IDEAS home Printed from https://ideas.repec.org/a/spr/patien/v16y2023i5d10.1007_s40271-023-00641-y.html
   My bibliography  Save this article

Preferences of People Living with HIV for Long-Acting Antiretroviral Treatment in Germany: Evidence from a Discrete Choice Experiment

Author

Listed:
  • Martin Emmert

    (University of Bayreuth)

  • Stefan Rohrbacher

    (University of Bayreuth)

  • Jennifer Jahn

    (GWS-Gesundheit Wissenschaft Strategie GmbH (Health-Science-Strategy Ltd.))

  • Katharina Fernando

    (GWS-Gesundheit Wissenschaft Strategie GmbH (Health-Science-Strategy Ltd.))

  • Michael Lauerer

    (University of Bayreuth
    GWS-Gesundheit Wissenschaft Strategie GmbH (Health-Science-Strategy Ltd.))

Abstract

Objective This study aimed to elicit preferences for attributes of current and novel long-acting antiretroviral therapy for human immunodeficiency virus treatment. Methods Primary survey data were collected (July–October 2022) on a sample of 333 people living with human immunodeficiency virus in Germany from a patient recruitment agency. Respondents were invited by e-mail to respond to a web-based questionnaire. After performing a systematic literature review, we conducted qualitative semi-structured interviews to identify and select the key attributes of drug therapy for patients’ preferences for human immunodeficiency virus treatment. Based on this, a discrete choice experiment survey elicited preferences for long-acting antiretroviral therapy characteristics, including the type of medication, frequency of dosing, the location of treatment, the risk of both short-term and long-term side effects, as well as possible interactions with other medications or (party) drugs. A statistical data analysis was performed using multinomial logit models. An additional latent class multinomial logit was performed to evaluate subgroup differences. Results Overall, 226 respondents (86% male, mean age 46.1 years) were included in the analysis. The frequency of dosing (36.1%) and the risk of long-term side effects (28.2%) had the greatest influence on preferences. The latent class analysis identified two patient groups. While the first class (n = 135; 87% male, mean age 44.4 years) found the frequency of dosing (44.1%) to be most important, the second class (n = 91; 85% male, mean age 48.6 years) focused on the risk of long-term side effects (50.3%). The evaluation of structural variables showed that male respondents, those living in small cities or villages, and those with better health status results were significantly more likely to be assigned to the second class (p

Suggested Citation

  • Martin Emmert & Stefan Rohrbacher & Jennifer Jahn & Katharina Fernando & Michael Lauerer, 2023. "Preferences of People Living with HIV for Long-Acting Antiretroviral Treatment in Germany: Evidence from a Discrete Choice Experiment," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 16(5), pages 537-553, September.
    • Handle: RePEc:spr:patien:v:16:y:2023:i:5:d:10.1007_s40271-023-00641-y
    DOI: 10.1007/s40271-023-00641-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40271-023-00641-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40271-023-00641-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. White,Halbert, 1996. "Estimation, Inference and Specification Analysis," Cambridge Books, Cambridge University Press, number 9780521574464, November.
    2. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tindara Addabbo & Anna Maccagnan & Carmen Llorca-Rodríguez & Rosa García-Fernández, 2010. "Income distribution and the effect of the financial crisis on the Italian and Spanish labour markets," Department of Economics 0639, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    2. Kruse, Tobias & Atkinson, Giles, 2022. "Understanding public support for international climate adaptation payments: Evidence from a choice experiment," Ecological Economics, Elsevier, vol. 194(C).
    3. Walter Beckert, 2015. "Choice in the Presence of Experts," Birkbeck Working Papers in Economics and Finance 1503, Birkbeck, Department of Economics, Mathematics & Statistics.
    4. Péter Czine & Péter Balogh & Zsanett Blága & Zoltán Szabó & Réka Szekeres & Stephane Hess & Béla Juhász, 2024. "Is It Sufficient to Select the Optimal Class Number Based Only on Information Criteria in Fixed- and Random-Parameter Latent Class Discrete Choice Modeling Approaches?," Econometrics, MDPI, vol. 12(3), pages 1-16, August.
    5. Ai, Chunrong & Chen, Xiaohong, 2007. "Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables," Journal of Econometrics, Elsevier, vol. 141(1), pages 5-43, November.
    6. Okhrin, Ostap & Ristig, Alexander & Sheen, Jeffrey R. & Trück, Stefan, 2015. "Conditional systemic risk with penalized copula," SFB 649 Discussion Papers 2015-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Xiaohong Chen & Roger Koenker & Zhijie Xiao, 2009. "Copula-based nonlinear quantile autoregression," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 50-67, January.
    8. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    9. Magnus, Jan R., 2007. "The Asymptotic Variance Of The Pseudo Maximum Likelihood Estimator," Econometric Theory, Cambridge University Press, vol. 23(5), pages 1022-1032, October.
    10. David Hensher & John Rose & Zheng Li, 2012. "Does the choice model method and/or the data matter?," Transportation, Springer, vol. 39(2), pages 351-385, March.
    11. Flores, Alvaro & Berbeglia, Gerardo & Van Hentenryck, Pascal, 2019. "Assortment optimization under the Sequential Multinomial Logit Model," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1052-1064.
    12. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    13. An, Wookhyun & Alarcón, Silverio, 2021. "Rural tourism preferences in Spain: Best-worst choices," Annals of Tourism Research, Elsevier, vol. 89(C).
    14. Chor-Yiu Sin, 2014. "Qmle Of A Standard Exponential Acd Model: Asymptotic Distribution And Residual Correlation," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 1-10.
    15. Wen, Chieh-Hua & Wang, Wei-Chung & Fu, Chiang, 2012. "Latent class nested logit model for analyzing high-speed rail access mode choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 545-554.
    16. Shin, Jungwoo & Hwang, Won-Sik, 2017. "Consumer preference and willingness to pay for a renewable fuel standard (RFS) policy: Focusing on ex-ante market analysis and segmentation," Energy Policy, Elsevier, vol. 106(C), pages 32-40.
    17. Le Gloux, Fanny & Dupraz, Pierre & Issanchou, Alice & Ropars-Collet, Carole, 2022. "Payments for environmental services with provision thresholds: farmers’ preferences for a conditional bonus," 96th Annual Conference, April 4-6, 2022, K U Leuven, Belgium 321177, Agricultural Economics Society - AES.
    18. D Rigby & M Burton, 2003. "Capturing Preference Heterogeneity in Stated Choice Models: A Random Parameter Logit Model of the Demand for GM Food," Economics Discussion Paper Series 0319, Economics, The University of Manchester.
    19. Wongsa-art, Pipat & Kim, Namhyun & Xia, Yingcun & Moscone, Francesco, 2024. "Varying coefficient panel data models and methods under correlated error components: Application to disparities in mental health services in England," Regional Science and Urban Economics, Elsevier, vol. 106(C).
    20. Coenen, Gunter & Wieland, Volker, 2005. "A small estimated euro area model with rational expectations and nominal rigidities," European Economic Review, Elsevier, vol. 49(5), pages 1081-1104, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:patien:v:16:y:2023:i:5:d:10.1007_s40271-023-00641-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.