Using Artificial Intelligence to Optimize Delivery of Weight Loss Treatment
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 301
- 试验地点
- 1
- 主要终点
- Costs
研究概览
简要总结
Project ReLearn is testing the efficacy and cost-effectiveness of an Artificial Intelligence system for optimizing weight loss coaching. Participants are randomized to a 1-year weekly gold standard behavioral weight loss remote (video) group treatment or the AI-optimized treatment, which is made up of a combination of remote group treatment, short video call and automated message. In the AI-optimized condition, the system monitors outcomes (via wireless scale, mobile phone app, and wristworn tracker) and, each week, assigns each participant the treatments they have responding to the best, within certain time constraints.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Factorial
- 主要目的
- Treatment
- 盲法
- Single (Outcomes Assessor)
入排标准
- 年龄范围
- 18 Years 至 70 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Individuals must be of overweight or obese BMI (27-50 kg/m)
- •Individuals must be adults (aged 18-70)
- •Able and willing to engage in the remote program
- •Able to engage in physical activity (defined as walking two city blocks without stopping)
- •Individuals must also provide consent for the research team to contact their personal physician if necessary, to provide clearance or to consult about rapid weight loss
- •Access and willingness to use an Apple or Android smartphone
- •Satisfactory completion of all enrollment procedures
排除标准
- •Medical condition (e.g., cancer, type I diabetes, psychosis, full-threshold eating disorder) that may pose a risk to the participant during intervention or cause a change in weight
- •Currently pregnant, breastfeeding, or planning to become pregnant in the next 12 months
- •Recently began or changed the dosage of medication that can cause significant change in weight
- •History of bariatric surgery
- •Weight loss of > 5% in the previous 3 months
研究组 & 干预措施
BWL-S
1 year of remote gold standard, small group-based behavioral weight loss treatment with an MS-level clinician.
干预措施: Standard Behavioral Weight Loss Treatment (Behavioral)
BWL-AI
1 year of remote weight loss treatment made up of a combination of (1) remote small group-based behavioral weight loss sessions, (2) 12-minute individual video calls, (2) automated text messages. An MS-level clinician will deliver the group treatment. Most video calls will be delivered by a paraprofessional coach, but some by an MS-level clinician. Each week the AI system will select one of the interventions for each participant based on which treatment the participant has responded to the best, within certain time constraints.
干预措施: AI-optimized Behavioral Weight Loss Treatment (Behavioral)
结局指标
主要结局
Costs
时间窗: Baseline, 1-month, 6-month, and 12-month assessment
All time spent training counselors, participants and supervising counselors, will be tracked by the project coordinator, as will time counselors spend delivering individual and group treatment. The web portal will track counselor time on the portal, e.g., reviewing food records and texting. While the basic time commitments are pre-set by condition, several factors will vary including participant no-shows, participant drop-outs, and counselor adherence to time limits.
Weight change
时间窗: Baseline, 1-month, 6-month, and 12-month assessment
Weight will be measured using the Fitbit Aria Air wireless scale, which is accurate to 0.2 kg. In order to maximize accuracy, we will (1) provide instructions (e.g., place scale on flat, hard surface; weigh upon waking, without clothes, after using the bathroom), (2) require participants to confirm that they are following instructions at each assessment point, (3) use an average of 5 consecutive daily weights for each timepoint, (4) remove errant weights (e.g., \>1 kg change in 1 day).
次要结局
- Calorie intake(Baseline, 1-month, 6-month, and 12-month assessment)
- Acceptability as Measured by Likert Self-report Scale(6-month and 12-month assessment)
- Physical Activity(Baseline, 1-month, 6-month, and 12-month assessment)
研究者
elafata@ori.org
Research Scientist
Oregon Research Institute