<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/NCT03787615</url>
  </required_header>
  <id_info>
    <org_study_id>STUDY00010778</org_study_id>
    <secondary_id>UL1TR002014</secondary_id>
    <nct_id>NCT03787615</nct_id>
  </id_info>
  <brief_title>Feasibility of Using sipIT Tools to Increase Compliance With Fluid Consumption Guidelines in Urolithiasis-Prone Subjects</brief_title>
  <acronym>sipIT</acronym>
  <official_title>Feasibility of Using sipIT Tools to Increase Compliance With Fluid Consumption Guidelines in Urolithiasis -Prone Subjects</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Penn State University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>National Institutes of Health (NIH)</agency>
      <agency_class>NIH</agency_class>
    </collaborator>
  </sponsors>
  <source>Penn State University</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>Yes</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      The purpose of this study is to examine the feasibility of using sipIT tools (i.e.,&#xD;
      wrist-worn sensors, smart water bottles, mobile applications) to increase compliance with&#xD;
      physician-recommended fluid consumption guidelines in participants with a history of&#xD;
      urolithiasis. The study aims to: 1) deliver notifications regarding fluid consumption to the&#xD;
      FitBit Versa and the participant's smartphone based on the participant's assessed fluid&#xD;
      intake, and 2) determine the acceptability of using the sipIT tools to increase fluid&#xD;
      consumption. It is hypothesized that receiving notifications regarding fluid consumption will&#xD;
      lead to an increased compliance in attaining fluid consumption guidelines. Further, it is&#xD;
      hypothesized that the frequency of notifications will diminish across the study duration.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Complying with fluid consumption guidelines provides a variety of health benefits. Patients&#xD;
      with a history of urolithiasis are a segment of the population that can benefit from meeting&#xD;
      physician-recommended fluid consumption guidelines. Preliminary studies with this population&#xD;
      have revealed patient interest in using various technologies (i.e., wrist-worn sensors, smart&#xD;
      water bottles, mobile applications) to increase their fluid consumption but the investigators&#xD;
      are not aware of any that combine multiple technologies. The investigators' long-term goal is&#xD;
      to examine if just-in-time reminder notifications to drink following periods when patients&#xD;
      have not been drinking will increase compliance among patients with a history of&#xD;
      urolithiasis. To prepare for that study, the investigators seek to evaluate the feasibility&#xD;
      and acceptability of the sipIT tools in this study.&#xD;
&#xD;
      This study is part three of a set of studies aimed at determining the feasibility of using&#xD;
      technology to increase compliance with fluid consumption guidelines. Preliminary data&#xD;
      included 1) a focus group of participants with a history of urolithiasis and 2) a lab study&#xD;
      to examine the feasibility of using wrist-worn sensors to detect non-alcoholic drinking&#xD;
      events. Data from the focus group revealed that participants are interested in using a&#xD;
      variety of technologies (e.g., wrist-worn sensors, smart water bottles, mobile applications)&#xD;
      to assist with increasing fluid consumption. Data from the lab study revealed that using&#xD;
      wrist-worn inertial sensors to detect drinking events is feasible. Based on data from the lab&#xD;
      study, an algorithm was developed to detect these drinking events and has been implemented in&#xD;
      a consumer smartwatch consumer smartwatch app for just-in-time drinking detection.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">November 19, 2018</start_date>
  <completion_date type="Actual">December 1, 2019</completion_date>
  <primary_completion_date type="Actual">December 1, 2019</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>N/A</allocation>
    <intervention_model>Single Group Assignment</intervention_model>
    <intervention_model_description>A variety of technologies (e.g., wrist-worn sensors, smart water bottles, mobile applications) can be utilized to engage participants over time and support compliance with increasing fluid consumption.</intervention_model_description>
    <primary_purpose>Prevention</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Adherence to Intervention Assessed by Study Completion</measure>
    <time_frame>3 months</time_frame>
    <description>Participants who continue to use the sipIT tools (app, connected water bottle, and smartwatch) at 3 month follow-up</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Difficulty of Use Subscale of the User Burden Scale</measure>
    <time_frame>3 months</time_frame>
    <description>Difficulty of Use subscale of the User Burden Scale (Suh et al., 2016).</description>
  </secondary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">31</enrollment>
  <condition>Urolithiasis</condition>
  <arm_group>
    <arm_group_label>The sipIT tools</arm_group_label>
    <arm_group_type>Other</arm_group_type>
    <description>The wrist-worn sensors used to detect a drinking event (FitBit Versa with custom algorithm), an H2OPal connected water bottle and fluid consumption monitoring mobile applications.</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>sipIT tools</intervention_name>
    <description>Just in time drinking detection tools to promote increase fluid consumption</description>
    <arm_group_label>The sipIT tools</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Fluent in spoken and written English, and capable of providing informed consent&#xD;
&#xD;
          -  Own an iPhone (version 6 or higher)&#xD;
&#xD;
          -  History of urolithiasis&#xD;
&#xD;
          -  Willingness to complete all study procedures: completing questionnaires, participating&#xD;
             in semi-structured interviews, tracking fluid consumption, wearing a FitBit Versa and&#xD;
             receiving notifications on the FitBit and their smartphone for a three-month period&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Any medical condition that interferes with regular fluid consumption&#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>David E Conroy, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>The Pennsylvania State University</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>The Pennsylvania State University</name>
      <address>
        <city>University Park</city>
        <state>Pennsylvania</state>
        <zip>16802</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>March 2021</verification_date>
  <study_first_submitted>December 20, 2018</study_first_submitted>
  <study_first_submitted_qc>December 21, 2018</study_first_submitted_qc>
  <study_first_posted type="Actual">December 26, 2018</study_first_posted>
  <results_first_submitted>January 28, 2021</results_first_submitted>
  <results_first_submitted_qc>March 11, 2021</results_first_submitted_qc>
  <results_first_posted type="Actual">March 17, 2021</results_first_posted>
  <last_update_submitted>March 11, 2021</last_update_submitted>
  <last_update_submitted_qc>March 11, 2021</last_update_submitted_qc>
  <last_update_posted type="Actual">March 17, 2021</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Penn State University</investigator_affiliation>
    <investigator_full_name>David E Conroy</investigator_full_name>
    <investigator_title>Professor of Kinesiology and Human Development &amp; Family Studies</investigator_title>
  </responsible_party>
  <keyword>kidney</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Urolithiasis</mesh_term>
    <mesh_term>Urinary Calculi</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
    <ipd_description>There is no plan to share the individual participant data with other researchers.</ipd_description>
  </patient_data>
  <provided_document_section>
    <provided_document>
      <document_type>Study Protocol and Statistical Analysis Plan</document_type>
      <document_has_protocol>Yes</document_has_protocol>
      <document_has_icf>No</document_has_icf>
      <document_has_sap>Yes</document_has_sap>
      <document_date>October 30, 2018</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/15/NCT03787615/Prot_SAP_000.pdf</document_url>
    </provided_document>
    <provided_document>
      <document_type>Informed Consent Form</document_type>
      <document_has_protocol>No</document_has_protocol>
      <document_has_icf>Yes</document_has_icf>
      <document_has_sap>No</document_has_sap>
      <document_date>November 12, 2018</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/15/NCT03787615/ICF_002.pdf</document_url>
    </provided_document>
  </provided_document_section>

  <clinical_results>

    <participant_flow>
      <group_list>
        <group group_id="P1">
          <title>The sipIT Tools</title>
          <description>The wrist-worn sensors used to detect a drinking event (FitBit Versa with custom algorithm), an H2OPal connected water bottle and fluid consumption monitoring mobile applications.&#xD;
sipIT tools: Just in time drinking detection tools to promote increase fluid consumption</description>
        </group>
      </group_list>
      <period_list>
        <period>
          <title>Overall Study</title>
          <milestone_list>
            <milestone>
              <title>STARTED</title>
              <participants_list>
                <participants group_id="P1" count="31"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="27"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>NOT COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="4"/>
              </participants_list>
            </milestone>
          </milestone_list>
          <drop_withdraw_reason_list>
            <drop_withdraw_reason>
              <title>Withdrawal by Subject</title>
              <participants_list>
                <participants group_id="P1" count="2"/>
              </participants_list>
            </drop_withdraw_reason>
            <drop_withdraw_reason>
              <title>Lost to Follow-up</title>
              <participants_list>
                <participants group_id="P1" count="2"/>
              </participants_list>
            </drop_withdraw_reason>
          </drop_withdraw_reason_list>
        </period>
      </period_list>
    </participant_flow>

    <baseline>
      <group_list>
        <group group_id="B1">
          <title>The sipIT Tools</title>
          <description>The wrist-worn sensors used to detect a drinking event (FitBit Versa with custom algorithm), an H2OPal connected water bottle and fluid consumption monitoring mobile applications.&#xD;
sipIT tools: Just in time drinking detection tools to promote increase fluid consumption</description>
        </group>
      </group_list>
      <analyzed_list>
        <analyzed>
          <units>Participants</units>
          <scope>Overall</scope>
          <count_list>
            <count group_id="B1" value="31"/>
          </count_list>
        </analyzed>
      </analyzed_list>
      <measure_list>
        <measure>
          <title>Age</title>
          <units>years</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="40.0" spread="14.3"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Sex: Female, Male</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>Female</title>
                  <measurement_list>
                    <measurement group_id="B1" value="18"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Male</title>
                  <measurement_list>
                    <measurement group_id="B1" value="13"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Ethnicity (NIH/OMB)</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>Hispanic or Latino</title>
                  <measurement_list>
                    <measurement group_id="B1" value="1"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Not Hispanic or Latino</title>
                  <measurement_list>
                    <measurement group_id="B1" value="30"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Unknown or Not Reported</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Race (NIH/OMB)</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>American Indian or Alaska Native</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Asian</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Native Hawaiian or Other Pacific Islander</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Black or African American</title>
                  <measurement_list>
                    <measurement group_id="B1" value="2"/>
                  </measurement_list>
                </category>
                <category>
                  <title>White</title>
                  <measurement_list>
                    <measurement group_id="B1" value="27"/>
                  </measurement_list>
                </category>
                <category>
                  <title>More than one race</title>
                  <measurement_list>
                    <measurement group_id="B1" value="1"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Unknown or Not Reported</title>
                  <measurement_list>
                    <measurement group_id="B1" value="1"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </measure_list>
    </baseline>

    <outcome_list>
      <outcome>
        <type>Primary</type>
        <title>Adherence to Intervention Assessed by Study Completion</title>
        <description>Participants who continue to use the sipIT tools (app, connected water bottle, and smartwatch) at 3 month follow-up</description>
        <time_frame>3 months</time_frame>
        <group_list>
          <group group_id="O1">
            <title>The sipIT Tools</title>
            <description>The wrist-worn sensors used to detect a drinking event (FitBit Versa with custom algorithm), an H2OPal connected water bottle and fluid consumption monitoring mobile applications.&#xD;
sipIT tools: Just in time drinking detection tools to promote increase fluid consumption</description>
          </group>
        </group_list>
        <measure>
          <title>Adherence to Intervention Assessed by Study Completion</title>
          <description>Participants who continue to use the sipIT tools (app, connected water bottle, and smartwatch) at 3 month follow-up</description>
          <units>Participants</units>
          <param>Count of Participants</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="31"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="27"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Difficulty of Use Subscale of the User Burden Scale</title>
        <description>Difficulty of Use subscale of the User Burden Scale (Suh et al., 2016).</description>
        <time_frame>3 months</time_frame>
        <population>Completers at 3-months only</population>
        <group_list>
          <group group_id="O1">
            <title>sipIT Group Completers @ 3 Months</title>
            <description>Participants who completed 3-month follow-up</description>
          </group>
        </group_list>
        <measure>
          <title>Difficulty of Use Subscale of the User Burden Scale</title>
          <description>Difficulty of Use subscale of the User Burden Scale (Suh et al., 2016).</description>
          <population>Completers at 3-months only</population>
          <units>score on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="27"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="NA" spread="NA">In analyses, we found that six items had no variance and all items had mean values &lt;1. Because of these skewed distributions and the restricted range indicative of little to no user burden, most sub-scale internal consistency estimates were not acceptable so scores from this measure were not calculated.</measurement>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
    </outcome_list>

    <reported_events>
      <time_frame>3 months</time_frame>
      <group_list>
        <group group_id="E1">
          <title>The sipIT Tools</title>
          <description>The wrist-worn sensors used to detect a drinking event (FitBit Versa with custom algorithm), an H2OPal connected water bottle and fluid consumption monitoring mobile applications.&#xD;
sipIT tools: Just in time drinking detection tools to promote increase fluid consumption</description>
        </group>
      </group_list>
      <serious_events>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, all-cause mortality</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="31"/>
              </event>
              <event>
                <sub_title>Total, serious adverse events</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="31"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </serious_events>
      <other_events>
        <frequency_threshold>0</frequency_threshold>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, other adverse events</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="31"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </other_events>
    </reported_events>

    <certain_agreements>
      <pi_employee>Principal Investigators are NOT employed by the organization sponsoring the study.</pi_employee>
      <restrictive_agreement>There is NOT an agreement between Principal Investigators and the Sponsor (or its agents) that restricts the PI's rights to discuss or publish trial results after the trial is completed. </restrictive_agreement>
    </certain_agreements>
    <point_of_contact>
      <name_or_title>Dr. David Conroy</name_or_title>
      <organization>The Pennsylvania State University</organization>
      <phone>814-863-3451</phone>
      <email>conroy@psu.edu</email>
    </point_of_contact>
  </clinical_results>
</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/NCT03787615
org study id: STUDY00010778
secondary id: UL1TR002014
nct id: NCT03787615
lead sponsor: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: Yes
The purpose of this study is to examine the feasibility of using sipIT tools (i.e.,
      wrist-worn sensors, smart water bottles, mobile applications) to increase compliance with
      physician-recommended fluid consumption guidelines in participants with a history of
      urolithiasis. The study aims to: 1) deliver notifications regarding fluid consumption to the
      FitBit Versa and the participant's smartphone based on the participant's assessed fluid
      intake, and 2) determine the acceptability of using the sipIT tools to increase fluid
      consumption. It is hypothesized that receiving notifications regarding fluid consumption will
      lead to an increased compliance in attaining fluid consumption guidelines. Further, it is
      hypothesized that the frequency of notifications will diminish across the study duration.
Complying with fluid consumption guidelines provides a variety of health benefits. Patients
      with a history of urolithiasis are a segment of the population that can benefit from meeting
      physician-recommended fluid consumption guidelines. Preliminary studies with this population
      have revealed patient interest in using various technologies (i.e., wrist-worn sensors, smart
      water bottles, mobile applications) to increase their fluid consumption but the investigators
      are not aware of any that combine multiple technologies. The investigators' long-term goal is
      to examine if just-in-time reminder notifications to drink following periods when patients
      have not been drinking will increase compliance among patients with a history of
      urolithiasis. To prepare for that study, the investigators seek to evaluate the feasibility
      and acceptability of the sipIT tools in this study.

      This study is part three of a set of studies aimed at determining the feasibility of using
      technology to increase compliance with fluid consumption guidelines. Preliminary data
      included 1) a focus group of participants with a history of urolithiasis and 2) a lab study
      to examine the feasibility of using wrist-worn sensors to detect non-alcoholic drinking
      events. Data from the focus group revealed that participants are interested in using a
      variety of technologies (e.g., wrist-worn sensors, smart water bottles, mobile applications)
      to assist with increasing fluid consumption. Data from the lab study revealed that using
      wrist-worn inertial sensors to detect drinking events is feasible. Based on data from the lab
      study, an algorithm was developed to detect these drinking events and has been implemented in
      a consumer smartwatch consumer smartwatch app for just-in-time drinking detection.
allocation: N/A
intervention model: Single Group Assignment
intervention model description: A variety of technologies (e.g., wrist-worn sensors, smart water bottles, mobile applications) can be utilized to engage participants over time and support compliance with increasing fluid consumption.
primary purpose: Prevention
masking: None (Open Label)
measure: Adherence to Intervention Assessed by Study Completion
time frame: 3 months
description: Participants who continue to use the sipIT tools (app, connected water bottle, and smartwatch) at 3 month follow-up
measure: Difficulty of Use Subscale of the User Burden Scale
time frame: 3 months
description: Difficulty of Use subscale of the User Burden Scale (Suh et al., 2016).
arm group label: The sipIT tools
arm group type: Other
description: The wrist-worn sensors used to detect a drinking event (FitBit Versa with custom algorithm), an H2OPal connected water bottle and fluid consumption monitoring mobile applications.
intervention type: Device
intervention name: sipIT tools
description: Just in time drinking detection tools to promote increase fluid consumption
arm group label: The sipIT tools
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
last name: David E Conroy, PhD
role: Principal Investigator
affiliation: The Pennsylvania State University
facility: 
country: United States
responsible party type: Principal Investigator
investigator affiliation: Penn State University
investigator full name: David E Conroy
investigator title: Professor of Kinesiology and Human Development & Family Studies
mesh term: Urolithiasis
mesh term: Urinary Calculi
sharing ipd: No
ipd description: There is no plan to share the individual participant data with other researchers.
provided document: 
provided document: 
participant flow: 
baseline: 
outcome list: 
reported events: 
certain agreements: 
point of contact: 