xml: <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/NCT05977517</url>
    </required_header>
    <id_info>
      <org_study_id>NUS1000</org_study_id>
      <nct_id>NCT05977517</nct_id>
    </id_info>
    <brief_title>Sleep, Learning and Wellbeing in NUS Undergraduates: The NUS1000 Study</brief_title>
    <acronym>NUS1000</acronym>
    <official_title>Sleep, Learning and Wellbeing in NUS Undergraduates: The NUS1000 Study</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>National University of Singapore</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>National University of Singapore</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>
        NUS1000 is a large scale freshman-year study of undergraduate sleep, well-being and learning&#xD;
        patterns that has unique key features: (1) continuous objective multi-dimensional data&#xD;
        gathered with passive sensing of sleep and stress over a semester, (2) utilisation of&#xD;
        Learning Management System-based outcome data as a marker of study behaviour and academic&#xD;
        achievement. The goal is to gather information that can be used to improve student sleep,&#xD;
        mental wellbeing and performance.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        The first year in university can be a challenging experience for undergraduates who must&#xD;
        learn to cope with learning in an unfamiliar environment, form new relationships, live away&#xD;
        from home and/or might have to manage personal finances for the first time. These academic,&#xD;
        social, and personal demands can result in significant stress, affecting sleep, learning and&#xD;
        mental/emotional wellbeing. Characterizing and understanding the time-course and&#xD;
        inter-relationship of these demands and their consequences is crucial for making&#xD;
        science-based improvements to a student's university experience. To this end, the&#xD;
        investigators will longitudinally evaluate sleep, learning and wellbeing in ~1000 first-year&#xD;
        students as they adapt to university life to understand how these behaviours fluctuate and&#xD;
        interact throughout the academic term.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">July 30, 2023</start_date>
    <completion_date type="Anticipated">August 2024</completion_date>
    <primary_completion_date type="Anticipated">August 2024</primary_completion_date>
    <study_type>Observational</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <observational_model>Cohort</observational_model>
      <time_perspective>Prospective</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>Change in sleep duration and timing from the start to the end of the semester</measure>
      <time_frame>20 weeks</time_frame>
      <description>The Oura ring is a sleep-tracking device worn on the finger. During the study, participants will need to sync their devices to a mobile app.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change from baseline sleep habits from the start to the end of the semester</measure>
      <time_frame>Week 1-2, Week 8-9, and Week 17-18</time_frame>
      <description>Participants will also be required to complete a set of sleep questionnaires probing sleep habits (bedtime, wake time, time taken to fall asleep, etc.)</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in daily well-being from the start to the end of the semester</measure>
      <time_frame>20 weeks</time_frame>
      <description>Participants will be prompted to fill in brief questions on daily well-being. At the end of each assessment, participants will be required to record an audio clip of their day, without any personal identifiers, for mood/sentiment analysis.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change from baseline well being from the start to the end of the semester</measure>
      <time_frame>Week 1-2, Week 8-9, and Week 17-18</time_frame>
      <description>Participants will also be required to complete a set of well-being questionnaires (e.g., feelings of connectedness or isolation, levels of stress, etc.)</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in learning outcomes from the start to the end of the semester</measure>
      <time_frame>20 weeks</time_frame>
      <description>Grades from quiz/assignments for each module will be collected.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in learning patterns from the start to the end of the semester</measure>
      <time_frame>20 weeks</time_frame>
      <description>Student interactions with the LMS-system will be collected, such as the number of page/file views.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in mood from the start to the end of the semester</measure>
      <time_frame>20 weeks</time_frame>
      <description>At the end of each day, participants will be required to record an audio clip of their day, without any personal identifiers, for mood analysis.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in time-use patterns from the start to the end of the semester</measure>
      <time_frame>Week 1-2, Week 8-9, and Week 17-18</time_frame>
      <description>Participants will be asked to fill out a time-use diary over three 2-week periods throughout the semester, indicating the activities they engaged in over the past day</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in smartphone touchscreen interaction patterns from the start to the end of the semester</measure>
      <time_frame>20 weeks</time_frame>
      <description>Phone taps will be tracked automatically through an EU-GDPR (the European Union's stringent privacy regulation) compliant smartphone app (QuantActions). This application logs human-smartphone screen interactions during regular use by logging a location-specific timestamp for each screen contact.</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Change in movement patterns from the start to the end of the semester</measure>
      <time_frame>20 weeks</time_frame>
      <description>The investigator's in-house smartphone app (Z4IP) will extract movement patterns from location data that will only be kept on the participant's phone up to 96 hours for these computations. The extracted movement patterns (and not geographical locations) will then be uploaded to secure servers, tagged to subject IDs without any personal identifiers, i.e., names and emails will not be linked to their movement patterns. As this component is optional, participants will be asked to indicate if they would like to opt-in at the informed consent stage.</description>
    </secondary_outcome>
    <enrollment type="Anticipated">500</enrollment>
    <condition>Sleep</condition>
    <condition>Well-Being, Psychological</condition>
    <intervention>
      <intervention_type>Behavioral</intervention_type>
      <intervention_name>Sleep and well-being tracking</intervention_name>
      <description>This study will track sleep, learning and wellbeing of 500 freshmen under free-living conditions for 20 weeks</description>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          NUS Freshmen students&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  NUS first-year students with smartphones operating on Android 8.0 and up, or iOS 14.0&#xD;
               or later&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
          Participants will be required to :&#xD;
  &#xD;
            1. Have their sleep and physical activity rhythms will be recorded via wearable sensors,&#xD;
               while they continue daily life as usual.&#xD;
  &#xD;
            2. Complete periodic questionnaires, short daily surveys and daily audio diaries on their&#xD;
               smartphones.&#xD;
  &#xD;
            3. Agree to interactions with their smartphones and as well as grades tracked.&#xD;
               Participants who do not agree to have these measures recorded will not be eligible for&#xD;
               the study.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>25 Years</maximum_age>
      <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
    </eligibility>
    <verification_date>July 2023</verification_date>
    <study_first_submitted>June 27, 2023</study_first_submitted>
    <study_first_submitted_qc>July 26, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 4, 2023</study_first_posted>
    <last_update_submitted>July 26, 2023</last_update_submitted>
    <last_update_submitted_qc>July 26, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 4, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Principal Investigator</responsible_party_type>
      <investigator_affiliation>National University of Singapore</investigator_affiliation>
      <investigator_full_name>Michael W.L. Chee</investigator_full_name>
      <investigator_title>Professor</investigator_title>
    </responsible_party>
    <patient_data>
      <sharing_ipd>Undecided</sharing_ipd>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: 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/NCT05977517
  org study id: NUS1000
  nct id: NCT05977517
  lead sponsor: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  NUS1000 is a large scale freshman-year study of undergraduate sleep, well-being and learning
        patterns that has unique key features: (1) continuous objective multi-dimensional data
        gathered with passive sensing of sleep and stress over a semester, (2) utilisation of
        Learning Management System-based outcome data as a marker of study behaviour and academic
        achievement. The goal is to gather information that can be used to improve student sleep,
        mental wellbeing and performance.
  The first year in university can be a challenging experience for undergraduates who must
        learn to cope with learning in an unfamiliar environment, form new relationships, live away
        from home and/or might have to manage personal finances for the first time. These academic,
        social, and personal demands can result in significant stress, affecting sleep, learning and
        mental/emotional wellbeing. Characterizing and understanding the time-course and
        inter-relationship of these demands and their consequences is crucial for making
        science-based improvements to a student's university experience. To this end, the
        investigators will longitudinally evaluate sleep, learning and wellbeing in ~1000 first-year
        students as they adapt to university life to understand how these behaviours fluctuate and
        interact throughout the academic term.
  observational model: Cohort
  time perspective: Prospective
  measure: Change in sleep duration and timing from the start to the end of the semester
  time frame: 20 weeks
  description: The Oura ring is a sleep-tracking device worn on the finger. During the study, participants will need to sync their devices to a mobile app.
  measure: Change from baseline sleep habits from the start to the end of the semester
  time frame: Week 1-2, Week 8-9, and Week 17-18
  description: Participants will also be required to complete a set of sleep questionnaires probing sleep habits (bedtime, wake time, time taken to fall asleep, etc.)
  measure: Change in daily well-being from the start to the end of the semester
  time frame: 20 weeks
  description: Participants will be prompted to fill in brief questions on daily well-being. At the end of each assessment, participants will be required to record an audio clip of their day, without any personal identifiers, for mood/sentiment analysis.
  measure: Change from baseline well being from the start to the end of the semester
  time frame: Week 1-2, Week 8-9, and Week 17-18
  description: Participants will also be required to complete a set of well-being questionnaires (e.g., feelings of connectedness or isolation, levels of stress, etc.)
  measure: Change in learning outcomes from the start to the end of the semester
  time frame: 20 weeks
  description: Grades from quiz/assignments for each module will be collected.
  measure: Change in learning patterns from the start to the end of the semester
  time frame: 20 weeks
  description: Student interactions with the LMS-system will be collected, such as the number of page/file views.
  measure: Change in mood from the start to the end of the semester
  time frame: 20 weeks
  description: At the end of each day, participants will be required to record an audio clip of their day, without any personal identifiers, for mood analysis.
  measure: Change in time-use patterns from the start to the end of the semester
  time frame: Week 1-2, Week 8-9, and Week 17-18
  description: Participants will be asked to fill out a time-use diary over three 2-week periods throughout the semester, indicating the activities they engaged in over the past day
  measure: Change in smartphone touchscreen interaction patterns from the start to the end of the semester
  time frame: 20 weeks
  description: Phone taps will be tracked automatically through an EU-GDPR (the European Union's stringent privacy regulation) compliant smartphone app (QuantActions). This application logs human-smartphone screen interactions during regular use by logging a location-specific timestamp for each screen contact.
  measure: Change in movement patterns from the start to the end of the semester
  time frame: 20 weeks
  description: The investigator's in-house smartphone app (Z4IP) will extract movement patterns from location data that will only be kept on the participant's phone up to 96 hours for these computations. The extracted movement patterns (and not geographical locations) will then be uploaded to secure servers, tagged to subject IDs without any personal identifiers, i.e., names and emails will not be linked to their movement patterns. As this component is optional, participants will be asked to indicate if they would like to opt-in at the informed consent stage.
  intervention type: Behavioral
  intervention name: Sleep and well-being tracking
  description: This study will track sleep, learning and wellbeing of 500 freshmen under free-living conditions for 20 weeks
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: 25 Years
  healthy volunteers: Accepts Healthy Volunteers
  responsible party type: Principal Investigator
  investigator affiliation: National University of Singapore
  investigator full name: Michael W.L. Chee
  investigator title: Professor
  sharing ipd: Undecided