CAPTURING PREFERENCE DYNAMICS IN DHT-SUPPORTED OBESITY CARE: A LONGITUDINAL HEALTH PREFERENCE RESEARCH STUDY EMBEDDED IN THE UNIFIED OBESITY USE CASE
Author(s)
Axel Christian Mühlbacher, PhD1, Ann-Kathrin Fischer, BSc, MSc2, Joanna Goralska, PhD3, Urszula Razny, PhD3, Malgorzata Malczewska-Malec, Prof. PhD3.
1Hochschule Neubrandenburg, Neubrandenburg, Germany, 2M.Sc., Hochschule Neubrandenburg, Neubrandenburg, Germany, 3Jagiellonian University Medical College, Kraków, Poland.
1Hochschule Neubrandenburg, Neubrandenburg, Germany, 2M.Sc., Hochschule Neubrandenburg, Neubrandenburg, Germany, 3Jagiellonian University Medical College, Kraków, Poland.
OBJECTIVES: Patient preference studies often capture preferences at a single point, although preferences may change over time. This study aims to quantify longitudinal preferences among adults living with obesity for two complementary domains: clinical outcomes relevant to obesity management and interaction-related characteristics of Digital Health Technologies (DHTs).
METHODS: This protocol presents the methodological concept of a patient preference study embedded in a UNIFIED clinical study involving adults living with obesity. The clinical study includes a control group receiving standard care and an experimental group receiving DHT-supported care to measure selected health- and behavior-related parameters. Qualitative interviews in Germany and Poland will inform attribute and level development. The Outcome-DCE will use the ICHOM Set of Patient-Centered Outcome Measures for Adults Living with Obesity as a structured starting point for identifying relevant outcome domains. The Interaction-DCE will assess DHT characteristics related to usability, support, feedback, care integration, privacy, and compatibility with daily life. Both components will use Best Worst Scaling Case 3 tasks. The Outcome-DCE will be administered at baseline and 6 months. The Interaction-DCE will be administered at 3 and 6 months.
RESULTS: The study will estimate utility coefficients, relative attribute importance, trade-offs, preference heterogeneity, latent preference patterns, and changes in preferences over time. Exploratory analyses will examine associations between preference changes, clinical outcomes, DHT-derived measures, and digital engagement.
CONCLUSIONS: This protocol addresses a key methodological limitation of preference research by presenting a design in which repeated preference elicitation directly accompanies a clinical DHT-supported obesity study. This integration creates the opportunity to examine preferences prospectively over time, across intervention and control groups, and in relation to clinical outcomes, DHT-derived measures, and digital engagement patterns. The study will assess whether patients’ valuation of clinical outcomes and digital interaction characteristics remains stable or changes with treatment experience and exposure to DHT-supported care.
METHODS: This protocol presents the methodological concept of a patient preference study embedded in a UNIFIED clinical study involving adults living with obesity. The clinical study includes a control group receiving standard care and an experimental group receiving DHT-supported care to measure selected health- and behavior-related parameters. Qualitative interviews in Germany and Poland will inform attribute and level development. The Outcome-DCE will use the ICHOM Set of Patient-Centered Outcome Measures for Adults Living with Obesity as a structured starting point for identifying relevant outcome domains. The Interaction-DCE will assess DHT characteristics related to usability, support, feedback, care integration, privacy, and compatibility with daily life. Both components will use Best Worst Scaling Case 3 tasks. The Outcome-DCE will be administered at baseline and 6 months. The Interaction-DCE will be administered at 3 and 6 months.
RESULTS: The study will estimate utility coefficients, relative attribute importance, trade-offs, preference heterogeneity, latent preference patterns, and changes in preferences over time. Exploratory analyses will examine associations between preference changes, clinical outcomes, DHT-derived measures, and digital engagement.
CONCLUSIONS: This protocol addresses a key methodological limitation of preference research by presenting a design in which repeated preference elicitation directly accompanies a clinical DHT-supported obesity study. This integration creates the opportunity to examine preferences prospectively over time, across intervention and control groups, and in relation to clinical outcomes, DHT-derived measures, and digital engagement patterns. The study will assess whether patients’ valuation of clinical outcomes and digital interaction characteristics remains stable or changes with treatment experience and exposure to DHT-supported care.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
SA89
Topic
Methodological & Statistical Research, Patient-Centered Research, Study Approaches
Topic Subcategory
Surveys & Expert Panels
Disease
Diabetes/Endocrine/Metabolic Disorders (including obesity)