<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/NCT04461184</url>
  </required_header>
  <id_info>
    <org_study_id>NorthDakotaSU</org_study_id>
    <nct_id>NCT04461184</nct_id>
  </id_info>
  <brief_title>The Great Plains Internet Wellness Study for Aging</brief_title>
  <official_title>The Great Plains Internet Wellness Study for Aging: The GP I-WAS Project</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>North Dakota State University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>North Dakota State University</source>
  <oversight_info>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Obesity is a major public health concern in older adults, who are also one of the fastest&#xD;
      growing populations in the United States. Engaging in healthy behaviors such as physical&#xD;
      activity, a healthy diet, and adequate sleep have each shown to be influential in reducing&#xD;
      obesity. The internet could be an effective tool for administering a wellness intervention&#xD;
      for older adults. Our goal is to help older adults achieve healthy lifestyles that promote&#xD;
      successful aging.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Obesity is a major public health concern in older adults, who are also one of the fastest&#xD;
      growing populations in the United States. The health consequences associated with obesity in&#xD;
      older adulthood are severe and include increased risk for chronic diseases, poor physical&#xD;
      functioning and early mortality. Concurrently engaging in healthy behaviors such as physical&#xD;
      activity, a healthy diet, and adequate sleep have each shown to be influential in reducing&#xD;
      obesity. Despite evidence suggesting that these healthy behaviors reduce the risk for&#xD;
      obesity, older adults have difficulty achieving such healthy lifestyles due to barriers such&#xD;
      as geographical isolation from lack of transportation, motivation and education. The internet&#xD;
      is an effective mode for relaying health information to a wide-ranging audience, including&#xD;
      those that live in rural communities or are home bound. Further, internet usage among older&#xD;
      adults continues to increase. Therefore, the internet could be an effective tool for&#xD;
      administering a wellness intervention for older adults and incorporating community-based&#xD;
      participatory research principles such as inviting stakeholders (i.e., older adults) in all&#xD;
      phases of the research will magnify the impact of the research for the population in which it&#xD;
      is intended to help. Our long-term goal is to help older adults achieve healthy lifestyles&#xD;
      that promote successful aging. The overall objective of the proposed research, which is the&#xD;
      next step in pursuit of that goal, is to improve healthy lifestyles in older adults by&#xD;
      utilizing the internet for delivering a wellness intervention that is designed by both&#xD;
      investigators and stakeholders. To propel toward accomplishing our overall objective, the&#xD;
      following three specific aims will be pursued: 1) collaborate with stakeholders in all phases&#xD;
      of the internet-based wellness intervention to gain knowledge on the perspectives of the&#xD;
      older adult population, 2) assess the feasibility of an internet-based wellness intervention&#xD;
      for obese older adults, and 3) determine if completing an internet based wellness&#xD;
      intervention improves healthy behaviors among obese older adults. We will recruit 20 eligible&#xD;
      older adults to participate in an internet-based wellness intervention. A prospective,&#xD;
      within-participant design with multiple assessments across the 10-week study period and&#xD;
      1-month follow-up will allow us to optimize power with a smaller sample size and assess&#xD;
      within-person change over time.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">January 1, 2021</start_date>
  <completion_date type="Actual">May 21, 2021</completion_date>
  <primary_completion_date type="Actual">May 21, 2021</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>
    <primary_purpose>Prevention</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Increase Physical Activity and Participation</measure>
    <time_frame>10-weeks</time_frame>
    <description>Actigraph accelerometer and physical activity recall will be used to measure and record physical activity throughout the 10-week internet wellness intervention.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Create a more balanced dietary intake based on nutrient dense foods</measure>
    <time_frame>10-weeks</time_frame>
    <description>Participants will complete the Arizona Food Frequency Questionnaire (AFFQ) to assess dietary intake at the beginning and end of the intervention, and at 1-month follow-up. The AFFQ is a modified version of the Health Habits Questionnaire and has demonstrated strong reliability and validity for assessing dietary intake. In addition, each report will contain a personalized message from the dietitian to each participant. Intake of nutritionally dense foods (e.g., vegetables, lean proteins) and decreased intake of calorically dense foods (e.g., high sugar foods) will be compared to assess dietary change.</description>
  </primary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">14</enrollment>
  <condition>Internet Based Wellness Program</condition>
  <condition>Obesity</condition>
  <condition>Adult Population</condition>
  <arm_group>
    <arm_group_label>Internet wellness intervention for aging</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Feasibility components will be evaluated with a 5-point Likert scale may include open ended items for more detailed feedback. Participants will be asked to visit NDSU at the beginning and end of the intervention, and at 1-month follow-up. After written informed consent, each participant will complete a descriptive questionnaire at the beginning of the intervention period, and a health-related questionnaire at the beginning and end of the intervention, and at follow-up that includes self-rated health, current smoking status, smoking history, alcohol use, morbid conditions, functional disability, and depression status. Standing height and waist circumference will be collected with a tape measure. Body weight and composition will be measured with the InBody 570. Anthropometric and body composition assessments will be collected pre, post, and follow up.</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Internet Wellness Intervention for Aging</intervention_name>
    <description>Internet technologies have emerged as a platform for performing wellness interventions that also have wide outreach. Previous studies that have used the internet for delivering health interventions have found that older adults valued this platform, used it for researching health information and social communications. Likewise, the effectiveness of delivering health-related information intended for behavior change through the internet is equal to that of print-based delivery, thereby lowering costs and expanding reach. Thus, the internet provides a unique platform for conducting interventions. The internet based wellness intervention will be a low cost method focused on older adults to help increase intrinsic motivation through autonomy, competence, and relatedness (Intrinsic Motivation) to help increase daily physical activity.</description>
    <arm_group_label>Internet wellness intervention for aging</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Adults aged at least 65 years that can use the internet daily, have a body mass index&#xD;
             of ≥ 30 kg/m2, and are apparently healthy (i.e., medically able to participate in&#xD;
             physical activity as determined by the PAR-Q+) Will be eligible for the study.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Those with a surgical implant, who are unable to read or speak the English language&#xD;
             fluently, with a severe cognitive impairment, and unable to wear an accelerometer on&#xD;
             their waist will be excluded.&#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>
  <location>
    <facility>
      <name>North Dakota State University Health, Nutrition, and Exercise Sciences</name>
      <address>
        <city>Fargo</city>
        <state>North Dakota</state>
        <zip>58102</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <link>
    <url>https://mronline.org/wp-content/uploads/2019/08/p25-1143.pdf</url>
    <description>Projections of the Size and Composition of the US Population: 2014 to 2060</description>
  </link>
  <link>
    <url>https://www.ncbi.nlm.nih.gov/sites/books/NBK532533/</url>
    <description>Obesity in Elderly</description>
  </link>
  <link>
    <url>http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.738.2737&amp;rep=rep1&amp;type=pdf</url>
    <description>Obesity in older adults</description>
  </link>
  <link>
    <url>http://doras.dcu.ie/20896/1/Wani-paper.pdf</url>
    <description>Web-based physical activity interventions for older adults: A review.</description>
  </link>
  <link>
    <url>http://lab.rockefeller.edu/cohenje/PDFs/159CohenBigFishLittleFishTheSciences1989.pdf</url>
    <description>Statistical power analysis for the behavioral sciences.</description>
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    <citation>Keadle SK, Shiroma EJ, Freedson PS, Lee IM. Impact of accelerometer data processing decisions on the sample size, wear time and physical activity level of a large cohort study. BMC Public Health. 2014 Nov 24;14:1210. doi: 10.1186/1471-2458-14-1210.</citation>
    <PMID>25421941</PMID>
  </reference>
  <reference>
    <citation>Cole RJ, Kripke DF, Gruen W, Mullaney DJ, Gillin JC. Automatic sleep/wake identification from wrist activity. Sleep. 1992 Oct;15(5):461-9. doi: 10.1093/sleep/15.5.461.</citation>
    <PMID>1455130</PMID>
  </reference>
  <reference>
    <citation>Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, O'Brien WL, Bassett DR Jr, Schmitz KH, Emplaincourt PO, Jacobs DR Jr, Leon AS. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000 Sep;32(9 Suppl):S498-504. doi: 10.1097/00005768-200009001-00009.</citation>
    <PMID>10993420</PMID>
  </reference>
  <reference>
    <citation>Gomersall SR, Olds TS, Ridley K. Development and evaluation of an adult use-of-time instrument with an energy expenditure focus. J Sci Med Sport. 2011 Mar;14(2):143-8. doi: 10.1016/j.jsams.2010.08.006. Epub 2010 Oct 6.</citation>
    <PMID>20932797</PMID>
  </reference>
  <reference>
    <citation>Mace CJ, Maddison R, Olds T, Kerse N. Validation of a computerized use of time recall for activity measurement in advanced-aged adults. J Aging Phys Act. 2014 Apr;22(2):245-54. doi: 10.1123/japa.2012-0280. Epub 2013 May 22.</citation>
    <PMID>23752221</PMID>
  </reference>
  <reference>
    <citation>Foley LS, Maddison R, Rush E, Olds TS, Ridley K, Jiang Y. Doubly labeled water validation of a computerized use-of-time recall in active young people. Metabolism. 2013 Jan;62(1):163-9. doi: 10.1016/j.metabol.2012.07.021. Epub 2012 Sep 11.</citation>
    <PMID>22980224</PMID>
  </reference>
  <reference>
    <citation>Thomson CA, Giuliano A, Rock CL, Ritenbaugh CK, Flatt SW, Faerber S, Newman V, Caan B, Graver E, Hartz V, Whitacre R, Parker F, Pierce JP, Marshall JR. Measuring dietary change in a diet intervention trial: comparing food frequency questionnaire and dietary recalls. Am J Epidemiol. 2003 Apr 15;157(8):754-62. doi: 10.1093/aje/kwg025.</citation>
    <PMID>12697580</PMID>
  </reference>
  <reference>
    <citation>Block G, Hartman AM, Dresser CM, Carroll MD, Gannon J, Gardner L. A data-based approach to diet questionnaire design and testing. Am J Epidemiol. 1986 Sep;124(3):453-69. doi: 10.1093/oxfordjournals.aje.a114416.</citation>
    <PMID>3740045</PMID>
  </reference>
  <verification_date>May 2021</verification_date>
  <study_first_submitted>June 25, 2020</study_first_submitted>
  <study_first_submitted_qc>July 1, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">July 8, 2020</study_first_posted>
  <last_update_submitted>May 21, 2021</last_update_submitted>
  <last_update_submitted_qc>May 21, 2021</last_update_submitted_qc>
  <last_update_posted type="Actual">May 25, 2021</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>North Dakota State University</investigator_affiliation>
    <investigator_full_name>Ryan McGrath</investigator_full_name>
    <investigator_title>Assistant Professor</investigator_title>
  </responsible_party>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </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>March 19, 2020</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/84/NCT04461184/Prot_SAP_000.pdf</document_url>
    </provided_document>
  </provided_document_section>
  <!-- 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/NCT04461184
org study id: NorthDakotaSU
nct id: NCT04461184
lead sponsor: 
is fda regulated drug: No
is fda regulated device: No
Obesity is a major public health concern in older adults, who are also one of the fastest
      growing populations in the United States. Engaging in healthy behaviors such as physical
      activity, a healthy diet, and adequate sleep have each shown to be influential in reducing
      obesity. The internet could be an effective tool for administering a wellness intervention
      for older adults. Our goal is to help older adults achieve healthy lifestyles that promote
      successful aging.
Obesity is a major public health concern in older adults, who are also one of the fastest
      growing populations in the United States. The health consequences associated with obesity in
      older adulthood are severe and include increased risk for chronic diseases, poor physical
      functioning and early mortality. Concurrently engaging in healthy behaviors such as physical
      activity, a healthy diet, and adequate sleep have each shown to be influential in reducing
      obesity. Despite evidence suggesting that these healthy behaviors reduce the risk for
      obesity, older adults have difficulty achieving such healthy lifestyles due to barriers such
      as geographical isolation from lack of transportation, motivation and education. The internet
      is an effective mode for relaying health information to a wide-ranging audience, including
      those that live in rural communities or are home bound. Further, internet usage among older
      adults continues to increase. Therefore, the internet could be an effective tool for
      administering a wellness intervention for older adults and incorporating community-based
      participatory research principles such as inviting stakeholders (i.e., older adults) in all
      phases of the research will magnify the impact of the research for the population in which it
      is intended to help. Our long-term goal is to help older adults achieve healthy lifestyles
      that promote successful aging. The overall objective of the proposed research, which is the
      next step in pursuit of that goal, is to improve healthy lifestyles in older adults by
      utilizing the internet for delivering a wellness intervention that is designed by both
      investigators and stakeholders. To propel toward accomplishing our overall objective, the
      following three specific aims will be pursued: 1) collaborate with stakeholders in all phases
      of the internet-based wellness intervention to gain knowledge on the perspectives of the
      older adult population, 2) assess the feasibility of an internet-based wellness intervention
      for obese older adults, and 3) determine if completing an internet based wellness
      intervention improves healthy behaviors among obese older adults. We will recruit 20 eligible
      older adults to participate in an internet-based wellness intervention. A prospective,
      within-participant design with multiple assessments across the 10-week study period and
      1-month follow-up will allow us to optimize power with a smaller sample size and assess
      within-person change over time.
allocation: N/A
intervention model: Single Group Assignment
primary purpose: Prevention
masking: None (Open Label)
measure: Increase Physical Activity and Participation
time frame: 10-weeks
description: Actigraph accelerometer and physical activity recall will be used to measure and record physical activity throughout the 10-week internet wellness intervention.
measure: Create a more balanced dietary intake based on nutrient dense foods
time frame: 10-weeks
description: Participants will complete the Arizona Food Frequency Questionnaire (AFFQ) to assess dietary intake at the beginning and end of the intervention, and at 1-month follow-up. The AFFQ is a modified version of the Health Habits Questionnaire and has demonstrated strong reliability and validity for assessing dietary intake. In addition, each report will contain a personalized message from the dietitian to each participant. Intake of nutritionally dense foods (e.g., vegetables, lean proteins) and decreased intake of calorically dense foods (e.g., high sugar foods) will be compared to assess dietary change.
arm group label: Internet wellness intervention for aging
arm group type: Experimental
description: Feasibility components will be evaluated with a 5-point Likert scale may include open ended items for more detailed feedback. Participants will be asked to visit NDSU at the beginning and end of the intervention, and at 1-month follow-up. After written informed consent, each participant will complete a descriptive questionnaire at the beginning of the intervention period, and a health-related questionnaire at the beginning and end of the intervention, and at follow-up that includes self-rated health, current smoking status, smoking history, alcohol use, morbid conditions, functional disability, and depression status. Standing height and waist circumference will be collected with a tape measure. Body weight and composition will be measured with the InBody 570. Anthropometric and body composition assessments will be collected pre, post, and follow up.
intervention type: Behavioral
intervention name: Internet Wellness Intervention for Aging
description: Internet technologies have emerged as a platform for performing wellness interventions that also have wide outreach. Previous studies that have used the internet for delivering health interventions have found that older adults valued this platform, used it for researching health information and social communications. Likewise, the effectiveness of delivering health-related information intended for behavior change through the internet is equal to that of print-based delivery, thereby lowering costs and expanding reach. Thus, the internet provides a unique platform for conducting interventions. The internet based wellness intervention will be a low cost method focused on older adults to help increase intrinsic motivation through autonomy, competence, and relatedness (Intrinsic Motivation) to help increase daily physical activity.
arm group label: Internet wellness intervention for aging
criteria: 
gender: All
minimum age: 65 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
facility: 
country: United States
url: https://mronline.org/wp-content/uploads/2019/08/p25-1143.pdf
description: Projections of the Size and Composition of the US Population: 2014 to 2060
url: https://www.ncbi.nlm.nih.gov/sites/books/NBK532533/
description: Obesity in Elderly
url: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.738.2737&rep=rep1&type=pdf
description: Obesity in older adults
url: http://doras.dcu.ie/20896/1/Wani-paper.pdf
description: Web-based physical activity interventions for older adults: A review.
url: http://lab.rockefeller.edu/cohenje/PDFs/159CohenBigFishLittleFishTheSciences1989.pdf
description: Statistical power analysis for the behavioral sciences.
url: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.996.3690&rep=rep1&type=pdf
description: Self-determination theory: A macrotheory of human motivation, development, and health.
url: https://www.usability.gov/
description: United States Department of Health and Human Services
url: https://www.cdc.gov/eval/guide/CDCEvalManual.pdf
description: United States Department of Health and Human Services. Centers for Diseasee Control and Prevention. Introduction to program evaluation for public health programs: a self-study guide
url: https://link.springer.com/content/pdf/10.1111/sbr.12103.pdf
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citation: Keadle SK, Shiroma EJ, Freedson PS, Lee IM. Impact of accelerometer data processing decisions on the sample size, wear time and physical activity level of a large cohort study. BMC Public Health. 2014 Nov 24;14:1210. doi: 10.1186/1471-2458-14-1210.
PMID: 25421941
citation: Cole RJ, Kripke DF, Gruen W, Mullaney DJ, Gillin JC. Automatic sleep/wake identification from wrist activity. Sleep. 1992 Oct;15(5):461-9. doi: 10.1093/sleep/15.5.461.
PMID: 1455130
citation: Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, O'Brien WL, Bassett DR Jr, Schmitz KH, Emplaincourt PO, Jacobs DR Jr, Leon AS. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000 Sep;32(9 Suppl):S498-504. doi: 10.1097/00005768-200009001-00009.
PMID: 10993420
citation: Gomersall SR, Olds TS, Ridley K. Development and evaluation of an adult use-of-time instrument with an energy expenditure focus. J Sci Med Sport. 2011 Mar;14(2):143-8. doi: 10.1016/j.jsams.2010.08.006. Epub 2010 Oct 6.
PMID: 20932797
citation: Mace CJ, Maddison R, Olds T, Kerse N. Validation of a computerized use of time recall for activity measurement in advanced-aged adults. J Aging Phys Act. 2014 Apr;22(2):245-54. doi: 10.1123/japa.2012-0280. Epub 2013 May 22.
PMID: 23752221
citation: Foley LS, Maddison R, Rush E, Olds TS, Ridley K, Jiang Y. Doubly labeled water validation of a computerized use-of-time recall in active young people. Metabolism. 2013 Jan;62(1):163-9. doi: 10.1016/j.metabol.2012.07.021. Epub 2012 Sep 11.
PMID: 22980224
citation: Thomson CA, Giuliano A, Rock CL, Ritenbaugh CK, Flatt SW, Faerber S, Newman V, Caan B, Graver E, Hartz V, Whitacre R, Parker F, Pierce JP, Marshall JR. Measuring dietary change in a diet intervention trial: comparing food frequency questionnaire and dietary recalls. Am J Epidemiol. 2003 Apr 15;157(8):754-62. doi: 10.1093/aje/kwg025.
PMID: 12697580
citation: Block G, Hartman AM, Dresser CM, Carroll MD, Gannon J, Gardner L. A data-based approach to diet questionnaire design and testing. Am J Epidemiol. 1986 Sep;124(3):453-69. doi: 10.1093/oxfordjournals.aje.a114416.
PMID: 3740045
responsible party type: Principal Investigator
investigator affiliation: North Dakota State University
investigator full name: Ryan McGrath
investigator title: Assistant Professor
sharing ipd: No
provided document: 