<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/NCT03837366</url>
  </required_header>
  <id_info>
    <org_study_id>LEllingson_Fitbit_Intervention</org_study_id>
    <nct_id>NCT03837366</nct_id>
  </id_info>
  <brief_title>Evaluating Motivational Interviewing and Habit Formation to Enhance the Effect of Activity Trackers on Physical Activity</brief_title>
  <official_title>Evaluating Motivational Interviewing and Habit Formation to Enhance the Effect of Activity Trackers on Healthy Adults' Activity Levels: A Randomized Intervention</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Laura Ellingson-Sayen</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Iowa State University</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Wearable fitness monitors are increasingly popular but the actual utility of these devices&#xD;
      for promoting physical activity behavior is unknown. The purpose is to examine the efficacy&#xD;
      of the Fitbit monitor for previously inactive individuals when used alone or following brief&#xD;
      training in behavior change strategies and techniques. Psychosocial factors will be assessed&#xD;
      and changes in physical activity will be monitored over three months to determine the&#xD;
      efficacy of this intervention and to better understand individual differences in&#xD;
      effectiveness.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The objective for this pilot study is to determine the efficacy of the Fitbit Charge wearable&#xD;
      fitness monitor alone or in combination with additional behavior change strategies for&#xD;
      increasing physical activity in inactive adults. A secondary objective is to assess the&#xD;
      influence of psychosocial factors (e.g. self-efficacy, self-regulation, habit formation) on&#xD;
      the effectiveness of this type of behavior change intervention. The central hypothesis is&#xD;
      that use of the Fitbit will increase physical activity from baseline and that adding&#xD;
      additional strategies will enhance this effect. This hypothesis is based on previous research&#xD;
      demonstrating that continuous self- monitoring (using wearable technology) is effective in&#xD;
      promotion of weight-loss in overweight and obese adults. This objective will be addressed&#xD;
      through pursuing the following specific aims.&#xD;
&#xD;
      Aim 1: To determine the efficacy of using the Fitbit to increase physical activity behaviors&#xD;
      and improve health markers in inactive adults. The working hypothesis is that wearing a&#xD;
      Fitbit for 3 months will increase physical activity and improve health markers from baseline&#xD;
      to follow-up in inactive adults.&#xD;
&#xD;
      Aim 2: To compare the efficacy of the Fitbit alone to the Fitbit in combination with behavior&#xD;
      change strategies for increasing physical activity and improving psychosocial factors in&#xD;
      inactive adults. The working hypothesis is that using the Fitbit along with behavior change&#xD;
      strategies will lead to greater improvements in physical activity and psychosocial factors&#xD;
      (self- motivation, self-regulation, self-efficacy, and social support) than using the Fitbit&#xD;
      alone.&#xD;
&#xD;
      Aim 3: To assess the influence of individual differences in psychosocial variables on changes&#xD;
      in physical activity over the intervention. The working hypothesis is that higher levels of&#xD;
      self- motivation, self-regulation, self-efficacy, and social support at baseline will be&#xD;
      predictive of greater improvements in physical activity over the intervention, regardless of&#xD;
      group assignment.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">June 11, 2015</start_date>
  <completion_date type="Actual">March 3, 2016</completion_date>
  <primary_completion_date type="Actual">March 3, 2016</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>
    <intervention_model_description>Participants are randomized to one of two groups. One group received an activity tracker and the other received an activity tracker in combination with Health Coaching.</intervention_model_description>
    <primary_purpose>Prevention</primary_purpose>
    <masking>Single (Outcomes Assessor)</masking>
    <masking_description>Individuals processing outcome data are blinded to experimental condition.</masking_description>
  </study_design_info>
  <primary_outcome>
    <measure>Steps</measure>
    <time_frame>3 months</time_frame>
    <description>Average steps accumulated per day assessed via the activPAL</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Moderate and Vigorous Physical Activity</measure>
    <time_frame>3 months</time_frame>
    <description>Average minutes per day assessed via a combination of activPAL and ActiGraph</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Habit Development</measure>
    <time_frame>3 months</time_frame>
    <description>Measured via the Automaticity Index of the Self-Reported Habit Index. The Self-Reported Habit Index consists of 12 items and the Automaticity Subscale includes 4 of these 12. Each item is scored on a 5-point (0-4) Likert scale with anchors ranging from strongly disagree (0) to strongly agree (4). As such, scores for the Automaticity Index range from 0-16 with higher scores indicating stronger habits.</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">91</enrollment>
  <condition>Physical Activity Promotion</condition>
  <arm_group>
    <arm_group_label>Activity Tracker with Health Coaching</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Participants assigned to this condition will receive a Fitbit activity tracker to use for 3 months. Also, they will be asked to come in for a visit approximately one week following baseline assessments. Using the principles of Motivational Interviewing and Habit Formation, participants will discuss their perceived benefits and barriers of becoming more physically active with a member of the research team. They will also be encouraged to set a goal related to using their Fitbit to increase their physical activity. Lastly, they will be given information regarding habit formation and encouraged to identify one or more cues that regularly occur in their daily life to check their Fitbit data as a prompt to engage in physical activity.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Activity Tracker alone</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>Participants assigned to this condition will use their Fitbit on their own for the duration of 3- month intervention, similar to the experience of participants buying the device off-the-shelf.</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Activity tracker and health coaching</intervention_name>
    <description>Use of an activity tracker alone or in combination with health coaching on physical activity behaviors.</description>
    <arm_group_label>Activity Tracker alone</arm_group_label>
    <arm_group_label>Activity Tracker with Health Coaching</arm_group_label>
    <other_name>Fitbit</other_name>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Not meeting physical activity guidelines&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Meeting physical activity guidelines&#xD;
&#xD;
          -  Injury or condition that limits mobility&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>24 Years</minimum_age>
    <maximum_age>60 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Laura D Ellingson-Sayen, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Iowa State University</affiliation>
  </overall_official>
  <verification_date>February 2019</verification_date>
  <study_first_submitted>February 7, 2019</study_first_submitted>
  <study_first_submitted_qc>February 8, 2019</study_first_submitted_qc>
  <study_first_posted type="Actual">February 12, 2019</study_first_posted>
  <last_update_submitted>February 11, 2019</last_update_submitted>
  <last_update_submitted_qc>February 11, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">February 15, 2019</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor-Investigator</responsible_party_type>
    <investigator_affiliation>Iowa State University</investigator_affiliation>
    <investigator_full_name>Laura Ellingson-Sayen</investigator_full_name>
    <investigator_title>Assistant Professor</investigator_title>
  </responsible_party>
  <keyword>Activity tracker</keyword>
  <keyword>Physical Activity</keyword>
  <keyword>mHealth</keyword>
  <keyword>habit</keyword>
  <keyword>Motivational Interviewing</keyword>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- 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/NCT03837366
org study id: LEllingson_Fitbit_Intervention
nct id: NCT03837366
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Wearable fitness monitors are increasingly popular but the actual utility of these devices
      for promoting physical activity behavior is unknown. The purpose is to examine the efficacy
      of the Fitbit monitor for previously inactive individuals when used alone or following brief
      training in behavior change strategies and techniques. Psychosocial factors will be assessed
      and changes in physical activity will be monitored over three months to determine the
      efficacy of this intervention and to better understand individual differences in
      effectiveness.
The objective for this pilot study is to determine the efficacy of the Fitbit Charge wearable
      fitness monitor alone or in combination with additional behavior change strategies for
      increasing physical activity in inactive adults. A secondary objective is to assess the
      influence of psychosocial factors (e.g. self-efficacy, self-regulation, habit formation) on
      the effectiveness of this type of behavior change intervention. The central hypothesis is
      that use of the Fitbit will increase physical activity from baseline and that adding
      additional strategies will enhance this effect. This hypothesis is based on previous research
      demonstrating that continuous self- monitoring (using wearable technology) is effective in
      promotion of weight-loss in overweight and obese adults. This objective will be addressed
      through pursuing the following specific aims.

      Aim 1: To determine the efficacy of using the Fitbit to increase physical activity behaviors
      and improve health markers in inactive adults. The working hypothesis is that wearing a
      Fitbit for 3 months will increase physical activity and improve health markers from baseline
      to follow-up in inactive adults.

      Aim 2: To compare the efficacy of the Fitbit alone to the Fitbit in combination with behavior
      change strategies for increasing physical activity and improving psychosocial factors in
      inactive adults. The working hypothesis is that using the Fitbit along with behavior change
      strategies will lead to greater improvements in physical activity and psychosocial factors
      (self- motivation, self-regulation, self-efficacy, and social support) than using the Fitbit
      alone.

      Aim 3: To assess the influence of individual differences in psychosocial variables on changes
      in physical activity over the intervention. The working hypothesis is that higher levels of
      self- motivation, self-regulation, self-efficacy, and social support at baseline will be
      predictive of greater improvements in physical activity over the intervention, regardless of
      group assignment.
allocation: Randomized
intervention model: Parallel Assignment
intervention model description: Participants are randomized to one of two groups. One group received an activity tracker and the other received an activity tracker in combination with Health Coaching.
primary purpose: Prevention
masking: Single (Outcomes Assessor)
masking description: Individuals processing outcome data are blinded to experimental condition.
measure: Steps
time frame: 3 months
description: Average steps accumulated per day assessed via the activPAL
measure: Moderate and Vigorous Physical Activity
time frame: 3 months
description: Average minutes per day assessed via a combination of activPAL and ActiGraph
measure: Habit Development
time frame: 3 months
description: Measured via the Automaticity Index of the Self-Reported Habit Index. The Self-Reported Habit Index consists of 12 items and the Automaticity Subscale includes 4 of these 12. Each item is scored on a 5-point (0-4) Likert scale with anchors ranging from strongly disagree (0) to strongly agree (4). As such, scores for the Automaticity Index range from 0-16 with higher scores indicating stronger habits.
arm group label: Activity Tracker with Health Coaching
arm group type: Experimental
description: Participants assigned to this condition will receive a Fitbit activity tracker to use for 3 months. Also, they will be asked to come in for a visit approximately one week following baseline assessments. Using the principles of Motivational Interviewing and Habit Formation, participants will discuss their perceived benefits and barriers of becoming more physically active with a member of the research team. They will also be encouraged to set a goal related to using their Fitbit to increase their physical activity. Lastly, they will be given information regarding habit formation and encouraged to identify one or more cues that regularly occur in their daily life to check their Fitbit data as a prompt to engage in physical activity.
arm group label: Activity Tracker alone
arm group type: Active Comparator
description: Participants assigned to this condition will use their Fitbit on their own for the duration of 3- month intervention, similar to the experience of participants buying the device off-the-shelf.
intervention type: Behavioral
intervention name: Activity tracker and health coaching
description: Use of an activity tracker alone or in combination with health coaching on physical activity behaviors.
arm group label: Activity Tracker alone
arm group label: Activity Tracker with Health Coaching
other name: Fitbit
criteria: 
gender: All
minimum age: 24 Years
maximum age: 60 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Laura D Ellingson-Sayen, PhD
role: Principal Investigator
affiliation: Iowa State University
responsible party type: Sponsor-Investigator
investigator affiliation: Iowa State University
investigator full name: Laura Ellingson-Sayen
investigator title: Assistant Professor
sharing ipd: No