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The overall goal of this study is to test personalized mobile phone-based physical activity interventions among staff members at the University of California, Berkeley. Most physical fitness applications for smartphones and activity trackers use a constant goal for the number of steps each day. However, if the step goals are dynamically adjusted according to past behavior, then the corresponding goals may encourage individuals to increase their physical activity level. This study consists of a randomized controlled trial in which we are assessing the efficacy of two different algorithms for calculating personalized goals for the number of steps each day.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Personalized Steps Goal | Experimental | Step Goal Delivery by Smartphone |
|
| Constant Steps Goal | Active Comparator | Step Goal Delivery by Smartphone |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Step Goal Delivery by Smartphone | Behavioral |
|
| Measure | Description | Time Frame |
|---|---|---|
| Daily Steps Taken Per Day | 10 weeks |
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Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of California, Berkeley | Berkeley | California | 94720 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 29371177 | Derived | Zhou M, Fukuoka Y, Mintz Y, Goldberg K, Kaminsky P, Flowers E, Aswani A. Evaluating Machine Learning-Based Automated Personalized Daily Step Goals Delivered Through a Mobile Phone App: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2018 Jan 25;6(1):e28. doi: 10.2196/mhealth.9117. |
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| ID | Term |
|---|---|
| D057185 | Sedentary Behavior |
| D009043 | Motor Activity |
| ID | Term |
|---|---|
| D001519 | Behavior |
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