- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT03961061
Increased Monitoring of Physical Activity and Calories With Technology (IMPACT)
Study Overview
Status
Detailed Description
Study Type
Enrollment (Actual)
Phase
- Not Applicable
Contacts and Locations
Study Contact
- Name: Camelia R Singletary, MPH
- Phone Number: 13369992469
- Email: crsingle@wakehealth.edu
Study Contact Backup
- Name: Justin Moore, PhD
- Phone Number: 336-716-3702
- Email: jusmoore@wakehealth.edu
Study Locations
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North Carolina
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Winston-Salem, North Carolina, United States, 27127
- Brenner Children's Hospital
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Description
Inclusion Criteria:
Youth with obesity, 13 - 18yrs, who are enrolled or eligible to enroll in Brenner Families in Training (FIT). Caregivers must live in the home with their youth participants. Obesity is defined a BMI (35.9 +/- 8.6). Participants must also have access to a smartphone or tablet
Exclusion Criteria:
Adolescents under the age of 13 will be excluded. If participants do not have access to a smartphone or tablet, they will not be able to participate.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Single
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Active Comparator: Brenner FIT (Standard Care)
Adolescents will participate in Brenner Families in Training along with their caregiver.
They will receive all components of standard Brenner FIT treatments.
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Families attend an orientation, in which they are then scheduled for an initial introductory 2-hour intake group session and cooking class; these occur within 2-4 weeks of the orientation.
Monthly 1-hour long visits with the dietitian, counselor, and PA specialist are held for 6 months, in which the child and caregiver see the pediatrician.
During the 6 months of treatment, they attend 4 group classes, choosing from topics such as meal planning, PA, and parenting.
Specialized visits with the PA specialist or dietician are scheduled as pertinent issues arise.
Motivational interviewing, modified by Brenner FIT for use with families, is the key to treatment; family counselors are trained in cognitive behavioral therapy, parenting support/mindfulness, and employ these approaches to assist families in developing healthy habits.
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Experimental: Brenner mFIT (standard care plus mobile health components)
Adolescents will participate in Brenner Families in Training along with their caregiver. Brenner mFIT (Families in Training + mobile health) includes all components of the standard Brenner FIT |
Brenner mFIT includes all components of the standard Brenner FIT program in addition to six mobile health components. The six mHealth components that will be used in addition to standard Brenner Families in Training program include-
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
BMI z-score
Time Frame: Baseline
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Weight status of caregivers and youth will be quantified through calculation of BMI derived from measurement of height and weight at the intake and follow-up visits.
Both height (plus/ minus 0.1 cm) and weight (plus/minus 0.5 kg) will be recorded twice and values will be averaged to produce the final value using a Tanita(registered trademark) digital scale and a Seca(registered trademark) Height Rod (respectively).
BMI will be calculated as kg /m2.
BMI z-score will be calculated using CDC growth charts.
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Baseline
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BMI z-score
Time Frame: 3 months
|
Weight status of caregivers and youth will be quantified through calculation of BMI derived from measurement of height and weight at the intake and follow-up visits.
Both height (plus/ minus 0.1 cm) and weight (plus/minus 0.5 kg) will be recorded twice and values will be averaged to produce the final value using a Tanita(registered trademark) digital scale and a Seca(registered trademark) Height Rod (respectively).
BMI will be calculated as kg /m2.
BMI z-score will be calculated using CDC growth charts.
|
3 months
|
BMI z-score
Time Frame: 6 months
|
Weight status of caregivers and youth will be quantified through calculation of BMI derived from measurement of height and weight at the intake and follow-up visits.
Both height (plus/ minus 0.1 cm) and weight (plus/minus 0.5 kg) will be recorded twice and values will be averaged to produce the final value using a Tanita(registered trademark) digital scale and a Seca(registered trademark) Height Rod (respectively).
BMI will be calculated as kg /m2.
BMI z-score will be calculated using CDC growth charts.
|
6 months
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Physical activity via accelerometry (bouts of physical activity)
Time Frame: Baseline
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Physical activity data will be collected using ActiGraph (trademark) accelerometers worn continuously over 7 days except during bathing and sleeping.
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Baseline
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Physical activity via accelerometry (bouts of physical activity)
Time Frame: 3 months
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Physical activity data will be collected using ActiGraph (trademark) accelerometers worn continuously over 7 days except during bathing and sleeping.
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3 months
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Physical activity via accelerometry (bouts of physical activity)
Time Frame: 6 months
|
Physical activity data will be collected using ActiGraph (trademark) accelerometers worn continuously over 7 days except during bathing and sleeping.
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6 months
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ASA24 Automated Self Administered 24 hour dietary assessment tool
Time Frame: Baseline
|
To assess diet in participating youth, we will use NCI's automated, self-administered 24-hour dietary recall, the Automated Self-Administered 24-hour (ASA24 (registered trademark) dietary assessment tool (version: ASA24-2016) on three, non-consecutive days (including one weekend day). Caloric intake will be expressed in kilocalories in order to compare dietary behavior following the delivery of some program components. There are no specific ranges. |
Baseline
|
ASA24 Automated Self Administered 24 hour dietary assessment tool
Time Frame: 3 months
|
To assess diet in participating youth, we will use NCI's automated, self-administered 24-hour dietary recall, the Automated Self-Administered 24-hour (ASA24 (registered trademark) dietary assessment tool (version: ASA24-2016) on three, non-consecutive days (including one weekend day). Caloric intake will be expressed in kilocalories in order to compare dietary behavior following the delivery of some program components. There are no specific ranges. |
3 months
|
ASA24 Automated Self Administered 24 hour dietary assessment tool
Time Frame: 6 months
|
To assess diet in participating youth, we will use NCI's automated, self-administered 24-hour dietary recall, the Automated Self-Administered 24-hour (ASA24 (registered trademark) dietary assessment tool (version: ASA24-2016) on three, non-consecutive days (including one weekend day). Caloric intake will be expressed in kilocalories in order to compare dietary behavior following the delivery of some program components. There are no specific ranges. |
6 months
|
Economic costs of the mHealth intervention costs
Time Frame: Baseline
|
Clinical costs of the mHealth intervention will be compiled over the duration of the program.
|
Baseline
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Economic costs of the mHealth intervention costs
Time Frame: 3 months
|
Clinical costs of the mHealth intervention will be compiled over the duration of the program.
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3 months
|
Economic costs of the mHealth intervention costs
Time Frame: 6 months
|
Clinical costs of the mHealth intervention will be compiled over the duration of the program.
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6 months
|
Collaborators and Investigators
Investigators
- Principal Investigator: Justin B Moore, PhD, Wake Forest Baptist Medical Center
Publications and helpful links
General Publications
- Thompson FE, Dixit-Joshi S, Potischman N, Dodd KW, Kirkpatrick SI, Kushi LH, Alexander GL, Coleman LA, Zimmerman TP, Sundaram ME, Clancy HA, Groesbeck M, Douglass D, George SM, Schap TE, Subar AF. Comparison of Interviewer-Administered and Automated Self-Administered 24-Hour Dietary Recalls in 3 Diverse Integrated Health Systems. Am J Epidemiol. 2015 Jun 15;181(12):970-8. doi: 10.1093/aje/kwu467. Epub 2015 May 10.
- Ryan RM, Connell JP. Perceived locus of causality and internalization: examining reasons for acting in two domains. J Pers Soc Psychol. 1989 Nov;57(5):749-61. doi: 10.1037//0022-3514.57.5.749.
- Skelton JA, Buehler C, Irby MB, Grzywacz JG. Where are family theories in family-based obesity treatment?: conceptualizing the study of families in pediatric weight management. Int J Obes (Lond). 2012 Jul;36(7):891-900. doi: 10.1038/ijo.2012.56. Epub 2012 Apr 24.
- Kirk S, Zeller M, Claytor R, Santangelo M, Khoury PR, Daniels SR. The relationship of health outcomes to improvement in BMI in children and adolescents. Obes Res. 2005 May;13(5):876-82. doi: 10.1038/oby.2005.101.
- Cheng JK, Wen X, Coletti KD, Cox JE, Taveras EM. 2-Year BMI Changes of Children Referred for Multidisciplinary Weight Management. Int J Pediatr. 2014;2014:152586. doi: 10.1155/2014/152586. Epub 2014 Jan 30.
- Skelton JA, Beech BM. Attrition in paediatric weight management: a review of the literature and new directions. Obes Rev. 2011 May;12(5):e273-81. doi: 10.1111/j.1467-789X.2010.00803.x. Epub 2010 Sep 29.
- Golan M. Fifteen years of the Family Eating and Activity Habits Questionnaire (FEAHQ): an update and review. Pediatr Obes. 2014 Apr;9(2):92-101. doi: 10.1111/j.2047-6310.2013.00144.x. Epub 2013 Feb 28.
- Turner-McGrievy GM, Beets MW, Moore JB, Kaczynski AT, Barr-Anderson DJ, Tate DF. Comparison of traditional versus mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in an mHealth weight loss program. J Am Med Inform Assoc. 2013 May 1;20(3):513-8. doi: 10.1136/amiajnl-2012-001510. Epub 2013 Feb 21.
- Irby MB, Kolbash S, Garner-Edwards D, Skelton JA. Pediatric Obesity Treatment in Children With Neurodevelopmental Disabilities: A Case Series and Review of the Literature. Infant Child Adolesc Nutr. 2012 Aug 1;4(4):215-221. doi: 10.1177/1941406412448527.
- Chandler JL, Brazendale K, Beets MW, Mealing BA. Classification of physical activity intensities using a wrist-worn accelerometer in 8-12-year-old children. Pediatr Obes. 2016 Apr;11(2):120-7. doi: 10.1111/ijpo.12033. Epub 2015 Apr 20.
- Chandler JL, Beets MW, Drenowatz C, et al. Analysis of Accelerometer Counts during Sedentary Activities on Dominant and Non-Dominant Wrists in 5-11 year old Children. Under review.
- Kirkpatrick SI, Subar AF, Douglass D, Zimmerman TP, Thompson FE, Kahle LL, George SM, Dodd KW, Potischman N. Performance of the Automated Self-Administered 24-hour Recall relative to a measure of true intakes and to an interviewer-administered 24-h recall. Am J Clin Nutr. 2014 Jul;100(1):233-40. doi: 10.3945/ajcn.114.083238. Epub 2014 Apr 30.
- Haines J, Rifas-Shiman SL, Horton NJ, Kleinman K, Bauer KW, Davison KK, Walton K, Austin SB, Field AE, Gillman MW. Family functioning and quality of parent-adolescent relationship: cross-sectional associations with adolescent weight-related behaviors and weight status. Int J Behav Nutr Phys Act. 2016 Jun 14;13:68. doi: 10.1186/s12966-016-0393-7.
- Motl RW, Dishman RK, Dowda M, Pate RR. Factorial validity and invariance of a self-report measure of physical activity among adolescent girls. Res Q Exerc Sport. 2004 Sep;75(3):259-71. doi: 10.1080/02701367.2004.10609159.
- Brown CL, Halvorson EE, Cohen GM, Lazorick S, Skelton JA. Addressing Childhood Obesity: Opportunities for Prevention. Pediatr Clin North Am. 2015 Oct;62(5):1241-61. doi: 10.1016/j.pcl.2015.05.013. Epub 2015 Jul 16.
- Skelton JA, Goff DC Jr, Ip E, Beech BM. Attrition in a Multidisciplinary Pediatric Weight Management Clinic. Child Obes. 2011 Jun 20;7(3):185-193. doi: 10.1089/chi.2011.0010.
- Irby M, Kaplan S, Garner-Edwards D, Kolbash S, Skelton JA. Motivational interviewing in a family-based pediatric obesity program: a case study. Fam Syst Health. 2010 Sep;28(3):236-46. doi: 10.1037/a0020101.
- Skelton JA, Martin S, Irby MB. Satisfaction and attrition in paediatric weight management. Clin Obes. 2016 Apr;6(2):143-53. doi: 10.1111/cob.12138. Epub 2016 Jan 27.
- Bishop J, Irby MB, Isom S, Blackwell CS, Vitolins MZ, Skelton JA. Diabetes prevention, weight loss, and social support: program participants' perceived influence on the health behaviors of their social support system. Fam Community Health. 2013 Apr-Jun;36(2):158-71. doi: 10.1097/FCH.0b013e318282b2d3.
- Giannini C, Irby MB, Skelton JA. Caregiver Expectations of Family-based Pediatric Obesity Treatment. Am J Health Behav. 2015 Jul;39(4):451-60. doi: 10.5993/AJHB.39.4.1.
- Skelton JA, Irby MB, Guzman MA, Beech BM. Children's Perceptions of Obesity and Health: A Focus Group Study With Hispanic Boys. Infant Child Adolesc Nutr. 2012 Oct 1;4(5):289-296. doi: 10.1177/1941406412446946.
- Turner-McGrievy G, Tate D. Tweets, Apps, and Pods: Results of the 6-month Mobile Pounds Off Digitally (Mobile POD) randomized weight-loss intervention among adults. J Med Internet Res. 2011 Dec 20;13(4):e120. doi: 10.2196/jmir.1841.
- Turner-McGrievy GM, Campbell MK, Tate DF, Truesdale KP, Bowling JM, Crosby L. Pounds Off Digitally study: a randomized podcasting weight-loss intervention. Am J Prev Med. 2009 Oct;37(4):263-9. doi: 10.1016/j.amepre.2009.06.010.
- Turner-McGrievy GM, Tate DF. Weight loss social support in 140 characters or less: use of an online social network in a remotely delivered weight loss intervention. Transl Behav Med. 2013 Sep;3(3):287-94. doi: 10.1007/s13142-012-0183-y.
- Pagoto SL, Waring ME, Schneider KL, Oleski JL, Olendzki E, Hayes RB, Appelhans BM, Whited MC, Busch AM, Lemon SC. Twitter-Delivered Behavioral Weight-Loss Interventions: A Pilot Series. JMIR Res Protoc. 2015 Oct 23;4(4):e123. doi: 10.2196/resprot.4864.
- Maher CA, Lewis LK, Ferrar K, Marshall S, De Bourdeaudhuij I, Vandelanotte C. Are health behavior change interventions that use online social networks effective? A systematic review. J Med Internet Res. 2014 Feb 14;16(2):e40. doi: 10.2196/jmir.2952.
- Hales SB, Davidson C, Turner-McGrievy GM. Varying social media post types differentially impacts engagement in a behavioral weight loss intervention. Transl Behav Med. 2014 Dec;4(4):355-62. doi: 10.1007/s13142-014-0274-z.
- Djafarian K, Speakman JR, Stewart J, Jackson DM. Comparison of activity levels measured by a wrist worn accelerometer and direct observation in young children. Open Journal of Pediatrics. 2013;03(04):422-427. 162.
- Crouter SE, Flynn JI, Bassett DR Jr. Estimating physical activity in youth using a wrist accelerometer. Med Sci Sports Exerc. 2015 May;47(5):944-51. doi: 10.1249/MSS.0000000000000502.
- Brazendale K, Beets MW, Bornstein DB, Moore JB, Pate RR, Weaver RG, Falck RS, Chandler JL, Andersen LB, Anderssen SA, Cardon G, Cooper A, Davey R, Froberg K, Hallal PC, Janz KF, Kordas K, Kriemler S, Puder JJ, Reilly JJ, Salmon J, Sardinha LB, Timperio A, van Sluijs EMF; International Children's Accelerometry Database (ICAD) Collaborators. Equating accelerometer estimates among youth: The Rosetta Stone 2. J Sci Med Sport. 2016 Mar;19(3):242-249. doi: 10.1016/j.jsams.2015.02.006. Epub 2015 Feb 23.
- Chandler JL, Beets MW, Drenowatz C, et al. The Rosetta Stone for equating hip and wrist- based accelerometer derived estimates of physical activity among elementary aged youth. Under review.
- Ward DS, Evenson KR, Vaughn A, Rodgers AB, Troiano RP. Accelerometer use in physical activity: best practices and research recommendations. Med Sci Sports Exerc. 2005 Nov;37(11 Suppl):S582-8. doi: 10.1249/01.mss.0000185292.71933.91.
- Moore JB, Brinkley J, Crawford TW, Evenson KR, Brownson RC. Association of the built environment with physical activity and adiposity in rural and urban youth. Prev Med. 2013 Feb;56(2):145-8. doi: 10.1016/j.ypmed.2012.11.019. Epub 2012 Dec 3.
- Moore JB, Brinkley J, Morris SF, Oniffrey TM, Kolbe MB. Effectiveness of Community-Based Minigrants to Increase Physical Activity and Decrease Sedentary Time in Youth. J Public Health Manag Pract. 2016 Jul-Aug;22(4):370-8. doi: 10.1097/PHH.0000000000000274.
- Morris SF, Kolbe MB, Moore JB. Lessons learned from a collaborative field-based collection of physical activity data using accelerometers. J Public Health Manag Pract. 2014 Mar-Apr;20(2):251-8. doi: 10.1097/PHH.0b013e3182893b9b.
- Beets MW, Glenn Weaver R, Turner-McGrievy G, Huberty J, Ward DS, Freedman DA, Saunders R, Pate RR, Beighle A, Hutto B, Moore JB. Making healthy eating and physical activity policy practice: the design and overview of a group randomized controlled trial in afterschool programs. Contemp Clin Trials. 2014 Jul;38(2):291-303. doi: 10.1016/j.cct.2014.05.013. Epub 2014 Jun 2.
- Kaplan SG, Arnold EM, Irby MB, Boles KA, Skelton JA. Family Systems Theory and Obesity Treatment: Applications for Clinicians. Infant Child Adolesc Nutr. 2014 Feb 1;6(1):24-29. doi: 10.1177/1941406413516001.
- Sallis JF, Pinski RB, Grossman RM, Patterson TL, Nader PR. The development of self-efficacy scales for health related diet and exercise behaviors. Health Education Research. 1988;3(3):283-292.
- Isasi CR, Wills TA. Behavioral Self-Regulation and Weight-Related Behaviors in Inner-City Adolescents: A Model of Direct and Indirect Effects. Child Obes. 2011 Aug 1;7(4):306-315. doi: 10.1089/chi.2011.0011.
- Kendall P, Williams CL. Assessing the cognitive and behavioral components of children's selfmanagement. In: Karoly P, Kanfer F, eds. Self-Management and Behavior Change. New York: Pergamon Press; 1982.
- Heiby EM. Assessment of Frequency of Self-Reinforcement. Journal of Personality and Social Psychology. 1983;44(6):1304-1307.
- Deci EL, Schwartz AJ, Sheinman L, Ryan RM. An Instrument to Assess Adults Orientations toward Control Versus Autonomy with Children - Reflections on Intrinsic Motivation and Perceived Competence. Journal of Educational Psychology. 1981;73(5):642-650.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- IRB00058207
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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