A Systematic Review Comparing the Acceptability, Validity and Concordance of Discrete Choice Experiments and Best–Worst Scaling for Eliciting Preferences in Healthcare

Whitty, Jennifer A.; Gonçalves, Ana Sofia Oliveira

doi:10.1007/s40271-017-0288-y

Cited by 30 publications

(22 citation statements)

References 58 publications

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“…The majority of studies were DCEs (63%) followed by CA (37%). BWS was conducted in only two studies possibly reflecting the more recent introduction of BWS in health research [31]. Our review supports the increasing applications of stated-preference methods in the field of HIV research as well as the diverse uses of stated-preference research to advance knowledge about the global HIV epidemic.…”

Section: Discussionsupporting

confidence: 64%

“…We conducted a systematic search following the Cochrane Collaboration guidelines and report our findings using the PRISMA-ScR (S1 Table) [26–28]. Our search criteria was informed by recent systematic reviews of the literature of health-related, stated-preference studies (S2 Table) [1, 2, 29–31]. We searched PubMed (indexed since 1945), Embase (indexed since 1947 and includes conference abstracts), PsycINFO (indexed since 1967 and includes conference abstracts), and the Cumulative Index to Nursing and Allied Health Literature (CINAHL; indexed since 1990), using text and MeSH terms exploded to include all subheadings.…”

Section: Methodsmentioning

confidence: 99%

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Stated-preference research in HIV: A scoping review

et al. 2019

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Discrete choice experiments (DCE), conjoint analysis (CA), and best-worst scaling (BWS) are quantitative techniques for estimating consumer preferences for products or services. These methods are increasingly used in healthcare research, but their applications within the field of HIV research have not yet been described. The objective of this scoping review was to systematically map the extent and nature of published DCE, CA, and BWS studies in the field of HIV and identify priority areas where these methods can be used in the future. Online databases were searched to identify published HIV-related DCE, CA and BWS studies in any country and year as the primary outcome. After screening 1,496 citations, 57 studies were identified that were conducted in 26 countries from 2000–2017. The frequency of published studies increased over time and covered HIV themes relating to prevention (n = 25), counselling and testing (n = 10), service delivery (n = 10), and antiretroviral therapy (n = 12). Most studies were DCEs (63%) followed by CA (37%) and BWS (4%). The median [IQR] sample size was 288 [138–496] participants, and 74% of studies used primary qualitative data to develop attributes. Only 30% of studies were conducted in sub-Saharan Africa where the burden of HIV is highest. Moreover, few studies surveyed key populations including men who have sex with men, transgender people, pregnant and postpartum women, adolescents, and people who inject drugs. These populations represent priorities for future stated-preference research. This scoping review can help researchers, policy makers, program implementers, and health economists to better understand the various applications of stated-preference research methods in the field of HIV.

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Section: Discussionsupporting

confidence: 64%

Section: Methodsmentioning

confidence: 99%

Stated-preference research in HIV: A scoping review

et al. 2019

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“…Conjoint analysis is a promising set of methods for eliciting stakeholder preferences that may overcome these limitations by engaging stakeholders in an intuitive yet powerful set of choice tasks that closely mimic real-life decisions and that can be easily implemented in large samples (12). By requiring respondents to consider trade-offs across a set of choices, conjoint analysis generates highly-accurate estimates of implicit preferences for a targeted set of objects (e.g., implementation strategies) in a timee cient, cost-effective, and generalizable manner (12)(13)(14)(15). These methods are especially valuable when the set of objects are carefully derived through elicitation work within the target population and when information on actual behavior or decisions are unavailable (or unobtainable), as is typically the case in implementation (16).…”

Section: Introductionmentioning

confidence: 99%

Community Stakeholder Preferences for Evidence-Based Practice Implementation Strategies in Behavioral Health: A Best-Worst Scaling Choice Experiment

Williams

Candon

Stewart

et al. 2020

Preprint

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Background: Community behavioral health clinicians, supervisors, and administrators play an essential role in implementing new psychosocial evidence-based practices (EBP) for patients receiving psychiatric care; however, little is known about these stakeholders’ values and preferences for implementation strategies that support EBP use, nor how best to elicit, quantify, or segment their preferences. This study sought to quantify clinician, supervisor, and administrator preferences for implementation strategies and to identify segments of these stakeholders with distinct preferences using a rigorous choice experiment method called best-worst scaling (BWS). Methods: A total of 240 clinicians, 74 clinical supervisors, and 29 administrators delivering publicly funded behavioral health services in a large metropolitan behavioral health system participated in a best-worst scaling choice experiment. Participants evaluated 14 implementation strategies developed through extensive elicitation and pilot work within the target system. Preference weights were generated for each strategy using hierarchical Bayesian estimation. Latent class analysis identified segments of stakeholders with unique preference profiles. Results: On average, clinicians, supervisors, and administrators preferred two strategies significantly more than all others—compensation for use of EBP per session and compensation for preparation time to use the EBP; two strategies were preferred significantly less than all others—performance feedback via email and performance feedback via leaderboard. However, latent class analysis identified four distinct segments of stakeholders with unique preferences: Segment 1 (n = 121, 35%) strongly preferred financial incentives over all other approaches; Segment 2 (n = 80, 23%) preferred technology-based strategies; Segment 3 (n = 52, 15%) preferred an improved waiting room to enhance client readiness and strongly disliked any type of clinical consultation; Segment 4 (n = 90, 26%) rejected financial incentives and strongly preferred strategies focused on clinical consultation. Conclusions: The presence of four heterogeneous subpopulations within this large group of behavioral health administrators, supervisors, and clinicians suggests optimal implementation may be achieved through targeted strategies derived via elicitation of stakeholder preferences. Best-worst scaling is a feasible, systematic, and rigorous method for eliciting stakeholders’ implementation preferences and identifying subpopulations with unique preferences in behavioral health settings.

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“…Best-worst scaling (BWS) is an elicitation method that has been used to measure people's preferences, including health related choices and policy problems requiring prioritization [16][17][18][19][20]. For example, BWS has been utilized to measure patient and caregiver health preferences to guide clinical decision making [21][22][23], inform health interventions [24,25], and measure public preferences for funding health technologies [19].…”

Section: Introductionmentioning

confidence: 99%

Health versus other sectors: Multisectoral resource allocation preferences in Mukono district, Uganda

Yemeke¹,

Ekirapa-Kiracho²,

Mutebi³

et al. 2020

PLoS ONE

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Objectives To elicit citizen preferences for national budget resource allocation in Uganda, examine respondents' preferences for health vis-à-vis other sectors, and compare these preferences with actual government budget allocations. Methods We surveyed 432 households in urban and rural areas of Mukono district in central Uganda. We elicited citizens' preferences for resource allocation across all sectors using a bestworst scaling (BWS) survey. The BWS survey consisted of 16 sectors corresponding to the Uganda national budget line items. Respondents chose, from a subset of four sectors across 16 choice tasks, which sectors they thought were most and least important to allocate resources to. We utilized the relative best-minus-worst score method and a conditional logistic regression to obtain ranked preferences for resource allocation across sectors. We then compared the respondents' preferences with actual government budget allocations. Results The health sector was the top ranked sector where 82% of respondents selected health as the most important sector for the government to fund, but it was ranked sixth in national budget allocation, encompassing 6.4% of the total budget. Beyond health, water and environment, agriculture, and social development sectors were largely underfunded compared to respondents' preferences. Works and transport, education, security, and justice, law and order received a larger share of the national budget compared to respondents' preferences.

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A Systematic Review Comparing the Acceptability, Validity and Concordance of Discrete Choice Experiments and Best–Worst Scaling for Eliciting Preferences in Healthcare

Cited by 30 publications

References 58 publications

Stated-preference research in HIV: A scoping review

Stated-preference research in HIV: A scoping review

Community Stakeholder Preferences for Evidence-Based Practice Implementation Strategies in Behavioral Health: A Best-Worst Scaling Choice Experiment

Health versus other sectors: Multisectoral resource allocation preferences in Mukono district, Uganda

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