<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/NCT03832101</url>
  </required_header>
  <id_info>
    <org_study_id>S-17-180</org_study_id>
    <nct_id>NCT03832101</nct_id>
  </id_info>
  <brief_title>Improvement of Facial Recognition Ability and Multitasking</brief_title>
  <official_title>Improvement of Facial Recognition Ability and Multitasking</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>
      This study aims to determine the efficacy of training on facial recognition and multitasking.&#xD;
      The researchers hypothesize that participants who have undergone facial recognition and&#xD;
      multitasking training will demonstrate an improved facial recognition ability and performance&#xD;
      in multi-tasking. The researchers also hypothesize that measures of sustained and selective&#xD;
      attention will predict performance on multitasking tasks. This work sets the ground work for&#xD;
      future research into if and how facial recognition and multitasking ability can be improved.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      There has been evidence showing improvements on performance on various cognitive tasks after&#xD;
      training, but evidence on multitasking and facial recognition is lacking. Both multi-tasking&#xD;
      and facial recognition are crucial for military and law enforcement personnel, and the&#xD;
      respective organizations can consider these abilities during their respective recruitment and&#xD;
      training processes.&#xD;
&#xD;
      This study will test whether training on multi-tasking and facial recognition tasks can&#xD;
      improve an individual's performance. Additionally, it will test whether their performance on&#xD;
      other measures of attention and multitasking can predict changes post-training.&#xD;
&#xD;
      Participants will go through 5 testing sessions span over 5 days. For each session,&#xD;
      participants will complete a multitasking task and a facial recognition task. Participants&#xD;
      are hypothesized to improve in their performance after 5 consecutive days of training on&#xD;
      these 2 tasks. Additionally, participants will also complete 2 attention tasks, 1 face memory&#xD;
      task, and 1 other multi-tasking task only on the first day. Both multitasking tasks are&#xD;
      expected to correlate at baseline, and performance on the attention tasks may predict&#xD;
      performance on multitasking tasks as these tasks require sustained and selective attention. A&#xD;
      face memory task will also be used to account for each individual's baseline facial&#xD;
      recognition ability.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Actual">February 13, 2018</start_date>
  <completion_date type="Anticipated">December 2020</completion_date>
  <primary_completion_date type="Anticipated">December 2020</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>Basic Science</primary_purpose>
    <masking>Single (Participant)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Facial recognition performance change during training</measure>
    <time_frame>Day 1, 2, 3, 4, 5</time_frame>
    <description>The crucial measure is percent correct recognition of target faces learned on the first day. These faces are either presented in isolation (Is this a target face? Yes/No) or with other faces (Which is the target?). Performance is measured on each day of training to establish learning trajectories.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Multi-tasking performance change during training</measure>
    <time_frame>Day 1, 2, 3, 4, 5</time_frame>
    <description>The crucial measures are speed and accuracy on each component task of the MATB (Multi-Attribute Task Battery; Comstock &amp; Arnegard, 1992). Performance is measured on each day of training to establish learning trajectories.</description>
  </primary_outcome>
  <number_of_arms>3</number_of_arms>
  <enrollment type="Anticipated">100</enrollment>
  <condition>Facial Discrimination</condition>
  <condition>Multitasking</condition>
  <arm_group>
    <arm_group_label>Difficult face discrimination</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>All participants will complete 5 training and testing sessions in total, once a day, over the course of a week (weekdays). On the first day, participants will go through an initial test (Cambridge Face Memory Test; approximately 15 minutes) to determine their baseline facial recognition ability. Thereafter, participants in the Difficult group will undergo training involving discriminations between highly similar faces. Each participant's involvement in the study will last only 5 consecutive days. The total participation time is 7.5 hours per participant.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Easy face discrimination</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>All participants will complete 5 training and testing sessions in total, once a day, over the course of a week (weekdays). On the first day, participants will go through an initial test (Cambridge Face Memory Test; approximately 15 minutes) to determine their baseline facial recognition ability. Those in the Easy group will discriminate between dissimilar faces. Each participant's involvement in the study will last only 5 consecutive days. The total participation time is 7.5 hours per participant.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Control</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>All participants will complete 5 training and testing sessions in total, once a day, over the course of a week (weekdays). On the first day, participants will go through an initial test (Cambridge Face Memory Test; approximately 15 minutes) to determine their baseline facial recognition ability. Those in the Control group will perform a simple face-matching exercise. This training will last for approximately 30 minutes. Each participant's involvement in the study will last only 5 consecutive days. The total participation time is 7.5 hours per participant.</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>MATB</intervention_name>
    <description>MATB has two multitasking tasks and two attention tasks. The two multitasking tasks evaluates performance on multiple cognitively demanding assignments in both the auditory and visual domains. The two attention tasks measures performance in sustained and selective attention</description>
    <arm_group_label>Control</arm_group_label>
    <arm_group_label>Difficult face discrimination</arm_group_label>
    <arm_group_label>Easy face discrimination</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Participants must be over 21 if they are not from NUS or Yale-NUS. NUS or Yale-NUS&#xD;
             students over 18 can also participate. All participants are expected to be fluent in&#xD;
             English.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Participants with a history of perceptual or memory deficit will be excluded.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>21 Years</minimum_age>
    <maximum_age>40 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_contact>
    <last_name>Christopher L Asplund, Ph.D.</last_name>
    <phone>+65660 3327</phone>
    <email>chris.asplund@yale-nus.edu.sg</email>
  </overall_contact>
  <location>
    <facility>
      <name>National University of Singapore</name>
      <address>
        <city>Singapore</city>
        <country>Singapore</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Christopher L Asplund, Ph.D.</last_name>
      <phone>+6566013327</phone>
      <email>chris.asplund@yale-nus.edu.sg</email>
    </contact>
  </location>
  <location_countries>
    <country>Singapore</country>
  </location_countries>
  <verification_date>February 2019</verification_date>
  <study_first_submitted>February 2, 2019</study_first_submitted>
  <study_first_submitted_qc>February 4, 2019</study_first_submitted_qc>
  <study_first_posted type="Actual">February 6, 2019</study_first_posted>
  <last_update_submitted>February 4, 2019</last_update_submitted>
  <last_update_submitted_qc>February 4, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">February 6, 2019</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>National University of Singapore</investigator_affiliation>
    <investigator_full_name>Christopher L. Asplund</investigator_full_name>
    <investigator_title>Assistant Professor</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Facies</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Undecided</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/NCT03832101
org study id: S-17-180
nct id: NCT03832101
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
This study aims to determine the efficacy of training on facial recognition and multitasking.
      The researchers hypothesize that participants who have undergone facial recognition and
      multitasking training will demonstrate an improved facial recognition ability and performance
      in multi-tasking. The researchers also hypothesize that measures of sustained and selective
      attention will predict performance on multitasking tasks. This work sets the ground work for
      future research into if and how facial recognition and multitasking ability can be improved.
There has been evidence showing improvements on performance on various cognitive tasks after
      training, but evidence on multitasking and facial recognition is lacking. Both multi-tasking
      and facial recognition are crucial for military and law enforcement personnel, and the
      respective organizations can consider these abilities during their respective recruitment and
      training processes.

      This study will test whether training on multi-tasking and facial recognition tasks can
      improve an individual's performance. Additionally, it will test whether their performance on
      other measures of attention and multitasking can predict changes post-training.

      Participants will go through 5 testing sessions span over 5 days. For each session,
      participants will complete a multitasking task and a facial recognition task. Participants
      are hypothesized to improve in their performance after 5 consecutive days of training on
      these 2 tasks. Additionally, participants will also complete 2 attention tasks, 1 face memory
      task, and 1 other multi-tasking task only on the first day. Both multitasking tasks are
      expected to correlate at baseline, and performance on the attention tasks may predict
      performance on multitasking tasks as these tasks require sustained and selective attention. A
      face memory task will also be used to account for each individual's baseline facial
      recognition ability.
allocation: Randomized
intervention model: Parallel Assignment
primary purpose: Basic Science
masking: Single (Participant)
measure: Facial recognition performance change during training
time frame: Day 1, 2, 3, 4, 5
description: The crucial measure is percent correct recognition of target faces learned on the first day. These faces are either presented in isolation (Is this a target face? Yes/No) or with other faces (Which is the target?). Performance is measured on each day of training to establish learning trajectories.
measure: Multi-tasking performance change during training
time frame: Day 1, 2, 3, 4, 5
description: The crucial measures are speed and accuracy on each component task of the MATB (Multi-Attribute Task Battery; Comstock & Arnegard, 1992). Performance is measured on each day of training to establish learning trajectories.
arm group label: Difficult face discrimination
arm group type: Experimental
description: All participants will complete 5 training and testing sessions in total, once a day, over the course of a week (weekdays). On the first day, participants will go through an initial test (Cambridge Face Memory Test; approximately 15 minutes) to determine their baseline facial recognition ability. Thereafter, participants in the Difficult group will undergo training involving discriminations between highly similar faces. Each participant's involvement in the study will last only 5 consecutive days. The total participation time is 7.5 hours per participant.
arm group label: Easy face discrimination
arm group type: Experimental
description: All participants will complete 5 training and testing sessions in total, once a day, over the course of a week (weekdays). On the first day, participants will go through an initial test (Cambridge Face Memory Test; approximately 15 minutes) to determine their baseline facial recognition ability. Those in the Easy group will discriminate between dissimilar faces. Each participant's involvement in the study will last only 5 consecutive days. The total participation time is 7.5 hours per participant.
arm group label: Control
arm group type: Active Comparator
description: All participants will complete 5 training and testing sessions in total, once a day, over the course of a week (weekdays). On the first day, participants will go through an initial test (Cambridge Face Memory Test; approximately 15 minutes) to determine their baseline facial recognition ability. Those in the Control group will perform a simple face-matching exercise. This training will last for approximately 30 minutes. Each participant's involvement in the study will last only 5 consecutive days. The total participation time is 7.5 hours per participant.
intervention type: Behavioral
intervention name: MATB
description: MATB has two multitasking tasks and two attention tasks. The two multitasking tasks evaluates performance on multiple cognitively demanding assignments in both the auditory and visual domains. The two attention tasks measures performance in sustained and selective attention
arm group label: Control
arm group label: Difficult face discrimination
arm group label: Easy face discrimination
criteria: 
gender: All
minimum age: 21 Years
maximum age: 40 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Christopher L Asplund, Ph.D.
phone: +65660 3327
email: chris.asplund@yale-nus.edu.sg
facility: 
status: Recruiting
contact: 
country: Singapore
responsible party type: Principal Investigator
investigator affiliation: National University of Singapore
investigator full name: Christopher L. Asplund
investigator title: Assistant Professor
mesh term: Facies
sharing ipd: Undecided