Obesity, Childhood Clinical Trial
— IMPACTOfficial title:
Increased Monitoring of Physical Activity and Calories With Technology
Verified date | May 2022 |
Source | Wake Forest University Health Sciences |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
Since severe obesity in youth has been steadily increasing. Specialized pediatric obesity clinics provide programs to aid in reducing obesity. Since the home environment and parental behavioral modeling are two of the strongest predictors of child weight loss during behavioral weight loss interventions, a family-based treatment approach is best. This strategy has been moderately successful in our existing, evidence-based pediatric weight management program, Brenner Families In Training (Brenner FIT). However, since programs such as Brenner Families in Training rely on face-to-face interactions and delivery, they are sometimes by the time constraints experienced by families. Therefore, the purpose of this study is to develop and pilot a tailored, mobile health component to potentially increase the benefits seen by Brenner FIT standard program components and similar pediatric weight management programs.
Status | Completed |
Enrollment | 30 |
Est. completion date | December 1, 2022 |
Est. primary completion date | December 1, 2022 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 13 Years to 18 Years |
Eligibility | 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. |
Country | Name | City | State |
---|---|---|---|
United States | Brenner Children's Hospital | Winston-Salem | North Carolina |
Lead Sponsor | Collaborator |
---|---|
Wake Forest University Health Sciences |
United States,
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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.
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.
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. — View Citation
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. — View Citation
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. — View Citation
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.
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.
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
Heiby EM. Assessment of Frequency of Self-Reinforcement. Journal of Personality and Social Psychology. 1983;44(6):1304-1307.
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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.
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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.
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
* Note: There are 42 references in all — Click here to view all references
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | BMI z-score | 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. | Baseline | |
Primary | BMI z-score | 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 | |
Primary | BMI z-score | 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 | Physical activity via accelerometry (bouts of physical activity) | Physical activity data will be collected using ActiGraph (trademark) accelerometers worn continuously over 7 days except during bathing and sleeping. | Baseline | |
Secondary | Physical activity via accelerometry (bouts of physical activity) | Physical activity data will be collected using ActiGraph (trademark) accelerometers worn continuously over 7 days except during bathing and sleeping. | 3 months | |
Secondary | Physical activity via accelerometry (bouts of physical activity) | Physical activity data will be collected using ActiGraph (trademark) accelerometers worn continuously over 7 days except during bathing and sleeping. | 6 months | |
Secondary | ASA24 Automated Self Administered 24 hour dietary assessment tool | 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 | |
Secondary | ASA24 Automated Self Administered 24 hour dietary assessment tool | 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 | |
Secondary | ASA24 Automated Self Administered 24 hour dietary assessment tool | 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 | |
Secondary | Economic costs of the mHealth intervention costs | Clinical costs of the mHealth intervention will be compiled over the duration of the program. | Baseline | |
Secondary | Economic costs of the mHealth intervention costs | Clinical costs of the mHealth intervention will be compiled over the duration of the program. | 3 months | |
Secondary | Economic costs of the mHealth intervention costs | Clinical costs of the mHealth intervention will be compiled over the duration of the program. | 6 months |
Status | Clinical Trial | Phase | |
---|---|---|---|
Not yet recruiting |
NCT03994419 -
PErioperAtive CHildhood ObesitY
|
||
Active, not recruiting |
NCT06259539 -
A YouTube Curriculum for Children With Autism and Obesity
|
N/A | |
Completed |
NCT03533621 -
Gut Microbiome, Adiposity, and Probiotics (GMAP)
|
N/A | |
Completed |
NCT03641521 -
A Trial to Increase Child Vegetable Intake Through Behavioral Strategies
|
N/A | |
Completed |
NCT04009304 -
Effective Training Models for Implementing Health-Promoting Practices Afterschool
|
N/A | |
Completed |
NCT05563311 -
Functional Assessment and Sleep Apnea in Obese Children and Adolescents
|
N/A | |
Terminated |
NCT03586544 -
Reducing Exercise-induced Bronchoconstriction in Children With Asthma and Obesity
|
Phase 4 | |
Completed |
NCT03575884 -
Fit 5 Kids Screen Time Reduction Curriculum for Latino Preschoolers
|
N/A | |
Completed |
NCT04628897 -
Physical Activity and the Home Environment in Preschool-aged Children in Urban Bangladesh
|
||
Completed |
NCT03399617 -
SPOON: Sustained Program for Improving Nutrition - Guatemala
|
N/A | |
Enrolling by invitation |
NCT06265597 -
The Effect of Healthy Nutrition and Yoga Program on Obese Children
|
N/A | |
Active, not recruiting |
NCT03843424 -
Treatment Efforts Addressing Child Weight Management by Unifying Patients, Parents & Providers
|
N/A | |
Completed |
NCT03170700 -
Online Videos and New Feeding Content to Enhance a Current EFNEP Program
|
N/A | |
Not yet recruiting |
NCT06464497 -
Whole Foods for Teens: A Pilot Dietary Intervention to Reduce Body Adiposity in Adolescents With Obesity
|
N/A | |
Enrolling by invitation |
NCT05551650 -
El Sendero: Pathways to Health Study
|
||
Completed |
NCT04346433 -
Sleep and Stigma: Novel Moderators in the Relationship Between Weight Status and Cognitive Function
|
N/A | |
Recruiting |
NCT03963557 -
Cognitive Function and Body Mass Index in Children and Adolescents
|
||
Completed |
NCT03495310 -
Effect of Mindfulness on Stress, Appetite Hormones and Body Weight of Obese Schoolchildren. Controlled Clinical Trial
|
N/A | |
Recruiting |
NCT06028113 -
A Novel Obesity Prevention Program for High-Risk Infants in Primary Care
|
Phase 2 | |
Active, not recruiting |
NCT05465057 -
"HIIT Med Kiloene".
|
N/A |