Exploring patient treatment decision making for osteoarthritis in the UAE: a cross-sectional adaptive choice-based conjoint study

Basem Al-Omari, Joviana Farhat, Mumtaz Khan, Hristo Grancharov, Zaki Abu Zahr, Sammy Hanna, Abdulla Alrahoomi

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: To assess osteoarthritis (OA) patients’ preferences for pharmaceutical treatment via Adaptive Choice-Based Conjoint (ACBC) method. Methods: A United Arab Emirates (UAE) based Patient and Public Involvement (PPI) group designed the ACBC questionnaire with 10 attributes and 34 levels. The questionnaire was developed using Sawtooth Software and analyzed through Hierarchical Bayesian (HB). Results were standardized using Z-score via SPSS. Results: Study participants were 1030 OA patients, 83.6% aged 50 or older and 83.4% female. The avoidance of medication’s side effects accounted for 66% relative importance compared to 6% relative importance for the medication’s benefits. The “way of taking the medicine” attribute had the highest coefficient of variation (70%) and the four side effect attributes “risk of gastric ulcer, addiction, kidney and liver impairment, and heart attacks and strokes” had a coefficient of variation from 18 to 21%. Conclusions: Arab OA patients are similar to other ethnic groups in trading-off benefits and side effects and consistently prioritizing the avoidance of medications’ side effects. Although the “Way of taking medicine” was the least important attribute it was associated with the highest variation amongst patients. OA patients also prefer prescribed medications to internet-purchased and over-the-counter options. © 2023, BioMed Central Ltd., part of Springer Nature.
Original languageAmerican English
JournalBMC Public Health
Volume23
Issue number1
DOIs
StatePublished - 2023

Keywords

  • Bayes theorem
  • cross-sectional study
  • decision making
  • epidemiology
  • female
  • human
  • male
  • osteoarthritis
  • patient preference
  • questionnaire
  • United Arab Emirates
  • Bayes Theorem
  • Cross-Sectional Studies
  • Decision Making
  • Female
  • Humans
  • Male
  • Osteoarthritis
  • Patient Preference
  • Surveys and Questionnaires

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