A Micro-randomized Trial of HeartSteps, an mHealth Intervention for Increasing Physical Activity
Condition: Physical Activity
Study type: Interventional

Summary: 
      The aim of this research is to evaluate the efficacy of contextually tailored activity
      suggestions and activity planning for increasing physical activity among sedentary adults.
    

Detailed description: 
      Physical activity is a key behavioral strategy for prevention of non-communicable diseases
      such as diabetes and heart disease. Mobile health (mHealth) interventions have shown promise
      for supporting physical activity adoption and maintenance in ways that are highly acceptable
      to users, scalable, and cost-efficient. This study examines two intervention
      strategies-contextually tailored activity suggestions and daily planning of the activity for
      the next day-that a mobile health intervention can use to encourage physical activity in
      sedentary adults.

      Study participants use HeartSteps, an mHealth physical intervention developed by the research
      team, in their daily lives for six weeks. Over the course of the study both of the HeartSteps
      intervention components-contextually-tailored activity suggestions and activity planning-are
      micro-randomized for each participant on each of the day of the study, in order the effects
      on physical activity of each component separately and how those effects change over time.

      The primary hypothesis for suggestions is that providing a contextually tailored activity
      suggestion increases participant step count over the subsequent 30 minutes following message
      delivery.

      The first secondary hypothesis for suggestions is that the proximal effect of the
      contextually tailored activity suggestions on the subsequent 30-minute step count will
      decrease with duration in the study.

      The primary hypothesis for planning is that receiving evening planning will increase step
      count on the following day.

      The primary analyses will use the methods developed in Boruvka et al. (2017). The primary
      longitudinal outcome for activity suggestions will be the log of the step count in the 30
      minutes subsequent to decision points. The log of the step count in the 30 minutes prior to
      randomization will be included as a control variable. The primary longitudinal outcome for
      planning will be the square root of the step count on the day following the randomization of
      planning treatment.

      All missing but "available" minute-by-minute step counts from the wrist band will be imputed
      as 0. See "Allocation" section for the definition of availability. Sensitivity analyses using
      step counts from the mobile phone (secondary data source) will be conducted.
    

Intervention name(s): HeartSteps: A just-in-time adaptive intervention for increasing physical activity amongst sedentary adults.
Intervention type(s): Behavioral
Intervention description(s): HeartSteps is an Android-based mHealth intervention that contains two main intervention components: contextually-tailored suggestions for activity and planning of the next day's activity. Activity suggestions provide individuals with actionable suggestions for how they can be active in their current context. Delivered suggestions are tailored based on time of day, user's location, day of the week (weekend/weekday), and weather. HeartSteps can deliver a user activity suggestions up to five times a day. Evening planning asks users to create or choose a plan of how they will be active on the following day. Planning can be delivered once a day, in the evening.
Intervention model: Single Group Assignment
Intervention model description: Each participant-time point is randomized between intervention or no intervention (delivery of a contextually tailored activity suggestion or no suggestion; planning or no planning)
Masking: None (Open Label)
Primary purpose: Treatment
Keywords: Physical Activity; Mobile Health; Self Monitoring; Wearable Sensors; Tailored Health Communication; Implementation Intentions; Mobile Apps; Anti-Sedentary Behavior; Opportunistic Physical Activity; Health Belief Model