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Social Determinants of Potential eHealth Engagement Among People Living with HIV Receiving Ryan White Case Management: Health Equity Implications from Project TECH

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Abstract

Objectives

Evaluate the relationships between social characteristics of Floridian persons living with HIV (PLWH) and both use of digital technologies and willingness to use eHealth for HIV-related information.

Methods

Ryan White case managers (N = 155) from 55 agencies in 47 Florida counties administered a survey to PLWH (N = 1268) from June 2016-April 2017. Multilevel logistic regression models were used to identify correlates of technology use and willingness.

Results

Use of mobile phones with text messaging was high (89%). Older (vs. younger) adults and non-Hispanic blacks (vs. whites) were less likely to use most technologies. These groups, along with Hispanics (vs. whites) were less likely to express willingness to use technologies for HIV-related information in models adjusting for use.

Conclusions

Among PLWH in Florida, eHealth-related inequities exist. Willingness to engage in HIV-related eHealth is affected by social determinants, even when considering technology access. Although eHealth may reduce some healthcare inequities, it may exacerbate others.

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References

  1. Navarra A-MD, Gwadz MV, Whittemore R, Bakken SR, Cleland CM, Burleson W, et al. Health technology-enabled interventions for adherence support and retention in care among US HIV-infected adolescents and young adults: an integrative review. AIDS Behav. 2017;21(11):3154–71.

    PubMed  Google Scholar 

  2. Henny KD, Wilkes AL, McDonald CM, Denson DJ, Neumann MS. A rapid review of eHealth interventions addressing the continuum of HIV care (2007-2017). AIDS Behav. 2018;22(1):43–63.

    PubMed  PubMed Central  Google Scholar 

  3. Cooper V, Clatworthy J, Whetham J, Consortium E. mHealth interventions to support self-management in HIV: a systematic review. Open AIDS J. 2017;11:119–32.

    PubMed  Google Scholar 

  4. Bussone A, Stumpf S, Wilson S. The use of online forums by people living with HIV for help in understanding personal health information. Int J Med Inform. 2017;108:64–70.

    PubMed  Google Scholar 

  5. Mo PK, Coulson NS. Are online support groups always beneficial? A qualitative exploration of the empowering and disempowering processes of participation within HIV/AIDS-related online support groups. Int J Nurs Stud. 2014;51(7):983–93.

    PubMed  Google Scholar 

  6. Flickinger TE, DeBolt C, Wispelwey E, Laurence C, Plews-Ogan E, Waldman AL, et al. Content analysis and user characteristics of a smartphone-based online support group for people living with HIV. Telemed J E Health. 2016;22(9):746–54.

    PubMed  Google Scholar 

  7. Marhefka SL, Turner D, Lockhart E, Rivara A, Wang W, Shuter J. Meeting our patients “where they are”: video-group smoking cessation for people living with HIV. J Assoc Nurses AIDS Care. 2018;29(2):338–44.

    PubMed  Google Scholar 

  8. Marhefka SL, Buhi ER, Baldwin J, Chen H, Johnson A, Lynn V, et al. Effectiveness of Healthy Relationships video-group—a videoconferencing group intervention for women living with HIV: preliminary findings from a randomized controlled trial. Telemed J E Health. 2014;20(2):128–34.

    PubMed  PubMed Central  Google Scholar 

  9. Shuter J, Bernstein SL, Moadel AB. Cigarette smoking behaviors and beliefs in persons living with HIV/AIDS. Am J Health Behav. 2012;36(1):75–85.

    PubMed  PubMed Central  Google Scholar 

  10. Cote J, Rouleau G, Godin G, Ramirez-Garcia P, Gueheneuc YG, Nahas G, Tremblay G, Otis J, Hernandez A. Acceptability and feasibility of a virtual intervention to help people living with HIV manage their daily therapies. J Telemed Telecare. 2012;18(7):409–12.

    PubMed  Google Scholar 

  11. Cote J, Godin G, Ramirez-Garcia P, Rouleau G, Bourbonnais A, Gueheneuc YG, Tremblay C, Otis J. Virtual intervention to support self-management of antiretroviral therapy among people living with HIV. J Med Internet Res. 2015;17(1):e6.

    PubMed  PubMed Central  Google Scholar 

  12. Marhefka SL, Fuhrmann HJ, Gilliam P, Lopez B, Baldwin J. Interest in, concerns about, and preferences for potential video-group delivery of an effective behavioral intervention among women living with HIV. AIDS Behav. 2012;16(7):1961–9.

    PubMed  Google Scholar 

  13. Kempf MC, Huang CH, Savage R, Safren SA. Technology-delivered mental health interventions for people living with HIV/AIDS (PLWHA): a review of recent advances. Curr HIV/AIDS Rep. 2015;12(4):472–80.

    PubMed  PubMed Central  Google Scholar 

  14. Green SM, Lockhart E, Marhefka SL. Advantages and disadvantages for receiving Internet-based HIV/AIDS interventions at home or at community-based organizations. AIDS Care. 2015;27(10):1304–8.

    PubMed  PubMed Central  Google Scholar 

  15. Griffiths F, Lindenmeyer A, Powell J, Lowe P, Thorogood M. Why are health care interventions delivered over the internet? A systematic review of the published literature. J Med Internet Res. 2006;8(2):e10.

    PubMed  PubMed Central  Google Scholar 

  16. Ahern DK, Kreslake JM, Phalen JM. What is eHealth: perspectives on the evolution of eHealth research. J Med Internet Res. 2006;8(1):e4.

    PubMed  PubMed Central  Google Scholar 

  17. Ownby RL, Waldrop-Valverde D, Jacobs RJ, Acevedo A, Caballero J. Cost effectiveness of a computer-delivered intervention to improve HIV medication adherence. BMC Med Inform Decis Mak. 2013;13:29.

    PubMed  PubMed Central  Google Scholar 

  18. Glasgow RE, Phillips SM, Sanchez MA. Implementation science approaches for integrating eHealth research into practice and policy. Int J Med Inform. 2014;83(7):e1–11.

    PubMed  Google Scholar 

  19. Balas EA, Boren SA. Managing clinical knowledge for health care improvement. Yearbook Med inform. 2000;9(01):65–70.

    Google Scholar 

  20. Bennett GG, Glasgow RE. The delivery of public health interventions via the Internet: actualizing their potential. Annu Rev Public Health. 2009;30:273–92.

    PubMed  Google Scholar 

  21. Bagot KL, Bladin CF, Vu M, Kim J, Hand PJ, Campbell B, et al. Exploring the benefits of a stroke telemedicine programme: an organisational and societal perspective. J Telemed Telecare. 2016;22(8):489–94.

    PubMed  Google Scholar 

  22. Green LW. Making research relevant: if it is an evidence-based practice, where’s the practice-based evidence? Fam Pract. 2008;25(suppl_1):i20–4.

    PubMed  Google Scholar 

  23. Pew Research Center. Mobile fact sheet. 2018. http://www.pewinternet.org/fact-sheet/mobile/. Accessed 17 Oct 2018.

  24. Pew Research Center. Internet/broadband fact sheet. 2018. Available from: http://www.pewinternet.org/fact-sheet/internet-broadband/. Accessed 17 Oct 2018.

  25. Shacham E, Stamm K, Overton ET. Can you hear me now? Limited use of technology among an urban HIV-infected cohort. AIDS Care. 2009;21(8):1000–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Calvert JK, Aidala AA, West JH. An ecological view of internet health information seeking behavior predictors: findings from the CHAIN study. Open AIDS J. 2013;7:42–6.

    PubMed  PubMed Central  Google Scholar 

  27. Kalichman SC, Benotsch EG, Weinhardt LS, Austin J, Luke W. Internet use among people living with HIV/AIDS: association of health information, health behaviors, and health status. AIDS Educ Prev. 2002;14(1):51–61.

    PubMed  Google Scholar 

  28. Thomas S, Shuter J. Internet access and usage in a sample of inner-city HIV-infected patients. J Assoc Nurses AIDS Care. 2010;21(5):444–8.

    PubMed  Google Scholar 

  29. Mayben JK, Giordano TP. Internet use among low-income persons recently diagnosed with HIV infection. AIDS Care. 2007;19(9):1182–7.

    CAS  PubMed  Google Scholar 

  30. Blackstock OJ, Haughton LJ, Garner RY, Horvath KJ, Norwood C, Cunningham CO. General and health-related Internet use among an urban, community-based sample of HIV-positive women: implications for intervention development. AIDS Care. 2015;27(4):536–44.

    PubMed  Google Scholar 

  31. Saberi P, Johnson MO. Correlation of internet use for health care engagement purposes and HIV clinical outcomes among HIV-positive individuals using online social media. J Health Commun. 2015;20(9):1026–32.

    PubMed  PubMed Central  Google Scholar 

  32. Huff A, Chumbler N, Cherry COB, Hill M. An in-depth mixed-methods approach to Ryan White HIV/AIDS care program comprehensive needs assessment from the Northeast Georgia Public Health District: The significance of patient privacy, psychological health, and social stigma to care. Eval Program Plan. 2015;49:137–48.

    Google Scholar 

  33. Reif S, Golin CE, Smith SR. Barriers to accessing HIV/AIDS care in North Carolina: rural and urban differences. AIDS Care. 2005;17(5):558–65.

    CAS  PubMed  Google Scholar 

  34. Snyder JE, Snyder JE, Jensen M, Nguyen NX, Filice CE. Defining rurality in medicare administrative data. Med Care. 2017;55(12):e164–9.

    PubMed  Google Scholar 

  35. Viswanath K, Kreuter MW. Health disparities, communication inequalities, and eHealth. Am J Prev Med. 2007;32(5):S131–3.

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Glasgow RE. eHealth evaluation and dissemination research. Am J Prev Med. 2007;32(5):S119–26.

    PubMed  Google Scholar 

  37. United States Census Bureau. Quick Facts: Florida. 2018. https://www.census.gov/quickfacts/fl. Accessed 15 Jan 2018.

  38. Sharpe TT, Harrison KM, Dean HD. Summary of CDC consultation to address social determinants of health for prevention of disparities in HIV/AIDS, viral hepatitis, sexually transmitted diseases, and tuberculosis. Public Health Rep. 2010;125(4_suppl):11–5.

    PubMed  PubMed Central  Google Scholar 

  39. U.S. Census Bureau. Computer and Internet Use in the United States: 2016. United States Census Bureau; Accessed 15 Jan 2018.

  40. Williams EC, McFarland LV, Nelson KM. Alcohol consumption among urban, suburban, and rural Veterans Affairs outpatients. J Rural Health. 2012;28(2):202–10.

    PubMed  Google Scholar 

  41. Pew Research Center. Millennials stand out for their technology use, but older generations also embrace digital life. 2018. http://www.pewresearch.org/fact-tank/2018/05/02/millennials-stand-out-for-their-technology-use-but-older-generations-also-embrace-digital-life/. Accessed 5 Feb 2019.

  42. Pew Research Center. Mobile Technology and Home Broadband. 2019. https://www.pewinternet.org/2019/06/13/mobile-technology-and-home-broadband-2019/. Accessed 23 Aug 2019.

  43. Pew Research Center. The Demographics of Device Ownership. 2015. https://www.pewinternet.org/2015/10/29/the-demographics-of-device-ownership/. Accessed 20 Aug 2019.

  44. US Department of Health and Human Services Health Resources and Services Administration HIV/AIDS Bureau. Overview: Ryan White HIV/AIDS Program Clients, 2016. 2018. https://hab.hrsa.gov/sites/default/files/hab/Publications/factsheets/population-factsheet-overview.pdf. Accessed 11 Feb 2019.

  45. US Department of Health and Human Services Health Resources and Services Administration [HRSA]. The Ryan White HIV/AIDS Program Annual Client-Level Data Report. 2018. https://hab.hrsa.gov/sites/default/files/hab/data/datareports/RWHAP-annual-client-level-data-report-2017.pdf. Accessed 11 Feb 2019.

  46. Dowshen N, Kuhns LM, Gray C, Lee S, Garofalo R. Feasibility of interactive text message response (ITR) as a novel, real-time measure of adherence to antiretroviral therapy for HIV + youth. AIDS Behav. 2013;17(6):2237–43.

    PubMed  Google Scholar 

  47. Garofalo R, Kuhns LM, Hotton A, Johnson A, Muldoon A, Rice D. A randomized controlled trial of personalized text message reminders to promote medication adherence among HIV-positive adolescents and young adults. AIDS Behav. 2016;20(5):1049–59.

    PubMed  PubMed Central  Google Scholar 

  48. Mayer JE, Fontelo P. Meta-analysis on the effect of text message reminders for HIV-related compliance. AIDS Care. 2017;29(4):409–17.

    PubMed  Google Scholar 

  49. Moore DJ, Pasipanodya EC, Umlauf A, Rooney AS, Gouaux B, Depp CA, et al. Individualized texting for adherence building (iTAB) for methamphetamine users living with HIV: a pilot randomized clinical trial. Drug Alcohol Depend. 2018;189:154–60.

    PubMed  PubMed Central  Google Scholar 

  50. Reback CJ, Grant DL, Fletcher JB, Branson CM, Shoptaw S, Bowers JR, et al. Text messaging reduces HIV risk behaviors among methamphetamine-using men who have sex with men. AIDS Behav. 2012;16(7):1993–2002.

    PubMed  PubMed Central  Google Scholar 

  51. Ganta V, Moonie S, Patel D, Hunt AT, Richardson J, Di John D, et al. Timely reminder interventions to improve annual Papanicolaou (Pap) smear rates among HIV-infected women in an outpatient center of southern Nevada: a short report. AIDS Care. 2017;29(9):1099–101.

    PubMed  Google Scholar 

  52. Nelson LA, Mulvaney SA, Gebretsadik T, Ho Y-X, Johnson KB, Osborn CY. Disparities in the use of a mHealth medication adherence promotion intervention for low-income adults with type 2 diabetes. J Am Med Inform Assoc. 2015;23(1):12–8.

    PubMed  PubMed Central  Google Scholar 

  53. Person AK, Blain ML, Jiang H, Rasmussen PW, Stout JE. Text messaging for enhancement of testing and treatment for tuberculosis, human immunodeficiency virus, and syphilis: a survey of attitudes toward cellular phones and healthcare. Telemed J E Health. 2011;17(3):189–95.

    PubMed  PubMed Central  Google Scholar 

  54. Martin T. Assessing mHealth: opportunities and barriers to patient engagement. J Health Care Poor Underserved. 2012;23(3):935–41.

    PubMed  Google Scholar 

  55. Smith A. Americans and their cell phones: mobile devices help people solve problems and stave off boredom, but create some new challenges and annoyances. Pew Research Center. 2011;2014:9.

    Google Scholar 

  56. Smith A. Technology trends among people of color. Pew Internet & American Life Project. 2010.

  57. Dolcini MM, Catania JA, Cotto-Negron C, Canchola JA, Warren J, Ashworth C, et al. Challenges in reach with online sexual health information among African American youth: assessing access and engagement. Sex Res Social Policy. 2019;16(1):12–21.

    Google Scholar 

  58. Duncan DT, Park SH, Goedel WC, Sheehan DM, Regan SD, Chaix B. Acceptability of smartphone applications for global positioning system (GPS) and ecological momentary assessment (EMA) research among sexual minority men. PLoS ONE. 2019;14(1):e0210240.

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Zhang X, Han X, Dang Y, Meng F, Guo X, Lin J. User acceptance of mobile health services from users’ perspectives: the role of self-efficacy and response-efficacy in technology acceptance. Inform Health Soc Care. 2017;42(2):194–206.

    PubMed  Google Scholar 

  60. Maiorana A, Steward WT, Koester KA, Pearson C, Shade SB, Chakravarty D, et al. Trust, confidentiality, and the acceptability of sharing HIV-related patient data: lessons learned from a mixed methods study about Health Information Exchanges. Implement Sci. 2012;7(1):34.

    PubMed  PubMed Central  Google Scholar 

  61. Rudolph AE, Young AM, Havens JR. Privacy, confidentiality, and safety considerations for conducting geographic momentary assessment studies among persons who use drugs and men who have sex with men. J Urban Health. 2018. https://doi.org/10.1007/s11524-018-0315-x.

    Article  PubMed Central  Google Scholar 

  62. Rudolph AE, Young AM, Havens JR. A rural/urban comparison of privacy and confidentiality concerns associated with providing sensitive location information in epidemiologic research involving persons who use drugs. Addict Behav. 2017;74:106–11.

    PubMed  PubMed Central  Google Scholar 

  63. Emlet CA. “You’re awfully old to have this disease”: experiences of stigma and ageism in adults 50 years and older living with HIV/AIDS. Gerontologist. 2006;46(6):781–90.

    PubMed  Google Scholar 

  64. Sangaramoorthy T, Jamison AM, Dyer TV. HIV stigma, retention in care, and adherence among older black women living with HIV. J Assoc Nurses AIDS Care. 2017;28(4):518–31.

    PubMed  Google Scholar 

  65. Earnshaw VA, Bogart LM, Dovidio JF, Williams DR. Stigma and racial/ethnic HIV disparities: moving toward resilience. Am Psychol. 2013;68(4):225–36.

    PubMed  PubMed Central  Google Scholar 

  66. Travaglini LE, Himelhoch SS, Fang LJ. HIV stigma and its relation to mental, physical and social health among black women living with HIV/AIDS. AIDS Behav. 2018;22(12):3783–94.

    PubMed  Google Scholar 

  67. Centers for Disease Control and Prevention. HIV in the United States by Geography. 2018. https://www.cdc.gov/hiv/statistics/overview/geographicdistribution.html. Accessed 30 Oct 2018.

  68. Pellowski JA. Barriers to care for rural people living with HIV: a review of domestic research and health care models. J Assoc Nurses AIDS Care. 2013;24(5):422–37.

    PubMed  PubMed Central  Google Scholar 

  69. Hubach RD, Dodge B, Schick V, Ramos WD, Herbenick D, Li MJ, et al. Experiences of HIV-positive gay, bisexual and other men who have sex with men residing in relatively rural areas. Cult Health Sex. 2015;17(7):795–809.

    PubMed  Google Scholar 

  70. Kalichman S, Katner H, Banas E, Kalichman M. Population density and AIDS-related stigma in large-urban, small-urban, and rural communities of the southeastern USA. Prev Sci. 2017;18(5):517–25.

    PubMed  PubMed Central  Google Scholar 

  71. Costelloe S, Kemppainen J, Brion J, MacKain S, Reid P, Frampton A, et al. Impact of anxiety and depressive symptoms on perceptions of stigma in persons living with HIV disease in rural versus urban North Carolina. AIDS Care. 2015;27(12):1425–8.

    PubMed  Google Scholar 

  72. Inagami S, Gao S, Karimi H, Shendge MM, Probst JC, Stone RA. Adapting the Index of Relative Rurality (IRR) to estimate rurality at the ZIP code level: a rural classification system in health services research. J Rural Health. 2016;32(2):219–27.

    PubMed  Google Scholar 

  73. Cohen SA, Kelley L, Bell AE. Spatiotemporal discordance in five common measures of rurality for US counties and applications for health disparities research in older adults. Front Public Health. 2015;3:267.

    PubMed  PubMed Central  Google Scholar 

  74. Waldorf B, Kim A, editors. Defining and measuring rurality in the US: From typologies to continuous indices. Commissioned paper presented at the Workshop on Rationalizing Rural Area Classifications, Washington, DC; 2015.

  75. Beynon MJ, Crawley A, Munday M. Measuring and understanding the differences between urban and rural areas. Environ Plan B. 2016;43(6):1136–54.

    Google Scholar 

  76. Elliot AJ, Mooney CJ, Douthit KZ, Lynch MF. Predictors of older adults’ technology use and its relationship to depressive symptoms and well-being. J Gerontol B. 2013;69(5):667–77.

    Google Scholar 

  77. Federal Communications Commission. Lifeline Program for Low-Income Consumers. 2019. https://www.fcc.gov/general/lifeline-program-low-income-consumers. Accessed 10 Mar 2019.

  78. Eisinger RW, Dieffenbach CW, Fauci AS. HIV viral load and transmissibility of HIV infection: undetectable equals untransmittable. JAMA. 2019;321(5):451–2.

    PubMed  Google Scholar 

  79. Hasin DS, Aharonovich E, Oleary A, Greenstein E, Pavlicova M, Arunajadai S, et al. Reducing heavy drinking in HIV primary care: A randomized trial of brief intervention, with and without technological enhancement. Addiction. 2013;108(7):1230–40.

    PubMed  PubMed Central  Google Scholar 

  80. Haberer JE, Kiwanuka J, Nansera D, Muzoora C, Hunt PW, So J, et al. Real-time adherence monitoring of antiretroviral therapy among HIV-infected adults and children in rural Uganda. AIDS. 2013;27(13):2166–8.

    PubMed  Google Scholar 

  81. Tucker JA, Blum ER, Xie L, Roth DL, Simpson CA. Interactive voice response self-monitoring to assess risk behaviors in rural substance users living with HIV/AIDS. AIDS Behav. 2012;16(2):432–40.

    PubMed  PubMed Central  Google Scholar 

  82. Saberi P, Yuan P, John M, Sheon N, Johnson MO. A pilot study to engage and counsel HIV-positive African American youth via telehealth technology. AIDS Patient Care STDS. 2013;27(9):529–32.

    PubMed  PubMed Central  Google Scholar 

  83. Marhefka S, Turner D, Lockhart E. Understanding women’s willingness to use ehealth for HIV-related services: a novel application of the Technology Readiness and Acceptance Model to highly stigmatized medical condition. Telemed J E Health. 2019;25(6):511–8.

    PubMed  Google Scholar 

  84. Rosen RK, McGarrity LA, Salmoirago-Blotcher E, Rich C, Rana A, Carey MP. Telephone-delivered mindfulness training for people living with HIV: a qualitative 360° inquiry. AIDS Behav. 2017;21(11):3194–201.

    PubMed  PubMed Central  Google Scholar 

  85. Himelhoch S, Medoff D, Maxfield J, Dihmes S, Dixon L, Robinson C, et al. Telephone based cognitive behavioral therapy targeting major depression among urban dwelling, low income people living with HIV/AIDS: results of a randomized controlled trial. AIDS Behav. 2013;17(8):2756–64.

    PubMed  Google Scholar 

  86. Gentry S, van-Velthoven MH, Car LT, Car J. Telephone delivered interventions for reducing morbidity and mortality in people with HIV infection. Cochrane Database Syst Rev. 2013;2013(5):CD009189.

    PubMed Central  Google Scholar 

  87. Glueckauf RL, Davis WS, Willis F, Sharma D, Gustafson DJ, Hayes J, et al. Telephone-based, cognitive-behavioral therapy for African American dementia caregivers with depression: initial findings. Rehabil Psychol. 2012;57(2):1.

    Google Scholar 

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Acknowledgements

This project was funded by NIH Award # 5R21MH108468-02, Research Towards Implementing Technology-Based Prevention with Positives.

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Authors and Affiliations

  1. College of Public Health, University of South Florida, 13201 Bruce B. Downs Blvd., MDC 56, Tampa, FL, 33612, USA

    Stephanie L. Marhefka, Elizabeth Lockhart, DeAnne Turner, Wei Wang & Regina Maria Roig-Romero

  2. Centre for Addiction and Mental Health (CAMH), Toronto, Canada

    Wei Wang

  3. Hallie E. Ford Center for Healthy Children and Families, College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA

    M. Margaret Dolcini

  4. Department of Health Sciences, Northern Arizona University, Flagstaff, AZ, USA

    Julie A. Baldwin

  5. Department of Mental Health Law & Policy, College of Behavioral & Community Sciences, University of South Florida, Tampa, FL, 33612, USA

    Celia M. Lescano

  6. Department of Behavioral Sciences & Social Medicine, College of Medicine Florida State University, Florida State University, Tallahassee, FL, USA

    Robert L. Glueckauf

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  1. Stephanie L. Marhefka
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  2. Elizabeth Lockhart
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Correspondence to Stephanie L. Marhefka.

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Marhefka, S.L., Lockhart, E., Turner, D. et al. Social Determinants of Potential eHealth Engagement Among People Living with HIV Receiving Ryan White Case Management: Health Equity Implications from Project TECH. AIDS Behav 24, 1463–1475 (2020). https://doi.org/10.1007/s10461-019-02723-1

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