- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06018844
Novel mHealth Physical Activity Intervention for Youth With Type 1 Diabetes Mellitus
August 1, 2025 updated by: Children's Mercy Hospital Kansas City
The goal of this longitudinal cohort study is to learn about a mHealth intervention in Type 1 Diabetes (T1D)
The main question[s] it aims to answer are:
- Does the intervention increase the amount of text messages between the mHealth software and participants?
- Do the text messages from the Nudge software increase moderate to vigorous physical activity (MVPA) in participants?
- Does the MVPA encouraged by the Nudge software improve the HbA1c levels of participants?
Participants will:
- Receive text messages from the Nudge software
- Report physical activity goals via the text messages to the Nudge software
- Wear both an accelerometer and an actigraph for three weeks (spread out across the beginning, 30 days, and 90 days of participation)
- Complete surveys at the beginning of participation
- Complete daily surveys while wearing the devices
- Complete surveys at the end of participation
- Record physical activity in study surveys
Study Overview
Study Type
Observational
Enrollment (Actual)
1
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
-
-
Missouri
-
Kansas City, Missouri, United States, 64111
- Children's Mercy
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
Accepts Healthy Volunteers
No
Sampling Method
Non-Probability Sample
Study Population
Patients 12.00 to 21.99 with Type 1 Diabetes
Description
Inclusion Criteria:
- Participants 12.00-21.99 years old
- Participants with a physician confirmed T1D diagnosis.
- T1D diagnosis was at least 6 months prior to study enrollment
- Participants are on an intensive insulin regiment (either with an insulin pump or multiple daily injection)
- Participants must be using a continuous glucose monitor (CGM)
- Participants and parents/legally authorized representatives (LARS) of participants less than 18.00 speak/read English.
Exclusion Criteria:
- Participants with evidence of type 2 or monogenic diabetes.
- Participants with a comorbid chronic condition (e.g., renal disease).
- Participants with presence of severe psychiatric disorders.
- Participants with a diagnosis of low vision (vision that cannot be corrected with contact lenses or eyeglasses).
- Participants with limited mobility that would prevent participant from engaging in daily physical activity, self-assessed by participant.
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
%Daily Text Messages Exchanged Between Youth and the NUDGE Bot
Time Frame: Through study completion, an average of 3.5 months
|
percent of daily text messages exchanged between youth and the NUDGE bot
|
Through study completion, an average of 3.5 months
|
|
Moderate to Vigorous Physical Activity (MVPA) Levels
Time Frame: Day 1, 30 and 90
|
Participants' MVPA levels
|
Day 1, 30 and 90
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
%Days That Youth Wear the Actigraph
Time Frame: Day 1, 30 and 90
|
Percent of days that youth wear the actigraph
|
Day 1, 30 and 90
|
|
%Daily Physical Activity (PA) Schedules That Participants Complete
Time Frame: Day 1, 30 and 90
|
percent of daily PA schedules that participants complete
|
Day 1, 30 and 90
|
|
Change in Participant HbA1c
Time Frame: Through study completion, an average of 3.5 months
|
Change in participant HbA1c
|
Through study completion, an average of 3.5 months
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Investigators
- Principal Investigator: Mark Clements, MD, Children's Mercy
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Larsen DL, Attkisson CC, Hargreaves WA, Nguyen TD. Assessment of client/patient satisfaction: development of a general scale. Eval Program Plann. 1979;2(3):197-207. doi: 10.1016/0149-7189(79)90094-6. No abstract available.
- Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009 Apr;42(2):377-81. doi: 10.1016/j.jbi.2008.08.010. Epub 2008 Sep 30.
- Lowe MR, Butryn ML, Didie ER, Annunziato RA, Thomas JG, Crerand CE, Ochner CN, Coletta MC, Bellace D, Wallaert M, Halford J. The Power of Food Scale. A new measure of the psychological influence of the food environment. Appetite. 2009 Aug;53(1):114-8. doi: 10.1016/j.appet.2009.05.016. Epub 2009 Jun 12.
- Varni JW, Seid M, Kurtin PS. PedsQL 4.0: reliability and validity of the Pediatric Quality of Life Inventory version 4.0 generic core scales in healthy and patient populations. Med Care. 2001 Aug;39(8):800-12. doi: 10.1097/00005650-200108000-00006.
- Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O'Neal L, McLeod L, Delacqua G, Delacqua F, Kirby J, Duda SN; REDCap Consortium. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform. 2019 Jul;95:103208. doi: 10.1016/j.jbi.2019.103208. Epub 2019 May 9.
- Motl RW, Dishman RK, Trost SG, Saunders RP, Dowda M, Felton G, Ward DS, Pate RR. Factorial validity and invariance of questionnaires measuring social-cognitive determinants of physical activity among adolescent girls. Prev Med. 2000 Nov;31(5):584-94. doi: 10.1006/pmed.2000.0735.
- Michie S, Abraham C, Whittington C, McAteer J, Gupta S. Effective techniques in healthy eating and physical activity interventions: a meta-regression. Health Psychol. 2009 Nov;28(6):690-701. doi: 10.1037/a0016136.
- Carver CS, Scheier MF. Control theory: a useful conceptual framework for personality-social, clinical, and health psychology. Psychol Bull. 1982 Jul;92(1):111-35. No abstract available.
- Bergenstal RM, Ahmann AJ, Bailey T, Beck RW, Bissen J, Buckingham B, Deeb L, Dolin RH, Garg SK, Goland R, Hirsch IB, Klonoff DC, Kruger DF, Matfin G, Mazze RS, Olson BA, Parkin C, Peters A, Powers MA, Rodriguez H, Southerland P, Strock ES, Tamborlane W, Wesley DM. Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the Ambulatory Glucose Profile (AGP). Diabetes Technol Ther. 2013 Mar;15(3):198-211. doi: 10.1089/dia.2013.0051. Epub 2013 Feb 28.
- Levesque CS, Williams GC, Elliot D, Pickering MA, Bodenhamer B, Finley PJ. Validating the theoretical structure of the Treatment Self-Regulation Questionnaire (TSRQ) across three different health behaviors. Health Educ Res. 2007 Oct;22(5):691-702. doi: 10.1093/her/cyl148. Epub 2006 Nov 30.
- Miculis CP, De Campos W, da Silva Boguszweski MC. Correlation between glycemic control and physical activity level in adolescents and children with type 1 diabetes. J Phys Act Health. 2015 Feb;12(2):232-7. doi: 10.1123/jpah.2013-0024. Epub 2014 Feb 5.
- Dabelea D. The accelerating epidemic of childhood diabetes. Lancet. 2009 Jun 13;373(9680):1999-2000. doi: 10.1016/S0140-6736(09)60874-6. Epub 2009 May 27. No abstract available.
- Vehik K, Hamman RF, Lezotte D, Norris JM, Klingensmith G, Bloch C, Rewers M, Dabelea D. Increasing incidence of type 1 diabetes in 0- to 17-year-old Colorado youth. Diabetes Care. 2007 Mar;30(3):503-9. doi: 10.2337/dc06-1837.
- Mayer-Davis EJ, Dabelea D, Lawrence JM. Incidence Trends of Type 1 and Type 2 Diabetes among Youths, 2002-2012. N Engl J Med. 2017 Jul 20;377(3):301. doi: 10.1056/NEJMc1706291. No abstract available.
- Miller GF, Coffield E, Leroy Z, Wallin R. Prevalence and Costs of Five Chronic Conditions in Children. J Sch Nurs. 2016 Oct;32(5):357-64. doi: 10.1177/1059840516641190. Epub 2016 Apr 4.
- American Diabetes Association. 13. Children and Adolescents: Standards of Medical Care in Diabetes-2020. Diabetes Care. 2020 Jan;43(Suppl 1):S163-S182. doi: 10.2337/dc20-S013.
- Nguyen T, Obeid J, Walker RG, Krause MP, Hawke TJ, McAssey K, Vandermeulen J, Timmons BW. Fitness and physical activity in youth with type 1 diabetes mellitus in good or poor glycemic control. Pediatr Diabetes. 2015 Feb;16(1):48-57. doi: 10.1111/pedi.12117. Epub 2014 Jan 20.
- Tully C, Aronow L, Mackey E, Streisand R. Physical Activity in Youth With Type 1 Diabetes: a Review. Curr Diab Rep. 2016 Sep;16(9):85. doi: 10.1007/s11892-016-0779-6.
- Cushing CC, Mitchell TB, Bejarano CM, Walters RW, Crick CJ, Noser AE. Bidirectional Associations Between Psychological States and Physical Activity in Adolescents: A mHealth Pilot Study. J Pediatr Psychol. 2017 Jun 1;42(5):559-568. doi: 10.1093/jpepsy/jsw099.
- Lenhart, A. (2015). Teens, Social Media, & Technology Overview. Retrieved from http://pewinternet.org/2015/04/09/teens-social-media-technology-2015/
- Yang CH, Maher JP, Conroy DE. Implementation of behavior change techniques in mobile applications for physical activity. Am J Prev Med. 2015 Apr;48(4):452-5. doi: 10.1016/j.amepre.2014.10.010. Epub 2015 Jan 6.
- Brannon EE, Cushing CC. A systematic review: is there an app for that? Translational science of pediatric behavior change for physical activity and dietary interventions. J Pediatr Psychol. 2015 May;40(4):373-84. doi: 10.1093/jpepsy/jsu108. Epub 2014 Dec 13.
- Militello LK, Melnyk BM, Hekler E, Small L, Jacobson D. Correlates of Healthy Lifestyle Beliefs and Behaviors in Parents of Overweight or Obese Preschool Children Before and After a Cognitive Behavioral Therapy Intervention With Text Messaging. J Pediatr Health Care. 2016 May-Jun;30(3):252-60. doi: 10.1016/j.pedhc.2015.08.002. Epub 2015 Oct 1.
- Cushing CC, Bejarano CM, Ortega A, Sayre N, Fedele DA, Smyth JM. Adaptive mHealth Intervention for Adolescent Physical Activity Promotion. J Pediatr Psychol. 2021 Jun 3;46(5):536-546. doi: 10.1093/jpepsy/jsaa125.
- Cushing CC, Steele RG. A meta-analytic review of eHealth interventions for pediatric health promoting and maintaining behaviors. J Pediatr Psychol. 2010 Oct;35(9):937-49. doi: 10.1093/jpepsy/jsq023. Epub 2010 Apr 14.
- Patton SR, Clements MA, Fridlington A, Cohoon C, Turpin AL, Delurgio SA. Frequency of mealtime insulin bolus as a proxy measure of adherence for children and youths with type 1 diabetes mellitus. Diabetes Technol Ther. 2013 Feb;15(2):124-8. doi: 10.1089/dia.2012.0229. Epub 2013 Jan 14.
- Laurent J, Catanzaro SJ, Joiner TE, Rudolph KD, Potter KI, Lambert S, Gathright T. A measure of positive and negative affect for children: scale development and preliminary validation. Psychol Assess. 1999; 11: pp. 326.
- Terry PC, Lane AM, Lane HJ, Keohane L. Development and validation of a mood measure for adolescents. J Sports Sci. 1999 Nov;17(11):861-72. doi: 10.1080/026404199365425.
- Nelson TD, Benson ER, Jensen CD. Negative attitudes toward physical activity: measurement and role in predicting physical activity levels among preadolescents. J Pediatr Psychol. 2010 Jan-Feb;35(1):89-98. doi: 10.1093/jpepsy/jsp040. Epub 2009 May 15.
- Fox KR, Corbin CB. The physical self-perception profile: development and preliminary validation. J Sport Exerc Psychol. 1989; 11:408-430.
- Duncan TE, McAuley E. Social support and efficacy cognitions in exercise adherence: a latent growth curve analysis. J Behav Med. 1993 Apr;16(2):199-218. doi: 10.1007/BF00844893.
- Fedele DA, Cushing CC, Fritz A, Amaro CM, Ortega A. Mobile Health Interventions for Improving Health Outcomes in Youth: A Meta-analysis. JAMA Pediatr. 2017 May 1;171(5):461-469. doi: 10.1001/jamapediatrics.2017.0042.
- Riddell MC, Gallen IW, Smart CE, Taplin CE, Adolfsson P, Lumb AN, Kowalski A, Rabasa-Lhoret R, McCrimmon RJ, Hume C, Annan F, Fournier PA, Graham C, Bode B, Galassetti P, Jones TW, Millan IS, Heise T, Peters AL, Petz A, Laffel LM. Exercise management in type 1 diabetes: a consensus statement. Lancet Diabetes Endocrinol. 2017 May;5(5):377-390. doi: 10.1016/S2213-8587(17)30014-1. Epub 2017 Jan 24.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
July 25, 2024
Primary Completion (Actual)
June 26, 2025
Study Completion (Actual)
June 26, 2025
Study Registration Dates
First Submitted
August 7, 2023
First Submitted That Met QC Criteria
August 29, 2023
First Posted (Actual)
August 31, 2023
Study Record Updates
Last Update Posted (Actual)
August 19, 2025
Last Update Submitted That Met QC Criteria
August 1, 2025
Last Verified
August 1, 2025
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- STUDY00002143
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
UNDECIDED
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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