Evidence map›Paper›PMID 36834057›Full record

ArticleInternational journal of environmental research and public health2023

The Role of Web-Based Adaptive Choice-Based Conjoint Analysis Technology in Eliciting Patients' Preferences for Osteoarthritis Treatment.

Basem Al-Omari, Joviana Farhat, Mujahed Shraim

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Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Basem Al-OmariDepartment of Epidemiology and Population Health, College of Medicine and Health Sciences, Khalifa University, Abu Dhabi P.O. Box 127788, United Arab Emirates.ORCID 0000-0002-7804-8050
Joviana FarhatDepartment of Epidemiology and Population Health, College of Medicine and Health Sciences, Khalifa University, Abu Dhabi P.O. Box 127788, United Arab Emirates.
Mujahed ShraimDepartment of Public Health, College of Health Sciences, Qatar University, QU Health, Doha P.O. Box 2713, Qatar.ORCID 0000-0001-7972-8210

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo assess the feasibility of using adaptive choice-based conjoint (ACBC) analysis to elicit patients' preferences for pharmacological treatment of osteoarthritis (OA), patients' satisfaction with completing the ACBC questionnaire, and factors associated with questionnaire completion time.

methodsAdult patients aged 18 years and older with a medical diagnosis of OA, experiencing joint pain in the past 12 months, and living in the Northeast of England participated in the study. The participants completed a web-based ACBC questionnaire about their preferences regarding pharmaceutical treatment for OA using a touchscreen laptop independently, and accordingly, the questionnaire completion time was measured. Moreover, the participants completed a pen-and-paper feedback form about their experience in completing the ACBC questionnaire.

resultsTwenty participants aged 40 years and older, 65% females, 75% had knee OA, and suffering from OA for more than 5 years participated in the study. About 60% of participants reported completing a computerized questionnaire in the past. About 85% of participants believed that the ACBC task helped them in making decisions regarding their OA medications, and 95% agreed or strongly agreed that they would be happy to complete a similar ACBC questionnaire in the future. The average questionnaire completion time was 16 min (range 10-24 min). The main factors associated with longer questionnaire completion time were older age, never using a computer in the past, and no previous experience in completing a questionnaire.

conclusionsThe ACBC analysis is a feasible and efficient method to elicit patients' preferences for pharmacological treatment of OA, which could be used in clinical settings to facilitate shared decision-making and patient-centered care. The ACBC questionnaire completion consumes a significantly longer time for elderly participants, who never used a computer, and never completed any questionnaire previously. Therefore, the contribution of patients and public involvement (PPI) group in the development of the ACBC questionnaire could facilitate participants' understanding and satisfaction with the task. Future research including patients with different chronic conditions may provide more useful information about the efficiency of ACBC analysis in eliciting patients' preferences for osteoarthritis treatment.

Indexed as

Osteoarthritis, KneePatient PreferenceAdultAgedDecision MakingFemaleHumansInternetMaleMiddle AgedPatient Satisfactionadaptive choice-based conjointconjoint analysisosteoarthritispatients’ preferencesshared decision makingweb-based

Identifiers

PMID36834057
PMCPMC9959784

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.