Medical Decision Making最新文献

BackgroundAlthough in vitro fertilization (IVF) has enhanced fertility opportunities for many people, it also comes with considerable burden. Concerns have been raised about patients holding unrealistic expectations and continuing treatment indefinitely. This study aimed to investigate whether anecdotes of IVF success affect hypothetical intentions to continue treatment despite very low chances of success.DesignOnline randomized controlled trial with a parallel 3-arm design, conducted in May 2022. After viewing a clinical vignette depicting 6 unsuccessful IVF cycles with less than 5% chance of subsequent treatment success, 606 females aged 18 to 45 years in Australia were randomized to receive either 1) an anecdote of IVF success despite limited chances, 2) the anecdote of success and an anecdote of failure, or 3) no anecdote. Outcomes were intention to undergo another IVF cycle, worry, likelihood of success, and narrative transportation.ResultsThere was a main effect of anecdote condition on intention to have another IVF cycle, with participants randomized to the positive and negative anecdote having higher intention than those given no additional information (mean difference = 0.65, 95% confidence interval [CI] = 0.12-1.18, P = 0.017). There were no differences between conditions regarding worry, likelihood of success, or narrative transportation. In adjusted analyses accounting for prior IVF experience, the main effect of anecdotes on intention was no longer statistically significant. Those with prior IVF experience reported a statistically higher likelihood of success and narrative transportation than those without prior IVF experience (mean difference [MD] = 34.28, 95% CI = 27.26-41.30, P < 0.001, and MD = 1.35, 95% CI = 0.96-1.74, P < 0.001, respectively).ConclusionHearing anecdotes may encourage continuation of IVF despite extremely low chances of success. These findings, along with our sample's overestimation of IVF success, illustrate the importance of frequent and frank discussions about expected treatment outcomes.Trial registration:ACTRN12622000576729.HighlightsThe presence of IVF anecdotes increased the intention to undergo another IVF cycle despite extremely low chances of success.Balancing an anecdote of success with an anecdote of failure had no attenuating effect on intention.IVF providers should be wary of the potential impact of success stories on patients' decision making.In the vignette depicting overuse of IVF, participants with previous IVF experience greatly overestimated the likelihood of success with another IVF cycle, supporting previous research finding that patients often have unrealistically high expectations about their own chance of success.

BackgroundBioethicists have advocated lotteries to distribute scarce health care resources, highlighting the benefits that make them attractive amid growing health care challenges. During the COVID-19 pandemic, lotteries were used to distribute vaccines within priority groups in some settings, notably in the United States. Nonetheless, limited evidence exists on public attitudes toward lotteries.MethodsTo assess public support for vaccine allocation by lottery versus expert committee, we conducted a survey-based experiment during the pandemic. Between November 2020 and May 2021, data were collected from 15,380 respondents across 14 diverse countries. Respondents were randomly allocated (1:1) to 1 of 2 hypothetical scenarios involving COVID-19 vaccine allocation among nurses: 1) by lottery and 2) prioritization by a committee of expert physicians. The outcome was agreement on the appropriateness of the allocation mechanism on a scale ranging from 0 (strongly disagree) to 100 (strongly agree), with differences stratified by a range of covariates. Two-sided t tests were used to test for overall differences in mean agreement between lottery and expert committee.FindingsMean agreement with lottery allocation was 37.25 (95% confidence interval [CI] 34.86-39.65), ranging from 21.1 (95% CI 15.07-27.13) in Chile to 62.33 (95% CI 54.45-70.21) in India. In every country, expert committee allocation received higher support, with mean agreement of 61.19 (95% CI: 60.04-62.35), varying from 51.25 in Chile to 69.77 in India. Greater agreement with lotteries was observed among males, higher-income individuals, those with lower education, and those identifying as politically right leaning.ConclusionsDespite arguments for lottery-based allocation of medical resources, we found low overall public support, albeit with substantial variation across countries. Successful implementation of lottery allocation will require targeted public engagement and clear communication of potential benefits.HighlightsThis study surveyed 15,380 respondents from 14 diverse countries during the COVID-19 pandemic, analyzing international agreement with the appropriateness of using lottery allocation for scarce health care resources.There was universal preference for allocating vaccines by expert committee rather than by lotteries, but there was significant variation in agreement between countries, indicating the need for region-specific policy approaches.Successful implementation of lottery allocation requires targeted public engagement and communication of their benefits, especially with groups less supportive of lotteries.

BackgroundAffective forecasting errors (i.e., errors in people's predictions about future emotions) are common in health decision making and can negatively affect health outcomes. Although narrative interventions have been used to mitigate these errors, many studies did not clearly identify the specific errors targeted or examine the impact of different narrative types on affective forecasting. We applied the narrative immersion model (NIM) to capture the nuances of narratives on mitigating specific affective forecasting errors in health decision making.MethodsUsing a narrative review of existing narrative affective forecasting interventions, we investigated the potential of experience, process, and outcome narratives to reduce specific affective forecasting errors (e.g., focalism, immune neglect).ResultsDifferent narrative types-experience, process, and outcome-may play distinct roles in mitigating affective forecasting errors. Experience narratives may reduce affective forecasting errors by describing what people most likely (targeted) or might (representative) experience, process narratives by modeling optimal decision making, and outcome narratives by broadening people's understanding of possible emotional outcomes. We further discuss how narrative characteristics related to content and structure (e.g., perspective taking, transportation, etc.) may advance narrative effects on affective forecasting.ConclusionsOur findings have implications for intervention design as they facilitate the selection of narrative types tailored to specific affective forecasting errors (e.g., framing, misconstruals, or impact bias).HighlightsSpecific affective forecasting errors may be reduced through different types of narratives, but greater understanding is needed regarding the exact mechanisms.The narrative immersion model is a useful framework to investigate the potential of experience, process, and outcome narratives to reduce specific types of affective forecasting errors.We describe the pathways through which narrative types most likely influence affective forecasting and facilitate the choice of narrative message type for a specific affective forecasting error.Narratives designed for affective forecasting interventions should include detailed and realistic descriptions of people's emotional health care experiences.Other narrative characteristics (e.g., realism, perspective taking, transportation) might affect a person's ability to imagine future emotional health states, and future research should consider their effects on affective forecasting.

BackgroundMessaging strategies hold promise to reduce breast cancer overscreening. However, it is not known whether they may have differential effects among medical maximizers who prefer to take action about their health versus medical minimizers who prefer to wait and see.MethodsIn a randomized controlled survey experiment that included 2 sequential surveys with 3,041 women aged 65+ y from a US population-based online panel, we randomized participants to 1) no messages, 2) single exposure to a screening cessation message, or 3) 2 exposures over time to the screening cessation message. We assessed support for stopping screening in a hypothetical patient and intention to stop screening oneself on 7-point scales, where higher values indicated stronger support and intentions to stop screening. We conducted stratified analyses by medical-maximizing preference and moderation analysis.ResultsOf the women, 40.7% (n = 1,238) were medical maximizers; they had lower support and intention for screening cessation in all groups compared with the medical minimizers. Two message exposures increased support for screening cessation among medical maximizers, with a mean score of 3.68 (95% confidence interval [CI] 3.51-3.85) compared with no message (mean score 2.20, 95% CI 2.00-2.39, P < 0.001). A similar pattern was seen for screening intention. Linear regression models showed no differential messaging effect by medical-maximizing preference.ConclusionsMedical maximizers, although less likely to support screening cessation, were nonetheless responsive to messaging strategies designed to reduce breast cancer overscreening.HighlightsIt is not known if a message on rationales for stopping breast cancer screening would have differential effects among medical maximizers who prefer to take action when it comes to their health versus medical minimizers who prefer to wait and see.In a 2-wave randomized controlled survey experiment with 3,041 older women, we found that medical maximizers, although less likely to support screening cessation compared with medical minimizers, were nonetheless responsive to the messaging intervention, and the magnitude of the intervention effect was similar between maximizers and minimizers.Medical maximizers reported higher levels of worry and annoyance after reading the message compared with the minimizers, but the absolute levels of worry and annoyance were low.Our findings suggest that messaging can be a useful tool for reducing overscreening even in a highly reluctant population.

BackgroundMedication adherence is a critical factor in hypertension management, which remains a challenge for public health systems.MethodsGraded-pair questions were used to quantify the perception of how much nonadherence to antihypertensives increases the risk of serious cardiovascular events. A discrete-choice experiment was used to quantify the relative importance of medication outcomes (e.g., reduction in cardiovascular event risk and medication side effects). Rating questions were used to assess perspectives of the effect of treatment nonadherence on treatment side effects. Results were combined to assess how preferences and outcome expectations influence adherence.ResultsPatients perceived treatment adherence as the most significant contributor to cardiovascular event risk. A reduction in cardiovascular risk was the most significant consideration when choosing medication. Missing consecutive (v. alternate) doses was associated with greater perceived cardiovascular risk and fewer side effects. The differences between complete adherence and any level of nonadherence were significantly larger for side effects than for changes in the risk of cardiovascular events, suggesting that side effects are perceived to be more sensitive to nonadherence than treatment efficacy.LimitationsOur study relied on hypothetical scenarios, which may not fully capture real-world decision making. While our findings shed light on the relationship between adherence patterns and treatment perceptions, it is essential to recognize the complexity of adherence behavior.ConclusionsPatients believe that they can manage medication side effects by skipping doses without compromising the efficacy to the same degree and that they can offset compromises in efficacy by avoiding missing consecutive doses for prolonged periods.ImplicationsHealth care providers should understand the importance of patient education and counseling to address misconceptions and promote realistic expectations regarding treatment efficacy and the consequences of nonadherence.HighlightsThe average patient believes that they can manage medication side effects by skipping doses without compromising the efficacy to the same degree.There is a belief that patients can offset some of the impact of nonadherence on their cardiovascular event risk, particularly if they avoid missing consecutive doses for prolonged periods of time.This highlights the importance of patient education and counseling to address misconceptions and promote realistic expectations regarding treatment efficacy and the consequences of nonadherence.

ObjectiveTo study the effects of exposure to a prior diagnosis (PD) on second opinions in breast pathology.Materials and MethodsPathologists interpreted digital breast biopsy cases in 2 phases separated by a washout. Phase 2 interpretations were randomly assigned to PD or no PD. When presented, PD was always more or less severe than a participant's phase 1 diagnosis. Viewing behaviors, including zoom level, were recorded during all interpretations. Twenty pathologists yielded 556 interpretations of 32 different cases.ResultsPathologists were 71% more likely to give a less severe diagnosis when exposed to a less severe PD than with no PD (RR 1.71, 95% CI 1.33-2.20, P < 0.001). In comparison, when exposed to a more severe PD than with no PD, pathologists were 27% more likely to give a more severe diagnosis, but the effect was not significant (RR 1.27, 95% CI 0.87-1.86, P = 0.223). Compared with no PD, viewing behavior shifted toward more focus on critical image regions with exposure to a less severe PD and toward higher zoom levels with exposure to a more severe PD.DiscussionResults indicate anchoring and confirmation biases from PD exposure, such that second opinions after PD exposure are not independent assessments. Viewing behaviors illustrated how PD alters the interpretive process, including increased zooming when exposed to a more severe PD. Results have implications for best practices for computer-aided diagnosis tools.ImplicationsWhen giving a second opinion, exposure to a PD can sway diagnostic classifications and alter interpretive behavior, highlighting a need for protocols that encourage independent assessments.HighlightsIn pathology diagnosis, second opinions are systematically influenced by prior diagnostic information.Less severe prior diagnoses shift pathologists' visual attention toward clinically critical regions of a pathology image, whereas more severe prior diagnoses tend to elicit increased magnification during case interpretation.Specific viewing behaviors partially mediate the effect of prior diagnoses on second opinion diagnoses.When prior diagnoses are disclosed to pathologists, anchoring and confirmation biases undermine the independence of second opinion decisions.

Background. Awareness of shared decision making (SDM) is growing, but its integration into clinical practice guidelines (CPGs) remains challenging. We sought expert insights to identify strategies for more successfully integrating SDM and decision support tools into CPGs. Specifically, our objectives were to determine 1) how to identify CPG recommendations where SDM is most relevant and 2) what factors in CPG development hinder or facilitate the consideration of SDM and the development of decision support tools. Methods. We conducted semi-structured interviews with experts on CPGs and SDM. We analyzed the data using Mayring's qualitative content analysis. Results. The 16 interviewed participants proposed several determinants of and strategies for identifying SDM-relevant recommendations. The most frequently mentioned determinant was "multiple options with benefits and harms where choices depend on individual preferences." The most frequently mentioned strategy was prioritization, similar to the CPG scoping phase. Participants highlighted the role of patient partners in facilitating the consideration of SDM in CPG development but noted that a supportive culture toward both patient and public involvement and SDM is needed. The absence of standardized methods and inadequate resources hinder the consideration of SDM and the combined development of CPGs and decision support tools. The current format of CPGs was deemed overwhelming, while the inclusion of choice awareness in CPG recommendations could facilitate SDM. Conclusions. The identified strategies provide a starting point for CPG organizations to explore ways for integrating SDM and decision support tools into CPGs while considering context-specific barriers and facilitators. Implications. Further research is needed to assess the usefulness and feasibility of the proposed strategies. New policies and stronger collaboration between CPG and SDM communities appear to be needed to address identified barriers.HighlightsWe explored expert knowledge and experience on how to successfully integrate shared decision making (SDM) and decision support tools into clinical practice guidelines (CPGs).A combined development of CPGs and decision support tools was deemed essential; however, development processes often remain separate, with the CPG development group unaware of the decision support tool development group, and vice versa.In addition to stating choice awareness in CPGs, participants highlighted the critical role of patient partners in considering SDM in CPG development, but resource issues and a culture that neglects patient involvement and SDM remain.For CPG development groups to consider SDM and for health care professionals to practice it, things need to be as easy as possible.

BackgroundDecision aids (DAs) are evidence-based tools to improve patient-centered care, but their use in routine care is limited. The purpose of this project was to work with orthopedic practices to deliver DAs.MethodsEligible sites needed to identify an administrative and clinical champion and have access to DAs for treatment of hip, knee, and/or spine conditions. The implementation strategies included an Orthopaedic Learning Collaborative (OLC), external facilitation, and audit and feedback. The project was conducted over 15 mo with 5 OLC sessions, individual monthly meetings, and monthly data reports. Clinicians and staff completed a baseline survey prior to the start of the project. Sites provided details on their DA workflow and number of DAs delivered. We calculated adoption (the number of specialists who used DAs) and estimated reach (percentage of eligible patients who received DAs). We calculated descriptive statistics and explored predictors of reach.ResultsTwelve participating sites had an average annual orthopedic surgical volume of 550, half were academic medical centers, and some (4/13, 30.7%) had prior experience with orthopedic DAs. Adoption was 76% (60/79 physicians). Sites distributed 9,626 DAs and reached 44% of eligible patients (range 7%-100%). Sites that indicated at baseline that DA delivery was a high priority for staff had higher reach (60% reach for high v. 47% for moderate v. 9% for low priority, P = 0.21). Sites with no prior experience with DAs had higher reach than those with prior experience did (60% v. 38%, P = 0.26, d = 0.71).ConclusionsParticipating sites were able to implement workflows that reached about half of eligible patients. Establishing DA delivery as a priority for staff at the outset appears important for reach, while prior experience does not.HighlightsThe 12 sites were able to reach, on average, 44% of eligible patients with decision aids in routine care demonstrating feasibility of distribution.The study and associated implementation toolkit provide concrete examples of workflows for orthopedic practices interested in incorporating decision aids into routine care.A bundle of implementation strategies, including a learning collaborative, external facilitation, and audit and feedback, helped most sites meet targets for decision aid implementation.

BackgroundResource scarcity during large-scale crises, such as pandemics, can increase the emphasis on efficiency in medical decision making. However, it remains unclear whether such shifts are primarily driven by the direct experience of scarcity or by the way in which ethical principles for health care priority setting are expressed in the context of a crisis. This study investigates whether a national crisis affects public support for health care priority-setting principles and whether abstract versus concrete formulations of these principles shape that support.DesignWe conducted a preregistered online experiment (N = 1,404) to examine public attitudes toward three ethical principles formalized in the Swedish ethical platform-human dignity, needs-solidarity, and cost-effectiveness-in both crisis and noncrisis contexts. We also manipulated how the principles were presented, using either abstract or concrete formulations.ResultsIn the crisis condition, support for the human dignity and cost-effectiveness principles decreased, while support for the needs-solidarity principle increased. However, these effects were small, and the overall ranking of the principles remained stable. Notably, the level of abstractness had a stronger impact than the crisis context did: support for needs solidarity was higher when described abstractly, whereas support for cost-effectiveness increased when it was presented in a more concrete, action-oriented way. Support for the human dignity principle was unaffected by the abstractness manipulation.ConclusionThe findings suggest that people's moral views are relatively stable in the face of crisis. Rather than the crisis context itself, the way ethical principles are formulated-abstractly or concretely-may be a more powerful driver of shifts in public support for different moral values in health care priority setting.HighlightsPublic support for ethical principles remained largely stable during a simulated national crisis.The level of abstraction in how principles were presented strongly influenced support.Support for needs-solidarity increased in a crisis, while cost-effectiveness support declined.The way ethical principles were formulated had a greater impact than the presence of a crisis.

Network meta-analysis (NMA) synthesizes data from randomized controlled trials to estimate the relative treatment effects among multiple interventions. When treatments can be grouped into classes, class effect NMA models can be used to inform recommendations at the class level and can also address challenges with sparse data and disconnected networks. Despite the potential of NMA class effects models and numerous applications in various disease areas, the literature lacks a comprehensive guide outlining the range of class effect models, their assumptions, practical considerations for estimation, model selection, checking assumptions, and presentation of results. In addition, there is no implementation available in standard software for NMA. This article aims to provide a modeling framework for class effect NMA models, propose a systematic approach to model selection, and provide practical guidance on implementing class effect NMA models using the multinma R package. We describe hierarchical NMA models that include random and fixed treatment-level effects and exchangeable and common class-level effects. We detail methods for testing assumptions of heterogeneity, consistency, and class effects, alongside assessing model fit to identify the most suitable models. A model selection strategy is proposed to guide users through these processes and assess the assumptions made by the different models. We illustrate the framework and structured approach for model selection using an NMA of 41 interventions from 17 classes for social anxiety.HighlightsProvides a practical guide and modelling framework for network meta-analysis (NMA) with class effects.Proposes a model selection strategy to guide researchers in choosing appropriate class effect models.Illustrates the strategy using a large case study of 41 interventions for social anxiety.