Impact of biofeedback and digitalized motivational interviewing on daily physical activity: Series of factorial N-of-1 RCTs piloting the Precious app (Preprint)

BACKGROUND Insufficient physical activity is an increasing public health concern. New technologies may help to change physical activity levels while also enabling the identification of key predictors with high accuracy. The Precious smartphone app was developed to investigate the effect of specific, modular intervention elements on physical activity, and to examine theory-based predictors within individuals. OBJECTIVE This study pilot tested a fully automated factorial N-of-1 RCT with the Precious app and examined if (1) digitalized motivational interviewing (dMI) and (2) heart-rate variability-based biofeedback features increase objectively recorded steps. The secondary aim was to assess whether daily self-efficacy and motivation predict within-person variability in daily steps. METHODS Fifteen adults took part in a 40-day factorial N-of-1 randomized controlled trial. They installed two study apps onto their phones: app 1 to receive intervention elements on individually randomized days and app 2 to collect Ecological Momentary Assessment (EMA) data on self-efficacy, motivation, perceived barriers, pain and illness. Steps were tracked through Xiaomi Mi Band activity bracelets. The factorial design included seven two-day biofeedback interventions with a Firstbeat bodyguard 2 heart-rate variability sensor, and seven two-day dMI interventions, a washout-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 with aggregated data using longitudinal multilevel modeling (level 1: daily observations, level 2: participants). The analyses adjusted for covariates that also predict daily steps, i.e. within- and between-person perceived barriers, pain or illness, time trends and recurring events. RESULTS All participants finished the study, and adherence to activity bracelet and EMA measurements was high. The implementation of the factorial design was successful, with the dMI features used on average 5.1 times of the 7 available interventions. Biofeedback interventions were used on average 5.7 times out of 7, though three participants used this feature a day later than suggested and one missed all suggested timings. Neither within- nor between-persons analyses revealed and significant intervention effects on step counts. Self-efficacy predicted steps in four individuals. Motivation predicted steps in three individuals. Aggregated data from 14 participants showed group-level effects: daily self-efficacy (B=.462, p<.001), motivation (B=.390, p<.001), and pain or illness (B=-1524, p<.001) were the strongest predictors of daily steps in all participants. 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, while 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 effects vary between individuals. This study provides recommendations based on the lessons learned on the implementation of factorial N-of-1 RCTs. CLINICALTRIAL The trial was not formally pre-registered, as conventions for registration of factorial n-of-1 experimental studies had not been established prior to this study’s commencement in 2016. However, a dated publicly available version of the study protocol was published just after the start of data collection and prior to any data analyses (Helf et al., 2016, pp. 13–17).