔬菜摄入量的增加。我们建议对收集到的数据进行二次分析 用于NICHD随机临床试验(R01 HD067314)。样本是从两个人中提取的160个GenY成员 城市和农村环境(底特律大都市区和宾夕法尼亚州农村)，成果衡量在 基线和3个月。我们经过验证的方法将加快以结果为导向的沟通步伐 研究并确定与健康饮食相关的有效沟通策略。这些发现将被用来 量身定制干预措施和公共卫生信息，并开发自动化电子教练。