Measuring the Preferences of Patients With Type II Diabetes Using Best-worst Scaling and Discrete Choice Experiment

Completed

Conditions: Type II Diabetes

Interventions: Other: Best-Worst Scaling (Case 2)
Other: Discrete Choice Experiment

Registration Number: NCT02637622

Lead Sponsor: Johns Hopkins Bloomberg School of Public Health

Brief Summary: In 2012, the FDA Center for Devices and Radiological Health (CDRH) issued guidance to clarify the principal benefit-risk factors FDA considers during the reviews for premarket approval applications and de novo classification requests. In addition to a detailed description of benefits and risks, CDRH listed "patient tolerance for risk and perspective on benefit" as a factor that CDRH may consider in regulatory reviews. It underlined the need for developing methods to measure patient preference and incorporate it into regulatory decision-making. The purpose of this study is to advance methods for patient and community engagement in patient-centered outcome research (PCOR) and has three objectives.

First, demonstrate good practices for patient and community involvement in PCOR projects by applying principles of community-based participatory research (CBPR).

Second, address methodological gaps pertaining to the use of stated-preference methods in studying preferences in PCOR. These include identifying the best methods for designing a preference study and strategies for analyzing variation in preferences. The investigators also seek to assess the relevance of stated-preference methods to patients and stakeholders using both qualitative and quantitative methods.

Third, demonstrate good practices for applying stated-preference methods by studying the preferences of patients with type II diabetes. While type II diabetes provides an important case study, this research will advance approaches and methods that will be broadly generalizable to other diseases, and to diverse patient and stakeholder groups.

Clinical Significance:

This project will illustrate and advance methods for assessing the values of patients and stakeholders. It will demonstrate how CBPR methods apply to PCOR studies and the value of stated-preference methods in measuring the preferences of patients and stakeholders and directing health care.

Detailed Description: This study will apply the principles of CBPR to involve patients and stakeholders associated with a local community board and a national diabetes advisory board in key decisions in the project. During year 1, the investigators will utilize mixed methods to develop, pretest, and pilot the survey instruments to assess the preferences of patients with type II diabetes. In year 2, the investigators plan further engagement to finalize the survey instruments, and will implement a nationally representative, racially/ethnically diverse sample of patients with type II diabetes. Based on further consultation, the investigators will conduct statistical analysis, including stratified analyses and segmentation of patients with similar preferences. In year 3, mixed methods will be applied to assess beliefs of patients and other consumers about the relevance of this work and its generalizability to other PCOR topics. Finally, lay language reports will be developed to highlight patient and stakeholder engagement and the application of stated-preference methods to the study of the preferences of patients with type II diabetes.

Recruitment & Eligibility

Status: COMPLETED

Sex: All

Target Recruitment: 1103

Inclusion Criteria

Participate in the GfK's KnowledgePanel
Self-reported Type II diabetes diagnosis

Exclusion Criteria

Does not have Type II diabetes diagnosis
Unable to communicate in English or Spanish

Study & Design

Study Type: OBSERVATIONAL

Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Best-Worst Scaling (Case 2)	Best-Worst Scaling (Case 2)	Preference elicitation survey using a best-worst scaling method.
Discrete Choice Experiment	Discrete Choice Experiment	Preference elicitation survey using a discrete choice experiment method.

Primary Outcome Measures

Name	Time	Method
Patient Medication Preference as Estimated by a Choice Model	One-time survey	Preference estimate for each medicine attribute level from a conditional logit regression analysis. For each arm, there were six attributes of the medication, with 3 levels each. Within each attribute the parameter estimates for each of the levels sum to 0. If a parameter estimate for a level is above (below) 0 then the parameter is higher (lower) than average for that medication attribute.
Weight Respondents Assign to Medication Attribute (Relative Attribute Importance) Assessed by a Choice Model	One-time survey	Relative attribute importance (RAI) for each attribute in each arm measures the overall importance of that attribute. It is estimated by subtracting the lowest parameter estimate from the highest parameter estimate within each attribute. The RAI was then re-scaled on a 0 to 10 scale with 0 demonstrating no importance and 10 reflecting the most important attribute in each arm.

Secondary Outcome Measures

Name	Time	Method
Self-reported Difficulty in Understanding and Answering the Survey Questions	One-time survey	Questions that asked the respondents to evaluate if the Best-Worst Scaling (BWS) or Discrete Choice Experiment (DCE tasks were easy to understand and answer.