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Clinical Trial Details — Status: Not yet recruiting

Administrative data

NCT number NCT06018844
Other study ID # STUDY00002143
Secondary ID
Status Not yet recruiting
Phase
First received
Last updated
Start date April 2025
Est. completion date April 2025

Study information

Verified date April 2024
Source Children's Mercy Hospital Kansas City
Contact Claire Petty
Phone 816-601-4546
Email ckpetty@cmh.edu
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

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


Recruitment information / eligibility

Status Not yet recruiting
Enrollment 250
Est. completion date April 2025
Est. primary completion date April 2025
Accepts healthy volunteers No
Gender All
Age group 13 Years to 21 Years
Eligibility 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 Design


Intervention

Other:
NUDGE
NUDGE is a brief mHealth text messaging intervention designed to promote activity in adolescents by allowing them to set, monitor, and receive feedback on daily PA goals through text message.

Locations

Country Name City State
n/a

Sponsors (3)

Lead Sponsor Collaborator
Children's Mercy Hospital Kansas City Nemours Children's Clinic, University of Kansas

References & Publications (33)

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. Erratum In: JAMA Pediatr. 2017 May 1;171(5):495. JAMA Pediatr. 2018 Mar 1;172(3):302. — View Citation

Fox KR, Corbin CB. The physical self-perception profile: development and preliminary validation. J Sport Exerc Psychol. 1989; 11:408-430.

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. — View Citation

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. — View Citation

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. — View Citation

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.

Lenhart, A. (2015). Teens, Social Media, & Technology Overview. Retrieved from http://pewinternet.org/2015/04/09/teens-social-media-technology-2015/

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. Erratum In: Lancet Diabetes Endocrinol. 2017 May;5(5):e3. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

* Note: There are 33 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary %daily text messages exchanged between youth and the NUDGE bot percent of daily text messages exchanged between youth and the NUDGE bot Through study completion, an average of 3.5 months
Primary Moderate to Vigorous Physical Activity (MVPA) levels Participants' MVPA levels Day 1, 30 and 90
Secondary %days that youth wear the actigraph Percent of days that youth wear the actigraph Day 1, 30 and 90
Secondary %daily physical activity (PA) schedules that participants complete percent of daily PA schedules that participants complete Day 1, 30 and 90
Secondary Change in participant HbA1c Change in participant HbA1c Through study completion, an average of 3.5 months
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