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Development of a Computer-Based Tailored Information Application to Improve HIV-Related Treatment Adherence: Preliminary Findings Raymond L Ownby, MD, PhD Nova Southeastern University Fort Lauderdale FL
Medication adherence in HIV Adherence needed to suppress viral replication= 80-95% Typical adherence = 60-70% Viral suppression ๏ƒ  decreased risk of infecting others Viral suppression ๏ƒ  better clinical outcomes
Health literacy Knowledge, abilities, and skills required to attain a desired state of health Related to multiple clinical variables Disease control (diabetes) Hospitalization (Medicare data) Death (Medicare data) Medication adherence (HIV)
IMB Model Information: How meds work, how to cope with side effects Motivation: Social support, depression Behavioral Skills: How to remember to take medications, cope with obstacles
Tailored information Personalization Individualized feedback Enhancing perceived relevance Increases impact on patient behavior ๏ƒ  10%+ increase in dietary intake of fruits ๏ƒ  10-15% improvement in adherence in older adults treated for memory problems
The intervention An overview of topics Instructional theory
A Flash animation provides a preliminary overview of the virus life cycle
The animation emphasizes specific stages in the viral life cycle These stages are later reviewed in discussion of how medications work
A key aspect of the intervention is interactivity Participant learning is assessed with questions If needed, content is retaught
MEMS Medication Event Monitoring System Adherence indices Taken (e.g.,30 pills in 30 days) Correct (e.g., 1pill/24 hours) Scheduled (e.g.,+/- 2 hours)
Sample (n = 110)
Results: LifeWindows IMB scale Information F= 7.141, p = 0.001  f = 0.35,  a medium to large effect size Motivation F= 0.75, p = 0.48 Behavioral Skills F= 8.64, p< 0.001  f = 0.39, a medium to large effect Based on completers 3 drop outs
Results: Self Efficacy, Depression Patient-Provider Interaction F= 5.17, p = 0.007; f = 0.29, medium effect Healthcare Self-efficacy  F= 11.71, p = 0.001; f = 0.39, medium to large effect Depression and Social Support Not significant
Results: Adherence Percent Taken Number of doses / month F= 4.21, p = 0.04; f = 0.25, a medium effect Percent Correct Number of doses / day F= 5.31, p = 0.02; f = 0.27, a medium effect
Conclusions Participation in the intervention is associated with improved Information  Behavioral skills  Self-reported ability to work with clinicians Healthcare self-efficacy Not associated with improved Motivation Social support Mood
Discussion Preliminary results Study not yet completed Clinical vs. statistical significance Medium effect sizes comparable to other behavioral interventions Adjunct to other interventions Pre-post design (no control group)
Future directions Other languages Other aspects of treatment adherence Appointments Diet, exercise Other disorders Diabetes Congestive heart failure
Support: Support for this study was provided by grant R21MH086491 to Dr. Ownby from the National Institute on Mental Health.
Collaborators Drenna Waldrop-Valverde, PhD Josh Caballero, PharmD Rosemary Davenport, RN, MSN, ARNP Robin Jacobs, PhD

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Development of a Computer-Based Tailored Information Application to Improve HIV-Related Treatment Adherence

  • 1. Development of a Computer-Based Tailored Information Application to Improve HIV-Related Treatment Adherence: Preliminary Findings Raymond L Ownby, MD, PhD Nova Southeastern University Fort Lauderdale FL
  • 2. Medication adherence in HIV Adherence needed to suppress viral replication= 80-95% Typical adherence = 60-70% Viral suppression ๏ƒ  decreased risk of infecting others Viral suppression ๏ƒ  better clinical outcomes
  • 3. Health literacy Knowledge, abilities, and skills required to attain a desired state of health Related to multiple clinical variables Disease control (diabetes) Hospitalization (Medicare data) Death (Medicare data) Medication adherence (HIV)
  • 4. IMB Model Information: How meds work, how to cope with side effects Motivation: Social support, depression Behavioral Skills: How to remember to take medications, cope with obstacles
  • 5. Tailored information Personalization Individualized feedback Enhancing perceived relevance Increases impact on patient behavior ๏ƒ  10%+ increase in dietary intake of fruits ๏ƒ  10-15% improvement in adherence in older adults treated for memory problems
  • 6. The intervention An overview of topics Instructional theory
  • 7. A Flash animation provides a preliminary overview of the virus life cycle
  • 8. The animation emphasizes specific stages in the viral life cycle These stages are later reviewed in discussion of how medications work
  • 9. A key aspect of the intervention is interactivity Participant learning is assessed with questions If needed, content is retaught
  • 10.
  • 11.
  • 12. MEMS Medication Event Monitoring System Adherence indices Taken (e.g.,30 pills in 30 days) Correct (e.g., 1pill/24 hours) Scheduled (e.g.,+/- 2 hours)
  • 13. Sample (n = 110)
  • 14.
  • 15.
  • 16. Results: LifeWindows IMB scale Information F= 7.141, p = 0.001 f = 0.35, a medium to large effect size Motivation F= 0.75, p = 0.48 Behavioral Skills F= 8.64, p< 0.001 f = 0.39, a medium to large effect Based on completers 3 drop outs
  • 17. Results: Self Efficacy, Depression Patient-Provider Interaction F= 5.17, p = 0.007; f = 0.29, medium effect Healthcare Self-efficacy F= 11.71, p = 0.001; f = 0.39, medium to large effect Depression and Social Support Not significant
  • 18. Results: Adherence Percent Taken Number of doses / month F= 4.21, p = 0.04; f = 0.25, a medium effect Percent Correct Number of doses / day F= 5.31, p = 0.02; f = 0.27, a medium effect
  • 19. Conclusions Participation in the intervention is associated with improved Information Behavioral skills Self-reported ability to work with clinicians Healthcare self-efficacy Not associated with improved Motivation Social support Mood
  • 20. Discussion Preliminary results Study not yet completed Clinical vs. statistical significance Medium effect sizes comparable to other behavioral interventions Adjunct to other interventions Pre-post design (no control group)
  • 21. Future directions Other languages Other aspects of treatment adherence Appointments Diet, exercise Other disorders Diabetes Congestive heart failure
  • 22. Support: Support for this study was provided by grant R21MH086491 to Dr. Ownby from the National Institute on Mental Health.
  • 23. Collaborators Drenna Waldrop-Valverde, PhD Josh Caballero, PharmD Rosemary Davenport, RN, MSN, ARNP Robin Jacobs, PhD