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Intensity of Social Support Matters: A Latent Class Analysis to Identify Levels of Social Support Associated with Optimal Health Outcomes Among Women Living with HIV

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Abstract

Social support is associated with improved HIV care and quality of life. We utilized latent class analysis to identify three classes of baseline emotional and tangible perceived social support, termed “Strong”, “Wavering” and “Weak”. “Weak” vs. “Strong” perceived social support was associated over time with an 8% decreased risk of optimal antiretroviral therapy (ART) adherence for emotional and 6% decreased risk for tangible perceived social support. Importantly, “Wavering” vs “Strong” social support also showed a decreased risk of ART adherence of 6% for emotional and 3% for tangible support. “Strong” vs. “Weak” perceived support had a similar association with undetectable viral load, but the association for “Strong” vs. “Wavering” support was not statistically significant. Intensity of social support is associated with HIV care outcomes, and strong social support may be needed for some individuals. It is important to quantify the level or intensity of social support that is needed to optimize HIV outcomes.

Resumen

El apoyo social está asociado con una mejor atención y calidad de vida del virus de inmunodeficiencia humana (VIH). Utilizamos el análisis de clase latente para identificar tres clases de apoyo social percibido emocional y tangible de referencia, denominado "fuerte", "vacilante" y "débil". El apoyo social percibido “débil” versus el “fuerte” se asoció con el tiempo con una disminución del 8% en el riesgo de una adherencia óptima al terapia antirretroviral (TAR) para el apoyo emocional y del 6% en el riesgo de un apoyo social percibido tangible. Es importante destacar que el apoyo social "vacilante" frente a "fuerte" también mostró una disminución del riesgo de adherencia al TAR del 6% para el apoyo emocional y del 3% para el apoyo tangible. El apoyo percibido "fuerte" frente a "débil" tuvo una asociación similar con una carga viral indetectable, pero la asociación entre el apoyo "fuerte" y el apoyo "vacilante" no fue estadísticamente significativa. La intensidad del apoyo social está asociada con los resultados de la atención del VIH, y algunas personas pueden necesitar un fuerte apoyo social. Es importante cuantificar el nivel o la intensidad del apoyo social que se necesita para optimizar los resultados del VIH.

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References

  1. Harandi TF, Taghinasab MM, Nayeri TD. The correlation of social support with mental health: a meta-analysis. Electron Phys. 2017;9(9):5212–22.

    Google Scholar 

  2. Lee S, Chung JE, Park N. Network environments and well-being: an examination of personal network structure, social capital, and perceived social support. Health Commun. 2018;33(1):22–31.

    PubMed  Google Scholar 

  3. Uchino BN, Bowen K, Kent de Grey RG, Mikel J, Fisher EB. Social support and physical health: models, mechanisms, and opportunities. In: Fisher E, editor. Principles and concepts of behavioral medicine. New York, NY: Springer; 2018. p. 341–72.

    Google Scholar 

  4. Lambert CC, Westfall A, Modi R, Amico RK, Golin C, Keruly J. HIV-related stigma, depression, and social support are associated with health-related quality of life among patients newly entering HIV Care. AIDS Care. 2020;32(6):681–8.

    Google Scholar 

  5. Kalichman SC, DiMarco M, Austin J, Luke W, DiFonzo K. Stress, social support, and HIV-status disclosure to family and friends among HIV-positive men and women. J Behav Med. 2003;26(4):315–32.

    PubMed  Google Scholar 

  6. Friedman MR, Coulter RW, Silvestre AJ, Stall R, Teplin L, Shoptaw S, et al. Someone to count on: social support as an effect modifier of viral load suppression in a prospective cohort study. AIDS Care. 2017;29(4):469–80.

    PubMed  Google Scholar 

  7. Mi T, Li X, Zhou G, Qiao S, Shen Z, Zhou Y. HIV disclosure to family members and medication adherence: role of social support and self-efficacy. AIDS Behav. 2020;24(1):45–54.

    PubMed  Google Scholar 

  8. Chandran A, Benning L, Musci RJ, Wilson TE, Milam J, Adedimeji A, et al. The longitudinal association between social support on HIV medication adherence and healthcare utilization in the women’s interagency HIV study. AIDS Behav. 2019;23(8):2014–24.

    PubMed  PubMed Central  Google Scholar 

  9. Wills TA. Social support and interpersonal relationships. In: Clark MS, editor. Prosocial behavior. Thousand Oaks, CA: SAGE; 1991. p. 265–89.

    Google Scholar 

  10. Taylor SE. Social support: a review. In: Friedman MS, editor. The handbook of health psychology. New York, NY: Oxford University Press; 2011. p. 189–214.

    Google Scholar 

  11. Wilson JM, Weiss A, Shook NJ. Mindfulness, self-compassion, and savoring: factors that explain the relation between perceived social support and well-being. Personal Individ Differ. 2020;152:1–9.

    Google Scholar 

  12. Feeney BC, Collins NL. New look at social support: a theoretical perspective on thriving through relationships. Personal Soc Psychol Rev. 2015;19(2):113–47.

    Google Scholar 

  13. Pillemer SC, Holtzer R. The differential relationships of dimensions of perceived social support with cognitive function among older adults. Aging Ment Health. 2016;20(7):727–35.

    PubMed  Google Scholar 

  14. Drogomyretska K, Fox R, Colbert D. Brief Report: stress and perceived social support in parents of children with ASD. J Autism and Dev Disord. 2020;50:4176.

    Google Scholar 

  15. Simoni JM, Frick PA, Huang B. A longitudinal evaluation of a social support model of medication adherence among HIV-positive men and women on antiretroviral therapy. Health Psychol. 2006;25(1):74–81.

    PubMed  PubMed Central  Google Scholar 

  16. Rogers E, Polonijo AN, Carpiano RM. Getting by with a little help from friends and colleagues: testing how residents’ social support networks affect loneliness and burnout. Can Fam Physician. 2016;62(11):e677–83.

    PubMed  Google Scholar 

  17. Lee CY, Goldstein SE. Loneliness, stress, and social support in young adulthood: does the source of support matter? J Youth Adolesc. 2016;45(3):568–80.

    PubMed  Google Scholar 

  18. Bekele T, Rourke SB, Tucker R, Greene S, Sobota M, Koornstra J, et al. Direct and indirect effects of perceived social support on health-related quality of life in persons living with HIV/AIDS. AIDS Care. 2013;25(3):337–46.

    PubMed  Google Scholar 

  19. Wright KB. Communication in health-related online social support groups/communities: a review of research on predictors of participation, applications of social support theory, and health outcomes. Rev Commun Res. 2016;4:65–87.

    Google Scholar 

  20. Ogbe E, Harmon S, Van den Bergh R, Degomme O. A systematic review of intimate partner violence interventions focused on improving social support and/ mental health outcomes of survivors. PLoS ONE. 2020;15(6):e0235177.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Young SD, Koussa M, Lee SJ, Perez H, Gill N, Gelberg L, et al. Feasibility of a social media/online community support group intervention among chronic pain patients on opioid therapy. J Addict Dis. 2018;37(1–2):96–101.

    PubMed  Google Scholar 

  22. Lee EJ, Cho E. When using facebook to avoid isolation reduces perceived social support. Cyberpsychol Behav Soc Netw. 2018;21(1):32–9.

    PubMed  Google Scholar 

  23. Bloom RD, Reblin M, Chou WS, Beck SL, Wilson A, Ellington L. Online social support for cancer caregivers: alignment between requests and offers on CaringBridge. J Psychosoc Oncol. 2021. https://doi.org/10.1080/07347332.2020.1806174.

    Article  PubMed  Google Scholar 

  24. Hakulinen C, Pulkki-Raback L, Jokela M, Ferrie JE, Aalto AM, Virtanen M, et al. Structural and functional aspects of social support as predictors of mental and physical health trajectories: Whitehall II cohort study. J Epidemiol Community Health. 2016;70(7):710–5.

    PubMed  Google Scholar 

  25. Spohr SA, Suzuki S, Marshall B, Taxman FS, Walters ST. Social support quality and availability affects risk behaviors in offenders. Health Justice. 2016;4:2.

    PubMed  PubMed Central  Google Scholar 

  26. Lloyd GR, Hoffman SA, Welch WA, Blanch-Hartigan D, Gavin KL, Cottrell A, et al. Breast cancer survivors’ preferences for social support features in technology-supported physical activity interventions: findings from a mixed methods evaluation. Transl Behav Med. 2020;10(2):423–34.

    PubMed  Google Scholar 

  27. Santos LM, Amorim LD, Santos DN, Barreto ML. Measuring the level of social support using latent class analysis. Soc Sci Res. 2015;50:139–46.

    PubMed  Google Scholar 

  28. Collins LM, Lanza ST. Latent class and latent transition analysis: with applications in the social, behavioral and health sciences. New York, NY: John Wiley & Sons, Inc.; 2009. p. 330.

    Google Scholar 

  29. Schaecher KL. The importance of treatment adherence in HIV. Am J Manag Care. 2013;19(12 Suppl):s231–7.

    PubMed  Google Scholar 

  30. Adimora AA, Ramirez C, Benning L, Greenblatt RM, Kempf MC, Tien PC, et al. Cohort profile: the women’s interagency HIV study (WIHS). Int J Epidemiol. 2018;47(2):393–4.

    PubMed  PubMed Central  Google Scholar 

  31. Sherbourne CD, Stewart AL. The MOS social support survey. Soc Sci Med. 1991;32(6):705–14.

    CAS  PubMed  Google Scholar 

  32. Altice F, Evuarherhe O, Shina S, Carter G, Beaubrun AC. Adherence to HIV treatment regimens: systematic literature review and meta-analysis. Patient Prefer Adherence. 2019;13:475–90.

    PubMed  PubMed Central  Google Scholar 

  33. Calabrese SK, Mayer KH. Providers should discuss U=U with all patients living with HIV. Lancet HIV. 2019;6(4):e211–3.

    PubMed  Google Scholar 

  34. Okoli C, Van de Velde N, Richman B, Allan B, Castellanos E, Young B, et al. Undetectable equals untransmittable (U = U): awareness and associations with health outcomes among people living with HIV in 25 countries. Sex Transm Infect. 2020. https://doi.org/10.1136/sextrans-2020-054551.

    Article  PubMed  Google Scholar 

  35. Radloff L. The CES-D scale: a self-reported depression scale for research in the general population. Appl Psychol Meas. 1977;1(3):385–401.

    Google Scholar 

  36. Linden-Carmichael AN, Vasilenko SA, Lanza ST, Maggs JL. High-intensity drinking versus heavy episodic drinking: prevalence rates and relative odds of alcohol use disorder across adulthood. Alcohol Clin Exp Res. 2017;41(10):1754–9.

    PubMed  PubMed Central  Google Scholar 

  37. Mack KA, Jones CM, Ballesteros MF. Illicit drug use, illicit drug use disorders, and drug overdose deaths in metropolitan and nonmetropolitan areas—United States. MMWR Surveill Summ. 2017;66(19):1–12.

    PubMed  PubMed Central  Google Scholar 

  38. Krieger N. Stormy weather: race, gene expression, and the science of health disparities. Am J Public Health. 2005;95(12):2155–60.

    PubMed  PubMed Central  Google Scholar 

  39. Chen W, Qian L, Shi J, Franklin M. Comparing performance between log-binomial and robust Poisson regression models for estimating risk ratios under model misspecification. BMC Med Res Methodol. 2018;18(1):63–75.

    PubMed  PubMed Central  Google Scholar 

  40. Hansell PS, Hughes CB, Caliandro G, Russo P, Budin WC, Hartman B, et al. The effect of a social support boosting intervention on stress, coping, and social support in caregivers of children with HIV/AIDS. Nurs Res. 1998;47(2):79–86.

    CAS  PubMed  Google Scholar 

  41. Simoni JM, Pantalone DW, Plummer MD, Huang B. A randomized controlled trial of a peer support intervention targeting antiretroviral medication adherence and depressive symptomatology in HIV-positive men and women. Health Psychol. 2007;26(4):488–95.

    PubMed  PubMed Central  Google Scholar 

  42. Beres LK, Narasimhan M, Robinson J, Welbourn A, Kennedy CE. Non-specialist psychosocial support interventions for women living with HIV: a systematic review. AIDS Care. 2017;29(9):1079–87.

    PubMed  PubMed Central  Google Scholar 

  43. Genberg BL, Shangani S, Sabatino K, Rachlis B, Wachira J, Braitstein P, et al. Improving engagement in the HIV care cascade: a systematic review of interventions involving people living with HIV/AIDS as peers. AIDS Behav. 2016;20(10):2452–63.

    PubMed  PubMed Central  Google Scholar 

  44. Macdonald V, Verster A, Baggaley R. A call for differentiated approaches to delivering HIV services to key populations. J Int AIDS Soc. 2017;20(Suppl 4):21658.

    PubMed  PubMed Central  Google Scholar 

  45. Nagin DS. Group-based modeling of development. Cambridge, MA: Harvard University Press; 2005. p. 214.

    Google Scholar 

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Funding

Data in this manuscript were collected by the Women’s Interagency HIV Study (U01-HL146193), now the MACS/WIHS Combined Cohort Study (MWCCS). We acknowledge the time and effort of all participating women and their families. The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health (NIH). MWCCS (Principal Investigators): Atlanta CRS (Ighovwerha Ofotokun, Anandi Sheth, and Gina Wingood), U01-HL146241; Bronx CRS (Kathryn Anastos and Anjali Sharma), U01-HL146204; Brooklyn CRS (Deborah Gustafson and Tracey Wilson), U01-HL146202; Data Analysis and Coordination Center (Gypsyamber D’Souza, Stephen Gange and Elizabeth Golub), U01-HL146193; Chicago-Cook County CRS (Mardge Cohen and Audrey French), U01-HL146245; Northern California CRS (Bradley Aouizerat, Jennifer Price, and Phyllis Tien), U01-HL146242; Metropolitan Washington CRS (Seble Kassaye and Daniel Merenstein), U01-HL146205; Miami CRS (Maria Alcaide, Margaret Fischl, and Deborah Jones), U01-HL146203; UAB-MS CRS (Mirjam-Colette Kempf, Jodie Dionne-Odom, and Deborah Konkle-Parker), U01-HL146192; UNC CRS (Adaora Adimora), U01-HL146194. The MWCCS is funded primarily by the National Heart, Lung, and Blood Institute (NHLBI), with additional co-funding from the Eunice Kennedy Shriver National Institute Of Child Health & Human Development (NICHD), National Institute On Aging (NIA), National Institute Of Dental & Craniofacial Research (NIDCR), National Institute Of Allergy And Infectious Diseases (NIAID), National Institute Of Neurological Disorders And Stroke (NINDS), National Institute Of Mental Health (NIMH), National Institute On Drug Abuse (NIDA), National Institute Of Nursing Research (NINR), National Cancer Institute (NCI), National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institute on Deafness and Other Communication Disorders (NIDCD), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute on Minority Health and Health Disparities (NIMHD), and in coordination and alignment with the research priorities of the National Institutes of Health, Office of AIDS Research (OAR). MWCCS data collection is also supported by UL1-TR000004 (UCSF CTSA), P30-AI-050409 (Atlanta CFAR), P30-AI-050410 (UNC CFAR), and P30-AI-027767 (UAB CFAR).

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Authors and Affiliations

  1. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Suite W6501, Baltimore, MD, 21205, USA

    Aruna Chandran & Fiona Bhondoekhan

  2. Department of Community Health Sciences, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, USA

    Tracey E. Wilson

  3. Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA

    Joel Milam

  4. Cook County Health and Hospital System, Chicago, IL, USA

    Mardge H. Cohen

  5. Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Adaora A. Adimora

  6. Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA

    Adebola Adedimeji

  7. Department of Clinical Pharmacy, University of California, San Francisco, San Francisco, CA, USA

    Jennifer Cocohoba

  8. Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA

    Carrigan Parish

  9. Nell Hodgson Woodruff School of Nursing, Atlanta, GA, USA

    Marcia Holstad

  10. Department of Medicine/Infectious Diseases, Georgetown University, Washington, DC, USA

    Seble Kassaye

  11. Schools of Nursing, Public Health and Medicine, University of Alabama at Birmingham, Birmingham, AL, USA

    Mirjam-Colette Kempf

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  1. Aruna Chandran
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  2. Fiona Bhondoekhan
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Correspondence to Aruna Chandran.

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Conflict of interest

Dr. Adimora has received consulting fees from Merck & Co., ViiV Healthcare, and Gilead Sciences. The remaining authors have no conflicts of interest to report.

Ethical Approval

Approval was obtained from the institutional review boards of each site’s host institution as well as the WIHS executive committee. The procedures used in this study adhere to the tenets of the Declaration of Helsinki.

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Informed consent was obtained from all individual participants included in the study.

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Chandran, A., Bhondoekhan, F., Wilson, T.E. et al. Intensity of Social Support Matters: A Latent Class Analysis to Identify Levels of Social Support Associated with Optimal Health Outcomes Among Women Living with HIV. AIDS Behav 26, 243–251 (2022). https://doi.org/10.1007/s10461-021-03377-8

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