Using Best-Worst Scaling in Horizon Scanning for Hepatocellular Carcinoma Technologies

Gallego, Gisselle; Bridges, John F.P.; Flynn, Terry N.; Blauvelt, Barri M.; Niessen, Louis

doi:10.1017/s026646231200027x

Cited by 35 publications

(34 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(2) [33]USA201116411NR4100102 Gallego et al. [34]International201212011115101013 Marti [35]Switzerland2012376151611101014 Mazanov et al. [36]Australia201216811115101113 Silverman et al.…”

Section: Resultsmentioning

confidence: 99%

Using Best–Worst Scaling to Investigate Preferences in Health Care

et al. 2016

View full text Add to dashboard Cite

IntroductionBest–worst scaling (BWS) is becoming increasingly popular to elicit preferences in health care. However, little is known about current practice and trends in the use of BWS in health care. This study aimed to identify, review and critically appraise BWS in health care, and to identify trends over time in key aspects of BWS.MethodsA systematic review was conducted, using Medline (via Pubmed) and EMBASE to identify all English-language BWS studies published up until April 2016. Using a predefined extraction form, two reviewers independently selected articles and critically appraised the study quality, using the Purpose, Respondents, Explanation, Findings, Significance (PREFS) checklist. Trends over time periods (≤2010, 2011, 2012, 2013, 2014 and 2015) were assessed further.ResultsA total of 62 BWS studies were identified, of which 26 were BWS object case studies, 29 were BWS profile case studies and seven were BWS multi-profile case studies. About two thirds of the studies were performed in the last 2 years. Decreasing sample sizes and decreasing numbers of factors in BWS object case studies, as well as use of less complicated analytical methods, were observed in recent studies. The quality of the BWS studies was generally acceptable according to the PREFS checklist, except that most studies did not indicate whether the responders were similar to the non-responders.ConclusionUse of BWS object case and BWS profile case has drastically increased in health care, especially in the last 2 years. In contrast with previous discrete-choice experiment reviews, there is increasing use of less sophisticated analytical methods.Electronic supplementary materialThe online version of this article (doi:10.1007/s40273-016-0429-5) contains supplementary material, which is available to authorized users.

show abstract

“…(2) [33]USA201116411NR4100102 Gallego et al. [34]International201212011115101013 Marti [35]Switzerland2012376151611101014 Mazanov et al. [36]Australia201216811115101113 Silverman et al.…”

Section: Resultsmentioning

confidence: 99%

Using Best–Worst Scaling to Investigate Preferences in Health Care

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Previously we analyzed the data using both approaches [21,47], and, since they are highly correlated [20,26], we presented results from the more accessible maximum difference approach [19]. Given that we conducted the BWS analysis two ways, rescaled the parameters and calculated correlations to find the two analytic approaches to BWS to be virtually identical [19], we felt confident that using the conditional logit analytic approach for comparing BWS with conjoint analysis would not qualitatively change the results.…”

Section: Discussionmentioning

confidence: 99%

“…Specifically, PPMD developed a framework for feasible communityengaged benefit-risk assessment that included best-worst scaling (BWS) [19]. BWS is a recently developed method that is used with increasing frequency in health research [20][21][22][23][24][25][26][27][28]. Here we aim to compare this approach with conjoint analysis, a more common stated-preference technique [29].…”

Section: Introductionmentioning

confidence: 99%

Caregiver Preferences for Emerging Duchenne Muscular Dystrophy Treatments: A Comparison of Best-Worst Scaling and Conjoint Analysis

Hollin

Peay

Bridges

2014

Patient

View full text Add to dashboard Cite

show abstract

“…5 BWS belongs to the conjoint analysis family of methods, which collectively serve to identify preferences and trade-offs that contribute to individuals' choices with respect to "goods." 6 These methods have been noted for their cognitive and administrative simplicity, 7 as well as their focus on the patient perspective. 8,9 In this article, we present the BWS method in the context of cervical cancer screening priorities for homeless women.…”

Section: B Est-worst Scaling (Bws) Is a Survey Methods For Assessing Imentioning

confidence: 99%

“…BWS is considered superior to rating scales because it avoids common biases, 25 and superior to rankings because it is cognitively simpler to identify items that are the extremes among a list than those that are in a middle position (eg, the best and worst items of a list are relatively easy to identify, whereas the middle items of a list are more difficult to distinguish among). 7 Each set of 5 attributes was presented singly; a sample question is given in Figure 1. The 11 sets were determined by an experimental design that ensured that each attribute was presented 5 times in total and viewed with each other twice (a so-called balanced incomplete block design).…”

mentioning

confidence: 99%

Using Best-Worst Scaling to Understand Patient Priorities: A Case Example of Papanicolaou Tests for Homeless Women

Wittenberg¹,

Bharel

Bridges

et al. 2016

The Annals of Family Medicine

View full text Add to dashboard Cite

PURPOSE Best-worst scaling (BWS) is a survey method for assessing individuals' priorities. It identifies the extremes-best and worst items, most and least important factors, biggest and smallest influences-among sets. In this article, we demonstrate an application of BWS in a primary care setting to illustrate its use in identifying patient priorities for services. METHODSWe conducted a BWS survey in 2014 in Boston, Massachusetts, to assess the relative importance of 10 previously identified attributes of Papanicolaou (Pap) testing services among women experiencing homelessness. Women were asked to evaluate 11 sets of 5 attributes of Pap services, and identify which attribute among each set would have the biggest and smallest influence on promoting uptake. We show how frequency analysis can be used to analyze results. RESULTSIn all, 165 women participated, a response rate of 72%. We identified the most and least salient influences on encouraging Pap screening based on their frequency of report among our sample, with possible standardized scores ranging from+1.0 (biggest influence) to -1.0 (smallest influence). Most important was the availability of support for issues beyond health (+0.39), while least important was the availability of accommodations for personal hygiene (-0.27).CONCLUSIONS BWS quantifies patient priorities in a manner that is transparent and accessible. It is easily comprehendible by patients and relatively easy to administer. Our application illustrates its use in a vulnerable population, showing that factors beyond those typically provided in health care settings are highly important to women in seeking Pap screening. This approach can be applied to other health care services where prioritization is helpful to guide decisions. Ann Fam Med 2016;14:359-364. doi: 10.1370/afm.1937 and what is important for clinicians when deciding on treatments. 5 BWS belongs to the conjoint analysis family of methods, which collectively serve to identify preferences and trade-offs that contribute to individuals' choices with respect to "goods."6 These methods have been noted for their cognitive and administrative simplicity, 7 as well as their focus on the patient perspective. 8,9 In this article, we present the BWS method in the context of cervical cancer screening priorities for homeless women.Homeless women die from cervical cancer at a rate nearly 6 times that of the general population. 10 The rate of guideline-adherent screening among homeless women has been reported to be approximately 50%, compared with 82.8% of the insured US population and 61.9% of the uninsured population. METHODS ParticipantsWe recruited adult women experiencing homelessness in Boston, Massachusetts, from 5 sheltered settings: a homeless medical respite center; a health care for the homeless outpatient medical clinic; an emergency (ie, overnight) shelter; a transitional housing program; and a residential substance use treatment program. Inclusion criteria were being aged 18 years or older, verbally proficient in English or Spa...

show abstract

Using Best-Worst Scaling in Horizon Scanning for Hepatocellular Carcinoma Technologies

Cited by 35 publications

References 20 publications

Using Best–Worst Scaling to Investigate Preferences in Health Care

Using Best–Worst Scaling to Investigate Preferences in Health Care

Caregiver Preferences for Emerging Duchenne Muscular Dystrophy Treatments: A Comparison of Best-Worst Scaling and Conjoint Analysis

Using Best-Worst Scaling to Understand Patient Priorities: A Case Example of Papanicolaou Tests for Homeless Women

Contact Info

Product

Resources

About