Guidelines for using the Voils two-part measure of medication nonadherence

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Brice Daniels
5 years ago
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1 Guidelines for using the Voils two-part measure of medication nonadherence Part 1: Extent of nonadherence (3 items) The items in the Extent scale are worded generally enough to apply across different research applications (patients, diseases, or medications) without being modified. Initial psychometric testing with patients treated for hypertension supported the reliability (alpha = 0.84) and validity of the extent scale (Voils et al., 2012). We encourage further confirmation of the psychometric properties of the Extent scale in new populations. The item response category consistent with perfect adherence (i.e., strongly disagree for the agreement response scale; none of the time or never for the frequency response scale) should be assigned a value of 1, and the item response category reflecting most nonadherence should be assigned a value of 5 (i.e., strongly agree for agreement response scale; all of the time or always for the frequency response scale) to enable comparisons across patient populations. We recommend estimating a score when > 50% of the items are answered (i.e., 2 of the 3 items). The 3 items in the Extent scale can be averaged, with higher scores representing greater nonadherence. We recommend averaging the items (rather than summing them) to minimize the effect of missing on one item and to provide some context for interpreting the score range when it is bounded within the range of the response scale. Depending on the patient population, the summary score may not be normally distributed. We have dichotomized the scale such that any response other than perfect adherence on any item is considered nonadherent (e.g., code as 1), and a response of perfect adherence on all items is considered adherent (e.g., code as 0) (for example, see Voils et al. 2014). A categorization of nonadherence triggers the reasons for nonadherence scale. Part 2: Reasons for nonadherence (to be administered when patients report nonadherence on the extent of nonadherence items) The Reasons scale includes items (21 in the Medical Care publication) to identify possible reasons for nonadherence to prescribed treatment (e.g., forgot, too expensive). These reasons were based on qualitative methods with patients taking antihypertensive medications conducted by Gbenga Ogedegbe and colleagues. The questions are worded so they may be used in other research applications. The list is neither exhaustive nor fully inclusive of the possible reasons for nonadherence in various contexts. We expect that a subset of the reasons will be relevant to medications for other diseases but that additional reasons may need to be added to be relevant to the target disease/population. If the reasons measure is to be used in a new population, we recommend conducting literature review and, if possible, further qualitative evaluation (i.e., interviews or focus groups) to determine a priori 1) which reasons in the current list are appropriate and inappropriate; and 2) which reasons not listed in the current version might be appropriate to add to a version specific to your medication(s) of interest.

2 The items in the Reasons scale stand on their own as descriptions for why a participant may be nonadherent. We recommend against summing the items to estimate a total score. Unlike the Extent scale, the Reasons scale is a causal indicator model, so it is inappropriate to combine theoretically uncorrelated items (see Voils et al., 2011). A total score would only provide information on whether people are higher or lower in reporting reasons for nonadherence but would not provide information about which or how many reasons were endorsed, or the relative importance of any one reason. Because the Reasons scale is a causal indicator model, internal consistency reliability (i.e., Cronbach s alpha) is irrelevant (see Voils et al., 2011). Guidance for scale users We created the scales with funding from the NIH (R21 AG035233) with the intention that they be freely available, as our goal is to improve outcome measurement. Thus, permission is not needed to use the scales. Please cite the scales appropriately. If you use the scales, we would appreciate you sharing your results and any published paper(s) with us so that we can share performance characteristics with other users. We are happy to provide guidance on assessing the scale s psychometric properties. Please contact Dr. Voils at corrine.voils@dm.duke.edu. Until we have more information on the various modifications of the extent of nonadherence scale (response scales, item wording see below), scale users should decide which version is appropriate for their research question. We expect the alpha to be sufficiently high with either the agreement version (strongly disagree to strongly agree) or the frequency version (never, rarely, sometimes, often, always) of the response scale. Scale users should be aware that even minor changes to the wording of items or response scales may affect reliability and validity. Anyone who modifies our scale does so at his/her own risk and cannot assume that the reliability and validity will be supported. Altering scale items or response scales represents a modification to the Voils scales and should be explicitly stated as such in any presentations and manuscripts. Ideally, one should validate the measure in a new population to ensure that it will retain ideal psychometric properties. We make the following recommendations: o We realize that researchers may have few resources to carry out a full-scale validation before including the measure in a study. At minimum, to determine whether additional reasons need to be added, consider conducting 8-12 cognitive interviews or 1-2 focus groups with (1) patients of the target population representing diverse backgrounds (e.g., race/ethnicity, literacy levels, age), and/or (2) clinicians with appropriate expertise/knowledge. For brevity s sake, you may also evaluate whether some items could be dropped or a higher-order reason could be used in place of two or more reasons. o If resources permit, consider enrolling a small sample to evaluate the internal consistency reliability (alpha) of the extent of nonadherence items. Coefficient alpha is based on inter-item correlations, and the inter-item correlations should be positive and large in magnitude, so a sample size as few as 30 patients would provide meaningful information.

3 Modifications to scales As scale development is an iterative process, we are continuing to make minor modifications to the scale to optimize its performance. Accordingly, the version published in the 2012 Medical Care article may change over time. Please contact Dr. Corrine Voils to inquire about the most current version. Please note the following iteration that we have conducted to date: o Response scale: The response scale in Voils et al (2012) represented agreement (ranging from strongly disagree to strongly agree). Participant agreement may not map onto actual behavior, so a different response scale was considered. In a second study with a similar population of patients treated for hypertension, we changed the response scale to measure nonadherence frequency (never, rarely, sometimes, often, always) to see how this would affect item distributions and psychometric properties of the scale. The distributions were more skewed, with fewer patients selecting response categories consistent with nonadherence. The internal consistency reliability (coefficient alpha) across 4 occasions was 0.86, 0.78, 0.94, and The citation for this study is Voils (2014). o Inclusion of reverse-scored item: Scale developers often include one or more reversescored item to avoid acquiescence bias (i.e., respondents provide the same response to all questions). However, we found that including a reverse-scored item did not reduce acquiescence bias and, instead, reduced reliability of scores. In Voils 2012 and Voils 2014, the scale, which included a reverse-scored item, was administered orally by highly trained research staff and yielded highly reliable scores. In Weidenbacher 2015, the sane version of the scale was self-administered in written format in the context of a larger survey. Half of the responses to the reverse-scored item were inconsistent with the responses to the other two items, leading to an inter-item correlation of near 0. Accordingly, that item was dropped from analyses. To avoid this issue, in the second version of the scale (see next bullet), we modified the items so that all are worded and scored in the same direction. o Addressing nonadherence to regimens with different characteristics: Regimens for different medical problems vary in dosing frequency, requirements, and timing. We conducted a study to determine if the version validated in patients with hypertension would capture extent of nonadherence for hepatitis C medications. Hepatitis C provides an interesting contrast to hypertension as Hepatitis C medications are typically prescribed for a limited time period (versus lifelong for antihypertensive medications) and have a distinct set of side effects (e.g., depression) and consequences (e.g., drug resistance) that are not present for antihypertensive medications. Another important distinction is that, whereas most antihypertensive medications can be taken once per day with forgiving timings between doses, Hepatitis C regimens (until recently) involved multiple doses per day, and the timing between doses was critical to achieve maximum efficacy. At the time that we began this work, the most commonly prescribed regimen was oral telaprevir three times daily, oral ribavirin twice daily, and weekly interferon

4 injections. We knew that interferon was on its way out, so we studied how well the measure worked for the two oral medications. These Hepatitis C oral medications required strict timing with doses, such that they had to be taken within a 2-hour window or else skipped. Additionally, 20g of fat needed to be consumed with the telaprevir. We conducted cognitive interviews with Hepatitis C patients and found that phrases such as as prescribed and as directed were interpreted differently by this population (e.g., as prescribed meant within the 2-hour window and with the required 20g of fat). Accordingly, we developed a modified set of extent of nonadherence items that, as indicated by cognitive interviews, appropriately referred to missed doses rather than a specific time window (as this was our construct of interest different items would be needed to assess timing of medications if that is of interest). We also ensured that all of these modified items were scored in the same direction (see previous bullet). These modified extent of nonadherence items were based on the same latent variable model that informed the first version of the scale and therefore should produce reliable scores. We administered this refined version in a sample of patients with Hepatitis C who were initiating single-drug therapy. In this study, we will evaluate reliability, convergent validity, and predictive validity (via 12-week and 24-week viral load) of the modified version. Ongoing Studies (as of May 2016) Corrine Voils: predictive validity in patients with Hepatitis C Ian Kronish: convergent validity compared to electronic drug monitoring in patients post acute coronary syndrome Please let us know about your studies! Publications Voils, C. I., Hoyle, R. H., Thorpe, C., Maciejewski, M. L., & Yancy, W. S. Jr. (2011). On improving the measurement of medication nonadherence. Journal of Clinical Epidemiology, 64, PMID Part of Variance and Dissent section accompanied by the following rejoinders: Morisky, D. E., & DiMatteo, R. Improving the measurement of self-reported medication nonadherence: Response to authors. Journal of Clinical Epidemiology, 64, Voils, C. I., Hoyle, R. H., Thorpe, C., Maciejewski, M. L., & Yancy, W. S. Jr. (2011). On improving the measurement of medication nonadherence: Response to authors. Journal of Clinical Epidemiology, 64, Morisky, D. E., & DiMatteo, R. Improving the measurement of self-reported medication nonadherence: Final response. Journal of Clinical Epidemiology, 64,

5 Voils, C. I., Maciejewski, M. L., Hoyle, R. H., Reeve, B. B., Gallagher, P., Bryson, C. L., & Yancy Jr., W. S. (2012). Initial validation of a self-report measure of the extent of and reasons for medication nonadherence. Medical Care, 50(12), Accompanying editorial: Steiner, J. F. Self-reported adherence measures: What do they assess and how should we use them? Medical Care, 50(12), Voils, C. I., King, H. A., Neelon, B., Hoyle, R. H., Reeve, B. B., Maciejewski, M. L., & Yancy Jr., W. S. (2014). Characterizing weekly self-reported antihypertensive medication nonadherence across repeated occasions. Patient Preference and Adherence, 8, PMID: Weidenbacher, H., Beadles, C. A., Maciejewski, M. L., Reeve, B. B., & Voils, C. I. (2015). Extent and reasons for nonadherence to anti-hypertensive, cholesterol, and diabetes medications: The association with depressive symptom burden in a sample of American veterans. Patient Preference and Adherence, 9, PMID

Self Report Measures

Self Report Measures I. Measuring Self-Report Variables A. The Survey Research Method - Many participants are randomly (e.g. stratified random sampling) or otherwise (nonprobablility sampling) p.140-146