Clarifying Values: An Updated and Expanded Systematic Review and Meta-Analysis:
TL;DR: In this paper, patient decision aids should help people make evidence-informed decisions aligned with their values, but there is limited guidance about how to achieve such alignment, and the guidance is limited.
Abstract: BackgroundPatient decision aids should help people make evidence-informed decisions aligned with their values. There is limited guidance about how to achieve such alignment.PurposeTo describe the r...
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TL;DR: In this article , the authors used a discrete choice experiment that presents a deceased donor kidney to patients who are waiting for, or have received, a kidney transplant, and the options involved trade-offs between accepting a kidney today or a future kidney.
Abstract: Approximately 20% of deceased donor kidneys are discarded each year in the United States. Some of these kidneys could benefit patients who are waitlisted. Understanding patient preferences regarding accepting marginal-quality kidneys could help more of the currently discarded kidneys be transplanted.This study uses a discrete choice experiment that presents a deceased donor kidney to patients who are waiting for, or have received, a kidney transplant. The choices involve trade-offs between accepting a kidney today or a future kidney. The options were designed experimentally to quantify the relative importance of kidney quality (expected graft survival and level of kidney function) and waiting time. Choices were analyzed using a random-parameters logit model and latent-class analysis.In total, 605 participants completed the discrete choice experiment. Respondents made trade-offs between kidney quality and waiting time. The average respondent would accept a kidney today, with 6.5 years of expected graft survival (95% confidence interval, 5.9 to 7.0), to avoid waiting 2 additional years for a kidney, with 11 years of expected graft survival. Three patient-preference classes were identified. Class 1 was averse to additional waiting time, but still responsive to improvements in kidney quality. Class 2 was less willing to accept increases in waiting time for improvements in kidney quality. Class 3 was willing to accept increases in waiting time even for small improvements in kidney quality. Relative to class 1, respondents in class 3 were likely to be age ≤61 years and to be waitlisted before starting dialysis, and respondents in class 2 were more likely to be older, Black, not have a college degree, and have lower Karnofsky performance status.Participants preferred accepting a lower-quality kidney in return for shorter waiting time, particularly those who were older and had lower functional status.
7 citations
TL;DR: A systematic review as mentioned in this paper identified studies published through to the end of 2021 that applied best-worst scaling to prioritize objects in health, to assess trends of using bestworst scaling in prioritization over time, and to assess the relationship between a legacy measure of quality and a novel assessment of subjective quality and policy relevance.
Abstract: Best-worst scaling is a theory-driven method that can be used to prioritize objects in health. We sought to characterize all studies of best-worst scaling to prioritize objects in health, to assess trends of using best-worst scaling in prioritization over time, and to assess the relationship between a legacy measure of quality (PREFS) and a novel assessment of subjective quality and policy relevance.A systematic review identified studies published through to the end of 2021 that applied best-worst scaling to study priorities in health (PROSPERO CRD42020209745), updating a prior review published in 2016. The PubMed, EBSCOhost, Embase, Scopus, APA PsychInfo, Web of Science, and Google Scholar databases were used and were supplemented by a hand search. Data describing the application, development, design, administration/analysis, quality, and policy relevance were summarized and we tested for trends by comparing articles before and after 1 January, 2017. Multivariate statistics were then used to assess the relationships between PREFS, subjective quality, policy relevance, and other possible indicators.From a total of 2826 unique papers identified, 165 best-worst scaling studies were included in this review. Applications of best-worst scaling to study priorities in health have continued to grow (p < 0.01) and are now used in all regions of the world, most often to study the priorities of patients/consumers (67%). Several key trends can be observed over time: increased use of pretesting (p < 0.05); increased use of online administration (p < 0.01), and decreased use of paper self-administered surveys (p = 0.02); increased use of heterogeneity analysis (p = 0.02); an increase in having a clearly stated purpose (p < 0.01); and a decrease in comparing respondents to non-respondents (p = 0.01). The average sample size has more than doubled, from 228 to 472 respondents, but formal sample size justifications remain low (5.3%) and unchanged over time (p = 0.68). While the average PREFS score remained unchanged at 3.1/5, both subjective quality and policy relevance trended up, but changes were not statistically significant (p = 0.06 and p = 0.13). Most of the variation in subjective quality was driven by PREFS (R2 = 0.42), but it was also positively assosciated with policy relevance, heterogeneity analysis, and using a balanced incomplete block design, and was negatively associated with not using developmental methods and an increasing sample size.Using best-worst scaling to prioritize objects is now commonly used around the world to assess the priorities of patients and other stakeholders in health. Best practices are clearly emerging for best-worst scaling. Although legacy measures (PREFS) to measure study quality are reasonable, there may need to be new tools to assess both study quality and policy relevance.
6 citations
TL;DR: This study uses a discrete choice experiment to quantify the relative importance of kidney quality (expected graft survival and level of kidney function) and waiting time and found participants preferred accepting a lower-quality kidney in return for shorter waiting time.
Abstract: Visual Abstract Background and objectives Approximately 20% of deceased donor kidneys are discarded each year in the United States. Some of these kidneys could benefit patients who are waitlisted. Understanding patient preferences regarding accepting marginal-quality kidneys could help more of the currently discarded kidneys be transplanted. Design, setting, participants, & measurements This study uses a discrete choice experiment that presents a deceased donor kidney to patients who are waiting for, or have received, a kidney transplant. The choices involve trade-offs between accepting a kidney today or a future kidney. The options were designed experimentally to quantify the relative importance of kidney quality (expected graft survival and level of kidney function) and waiting time. Choices were analyzed using a random-parameters logit model and latent-class analysis. Results In total, 605 participants completed the discrete choice experiment. Respondents made trade-offs between kidney quality and waiting time. The average respondent would accept a kidney today, with 6.5 years of expected graft survival (95% confidence interval, 5.9 to 7.0), to avoid waiting 2 additional years for a kidney, with 11 years of expected graft survival. Three patient-preference classes were identified. Class 1 was averse to additional waiting time, but still responsive to improvements in kidney quality. Class 2 was less willing to accept increases in waiting time for improvements in kidney quality. Class 3 was willing to accept increases in waiting time even for small improvements in kidney quality. Relative to class 1, respondents in class 3 were likely to be age ≤61 years and to be waitlisted before starting dialysis, and respondents in class 2 were more likely to be older, Black, not have a college degree, and have lower Karnofsky performance status. Conclusions Participants preferred accepting a lower-quality kidney in return for shorter waiting time, particularly those who were older and had lower functional status.
5 citations
TL;DR: Fuzzy-trace theory (FTT) has been used to understand mental processes that drive decisions and to help patients and providers make decisions that reflect medical advances and personal values as discussed by the authors .
Abstract: Theory—understanding mental processes that drive decisions—is important to help patients and providers make decisions that reflect medical advances and personal values. Building on a 2008 review, we summarize current tenets of fuzzy-trace theory (FTT) in light of new evidence that provides insight regarding mental representations of options and how such representations connect to values and evoke emotions. We discuss implications for communicating risks, preventing risky behaviors, discouraging misinformation, and choosing appropriate treatments. Findings suggest that simple, fuzzy but meaningful gist representations of information often determine decisions. Within minutes of conversing with their doctor, reading a health-related web post, or processing other health information, patients rely on gist memories of that information rather than verbatim details. This fuzzy-processing preference explains puzzles and paradoxes in how patients (and sometimes providers) think about probabilities (e.g., “50-50” chance), outcomes of treatment (e.g., with antibiotics), experiences of pain, end-of-life decisions, memories for medication instructions, symptoms of concussion, and transmission of viruses (e.g., in AIDS and COVID-19). As examples, participation in clinical trials or seeking treatments with low probabilities of success (e.g., with antibiotics or at the end of life) may indicate a defensibly different categorical gist perspective on risk as opposed to simply misunderstanding probabilities or failing to make prescribed tradeoffs. Thus, FTT explains why people avoid precise tradeoffs despite computing them. Facilitating gist representations of information offers an alternative approach that goes beyond providing uninterpreted “neutral” facts versus persuading or shifting the balance between fast versus slow thinking (or emotion vs. cognition). In contrast to either taking mental shortcuts or deliberating about details, gist processing facilitates application of advanced knowledge and deeply held values to choices. Highlights Fuzzy-trace theory (FTT) supports practical approaches to improving health and medicine. FTT differs in important respects from other theories of decision making, which has implications for how to help patients, providers, and health communicators. Gist mental representations emphasize categorical distinctions, reflect understanding in context, and help cue values relevant to health and patient care. Understanding the science behind theory is crucial for evidence-based medicine.
4 citations
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TL;DR: Moher et al. as mentioned in this paper introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses, which is used in this paper.
Abstract: David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses
62,157 citations
TL;DR: A new quantity is developed, I 2, which the authors believe gives a better measure of the consistency between trials in a meta-analysis, which is susceptible to the number of trials included in the meta- analysis.
Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice?
Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis.
Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4
Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted?
A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …
45,105 citations
TL;DR: Although the checklist should not be interpreted as endorsing any specific methodological approach to conjoint analysis, it can facilitate future training activities and discussions of good research practices for the application of conjoint-analysis methods in health care studies.
1,365 citations
TL;DR: The A5- item scale is a useful indicator of health care decision regret at a given point in time and was greater among those who changed their decisions than those who did not.
Abstract: Background.As patients become more involved in health care decisions, there may be greater opportunity for decision regret. The authors could not find a validated, reliable tool for measuring regret after health care decisions.Methods.A5- item scale was administered to 4 patient groups making different health care decisions. Convergent validity was deter- mined by examining the scale's correlation with satisfaction measures, decisional conflict, and health outcome measures.Results.The scale showed good internal consistency (Cronbach's = 0.81 to 0.92). It correlated strongly with decision satisfaction (r = -0.40 to -0.60), decisional conflict (r = 0.31 to 0.52), and overall rated quality of life (r = -0.25 to - 0.27). Groups differing on feelings about a decision also differed on rated regret: F(2, 190) = 31.1, P < 0.001. Regret was greater among those who changed their decisions than those who did not, t(175) = 16.11, P < 0.001.Conclusions.The scale is a useful indicator of health care decision regret at ...
968 citations
TL;DR: This dissertation aims to develop a measure of informed choice that helps decision-makers make more informed decisions about where to live, work and play.
Abstract: Objective To develop a measure of informed choice.
Conceptualization and measurement The measure is based on the following definition of an informed choice: one that is based on relevant knowledge, consistent with the decision-maker’s values and behaviourally implemented. The measure comprises an eight-item scale of knowledge, a four-item scale assessing attitudes towards undergoing the screening test and a record of test uptake.
Participants Sixty-six women awaiting their first antenatal clinic appointments.
Measure development In women offered a screening test in pregnancy, the internal reliability of both the knowledge and the attitude scales was acceptable (alpha coefficients 0.82 and 0.83, respectively). Of the 42 women completing both scales, 18 were classified as having made an informed choice, and 24 were classified as having made an uninformed choice.
Conclusion The results of this preliminary study provide some evidence to support the feasibility of conceptualizing and measuring informed choices regarding screening using a brief measure assessing knowledge and attitudes. The validity and utility of this approach awaits further studies, involving larger numbers of participants, offered different screening tests.
681 citations