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What’s Love Got to Do With It?

What’s Love Got to Do With It?. Mallory O. Johnson, Ph.D. Mallory.Johnson@ucsf.edu Center for AIDS Prevention Studies University of California, San Francisco. Relationship Factors and HIV Treatment Adherence. Center for Health, Intervention, and Prevention Nov. 18, 2010. Objectives.

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What’s Love Got to Do With It?

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  1. What’s Love Got to Do With It? Mallory O. Johnson, Ph.D. Mallory.Johnson@ucsf.edu Center for AIDS Prevention Studies University of California, San Francisco Relationship Factors and HIV Treatment Adherence Center for Health, Intervention, and Prevention Nov. 18, 2010

  2. Objectives • Why study couples and HIV treatment adherence • What have we learned • Where are we going

  3. AIDS Cases, Deaths & Prevalence1980 - 2006

  4. Why Study Adherence?Adherence related to • Virologic control • Treatment resistance • Morbidity • Quality of life • Survival • Health care costs • HIV transmission • Personal and community

  5. Side effects Substance use/abuse Regimen complexity Depression Poor social support Lack of knowledge Low perceived efficacy of treatment Memory problems Stigma Predictors of Poor Adherence

  6. Why Study Couples? • Social support and health • Primary relationships • Education • Diet • Exercise • Drug use • Smoking

  7. Challenges of Studying Couples • Complicated • Definition of a couple • Design, data collection, and analysis • Expensive

  8. Why Study Couples and Adherence? • Prior counter-intuitive findings • Can relationships promote or derail adherence?

  9. Duo Project Relationship Factors and HIV Treatment Adherence R01NR010187

  10. Duo Phases

  11. Framework • Interdependence Theory • Social Control • Health Care Empowerment

  12. Responsibility Divided He’s so pissed. He goes, “Well,” when he finds out, especially last week when I missed four days in a row, “God damn it.” And he goes, “I’m going to have to just light up your cell phone. I don’t care what you’re doing, you know, whatever you’re doing you’re going to drop what you’re doing and take your pills.” He said, “I’m going to call you between ten and one everyday, just light up your phone until you tell me you’ve taken your pills.” But ever since then I’ve been taking them so when he does call, “Yeah, I took them.” So that’s it.

  13. Autonomy He doesn't need me to stand behind him to take it. And this is another thing why we get along so well, is because you know what, if he decides one day that he doesn't want to take it, I’m not going to push him on it, okay? Because it’s his choice whether he wants to take it, okay? It’s his body, it’s his temple.

  14. Partner A: “I like the daddy type and he certainly is—he’s that type, looks, and personality.” Partner B: “Well, I certainly love him. He’s very dependent, which I don’t mind. I mean, I don’t mind being a parent.” Partner dynamics “We seem to be very compatible, because he pushes me around and I let him.

  15. Cross-sectional approach

  16. Meet Paul and Phil • Both HIV+ • Both on meds

  17. Paul’s Stuff Paul’s Outcomes Actor Effect Phil’s Outcomes Phil’s Stuff Actor Effect

  18. Paul’s Stuff Paul’s Outcomes Partner Effect Partner Effect Phil’s Outcomes Phil’s Stuff

  19. Paul’s Stuff Paul’s Outcomes Actor Effect Partner Effect Partner Effect Phil’s Outcomes Phil’s Stuff Actor Effect

  20. Recruitment • Sought male couples • Together at least 3 months • One or both men are HIV+ • One or both taking HIV meds

  21. Recruitment

  22. Methods • Phone screen • Separate • “Smell check” for fake couples • Verified meds and identity • Separate ACASI interviews • Blood draw for CD4 and viral load

  23. Explanatory Variables • Depression • Treatment Beliefs • General med concerns • Specific concerns • Specific necessity Relationship • Satisfaction • Autonomy • Intimacy • Equality • Commitment • Communication

  24. Outcomes • Adherence Self Efficacy • Integration • Perseverance • Self Reported Adherence • 3 day • 30 day • Viral Load • Detectable v not • Log10 transformed

  25. Analysis • Actor- Partner analyses • Multivariate using p<.25 for inclusion • All results are p<.05 in adjusted models • Control for actor’s • Relationship Length • Living Together • Time on ART • Age • Number of pills per day

  26. Sample • 420 men • 91 discordant couples • 119 concordant couples • 45 years old • 17% AA • 18% Latino • 91% gay • 26% HS grad or less • 84 months as couple • 12 years HIV+ • 9+ years on meds

  27. Self EfficacyIntegration Scale PAUL’s Concerns about Meds (-) Autonomy Age Time on Meds (-) PAUL’s Adherence Self Efficacy INTEGRATION PHIL’s Depression (-)

  28. Self Efficacy (Perseverance) PAUL’s General Med Concerns (-) Specific Med Concerns (-) Depression (-) Autonomy Intimacy Time on Meds (-) PAUL’s Adherence Self-Efficacy PERSEVERANCE PHIL’s Relationship Satisfaction

  29. 3 DAY ADHERENCE PAUL’s General Med Concerns (-) Fewer pills per day PAUL’s 3 DAY ADHERENCE PHIL’s Beliefs that Paul’s meds are necessary

  30. 30 DAY ADHERENCE PAUL’s Relationship Communication Time on meds (-) PAUL’s 30 DAY ADHERENCE PHIL’s General Concerns about Meds (-)

  31. VIRAL LOAD (Detect v. not) PAUL’s NOTHING Time in relationship (-) PAUL’s Detectable Viral Load PHIL’s Commitment (-)

  32. VIRAL LOAD (log10) PAUL’s NOTHING PAUL’s Viral Load PHIL’s Commitment (-)

  33. Summary of Findings • Both actor and partner effects on • Self Efficacy for Adherence • Self-Reported Adherence • Viral load • Relevant constructs • Depression • Treatment beliefs (general and specific) • Relationship factors (autonomy, commitment, satisfaction, intimacy, and communication) • Partner effects w/o corresponding actor effects

  34. Limitations • Cross-sectional data • Convenience sample • High levels of adherence • Long time with HIV • Long time on meds • Relationship length • Self-reported adherence

  35. From here to where? • Follow couples over time • 6, 12, 18, and 24 months • Include break up interviews • Qualitative interviews • Intervention development

  36. Paul’s Stuff Paul’s Outcomes Actor Effect Partner Effect Partner Effect Phil’s Outcomes Phil’s Stuff Actor Effect

  37. Paul’s Stuff Paul’s Outcomes Partner Effect Partner Effect Phil’s Outcomes Phil’s Stuff

  38. What’s in the black box? • Tactics • Support Received • Support Provided • Substance Use?

  39. Figure 1. Conceptual Model

  40. Duo Phases

  41. Tactics • Ask (76%) • Check in (72%) • Model (65%) • Remind (61%) • Encourage (56%) • Fill Rx (43%) • Point out importance (37%) • Reassure (36%) • Express concern (35%) • Watch, monitor, verify (35%) • Nag (31%) • Give meds directly (27%) • Offer advice (27%) • Point out conseq. (26%)

  42. ‘Invisible’ TacticsWatch, Monitor, Verify • 34% received • 48% provided

  43. Perceived effects of tactics • Affective response • Loved, valued, pleased, inspired? • Anxious, irritated? • On adherence (positive or negative) • On relationship (positive or negative)

  44. Partner Support/Involvement • Communication • Knowledge • Involvement • Support • Regimen knowledge

  45. Actor-Partner Effects Sums and Differences Analysis Doctors prescribe too many medications. 0 = not true to 10= very true Dyadic Data Analysis • Peter says 6 • Ned says 6 • Sum = 12 • Difference = 0 • Paul says 10 • Phil says 2 • Sum = 12 • Difference = 8

  46. What about other couples?

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