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Clinical Trial Details — Status: Active, not recruiting

Administrative data

NCT number NCT05151445
Other study ID # 2020B0261
Secondary ID
Status Active, not recruiting
Phase
First received
Last updated
Start date March 1, 2021
Est. completion date December 2023

Study information

Verified date March 2023
Source Ohio State University
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The purpose of the study is to test the feasibility mHealth dietary app + health coaching for improving primary outcomes (recruitment, retention, and adherence) and secondary outcomes (perceived stress [ Perceived Stress Scale], exercise self-efficacy[Exercise Self-efficacy Scale], vegetable intake [Fruit, Vegetables, and Fiber Screen] fat intake [Lose-it Premium database], carbohydrate intake [Lose-it Premium database], weight, [Wi-Fi weight scale using the Lose-it Premium database], and blood pressure [Wi-Fi blood pressure cuff using the Lose-it Premium database].


Description:

The proposed study seeks to shift the paradigm for promoting diet intake and physical activity using education and self-report to provide a powerful combination of mHealth dietary app and health coaching (set goals, provide ongoing feedback, and self-monitor behaviors). To the investigators knowledge, this is the first time a mHealth dietary app and health coaching intervention has been used in kidney transplant recipients to link real-time data for monitoring dietary intake and physical activity. The long-term goal of this work is to enhance well-being in kidney recipients via lifestyle self-management of care for dietary intake and physical activity to ultimately prevent chronic diseases. The proposed study is important because early weight gain after kidney transplant is associated with adverse effects on the transplanted kidney function resulting in increased health care cost and poor quality of life. Interventions are needed to monitor kidney transplant recipients diet and physical activity in real-time to prevent health decline.


Recruitment information / eligibility

Status Active, not recruiting
Enrollment 20
Est. completion date December 2023
Est. primary completion date January 1, 2023
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - age 18 or older men and women - functioning KTR (not on dialysis) - ability to speak, read, and hear English, - possession of a smartphone capable of accessing and downloading a mHealth dietary app - Wi-Fi or Internet access, - greater than 3 months post-transplant (due to medication adjustments and decreased functional levels), - not hospitalized - capable of self-consent per capacity screening. Exclusion Criteria: - Participation in a weight loss program - participation in a structured exercise program - diagnosis of dementia.

Study Design


Related Conditions & MeSH terms


Intervention

Behavioral:
mHealth dietary app + health coaching intervention
The "Lose-It" app will be set up with Gmail accounts with unique unidentifiable codes developed by the research team. Participants be trained to enter their dietary intake and physical activity daily for 12-weeks. Participants will monitor their vegetable intake, fat intake, carbohydrate intake, weight, and blood pressure. Wi-Fi connected weight scales and blood pressure cuff will be supplied for weight and blood pressure monitoring. Participants will be taught how to sync the data from the scales and blood pressure cuff to the app for the research team to access. Participants will perform a return demonstration to confirm that they can record their dietary intake daily, physical activity, weight, and blood pressure using the "Lose-It" app. We also review with the participant the "My Plate" method for proper nutrition and the steps to distance conversion chart.

Locations

Country Name City State
United States Ohio State University Medical Center Columbus Ohio

Sponsors (1)

Lead Sponsor Collaborator
Ohio State University

Country where clinical trial is conducted

United States, 

References & Publications (35)

Aksoy N. Weight Gain After Kidney Transplant. Exp Clin Transplant. 2016 Nov;14(Suppl 3):138-140. — View Citation

Aminu MS, Sagren N, Manga P, Nazir MS, Naicker S. Obesity and graft dysfunction among kidney transplant recipients: Increased risk for atherosclerosis. Indian J Nephrol. 2015 Nov-Dec;25(6):340-3. doi: 10.4103/0971-4065.151358. — View Citation

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Clunk JM, Lin CY, Curtis JJ. Variables affecting weight gain in renal transplant recipients. Am J Kidney Dis. 2001 Aug;38(2):349-53. doi: 10.1053/ajkd.2001.26100. — View Citation

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Conte C, Secchi A. Post-transplantation diabetes in kidney transplant recipients: an update on management and prevention. Acta Diabetol. 2018 Aug;55(8):763-779. doi: 10.1007/s00592-018-1137-8. Epub 2018 Apr 4. — View Citation

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Edwards ES, Sackett SC. Psychosocial Variables Related to Why Women are Less Active than Men and Related Health Implications. Clin Med Insights Womens Health. 2016 Jul 4;9(Suppl 1):47-56. doi: 10.4137/CMWH.S34668. eCollection 2016. — View Citation

Hap K, Madziarska K, Hap W, Zmonarski S, Zielinska D, Kaminska D, Banasik M, Koscielska-Kasprzak K, Klinger M, Mazanowska O. Are Females More Prone Than Males to Become Obese After Kidney Transplantation? Ann Transplant. 2019 Jan 29;24:57-61. doi: 10.12659/AOT.912096. — View Citation

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Kim IK, Choi SH, Son S, Ju MK. Early Weight Gain After Transplantation Can Cause Adverse Effect on Transplant Kidney Function. Transplant Proc. 2016 Apr;48(3):893-6. doi: 10.1016/j.transproceed.2015.10.064. — View Citation

Klaassen G, Zelle DM, Navis GJ, Dijkema D, Bemelman FJ, Bakker SJL, Corpeleijn E. Lifestyle intervention to improve quality of life and prevent weight gain after renal transplantation: Design of the Active Care after Transplantation (ACT) randomized controlled trial. BMC Nephrol. 2017 Sep 15;18(1):296. doi: 10.1186/s12882-017-0709-0. — View Citation

Mellen PB, Gao SK, Vitolins MZ, Goff DC Jr. Deteriorating dietary habits among adults with hypertension: DASH dietary accordance, NHANES 1988-1994 and 1999-2004. Arch Intern Med. 2008 Feb 11;168(3):308-14. doi: 10.1001/archinternmed.2007.119. — View Citation

Moore SM, Jones L, Alemi F. Family self-tailoring: Applying a systems approach to improving family healthy living behaviors. Nurs Outlook. 2016 Jul-Aug;64(4):306-311. doi: 10.1016/j.outlook.2016.05.006. Epub 2016 May 18. — View Citation

O'Brien T, Hathaway D, Russell CL, Moore SM. Merging an Activity Tracker with SystemCHANGE to Improve Physical Activity in Older Kidney Transplant Recipients. Nephrol Nurs J. 2017 Mar-Apr;44(2):153-157. — View Citation

O'Brien T, Hathaway D. An Integrative Literature Review of Physical Activity Recommendations for Adult Renal Transplant Recipients. Prog Transplant. 2016 Dec;26(4):381-385. doi: 10.1177/1526924816664079. Epub 2016 Sep 20. — View Citation

O'Brien T, Jenkins C, Amella E, Mueller M, Moore M, Hathaway D. An Internet-Assisted Weight Loss Intervention for Older Overweight and Obese Rural Women: A Feasibility Study. Comput Inform Nurs. 2016 Nov;34(11):513-519. doi: 10.1097/CIN.0000000000000275. — View Citation

O'Brien T, Meyer T. A Feasibility Study for Teaching Older Kidney Transplant Recipients How to Wear and Use an Activity Tracker to Promote Daily Physical Activity. Nephrol Nurs J. 2020 Jan-Feb;47(1):47-51. — View Citation

O'Brien T, Russell CL, AlKahlout N, Rosenthal A, Meyer T, Tan A, Daloul R, Hathaway D. Recruitment of Older Kidney Transplant Recipients to a Longitudinal Study. Nurs Res. 2020 May/Jun;69(3):233-237. doi: 10.1097/NNR.0000000000000406. — View Citation

O'Brien T, Russell CL, Tan A, Mion L, Rose K, Focht B, Daloul R, Hathaway D. A Pilot Randomized Controlled Trial Using SystemCHANGE Approach to Increase Physical Activity in Older Kidney Transplant Recipients. Prog Transplant. 2020 Dec;30(4):306-314. doi: 10.1177/1526924820958148. Epub 2020 Sep 10. — View Citation

O'Brien T, Russell CL, Tan A, Washington M, Hathaway D. An Exploratory Correlational Study in the Use of Mobile Technology Among Adult Kidney Transplant Recipients. Prog Transplant. 2018 Dec;28(4):368-375. doi: 10.1177/1526924818800051. Epub 2018 Sep 24. — View Citation

O'Brien T, Troutman-Jordan M, Hathaway D, Armstrong S, Moore M. Acceptability of wristband activity trackers among community dwelling older adults. Geriatr Nurs. 2015 Mar-Apr;36(2 Suppl):S21-5. doi: 10.1016/j.gerinurse.2015.02.019. Epub 2015 Mar 13. — View Citation

Pedrollo EF, Nicoletto BB, Carpes LS, de Freitas JMC, Buboltz JR, Forte CC, Bauer AC, Manfro RC, Souza GC, Leitao CB. Effect of an intensive nutrition intervention of a high protein and low glycemic-index diet on weight of kidney transplant recipients: study protocol for a randomized clinical trial. Trials. 2017 Sep 6;18(1):413. doi: 10.1186/s13063-017-2158-2. — View Citation

Resnick B, Gruber-Baldini AL, Pretzer-Aboff I, Galik E, Buie VC, Russ K, Zimmerman S. Reliability and validity of the evaluation to sign consent measure. Gerontologist. 2007 Feb;47(1):69-77. doi: 10.1093/geront/47.1.69. — View Citation

Resnick B, Jenkins LS. Testing the reliability and validity of the Self-Efficacy for Exercise scale. Nurs Res. 2000 May-Jun;49(3):154-9. doi: 10.1097/00006199-200005000-00007. — View Citation

Rosenberger J, Geckova AM, Dijk JP, Roland R, Heuvel WJ, Groothof F JW. Factors modifying stress from adverse effects of immunosuppressive medication in kidney transplant recipients. Clin Transplant. 2005 Feb;19(1):70-6. doi: 10.1111/j.1399-0012.2004.00300.x. — View Citation

Sun Y, Gao L, Kan Y, Shi BX. The Perceived Stress Scale-10 (PSS-10) is reliable and has construct validity in Chinese patients with systemic lupus erythematosus. Lupus. 2019 Feb;28(2):149-155. doi: 10.1177/0961203318815595. Epub 2018 Dec 5. — View Citation

Sundararajan V, Quan H, Halfon P, Fushimi K, Luthi JC, Burnand B, Ghali WA; International Methodology Consortium for Coded Health Information (IMECCHI). Cross-national comparative performance of three versions of the ICD-10 Charlson index. Med Care. 2007 Dec;45(12):1210-5. doi: 10.1097/MLR.0b013e3181484347. — View Citation

Wilcox J, Waite C, Tomlinson L, Driscoll J, Karim A, Day E, Sharif A. Comparing glycaemic benefits of Active Versus passive lifestyle Intervention in kidney Allograft Recipients (CAVIAR): study protocol for a randomised controlled trial. Trials. 2016 Aug 22;17(1):417. doi: 10.1186/s13063-016-1543-6. — View Citation

Williams-Hooker R, Draper CM, Chen L, Mitchell CO, Cashion AK. The relationship between fruit and vegetable consumption and weight gain in kidney transplant recipients within 1 year posttransplant. Top Clin Nutr. 2015;30(4):324-332.

Wolever RQ, Simmons LA, Sforzo GA, Dill D, Kaye M, Bechard EM, Southard ME, Kennedy M, Vosloo J, Yang N. A Systematic Review of the Literature on Health and Wellness Coaching: Defining a Key Behavioral intervention in Healthcare. Glob Adv Health Med. 2013 Jul;2(4):38-57. doi: 10.7453/gahmj.2013.042. — View Citation

Workeneh B, Moore LW, Nolte Fong JV, Shypailo R, Gaber AO, Mitch WE. Successful Kidney Transplantation Is Associated With Weight Gain From Truncal Obesity and Insulin Resistance. J Ren Nutr. 2019 Nov;29(6):548-555. doi: 10.1053/j.jrn.2019.01.009. Epub 2019 Mar 7. — View Citation

Zelle DM, Kok T, Dontje ML, Danchell EI, Navis G, van Son WJ, Bakker SJ, Corpeleijn E. The role of diet and physical activity in post-transplant weight gain after renal transplantation. Clin Transplant. 2013 Jul-Aug;27(4):E484-90. doi: 10.1111/ctr.12149. Epub 2013 Jun 13. — View Citation

Zeltzer SM, Taylor DO, Tang WH. Long-term dietary habits and interventions in solid-organ transplantation. J Heart Lung Transplant. 2015 Nov;34(11):1357-65. doi: 10.1016/j.healun.2015.06.014. Epub 2015 Jul 6. — View Citation

* Note: There are 35 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary The Feasibility of the study Recruitment for the Study Recruitment (percent of participants approached to be in the study), will be recorded by the research assistant. Baseline
Primary The Feasibility of Participant Retention for the Study Retention (percent of participants that dropped during the study), will be recorded by the research assistant. To assess for a change in participant retention from Baseline, 4 weeks, 8 weeks, and 12 weeks
Primary The Feasibility of Adherence for using the Lose- It App to Record Diet and Physical Actvity Adherence (percent to adhere to logging daily dietary intake and physical activity) will be recorded continuously each day by the "Lose-It" app. To assess for a change in participant adherence from Baseline, 4 weeks, 8 weeks, and 12 weeks
Secondary Perceived Stress Level Perceived Stress Scale will be evaluated by using the Perceived Stress Scale (PSS).The PSS is a 10-item questionnaire using a Likert Scale to rate feelings of stress from 0 "never" to 4 "very often." Individual scores on the PSS can range from 0 to 40 with higher scores indicating higher perceived stress. This scale has a range of total scores from 0-90. A higher score indicates higher self-efficacy for exercise. To assess for a change in participant perceived stress from Baseline, 4 weeks, 8 weeks, and 12 weeks
Secondary Exercise Self-Efficacy Exercise Self-Efficacy Scale will be evaluated by using the Self-Efficacy for Exercise (SEE) Scale. The SEE is a 9-item questionnaire using a Likert Scale to rate feelings of stress from 0 "not confident" to 10 "very confident." To assess for a change in participant exercise self-efficacy from Baseline, 4 weeks, 8 weeks, and 12 weeks
Secondary Fruit and Vegetable Intake Fruit and vegetable intake will be assessed using the Fruit, Vegetable and Fiber Screen which uses a scale to assess fruit and vegetable intake using a Likert Scale to rate intake from less than1/ per week to more than 2 a day. To assess for a change in participant fruit, vegetable, and fiber intake from Baseline, 4 weeks, 8 weeks, and 12 weeks
Secondary Fiber Intake Fiber intake will be assessed using the Fruit, Vegetable and Fiber Screen which uses a scale to assess fruit and vegetable intake using a Likert Scale to rate intake from less than1/ per week to more than 2 a day. To assess for a change in participant fruit, vegetable, and fiber intake from Baseline, 4 weeks, 8 weeks, and 12 weeks
Secondary Fat Intake The participant will record their percent of fat intake each day into the Lose-it Premium application. To assess for a change in participant fat intake from Baseline, 4 weeks, 8 weeks, and 12 weeks
Secondary Carbohydrate Intake The participant will record their percent of carbohydrate intake each day into the Lose-it Premium application. To assess for a change in participant carbohydrate intake from Baseline, 4 weeks, 8 weeks, and 12 weeks
Secondary Weight Weight (pounds) will be measured each day by the participant using a wireless Wi Fi weight scale. The data from the wireless weight scale will sync the data from the participant's mobile phone to the premium password-protect "Lose-It" database each day. To assess for a change in participant weight from Baseline, 4 weeks, 8 weeks, and 12 weeks
Secondary Systolic Blood Pressure Systolic blood pressure (millimeters of mercury [mmHg]) will be recorded each day by the participant using a wireless Wi Fi blood pressure cuff. The data from the wireless cuff will sync from the participant's mobile phone to the premium password-protect "Lose-It" database each day. To assess for a change in participant systolic blood pressure from Baseline, 4 weeks, 8 weeks, and 12 weeks
Secondary Diastolic Blood Pressure Systolic blood pressure (millimeters of mercury [mmHg]) will be recorded each day by the participant using a wireless Wi Fi blood pressure cuff. The data from the wireless cuff will sync from the participant's mobile phone to the premium password-protect "Lose-It" database each day. To assess for a change in participant diastolic blood pressure from Baseline, 4 weeks, 8 weeks, and 12 weeks
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