Can Patients Diagnosed with Schizophrenia Complete Choice-Based Conjoint Analysis Tasks?
ABSTRACT Schizophrenia is a severe mental illness associated with hallucinations, delusions, apathy, poor social functioning, and impaired cognition. Researchers and funders have been hesitant to focus efforts on treatment preferences of patients with schizophrenia because of the perceived cognitive burden that research methods, such as conjoint analysis, place on them.
The objective of this study was to test if patients diagnosed with schizophrenia were able to complete a choice-based conjoint analysis (often referred to as discrete-choice experiments) and to test if meaningful trade-offs were being made.
German outpatients diagnosed with schizophrenia were eligible to participate in this study if they were aged 18-65 years, had received treatment for at least 1 year and were not experiencing acute symptoms. Conjoint analysis tasks were based on six attributes, each with two levels, which were identified via a literature review and focus groups. A psychologist in a professional interview facility presented each respondent with the eight tasks with little explanation. All interviews were recorded, transcribed, and analyzed to verify that respondents understood the tasks. Preferences were assessed using logistic regression, with a correction for clustering.
We found evidence that the 21 patients diagnosed with schizophrenia participating in the study could complete conjoint analysis tasks in a meaningful way. Patients not only related to the scenarios presented in conjoint tasks, but explicitly stated that they used their own preferences to judge which scenarios were better. Statistical analysis confirmed all hypotheses about the attributes (i.e. all attributes had the expected sign). Having a supportive physician, not feeling slowed, and improvements in stressful situations (p < 0.01) were the most important attributes.
We found that patients diagnosed with schizophrenia can complete conjoint analysis tasks, that they base their decisions on their own preferences, and that patients make trade-offs between attributes.
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ABSTRACT: Background Through Patient-Focused Drug Development, the US Food and Drug Administration (FDA) documents the perspective of patients and caregivers and are currently conducting 20 public meetings on a limited number of disease areas. Parent Project Muscular Dystrophy (PPMD), an advocacy organization for Duchenne muscular dystrophy (DMD), has demonstrated a community-engaged program of preference research that would complement the FDA’s approach. Objective Our objective was to compare two stated-preference methods, best-worst scaling (BWS) and conjoint analysis, within a study measuring caregivers’ DMD-treatment preferences. Methods Within one survey, two preference-elicitation methods were applied to 18 potential treatments incorporating six attributes and three levels. For each treatment profile, caregivers identified the best and worst feature and intention to use the treatment. We conducted three analyses to compare the elicitation methods using parameter estimates, conditional attribute importance and policy simulations focused on the 18 treatment profiles. For each, concordance between the results was compared using Spearman’s rho. Results BWS and conjoint analysis produced similar parameter estimates (p p p Conclusions The observed concordance between approaches demonstrates the reliability of the stated-preference methods. Given the simplicity of combining BWS and conjoint analysis on single profiles, a combination approach is easily adopted. Minor irregularities for the conjoint-analysis results could not be explained by additional analyses and needs to be the focus of future research.The patient 12/2014; 8(1). DOI:10.1007/s40271-014-0104-x · 1.96 Impact Factor
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ABSTRACT: Background There is growing agreement that regulators performing benefit–risk evaluations should take patients’ and caregivers’ preferences into consideration. The Patient-Focused Drug Development Initiative at the US Food and Drug Administration offers patients and caregivers an enhanced opportunity to contribute to regulatory processes by offering direct testimonials. This process may be advanced by providing scientific evidence regarding treatment preferences through engagement of a broad community of patients and caregivers. Objective In this article, we demonstrate a community-engaged approach to measure caregiver preferences for potential benefits and risks of emerging therapies for Duchenne muscular dystrophy (DMD). Methods An advocacy oversight team led the community-engaged study. Caregivers’ treatment preferences were measured by using best–worst scaling (BWS). Six relevant and understandable attributes describing potential benefits and risks of emerging DMD therapies were identified through engagement with advocates (n = 5), clinicians (n = 9), drug developers from pharmaceutical companies and academic centers (n = 11), and other stakeholders (n = 5). The attributes, each defined across 3 levels, included muscle function, life span, knowledge about the drug, nausea, risk of bleeds, and risk of arrhythmia. Cognitive interviewing with caregivers (n = 7) was used to refine terminology and assess acceptability of the BWS instrument. The study was implemented through an online survey of DMD caregivers, who were recruited in the United States through an advocacy group and snowball sampling. Caregivers were presented with 18 treatment profiles, identified via a main-effect orthogonal experimental design, in which the dependent variable was the respondents’ judgment as to the best and worst feature in each profile. Preference weights were estimated by calculating the relative number of times a feature was chosen as best and as worst, which were then used to estimate relative attribute importance. Results A total of 119 DMD caregivers completed the BWS instrument; they were predominately biological mothers (67.2%), married (89.9%), and white (91.6%). Treatment effect on muscle function was the most important among experimental attributes (28.7%), followed by risk of heart arrhythmia (22.4%) and risk of bleeding (21.2%). Having additional postapproval data was relatively the least important attribute (2.3%). Conclusions We present a model process for advocacy organizations aiming to promote patient-centered drug development. The community-engaged approach was successfully used to develop and implement a survey to measure caregiver preferences. Caregivers were willing to accept a serious risk when balanced with a noncurative treatment, even absent improvement in life span. These preferences should inform the Food and Drug Administration’s benefit–risk assessment of emerging DMD therapies. This study highlights the synergistic integration of traditional advocacy methods and scientific approach to quantify benefit–risk preferences.Clinical Therapeutics 05/2014; 36(5):624–637. DOI:10.1016/j.clinthera.2014.04.011 · 2.59 Impact Factor
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ABSTRACT: Discrete choice experiments (DCEs) are increasingly used in health economics to address a wide range of health policy-related concerns.PharmacoEconomics 07/2014; 32(9). DOI:10.1007/s40273-014-0170-x · 3.34 Impact Factor