Can Methods From Computational Psychology be Used to Phenotype Individuals Most Likely to be Non-adherent to Fitness Goals?
试验速览
- 阶段
- 不适用
- 入组人数
- 200
- 试验地点
- 1
- 主要终点
- Change in physical activity measured by an increase in weekly steps measured by Fitbit.
研究概览
简要总结
This is a longitudinal study combining objective sensor data, with decision-making games and contextual personality traits to identify patterns in exercise decay. The data generated will be used to build computational models to predict digital personas, and help identify those individuals most likely to abandon exercise goals.
详细描述
Interested individuals to be recruited on social media and invited to download the study app. The plain language statement and informed consent are embedded in the app. Once e-consent is obtained, individuals will share their Fitbit data and complete the following questionnaires; Type D Personality, Goal Setting, and Self-Efficacy questionnaire and a decision-making game based on the IGT. After a 6 month time period, they will be requested to retake the questionnaires and decision-making game.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Healthy individuals who have a Fitbit
排除标准
- •Individuals under the age of 18 years of age.
结局指标
主要结局
Change in physical activity measured by an increase in weekly steps measured by Fitbit.
时间窗: Week 1 and 6 months
Fitbit is a physical activity tracker worn on the wrist and objectively measures steps taken.
次要结局
未报告次要终点