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.

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.

Inclusion Criteria:

• English speakers,
• between 18 and 60 years of age,
• could walk for exercise without discomfort, and
• either had a full-time daytime job or a regular schedule outside the home (e.g., students)
• have a personal phone running Android 5.0 or higher or willing to use a study-provided phone as their primary phone for the duration of the study.

Exclusion Criteria:

• Need medical supervision to exercise
• Currently using an activity tracker (e.g., FitBit)

A de-identified dataset (i.e., containing no raw location/GPS information) will be generated and made available to the research community. The dataset will be stripped of all codes or any other information that could be linked back to the original data or to an individual participant. Prospective users of this dataset must agree to a confidentiality agreement, meaning that they must get permission from the HeartSteps Primary Investigator to share the data with anyone else. All external requests for data will be directed to Dr. Predrag Klasnja. Prospective investigators will submit a written proposal to the HeartSteps Investigator Team outlining the question they will investigate, the specific variables that they need to answer that question, their analytic plan for answering that question, and documentation of sufficient Institutional Review Board oversight (e.g., approval or exemption). Investigators will also need to sign a confidentiality agreement.