背景:身体活动不足是一个公共卫生问题。新技术可以提高身体活动水平,并能够高精度地识别其预测因子。开发了珍贵的智能手机应用程序,以调查特定的模块化干预元素对身体活动的影响,并检查基于理论的预测因素。
目的:本研究采用Preciousapp对一项全自动因子N-of-1随机对照试验(RCT)进行了初步测试,并检查了数字化动机访谈(dMI)和基于心率变异性的生物反馈功能是否增加了客观记录的步骤。次要目的是评估日常自我效能感和动机是否可以预测日常步骤中的人内变异性。
方法:总共,从报纸广告中招募的15名成年人参加了为期40天的阶乘N-of-1RCT。他们在手机上安装了2个研究应用程序:一个用于接收干预元素,另一个用于收集有关自我效能感的生态瞬时评估(EMA)数据。动机,感知障碍,疼痛,和疾病。使用小米MiBand活动手镯跟踪步骤。阶乘设计包括7个2天的生物反馈干预措施,使用FirstbeatBodyguard2(FirstbeatTechnologiesLtd)心率变异性传感器,7个为期2天的DMI干预,每次干预后的一天,11个控制日EMA问题每天发送两次。自我效能感的影响,动机,使用人内动态回归模型分析后续步骤的干预措施,并使用纵向多水平建模(1级:每日观察;2级:参与者)汇总数据.分析对协变量进行了调整(即,在人与人之间的感知障碍,疼痛或疾病,时间趋势,和经常性事件)。
结果:所有参与者都完成了研究,对活动手镯和EMA测量的依从性很高。阶乘设计的实施是成功的,使用的dmi功能,平均而言,7种可用干预措施的5.1(SD1.0)倍。使用生物反馈干预措施,平均而言,5.7(SD1.4)次,共7次,尽管3名参与者比建议的时间晚一天使用此功能,而1名参与者根本没有使用它。人员内部和人员之间的分析均未显示出对步数的显着干预作用。27%(4/15)的参与者对自我效能感进行了预测。动机预测20%(3/15)的参与者的步骤。汇总数据显示白天自我效能感的显著群体水平效应(B=0.462;P<.001),动机(B=0.390;P<.001),和疼痛或疾病(B=-1524;P<.001)每天的步骤。
结论:使用Precious应用程序的自动阶乘N-of-1试验大多是可行和可接受的,特别是DMI组件的自动交付,而自我传导的生物反馈测量更难以正确计时。研究结果表明,自我效能感和动机的变化可能会对体育锻炼产生当天的影响,但是效果因人而异。本研究根据在执行阶乘N-of-1RCT方面的经验教训提供了建议。
BACKGROUND: Insufficient physical activity is a public health concern. New technologies may improve physical activity levels and enable the identification of its predictors with high accuracy. The Precious smartphone app was developed to investigate the effect of specific modular intervention elements on physical activity and examine theory-based predictors within individuals.
OBJECTIVE: This study pilot-tested a fully automated factorial N-of-1 randomized controlled trial (RCT) with the Precious app and examined whether digitalized motivational interviewing (dMI) and heart rate variability-based biofeedback features increased objectively recorded steps. The secondary aim was to assess whether daily self-efficacy and motivation predicted within-person variability in daily steps.
METHODS: In total, 15 adults recruited from newspaper advertisements participated in a 40-day factorial N-of-1 RCT. They installed 2 study apps on their phones: one to receive intervention elements and one to collect ecological momentary assessment (EMA) data on self-efficacy, motivation, perceived barriers, pain, and illness. Steps were tracked using Xiaomi Mi Band activity bracelets. The factorial design included seven 2-day biofeedback interventions with a Firstbeat Bodyguard 2 (Firstbeat Technologies Ltd) heart rate variability sensor, seven 2-day dMI interventions, a wash-out day after each intervention, and 11 control days. EMA questions were sent twice per day. The effects of self-efficacy, motivation, and the interventions on subsequent steps were analyzed using within-person dynamic regression models and aggregated data using longitudinal multilevel modeling (level 1: daily observations; level 2: participants). The analyses were adjusted for covariates (ie, within- and between-person perceived barriers, pain or illness, time trends, and recurring events).
RESULTS: All participants completed the study, and adherence to activity bracelets and EMA measurements was high. The implementation of the factorial design was successful, with the dMI features used, on average, 5.1 (SD 1.0) times of the 7 available interventions. Biofeedback interventions were used, on average, 5.7 (SD 1.4) times out of 7, although 3 participants used this feature a day later than suggested and 1 did not use it at all. Neither within- nor between-person analyses revealed significant intervention effects on step counts. Self-efficacy predicted steps in 27% (4/15) of the participants. Motivation predicted steps in 20% (3/15) of the participants. Aggregated data showed significant group-level effects of day-level self-efficacy (B=0.462; P<.001), motivation (B=0.390; P<.001), and pain or illness (B=-1524; P<.001) on daily steps.
CONCLUSIONS: The automated factorial N-of-1 trial with the Precious app was mostly feasible and acceptable, especially the automated delivery of the dMI components, whereas self-conducted biofeedback measurements were more difficult to time correctly. The findings suggest that changes in self-efficacy and motivation may have same-day effects on physical activity, but the effects vary across individuals. This study provides recommendations based on the lessons learned on the implementation of factorial N-of-1 RCTs.