Skip to main content

Advertisement

SpringerLink
Log in

Can Individualized-Targeted Computerized Cognitive Training Benefit Adults with HIV-Associated Neurocognitive Disorder? The Training on Purpose Study (TOPS)

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

Abstract

Half of people with HIV (PWH) have HIV-associated neurocognitive disorder (HAND). This study examined whether cognition can be improved using a framework targeting impaired individual cognitive domains in PWH with HAND. In this two-group pre-post experimental design study, 88 adults with HAND were randomized to either: (1) a no-contact control group (n = 40) or (2) the Individualized-Targeted Cognitive Training group (n = 48). Baseline cognitive performance was assessed on eight cognitive domains. A theoretical framework was used to determine the two cognitive domains selected for training. With priority on speed of processing (SOP) and attention impairments, participants received SOP and/or attention training if such impairments were detected; if not, participants were assigned to cognitive training in one/two of the least impaired cognitive domains contributing to their HAND diagnosis. Global cognitive score was slightly improved following training (p = 0.256; d = − 0.21), but it was not significant. Significant improvements were observed on SOP following training in that domain (SOP; d = − 0.88; p = 0.011). SOP training also improved functioning in other cognitive domains. This individualized cognitive intervention did not change HAND status, but it did result in improved SOP, in turn yielding improvement in other cognitive domains.

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. Centers for Disease Control and Prevention C. HIV Surveilance Report, 2018 (updated). 2020.

  2. Smit M, Brinkman K, Geerlings S, et al. Future challenges for clinical care of an ageing population infected with HIV: a modelling study. Lancet Infect Dis. 2015;15(7):810–8. https://doi.org/10.1016/S473-3099(15)00056-0.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Goodkin K, Miller EN, Cox C, et al. Effect of ageing on neurocognitive function by stage of HIV infection: evidence from the Multicenter AIDS Cohort Study. Lancet HIV. 2017;4(9):e411–22. https://doi.org/10.1016/S2352-3018(17)30098-X.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Vance DE, Fazeli PL, Gakumo CA. The impact of neuropsychological performance on everyday functioning between older and younger adults with and without HIV. J Assoc Nurses AIDS Care. 2013;24(2):112–25. https://doi.org/10.1016/j.jana.2012.05.002.

    Article  PubMed  Google Scholar 

  5. Cody SL, Vance DE. The neurobiology of HIV and its impact on cognitive reserve: a review of cognitive interventions for an aging population. Neurobiol Dis. 2016;92(Pt B):144–56. https://doi.org/10.1016/j.nbd.2016.01.011.

    Article  PubMed  Google Scholar 

  6. Lee Y, Batey DS, Clay OJ, Emlet CA, Fazeli PL, Vance DE. Older caregivers with HIV: an unrecognized gap in the literature. J Assoc Nurses AIDS Care. 2021;32(1):29–36. https://doi.org/10.1097/JNC.0000000000000180.

    Article  PubMed  Google Scholar 

  7. Antinori A, Arendt G, Becker JT, et al. Updated research nosology for HIV-associated neurocognitive disorders. Neurology. 2007;69(18):1789–99. https://doi.org/10.1212/01.WNL.0000287431.88658.8b.

    Article  CAS  PubMed  Google Scholar 

  8. Vance DE, Cody SL, Moneyham L. Remediating HIV-associated neurocognitive disorders via cognitive training: a perspective on neurocognitive aging. Interdiscip Top Gerontol Geriatr. 2017;42:173–86. https://doi.org/10.1159/000448562.

    Article  PubMed  Google Scholar 

  9. Blackstone K, Moore DJ, Franklin DR, et al. Defining neurocognitive impairment in HIV: deficit scores versus clinical ratings. The Clin Neuropsychol. 2012;26(6):894–908. https://doi.org/10.1080/13854046.2012.694479.

    Article  CAS  PubMed  Google Scholar 

  10. Rubin LH, Maki PM, Springer G, et al. Cognitive trajectories over 4 years among HIV-infected women with optimal viral suppression. Neurology. 2017;89(15):1594–603. https://doi.org/10.1097/QAD.0000000000001625.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Vance DE, Fazeli PL, Cheatwood J, Nicholson WC, Morrison SA, Moneyham LD. Computerized cognitive training for the neurocognitive complications of HIV infection: a systematic review. J Assoc Nurses AIDS Care. 2019;30(1):51–72. https://doi.org/10.1097/JNC.0000000000000030.

    Article  PubMed  Google Scholar 

  12. Vance DE, Fazeli PL, Ross LA, Wadley VG, Ball KK. Speed of processing training with middle-age and older adults with HIV: a pilot study. J Assoc Nurses AIDS Care. 2012;23(6):500–10. https://doi.org/10.1016/j.jana.2012.01.005.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Lampit A, Hallock H, Valenzuela M. Computerized cognitive training in cognitively healthy older adults: a systematic review and meta-analysis of effect modifiers. PLoS Med. 2014;11(11):e1001756. https://doi.org/10.1371/journal.pmed.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Vance DE, Fazeli PL, Azuero A, Wadley VG, Jensen M, Raper JL. Can computerized cognitive training reverse the diagnosis of HIV-associated neurocognitive disorder? A research protocol. Res Nurs Health. 2018;41(1):11–8. https://doi.org/10.1002/nur.21841.

    Article  PubMed  Google Scholar 

  15. Salthouse TA. Constraints on theories of cognitive aging. Psychon Bull Rev. 1996;3(3):287–99.

    Article  CAS  Google Scholar 

  16. Wickens CD, Hollands JG, Bandbury S, Parasuraman R. A model of human information processing. Engineering Psychology and Human Performance. Upper Saddle River, NJ: Pearson; 2013.

    Google Scholar 

  17. Fellows RP, Byrd DA, Morgello S. Effects of information processing speed on learning, memory, and executive functioning in people living with HIV/AIDS. J Clin Exp Neuropsychol. 2014;36(8):806–17. https://doi.org/10.1080/13803395.2014.943696.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Radloff LS. The use of the Center for Epidemiologic Studies Depression Scale in adolescents and young adults. J Youth Adolesc. 1991;20(2):149–66. https://doi.org/10.1007/BF01537606.

    Article  CAS  PubMed  Google Scholar 

  19. Woods SP, Iudicello JE, Moran LM, et al. HIV-associated prospective memory impairment increases risk of dependence in everyday functioning. Neuropsychology. 2008;22(1):110–7. https://doi.org/10.1037/0894-4105.22.1.110.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Lezak MD. Neuropsychological Assessment. 3rd ed. New York, NY: Oxford University Press; 1995.

    Google Scholar 

  21. Ball K, Berch DB, Helmers KF, et al. Effects of cognitive training interventions with older adults: a randomized controlled trial. JAMA. 2002;288(18):2271–81. https://doi.org/10.1001/jama.288.18.2271.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Imbens G, Rubin D. Causal inference for statistics, social, and biomedical sciences: an introduction. Cambridge: Cambridge University Press; 2015.

    Book  Google Scholar 

  23. Leon AC, Davis LL, Kraemer HC. The role and interpretation of pilot studies in clinical research. J Psychiatr Res. 2011;45(5):626–9. https://doi.org/10.1016/j.jpsychires.2010.10.008.

    Article  PubMed  Google Scholar 

  24. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. New York, NY: New York University Press; 1988.

    Google Scholar 

  25. Team RC. R: a language and environment for statistical computing: R Foundation for Statistical Computing. 2019. https://www.R-project.org/.

  26. Vance DE, Jensen M, Tende F, Raper JL, Morrison S, Fazeli PL. Individualized-targeted computerized cognitive training to treat HIV-associated neurocognitive disorder: an interim descriptive analysis. J Assoc Nurses AIDS Care. 2018;29(4):604–11. https://doi.org/10.1016/j.jana.2018.04.005.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Vance DE, Wright MA. Positive and negative neuroplasticity: implications for age-related cognitive declines. J Gerontol Nurs. 2009;35(6):11–7; quiz 8–9.

    Article  Google Scholar 

  28. Edwards JD, Xu H, Clark DO, Guey LT, Ross LA, Unverzagt FW. Speed of processing training results in lower risk of dementia. Alzheimers Dement (N Y). 2017;3(4):603–11. https://doi.org/10.1016/j.trci.2017.09.002.

    Article  Google Scholar 

  29. Ross LA, Edwards JD, O’Connor ML, Ball KK, Wadley VG, Vance DE. The transfer of cognitive speed of processing training to older adults’ driving mobility across 5 years. J Gerontol B. 2016;71(1):87–97. https://doi.org/10.1093/geronb/gbv022.

    Article  Google Scholar 

  30. Vance DE. Speed of processing in older adults: a cognitive overview for nursing. J Neurosci Nurs. 2009;41(6):290–7. https://doi.org/10.1097/jnn.0b013e3181b6beda.

    Article  PubMed  Google Scholar 

  31. Vance DE, Jensen M, Tende F, et al. Informing adults with HIV of cognitive performance deficits indicative of HIV-associated neurocognitive disorder: a content analysis. J Psychosoc Nurs Ment Health Serv. 2019;57(12):48–55. https://doi.org/10.3928/02793695-20190821-03.

    Article  PubMed  Google Scholar 

  32. Morgan EE, Woods SP, Grant I, Group HIVNRP. Intra-individual neurocognitive variability confers risk of dependence in activities of daily living among HIV-seropositive individuals without HIV-associated neurocognitive disorders. Arch Clin Neuropsychol. 2012;27(3):293–303. https://doi.org/10.1093/arclin/acs003.

  33. Bangen KJ, Weigand AJ, Thomas KR, et al. Cognitive dispersion is a sensitive marker for early neurodegenerative changes and functional decline in nondemented older adults. Neuropsychology. 2019;33(5):599–608. https://doi.org/10.1037/neu0000532.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Hilborn JV, Strauss E, Hultsch DF, Hunter MA. Intraindividual variability across cognitive domains: investigation of dispersion levels and performance profiles in older adults. J Clin Exp Neuropsychol. 2009;31(4):412–24. https://doi.org/10.1080/13803390802232659.

    Article  PubMed  Google Scholar 

  35. Pope CN, Fazeli PL, Vance DE, Mrug S, Ball KK, Stavrinos D. Cognitive reserve attenuates the association between HIV serostatus and cognitive performance in adults living in the deep South. Appl Neuropsychol Adult 2020;1–10. https://doi.org/10.1080/23279095.2020.1832095.

  36. Vance D, Fazeli P, Shacka J, et al. Testing a computerized cognitive training protocol in adults aging with HIV-associated neurocognitive disorder: randomized controlled trial rationale and protocol. JMIR Res Protoc. 2017;6(4):e68. https://doi.org/10.2196/resprot.6625.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Wadley VG, Benz RL, Ball KK, Roenker DL, Edwards JD, Vance DE. Development and evaluation of home-based speed-of-processing training for older adults. Arch Phys Med Rehabil. 2006;87(6):757–63. https://doi.org/10.1016/j.apmr.2006.02.027.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Special thanks to our research team, especially Brittany Bradley, Delaney Diehl, Shyla Hossain, Michael Jenson, Peggy McKie, Josiah Robinson, Frida Tende, and Tess Walker.

Funding

This study was funded by an NIH/NINR R21-award (1R21NR016632-01; ClinicalTrials.gov (NCT03122288); Vance, Principal Investigator) titled “Individualized-Targeted Cognitive Training in Older Adults with HAND”; by an NIH/National Institute on Aging (NIA) R00-award (R00 AG048762; PI: Fazeli); and by an NIH/NIA P30-award (Edward R. Roybal Center for Translational Research in Aging and Mobility; P30 AG022838; PI: Ball).

Author information

Authors and Affiliations

  1. School of Nursing, University of Alabama at Birmingham, 1701 University Boulevard, Birmingham, AL, 35294-1210, USA

    David E. Vance, Pariya L. Fazeli & Andres Azuero

  2. Integrative Center for Aging Research, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA

    Virginia G. Wadley

  3. UAB 1917 Clinic at Dewberry, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA

    James L. Raper

  4. UAB Center for Research on Applied Gerontology, University of Alabama at Birmingham, Birmingham, AL, USA

    Karlene K. Ball

Authors
  1. David E. Vance
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pariya L. Fazeli
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andres Azuero
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Virginia G. Wadley
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. James L. Raper
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Karlene K. Ball
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David E. Vance.

Ethics declarations

Conflict of interest

Financial interests—Karlene Ball owns stock in the Visual Awareness Research Group (formerly Visual Awareness, Inc.), and Posit Science, Inc., the companies that market the Useful Field of View Test and speed of processing training software. Posit Science acquired Visual Awareness, and Dr. Ball continues to collaborate on the design and testing of these Assessment and training programs as a member of the Posit Science Scientific Advisory Board. Non-financial interests—David E. Vance, Pariya L. Fazeli, Andres Azuero, Virginia Wadley, and James L. Raper report no real or perceived vested interest that relate to this article that could be construed as a conflict of interest.

Consent to Participate

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

Consent to Publish

Participants consented that their data would be used in aggregate form for publication purposes.

Research Involving Human Participants and/or Animals

This study was approved by the ethics committee of the University of Alabama at Birmingham’s Institutional Review Board (IRB) titled “Individualized-Target Cognitive Training in Older Adults with HIV (Training On Purpose Study) TOPS))”, with the following Registration Number – IRB00000726. All procedures performed in this study 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.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 49 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vance, D.E., Fazeli, P.L., Azuero, A. et al. Can Individualized-Targeted Computerized Cognitive Training Benefit Adults with HIV-Associated Neurocognitive Disorder? The Training on Purpose Study (TOPS). AIDS Behav 25, 3898–3908 (2021). https://doi.org/10.1007/s10461-021-03230-y

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10461-021-03230-y

Keywords

Search

Navigation