Testing the effectiveness of physical activity advice delivered via text messaging vs. human phone advisors in a Latino population: The On The Move randomized controlled trial design and methods

Abby C King, Ines Campero, Jylana L Sheats, Cynthia M Castro Sweet, Patricia Rodriguez Espinosa, Dulce Garcia, Michelle Hauser, Monica Done, Michele L Patel, Nina M Parikh, Cecilia Corral, David K Ahn, Abby C King, Ines Campero, Jylana L Sheats, Cynthia M Castro Sweet, Patricia Rodriguez Espinosa, Dulce Garcia, Michelle Hauser, Monica Done, Michele L Patel, Nina M Parikh, Cecilia Corral, David K Ahn

Abstract

Physical inactivity is a key risk factor for a range of chronic diseases and conditions, yet, approximately 50% of U.S. adults fall below recommended levels of regular aerobic physical activity (PA). This is particularly true for ethnic minority populations such as Latino adults for whom few culturally adapted programs have been developed and tested. Text messaging (SMS) represents a convenient and accessible communication channel for delivering targeted PA information and support, but has not been rigorously evaluated against standard telehealth advising programs. The objective of the On The Move randomized controlled trial is to test the effectiveness of a linguistically and culturally targeted SMS PA intervention (SMS PA Advisor) versus two comparison conditions: a) a standard, staff-delivered phone PA intervention (Telephone PA Advisor) and b) an attention-control arm consisting of a culturally targeted SMS intervention to promote a healthy diet (SMS Nutrition Advisor). The study sample (N = 350) consists of generally healthy, insufficiently active Latino adults ages 35 years and older living in five northern California counties. Study assessments occur at baseline, 6, and 12 months, with a subset of participants completing 18-month assessments. The primary outcome is 12-month change in walking, and secondary outcomes include other forms of PA, assessed via validated self-report measures and supported by accelerometry, and physical function and well-being variables. Potential mediators and moderators of intervention success will be explored to better determine which subgroups do best with which type of intervention. Here we present the study design and methods, including recruitment strategies and yields. Trial Registration: clinicaltrial.gov Identifier = NCT02385591.

Keywords: Aging; Digital health; Latino; Physical activity; Text-messaging; mHealth.

Conflict of interest statement

Declaration of Competing Interest The authors report no competing or conflicts of interest.

Copyright © 2020 Elsevier Inc. All rights reserved.

Figures

Fig. 1
Fig. 1
Social cognitive theory and self-determination theory elements that can increase physical activity.
Fig. 2
Fig. 2
Recruitment methods and study enrollment yield, by method.

References

    1. U.S. Department of Health & Human Services . 2nd ed. Department of Health & Human Services; Washington, DC: U.S: 2018. Physical Activity Guidelines for Americans.
    1. Pleis J.R., Ward B.W., Lucas J.W. Summary health statistics for U.S. adults: National Health Interview Survey, 2009. In: Statistics NCfH, editor. Vital Health Stat. vol. 10(249) CDC; Atlanta, CA: 2010.
    1. Livingston G., Minushkin S., Cohn D. Pew Hispanic Center. 2008. Hispanics and health care in the United States: Access, information and knowledge.
    1. Silvia C.A. Barriers to physical activity in the Hispanic community. J. Public Health Policy. 2003;24(1):41–58.
    1. Physical Activity Guidelines Advisory Committee . Department of Health and Human Services; Washington, DC: U.S: 2018. 2018 Physical Activity Guidelines Advisory Committee Scientific Report.
    1. Pew Research Center Mobile Fact Sheet. 2019.
    1. Marquez D.X., Hoyem R., Fogg L., Bustamante E.E., Staffileno B., Wilbur J. Physical activity of urban community-dwelling older Latino adults. J. Phys. Act. Health. 2011;8(Suppl. 2):S161–S170.
    1. King A.C., Bickmore T.W., Campero M.I., Pruitt L.A., Yin J.L. Employing “virtual advisors” in preventive care for underserved communities: results from the COMPASS study. J. Health Commun. Int. Perspect. 2013;18(12):1449–1464.
    1. Buchholz S.W., Wilbur J., Ingram D., Fogg L. Physical activity text messaging interventions in adults: a systematic review. Worldviews on Evid. Based Nurs. Sigma Theta Tau Int. Honor Soc. Nurs. 2013;10(3):163–173.
    1. Head K.J., Noar S.M., Iannarino N.T., Grant H.N. Efficacy ot text messaging-based interventions for health promotion: a meta-analysis. Soc. Sci. Med. 2013;97:41–48.
    1. U.S. Census Bureau . U.S. Census Bureau; Washington, DC: 2015. 2015 American Community Survey. In.
    1. U.S Census Data. 2010.
    1. Physical Activity Guidelines Advisory Committee . Department of Health and Human Services; Washington, DC: U.S: 2008. Report of the Physical Activity Guidelines Advisory Committee, 2008.
    1. Stewart A.L., Mills K.M., King A.C., Haskell W.L., Gillis D., Ritter P.L. CHAMPS physical activity questionnaire for older adults: outcomes for interventions. Med. Sci. Sports Exerc. 2001;33(7):1126–1141.
    1. Thomas S., Reading J., Shephard R.J. Revision of the physical activity readiness questionnaire (PAR-Q) Canadian J. Sports Sci. 1992;17:338–345.
    1. King A.C., Harris R.B., Haskell W.L. Effect of recruitment strategy on types of subjects entered into a primary prevention clinical trial. Ann. Epidemiol. 1994;4:312–320.
    1. Kiernan M., Phillips K., Fair J.M., King A.C. Using direct mail to recruit Hispanic adults into a dietary intervention: an experimental study. Ann. Behav. Med. 2000;22(1):89–93.
    1. Brown S.D., Lee K., Schoffman D.E., King A.C., Crawley L.M., Kiernan M. Minority recruitment into clinical trials: experimental findings and practical implications. Contemp. Clin. Trials. 2012;33(4):620–623.
    1. Soto J., Campero M.I., Castro C.M., King A.C. Society of Behavioral Medicine 33rd Annual Meeting and Scientific Sessions: Rapid Communications. vol. 33. Society of Behavioral Medicine; New Orleans, LA: 2012. Lessons from recruiting Latino older adults into the LIFE trial; p. 56.
    1. Goldberg J.H., Kiernan M. Innovative techniques to address retention in a behavioral weight-loss trial. Health Educ. Res. 2005;20(4):439–447.
    1. King A.C., Haskell W.L., Taylor C.B., Kraemer H.C., DeBusk R.F. Group- vs home-based exercise training in healthy older men and women. A community-based clinical trial. JAMA. 1991;266(11):1535–1542.
    1. King A.C., Friedman R.M., Marcus B.H., Castro C., Napolitano M., Ahn D., Baker L. Ongoing physical activity advice by humans versus computers: the community health advice by telephone (CHAT) trial. Health Psychol. 2007;26:718–727.
    1. King A.C., Castro C.M., Buman M.P., Hekler E.B., Urizar G., Ahn D.G. Behavioral impacts of sequentially versus simultaneously delivered dietary plus physical activity interventions: the CALM Trial. Ann. Behav. Med. 2013;46(2):157–168.
    1. Wilcox S., Dowda M., Leviton L.C., Bartlett-Prescott J., Bazzarre T., Campbell-Voytal K., Carpenter R.A., Castro C.M., Dowdy D., Dunn A.L. Active for life: final results from the translation of two physical activity programs. Am. J. Prev. Med. 2008;35(4):340–351.
    1. Castro C.M., King A.C. Telephone-assisted counseling for physical activity. Exerc. Sport Sci. Rev. 2002;30(2):64–68.
    1. Bandura A. Health promotion by social cognitive means. Health Educ. Behav. 2004;31(2):143–164.
    1. Ryan R.M., Deci E.L. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am. Psychol. 2000;55:68–78.
    1. Greaves C.J., Sheppard K.E., Abraham C., Hardeman W., Roden M., Evans P.H., Schwarz P., Group TIS Systematic review of reviews of intervention components associated with increased effectiveness in dietary and physical activity interventions. BMC Public Health. 2011;11:119–130.
    1. Teixeira P.J., Carraca E.V., Markland D., Silva M.N., Ryan R.M. Exercise, physical activity, and self-determination theory: a systematic review. Int. J. Behav. Nutr. Phys. Act. 2012;9:78–107.
    1. Bandura A. Englewood Cliffs, NJ; Prentice Hall: 1986. Social Foundations of Thought and Action: A Social Cognitive Theory.
    1. Pescatello L.S., Arena R., Riebe D., Thompson P.D. 9th ed. Lippincott Williams and Wilkins; Baltimore: 2013. ACSM’s Guidelines for Exercise Testing and Prescription.
    1. Ryan R.M., Frederick C.M., Lepes D., Rubio N., Sheldon K.M. Intrinsic motivation and exercise adherence. Int. J. Sport Psychol. 1997;28:335–354.
    1. Chatzisarantis N.L., Hagger M.S. Effects of an intervention based on self-determination theory on self-reported leisure-time physical activity participation. Psychol. Health. 2009;24(1):29–48.
    1. Chatzisarantis N.L., Hagger M.S., Kamarova S., Kawabata M. When effects of the universal psychological need for autonomy on health behaviour extend to a large proportion of individuals: a field experiment. Br. J. Health Psychol. 2012;17(4):785–797.
    1. Watterson J.L., Rodriguez H.P., Shortell S.M., Aguilera A. Improved diabetes care management through a text-message intervention for low-income patients: mixed-methods pilot study. JMIR Diabet. 2018;3(4)
    1. Axley P., Kodali S., Kuo Y.F., Ravi S., Seay T., Parikh N.M., Singal A.K. Text messaging approach improves weight loss in patients with nonalcoholic fatty liver disease: a randomized study. Liver Int. 2018;38(5):924–931.
    1. Weiss C., Ammerman S.D. Designing, implementing and assessing a novel text-messaging intervention for an adolescent mobile health clinic: a collaborative approach. J. Child. Adolesc. Behav. 2016;4:299.
    1. Cheyne K., Smith M., Felter E.M., Orozco M., Steiner E.A., Park Y., Gary-Webb T.L. Food Bank-based diabetes prevention intervention to address food security, dietary intake, and physical activity in a food-insecure cohort at high risk for diabetes. Prev. Chronic Dis. 2020;17
    1. Cotugna N., Vickery C.E., Carpenter-Haefele K.M. Evaluation of literacy level of patient education pages in health-related journals. J. Community Health. 2005;30(3):213–219.
    1. Williamson J.M., Martin A.G. Analysis of patient information leaflets provided by a district general hospital by the Flesch and Flesch-Kincaid method. Int. J. Clin. Pract. 2010;64(13):1824–1831.
    1. King A.C., Sallis J.F., Dunn A.L., Simons-Morton D.G., Albright C.A., Cohen S., Rejeski J., Marcus B.H., Coday M.C. For the activity counseling trial research group: overview of the activity counseling trial (ACT) intervention for promoting physical activity in primary care settings. Med. Sci. Sports Exerc. 1998;30:1086–1096.
    1. Castro C.M., Pruitt L.A., Buman M.P., King A.C. Physical activity program delivery by professionals versus volunteers: the TEAM randomized trial. Health Psychol. 2011;30(3):285–294.
    1. Pahor M., Guralnik J.M., Ambrosius W.T., Blair S., Bonds D.E., Church T.S., Espeland M.A., Fielding R.A., Gill T.M., Groessl E.J. Effect of structured physical activity on prevention of major mobility disability in older adults: the LIFE study randomized clinical trial. JAMA. 2014;311(23):2387–2396.
    1. King A.C., Sallis J.F., Frank L.D., Saelens B.E., Cain K., Conway T.L., Chapman J.E., Ahn D.K., Kerr J. Aging in neighborhoods differing in walkability and income: associations with physical activity and obesity in older adults. Soc. Sci. Med. 2011;73:1525–1533.
    1. Troiano R.P., McClain J.J., Brychta R.J., Chen K.Y. Evolution of accelerometer methods for physical activity research. Br. J. Sports Med. 2014;48(13):1019–1023.
    1. Harada N.D., Chiu V., King A.C., Stewart A.L. An evaluation of three self-report physical activity instruments for older adults. Med. Sci. Sports Exerc. 2001;33:962–970.
    1. Hekler E.B., Buman M.P., Haskell W.L., Conway T.L., Cain K.L., Sallis J.F., Saelens B.E., Frank L.D., Kerr J., King A.C. Reliability and validity of CHAMPS self-reported sedentary to vigorous intensity physical activity in older adults. J. Phys. Act. Health. 2012;9:225–236.
    1. Colbert L.H., Matthews C.E., Havighurst T.C., Kim K., Schoeller D.A. Comparative validity of physical activity measures in older adults. Med. Sci. Sports Exerc. 2011;43(5):867–876.
    1. Piercy K.L., Troiano R.P., Ballard R.M., Carlson S.A., Fulton J.E., Galuska D.A., George S.M., Olson R.D. The physical activity guidelines for Americans. JAMA. 2018;320:2020–2028.
    1. Feito Y., Bassett D.R., Thompson D.L. Evaluation of activity monitors in controlled and free-living environments. Med. Sci. Sports Exerc. 2011;44(4):733–741.
    1. Hart T.L., Swartz A.M., Cashin S.E., Strath S.J. How many days of monitoring predict physical activity and sedentary behaviour in older adults? Int. J. Behav. Nutr. Phys. Act. 2011;8:62–68.
    1. Evenson K.R., Wen F., Metzger J.S., Herring A.H. Physical activity and sedentary behavior patterns using accelerometry from a national sample of United States adults. Int. J. Behav. Nutr. Phys. Act. 2015;12:20.
    1. Evenson K.R., Wen F., Herring A.H. Associations of accelerometry-assessed and self-reported physical activity and sedentary behavior with all-cause and cardiovascular mortality among US adults. Am. J. Epidemiol. 2016;184(9):621–632.
    1. Choi L., Liu Z., Matthews C.E., Buchowski M.S. Validation of accelerometer wear and nonwear time classification algorithm. Med. Sci. Sports Exerc. 2011;43(2):357–364.
    1. Rejeski W.J., Marsh A.P., Brubaker P.H., Buman M., Fielding R.A., Hire D., Manini T., Rego A., Miller M.E., Investigators L.S. Analysis and interpretation of accelerometry data in older adults: the LIFE study. J. Gerontol. A Biol. Sci. Med. Sci. 2016;71(4):521–528.
    1. Copeland J.L., Esliger D.W. Accelerometer assessment of physical activity in active, healthy older adults. J. Aging Phys. Act. 2009;17(1):17–30.
    1. Gardiner P.A., Clark B.K., Healy G.N., Eakin E.G., Winkler E.A.H., Owen N. Measuring older adults’ sedentary time: reliability, validity, and responsiveness. Med. Sci. Sports Exerc. 2011;43(11):2127–2133.
    1. Rikli R.E., Jones C.J. Development and validation of a functional fitness test for community-residing older adults. J. Aging Phys. Act. 1999;7:129–161.
    1. World Health Organization Development of the World Health Organization WHOQOL-BREF quality of life assessment. The WHOQOL group. Psychol. Med. 1998;28(3):551–558.
    1. Skevington S.M., Lotfy M., O’Connell K.A., Group. W The World Health Organization’s WHOQOL-BREF quality of life assessment: psychometric properties and results of the international field trial. A report from the WHOQOL group. Qual. Life Res. 2004;13(2):299–310.
    1. Chrisinger B.W., Gustafson J.A., King A.C., Winter S.J. Understanding where we are well: neighborhood-level social and environmental correlates of well-being in the stanford well for life study. Int. J. Environ. Res. Public Health. 2019:16(10).
    1. Heaney C.A., Avery E.C., Rich T., Ahuja N.J., Winter S.J. Stanford WELL for life: learning what it means to be well. Am. J. Health Promot. 2017;31:449.
    1. Horvath A., Greenberg L. Development and validation of the working alliance inventory. J. Couns. Psychol. 1989;36(2):223–233.
    1. King A.C., Hekler E.B., Castro C.M., Buman M.P., Marcus B.H., Friedman R.H., Napolitano M.A. Exercise advice by humans versus computers: maintenance effects at 18 months. Health Psychol. 2013;33:192–196.
    1. Hekler E.B., Buman M.P., Otten J., Castro C.M., Grieco L., Marcus B., Friedman R.H., Napolitano M.A., King A.C. Determining who responds better to a computer- vs. human-delivered physical activity intervention: results from the community health advice by telephone (CHAT) trial. Int. J. Behav. Nutr. Phys. Act. 2013;10:109–118.
    1. Caplan S.E. Relations samong loneliness, social anxiety, and problematic internet use. CyberPsychol. Behav. 2007;10(2):234–242.
    1. HIgh A.C., Caplan S.E. Social anxiety and computer-mediated communication during initial interactions: implications for the hyperpersonal perspective. Comput. Hum. Behav. 2009;25(2):475–482.
    1. Reid D.J., Reid F.J. Text or talk? Social anxiety, loneliness, and divergent preferences for cell phone use. CyberPsychol. Behav. 2007;10(3):424–435.
    1. Fenigstein A., Scheier M.F., Buss A.H. Public and private self-consciousness: assessment and theory. J. Consult. Clin. Psychol. 1975;43:522–527.
    1. Davis T.C., Long S.W., Jackson R.H., Mayeayx E.J., George R.B., Murphy P.W., Crouch M.A. Rapid estimate of adult literacy in medicine:a shortened screening instrument. Fam. Med. 1993;25(6):391–395.
    1. Lee S.Y.D., Bender D.E., Ruiz R.E., Choi Y.I. Development of an easy-to-use Spanish health literacy test. Health Serv. Res. 2006;41:1392–1412.
    1. Marin G., Sabogal F., Marin B., Otero-Sabogal R., Perez-Stable E. Development of a short acculturation scale for Hispanics. Hisp. J. Behav. Sci. 1987;9:183–205.
    1. Sundquist J., Winkleby M. Country of birth, acculturation status and abdominal obesity in a national sample of Mexican-American women and men. Int. J. Epidemiol. 2000;29(3):470–477.
    1. Brown S.C., Mason C.A., Perrino T., Lombard J.L., Martinez F., Plater-Zyberk E., Spokane A.R., Szapocznik J. Built environment and physical functioning in Hispanic elders: the role of “eyes on the street”. Environ. Health Perspect. 2008;116:1300–1307.
    1. Martinez S.M., Ayala G.X., Patrick K., Arredondo E.M., Roesch S., Elder J. Associated pathways between neighborhood environment, community resource factors, and leisure-time physical activity among Mexican-American adults in San Diego, California. Am. J. Health Promot. 2012;26(5):281–288.
    1. Adams M.A., Ryan S., Kerr J., Sallis J.F., Patrick K., Frank L.D., Norman G.J. Validation of the neighborhood environment walkability scale (NEWS) items using geographic information systems. J. Phys. Act. Health. 2009;6(s1):S113–S123.
    1. Sampson R.J., Raudenbush S.W., Earls F. Neighborhoods and violent crime: a multilevel study of collective efficacy. Science. 1997;277(5328):918–924.
    1. Deci E.L., Ryan R.M. The support of autonomy and the control of behavior. J. Pers. Soc. Psychol. 1987;53(6):1024–1037.
    1. Levesque C.S., Williams G.C., Elliot D., Pickering M.A., Bodenhamer B., Finley P.J. Validating the theoretical structure of the treatment self-regulation questionnaire (TSRQ) across three different health behaviors. Health Educ. Res. 2007;22(5):691–702.
    1. Anderson E.S., Wojcik J.R., Winett R.A., Williams D.M. Social-cognitive determinants of physical activity: the influence of social support, self-efficacy, outcome expectations, and self-regulation among participants in a church-based health promotion study. Health Psychol. 2006;25(4):510–520.
    1. Anderson E.S., Winett R.A., Wojcik J.R., Williams D.M. Social cognitive mediators of change in a group randomized nutrition and physical activity intervention: social support, self-efficacy, outcome expectations and self-regulation in the guide-to-health trial. J. Health Psychol. 2010;15(1):21–32.
    1. Sallis J.F., Grossman R.M., Pinski R.B., Patterson T.L., Nader P.R. The development of scales to measure social support for diet and exercise behaviors. Prev. Med. 1987;16:825–836.
    1. Efron B. Forcing a sequential experiment to be balanced. Biometrika. 1971;58:403–417.
    1. Kraemer H.C., Blasey C. 2nd ed. Sage Publications, Inc.; Los Angeles: 2016. How Many Subjects? Statistical Power Analysis in Research.
    1. Little R.J.A., Rubin D.B. Second ed. John Wiley & Sons; New York: 2002. Statistical Analysis with Missing Data.
    1. SAS Institute Inc . second ed. SAS Institute Inc.; Cary, NC: 2009. SAS/STAT 9.2 User's Guide.
    1. Gibbons R.D., Hedeker D., Waternaux C., Kraemer H.C., Greenhouse J.B. Some conceptual and statistical issues in the analysis of longitudinal psychiatric data. Arch. Gen. Psychiatry. 1993;50:739–750.
    1. Laird N., Lange N., Stram D. Maximum likelihood computations with repeated measures: application. J. Am. Stat. Assoc. 1987;82:97–105.
    1. Tate D.F., Finkelstein E.A., Khavjou O., Gustafson A. Cost effectiveness of internet interventions: review and recommendations. Ann. Behav. Med. 2009;38:40–45.
    1. U.S. Department of Health and Human Services . USDHHS; Washington, DC: 2011. HHS Action plan to Reduce Racial and Ethnic Disparities: A Nation Free of Disparities in Health and Health Care.
    1. Roux L., Pratt M., Tengs TO, Yore M.M., Yanagawa T.L., Van Den Bos J., Rutt C., Brownson R.C., Powell K.E., Heath G. Cost effectiveness of community-based physical activity interventions. Am. J. Prev. Med. 2008;35(6):578–588.
    1. Sevick M.A., Dunn A.L., Morrow M.S., Marcus B.H., Chen G.J., Blair S.N. Cost-effectiveness of lifestyle and structured exercise interventions in sedentary adults: results of project ACTIVE. Am. J. Prev. Med. 2000;19(1):1–8.
    1. King A.C., Campero I., Sheats J.L., Castro Sweet C.M., Garcia D., Chazaro A., Blanco G., Hauser M., Fierros F., Ahn D.K. Testing the comparative effects of physical activity advice by humans vs. computers in underserved populations: the COMPASS trial design, methods, and baseline characteristics. Contemp. Clin. Trials. 2017;61(October):115–125.
    1. Warner K.E., Luce B.R. Health Administration Press; Ann Arbor: 1982. Cost-Benefit and Cost-Effectiveness Analyses in Health Care: Principles, Practice, and Potential.
    1. Thomas K.S., Miller P., Doherty M., Muir K.R., Jones A.C., O’Reilly S.C. Cost-effectiveness of a two-year home exercise program for the treatment of knee pain. Arthritis Rheum. 2005;53(3):388–394.
    1. Kraemer H.C., Wilson G.T., Fairburn C.G., Agras W.S. Mediators and moderators of treatment effects in randomized clinical trials. Arch. Gen. Psychiatry. 2002;59 (887–883)
    1. Rosenthal R., Rosnow R.L. 2nd ed. McGraw-Hill; New York: 1991. Essentials of Behavioral Research: Methods and Data Analysis.
    1. Napolitano M.A., Papandonatos G.D., Lewis B.A., Whiteley J.A., Williams D.M., King A.C., Bock B.C., Pinto B., Marcus B.H. Mediators of physical activity behavior change: a multivariate approach. Health Psychol. 2008;27(4):409–418.
    1. Buman M.P., Hekler E.B., Bliwise D.L., King A.C. Moderators and mediators of exercise-induced objective sleep improvements in midlife and older adults with sleep complaints. Health Psychol. 2011;30(5):579–587.
    1. Baron R.M., Kenny D.A. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J. Pers. Soc. Psychol. 1986;51:1173–1182.
    1. MacKinnon D.P., Fairchild A.J., Fritz M.S. Mediation analysis. Annu. Rev. Psychol. 2007;58:593–614.
    1. Preacher K., Hayes A. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav. Res. Methods. 2008;40:879–891.
    1. Fan J.X., Kowaleski-Jones L., Wen M. Walking or dancing: patterns of physical activity by cross-sectional age among U.S. women. J. Aging Health. 2013;25(7):1182–1203.
    1. Arredondo E.M., Sotres-Alvarez D., Stoutenberg M., Davis S.M., Crespo N.C., Carnethon M.R., Castaneda S.F., Isasi C.R., Espinoza R.A., Daviglus M.L. Physical activity levels in U.S. Latino/Hispanic adults: results from the Hispanic community health study/study of Latinos. Am. J. Prev. Med. 2016;50(4):500–508.
    1. Munoz R.F. Using evidence-based internet interventions to reduce health disparities worldwide. J. Med. Internet Res. 2010;12(5)

Source: PubMed

Sponsors and Collaborators

Medical Conditions

Drug Interventions

3
Subscribe