Skip to main content

Advertisement

SpringerLink
Log in

Structural Network Position and Performance of Health Leaders Within an HIV Prevention Trial

  • Original Paper
  • Published:
AIDS and Behavior Aims and scope Submit manuscript

Abstract

The effectiveness of peer leaders in promoting health may depend on the position they occupy within their social networks. Using sociocentric (whole network) and behavioral data from the intervention arm of a cluster-randomized HIV prevention trial in Dar es Salaam, Tanzania, we used generalized linear models with standardized predictors to examine the association between heath leaders’ baseline structural network position (i.e., in-degree and betweenness centrality) and their 12-month self-reported (1) confidence in educating network members about HIV and gender-based violence (GBV) and (2) number of past-week conversations about HIV and GBV. As in-degree centrality increased, leaders reported fewer HIV-related conversations. As betweenness centrality increased, leaders reported greater number of conversations about GBV. Network position was not significantly associated with confidence in discussing either topic. Our results suggest that peer leaders who occupy spaces between sub-groups of network members may be more effective in engaging their peers in sensitive or controversial topics like GBV than more popular peer leaders.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Yamanis TJ, Dervisevic E, Mulawa M, et al. Social network influence on HIV testing among urban men in tanzania. AIDS Behav. 2017;21(4):1171–82.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Mulawa M, Yamanis TJ, Balvanz P, Kajula LJ, Maman S. Comparing perceptions with actual reports of close friend’s HIV testing behavior among urban tanzanian men. AIDS Behav. 2016;20(9):2014–22.

    Article  PubMed  PubMed Central  Google Scholar 

  3. De P, Cox J, Boivin JF, Platt RW, Jolly AM. The importance of social networks in their association to drug equipment sharing among injection drug users: a review. Addiction. 2007;102(11):1730–9.

    Article  PubMed  Google Scholar 

  4. Latkin CA, Kuramoto SJ, Davey-Rothwell MA, Tobin KE. Social norms, social networks, and HIV risk behavior among injection drug users. AIDS Behav. 2010;14(5):1159–68.

    Article  PubMed  CAS  Google Scholar 

  5. Sentse M, Dijkstra JK, Salmivalli C, Cillessen AH. The dynamics of friendships and victimization in adolescence: a longitudinal social network perspective. Aggress Behav. 2013;39(3):229–38.

    Article  PubMed  Google Scholar 

  6. Mulawa MI, Reyes HLM, Foshee VA, et al. Associations between peer network gender norms and the perpetration of intimate partner violence among urban tanzanian men: a multilevel analysis. Prev Sci. 2018;19(4):427–36.

    Article  PubMed  Google Scholar 

  7. Tieu HV, Liu TY, Hussen S, et al. Sexual networks and HIV risk among black men who have sex with men in 6 U.S. Cities. PLoS ONE. 2015;10(8):e0134085.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  8. Fearon E, Wiggins RD, Pettifor AE, Hargreaves JR. Is the sexual behaviour of young people in sub-saharan africa influenced by their peers? A systematic review. Soc Sci Med. 2015;146:62–74.

    Article  PubMed  Google Scholar 

  9. Yamanis TJ, Fisher JC, Moody JW, Kajula LJ. Young men’s social network characteristics and associations with sexual partnership concurrency in tanzania. AIDS Behav. 2016;20(6):1244–55.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Ghosh D, Krishnan A, Gibson B, Brown SE, Latkin CA, Altice FL. Social network strategies to address HIV prevention and treatment continuum of care among at-risk and HIV-infected substance users: a systematic scoping review. AIDS Behav. 2017;21(4):1183–207.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Simoni JM, Nelson KM, Franks JC, Yard SS, Lehavot K. Are peer interventions for HIV efficacious? A systematic review. AIDS Behav. 2011;15(8):1589–95.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Medley A, Kennedy C, O’Reilly K, Sweat M. Effectiveness of peer education interventions for HIV prevention in developing countries: a systematic review and meta-analysis. AIDS Educ Prev. 2009;21(3):181–206.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Valente TW, Pumpuang P. Identifying opinion leaders to promote behavior change. Health Educ Behav. 2007;34(6):881–96.

    Article  PubMed  Google Scholar 

  14. Valente TW. Opinion leader interventions in social networks. BMJ. 2006;333(7578):1082–3.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Kelly JA, St Lawrence JS, Diaz YE, et al. HIV risk behavior reduction following intervention with key opinion leaders of population: an experimental analysis. Am J Public Health. 1991;81(2):168–71.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Rogers EM. Diffusion of innovations. New York: Free Press; 1995.

    Google Scholar 

  17. Group NCHSPT. The community popular opinion leader HIV prevention programme: conceptual basis and intervention procedures. AIDS. 2007;21(Suppl 2):S59–68.

    Article  Google Scholar 

  18. Kelly JA, Murphy DA, Sikkema KJ, et al. Randomised, controlled, community-level HIV-prevention intervention for sexual-risk behaviour among homosexual men in us cities. Community HIV prevention research collaborative. Lancet. 1997;350(9090):1500–5.

    Article  PubMed  CAS  Google Scholar 

  19. Sikkema KJ, Kelly JA, Winett RA, et al. Outcomes of a randomized community-level HIV prevention intervention for women living in 18 low-income housing developments. Am J Public Health. 2000;90(1):57–63.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Group NCHSPT. Results of the nimh collaborative HIV/sexually transmitted disease prevention trial of a community popular opinion leader intervention. J Acquir Immune Defic Syndr. 2010;54(2):204–14.

    Google Scholar 

  21. Rotheram-Borus MJ, Wu Z, Liang LJ, et al. Reductions in sexually transmitted infections associated with popular opinion leaders in china in a randomised controlled trial. Sex Transm Infect. 2011;87(4):337–43.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Young SD, Konda K, Caceres C, et al. Effect of a community popular opinion leader HIV/STI intervention on stigma in urban, coastal peru. AIDS Behav. 2011;15(5):930–7.

    Article  PubMed  Google Scholar 

  23. Li L, Wu Z, Liang LJ, et al. Reducing HIV-related stigma in health care settings: a randomized controlled trial in china. Am J Public Health. 2013;103(2):286–92.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Young SD, Cumberland WG, Nianogo R, Menacho LA, Galea JT, Coates T. The hope social media intervention for global HIV prevention in Peru: a cluster randomised controlled trial. The lancet HIV. 2015;2(1):e27–32.

    Article  PubMed  Google Scholar 

  25. Schneider JA, Zhou AN, Laumann EO. A new HIV prevention network approach: sociometric peer change agent selection. Soc Sci Med. 2015;125:192–202.

    Article  PubMed  Google Scholar 

  26. Valente TW, Fujimoto K. Bridging: locating critical connectors in a network. Soc Netw. 2010;32(3):212–20.

    Article  Google Scholar 

  27. Becker MH. Sociometric location and innovativeness: reformulation and extension of the diffusion model. Am Sociol Rev. 1970;35:267–82.

    Article  Google Scholar 

  28. Statistics for development (Internet). 2012. [cited May 6, 2015]. http://www.nbs.go.tz/nbs/index.php?option=com_content&view=article&id=597:population-distribution-by-enumeration-area-as-per-2002-population-and-housing-census&catid=57:censuses&Itemid=82.

  29. Fleischman J. Gender-based violence and HIV: Emerging lessons from the pepfar initiative in Tanzania. Center for strategic and international studies. 2012.

  30. Tanzania Commission for AIDS (TACAIDS) ZACZ, National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS), and ICF International. Tanzania HIV/AIDS and malaria indicator survey 2011-12. Dar es Salaam, Tanzania: TACAIDS, ZAC, NBS, OCGS, and ICF International.; 2013.

  31. MoHCDGEC MoH NBS OCGS and ICF. Tanzania demographic and health survey and malaria indicator survey 2015-2016. Dar es Salaam, Tanzania, and Rockville, Maryland, USA: MoHCDGEC, MoH, NBS, OCGS, and ICF; 2016.

  32. Kajula L, Balvanz P, Kilonzo MN, et al. Vijana vijiweni ii: a cluster-randomized trial to evaluate the efficacy of a microfinance and peer health leadership intervention for HIV and intimate partner violence prevention among social networks of young men in Dar es Salaam. BMC Public Health. 2016;16:113.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Maman S, Kajula L, Balvanz P, Kilonzo M, Mulawa M, Yamanis T. Leveraging strong social ties among young men in Dar es Salaam: a pilot intervention of microfinance and peer leadership for HIV and gender-based violence prevention. Glob Public Health. 2016;11(10):1202–15.

    Article  PubMed  Google Scholar 

  34. Yamanis TJ, Maman S, Mbwambo JK, Earp JA, Kajula LJ. Social venues that protect against and promote HIV risk for young men in Dar es Salaam, Tanzania. Soc Sci Med. 2010;71(9):1601–9.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Csardi G, Nepusz T. The igraph software package for complex network re- search. Interjournal, Complex Systems, 1695. http://www.Interjournal.Org/manuscript_. 2006.

  36. Friedkin NE. A structural theory of social influence. Cambridge: Cambridge University Press; 2006.

    Google Scholar 

  37. Costenbader B, Valente TW. The stability of centrality measures when networks are sampled. Soc Netw. 2003;25(4):283–307.

    Article  Google Scholar 

  38. Valente TW, Coronges K, Lakon C, Costenbader E. How correlated are network centrality measures? Connections. 2008;28(1):16–26.

    PubMed  Google Scholar 

  39. Kreager DA, Rulison K, Moody J. Delinquency and the structure of adolescent peer groups. Criminology. 2011;49(1):95–127.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Haynie DL, Doogan NJ, Soller B. Gender, friendship networks, and delinquency: a dynamic network approach. Criminology. 2014;52(4):688–722.

    Article  PubMed  PubMed Central  Google Scholar 

  41. SAS Institute Inc. Sas® 9.4 cary, nc. 2011.

  42. Hanley JA, Negassa A, Edwardes MD, Forrester JE. Statistical analysis of correlated data using generalized estimating equations: an orientation. Am J Epidemiol. 2003;157(4):364–75.

    Article  PubMed  Google Scholar 

  43. Orelien JG. Model fitting in proc genmod. 2001.

  44. Holme P, Ghoshal G. The diplomat’s dilemma: maximal power for minimal effort in social networks. In: Gross T, Sayama H, editors. Adaptive networks. Understanding complex systems. Berlin: Springer; 2009. p. 269–88.

    Google Scholar 

  45. Schneider JA, Laumann EO. Alternative explanations for negative findings in the community popular opinion leader multisite trial and recommendations for improvements of health interventions through social network analysis. J Acquir Immune Defic Syndr. 2011;56(4):e119–20.

    Article  PubMed  Google Scholar 

  46. Fang R, Landis B, Zhang Z, Anderson MH, Shaw JD, Kilduff M. Integrating personality and social networks: a meta-analysis of personality, network position, and work outcomes in organizations. Org Sci. 2015;26(4):1243–60.

    Article  Google Scholar 

  47. Mulawa MI, Kajula LJ, Maman S. Peer network influence on intimate partner violence perpetration among urban tanzanian men. Cult Health Sex. 2018;20(4):474–88.

    Article  PubMed  Google Scholar 

  48. Shah NS, Iveniuk J, Muth SQ, et al. Structural bridging network position is associated with HIV status in a younger black men who have sex with men epidemic. AIDS Behav. 2014;18(2):335–45.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Gyarmathy VA, Caplinskiene I, Caplinskas S, Latkin CA. Social network structure and HIV infection among injecting drug users in lithuania: gatekeepers as bridges of infection. AIDS Behav. 2014;18(3):505–10.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We wish to acknowledge the work and dedication of our study interviewers as well as our research team in Chapel Hill, NC and Dar es Salaam, Tanzania who coordinated the data collection and intervention activities for our trial including Mrema Noel Kilonzo, Dr. Kasubi Mabula, Gema Lambert, Deus Kajuna, Brenda Mkony, Joyce Kondela. We also thank the participants of our study for their contributions.

Funding

Research reported in this publication was supported by the National Institute of Mental Health of the National Institutes of Health under Award Number R01MH098690. Additionally, M. Mulawa is supported by the National Institute of Allergy and Infectious Disease under Award Number T32AI007392. M. Mulawa also received support from the National Institute of Child Health and Human Development under Award Number R25HD079352. T. Yamanis received support from the National Institute on Drug Abuse under Award Number R25DA031608. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author information

Authors and Affiliations

  1. Duke Global Health Institute, Duke University, 310 Trent Drive, Room 334, Durham, 27710, NC, USA

    Marta I. Mulawa

  2. School of International Service, American University, Washington, DC, USA

    Thespina J. Yamanis

  3. Department of Psychiatry and Mental Health, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania

    Lusajo J. Kajula

  4. Department of Health Behavior, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA

    Peter Balvanz & Suzanne Maman

Authors
  1. Marta I. Mulawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thespina J. Yamanis
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lusajo J. Kajula
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Peter Balvanz
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Suzanne Maman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marta I. Mulawa.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mulawa, M.I., Yamanis, T.J., Kajula, L.J. et al. Structural Network Position and Performance of Health Leaders Within an HIV Prevention Trial. AIDS Behav 22, 3033–3043 (2018). https://doi.org/10.1007/s10461-018-2126-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10461-018-2126-1

Keywords

Search

Navigation