At a glance
ClinicalIndex Comparison RecordStandardized by ClinicalIndex from the ClinicalTrials.gov record · verify against the source.
Concept Mapping as a Scalable Method for Identifying Patient-Important Outcomes
In Brief
An observational study evaluating Interviews and Concept Mapping (CM) for Concept Mapping Versus Interviews. Completed, enrolled 148 participants across 1 site.
Detailed Summary
The goal of this study is to improve the methods with which researchers identify patient centered outcomes for use in research. Specifically, the investigators will test the application of concept mapping as compared to one-on-one interviews as a comprehensive and efficient method of identifying patient-important outcomes for use in research.
Study Details
Timeline
Interventions
Patients will be engaged in open-ended, semi-structured qualitative interviews, which will be performed one-on-one either in person or over the phone (depending on the healthcare setting that they are recruited from). Qualitative interviews will be audio recorded, with the patient's permission, transcribed, de-identified and entered into NVivo software for coding and analysis.
The CM process consists of 3 steps that take place over 3 sessions: Step 1: Generation of Ideas- Participants brainstorm and generate responses to the focus statement. Once the group agrees that no new statements are being generated, the list of statements is reviewed within the group. Step 2: Structuring of Statements- Each participant is given a set of sort cards and asked to sort the statements into piles. Participants then rate each idea regarding importance. Research staff enters this information into the CM software. Concept Systems Global Software generates point maps using a technique that detects underlying similarities/differences between statements. The CM software then uses hierarchical cluster analysis to draw boundaries around the point map to create conceptual clusters. Step 3: Interpretation- The CM group revises the concept map. Participants review the cluster names suggested by the software and decide upon final naming of each cluster as a group.