Daniel Kahneman (1934-2024).

Pioneer in the psychology of judgment and decision-making.

Clinicians' approach to predicting post-cardiac arrest outcomes for patients enrolled in a United States clinical trial.

PURPOSE: Perceived poor prognosis can lead to withdrawal of life-sustaining therapies (WLST) in patients who might otherwise recover. We characterized clinicians' approach to post-arrest prognostication in a multicenter clinical trial. METHODS: Semi-structured interviews were conducted with clinicians who treated a comatose post-cardiac arrest patient enrolled in the Influence of Cooling Duration on Efficacy in Cardiac Arrest Patients (ICECAP) trial (NCT04217551). Two authors independently analyzed each interview using inductive and deductive coding. The clinician reported how they arrived at a prognosis for the specific patient. We summarized the frequency with which clinicians reported using objective diagnostics to formulate their prognosis, and compared the reported approaches to established guidelines. Each respondent provided demographic information and described local neuroprognostication practices. RESULTS: We interviewed 30 clinicians at 19 US hospitals. Most claimed adherence to local hospital neuroprognostication protocols (n = 19). Prognostication led to WLST for perceived poor neurological prognosis in 15/30 patients, of whom most showed inconsistencies with guidelines or trial recommendations, respectively. In 10/15 WLST cases, clinicians reported relying on multimodal testing. A prevalent theme was the use of "clinical gestalt," defined as prognosticating based on a patient's overall appearance or a subjective impression in the absence of objective data. Many clinicians (21/30) reported using clinical gestalt for initial prognostication, with 9/21 expressing high confidence initially. CONCLUSION: Clinicians in our study state they follow neuroprognostication guidelines in general but often do not do so in actual practice. They reported clinical gestalt frequently informed early, highly confident prognostic judgments, and few objective tests changed initial impressions. Subjective prognostication may undermine well-designed trials.

Achieving Goals of Care Decisions in Chronic Critical Illness: A Multi-Institutional Qualitative Study.

BACKGROUND: Physicians, patients, and families alike perceive a need to improve how goals of care (GOC) decisions occur in chronic critical illness (CCI), but little is currently known about this decision-making process. RESEARCH QUESTION: How do intensivists from various health systems facilitate decision-making about GOC for patients with CCI? What are barriers to, and facilitators of, this decision-making process? STUDY DESIGN AND METHODS: We conducted semistructured interviews with a purposeful sample of intensivists from the United States and Canada using a mental models approach adapted from decision science. We analyzed transcripts inductively using qualitative description. RESULTS: We interviewed 29 intensivists from six institutions. Participants across all sites described GOC decision-making in CCI as a complex, longitudinal, and iterative process that involved substantial preparatory work, numerous stakeholders, and multiple family meetings. Intensivists required considerable time to collect information on prior events and conversations, and to arrive at a prognostic consensus with other involved physicians prior to meeting with families. Many intensivists stressed the importance of scheduling multiple family meetings to build trust and relationships prior to explicitly discussing GOC. Physician-identified barriers to GOC decision-making included 1-week staffing models, limited time and cognitive bandwidth, difficulty eliciting patient values, and interpersonal challenges with care team members or families. Potential facilitators included scheduled family meetings at regular intervals, greater interprofessional involvement in decisions, and consistent messaging from care team members. INTERPRETATION: Intensivists described a complex time- and labor-intensive group process to achieve GOC decision-making in CCI. System-level interventions that improve how information is shared between physicians and decrease logistical and relational barriers to timely and consistent communication are key to improving GOC decision-making in CCI.

Using a theory-based, customized video game as an educational tool to improve physicians' trauma triage decisions: study protocol for a randomized cluster trial.

BACKGROUND: Transfer of severely injured patients to trauma centers, either directly from the field or after evaluation at non-trauma centers, reduces preventable morbidity and mortality. Failure to transfer these patients appropriately (i.e., under-triage) remains common, and occurs in part because physicians at non-trauma centers make diagnostic errors when evaluating the severity of patients' injuries. We developed Night Shift, a theory-based adventure video game, to recalibrate physician heuristics (intuitive judgments) in trauma triage and established its efficacy in the laboratory. We plan a type 1 hybrid effectiveness-implementation trial to determine whether the game changes physician triage decisions in real-life and hypothesize that it will reduce the proportion of patients under-triaged. METHODS: We will recruit 800 physicians who work in the emergency departments (EDs) of non-trauma centers in the US and will randomize them to the game (intervention) or to usual education and training (control). We will ask those in the intervention group to play Night Shift for 2 h within 2 weeks of enrollment and again for 20 min at quarterly intervals. Those in the control group will receive only usual education (i.e., nothing supplemental). We will then assess physicians' triage practices for older, severely injured adults in the 1-year following enrollment, using Medicare claims, and will compare under-triage (primary outcome), 30-day mortality and re-admissions, functional independence, and over-triage between the two groups. We will evaluate contextual factors influencing reach, adoption, implementation, and maintenance with interviews of a subset of trial participants (n = 20) and of other key decision makers (e.g., patients, first responders, administrators [n = 100]). DISCUSSION: The results of the trial will inform future efforts to improve the implementation of clinical practice guidelines in trauma triage and will provide deeper understanding of effective strategies to reduce diagnostic errors during time-sensitive decision making. TRIAL REGISTRATION: ClinicalTrials.gov; NCT06063434 . Registered 26 September 2023.

Improving Social Bot Detection Through Aid and Training.

OBJECTIVE: We test the effects of three aids on individuals' ability to detect social bots among Twitter personas: a bot indicator score, a training video, and a warning. BACKGROUND: Detecting social bots can prevent online deception. We use a simulated social media task to evaluate three aids. METHOD: Lay participants judged whether each of 60 Twitter personas was a human or social bot in a simulated online environment, using agreement between three machine learning algorithms to estimate the probability of each persona being a bot. Experiment 1 compared a control group and two intervention groups, one provided a bot indicator score for each tweet; the other provided a warning about social bots. Experiment 2 compared a control group and two intervention groups, one receiving the bot indicator scores and the other a training video, focused on heuristics for identifying social bots. RESULTS: The bot indicator score intervention improved predictive performance and reduced overconfidence in both experiments. The training video was also effective, although somewhat less so. The warning had no effect. Participants rarely reported willingness to share content for a persona that they labeled as a bot, even when they agreed with it. CONCLUSIONS: Informative interventions improved social bot detection; warning alone did not. APPLICATION: We offer an experimental testbed and methodology that can be used to evaluate and refine interventions designed to reduce vulnerability to social bots. We show the value of two interventions that could be applied in many settings.

Collection and Analysis of Adherence Information for Software as a Medical Device Clinical Trials: Systematic Review.

BACKGROUND: The rapid growth of digital health apps has necessitated new regulatory approaches to ensure compliance with safety and effectiveness standards. Nonadherence and heterogeneous user engagement with digital health apps can lead to trial estimates that overestimate or underestimate an app's effectiveness. However, there are no current standards for how researchers should measure adherence or address the risk of bias imposed by nonadherence through efficacy analyses. OBJECTIVE: This systematic review aims to address 2 critical questions regarding clinical trials of software as a medical device (SaMD) apps: How well do researchers report adherence and engagement metrics for studies of effectiveness and efficacy? and What efficacy analyses do researchers use to account for nonadherence and how appropriate are their methods? METHODS: We searched the Food and Drug Administration's registration database for registrations of repeated-use, patient-facing SaMD therapeutics. For each such registration, we searched ClinicalTrials.gov, company websites, and MEDLINE for the corresponding clinical trial and study articles through March 2022. Adherence and engagement data were summarized for each of the 24 identified articles, corresponding to 10 SaMD therapeutics. Each article was analyzed with a framework developed using the Cochrane risk-of-bias questions to estimate the potential effects of imperfect adherence on SaMD effectiveness. This review, funded by the Richard King Mellon Foundation, is registered on the Open Science Framework. RESULTS: We found that although most articles (23/24, 96%) reported collecting information about SaMD therapeutic engagement, of the 20 articles for apps with prescribed use, only 9 (45%) reported adherence information across all aspects of prescribed use: 15 (75%) reported metrics for the initiation of therapeutic use, 16 (80%) reported metrics reporting adherence between the initiation and discontinuation of the therapeutic (implementation), and 4 (20%) reported the discontinuation of the therapeutic (persistence). The articles varied in the reported metrics. For trials that reported adherence or engagement, there were 4 definitions of initiation, 8 definitions of implementation, and 4 definitions of persistence. All articles studying a therapeutic with a prescribed use reported effectiveness estimates that might have been affected by nonadherence; only a few (2/20, 10%) used methods appropriate to evaluate efficacy. CONCLUSIONS: This review identifies 5 areas for improving future SaMD trials and studies: use consistent metrics for reporting adherence, use reliable adherence metrics, preregister analyses for observational studies, use less biased efficacy analysis methods, and fully report statistical methods and assumptions.

Cognitive Biases and Shared Decision Making in Acute Brain Injury.

Many patients hospitalized after severe acute brain injury are comatose and require life-sustaining therapies. Some of these patients make favorable recoveries with continued intensive care, while others do not. In addition to providing medical care, clinicians must guide surrogate decision makers through high-stakes, emotionally charged decisions about whether to continue life-sustaining therapies. These consultations require clinicians first to assess a patient's likelihood of recovery given continued life-sustaining therapies (i.e., prognosticate), then to communicate that prediction to surrogates, and, finally, to elicit and interpret the patient's preferences. At each step, both clinicians and surrogates are vulnerable to flawed decision making. Clinicians can be imprecise, biased, and overconfident when prognosticating after brain injury. Surrogates can misperceive the choice and misunderstand or misrepresent a patient's wishes, which may never have been communicated clearly. These biases can undermine the ability to reach choices congruent with patients' preferences through shared decision making (SDM). Decision science has extensively studied these biases. In this article, we apply that research to improving SDM for patients who are comatose after acute brain injury. After introducing SDM and the medical context, we describe principal decision science results as they relate to neurologic prognostication and end-of-life decisions, by both clinicians and surrogates. Based on research regarding general processes that can produce imprecise, biased, and overconfident prognoses, we propose interventions that could improve SDM, supporting clinicians and surrogates in making these challenging decisions.

When Do Humans Heed AI Agents' Advice? When Should They?

OBJECTIVE: We manipulate the presence, skill, and display of artificial intelligence (AI) recommendations in a strategy game to measure their effect on users' performance. BACKGROUND: Many applications of AI require humans and AI agents to make decisions collaboratively. Success depends on how appropriately humans rely on the AI agent. We demonstrate an evaluation method for a platform that uses neural network agents of varying skill levels for the simple strategic game of Connect Four. METHODS: We report results from a 2 × 3 between-subjects factorial experiment that varies the format of AI recommendations (categorical or probabilistic) and the AI agent's amount of training (low, medium, or high). On each round of 10 games, participants proposed a move, saw the AI agent's recommendations, and then moved. RESULTS: Participants' performance improved with a highly skilled agent, but quickly plateaued, as they relied uncritically on the agent. Participants relied too little on lower skilled agents. The display format had no effect on users' skill or choices. CONCLUSIONS: The value of these AI agents depended on their skill level and users' ability to extract lessons from their advice. APPLICATION: Organizations employing AI decision support systems must consider behavioral aspects of the human-agent team. We demonstrate an approach to evaluating competing designs and assessing their performance.

Communicating health information with visual displays.

Well-designed visual displays have the power to convey health messages in clear, effective ways to non-experts, including journalists, patients and policymakers. Poorly designed visual displays, however, can confuse and alienate recipients, undermining health messages. In this Perspective, we propose a structured framework for effective visual communication of health information, using case examples of three common communication tasks: comparing treatment options, interpreting test results, and evaluating risk scenarios. We also show simple, practical ways to evaluate a design's success and guide improvements. The proposed framework is grounded in research on health risk communication, visualization and decision science, as well as our experience in communicating health data.

Testing a Novel Deliberate Practice Intervention to Improve Diagnostic Reasoning in Trauma Triage: A Pilot Randomized Clinical Trial.

Importance: Diagnostic errors made during triage at nontrauma centers contribute to preventable morbidity and mortality after injury. Objective: To test the feasibility, acceptability, and preliminary effect of a novel deliberate practice intervention to improve diagnostic reasoning in trauma triage. Design, Setting, and Participants: This pilot randomized clinical trial was conducted online in a national convenience sample of 72 emergency physicians between January 1 and March 31, 2022, without follow-up. Interventions: Participants were randomly assigned to receive either usual care (ie, passive control) or a deliberate practice intervention, consisting of 3 weekly, 30-minute, video-conferenced sessions during which physicians played a customized, theory-based video game while being observed by content experts (coaches) who provided immediate, personalized feedback on diagnostic reasoning. Main Outcomes and Measures: Using the Proctor framework of outcomes for implementation research, the feasibility, fidelity, acceptability, adoption, and appropriateness of the intervention was assessed by reviewing videos of the coaching sessions and conducting debriefing interviews with participants. A validated online simulation was used to assess the intervention's effect on behavior, and triage among control and intervention physicians was compared using mixed-effects logistic regression. Implementation outcomes were analyzed using an intention-to-treat approach, but participants who did not use the simulation were excluded from the efficacy analysis. Results: The study enrolled 72 physicians (mean [SD] age, 43.3 [9.4] years; 44 men [61%]) but limited registration of physicians in the intervention group to 30 because of the availability of the coaches. Physicians worked in 20 states; 62 (86%) were board certified in emergency medicine. The intervention was delivered with high fidelity, with 28 of 30 physicians (93%) completing 3 coaching sessions and with coaches delivering 95% of session components (642 of 674). A total of 21 of 36 physicians (58%) in the control group participated in outcome assessment; 28 of 30 physicians (93%) in the intervention group participated in semistructured interviews, and 26 of 30 physicians (87%) in the intervention group participated in outcome assessment. Most physicians in the intervention group (93% [26 of 28]) described the sessions as entertaining and valuable; most (88% [22 of 25]) affirmed the intention to adopt the principles discussed. Suggestions for refinement included providing more time with the coach and addressing contextual barriers to triage. During the simulation, the triage decisions of physicians in the intervention group were more likely to adhere to clinical practice guidelines than those in the control group (odds ratio; 13.8, 95% CI, 2.8-69.6; P = .001). Conclusions and Relevance: In this pilot randomized clinical trial, coaching was feasible and acceptable and had a large effect on simulated trauma triage decisions, setting the stage for a phase 3 trial. Trial Registration: ClinicalTrials.gov Identifier: NCT05168579.

Antenatal consultation and deliberation: adapting to parental preferences.

OBJECTIVE: To analyze and compare perspectives on antenatal consultation and decision-making from participants with varying degrees of prematurity experience and clinician-experts. STUDY DESIGN: Open-ended interviews structured around topics previously identified by recognized clinician-experts were conducted with participants having different levels of prematurity experience. Analysis used mixed methods (thematic and mental models analysis). Secondary sub-group comparisons were performed, based on degree of experience. RESULTS: Non-clinician participants' (n = 80) perspectives differed regarding: amount and content of information desired, decision-making strategies, and who - parent or clinician - should direct consultations. Most wanted to retain decisional authority, all recognized their emotional limitations and many advocated for deliberation support. Participants worried parents' would regret choosing palliative care contrary to clinicians. Bereaved parents often saw issues differently. CONCLUSIONS: Parents approach risk and decision-making for extremely premature infants in a personal fashion. They need personalized support tailored to their unique circumstances, decision-making preferences, and emotions.

Bereaved Parents: Insights for the Antenatal Consultation.

OBJECTIVE: The study aimed to explore experiences of extremely preterm infant loss in the delivery room and perspectives about antenatal consultation. STUDY DESIGN: Bereaved participants were interviewed, following a semi-structured protocol. Personal narratives were analyzed with a mixed-methods approach. RESULTS: In total, 13 participants, reflecting on 17 pregnancies, shared positive, healing and negative, harmful interactions with clinicians and institutions: feeling cared for or abandoned, doubted or believed, being treated rigidly or flexibly, and feeling that infant's life was valued or not. Participants stressed their need for personalized information, individualized approaches, and affective support. Their decision processes varied; some wanted different things for themselves than what they recommended for others. These interactions shaped their immediate experiences, long-term well-being, healing, and regrets. All had successful subsequent pregnancies; few returned to institutions where they felt poorly treated. CONCLUSION: Antenatal consultations can be strengthened by personalizing them, within a strong caregiver relationship and supportive institutional practices. KEY POINTS: · Personalized antenatal consultations should strive to balance cognitive and affective needs.. · Including perspectives from bereaved parents can strengthen antenatal consultations.. · Trusting provider-parent partnerships are pivotal for risk communication..

Testing the feasibility, acceptability, and preliminary effect of a novel deliberate practice intervention to reduce diagnostic error in trauma triage: a study protocol for a randomized pilot trial.

BACKGROUND: Non-compliance with clinical practice guidelines in trauma remains common, in part because physicians make diagnostic errors when triaging injured patients. Deliberate practice, purposeful participation in a training task under the oversight of a coach, effectively changes behavior in procedural domains of medicine but has rarely been used to improve diagnostic skill. We plan a pilot parallel randomized trial to test the feasibility, acceptability, and preliminary effect of a novel deliberate practice intervention to reduce physician diagnostic errors in trauma triage. METHODS: We will randomize a national convenience sample of physicians who work at non-trauma centers (n = 60) in a 1:1 ratio to a deliberate practice intervention or to a passive control. We will use a customized, theory-based serious video game as the basis of our training task, selected based on its behavior change techniques and game mechanics, along with a coaching manual to standardize the fidelity of the intervention delivery. The intervention consists of three 30-min sessions with content experts (coaches), conducted remotely, during which physicians (trainees) play the game and receive feedback on their diagnostic processes. We will assess (a) the fidelity with which the intervention is delivered by reviewing video recordings of the coaching sessions; (b) the acceptability of the intervention through surveys and semi-structured interviews, and (c) the effect of the intervention by comparing the performance of trainees and a control group of physicians on a validated virtual simulation. We hypothesize that trainees will make ≥ 25% fewer diagnostic errors on the simulation than control physicians, a large effect size. We additionally hypothesize that ≥ 90% of trainees will receive their intervention as planned. CONCLUSIONS: The results of the trial will inform the decision to proceed with a future hybrid effectiveness-implementation trial of the intervention. It will also provide a deeper understanding of the challenges of using deliberate practice to modify the diagnostic skill of physicians. TRIAL REGISTRATION: Clinical trials.gov ( NCT05168579 ); 23 December 2021.

Risk heatmaps as visual displays: Opening movie studios after the COVID-19 shutdown.

Upon shutting down operations in early 2020 due to the COVID-19 pandemic, the movie industry assembled teams of experts to help develop guidelines for returning to operation. It resulted in a joint report, The Safe Way Forward, which was created in consultation with union members and provided the basis for negotiations with the studios. A centerpiece of the report was a set of heatmaps displaying SARS-CoV-2 risks for a shoot, as a function of testing rate, community infection prevalence, community transmission rate (R0), and risk measure (either expected number of cases or probability of at least one case). We develop and demonstrate a methodology for evaluating such complex displays, in terms of how well they inform potential users, in this case, workers deciding whether the risks of a shoot are acceptable. We ask whether individuals making hypothetical return-to-work decisions can (a) read display entries, (b) compare display entries, and (c) make inferences based on display entries. Generally speaking, respondents recruited through the Amazon MTurk platform could interpret the display information accurately and make coherent decisions, suggesting that heatmaps can communicate complex risks to lay audiences. Although these heatmaps were created for practical, rather than theoretical, purposes, these results provide partial support for theoretical accounts of visual information processing and identify challenges in applying them to complex settings.

The value of adherence information during clinical pharmaceutical trials.

BACKGROUND/AIMS: The quality of the evidence used to evaluate a drug's safety and efficacy depends, in part, on how well participants adhere to the prescribed drug-taking regime. There are multiple approaches to measure adherence in clinical trials, varying in their cost and accuracy. We demonstrate a method for evaluating the cost-effectiveness of common adherence monitoring methods, considering the costs and data quality for drugs that differ in how forgiving they are of nonadherence. METHODS: We propose a simulation approach to estimate the value of evidence about adherence, considering both costs of collection and potential errors in interpreting clinical trial results. We demonstrate the approach with a simulated clinical trial of nitrendipine, a common calcium channel blocker. We consider two trial designs, one using pretrial adherence to "enrich" the trial sample and one without an enrichment strategy. We use scenarios combining high and low values of two key properties of a clinical trial: participant adherence and drug forgiveness. RESULTS: Under the conditions of these simulations, the most cost-effective adherence monitoring approach depends on both trial participant adherence and drug forgiveness. For example, the enrichment strategy is not cost-effective for the base scenario (high forgiveness and high adherence), but is for other scenarios. We also estimate the effects of evaluable patient analysis, a controversial procedure that excludes nonadherent participants from the analyses, after a trial is completed. CONCLUSIONS: Our proposed approach can guide drug regulators and developers in designing efficient clinical trials and assessing the impact of nonadherence on trial results. It can identify cost-effective adherence-monitoring methods, given available knowledge about the methods, drug, and patients' expected adherence.

Duped by Bots: Why Some are Better than Others at Detecting Fake Social Media Personas.

OBJECTIVE: We examine individuals' ability to detect social bots among Twitter personas, along with participant and persona features associated with that ability. BACKGROUND: Social media users need to distinguish bots from human users. We develop and demonstrate a methodology for assessing those abilities, with a simulated social media task. METHOD: We analyze performance from a signal detection theory perspective, using a task that asked lay participants whether each of 50 Twitter personas was a human or social bot. We used the agreement of two machine learning models to estimate the probability of each persona being a bot. We estimated the probability of participants indicating that a persona was a bot with a generalized linear mixed-effects model using participant characteristics (social media experience, analytical reasoning, and political views) and stimulus characteristics (bot indicator score and political tone) as regressors. RESULTS: On average, participants had modest sensitivity (d') and a criterion that favored responding "human." Exploratory analyses found greater sensitivity for participants (a) with less self-reported social media experience, (b) greater analytical reasoning ability, and (c) who were evaluating personas with opposing political views. Some patterns varied with participants' political identity. CONCLUSIONS: Individuals have limited ability to detect social bots, with greater aversion to mistaking bots for humans than vice versa. Greater social media experience and myside bias appeared to reduce performance, as did less analytical reasoning ability. APPLICATION: These patterns suggest the need for interventions, especially when users feel most familiar with social media.

Assessing How Consumers Interpret and Act on Results From At-Home COVID-19 Self-test Kits: A Randomized Clinical Trial.

IMPORTANCE: The US Food and Drug Administration (FDA) authorized SARS-CoV-2 rapid at-home self-test kits for individuals with and without symptoms. How appropriately users interpret and act on the results of at-home COVID-19 self-tests is unknown. OBJECTIVE: To assess how users of at-home COVID-19 self-test kits interpret and act on results when given instructions authorized by the FDA, instructions based on decision science principles, or no instructions. DESIGN, SETTING, AND PARTICIPANTS: A randomized clinical trial was conducted of 360 adults in the US who were recruited in April 2021 to complete an online survey on their interpretation of at-home COVID-19 self-test results. Participants were given 1 of 3 instruction types and were presented with 1 of 4 risk scenarios. Participants were paid $5 and had a median survey completion time of 8.7 minutes. Data analyses were performed from June to July 2021. INTERVENTION: Participants were randomized to receiving either the FDA-authorized instructions (authorized), the intervention instructions (intervention), or no instructions (control), and to 1 of 4 scenarios: 3 with a high pretest probability of infection (COVID-19 symptoms and/or a close contact with COVID-19) and 1 with low pretest probability (no symptoms and no contact). The intervention instructions were designed using decision science principles. MAIN OUTCOMES AND MEASURES: Proportion of participants in the high pretest probability scenarios choosing to quarantine per federal recommendations and perceived probabilities of infection given a negative or positive COVID-19 test result. A Bonferroni correction accounted for multiple comparisons (3 instruction types × 4 scenarios; α = 0.004). RESULTS: After excluding 22 individuals who completed the survey too quickly, the responses of 338 participants (median [IQR] age, 38 [31 to 48] years; 154 (46%) women; 215 (64%) with a college degree or higher) were included in the study analysis. Given a positive test result, 95% (322 of 338; 95% CI, 0.92 to 0.97) of the total participants appropriately chose to quarantine regardless of which instructions they had received. Given a negative test result, participants in the high pretest probability scenarios were more likely to fail to quarantine appropriately with the authorized instructions (33%) than with the intervention (14%; 95% CI for the 19% difference, 6% to 31%; P = .004) or control (24%; 95% CI for the 9% difference, -4% to 23%; P = .02). In the low pretest probability scenario, the proportion choosing unnecessary quarantine was higher with the authorized instructions (31%) than with the intervention (22%; 95% CI for the 9% difference, -14% to 31%) or control (10%; 95% CI for the 21% difference, 0.5% to 41%)-neither comparison was statistically significant (P = .05 and P = .20 respectively). CONCLUSIONS AND RELEVANCE: The findings of this randomized clinical trial indicate that at-home COVID-19 self-test kit users relying on the authorized instructions may not follow the Centers for Disease Control and Prevention's quarantine recommendations, producing unintended risks and unnecessary disruptions. Redesigned instructions that follow decision science principles may improve compliance. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04758299.

A Procedure for Eliciting Women's Preferences for Breast Cancer Screening Frequency.

BACKGROUND: We evaluate the construct validity of a proposed procedure for eliciting lay preferences among health care policy options, suited for structured surveys. It is illustrated with breast cancer screening, a domain in which people may have heterogeneous preferences. METHODS: Our procedure applies behavioral decision research principles to eliciting preferences among policy options expressed in quantitative terms. Three-hundred women older than 18 y without a history of breast cancer were recruited through Amazon MTurk. Participants evaluated 4 screening options for each of 4 groups of women, with varying risk of breast cancer. Each option was characterized by estimates of 3 primary outcomes: breast cancer deaths, false alarms, and overdiagnosis resulting in unnecessary treatment of cancers that would not progress. These estimates were based on those currently being developed by the Breast Cancer Surveillance Consortium. For each risk group, participants stated how frequently they would wish to receive screening, if the predicted outcomes applied to them. RESULTS: A preregistered test found that preferences were robust enough to be unaffected by the order of introducing and displaying the outcomes. Other tests of construct validity also suggested that respondents generally understood the task and expressed consistent preferences. Those preferences were related to participants' age and mammography history but not to measures of their numeracy, subjective numeracy, or demographics. There was considerable heterogeneity in their preferences. CONCLUSIONS: Members of the public can be engaged more fully in informing future screening guidelines if they evaluate the screening options characterized by the expected health outcomes expressed in quantitative terms. We offer and evaluate such a procedure, in terms of its construct validity with a diverse sample of women. HIGHLIGHTS: A novel survey method for eliciting lay preferences for breast cancer screening is proposed and evaluated in terms of its construct validity.Participants were generally insensitive to irrelevant task features (e.g., order of presentation) and sensitive to relevant ones (e.g., quantitative estimates of breast cancer risk, harms from screening).The proposed method elicits lay preferences in terms that can inform future screening guidelines, potentially improving communication between the public and policy makers.

Physicians' cognitive approach to prognostication after cardiac arrest.

OBJECTIVE: Elucidate how physicians formulate a neurological prognosis after cardiac arrest and compare differences between experts and general providers. METHODS: We performed semi-structured interviews with experts in post-arrest care and general physicians. We created an initial model and interview guide based on professional society guidelines. Two authors independently coded interviews based on this initial model, then identified new topics not included in it. To describe individual physicians' cognitive approach to prognostication, we created a graphical representation. We summarized these individual "mental models" into a single overall model, as well as two models stratified by expertise. RESULTS: We performed 36 interviews (17 experts and 19 generalists), most of whom practice in Europe (23) or North America (12). Participants described their approach to prognosis formulation as complex and iterative, with sequential and repeated data acquisition, interpretation, and prognosis formulation. Eventually, this cycle results in a final prognosis and treatment recommendation. Commonly mentioned factors were diagnostic test performance, time from arrest, patient characteristics. Participants also discussed factors rarely discussed in prognostication research including physician and hospital characteristics. We found no substantial differences between experts and general physicians. CONCLUSION: Physicians' cognitive approach to neurologic prognostication is complex and influenced by many factors, including some rarely considered in current research. Understanding these processes better could inform interventions designed to aid physicians in prognostication.

Media exposure, risk perceptions, and fear: Americans' behavioral responses to the Ebola public health crisis.

We examined media exposure, psychological fear and worry, perceptions of risk, and health protective behaviors surrounding the 2014 Ebola virus outbreak in a probability-based, representative, national sample of Americans (N = 3447). Structural equation models examined relationships between amount (hours/day) and content (e.g., graphic images of dead bodies) of media exposure and counts of self-reported health protective behaviors that participants performed or would perform if Ebola spread to their community. Ebola-related risk perceptions and fear and worry were potential mediators. Greater total hours and more graphic media exposure positively correlated with more fear and worry; greater total hours of media exposure also positively correlated with higher perceived risk. Higher risk perceptions were associated with more health protective behaviors performed and intended. Greater fear and worry were associated with more behaviors performed. Amount and content of media exposure exhibited indirect effects on behaviors performed; amount of media exposure had indirect effects on intentions. Media may help promote health protective behaviors during public health threats; the amount and content should be congruent with threat to minimize distress and maximize resources.