Skip to main content

Advertisement

SpringerLink
Log in

Getting less of what you want: reductions in statistical power and increased bias when categorizing medication adherence data

  • Published:
Journal of Behavioral Medicine Aims and scope Submit manuscript

Abstract

Medication adherence is thought to be the principal clinical predictor of positive clinical outcomes, not only for serious mental illnesses such as schizophrenia, bipolar disorder, or depression, but also for physical conditions such as diabetes. Consequently, research on medication often looks not only at medication condition (e.g., placebo, standard medication, investigative medication), but also at adherence in taking those medications within each medication condition. The percentage (or proportion) scale is one of the more frequently employed and easily interpretable measures. Patients can be 0 % adherent, 100 % adherent, or somewhere in between. For simplicity, many reported adherence analyses dichotomize or trichotomize the adherence predictor when estimating its effect on outcomes of interest. However, the methodological literature shows that the practice of categorizing continuously distributed predictors reduces statistical power at best and, at worst, can severely bias parameter estimates. This can result in inflated Type I errors (false positive acceptance of null adherence effects) or Type II errors (false negative rejection of true adherence effects). We extend the methodological literature on categorization to the construct of adherence. The measurement scale of adherence leads to a diverse family of potential distributions including uniform, n-shaped, u-shaped (i.e., bimodal), positively skewed, and negatively skewed. Using a simulation study, we generated negative, null, and positive “true” effects of adherence on simulated continuous and binary outcomes. We then estimated the adherence effect with and without categorizing the adherence variable. We show how parameter estimates and standard errors can be severely biased when categorizing adherence. The categorization of adherence is shown to cause null effects to become positive or negative depending on the distribution of the simulated adherence variable, inflating Type I errors. When the adherence effect was significantly different from zero, categorization can render the effect null, inflating Type II errors. We recommend that adherence be measured continuously and analyzed without categorization when using it as a predictor in regression models.

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

  • Acosta, F. J., Ramallo-Fariña, Y., & Siris, S. G. (2014). Should full adherence be a necessary goal in schizophrenia? Full versus non-full adherence to antipsychotic treatment. Comprehensive Psychiatry, 55, 33–39.

    Article  PubMed  Google Scholar 

  • Ascher-Svanum, H., Zhu, B., Faries, D. E., Salkever, D., Slade, E. P., Peng, X., & Conley, R. R. (2010). The cost of relapse and the predictors of relapse in the treatment of schizophrenia. BMC Psychiatry, 10, 2.

    Article  PubMed  PubMed Central  Google Scholar 

  • Asmundson, G. J., Taylor, S., Carleton, R. N., Weeks, J. W., & Hadjstavropoulos, H. D. (2012). Should health anxiety be carved at the joint? A look at the health anxiety construct using factor mixture modeling in a non-clinical sample. Journal of Anxiety Disorders, 26, 246–251.

    Article  PubMed  Google Scholar 

  • Ballif, M., Ledergerber, B., Battegay, M., Cavassini, M., Bernasconi, E., Schmid, P., et al. (2009). Impact of previous virological treatment failures and adherence on the outcome of antiretroviral therapy in 2007. PLoS ONE, 4, e8275. doi:10.1371/journal.pone.0008275

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Buysman, E. K., Liu, F., Hammer, M., & Langer, J. (2015). Impact of medication adherence and persistence on clinical and economic outcomes in patients with type 2 diabetes treated with liraglutide: A retrospective cohort study. Advances in Therapy, 32, 341–355.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Byerly, M., Fisher, R., Whatley, K., Holland, R., Varghese, F., Carmody, T., et al. (2005). A comparison of electronic monitoring vs. clinician rating of antipsychotic adherence in outpatients with schizophrenia. Psychiatry Research, 133, 129–133.

    Article  PubMed  Google Scholar 

  • Byerly, M. J., Nakonezny, P. A., & Rush, A. J. (2008). The Brief Adherence Rating Scale (BARS) validated against electronic monitoring in assessing the antipsychotic medication adherence of outpatients with schizophrenia and schizoaffective disorder. Schizophrenia Research, 100, 60–69.

    Article  PubMed  Google Scholar 

  • Davis, J. M., Chen, N., & Glick, I. D. (2003). A meta-analysis of the efficacy of second-generation antipsychotics. Archives of General Psychiatry, 60, 553–564.

    Article  CAS  PubMed  Google Scholar 

  • DeCoster, J., Iselin, A. M. R., & Gallucci, M. (2009). A conceptual and empirical examination of justifications for dichotomization. Psychological Methods, 14, 349.

    Article  PubMed  Google Scholar 

  • Elbogen, E. B., Swanson, J. W., Swartz, M. S., & Van Dorn, R. (2005). Medication nonadherence and substance abuse in psychotic disorders: Impact of depressive symptoms and social stability. The Journal of Nervous and Mental Disease, 193, 673–679.

    Article  PubMed  Google Scholar 

  • Fedorov, V., Mannino, F., & Zhang, R. (2009). Consequences of dichotomization. Pharmaceutical Statistics, 8, 50–61.

    Article  PubMed  Google Scholar 

  • Ferguson, N. M., Donnelly, C. A., Hooper, J., Ghani, A. C., Fraser, C., Bartley, L. M., et al. (2005). Adherence to antiretroviral therapy and its impact on clinical outcome in HIV-infected patients. Journal of the Royal Society, Interface, 2, 349–363.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Gilmer, T. P., Dolder, C. R., Lacro, J. P., Folsom, D. P., Lindamer, L., Garcia, P., & Jeste, D. V. (2004). Adherence to treatment with antipsychotic medication and health care costs among Medicaid beneficiaries with schizophrenia. American Journal of Psychiatry, 161, 692–699.

    Article  PubMed  Google Scholar 

  • Hepke, K. L., Martus, M. T., & Share, D. A. (2004). Costs and utilization associated with pharmaceutical adherence in a diabetic population. The American Journal of Managed Care, 10, 144–151.

    PubMed  Google Scholar 

  • Hershman, D. L., Shao, T., Kushi, L. H., Buono, D., Tsai, W. Y., Fehrenbacher, L., et al. (2011). Early discontinuation and non-adherence to adjuvant hormonal therapy are associated with increased mortality in women with breast cancer. Breast Cancer Research and Treatment, 126, 529–537.

    Article  CAS  PubMed  Google Scholar 

  • Ho, P. M., Bryson, C. L., & Rumsfeld, J. S. (2009). Medication adherence: Its importance in cardiovascular outcomes. Circulation, 119, 3028–3035.

    Article  PubMed  Google Scholar 

  • Hommel, K. A., Davis, C. M., & Baldassano, R. N. (2008). Medication adherence and quality of life in pediatric inflammatory bowel disease. Journal of Pediatric Psychology, 33, 867–874.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hsieh, K. P., Chen, L. C., Cheung, K. L., Chang, C. S., & Yang, Y. H. (2014). Interruption and non-adherence to long-term adjuvant hormone therapy is associated with adverse survival outcome of breast cancer women—An Asian population-based study. PLoS ONE, 9, e87027. doi:10.1371/journal.pone.0087027

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ibrahim, A. R., Eliasson, L., Apperley, J. F., Milojkovic, D., Bua, M., Szydlo, R., et al. (2011). Poor adherence is the main reason for loss of CCyR and imatinib failure for chronic myeloid leukemia patients on long-term therapy. Blood, 117, 3733–3736.

    Article  CAS  PubMed  Google Scholar 

  • Ivanova, J. I., Bergman, R. E., Birnbaum, H. G., Phillips, A. L., Stewart, M., & Meletiche, D. M. (2012). Impact of medication adherence to disease-modifying drugs on severe relapse, and direct and indirect costs among employees with multiple sclerosis in the US. Journal of Medical Economics, 15, 601–609.

    Article  CAS  PubMed  Google Scholar 

  • Juarez, D. T., Tan, C., Davis, J., & Mau, M. (2013). Factors affecting sustained medication adherence and its impact on healthcare utilization in patients with diabetes. Journal of Pharmaceutical Health Services Research, 4, 89–94.

    Article  PubMed  PubMed Central  Google Scholar 

  • Knapp, M., King, D., Pugner, K., & Lapuerta, P. (2004). Non-adherence to antipsychotic medication regimens: Associations with resource use and costs. The British Journal of Psychiatry, 184, 509–516.

    Article  PubMed  Google Scholar 

  • Lilienfeld, S. O. (2014). DSM-5: Centripetal scientific and centrifugal antiscientific forces. Clinical Psychology: Science and Practice, 21, 269–279.

    Google Scholar 

  • Lubke, G. H., & Miller, P. J. (2015). Does nature have joints worth carving? A discussion of taxometrics, model-based clustering and latent variable mixture modeling. Psychological Medicine, 45, 705–715.

    Article  CAS  PubMed  Google Scholar 

  • Lubke, G., & Tueller, S. (2010). Latent class detection and class assignment: A comparison of the MAXEIG taxometric procedure and factor mixture modeling approaches. Structural Equation Modeling, 17, 605–628.

    Article  PubMed  PubMed Central  Google Scholar 

  • MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002). On the practice of dichotomization of quantitative variables. Psychological Methods, 7, 19.

    Article  PubMed  Google Scholar 

  • Maggiolo, F., Airoldi, M., Kleinloog, H. D., Callegaro, A., Ravasio, V., Arici, C., et al. (2007). Effect of adherence to HAART on virologic outcome and on the selection of resistance-conferring mutations in NNRTI-or PI-treated patients. HIV Clinical Trials, 8, 282–292.

    Article  PubMed  Google Scholar 

  • McFadden, D. (1974). Conditional logit analysis of qualitative choice behavior. In P. Zarembka (Ed.), Frontiers in econometrics (pp. 105–142). New York, NY: Academic Press.

    Google Scholar 

  • Menard, S. (2000). Coefficients of determination for multiple logistic regression analysis. The American Statistician, 54, 17–24.

    Google Scholar 

  • Nakonezny, P. A., Byerly, M. J., & Rush, A. J. (2008). Electronic monitoring of antipsychotic medication adherence in outpatients with schizophrenia or schizoaffective disorder: An empirical evaluation of its reliability and predictive validity. Psychiatry Research, 157, 259–263.

    Article  PubMed  Google Scholar 

  • Nichols, G. A., Rosales, A. G., Kimes, T. M., Tunceli, K., Kurtyka, K., Mavros, P., & Steiner, J. F. (2015). Impact on glycated haemoglobin of a biological response-based measure of medication adherence. Diabetes, Obesity & Metabolism, 17, 843–848. doi:10.1111/dom.12476

    Article  CAS  Google Scholar 

  • Olfson, M., Mechanic, D., Hansell, S., Boyer, C. A., Walkup, J., & Weiden, P. J. (2014). Predicting medication noncompliance after hospital discharge among patients with schizophrenia. Psychiatric Services, 51, 216–222.

    Article  Google Scholar 

  • Onyebuchi, A. K., Lawani, L. O., Iyoke, C. A., Onoh, C. R., & Okeke, N. E. (2014). Adherence to intermittent preventive treatment for malaria with sulphadoxine-pyrimethamine and outcome of pregnancy among parturients in South East Nigeria. Patient Preference and Adherence, 8, 447–452. doi:10.2147/PPA.S61448

    PubMed  PubMed Central  Google Scholar 

  • Peterson, A. M., Nau, D. P., Cramer, J. A., Benner, J., Gwadry-Sridhar, F., & Nichol, M. (2007). A checklist for medication compliance and persistence studies using retrospective databases. Value in Health, 10, 3–12. doi:10.1111/j.1524-4733.2006.00139.x

    Article  PubMed  Google Scholar 

  • Pringle, J. L., Boyer, A., Conklin, M. H., McCullough, J. W., & Aldridge, A. (2014). The Pennsylvania Project: Pharmacist intervention improved medication adherence and reduced health care costs. Health Affairs, 33, 1444–1452.

    Article  PubMed  Google Scholar 

  • R Core Team. (2015). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. http://www.R-project.org/

  • Remington, G., Kwon, J., Collins, A., Laporte, D., Mann, S., & Christensen, B. (2007). The use of electronic monitoring (MEMS®) to evaluate antipsychotic compliance in outpatients with schizophrenia. Schizophrenia Research, 90, 229–237.

    Article  PubMed  Google Scholar 

  • Roebuck, M. C., Liberman, J. N., Gemmill-Toyama, M., & Brennan, T. A. (2011). Medication adherence leads to lower health care use and costs despite increased drug spending. Health Affairs, 30, 91–99.

    Article  PubMed  Google Scholar 

  • Shentu, Y., & Xie, M. (2010). A note on dichotomization of continuous response variable in the presence of contamination and model misspecification. Statistics in Medicine, 29, 2200–2214.

    Article  PubMed  Google Scholar 

  • Simpson, S. H., Eurich, D. T., Majumdar, S. R., Padwal, R. S., Tsuyuki, R. T., Varney, J., & Johnson, J. A. (2006). A meta-analysis of the association between adherence to drug therapy and mortality. British Medical Journal, 333, 15. doi:10.1136/bmj.38875.675486.55

    Article  PubMed  PubMed Central  Google Scholar 

  • Sokol, M. C., McGuigan, K. A., Verbrugge, R. R., & Epstein, R. S. (2005). Impact of medication adherence on hospitalization risk and healthcare cost. Medical Care, 43, 521–530.

    Article  PubMed  Google Scholar 

  • Sun, S. X., Liu, G. G., Christensen, D. B., & Fu, A. Z. (2007). Review and analysis of hospitalization costs associated with antipsychotic nonadherence in the treatment of schizophrenia in the United States. Current Medical Research and Opinion, 23, 2305–2312. doi:10.1185/030079907X226050

    Article  PubMed  Google Scholar 

  • Svarstad, B., Shireman, T., & Sweeney, J. (2001). Using drug claims data to assess the relationship of medication adherence with hospitalization and costs. Psychiatric Services, 52, 805–811.

    Article  CAS  PubMed  Google Scholar 

  • Swanson, J. W., Swartz, M. S., Van Dorn, R. A., Elbogen, E. B., Wagner, H. R., Rosenheck, R. A., et al. (2006). A national study of violent behavior in persons with schizophrenia. Archives of General Psychiatry, 63, 490–499.

    Article  PubMed  Google Scholar 

  • Swanson, J. W., Swartz, M. S., Van Dorn, R. A., Volavka, J., Monahan, J., Stroup, T. S., et al. (2008). Comparison of antipsychotic medication effects on reducing violence in people with schizophrenia. The British Journal of Psychiatry, 193, 37–43.

    Article  PubMed  PubMed Central  Google Scholar 

  • Swanson, J., Van Dorn, R. A., & Swartz, M. S. (2007). Effectiveness of atypical antipsychotics for substance use in schizophrenia patients. Schizophrenia Research, 94, 114–118.

    Article  PubMed  Google Scholar 

  • Swartz, M. S., Swanson, J. W., Hiday, V. A., Borum, R., Wagner, H. R., & Burns, B. J. (1998a). Violence and severe mental illness: The effects of substance abuse and nonadherence to medication. American Journal of Psychiatry, 155, 226–231.

    CAS  PubMed  Google Scholar 

  • Swartz, M. S., Swanson, J. W., Hiday, V. A., Borum, R., Wagner, R., & Burns, B. J. (1998b). Taking the wrong drugs: The role of substance abuse and medication noncompliance in violence among severely mentally ill individuals. Social Psychiatry and Psychiatric Epidemiology, 33, S75–S80.

    Article  PubMed  Google Scholar 

  • Valenstein, M., Copeland, L. A., Blow, F. C., McCarthy, J. F., Zeber, J. E., Gillon, L., et al. (2002). Pharmacy data identify poorly adherent patients with schizophrenia at increased risk for admission. Medical Care, 40, 630–639.

    Article  PubMed  Google Scholar 

  • Valenstein, M., Ganoczy, D., McCarthy, J. F., Myra, K. H., Lee, T. A., & Blow, F. C. (2006). Antipsychotic adherence over time among patients receiving treatment for schizophrenia: A retrospective review. The Journal of Clinical Psychiatry, 67, 1542–1550.

    Article  PubMed  Google Scholar 

  • Van Dorn, R. A., Desmarais, S. L., Petrila, J., Haynes, D., & Singh, J. P. (2013). Effects of outpatient treatment on risk of arrest of adults with serious mental illness and associated costs. Psychiatric Services, 64, 856–862.

    Article  PubMed  Google Scholar 

  • Vestbo, J., Anderson, J. A., Calverley, P. M., Celli, B., Ferguson, G. T., Jenkins, C., et al. (2009). Adherence to inhaled therapy, mortality and hospital admission in COPD. Thorax, 64, 939–943.

    Article  CAS  PubMed  Google Scholar 

  • Wei, L., Fahey, T., & MacDonald, T. M. (2008). Adherence to statin or aspirin or both in patients with established cardiovascular disease: Exploring healthy behaviour vs. drug effects and 10-year follow-up of outcome. British Journal of Clinical Pharmacology, 66, 110–116.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Weiden, P. J., Kozma, C., Grogg, A., & Locklear, J. (2004). Partial compliance and risk of rehospitalization among California Medicaid patients with schizophrenia. Psychiatric Services, 55, 886–891.

    Article  PubMed  Google Scholar 

  • Wood, E., Hogg, R. S., Yip, B., Harrigan, P. R., O’Shaughnessy, M. V., & Montaner, J. S. (2003). Effect of medication adherence on survival of HIV-infected adults who start highly active antiretroviral therapy when the CD4 + cell count is 0.200 to 0.350 × 109 cells/L. Annals of Internal Medicine, 139, 810–816.

    Article  PubMed  Google Scholar 

  • Yasuda, J. M., Miller, C., Currier, J. S., Forthal, D. N., Kemper, C. A., Beall, G. N., et al. (2004). The correlation between plasma concentrations of protease inhibitors, medication adherence and virological outcome in HIV-infected patients. Antiviral Therapy, 9, 753–762.

    CAS  PubMed  Google Scholar 

  • Yen, C. F., Chen, C. S., Ko, C. H., Yeh, M. L., Yang, S. J., Yen, J. Y., et al. (2005). Relationships between insight and medication adherence in outpatients with schizophrenia and bipolar disorder: Prospective study. Psychiatry and Clinical Neurosciences, 59, 403–409.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This study was supported by National Institute of Mental Health (1R03MH103477-01A1).

Author information

Authors and Affiliations

  1. RTI International, 3040 E. Cornwallis Road, P.O. Box 12194, Research Triangle Park, NC, 27709, USA

    Stephen J. Tueller & Richard A. Van Dorn

  2. University of Kansas, Lawrence, KS, USA

    Pascal R. Deboeck

Authors
  1. Stephen J. Tueller
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pascal R. Deboeck
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Richard A. Van Dorn
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Stephen J. Tueller.

Ethics declarations

Conflicts of interest

Stephen J. Tueller, Pascal R. Deboeck and Richard A. Van Dorn declare that they have no conflict of interest.

Human and animal rights and Informed consent

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 patients for being 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

Tueller, S.J., Deboeck, P.R. & Van Dorn, R.A. Getting less of what you want: reductions in statistical power and increased bias when categorizing medication adherence data. J Behav Med 39, 969–980 (2016). https://doi.org/10.1007/s10865-016-9727-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10865-016-9727-9

Keywords

Search

Navigation