<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/NCT02188134</url>
  </required_header>
  <id_info>
    <org_study_id>MSU14-679</org_study_id>
    <nct_id>NCT02188134</nct_id>
  </id_info>
  <brief_title>Quantifying the Attentive Behaviors of Older Adults During Over-the-counter Drug Selection</brief_title>
  <official_title>Quantifying the Attentive Behaviors of Older Adults During Over-the-counter Drug Selection</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Michigan State University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Consumer Healthcare Products Association</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Michigan State University</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      Per-capita consumption of medication is higher in older adults than any other sector of the&#xD;
      population. In fact, it has been estimated that although older adults comprise 13% of the&#xD;
      population they take 34% of all prescriptions and 30% of the over-the-counter (OTCs) consumed&#xD;
      in the US (National Council on Patient Information and Education, 2010). Given current trends&#xD;
      in aging, the savings, freedom and flexibility that self-medicating provides, as well as the&#xD;
      trends to switch prescription products to an OTC status, it is likely that older adults will&#xD;
      increasingly turn to OTCs as part of their medical regimens for years to come (Hanlon, J et&#xD;
      al, 2001).&#xD;
&#xD;
      In addition to the advantages that self-medicating offers, there are risks. These risks are&#xD;
      more pronounced in older consumers, who are likely experiencing physiological changes (e.g.&#xD;
      pharmacokinetics, pharmacodynamics, perceptual, cognitive and motor); this combines with a&#xD;
      propensity for poly-pharmacy that escalates the likelihood of adverse drug reactions. It has&#xD;
      also been suggested that low health literacy rates in older consumers detrimentally impact&#xD;
      health and health outcomes in this population (Kutner et al., 2005 and Federman et al.,&#xD;
      2009).&#xD;
&#xD;
      Despite the risks associated with improper OTC use, the critical importance of OTC labeling&#xD;
      information (there is no learned intermediary), and the fact that older consumers are&#xD;
      significantly more likely to experience an adverse drug reaction than younger adults,&#xD;
      surprisingly little information exists about the decision making process older adults employ&#xD;
      when selecting and using an OTC product.&#xD;
&#xD;
      We propose to recruit people 65 and older for an eye tracking study of mock OTC brands. The&#xD;
      study has the following objectives:&#xD;
&#xD;
        1. To begin to garner insights regarding the proportion of subjects who closely examine&#xD;
           (e.g. turn to the Drug Facts Label) the labeling of an OTC when deciding whether (or&#xD;
           not) a drug is appropriate for them (based on their health history and current&#xD;
           medications).&#xD;
&#xD;
        2. To quantify and compare the attentive behaviors to specific information (Specifically:&#xD;
           name, active ingredient, symptom relief).&#xD;
&#xD;
        3. To quantify and compare the attentive behaviors to different formats of information&#xD;
           (prominently featured information vs less prominently featured information).&#xD;
&#xD;
        4. To begin to benchmark whether or not older consumers make appropriate choices based on&#xD;
           their current conditions and medication history.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Eligibility Criteria 65 or older Administer own medications Legally sighted Purchase&#xD;
      over-the-counter medications on occasion Be willing to share complete health history and&#xD;
      complete list of all OTC and prescription medications Have transportation to one of two test&#xD;
      sites (MSU Campus or Lansing Ingham County Building)&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date>October 2014</start_date>
  <completion_date type="Actual">April 2015</completion_date>
  <primary_completion_date type="Actual">November 2014</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <time_perspective>Cross-Sectional</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Time in zone</measure>
    <time_frame>Measure taken in a single session with participant</time_frame>
    <description>Eye tracking will be done while mock OTCs appear on a computer screen, and participants will be asked to make a binary choice (yes/no) regarding whether (or not) the drug is safe choice for them at present.&#xD;
Treatments will appear in random order . Subjects will be asked to answer the question, &quot;Assuming you have this condition, is this product appropriate for you?&quot; for each of the twenty-seven trials while we track the movement of the eye.&#xD;
Zones for the analysis of the data include product name, symptom relief and active ingredient. Time in zone is the amount of time a subject's eye spends on the targeted information.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Time to first hit</measure>
    <time_frame>Measure taken in a single session with participant</time_frame>
    <description>Eye tracking will be done while mock OTCs appear on a computer screen, and participants will be asked to make a binary choice (yes/no) regarding whether (or not) the drug is safe choice for them at present.&#xD;
Treatments will appear in random order . Subjects will be asked to answer the question, &quot;Assuming you have this condition, is this product appropriate for you?&quot; for each of the twenty-seven trials while we track the movement of the eye.&#xD;
Zones for the analysis of the data include product name, symptom relief and active ingredient. Time to first hit is the measure of time it takes for a subject to fixate information in the zones described above.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Number of visual hits</measure>
    <time_frame>Measure taken in a single session with participant</time_frame>
    <description>Eye tracking will be done while mock OTCs appear on a computer screen, and participants will be asked to make a binary choice (yes/no) regarding whether (or not) the drug is safe choice for them at present.&#xD;
Treatments will appear in random order . Subjects will be asked to answer the question, &quot;Assuming you have this condition, is this product appropriate for you?&quot; for each of the twenty-seven trials while we track the movement of the eye.&#xD;
Zones for the analysis of the data include product name, symptom relief and active ingredient. Number of visual hits is the number of times the eye returns to a given information zone</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Appropriate product selection</measure>
    <time_frame>Measure taken in a single session with participant</time_frame>
    <description>Eye tracking will be done while mock OTCs appear on a computer screen, and participants will be asked to make a binary choice (yes/no) regarding whether (or not) the drug is safe choice for them at present.&#xD;
Treatments will appear in random order . Subjects will be asked to answer the question, &quot;Assuming you have this condition, is this product appropriate for you?&quot; for each of the twenty-seven trials while we track the movement of the eye.&#xD;
Based on the self-reported history that is provided during a guided interview, and the medications that they have brought with them, an assessment will be made regarding the &quot;correctness&quot; of their response to whether or not the drug is an appropriate choice for them</description>
  </primary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Actual">82</enrollment>
  <condition>Older Adults (65 Years and Older)</condition>
  <arm_group>
    <arm_group_label>65 and older</arm_group_label>
    <description>No intervention will be administered</description>
  </arm_group>
  <eligibility>
    <study_pop>
      <textblock>
        65 and older self administer medication Purchase OTCs&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  65 or older legally sighted administer own medication purchase OTC have transportation&#xD;
             to one of two test sites Be willing to share a complete health history and complete&#xD;
             list of medications&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Legally blind Does not use OTC medications Less than 65 Does not administer own&#xD;
             medication&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>65 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Laura Bix, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Michigan State Univeristy</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Packaging Building</name>
      <address>
        <city>East Lansing</city>
        <state>Michigan</state>
        <zip>48824</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>April 2015</verification_date>
  <study_first_submitted>July 8, 2014</study_first_submitted>
  <study_first_submitted_qc>July 9, 2014</study_first_submitted_qc>
  <study_first_posted type="Estimate">July 11, 2014</study_first_posted>
  <last_update_submitted>April 6, 2015</last_update_submitted>
  <last_update_submitted_qc>April 6, 2015</last_update_submitted_qc>
  <last_update_posted type="Estimate">April 7, 2015</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Michigan State University</investigator_affiliation>
    <investigator_full_name>Laura Bix</investigator_full_name>
    <investigator_title>Associate Professor</investigator_title>
  </responsible_party>
  <keyword>Adverse events,</keyword>
  <keyword>adverse drug reactions,</keyword>
  <keyword>medication error,</keyword>
  <keyword>noncompliance</keyword>
  <!-- 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/NCT02188134
org study id: MSU14-679
nct id: NCT02188134
lead sponsor: 
collaborator: 
has dmc: No
Per-capita consumption of medication is higher in older adults than any other sector of the
      population. In fact, it has been estimated that although older adults comprise 13% of the
      population they take 34% of all prescriptions and 30% of the over-the-counter (OTCs) consumed
      in the US (National Council on Patient Information and Education, 2010). Given current trends
      in aging, the savings, freedom and flexibility that self-medicating provides, as well as the
      trends to switch prescription products to an OTC status, it is likely that older adults will
      increasingly turn to OTCs as part of their medical regimens for years to come (Hanlon, J et
      al, 2001).

      In addition to the advantages that self-medicating offers, there are risks. These risks are
      more pronounced in older consumers, who are likely experiencing physiological changes (e.g.
      pharmacokinetics, pharmacodynamics, perceptual, cognitive and motor); this combines with a
      propensity for poly-pharmacy that escalates the likelihood of adverse drug reactions. It has
      also been suggested that low health literacy rates in older consumers detrimentally impact
      health and health outcomes in this population (Kutner et al., 2005 and Federman et al.,
      2009).

      Despite the risks associated with improper OTC use, the critical importance of OTC labeling
      information (there is no learned intermediary), and the fact that older consumers are
      significantly more likely to experience an adverse drug reaction than younger adults,
      surprisingly little information exists about the decision making process older adults employ
      when selecting and using an OTC product.

      We propose to recruit people 65 and older for an eye tracking study of mock OTC brands. The
      study has the following objectives:

        1. To begin to garner insights regarding the proportion of subjects who closely examine
           (e.g. turn to the Drug Facts Label) the labeling of an OTC when deciding whether (or
           not) a drug is appropriate for them (based on their health history and current
           medications).

        2. To quantify and compare the attentive behaviors to specific information (Specifically:
           name, active ingredient, symptom relief).

        3. To quantify and compare the attentive behaviors to different formats of information
           (prominently featured information vs less prominently featured information).

        4. To begin to benchmark whether or not older consumers make appropriate choices based on
           their current conditions and medication history.
Eligibility Criteria 65 or older Administer own medications Legally sighted Purchase
      over-the-counter medications on occasion Be willing to share complete health history and
      complete list of all OTC and prescription medications Have transportation to one of two test
      sites (MSU Campus or Lansing Ingham County Building)
time perspective: Cross-Sectional
measure: Time in zone
time frame: Measure taken in a single session with participant
description: Eye tracking will be done while mock OTCs appear on a computer screen, and participants will be asked to make a binary choice (yes/no) regarding whether (or not) the drug is safe choice for them at present.
Treatments will appear in random order . Subjects will be asked to answer the question, "Assuming you have this condition, is this product appropriate for you?" for each of the twenty-seven trials while we track the movement of the eye.
Zones for the analysis of the data include product name, symptom relief and active ingredient. Time in zone is the amount of time a subject's eye spends on the targeted information.
measure: Time to first hit
time frame: Measure taken in a single session with participant
description: Eye tracking will be done while mock OTCs appear on a computer screen, and participants will be asked to make a binary choice (yes/no) regarding whether (or not) the drug is safe choice for them at present.
Treatments will appear in random order . Subjects will be asked to answer the question, "Assuming you have this condition, is this product appropriate for you?" for each of the twenty-seven trials while we track the movement of the eye.
Zones for the analysis of the data include product name, symptom relief and active ingredient. Time to first hit is the measure of time it takes for a subject to fixate information in the zones described above.
measure: Number of visual hits
time frame: Measure taken in a single session with participant
description: Eye tracking will be done while mock OTCs appear on a computer screen, and participants will be asked to make a binary choice (yes/no) regarding whether (or not) the drug is safe choice for them at present.
Treatments will appear in random order . Subjects will be asked to answer the question, "Assuming you have this condition, is this product appropriate for you?" for each of the twenty-seven trials while we track the movement of the eye.
Zones for the analysis of the data include product name, symptom relief and active ingredient. Number of visual hits is the number of times the eye returns to a given information zone
measure: Appropriate product selection
time frame: Measure taken in a single session with participant
description: Eye tracking will be done while mock OTCs appear on a computer screen, and participants will be asked to make a binary choice (yes/no) regarding whether (or not) the drug is safe choice for them at present.
Treatments will appear in random order . Subjects will be asked to answer the question, "Assuming you have this condition, is this product appropriate for you?" for each of the twenty-seven trials while we track the movement of the eye.
Based on the self-reported history that is provided during a guided interview, and the medications that they have brought with them, an assessment will be made regarding the "correctness" of their response to whether or not the drug is an appropriate choice for them
arm group label: 65 and older
description: No intervention will be administered
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 65 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
last name: Laura Bix, PhD
role: Principal Investigator
affiliation: Michigan State Univeristy
facility: 
country: United States
responsible party type: Principal Investigator
investigator affiliation: Michigan State University
investigator full name: Laura Bix
investigator title: Associate Professor