<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT02206893</url>
  </required_header>
  <id_info>
    <org_study_id>HS14-249</org_study_id>
    <nct_id>NCT02206893</nct_id>
  </id_info>
  <brief_title>Evaluating Consumer m-Health Services for User Engagement and Health Promotion: An Organizational Field Experiment</brief_title>
  <sponsors>
    <lead_sponsor>
      <agency>Carnegie Mellon University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Carnegie Mellon University</source>
  <brief_summary>
    <textblock>
      Introduction Chronic disease is prevalent and costly in the U.S. (Tu &amp; Cohen, 2009). Poor&#xD;
      eating habit is one factor that account for risk of chronic disease (Arsand, Varmedal, &amp;&#xD;
      Hartvigsen, 2007). Smartphone technology has been promising to improve preventive health&#xD;
      outcomes. However, its great potential has not been widely applied to people's eating&#xD;
      behaviors and its impact is unknown.&#xD;
&#xD;
      Professional and peer supports can improve health status (Elkjaer et al., 2010; Lorig et al.,&#xD;
      1999; Perri, Sears, &amp; Clark, 1993). However, the former is usually delivered didactically or&#xD;
      passively with limited use of smartphones. There is also little evidence of the effect of&#xD;
      peer support delivered by smartphones in the domain of healthy eating. This research aims to&#xD;
      study what smartphone technology can do to upgrade professional and peer supports, and to&#xD;
      evaluate the impact of these mobile-app enabled supports on people's behavior of healthy&#xD;
      eating and user engagement.&#xD;
&#xD;
      Hypotheses&#xD;
&#xD;
      According to Social Cognitive Theory, we hypothesize the following:&#xD;
&#xD;
        1. Mobile-enabled self-monitoring approach improves users' healthy eating behaviors through&#xD;
           improved self-efficacy&#xD;
&#xD;
        2. Professional support improves users' healthy eating behaviors through improved&#xD;
           self-efficacy&#xD;
&#xD;
        3. Peer support improves users' healthy eating behaviors through improved self-efficacy&#xD;
&#xD;
        4. The amount of support is positively correlated with the change in behaviors and their&#xD;
           determinants&#xD;
&#xD;
      Experiment Design The hypotheses will be examined bya 4-month randomized field experiment.&#xD;
      375 subjects will be recruited and assigned to one of the five arms to receive the&#xD;
      corresponding tool for diet management at no cost.&#xD;
&#xD;
      Arm 1: a mobile App with both professional and peer support Arm 2: a mobile App with peer&#xD;
      support only Arm 3: a mobile App with professional support only Arm 4: a mobile App without&#xD;
      any support Arm 5: a non-mobile web App In addition to the App usage data, five surveys are&#xD;
      conducted at baseline and the end of each month. Respondents will be compensated by $8 and a&#xD;
      chance to win $200 for each completed survey.&#xD;
&#xD;
      Interventions&#xD;
&#xD;
        1. All subjects receive the following interventions: an education package includes the&#xD;
           importance of healthy eating, concept of MyPlate, personalized daily food plans;&#xD;
           reminders throughout the study; goal setting capabilities;&#xD;
&#xD;
        2. Self-monitoring provided by an Android App: a heuristic approach inspired by MyPlate to&#xD;
           record their food consumption which allows users to record their meals by images and&#xD;
           doesn't require estimations in cups and ounces; daily reports and trend reports&#xD;
&#xD;
        3. Self-monitoring provided by the web App: a traditional approach to record their food&#xD;
           consumption which requires estimations in cups and ounces, and no images are allowed; no&#xD;
           daily reports and trend reports are provided&#xD;
&#xD;
        4. Professional support provided by a registered dietitian via the Android App: the&#xD;
           supports include the following:&#xD;
&#xD;
             1. Reply to users' messages regarding healthy eating&#xD;
&#xD;
             2. Provide meal-specific comments on subjects' meal consumptions: one meal per week&#xD;
&#xD;
             3. Provide feedback on the subjects' consumption patterns: once per week&#xD;
&#xD;
        5. Peer support provided by other subjects via the Android App: the App provides platforms&#xD;
           for subjects who have the same interest to communicate to each other. The actions the&#xD;
           subjects can do in the platforms include:&#xD;
&#xD;
             1. Post images or texts related to healthy eating&#xD;
&#xD;
             2. Share meals with their ratings&#xD;
&#xD;
             3. Like/dislike others' posts&#xD;
&#xD;
             4. Comment on others' posts e Create groups which allow subjects who have the same&#xD;
                interest to join&#xD;
&#xD;
      Measurements&#xD;
&#xD;
        1. Dependent Variables&#xD;
&#xD;
             1. Eating behavior: a score of healthiness of a meal will be assigned by a dietitian.&#xD;
                The scores obtained by the same subject along the experiment compose the subject's&#xD;
                eating behavior&#xD;
&#xD;
             2. Engaging behavior: this is measured by the number of meals recorded by the subject&#xD;
                in a week. The numbers for the same subject along the experiment compose the&#xD;
                subject's engaging behavior&#xD;
&#xD;
        2. Independent Variables&#xD;
&#xD;
             1. Level of peer support: this will be measured by a score representing the number of&#xD;
                posts, likes, and comments received and given by a subject in a week&#xD;
&#xD;
             2. Level of professional support: this will be measured by a score representing the&#xD;
                number of messages or comments exchanged with the dietitian in a week&#xD;
&#xD;
        3. Mediator Variables: self-efficacy, outcome expectation, and impediments will be measured&#xD;
           by survey instruments&#xD;
&#xD;
      Data&#xD;
&#xD;
        1. User Survey: characteristics and perceptions&#xD;
&#xD;
        2. Mobile App: time, location, and contents of goal setting, meal entries, communications&#xD;
           with professionals and peers&#xD;
&#xD;
        3. Web App: contents of goal setting and meal entries&#xD;
&#xD;
      Analysis Confirmatory factor analysis and statistical modeling such as structural equation&#xD;
      modeling and mixed models will be conducted to test our hypotheses.&#xD;
    </textblock>
  </brief_summary>
  <overall_status>Completed</overall_status>
  <start_date>March 2014</start_date>
  <completion_date type="Actual">October 2014</completion_date>
  <primary_completion_date type="Actual">October 2014</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <primary_purpose>Supportive Care</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Healthy Eating Behavior</measure>
    <time_frame>4 months after signed up</time_frame>
    <description>This will be measured by a score representing the healthiness of each selected meal, evaluated by dietitians. Specifically, the score is composed of three sub-scores: 1) portion of fruits and vegetables (7-point Likert scale); 2) portion of the entire meal (7-point Likert scale); 3) evaluators confidence level (4-point Likert scale). One subject will get one score per week, and hence 16 scores in 4-months.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Engaging Behavior</measure>
    <time_frame>4 months after signed up</time_frame>
    <description>This will be measured by the number of records submitted by the subject via the assigned tool in a week. One subject will get one score per week, and hence 16 scores in 4-months.</description>
  </primary_outcome>
  <number_of_arms>5</number_of_arms>
  <enrollment type="Actual">425</enrollment>
  <condition>Dietary Habits</condition>
  <condition>Compliance Behavior</condition>
  <arm_group>
    <arm_group_label>Mobile: Professional and peer support</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>A mobile app that provides both professional support and peer support</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Mobile: Peer support</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>A mobile app that provides peer support, but not professional support</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Mobile: Professional Support</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>A mobile app that provides professional support, but no peer support</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Mobile: No Support</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>A mobile app that provides neither peer support nor professional support</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Web: No Support</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>A web app that provides neither peer support, nor professional support</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Self-monitoring via Smartphone</intervention_name>
    <arm_group_label>Mobile: No Support</arm_group_label>
    <arm_group_label>Mobile: Peer support</arm_group_label>
    <arm_group_label>Mobile: Professional Support</arm_group_label>
    <arm_group_label>Mobile: Professional and peer support</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Peer support via Smartphone</intervention_name>
    <arm_group_label>Mobile: Peer support</arm_group_label>
    <arm_group_label>Mobile: Professional and peer support</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Professional support via Smartphone</intervention_name>
    <arm_group_label>Mobile: Professional Support</arm_group_label>
    <arm_group_label>Mobile: Professional and peer support</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Self-monitoring via Web (Static)</intervention_name>
    <arm_group_label>Web: No Support</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  age at least 18 years&#xD;
&#xD;
          -  Android smartphone users&#xD;
&#xD;
          -  having internet accessibility on the smartphone during the study period&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  currently participating in other similar programs&#xD;
&#xD;
          -  having specific medical conditions that require specialized diets&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Yi-Chin Lin, MS</last_name>
    <role>Principal Investigator</role>
    <affiliation>Carnegie Mellon University</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Rema Padman, PhD</last_name>
    <role>Study Chair</role>
    <affiliation>Carnegie Mellon University</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Julie Downs, PhD</last_name>
    <role>Study Director</role>
    <affiliation>Carnegie Mellon University</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Vibhanshu Abhishek, PhD</last_name>
    <role>Study Director</role>
    <affiliation>Carnegie Mellon University</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Carnegie Mellon University</name>
      <address>
        <city>Pittsburgh</city>
        <state>Pennsylvania</state>
        <zip>15213</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>July 2015</verification_date>
  <study_first_submitted>July 31, 2014</study_first_submitted>
  <study_first_submitted_qc>July 31, 2014</study_first_submitted_qc>
  <study_first_posted type="Estimate">August 1, 2014</study_first_posted>
  <last_update_submitted>July 27, 2015</last_update_submitted>
  <last_update_submitted_qc>July 27, 2015</last_update_submitted_qc>
  <last_update_posted type="Estimate">July 28, 2015</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Carnegie Mellon University</investigator_affiliation>
    <investigator_full_name>Yi-Chin Lin</investigator_full_name>
    <investigator_title>PhD Candidate</investigator_title>
  </responsible_party>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT02206893
org study id: HS14-249
nct id: NCT02206893
lead sponsor: 
Introduction Chronic disease is prevalent and costly in the U.S. (Tu & Cohen, 2009). Poor
      eating habit is one factor that account for risk of chronic disease (Arsand, Varmedal, &
      Hartvigsen, 2007). Smartphone technology has been promising to improve preventive health
      outcomes. However, its great potential has not been widely applied to people's eating
      behaviors and its impact is unknown.

      Professional and peer supports can improve health status (Elkjaer et al., 2010; Lorig et al.,
      1999; Perri, Sears, & Clark, 1993). However, the former is usually delivered didactically or
      passively with limited use of smartphones. There is also little evidence of the effect of
      peer support delivered by smartphones in the domain of healthy eating. This research aims to
      study what smartphone technology can do to upgrade professional and peer supports, and to
      evaluate the impact of these mobile-app enabled supports on people's behavior of healthy
      eating and user engagement.

      Hypotheses

      According to Social Cognitive Theory, we hypothesize the following:

        1. Mobile-enabled self-monitoring approach improves users' healthy eating behaviors through
           improved self-efficacy

        2. Professional support improves users' healthy eating behaviors through improved
           self-efficacy

        3. Peer support improves users' healthy eating behaviors through improved self-efficacy

        4. The amount of support is positively correlated with the change in behaviors and their
           determinants

      Experiment Design The hypotheses will be examined bya 4-month randomized field experiment.
      375 subjects will be recruited and assigned to one of the five arms to receive the
      corresponding tool for diet management at no cost.

      Arm 1: a mobile App with both professional and peer support Arm 2: a mobile App with peer
      support only Arm 3: a mobile App with professional support only Arm 4: a mobile App without
      any support Arm 5: a non-mobile web App In addition to the App usage data, five surveys are
      conducted at baseline and the end of each month. Respondents will be compensated by $8 and a
      chance to win $200 for each completed survey.

      Interventions

        1. All subjects receive the following interventions: an education package includes the
           importance of healthy eating, concept of MyPlate, personalized daily food plans;
           reminders throughout the study; goal setting capabilities;

        2. Self-monitoring provided by an Android App: a heuristic approach inspired by MyPlate to
           record their food consumption which allows users to record their meals by images and
           doesn't require estimations in cups and ounces; daily reports and trend reports

        3. Self-monitoring provided by the web App: a traditional approach to record their food
           consumption which requires estimations in cups and ounces, and no images are allowed; no
           daily reports and trend reports are provided

        4. Professional support provided by a registered dietitian via the Android App: the
           supports include the following:

             1. Reply to users' messages regarding healthy eating

             2. Provide meal-specific comments on subjects' meal consumptions: one meal per week

             3. Provide feedback on the subjects' consumption patterns: once per week

        5. Peer support provided by other subjects via the Android App: the App provides platforms
           for subjects who have the same interest to communicate to each other. The actions the
           subjects can do in the platforms include:

             1. Post images or texts related to healthy eating

             2. Share meals with their ratings

             3. Like/dislike others' posts

             4. Comment on others' posts e Create groups which allow subjects who have the same
                interest to join

      Measurements

        1. Dependent Variables

             1. Eating behavior: a score of healthiness of a meal will be assigned by a dietitian.
                The scores obtained by the same subject along the experiment compose the subject's
                eating behavior

             2. Engaging behavior: this is measured by the number of meals recorded by the subject
                in a week. The numbers for the same subject along the experiment compose the
                subject's engaging behavior

        2. Independent Variables

             1. Level of peer support: this will be measured by a score representing the number of
                posts, likes, and comments received and given by a subject in a week

             2. Level of professional support: this will be measured by a score representing the
                number of messages or comments exchanged with the dietitian in a week

        3. Mediator Variables: self-efficacy, outcome expectation, and impediments will be measured
           by survey instruments

      Data

        1. User Survey: characteristics and perceptions

        2. Mobile App: time, location, and contents of goal setting, meal entries, communications
           with professionals and peers

        3. Web App: contents of goal setting and meal entries

      Analysis Confirmatory factor analysis and statistical modeling such as structural equation
      modeling and mixed models will be conducted to test our hypotheses.
allocation: Randomized
intervention model: Parallel Assignment
primary purpose: Supportive Care
masking: None (Open Label)
measure: Healthy Eating Behavior
time frame: 4 months after signed up
description: This will be measured by a score representing the healthiness of each selected meal, evaluated by dietitians. Specifically, the score is composed of three sub-scores: 1) portion of fruits and vegetables (7-point Likert scale); 2) portion of the entire meal (7-point Likert scale); 3) evaluators confidence level (4-point Likert scale). One subject will get one score per week, and hence 16 scores in 4-months.
measure: Engaging Behavior
time frame: 4 months after signed up
description: This will be measured by the number of records submitted by the subject via the assigned tool in a week. One subject will get one score per week, and hence 16 scores in 4-months.
arm group label: Mobile: Professional and peer support
arm group type: Experimental
description: A mobile app that provides both professional support and peer support
arm group label: Mobile: Peer support
arm group type: Experimental
description: A mobile app that provides peer support, but not professional support
arm group label: Mobile: Professional Support
arm group type: Experimental
description: A mobile app that provides professional support, but no peer support
arm group label: Mobile: No Support
arm group type: Active Comparator
description: A mobile app that provides neither peer support nor professional support
arm group label: Web: No Support
arm group type: Active Comparator
description: A web app that provides neither peer support, nor professional support
intervention type: Behavioral
intervention name: Self-monitoring via Smartphone
arm group label: Mobile: No Support
arm group label: Mobile: Peer support
arm group label: Mobile: Professional Support
arm group label: Mobile: Professional and peer support
intervention type: Behavioral
intervention name: Peer support via Smartphone
arm group label: Mobile: Peer support
arm group label: Mobile: Professional and peer support
intervention type: Behavioral
intervention name: Professional support via Smartphone
arm group label: Mobile: Professional Support
arm group label: Mobile: Professional and peer support
intervention type: Behavioral
intervention name: Self-monitoring via Web (Static)
arm group label: Web: No Support
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
last name: Yi-Chin Lin, MS
role: Principal Investigator
affiliation: Carnegie Mellon University
last name: Rema Padman, PhD
role: Study Chair
affiliation: Carnegie Mellon University
last name: Julie Downs, PhD
role: Study Director
affiliation: Carnegie Mellon University
last name: Vibhanshu Abhishek, PhD
role: Study Director
affiliation: Carnegie Mellon University
facility: 
country: United States
responsible party type: Principal Investigator
investigator affiliation: Carnegie Mellon University
investigator full name: Yi-Chin Lin
investigator title: PhD Candidate