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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT06411769
Other study ID # U01MD019289
Secondary ID 7U01MD019289-02
Status Recruiting
Phase N/A
First received
Last updated
Start date August 2025
Est. completion date June 2027

Study information

Verified date May 2024
Source University of Texas, El Paso
Contact Jennifer J Salinas, Ph.D.,LMSW
Phone 915-747-7292
Email jsalinas7@utep.edu
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

The investigators will test if the 50,000 for Life (50K4Life) is effective at improving walking engagement in school employees in 30 public schools by delivering a two-phased adaptive intervention to improve walking engagement in school workers in 30 public schools. In Phase 1, all study schools will be randomly assigned to a 50K4Life only, or 50K4Life + SMS Text Messaging group. In Phase 2, non-responder schools will be randomly assigned to one of two 6-month adaptive treatments: a) an individual-level intervention that includes remote education modules (REM) and one-to-one monthly phone-based coaching, or, b) a school-level intervention that includes group educational sessions, school environmental modifications (floor distance markings, signage in corridors and breakrooms, promotional items), and work time/weekend group walks/hikes. The schools that 50% or more participants who achieve 50,000 steps in one week will continue with the Phase 1 condition. Intervention strategies will be coordinated by health educators and managed using the Pathverse app. Data collection will occur at baseline, 8 weeks (Phase 2 randomization decision point), 8 months (immediate post intervention), 12 months (4 months post-intervention), and 18 months (10 months post-intervention) for a total of 18 months of study participation.


Description:

Mexican Americans who live in the U.S.-Mexico border region suffer disproportionately from preventable cardiometabolic diseases. Regular brisk walking is an effective measure in regulating metabolic processes and preventing disease. Employer-based wellness programs are promising strategies to address this public health problem because of the opportunity to take advantage of workplace environments to improve opportunities for walking engagement while also addressing barriers associated with inactivity. Employer-based walking programs have not been widely tested on the U.S.-Mexico border. A clustered Sequential Multiple Assignment Randomized Trial (SMART) will be conducted to determine the effectiveness of an employer-based walking challenge intervention- 50,000 for Life (50K4Life)- in improving brisk walking engagement (at least 7,000 steps/day) among school district employees. The proposed intervention strategies are based on the walking interventions conducted by the Principal Investigator(s) in El Paso and behavioral, environmental and worksite interventions by the Co-Investigators. The trial will include 30 randomly selected public schools with predominantly Mexican American employees from El Paso County area school districts. The intervention strategies in 50K4Life will be in two phases: 1) 50K4Life vs. 50K4Life + SMS text messaging and 2) Individual vs. School level adaptation for campuses with a low response to the initial intervention phase. The investigators hypothesize that walking challenges with multilevel capacity building and adaptations based on intervention response will lead to improved adherence to PA guidelines. This proposed socioecological model-based study leverages resources through Hispanic Serving Institutions (HSI) from Texas and expertise in employer-based workplace interventions from the University of Georgia (UGA) based on the partner's accumulative work to address the disparity in PA and advance health equity in the Mexican American population. As part of the intervention evaluation, the PIs will conduct a process evaluation and cost-effectiveness to provide insight into cost and scalability. This study will provide needed information on optimizing the implementation of evidence-based behavioral interventions to improve walking engagement among Mexican Americans living in the U.S.-Mexico border region.


Recruitment information / eligibility

Status Recruiting
Enrollment 406
Est. completion date June 2027
Est. primary completion date June 2027
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - A school is eligible if it is located within one of the four target school districts - adult 18 years or older - full-time school-based school district employee - not pregnant and able to walk without physical limitations or assistive device - willing to wear our Fitbit tracking device or use their own tracking device for 18 months - own a smartphone - willingness to use a personal smartphone for tracking activity related to the Fitbit tracker, access online intervention content, and receive text messages. Exclusion Criteria: - Works at more than one school - Does not work on a district school campus - schools that previously participated in walking challenges

Study Design


Related Conditions & MeSH terms


Intervention

Behavioral:
50K4LIfe
This intervention will consist of the Walking Challenge only.
SMS Text Messaging
In this intervention, participants will received notifications onto the Pathverse app
Individual
In this Phase 2 individual-level intervention, participants will receive remote education modules and one-to-one monthly phone-based coaching.
School
In this Phase 2 school-level intervention, participants will receive group educational sessions, school environmental modifications (floor distance markings, signage in corridors and breakrooms, promotional items), and participate in work time/weekend group walks/hikes.

Locations

Country Name City State
United States University of Texas at El Paso El Paso Texas

Sponsors (2)

Lead Sponsor Collaborator
University of Texas, El Paso National Institute on Minority Health and Health Disparities (NIMHD)

Country where clinical trial is conducted

United States, 

References & Publications (36)

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Gay JL, Buchner DM, Smith J, He C. An examination of compensation effects in accelerometer-measured occupational and non-occupational physical activity. Prev Med Rep. 2017 Aug 5;8:55-59. doi: 10.1016/j.pmedr.2017.07.013. eCollection 2017 Dec. — View Citation

Gay JL, Buchner DM, Smith J. Occupational Physical Activity Opposes Obesity: A Cross-Sectional Modern Replication of the Morris 1953 London Busmen Study. J Occup Environ Med. 2019 Mar;61(3):177-182. doi: 10.1097/JOM.0000000000001489. — View Citation

Gay JL, Buchner DM. Ethnic disparities in objectively measured physical activity may be due to occupational activity. Prev Med. 2014 Jun;63:58-62. doi: 10.1016/j.ypmed.2014.02.015. Epub 2014 Feb 28. — View Citation

Gay JL, Saunders RP, Rees-Punia E, Dowda M, van den Berg AE. Role of Organizational Support on Implementation of an Environmental Change Intervention to Improve Child Fruit and Vegetable Intake: a Randomized Cross-Over Design. Prev Sci. 2019 Nov;20(8):1211-1218. doi: 10.1007/s11121-019-01043-z. — View Citation

Jung J, Cho I. Promoting Physical Activity and Weight Loss With mHealth Interventions Among Workers: Systematic Review and Meta-analysis of Randomized Controlled Trials. JMIR Mhealth Uhealth. 2022 Jan 21;10(1):e30682. doi: 10.2196/30682. — View Citation

Karstoft K, Clark MA, Jakobsen I, Muller IA, Pedersen BK, Solomon TP, Ried-Larsen M. The effects of 2 weeks of interval vs continuous walking training on glycaemic control and whole-body oxidative stress in individuals with type 2 diabetes: a controlled, randomised, crossover trial. Diabetologia. 2017 Mar;60(3):508-517. doi: 10.1007/s00125-016-4170-6. Epub 2016 Dec 9. — View Citation

Marteau TM, Ashcroft RE, Oliver A. Using financial incentives to achieve healthy behaviour. BMJ. 2009 Apr 9;338:b1415. doi: 10.1136/bmj.b1415. No abstract available. — View Citation

Mehta S, Dimsdale J, Nagle B, Holub CK, Woods C, Barquera S, Elder JP. Worksite interventions: improving lifestyle habits among Latin American adults. Am J Prev Med. 2013 May;44(5):538-42. doi: 10.1016/j.amepre.2013.01.015. — View Citation

Meng L, Wolff MB, Mattick KA, DeJoy DM, Wilson MG, Smith ML. Strategies for Worksite Health Interventions to Employees with Elevated Risk of Chronic Diseases. Saf Health Work. 2017 Jun;8(2):117-129. doi: 10.1016/j.shaw.2016.11.004. Epub 2016 Dec 2. — View Citation

Mitchell MS, Orstad SL, Biswas A, Oh PI, Jay M, Pakosh MT, Faulkner G. Financial incentives for physical activity in adults: systematic review and meta-analysis. Br J Sports Med. 2020 Nov;54(21):1259-1268. doi: 10.1136/bjsports-2019-100633. Epub 2019 May 15. — View Citation

Morton K, Sutton S, Hardeman W, Troughton J, Yates T, Griffin S, Davies M, Khunti K, Eborall H. A Text-Messaging and Pedometer Program to Promote Physical Activity in People at High Risk of Type 2 Diabetes: The Development of the PROPELS Follow-On Support Program. JMIR Mhealth Uhealth. 2015 Dec 15;3(4):e105. doi: 10.2196/mhealth.5026. — View Citation

Muir SD, Silva SSM, Woldegiorgis MA, Rider H, Meyer D, Jayawardana MW. Predictors of Success of Workplace Physical Activity Interventions: A Systematic Review. J Phys Act Health. 2019 Aug 1;16(8):647-656. doi: 10.1123/jpah.2018-0077. — View Citation

Parra-Medina D, Hilfinger Messias DK. Promotion of Physical Activity Among Mexican-Origin Women in Texas and South Carolina: An Examination of Social, Cultural, Economic, and Environmental Factors. Quest. 2011 Feb;63(1):100-117. doi: 10.1080/00336297.2011.10483668. — View Citation

Parra-Medina D, Mojica C, Liang Y, Ouyang Y, Ramos AI, Gomez I. Promoting Weight Maintenance among Overweight and Obese Hispanic Children in a Rural Practice. Child Obes. 2015 Aug;11(4):355-63. doi: 10.1089/chi.2014.0120. Epub 2015 May 7. — View Citation

Ramirez M, Wu S, Beale E. Designing a Text Messaging Intervention to Improve Physical Activity Behavior Among Low-Income Latino Patients With Diabetes: A Discrete-Choice Experiment, Los Angeles, 2014-2015. Prev Chronic Dis. 2016 Dec 22;13:E171. doi: 10.5888/pcd13.160035. — View Citation

Saadiq S, Valenzuela R, Wang J, Yin Z, Parra-Medina D, Gay J, Salinas JJ. Walking Engagement in Mexican Americans Who Participated in a Community-Wide Step Challenge in El Paso, TX. Int J Environ Res Public Health. 2021 Dec 2;18(23):12738. doi: 10.3390/ijerph182312738. — View Citation

Salinas JJ, McDaniel M, Parra-Medina D. The Role of Social Support and the Neighborhood Environment on Physical Activity in Low-income, Mexican-American Women in South Texas. J Prev Med Public Health. 2018 Sep;51(5):234-241. doi: 10.3961/jpmph.18.052. Epub 2018 Jul 25. — View Citation

Salinas JJ, Parra-Medina D. Physical activity change after a promotora-led intervention in low-income Mexican American women residing in South Texas. BMC Public Health. 2019 Jun 20;19(1):782. doi: 10.1186/s12889-019-7105-6. — View Citation

Salinas JJ, Valenzuela R, Sheen J, Carlyle M, Gay J, Morales A. An ORBIT Phase 1: Design study of a citywide employer-based walking challenges in a predominantly Mexican American metropolitan area. J Health Psychol. 2022 Mar;27(4):961-973. doi: 10.1177/1359105320977650. Epub 2020 Dec 20. — View Citation

Sallis JF, Grossman RM, Pinski RB, Patterson TL, Nader PR. The development of scales to measure social support for diet and exercise behaviors. Prev Med. 1987 Nov;16(6):825-36. doi: 10.1016/0091-7435(87)90022-3. — View Citation

Sedani A, Stover D, Coyle B, Wani RJ. Assessing Workplace Health and Safety Strategies, Trends, and Barriers through a Statewide Worksite Survey. Int J Environ Res Public Health. 2019 Jul 11;16(14):2475. doi: 10.3390/ijerph16142475. — View Citation

Stephenson A, McDonough SM, Murphy MH, Nugent CD, Mair JL. Using computer, mobile and wearable technology enhanced interventions to reduce sedentary behaviour: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2017 Aug 11;14(1):105. doi: 10.1186/s12966-017-0561-4. — View Citation

Tucker JM, Welk GJ, Beyler NK. Physical activity in U.S.: adults compliance with the Physical Activity Guidelines for Americans. Am J Prev Med. 2011 Apr;40(4):454-61. doi: 10.1016/j.amepre.2010.12.016. — View Citation

Valenzuela R, Morales A, Sheen J, Rangel S, Salinas JJ. The Implementation of Evidence-Based Obesity Education Curricula to Prevent Cancer in a Predominantly Mexican-American Community on the U.S.-Mexico Border. J Cancer Educ. 2023 Feb;38(1):215-224. doi: 10.1007/s13187-021-02101-3. Epub 2021 Oct 8. — View Citation

Wang J, Cai C, Padhye N, Orlander P, Zare M. A Behavioral Lifestyle Intervention Enhanced With Multiple-Behavior Self-Monitoring Using Mobile and Connected Tools for Underserved Individuals With Type 2 Diabetes and Comorbid Overweight or Obesity: Pilot Comparative Effectiveness Trial. JMIR Mhealth Uhealth. 2018 Apr 10;6(4):e92. doi: 10.2196/mhealth.4478. — View Citation

Wang J, Chu CF, Li C, Hayes L, Siminerio L. Diabetes Educators' Insights Regarding Connecting Mobile Phone- and Wearable Tracker-Collected Self-Monitoring Information to a Nationally-Used Electronic Health Record System for Diabetes Education: Descriptive Qualitative Study. JMIR Mhealth Uhealth. 2018 Jul 26;6(7):e10206. doi: 10.2196/10206. — View Citation

Wang J, Sereika SM, Chasens ER, Ewing LJ, Matthews JT, Burke LE. Effect of adherence to self-monitoring of diet and physical activity on weight loss in a technology-supported behavioral intervention. Patient Prefer Adherence. 2012;6:221-6. doi: 10.2147/PPA.S28889. Epub 2012 Mar 22. — View Citation

Weinstock J, Petry NM. Framing Financial Incentives to Increase Physical Activity Among Overweight and Obese Adults. Ann Intern Med. 2016 Oct 18;165(8):599. doi: 10.7326/L16-0281. No abstract available. — View Citation

Wolfenden L, Goldman S, Stacey FG, Grady A, Kingsland M, Williams CM, Wiggers J, Milat A, Rissel C, Bauman A, Farrell MM, Legare F, Ben Charif A, Zomahoun HTV, Hodder RK, Jones J, Booth D, Parmenter B, Regan T, Yoong SL. Strategies to improve the implementation of workplace-based policies or practices targeting tobacco, alcohol, diet, physical activity and obesity. Cochrane Database Syst Rev. 2018 Nov 14;11(11):CD012439. doi: 10.1002/14651858.CD012439.pub2. — View Citation

Wu S, Fisher-Hoch SP, Reninger B, McCormick JB. Meeting or Exceeding Physical Activity Guidelines is Associated with Reduced Risk for Cancer in Mexican-Americans. Am J Cancer Prev. 2016;4(1):1-7. doi: 10.12691/ajcp-4-1-1. Epub 2016 Jan 29. — View Citation

Yin Z, Errisuriz VL, Evans M, Inupakutika D, Kaghyan S, Li S, Esparza L, Akopian D, Parra-Medina D. A Digital Health Intervention for Weight Management for Latino Families Living in Rural Communities: Perspectives and Lessons Learned During Development. JMIR Form Res. 2020 Aug 20;4(8):e20679. doi: 10.2196/20679. — View Citation

Yin Z, Lesser J, Paiva KA, Zapata J Jr, Moreno-Vasquez A, Grigsby TJ, Ryan-Pettes SR, Parra-Medina D, Estrada V, Li S, Wang J. Using Mobile Health Tools to Engage Rural Underserved Individuals in a Diabetes Education Program in South Texas: Feasibility Study. JMIR Mhealth Uhealth. 2020 Mar 24;8(3):e16683. doi: 10.2196/16683. — View Citation

* Note: There are 36 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary Daily Step Count The Pathverse app synced with an activity tracker will be used to collect daily step counts. The goal is for teams (schools) to have 50% of their staff with an average weekly steps > 50,000. Daily, Weekly up to 18 months.
Secondary Cardiorespiratory Fitness (CVF) The heart rate/minute at the end of the YMCA 3-minute submaximal bench-stepping test will be used to assess the level of CVF associated with increased PA. Baseline, 8 weeks, 8 months, 12, months 18 months up to 18 months.
Secondary Weight Weight (to the nearest 0.1 kg) will be collected using a portable scale Baseline, 8 weeks, 8 months, 12 months, 18 months up to 18 months.
Secondary Height Height (measured to the nearest 0.1 cm) will be obtained using a stadiometer. Baseline
Secondary Body Mass Index Body Mass Index (BMI) will be calculated as weight (kg)/height squared (m2). Baseline, 8 weeks, 8 months, 12 months, 18 months up to 18 months.
Secondary Waist Circumference Waist circumference will be measured at the midway between the iliac crests and the lower ribs. Baseline, 8 weeks, 8 months, 12 months, 18 months up to 18 months.
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