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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].
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| mHealth dietary app + health coaching intervention | A feasibility study will be utilized to establish the recruitment, retention, and adherence with post-kidney transplant recipients using a consumer-based mHealth dietary app + health coaching. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| mHealth dietary app + health coaching intervention | Behavioral | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| 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 |
| The Feasibility of Participant Retention for the Study | Retention (percent of participants that dropped during the study), will be recorded by the research assistant. | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
| The Feasibility of Adherence for Using the Lose- It App to Record Diet | Adherence (percent to adhere to logging daily dietary intake) will be recorded continuously each day by the "Lose-It" app. | Weekly for 12 weeks |
| The Feasibility of Adherence for Using the Lose- It App to Physical Actvity | Adherence (percent to adhere to logging daily physical activity) will be recorded continuously each day by the "Lose-It" app. | Weekly for 12 weeks |
| Measure | Description | Time Frame |
|---|---|---|
| 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. | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
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Inclusion Criteria:
Exclusion Criteria:
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The participants will be recruited or contacted from a list of kidney recipients that have already requested they be contacted for future studies from our previous study. This list consists of approximately 60 people.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Ohio State University Medical Center | Columbus | Ohio | 43210 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 29619563 | Background | 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. | |
| 27805534 | Background | Aksoy N. Weight Gain After Kidney Transplant. Exp Clin Transplant. 2016 Nov;14(Suppl 3):138-140. |
| Label | URL |
|---|---|
| National Institute of Diabetes and Digestive and Kidney Diseases. Mission \& Vision. 2019 Accessed August, 30, 2019 | View source |
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Participants were not eligible for this study if they were participating in a weight loss or structured exercise program or could not pass a brief cognitive test.
Recruitment of of participatns took place among patients who received care at a Midwest Medical Center Kidney Transplant Clinic or attended a Midwest transplant support group over four months using a convenience sampling strategy. Eligibility criteria for this study consisted of KRs, age 18 years or older, not on dialysis, the ability to speak and hear English, and possession of a smartphone capable of accessing and downloading mobile applications (apps), Wi-Fi, or Internet access.
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| ID | Title | Description |
|---|---|---|
| FG000 | mHealth Dietary App + Health Coaching Intervention | A feasibility study will be utilized to establish the recruitment, retention, and adherence with post-kidney transplant recipients using a consumer-based mHealth dietary app + health coaching. 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. |
| Title | Milestones | Reasons Not Completed | ||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
|
|
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| ID | Title | Description |
|---|---|---|
| BG000 | mHealth Dietary App + Health Coaching Intervention | A feasibility study will be utilized to establish the recruitment, retention, and adherence with post-kidney transplant recipients using a consumer-based mHealth dietary app + health coaching. 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. |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Continuous | Mean |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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. | Posted | Count of Participants | Participants | Baseline |
|
12 weeks
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | mHealth Dietary App + Health Coaching Intervention | A feasibility study will be utilized to establish the recruitment, retention, and adherence with post-kidney transplant recipients using a consumer-based mHealth dietary app + health coaching. 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. |
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| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Tara O'Brien | Ohio State University College of Nursing | 614-292-8045 | obrien.782@osu.edu |
Not provided
| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | May 5, 2021 | Jan 24, 2024 | Prot_SAP_000.pdf |
| ICF | No | No | Yes | Informed Consent Form | Nov 19, 2020 | Jan 24, 2024 | ICF_001.pdf |
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|
| 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." This scale has a range of total scores from 0-90. A higher score indicates higher self-efficacy for exercise. | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
| Fruit and Vegetable Servings Per Day | 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. Higher scores indicate that more fruits and vegetables are being consumed by participants. | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
| Fiber Intake | Fiber intake will be assessed using the Fruit, Vegetable and Fiber Screen which uses a scale to assessfiber intake using a Likert Scale to rate intake from less than1/ per week to more than 2 a day.Higher scores indicate more fiber intake. | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
| Fat Intake | The participant will record their percent of fat intake each day into the Lose-it Premium application. | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
| Carbohydrate Intake | The participant will record their percent of carbohydrate intake each day into the Lose-it Premium application. | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
| 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. | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
| 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. | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
| 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. | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
| 23758229 | Background | 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. |
| 30852120 | Background | 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. |
| 15659137 | Background | 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. |
| 28915863 | Background | 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. |
| 27234761 | Background | 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. |
| 27398045 | Background | 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. |
| 30737367 | Background | 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. |
| 28874181 | Background | 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. |
| 27550305 | Background | 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. |
| 11479161 | Background | 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. |
| 26664208 | Background | 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. |
| Background | 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. |
| 18268173 | Background | 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. |
| 26250965 | Background | 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. |
| 27392256 | Background | 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. |
| 27585627 | Background | Boehmer KR, Barakat S, Ahn S, Prokop LJ, Erwin PJ, Murad MH. Health coaching interventions for persons with chronic conditions: a systematic review and meta-analysis protocol. Syst Rev. 2016 Sep 1;5(1):146. doi: 10.1186/s13643-016-0316-3. |
| 24416684 | Background | 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. |
| 25771957 | Background | 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. |
| 32912051 | Background | 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. |
| 27555071 | Background | 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. |
| 29165966 | Background | 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. |
| 31688340 | Background | 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. |
| 32083436 | Background | 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. |
| 30249156 | Background | 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. |
| 27301950 | Background | 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. |
| Background | Deming WE, Orsini JN. The essential Deming : leadership principles from the father of quality management. New York: McGraw-Hill; 2013. |
| 17327542 | Background | 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. |
| 18007172 | Background | 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. |
| 18929686 | Background | 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. |
| 6668417 | Background | Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983 Dec;24(4):385-96. No abstract available. |
| 30518288 | Background | 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. |
| 10882320 | Background | 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. |
| 10788730 | Background | Block G, Gillespie C, Rosenbaum EH, Jenson C. A rapid food screener to assess fat and fruit and vegetable intake. Am J Prev Med. 2000 May;18(4):284-8. doi: 10.1016/s0749-3797(00)00119-7. |
| 37993961 | Derived | O'Brien T, Rose K, Focht B, Al Kahlout N, Jensen T, Heareth K, Nori U, Daloul R. The feasibility of Technology, Application, Self-Management for Kidney (TASK) intervention in post-kidney transplant recipients using a pre/posttest design. Pilot Feasibility Stud. 2023 Nov 22;9(1):190. doi: 10.1186/s40814-023-01417-9. |
| years |
|
| Sex: Female, Male | Count of Participants | Participants |
|
| Race (NIH/OMB) | Count of Participants | Participants |
|
| Region of Enrollment | Number | participants |
|
| Employment | Count of Participants | Participants |
|
| Number of kidney transplants | Count of Participants | Participants |
|
| Type of transplant | Count of Participants | Participants |
|
| Caregiver | Count of Participants | Participants |
|
| Number of household members | Count of Participants | Participants |
|
| Income | Count of Participants | Participants |
|
| Education | Count of Participants | Participants |
|
|
|
| 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. | Posted | Count of Participants | Participants | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
|
|
|
| Primary | The Feasibility of Adherence for Using the Lose- It App to Record Diet | Adherence (percent to adhere to logging daily dietary intake) will be recorded continuously each day by the "Lose-It" app. | Posted | Count of Participants | Participants | Weekly for 12 weeks |
|
|
|
| Primary | The Feasibility of Adherence for Using the Lose- It App to Physical Actvity | Adherence (percent to adhere to logging daily physical activity) will be recorded continuously each day by the "Lose-It" app. | Posted | Count of Participants | Participants | Weekly for 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. | There were some participants who withdrew from the study over time. | Posted | Mean | Standard Deviation | score on a scale | Assessed at 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." This scale has a range of total scores from 0-90. A higher score indicates higher self-efficacy for exercise. | Posted | Mean | Standard Deviation | score on a scale | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
|
|
|
|
| Secondary | Fruit and Vegetable Servings Per Day | 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. Higher scores indicate that more fruits and vegetables are being consumed by participants. | Posted | Number | servings of fruit and vegetables per day | Assessed at 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 assessfiber intake using a Likert Scale to rate intake from less than1/ per week to more than 2 a day.Higher scores indicate more fiber intake. | Posted | Count of Participants | Participants | Assessed at 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. | Posted | Mean | Standard Deviation | percentage of fat intake | Assessed at 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. | Posted | Mean | Standard Deviation | percentage of carbohydrate intake | Assessed at 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. | Posted | Mean | Standard Deviation | pounds | Assessed at 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. | Posted | Mean | Standard Deviation | millimeters of mercury (mmHg) | Assessed at 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. | Posted | Mean | Standard Deviation | millimeters of mercury (mmHg) | Assessed at Baseline, 4 weeks, 8 weeks, and 12 weeks |
|
|
|
|
| 0 |
| 20 |
| 0 |
| 20 |
| 0 |
| 20 |
Not provided
Not provided
Not provided
| Title | Measurements |
|---|
|
| 12 weeks |
|
| Title | Measurements |
|---|
|
| Week 4 |
|
| Week 5 |
|
| Week 6 |
|
| Week 7 |
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| Week 8 |
|
| Week 9 |
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| Week 10 |
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| Week 11 |
|
| Week 12 |
|
| Title | Measurements |
|---|
|
| Week 4 |
|
| Week 5 |
|
| Week 6 |
|
| Week 7 |
|
| Week 8 |
|
| Week 9 |
|
| Week 10 |
|
| Week 11 |
|
| Week 12 |
|
|
| Week 8 |
|
|
| Week 12 |
|
|
| 0.004 |
| 95% CI |
| -3.11 |
| 2-Sided |
| 95 |
| -5.07 |
| -1.15 |
| Other |
| Week 12 vs. Baseline | McNemar | 0.038 | 95% CI | -2.53 | 2-Sided | 95 | -4.90 | 0.16 | Other |
| Title | Measurements |
|---|---|
|
| Week 12 |
|
| 0.098 |
| 95% CI |
| 9.78 |
| 2-Sided |
| 95 |
| -2.01 |
| 21.56 |
| Other |
| Week 12 vs. Baseline | McNemar | 0.003 | 95% CI | 17.06 | 2-Sided | 95 | 6.51 | 27.60 | Other |
| Title | Measurements |
|---|---|
|
| Week 4 - 3 Servings or More |
|
| Week 8 - 2 Servings or Less |
|
| Week 8 - 3 Servings or More |
|
| Week 12 - 2 Servings or Less |
|
| Week 12 - 3 Servings or More |
|
| Other |
| Week 12 vs. Baseline | McNemar | 0.289 | Other |
| Title | Measurements |
|---|---|
|
| Week 4 - 21 mg or More |
|
| Week 8 - 20 mg or Less |
|
| Week 8 - 21 mg or More |
|
| Week 12 - 20 mg or Less |
|
| Week 12 - 21 mg or More |
|
| Other |
| Weel 12 vs. Baseline | McNemar | 1.000 | Other |
| Title | Measurements |
|---|---|
|
| Week 12 |
|
| 0.734 |
| 95% CI |
| -1.08 |
| 2-Sided |
| 95 |
| -7.72 |
| 5.56 |
| Other |
| Week 12 vs. Baseline | McNemar | 0.249 | 95% CI | -4.15 | 2-Sided | 95 | -11.53 | 3.23 | Other |
| Title | Measurements |
|---|---|
|
| Week 12 |
|
| 0.263 |
| 95% CI |
| 3.43 |
| 2-Sided |
| 95 |
| -2.83 |
| 9.69 |
| Other |
| Week 12 vs. Baseline | McNemar | 0.882 | Slope | 0.44 | 2-Sided | 95 | -5.80 | 6.68 | Other |
| Title | Measurements |
|---|---|
|
| Week 12 |
|
| 0.205 |
| 95% CI |
| -4.98 |
| 2-Sided |
| 95 |
| -9.08 |
| -0.88 |
| Other |
| Week 12 vs. Baseline | McNemar | 0.020 | 95% CI | -4.98 | 2-Sided | 95 | -9.08 | -0.8 | Other |
| Title | Measurements |
|---|---|
|
| Week 12 |
|
| 0.255 |
| 95% CI |
| -4.39 |
| 2-Sided |
| 95 |
| -12.24 |
| 3.46 |
| Other |
| Week 12 vs. Baseline | McNemar | 0.102 | 95% CI | -7.00 | 2-Sided | 95 | -15.55 | 1.55 | Other |
| Title | Measurements |
|---|---|
|
| Week 12 |
|
| 0.198 |
| 95% CI |
| -4.11 |
| 2-Sided |
| 95 |
| -10.59 |
| 2.37 |
| Other |
| Week 12 vs. Baseline | McNemar | .225 | 95% CI | -3.76 | 2-Sided | 95 | -10.08 | 2.55 | Other |