Numeric, verbal, and visual formats of conveying health risks: suggested best practices and future recommendations

Awareness of cardiovascular risk among persons with type 2 diabetes: a qualitative study

PURPOSE

To describe the process of becoming aware of and acting on personal cardiovascular (CVD) risk in type 2 diabetes (T2D).

METHOD

A purposive sample of 14 persons living with T2D participated in semi-structured, open-ended, in-dept interviews. The interviews were analysed with grounded theory.

RESULT

The analysis identified the core category "Balancing emotions, integrating knowledge and understanding to achieve risk awareness and act on it." Five categories describe the movement from not being aware of the risk of cardiovascular disease (CVD) to becoming aware of this risk and taking action to reduce it. Persons with T2D need to transform their knowledge and experience of CVD risk and incorporate it in their individual situations. Emotional and existential experiences of CVD risk can lead to awareness about the severity of the condition and contribute to increased motivation for self-management. However, an overly high emotional response can be overwhelming and may result in insufficient self-management.

CONCLUSION

Persons with T2D seemed not to fully grasp their increased risk of CVD or recognize that self-management activities were aimed at reducing this risk. However, their awareness of CVD risk gradually increased as they came to understand the severity of T2D and became more emotionally and existentially engaged.

Evaluating Multi-Jurisdictional Enteric Illness Outbreak Messaging in Canada: A Content Analysis of Public Health Notices

Effective risk communication during enteric illness outbreaks requires the provision of clear and consistent information to diverse audiences to reduce risk of exposure, inform behavior changes, and prevent illness. Most enteric illnesses are caused by pathogens transmitted through consumption of contaminated food or water, contact with animals, or person-to-person contact. When multi-jurisdictional outbreaks occur, the Public Health Agency of Canada posts web-based Public Health Notices (PHNs) to inform Canadians. This study evaluated the comprehensibility of PHNs to optimize federal risk communication approaches. Publicly available web-based PHNs (n = 42) from 2014-2022 were obtained. A codebook was developed using the Centers for Disease Control and Prevention's (CDC) Clear Communication Index (CCI) and Health Belief Model (HBM) and systematically applied. A SMOG readability calculator was used to determine reading grade level. Descriptive statistics were calculated to summarize coded data. The average reading grade level was above Grade 12 (13.9 ± 1.1). PHNs communicated the nature of the risk (100%) and behavioral recommendations (96.5%) clearly. An active voice was sometimes used (61.9%), but numerical information was less commonly presented using best practices (38.1%). The HBM was fully incorporated in seven PHNs, with most PHNs using five of six constructs (66.7%). PHNs shared similar information in a consistent order (75.0%). Aligning PHNs to best practices in risk communication is recommended, including writing content at a reading grade level that supports comprehension by diverse audiences, following the CCI to increase clarity, including all HBM constructs to promote behavior change, and maintaining message consistency.

Exploring the MAPPING application to facilitate risk communication and shared decision-making between physicians and patients with gynaecological cancer

This is an observational study in which we evaluated current levels of risk communication (RC) among gynaecological oncologists and their view on the Mapping All Patient Probabilities in Numerical Graphs (MAPPING) application as a possible tool to facilitate RC and shared decision-making (SDM). In part A, we audio-recorded 29 conversations between gynaecological oncologists and patients when discussing treatment options. In part B, interviews were performed with eight gynaecological oncologists.RC and SDM were measured using two observer-based measures, that is, the RC content (RCC) tool (scale 0-2) and the OPTION-5 instrument (scale 0-100). We used CollaboRATE questionnaire (scale 0-10) and a self-developed survey to assess patient-reported RC and SDM. In part B, we evaluated physicians' attitudes regarding the use of the MAPPING application to support RC. Patients were minimally involved in the decision-making process (OPTION-5 25.9%±13.4 RCC 0.21±0.18). Patient-reported SDM was high (mean collaboRATE score 9.19±1.79) and patients preferred receiving numeric information, whereas most physicians used qualitative risk terms rather than exact numbers. In part B, gynaecologists had a positive attitude towards the MAPPING application. However, they stated that the app was difficult to use improvement of layout and better implementations are needed.

Patients' perceptions matter: Risk communication and psychosocial factors in orthodontics

INTRODUCTION

Effective risk communication is essential for achieving patient-centered oral health care, but the limited understanding of patients' subjective perceptions of orthodontic-related risks hinders this process. This study aimed to investigate adults' awareness, concerns, and risk-avoidance behaviors about long-term orthodontic risks, exploring their relationship with psychosocial factors.

METHODS

We included 498 adult patients (mean age, 27.3 ± 6.8 years; women, 75.5%) during their initial visits to the orthodontic department at a hospital in Chengdu, China. Participants' understanding of orthodontic risks was gauged before and after exposure to the Oral Health Education Comics (OHEC), a specifically designed digital tool. Concurrently, we used logistic regression models to investigate the associations between patients' depression, anxiety, self-esteem, perfectionism, and dentofacial esthetics with risk perceptions.

RESULTS

Approximately 79.5% of participants initially reported low awareness of orthodontic risks, with most knowledge from online sources. Notably, the percentage of participants with high awareness increased to 64.8% after OHEC. The negative facial soft-tissue change was most concerning for participants: 53.4% showed high concerns, and 28.1% showed high avoidance. Furthermore, linear regression indicated positive associations between depression (β = 0.42 [95% confidence interval {CI}, 0.07-0.77]) and anxiety (β = 0.76 [95% CI, 0.35-1.18]) with orthodontic risk concerns, whereas risk avoidance was positively associated with depression (β = 0.62 [95% CI, 0.27-0.97]), anxiety (β = 1.09 [95% CI, 0.68-1.50]), and perfectionism (β = 0.24 [95% CI, 0.02-0.46]).

CONCLUSIONS

Findings emphasize the imperative of streamlined risk communication in orthodontics. By incorporating comprehensible tools such as OHEC and integrating psychosocial evaluations, more refined patient-practitioner communication and psychosomatic-based dental care can be achieved.

Numerical versus graphical aids for decision-making in a multi-cue signal identification task

Decision aids are commonly used in tactical decision-making environments to help humans integrate base-rate and multi-cue information. However, it is important that users appropriately trust and rely on aids. Decision aids can be presented in many ways, but the literature lacks clarity over the conditions surrounding their effectiveness. This research aims to determine whether a numerical or graphical aid more effectively supports human performance, and explores the relationships between aid presentation, trust, and workload. Participants (N = 30) completed a signal-identification task that required integration of readings from a set of three dynamic gauges. Participants experienced three conditions: unaided, using a numerical aid, and using a graphical aid. The aids combined gauge and base-rate information in a statistically-optimal fashion. Participants also indicated how much they trusted the system and how hard they worked during the task. Analyses explored the impact of aid condition on sensitivity, response bias, response time, trust, and workload. Both the numerical and graphical aids produced significant increases in sensitivity and trust, and significant decreases in workload in comparison to the unaided condition. The difference in response time between the graphical and unaided conditions approached significance, with participants responding faster using the graphical aid without decrements in sensitivity. Significant interactions between aid and signal type indicated that both aided conditions promoted faster responding to non-hostile signals, with larger mean differences in the graphical aid condition. Practically, graphical aids in which suggestions are more salient to users may promote faster responding in tactical environments, with negligible cost of accuracy.

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.

Desired dementia care towards end of life: Development and experiences of implementing a new approach to improve person-centred dementia care

AIMS

To describe the co-creation of the 'Desired Dementia Care Towards End of Life' (DEDICATED) approach to improve person-centred palliative care for individuals with dementia and to describe the experiences of healthcare professionals during the approach's implementation.

METHODS

A needs assessment, comprising both qualitative and quantitative studies, informed palliative care needs of healthcare professionals, family caregivers and individuals with dementia. The approach was co-created with healthcare and education professionals, guided by the findings. Then, healthcare professionals were trained to implement the approach in their organizations. From April to June 2022, semi-structured interviews with actively engaged professionals were analysed using Conventional Content Analysis.

RESULTS

The needs assessment yielded six key themes: (1) raising palliative care awareness, (2) familiarization with a person with dementia, (3) communication about future care preferences, (4) managing pain and responsive behaviour, (5) enhancing interprofessional collaboration in advance care planning and (6) improving interprofessional collaboration during transitions to nursing homes. Interviews with 17 healthcare professionals revealed that active involvement in co-creating or providing feedback facilitated implementation. Overall, the DEDICATED approach was perceived as a valuable toolkit for optimizing palliative care for people with dementia and their loved ones.

CONCLUSION

Co-creating the DEDICATED approach with healthcare professionals facilitated implementation in daily practice. The approach was considered helpful in enhancing person-centred palliative dementia care.

IMPACT STATEMENT

This study underscores the importance of active involvement of healthcare professionals in the research and development of new interventions or tools for palliative care, which can influence the successful implementation, dissemination and sustained usage of the developed tools.

IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE

The developed approach can improve person-centred palliative care for individuals with dementia, ultimately improving their quality of life and that of their loved ones.

REPORTING METHOD

This study used the Consolidated Criteria for Reporting Qualitative Research.

PATIENT OF PUBLIC CONTRIBUTION

No patient or public contribution.

Clinical Risk Assessment and Prediction in Congenital Heart Disease Across the Lifespan: JACC Scientific Statement

Congenital heart disease (CHD) comprises a range of structural anomalies, each with a unique natural history, evolving treatment strategies, and distinct long-term consequences. Current prediction models are challenged by generalizability, limited validation, and questionable application to extended follow-up periods. In this JACC Scientific Statement, we tackle the difficulty of risk measurement across the lifespan. We appraise current and future risk measurement frameworks and describe domains of risk specific to CHD. Risk of adverse outcomes varies with age, sex, genetics, era, socioeconomic status, behavior, and comorbidities as they evolve through the lifespan and across care settings. Emerging technologies and approaches promise to improve risk assessment, but there is also need for large, longitudinal, representative, prospective CHD cohorts with multidimensional data and consensus-driven methodologies to provide insight into time-varying risk. Communication of risk, particularly with patients and their families, poses a separate and equally important challenge, and best practices are reviewed.

A Practical Significance Bias in Laypeople's Evaluation of Scientific Findings

People often rely on scientific findings to help them make decisions-however, failing to report effect magnitudes might lead to a potential bias in assuming findings are practically significant. Across two online studies (Prolific; N = 800), we measured U.S. adults' endorsements of expensive interventions described in media reports that led to effects that were small, large, or of unreported magnitude between groups. Participants who viewed interventions with unreported effect magnitudes were more likely to endorse interventions compared with those who viewed interventions with small effects and were just as likely to endorse interventions as those who viewed interventions with large effects, suggesting a practical significance bias. When effect magnitudes were reported, participants on average adjusted their evaluations accordingly. However, some individuals, such as those with low numeracy skills, were more likely than others to act on small effects, even when explicitly prompted to first consider the meaningfulness of the effect.

Clearing the air: evaluating institutions' social media health messaging on wildfire and smoke risks in the US Pacific Northwest

BACKGROUND

Wildfire smoke contributes substantially to the global disease burden and is a major cause of air pollution in the US states of Oregon and Washington. Climate change is expected to bring more wildfires to this region. Social media is a popular platform for health promotion and a need exists for effective communication about smoke risks and mitigation measures to educate citizens and safeguard public health.

METHODS

Using a sample of 1,287 Tweets from 2022, we aimed to analyze temporal Tweeting patterns in relation to potential smoke exposure and evaluate and compare institutions' use of social media communication best practices which include (i) encouraging adoption of smoke-protective actions; (ii) leveraging numeric, verbal, and Air Quality Index risk information; and (iii) promoting community-building. Tweets were characterized using keyword searches and the Linguistic Inquiry and Word Count (LIWC) software. Descriptive and inferential statistics were carried out.

RESULTS

44% of Tweets in our sample were authored between January-August 2022, prior to peak wildfire smoke levels, whereas 54% of Tweets were authored during the two-month peak in smoke (September-October). Institutional accounts used Twitter (or X) to encourage the adoption of smoke-related protective actions (82% of Tweets), more than they used it to disseminate wildfire smoke risk information (25%) or promote community-building (47%). Only 10% of Tweets discussed populations vulnerable to wildfire smoke health effects, and 14% mentioned smoke mitigation measures. Tweets from Washington-based accounts used significantly more verbal and numeric risk information to discuss wildfire smoke than Oregon-based accounts (p = 0.042 and p = 0.003, respectively); however, Tweets from Oregon-based accounts on average contained a higher percentage of words associated with community-building language (p < 0.001).

CONCLUSIONS

This research provides practical recommendations for public health practitioners and researchers communicating wildfire smoke risks on social media. As exposures to wildfire smoke rise due to climate change, reducing the environmental disease burden requires health officials to leverage popular communication platforms, distribute necessary health-related messaging rapidly, and get the message right. Timely, evidence-based, and theory-driven messaging is critical for educating and empowering individuals to make informed decisions about protecting themselves from harmful exposures. Thus, proactive and sustained communications about wildfire smoke should be prioritized even during wildfire "off-seasons."

Stated-Preference Survey Design and Testing in Health Applications

Following the conceptualization of a well-formulated and relevant research question, selection of an appropriate stated-preference method, and related methodological issues, researchers are tasked with developing a survey instrument. A major goal of designing a stated-preference survey for health applications is to elicit high-quality data that reflect thoughtful responses from well-informed respondents. Achieving this goal requires researchers to design engaging surveys that maximize response rates, minimize hypothetical bias, and collect all the necessary information needed to answer the research question. Designing such a survey requires researchers to make numerous interrelated decisions that build upon the decision context, selection of attributes, and experimental design. Such decisions include considering the setting(s) and study population in which the survey will be administered, the format and mode of administration, and types of contextual information to collect. Development of a survey is an interactive process in which feedback from respondents should be collected and documented through qualitative pre-test interviews and pilot testing. This paper describes important issues to consider across all major steps required to design and test a stated-choice survey to elicit patient preferences for health preference research.

Probability and informed consent

In this paper, we illustrate some serious difficulties involved in conveying information about uncertain risks and securing informed consent for risky interventions in a clinical setting. We argue that in order to secure informed consent for a medical intervention, physicians often need to do more than report a bare, numerical probability value. When probabilities are given, securing informed consent generally requires communicating how probability expressions are to be interpreted and communicating something about the quality and quantity of the evidence for the probabilities reported. Patients may also require guidance on how probability claims may or may not be relevant to their decisions, and physicians should be ready to help patients understand these issues.

Talking numbers: how women and providers use risk scores during and after risk counseling - a qualitative investigation from the NRG Oncology/NSABP DMP-1 study

OBJECTIVES

Little research exists on how risk scores are used in counselling. We examined (a) how Breast Cancer Risk Assessment Tool (BCRAT) scores are presented during counselling; (b) how women react and (c) discuss them afterwards.

DESIGN

Consultations were video-recorded and participants were interviewed after the consultation as part of the NRG Oncology/National Surgical Adjuvant Breast and Bowel Project Decision-Making Project 1 (NSABP DMP-1).

SETTING

Two NSABP DMP-1 breast cancer care centres in the USA: one large comprehensive cancer centre serving a high-risk population and an academic safety-net medical centre in an urban setting.

PARTICIPANTS

Thirty women evaluated for breast cancer risk and their counselling providers were included.

METHODS

Participants who were identified as at increased risk of breast cancer were recruited to participate in qualitative study with a video-recorded consultation and subsequent semi-structured interview that included giving feedback and input after viewing their own consultation. Consultation videos were summarised jointly and inductively as a team.tThe interview material was searched deductively for text segments that contained the inductively derived themes related to risk assessment. Subgroup analysis according to demographic variables such as age and Gail score were conducted, investigating reactions to risk scores and contrasting and comparing them with the pertinent video analysis data. From this, four descriptive categories of reactions to risk scores emerged. The descriptive categories were clearly defined after 19 interviews; all 30 interviews fit principally into one of the four descriptive categories.

RESULTS

Risk scores were individualised and given meaning by providers through: (a) presenting thresholds, (b) making comparisons and (c) emphasising or minimising the calculated risk. The risk score information elicited little reaction from participants during consultations, though some added to, agreed with or qualified the provider's information. During interviews, participants reacted to the numbers in four primary ways: (a) engaging easily with numbers; (b) expressing greater anxiety after discussing the risk score; (c) accepting the risk score and (d) not talking about the risk score.

CONCLUSIONS

Our study highlights the necessity that patients' experiences must be understood and put into relation to risk assessment information to become a meaningful treatment decision-making tool, for instance by categorising patients' information engagement into types.

TRIAL REGISTRATION NUMBER

NCT01399359.

Medical AI, inductive risk and the communication of uncertainty: the case of disorders of consciousness

Some patients, following brain injury, do not outwardly respond to spoken commands, yet show patterns of brain activity that indicate responsiveness. This is 'cognitive-motor dissociation' (CMD). Recent research has used machine learning to diagnose CMD from electroencephalogram recordings. These techniques have high false discovery rates, raising a serious problem of inductive risk. It is no solution to communicate the false discovery rates directly to the patient's family, because this information may confuse, alarm and mislead. Instead, we need a procedure for generating case-specific probabilistic assessments that can be communicated clearly. This article constructs a possible procedure with three key elements: (1) A shift from categorical 'responding or not' assessments to degrees of evidence; (2) The use of patient-centred priors to convert degrees of evidence to probabilistic assessments; and (3) The use of standardised probability yardsticks to convey those assessments as clearly as possible.

Communication of benefits and harms in shared decision making with patients with limited health literacy: A systematic review of risk communication strategies

OBJECTIVES

Risk communication (RC), as part of shared decision making, is challenging with people with limited health literacy (LHL). We aim to provide an overview of strategies to communicate benefits and harms of diagnostic and treatment options to this group.

METHODS

We systematically searched PubMed, Embase, Cinahl and PsycInfo. We included 28 studies on RC in informed/shared decision making without restriction to a health setting or condition and using a broad conceptualization of health literacy. Two researchers independently selected studies and one researcher performed data extraction. We descriptively compared findings for people with LHL towards recommendations for RC.

RESULTS

Health literacy levels varied in the included studies. Most studies used experimental designs, primarily on visual RC. Findings show verbal RC alone should be avoided. Framing of risk information influences risk perception (less risky when positively framed, riskier when negatively framed). Most studies recommended the use of icon arrays. Graph literacy should be considered when using visual RC.

CONCLUSIONS

The limited available evidence suggests that recommended RC strategies seem mainly to be valid for people with LHL, but more research is required.

PRACTICE IMPLICATIONS

More qualitative research involving people with LHL is needed to gain further in-depth insights into optimal RC strategies.

PROTOCOL REGISTRATION

PROSPERO ID 275022.

Information provision and decision-making in the treatment of abdominal aortic aneurysm: A qualitative study of patient experience

INTRODUCTION

Shared decision making (SDM) refers to patients and health care professionals working together to reach a decision about treatment/care. In abdominal aortic aneurysm (AAA) treatment options are influenced by patients' clinical characteristics, their preferences, and potential trade-offs between alternative interventions. This is a prime example of where SDM is essential to ensure the right decision is made for the right patient, yet we have little understanding of what happens in practice. This study explored patient experiences to understand SDM practice in AAA surgery.

METHODS

We used a qualitative approach to describe, and identify improvements to, current treatment decision making in abdominal aortic aneurysm (AAA) surgery. Two groups of patients were interviewed: those at the point of discussing treatment options (with corresponding digitally recorded consultation data) and following surgical intervention from one hospital. Framework analysis was used.

RESULTS

Fifteen patients were interviewed, seven at the point of discussing treatment options and eight following surgical intervention. Timing, format and sources of information, verbal framing of interventions and level of patient engagement were key themes. Four areas for improvement were identified: earlier provision and more detailed written information along with signposting to quality on-line information; both intervention options, risks, benefits, and consequences, were not always discussed; some clinicians were somewhat directive in the decision-making process; and patients' treatment values/preferences were not explored-the only example was in one of the eight recorded consultations. Patients could feel overwhelmed by the information and decision and fearful of the impending surgery.

CONCLUSIONS

More emphasis should be placed on the provision of full information and the exploration of patient values and preferences for treatment. Clinician training and support for patients, including decision aids, could facilitate the decision-making process. Providing written information earlier and guidance on reliable on-line resources would benefits patients and their families.

Healthcare providers' understanding of data displays of clinical trial information: a scoping review of the literature

BACKGROUND

Healthcare providers often encounter clinical trial results in the form of visual data displays. Although there is a robust literature on patient responses to data displays in medical settings, less is known about how providers comprehend and apply this information. Our study provides a scoping review of the literature on providers' reactions to and perceptions of data displays.

METHODS

We searched article databases (PubMed, PsycINFO, Web of Science, Cumulative Index to Nursing and Allied Health Literature, the Cochrane Library) supplemented by handsearching. Eligible articles were published in English from 1990 to 2020.

RESULTS

We identified 15 articles meeting our criteria. Studies with physicians were more prevalent (13/15) than those with other healthcare providers (6/15). Commonly assessed outcomes included objective (10/15) and subjective comprehension (4/15), preference for certain data display formats (6/15), and hypothetical decision-making around prescribing (4/15). In studies that assessed comprehension of clinical trial concepts, scores were average or below what would be considered mastery of the information. Data display formats that were preferred did not always correlate with better comprehension of information; lesser preferred formats (e.g. icon array) often resulted in better comprehension.

CONCLUSION

Our findings suggest that healthcare providers may not accurately interpret complex types of data displays, and it is unknown if such limitations affect actual decision-making. Interventions are needed to enhance comprehension of complex data displays within the context of prescription drug professional promotion.

Strategies for communicating scientific evidence on healthcare to managers and the population: a scoping review

BACKGROUND

Health evidence needs to be communicated and disseminated in a manner that is clearly understood by decision-makers. As an inherent component of health knowledge translation, communicating results of scientific studies, effects of interventions and health risk estimates, in addition to understanding key concepts of clinical epidemiology and interpreting evidence, represent a set of essential instruments to reduce the gap between science and practice. The advancement of digital and social media has reshaped the concept of health communication, introducing new, direct and powerful communication platforms and gateways between researchers and the public. The objective of this scoping review was to identify strategies for communicating scientific evidence in healthcare to managers and/or population.

METHODS

We searched Cochrane Library, Embase®, MEDLINE® and other six electronic databases, in addition to grey literature, relevant websites from related organizations for studies, documents or reports published from 2000, addressing any strategy for communicating scientific evidence on healthcare to managers and/or population.

RESULTS

Our search identified 24 598 unique records, of which 80 met the inclusion criteria and addressed 78 strategies. Most strategies focused on risk and benefit communication in health, were presented by textual format and had been implemented and somehow evaluated. Among the strategies evaluated and appearing to yield some benefit are (i) risk/benefit communication: natural frequencies instead of percentages, absolute risk instead relative risk and number needed to treat, numerical instead nominal communication, mortality instead survival; negative or loss content appear to be more effective than positive or gain content; (ii) evidence synthesis: plain languages summaries to communicate the results of Cochrane reviews to the community were perceived as more reliable, easier to find and understand, and better to support decisions than the original summaries; (iii) teaching/learning: the Informed Health Choices resources seem to be effective for improving critical thinking skills.

CONCLUSION

Our findings contribute to both the knowledge translation process by identifying communication strategies with potential for immediate implementation and to future research by recognizing the need to evaluate the clinical and social impact of other strategies to support evidence-informed policies. Trial registration protocol is prospectively available in MedArxiv (doi.org/10.1101/2021.11.04.21265922).

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 effect of numeric information about the likelihood of receiving a false negative or false positive result on people's attitudes towards colorectal cancer screening using faecal immunochemical testing (FIT)

OBJECTIVE

To examine the impact of numeric risk information about false negative (FN) and false positive (FP) rates in fecal immunochemical testing (FIT) on attitudes towards screening.

METHODS

102 people aged 45-55, living in the UK, read 6 hypothetical vignettes presented online about the use of FIT kits to detect colorectal cancer, in which information about FN and FP rates was systematically varied.

RESULTS

Numeric FN risk information reduced people's interest in screening, perception of screening effectiveness and lowered trust in screening compared to verbal FN information. Verbal FN information reduced perceptions of screening effectiveness and trust compared to no FN information. People with high subjective numeracy reported lower trust in screening following the provision of numeric FN information but numeracy did not moderate any other associations. FP information did not affect attitudes towards FIT testing.

CONCLUSION

Numeric FN risk information decreased people's perceptions of screening effectiveness and trust in the results of screening. While it influenced people's interest in screening, the effect was small.

PRACTICE IMPLICATIONS

Numeric FN information has a small effect on interest in screening and could promote informed decision making without affecting screening uptake.

Taking the Shortcut: Simplifying Heuristics in Discrete Choice Experiments

Health-related discrete choice experiments (DCEs) information can be used to inform decision-making on the development, authorisation, reimbursement and marketing of drugs and devices as well as treatments in clinical practice. Discrete choice experiment is a stated preference method based on random utility theory (RUT), which imposes strong assumptions on respondent choice behaviour. However, respondents may use choice processes that do not adhere to the normative rationality assumptions implied by RUT, applying simplifying decision rules that are more selective in the amount and type of processed information (i.e., simplifying heuristics). An overview of commonly detected simplifying heuristics in health-related DCEs is lacking, making it unclear how to identify and deal with these heuristics; more specifically, how researchers might alter DCE design and modelling strategies to accommodate for the effects of heuristics. Therefore, the aim of this paper is three-fold: (1) provide an overview of common simplifying heuristics in health-related DCEs, (2) describe how choice task design and context as well as target population selection might impact the use of heuristics, (3) outline DCE design strategies that recognise the use of simplifying heuristics and develop modelling strategies to demonstrate the detection and impact of simplifying heuristics in DCE study outcomes.

Linguistic analysis of plain language summaries and corresponding scientific summaries of Cochrane systematic reviews about oncology interventions

BACKGROUND

Cochrane plain language summaries (PLSs) are an important format to present high-quality healthcare evidence to patients with cancer and their families. They should be written in a way everyone can understand, since they serve as a tool in decision-making and present a bridge to overcome the gap between the healthcare users and professionals.

OBJECTIVE

The aim of the study was to assess the language characteristics of PLSs of Cochrane systematic reviews of oncology interventions in comparison with corresponding Cochrane scientific abstracts (SAs).

METHODS

In this cross-sectional study, we included all Cochrane PLSs and SAs of systematic reviews of oncology interventions available in the Cochrane Database of Systematic Reviews. We assessed text readability, measured using the Simple Measure of Gobbledygook (SMOG) index, and the prevalence of words related to different language tones (clout, authenticity, emotions and analytical tones). Two independent assessors categorized the conclusiveness of the efficacy of interventions into nine categories.

RESULTS

The overall median SMOG index for 275 PLSs was 13.0 (95% confidence interval [CI] 12.8-13.3). Readability scores did not differ across Cochrane Review Groups. SAs had a higher readability index than the corresponding PLSs (median = 16.6, 95% CI = 16.4-16.8). Regarding linguistic characteristics, PLSs were shorter than SAs, with less use of analytical tone, but more use of a positive emotional tone and authenticity. Overall, the 'Unclear' category of conclusiveness was the most common among all PLSs. Also, PLSs with 'No evidence' conclusions were the shortest and had the lowest SMOG index.

CONCLUSION

PLSs of Cochrane systematic reviews of oncological interventions have low readability and most give unclear conclusions about the efficacy of interventions. PLSs should be simplified so that patients and their families can benefit from appropriate health information on evidence synthesis. Further research is needed into reasons for unclear language to describe evidence from oncology trials.

Quantitative Benefit-Risk Assessment in Medical Product Decision Making: A Good Practices Report of an ISPOR Task Force

Benefit-risk assessment is commonly conducted by drug and medical device developers and regulators, to evaluate and communicate issues around benefit-risk balance of medical products. Quantitative benefit-risk assessment (qBRA) is a set of techniques that incorporate explicit outcome weighting within a formal analysis to evaluate the benefit-risk balance. This report describes emerging good practices for the 5 main steps of developing qBRAs based on the multicriteria decision analysis process. First, research question formulation needs to identify the needs of decision makers and requirements for preference data and specify the role of external experts. Second, the formal analysis model should be developed by selecting benefit and safety endpoints while eliminating double counting and considering attribute value dependence. Third, preference elicitation method needs to be chosen, attributes framed appropriately within the elicitation instrument, and quality of the data should be evaluated. Fourth, analysis may need to normalize the preference weights, base-case and sensitivity analyses should be conducted, and the effect of preference heterogeneity analyzed. Finally, results should be communicated efficiently to decision makers and other stakeholders. In addition to detailed recommendations, we provide a checklist for reporting qBRAs developed through a Delphi process conducted with 34 experts.

Verbal Descriptions of the Probability of Treatment Complications Lead to High Variability in Risk Perceptions: A Survey Study

OBJECTIVE

To assess whether different methods for communicating the probability of treatment complications for operative and nonoperative appendicitis treatments result in differences in risk perception.

BACKGROUND

Surgeons must communicate the probability of treatment complications to patients, and how risks are communicated may impact the accuracy and variability in patient risk perceptions and ultimately their decision making.

METHODS

A series of online surveys of American adults communicated the probability of complications associated with surgical or antibiotic treatment of acute appendicitis. Probability was communicated with verbal descriptors (eg, "uncommon"), point estimates (eg, "3% risk"), or risk ranges (eg, "1% to 5%"). Respondents then estimated the probability of a complication for a "typical patient with appendicitis." The Fligner-Killeen test of homogeneity of variance was used to compare the variability in respondent risk estimates based on the method of probability communication.

RESULTS

Among 296 respondents, variance in probability estimates was significantly higher when verbal descriptions were used compared to point estimates ( P < 0.001) or risk ranges ( P < 0.001). Identical verbal descriptors produced meaningfully different risk estimates depending on the complication being described. For example, "common" was perceived as a 45.6% for surgical site infection but 61.7% for antibiotic-associated diarrhea.

CONCLUSION

Verbal probability descriptors are associated with widely varying and inaccurate perceptions about treatment risks. Surgeons should consider alternative ways to communicate probability during informed consent and shared decision-making discussions.

MyLynch: A Patient-Facing Clinical Decision Support Tool for Genetically-Guided Personalized Medicine in Lynch Syndrome

Lynch syndrome (LS) is a hereditary cancer susceptibility condition associated with varying cancer risks depending on which of the five causative genes harbors a pathogenic variant; however, lifestyle and medical interventions provide options to lower those risks. We developed MyLynch, a patient-facing clinical decision support (CDS) web application that applies genetically-guided personalized medicine (GPM) for individuals with LS. The tool was developed in R Shiny through a patient-focused iterative design process. The knowledge base used to estimate patient-specific risk leveraged a rigorously curated literature review. MyLynch informs LS patients of their personal cancer risks, educates patients on relevant interventions, and provides patients with adjusted risk estimates, depending on the interventions they choose to pursue. MyLynch can improve risk communication between patients and providers while also encouraging communication among relatives with the goal of increasing cascade testing. As genetic panel testing becomes more widely available, GPM will play an increasingly important role in patient care, and CDS tools offer patients and providers tailored information to inform decision-making. MyLynch provides personalized cancer risk estimates and interventions to lower these risks for patients with LS.

Identifying best practices for disclosure of amyloid imaging results: A randomized controlled trial

INTRODUCTION

Empirical studies on effective communication for amyloid disclosure in mild cognitive impairment (MCI) are lacking. We aimed to study the impact of six communication strategies.

METHOD

We performed a randomized controlled trial with seven randomly assigned, video-vignette conditions: six emphasizing a communication strategy and one basic condition. All showed a scripted consultation of a neurologist disclosing positive amyloid positron emission tomography (PET) scan results to an MCI patient. Healthy individuals (N = 1017; mean age ± SD 64 ± 8, 808 (79%) female) were instructed to imagine themselves in the video, answered questionnaires assessing information recall, emotional state, and behavioral intentions, and evaluate the physician/information.

RESULTS

"Risk best practice" resulted in highest free recall compared to other strategies (P < .05), except "emotional support". Recall in "emotional support" was better compared to "basic-' and elaborate information"(P < .05). "Risk best practice" resulted in the highest uncertainty (P < .001). "Teach-back" and "emotional support" contributed to the highest evaluations (P -values < .01).

CONCLUSION

Risk communication best practices, attending to emotions, and teach-back techniques enhance information recall of amyloid-PET results, and could contribute to positive care evaluations.

Leveraging Math Cognition to Combat Health Innumeracy

Rational numbers (i.e., fractions, percentages, decimals, and whole-number frequencies) are notoriously difficult mathematical constructs. Yet correctly interpreting rational numbers is imperative for understanding health statistics, such as gauging the likelihood of side effects from a medication. Several pernicious biases affect health decision-making involving rational numbers. In our novel developmental framework, the natural-number bias-a tendency to misapply knowledge about natural numbers to all numbers-is the mechanism underlying other biases that shape health decision-making. Natural-number bias occurs when people automatically process natural-number magnitudes and disregard ratio magnitudes. Math-cognition researchers have identified individual differences and environmental factors underlying natural-number bias and devised ways to teach people how to avoid these biases. Although effective interventions from other areas of research can help adults evaluate numerical health information, they circumvent the core issue: people's penchant to automatically process natural-number magnitudes and disregard ratio magnitudes. We describe the origins of natural-number bias and how researchers may harness the bias to improve rational-number understanding and ameliorate innumeracy in real-world contexts, including health. We recommend modifications to formal math education to help children learn the connections among natural and rational numbers. We also call on researchers to consider individual differences people bring to health decision-making contexts and how measures from math cognition might identify those who would benefit most from support when interpreting health statistics. Investigating innumeracy with an interdisciplinary lens could advance understanding of innumeracy in theoretically meaningful and practical ways.

The role of perceived risk on dishonest decision making during a pandemic

The COVID-19 pandemic presented serious risks to the health and financial wellbeing of millions of people across the world. While many individuals adapted to these challenges through a variety of prosocial and protective behaviors (e.g., social distancing, working from home), many others also engaged in dishonest behaviors (e.g., lying to obtain vaccines or furlough payments). Hence, the COVID-19 pandemic provided a unique context in which to obtain a better understanding of the relationship between risk and dishonesty. Across three preregistered studies, we assessed whether objective risk and perceived risk influenced the decision to behave dishonestly in order to gain access to vaccines and furlough payments during a pandemic. We also assessed the extent to which such dishonesty was deterred by the probability of the dishonesty being detected. We found that heightened health risk perceptions were positively related with lying to obtain a vaccine (Studies 1 and 2), but found no evidence of the same relationship between financial risk perceptions and lying to access furlough payments (Study 2). We also found that the probability of dishonesty being detected had a negative relationship with dishonest behavior (Study 3). In addition, across the three studies, we found that (i) dishonesty was consistently evident in approximately one-third of all of our samples, and (ii) greater dishonesty was associated with older age. We discuss how our findings could be utilized by policy makers to better deter and detect dishonest behaviors during future similar crises.

COVID-19 risk perception framework of the public: an infodemic tool for future pandemics and epidemics

Understanding the risk perceptions of the public is central for risk communications and infodemic management during emergency and preparedness planning as people's behavior depends on how they perceive the related risks. This qualitative study aimed to identify and describe factors related to COVID-19 risk perceptions of the public in Finland and to make this information readily available to those who communicate with the public during crises. The study is part of a larger project exploring crisis narratives through a mixed-methods approach. The study was based on a dataset of over 10,000 comments on the Facebook and Twitter posts of the Finnish Institute of Health and Welfare (THL) between March-May 2021. The data were analyzed qualitatively using thematic analysis. The study identified concepts linked with the pandemic risk perception that included knowledge, perceptions, personal experiences, trust, attitudes, and cultural values. The findings resulted in a framework of risk perceptions that can be used as taxonomy and a set of key concepts and keywords in social listening to monitor risk perception during future epidemics and pandemics.

Assessing strategic, tactical, and operational decision-making and risk in a livestock production chain through experimental simulation platforms

This paper provides a research summary of a series of serious games and simulations that form the basis of an experimental platform for the study of human decision-making and behavior associated with biosecurity across complex livestock production chains. This platform is the first of its kind to address the challenges associated with scaling micro-behavior of biosecurity decision-making to macro-patterns of disease spread across strategic, tactical and operational levels, capturing the roles that facility managers and front-line workers play in making biosecurity decisions under risk and uncertainty. Informational and incentive treatments are tested within each game and simulation. Behavioral theories are used to explain these findings. Results from serious games in the form of behavioral probability distributions are then used to simulate disease incidence and spread across a complex production chain, demonstrating how micro-level behaviors contribute to larger macro-level patterns. In the case of this study, the propensity to adopt micro-level biosecurity practices are applied to a network percolation disease spread model. By presenting the suite of companion models of behavior and disease spread we are able to capture scaling dynamics of complex systems, and in the process, better understand how individual behaviors impact whole systems.

Need for numbers: assessing cancer survivors' needs for personalized and generic statistical information

Background

Statistical information (e.g., on long-term survival or side effects) may be valuable for healthcare providers to share with their patients to facilitate shared decision making on treatment options. In this pre-registered study, we assessed cancer survivors’ need for generic (population-based) versus personalized (tailored towards patient/tumor characteristics) statistical information after their diagnosis. We examined how information coping style, subjective numeracy, and anxiety levels of survivors relate to these needs and identified statistical need profiles. Additionally, we qualitatively explored survivors’ considerations for (not) wanting statistical information.

Methods

Cancer survivors’ need for statistics regarding incidence, survival, recurrence, side effects and quality of life were assessed with an online questionnaire. For each of these topics, survivors were asked to think back to their first cancer diagnosis and to indicate their need for generic and personalized statistics on a 4-point scale (‘not at all’- ‘very much’). Associations between information coping style, subjective numeracy, and anxiety with need for generic and personalized statistics were examined with Pearson’s correlations. Statistical need profiles were identified using latent class analysis. Considerations for (not) wanting statistics were analyzed qualitatively.

Results

Overall, cancer survivors (n = 174) had a higher need for personalized than for generic statistics (p < .001, d = 0.74). Need for personalized statistics was associated with higher subjective numeracy (r = .29) and an information-seeking coping style (r = .41). Three statistical need profiles were identified (1) a strong need for both generic and personalized statistics (34%), (2) a stronger need for personalized than for generic statistics (55%), and (3) a little need for both generic and personalized statistics (11%). Considerations for wanting personalized cancer statistics ranged from feelings of being in control to making better informed decisions about treatment. Considerations for not wanting statistics related to negative experience with statistics and to the unpredictability of future events for individual patients.

Conclusions

In light of the increased possibilities for using personalized statistics in clinical practice and decision aids, it appears that most cancer survivors want personalized statistical information during treatment decision-making. Subjective numeracy and information coping style seem important factors influencing this need. We encourage further development and implementation of data-driven personalized decision support technologies in oncological care to support patients in treatment decision making.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-02005-2.

Communication, perception, and use of personalized side-effect risks in prostate cancer treatment-decision making: An observational and interview study

OBJECTIVE

We investigated how healthcare professionals (HPs) communicate personalized risks of treatment side-effects to patients with localized prostate cancer during consultations, and explored how these patients perceive and use such risks during treatment decision-making.

METHODS

Patient consultations with nurse practitioners and urologists discussing personalized risks of urinary incontinence after prostatectomy were audiotaped, transcribed, and coded. Patients (n = 27) were then interviewed to explore their perceptions and use of personalized side-effect risks.

RESULTS

HPs explained personalized risks by discussing risk factors, which was appreciated and recalled by patients. Personalized risks were typically communicated both numerically and verbally (70%). When using numbers, HPs always used percentages, but rarely used natural frequencies (14%). Uncertainty was disclosed in only 34% of consultations. One-third of patients used personalized risks in their treatment decision-making by either switching to another treatment or sticking to their initial preference.

CONCLUSIONS

Patients value and use personalized side-effect risks during treatment decision-making. Clearly explaining the relationship between risk factors and personalized risk estimates may help patients understand and recall those. Practice implications HPs should not only give patients specific and precise numerical risk information, but should also put effort in explaining how the personalized side-effect risks are determined.

The Role of Attribute Screening and Choice Set Formation in Health Discrete Choice Experiments: Modeling the Impact of Benefit and Risk Attributes

OBJECTIVES

This study aimed to demonstrate the econometric modeling of benefit/risk-based choice set formation (CSF) within health-related discrete choice experiments.

METHODS

In 4 different case studies, first, a trade-off model was fitted; building on this, a screening model was fitted; and finally, a full CSF model was estimated. This final model allows for attributes to be used first to screen out alternatives from choice tasks before respondents' trade-off attributes and make a choice among feasible alternatives. Educational level and health literacy of respondents were accounted for in all models.

RESULTS

Model fit in terms of log likelihood, pseudo-R², Akaike information criterion, and Bayesian information criterion improved from using only trade-off or screening models compared with CSF models in 3 of the 4 case studies. In those studies, significant screening behavior was identified that (1) affected trade-off inferences, (2) rejects the pure trade-off model, and (3) supports the existence of screening on the basis of benefit-risk profiles, and other attributes. Educational level and health literacy showed significant interactions with multiple attributes in all case studies.

CONCLUSIONS

Choice modelers should pay close attention to noncompensatory respondent behavior when they include benefit or risk attributes in their discrete choice experiment. Further studies should investigate why and when respondents undertake screening behavior. Screening behavior in choice data analysis is always a possibility, so researchers should explore extensions of econometric models to reflect noncompensatory behavior. Assuming that benefit and risk attributes will only affect trade-off behavior is likely to lead to biased conclusions about benefit or risk-based behavior.

A process for creating data report-back tools to improve equity in environmental health

BACKGROUND

Although there is increasing interest in reporting results of environmental research efforts back to participants, evidence-based tools have not yet been applied to developed materials to ensure their accessibility in terms of literacy, numeracy, and data visualization demand. Additionally, there is not yet guidance as to how to formally assess the created materials to assure a match with the intended audience.

METHODS

Relying on formative qualitative research with participants of an indoor air quality study in Dorchester, Massachusetts, we identified means of enhancing accessibility of indoor air quality data report-back materials for participants. Participants (n = 20) engaged in semi-structured interviews in which they described challenges they encountered with scientific and medical materials and outlined written and verbal communication techniques that would help facilitate engagement with and accessibility of environmental health report-back materials. We coupled these insights from participants with best practice guidelines for written materials by operationalizing health literacy tools to produce accessible audience-informed data report-back materials.

RESULTS

The resulting data report-back materials had a 7th -grade reading level, and between a 4th -8th grade level of overall document complexity. The numeracy skills required to engage with the material were of the lowest demand, and we incorporated best practices for risk communication and facilitating understanding and actionability of the materials. Use of a rigorous assessment tool provides evidence of accessibility and appropriateness of the material for the audience.

CONCLUSIONS

We outline a process for developing and evaluating environmental health data reports that are tailored to inspire risk-reduction actions, and are demonstrably accessible in terms of their literacy, numeracy, and data visualization demand. Adapting health literacy tools to create and evaluate environmental data report-back materials is a novel and evidence-based means of ensuring their accessibility.

Exploring the Role of Provider–Patient Communication in Women’s Sexual Health and Pre-Exposure Prophylaxis Care in the Primary Care Settings in New York State of the United States

Background: Women shoulder a disproportionate burden of HIV infection in the United States and worldwide. Pre-exposure prophylaxis (PrEP) is an effective tool for HIV prevention, but its use is suboptimal. Primary care providers (PCP) are considered the ideal PrEP caregivers, but they generally underperform in PrEP care implementation. Methods: From 2020 to 2022, we employed semi-structured in-depth interviews to collect information about barriers and facilitators in PrEP care and beliefs and opinions regarding sexual wellness among 18 PCP and 29 PrEP-eligible women. We employed content analysis and thematic analysis to explore the transcribed narrative data. Results: The current study was guided by the “Communication Pathways” Framework. We studied how communication functions affect PrEP care and women’s sexual wellness on the pathways. We identified several specific pathways between communication and PrEP care implementation in primary care settings, including patient knowledge, linkage to care, therapeutic alliance, and decision making on PrEP care. A paradox regarding who should initiate the discussion regarding sexual history and PrEP care was identified. Conclusions: Findings suggested that a navigation and assistance system for PrEP care in patients and providers is urgently needed. Future studies should facilitate PrEP discussion, engagement, and monitoring in primary care settings.

A Mobile App for Prevention of Cardiovascular Disease and Type 2 Diabetes Mellitus: Development and Usability Study

BACKGROUND

Cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) are posing a huge burden on health care systems worldwide. Mobile apps can deliver behavior change interventions for chronic disease prevention on a large scale, but current evidence for their effectiveness is limited.

OBJECTIVE

This paper reported on the development and user testing of a mobile app that aims at increasing risk awareness and engaging users in behavior change. It would form part of an intervention for primary prevention of CVD and T2DM.

METHODS

The theoretical framework of the app design was based on the Behaviour Change Wheel, combined with the capability, opportunity, and motivation for behavior change system and the behavior change techniques from the Behavior Change Technique Taxonomy (version 1). In addition, evidence from scientific literature has guided the development process. The prototype was tested for user-friendliness via an iterative approach. We conducted semistructured interviews with individuals in the target populations, which included the System Usability Scale. We transcribed and analyzed the interviews using descriptive statistics for the System Usability Scale and thematic analysis to identify app features that improved utility and usability.

RESULTS

The target population was Australians aged ≥45 years. The app included 4 core modules (risk score, goal setting, health measures, and education). In these modules, users learned about their risk for CVD and T2DM; set goals for smoking, alcohol consumption, diet, and physical activity; and tracked them. In total, we included 12 behavior change techniques. We conducted 2 rounds of usability testing, each involving 5 participants. The average age of the participants was 58 (SD 8) years. Totally, 60% (6/10) of the participants owned iPhone Operating System phones, and 40% (4/10) of them owned Android phones. In the first round, we identified a technical issue that prevented 30% (3/10) of the participants from completing the registration process. Among the 70% (7/10) of participants who were able to complete the registration process, 71% (5/7) rated the app above average, based on the System Usability Scale. During the interviews, we identified some issues related to functionality, content, and language and clarity. We used the participants' feedback to improve these aspects.

CONCLUSIONS

We developed the app using behavior change theory and scientific evidence. The user testing allowed us to identify and remove technical errors and integrate additional functions into the app, which the participants had requested. Next, we will evaluate the feasibility of the revised version of the app developed through this design process and usability testing.

Comparison of the accuracy of residents, senior physicians and surrogate decision-makers for predicting hospital mortality of critically ill patients

OBJECTIVE

To compare the predictive performance of residents, senior intensive care unit physicians and surrogates early during intensive care unit stays and to evaluate whether different presentations of prognostic data (probability of survival versus probability of death) influenced their performance.

METHODS

We questioned surrogates and physicians in charge of critically ill patients during the first 48 hours of intensive care unit admission on the patient's probability of hospital outcome. The question framing (i.e., probability of survival versus probability of death during hospitalization) was randomized. To evaluate the predictive performance, we compared the areas under the ROC curves (AUCs) for hospital outcome between surrogates and physicians' categories. We also stratified the results according to randomized question framing.

RESULTS

We interviewed surrogates and physicians on the hospital outcomes of 118 patients. The predictive performance of surrogate decisionmakers was significantly lower than that of physicians (AUC of 0.63 for surrogates, 0.82 for residents, 0.80 for intensive care unit fellows and 0.81 for intensive care unit senior physicians). There was no increase in predictive performance related to physicians' experience (i.e., senior physicians did not predict outcomes better than junior physicians). Surrogate decisionmakers worsened their prediction performance when they were asked about probability of death instead of probability of survival, but there was no difference for physicians.

CONCLUSION

Different predictive performance was observed when comparing surrogate decision-makers and physicians, with no effect of experience on health care professionals' prediction. Question framing affected the predictive performance of surrogates but not of physicians.

Policies to influence perceptions about COVID-19 risk: The case of maps

Choropleth disease maps are often used to inform the public about the risks posed by coronavirus disease 2019 (COVID-19). In a survey conducted in the U.S. state of Georgia in June 2020, we randomly assigned respondents to view either of two maps. The first map reported county-level COVID case counts; the second displayed case rates per 100,000 people. Respondents who saw case rate maps were less likely to perceive COVID as mostly an urban problem and reported higher levels of concerns about the virus. Case rate maps also increased support for policies aimed at mitigating the spread of the virus, although, for this outcome, the effect was quantitatively small and the maps did not change individuals' self-reported behavior. For several outcomes, the impact of the case rate map was strongest for rural residents and self-identified Republicans, both of whom were less worried about the virus and more skeptical about public health measures to mitigate its spread.

A Visualization Analysis of Crisis and Risk Communication Research Using CiteSpace

This study aims to understand the research status and development trend of crisis and risk communication research (CRCR) through a visual analysis in CiteSpace, thereby providing a more comprehensive perspective for future research agenda. First, we retrieved published papers from Web of Science (1986–2020) and Scopus (1979–2020) with a title search. Subsequently, we analyzed the main research strengths and main topics of CRCR from two dimensions: co-authorship network and co-citation network. We conducted an in-depth co-citation network analysis from four perspectives: cluster analysis, high co-cited literature analysis, burst analysis, and turning points analysis. These results revealed the main research topics in the CRCR field, the most eye-catching research literature, the emerging research hotspots in each period, and the turning points of the overall development. Finally, we suggested further research directions for future avenues.

What CVD risk factors predict self-perceived risk of having a myocardial infarction? A cross-sectional study

Background

This study aims to identify predictors of self-perceived risk of myocardial infarction (MI).

Methods

Among 564 men and women (50–65 years; randomly selected from the Swedish population), we assessed risk perception as relative self-perceived risk compared to others (lower, same, higher) and percentage ten-year absolute risk. Predictors (added blockwise) were identified using multinomial or linear regression, providing odds ratios (ORs) or β coefficients with their 95% confidence intervals (CI).

Results

The mean of self-perceived 10-year MI risk was 12%. Lower BMI (AOR 0.57, 95% CI: 0.44–0.75), low stress (AOR 2.51, 95% CI: 1.39–4.52), high level of physical activity (AOR 1.66, 95% CI:1.01–2.74), hypertension (AOR 0.42, 95% CI: 0.23–0.76), family history (AOR 0.38, 95% CI: 0.21–0.69), and poor general health (AOR 0.41, 95% CI: 0.19–0.89) predicted if respondents perceived their MI risk as lower. Poor general health (AOR 1.94, 95% CI: 1.01–3.73), family history (AOR 2.72, 95% CI: 1.57–4.72), and high cholesterol (AOR 2.45, 95% CI: 1.18–5.09) predicted if respondents perceived their MI risk as higher. Low level of self-perceived CVD knowledge and low numeracy predicted if respondents perceived their MI risk as the same as others. High cholesterol (B 6.85, 95% CI: 2.47–11.32) and poor general health (B 8.75, 95% CI: 4.58–13.00) predicted a higher percentage of perceived ten-year risk.

Conclusion

General health was a common predictor of self-perceived MI risk. Lifestyle factors (BMI, physical activity) and stress dominated the predictors for perceiving MI risk as lower than others, while high cholesterol predicted perception of high risk.

Identifying and managing psoriasis-associated comorbidities: the IMPACT research programme

Background

Psoriasis is a common, lifelong inflammatory skin disease, the severity of which can range from limited disease involving a small body surface area to extensive skin involvement. It is associated with high levels of physical and psychosocial disability and a range of comorbidities, including cardiovascular disease, and it is currently incurable.

Objectives

To (1) confirm which patients with psoriasis are at highest risk of developing additional long-term conditions and identify service use and costs to patient, (2) apply knowledge about risk of comorbid disease to the development of targeted screening services to reduce risk of further disease, (3) learn how patients with psoriasis cope with their condition and about their views of service provision, (4) identify the barriers to provision of best care for patients with psoriasis and (5) develop patient self-management resources and staff training packages to improve the lives of people with psoriasis.

Design

Mixed methods including two systematic reviews, one population cohort study, one primary care screening study, one discrete choice study, four qualitative studies and three mixed-methodology studies.

Setting

Primary care, secondary care and online surveys.

Participants

People with psoriasis and health-care professionals who manage patients with psoriasis.

Results

Prevalence rates for psoriasis vary by geographical location. Incidence in the UK was estimated to be between 1.30% and 2.60%. Knowledge about the cost-effectiveness of therapies is limited because high-quality clinical comparisons of interventions have not been done or involve short-term follow-up. After adjusting for known cardiovascular risk factors, psoriasis (including severe forms) was not found to be an independent risk factor for major cardiovascular events; however, co-occurrence of inflammatory arthritis was a risk factor. Traditional risk factors were high in patients with psoriasis. Large numbers of patients with suboptimal management of known risk factors were found by screening patients in primary care. Risk information was seldom discussed with patients as part of screening consultations, meaning that a traditional screening approach may not be effective in reducing comorbidities associated with psoriasis. Gaps in training of health-care practitioners to manage psoriasis effectively were identified, including knowledge about risk factors for comorbidities and methods of facilitating behavioural change. Theory-based, high-design-quality patient materials broadened patient understanding of psoriasis and self-management. A 1-day training course based on motivational interviewing principles was effective in increasing practitioner knowledge and changing consultation styles. The primary economic analysis indicated a high level of uncertainty. Sensitivity analysis indicated some situations when the interventions may be cost-effective. The interventions need to be assessed for long-term (cost-)effectiveness.

Limitations

The duration of patient follow-up in the study of cardiovascular disease was relatively short; as a result, future studies with longer follow-up are recommended.

Conclusions

Recognition of the nature of the psoriasis and its impact, knowledge of best practice and guideline use are all limited in those most likely to provide care for the majority of patients. Patients and practitioners are likely to benefit from the provision of appropriate support and/or training that broadens understanding of psoriasis as a complex condition and incorporates support for appropriate health behaviour change. Both interventions were feasible and acceptable to patients and practitioners. Cost-effectiveness remains to be explored.

Future work

Patient support materials have been created for patients and NHS providers. A 1-day training programme with training materials for dermatologists, specialist nurses and primary care practitioners has been designed. Spin-off research projects include a national study of responses to psoriasis therapy and a global study of the prevalence and incidence of psoriasis. A new clinical service is being developed locally based on the key findings of the Identification and Management of Psoriasis Associated ComorbidiTy (IMPACT) programme.

Funding

This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 10, No. 3. See the NIHR Journals Library website for further project information.

Effects of icon arrays to communicate risk in a repeated risky decision-making task

In two experiments, participants decided on each of several trials whether or not to take a risk. If they chose to take the risk, they had a relatively high probability (from 75% to 95%) of winning a small number of points and a relatively low probability (5% to 25%) of losing a large number of points. The loss amounts varied so that the expected value of taking the risk was positive on some trials, zero on others, and negative on the rest. The main independent variable was whether the probability of losing was communicated using numerical percentages or icon arrays. Both experiments included random icon arrays, in which the icons representing losses were randomly distributed throughout the array. Experiment 2 also included grouped icon arrays, in which the icons representing losses were grouped at the bottom of the array. Neither type of icon array led to better performance in the task. However, the random icon arrays led to less risk taking than the numerical percentages or the grouped icon arrays, especially at the higher loss probabilities. In a third experiment, participants made direct judgments of the percentages and probabilities represented by the icon arrays from Experiment 2. The results supported the idea that random arrays lead to less risk taking because they are perceived to represent greater loss probabilities. These results have several implications for the study of icon arrays and their use in risk communication.

The risk matrix approach: a helpful tool weighing probability and impact when deciding on preventive and diagnostic interventions

Background

Clinical guidelines are developed to lower risks, mostly viewed upon as probability. However, in daily practice, risk is perceived as the combination of probability and the impact of desired and adverse events. This combination of probability and impact can be visualized in a risk matrix. We evaluated the effect of interventions and diagnostic thresholds on modeled risk, by using the risk matrix approach (RMA) in a clinical guideline development process, and investigated which additional factors affected choices.

Methods

To improve care outcomes, we developed new guidelines in which care professionals had to decide upon novel interventions and diagnostic thresholds. A risk matrix showed the probability and impact of an intervention, together with the corresponding risk category. First, professionals’ opinion on required performance characteristics on risk were evaluated by a qualitative online survey. Second, qualitative assessment of possible additional factors affecting final decisions, that followed from group discussion and guideline development were evaluated.

Results

Upfront, professionals opinioned that non-invasive interventions should decrease the general population risk, whereas invasive interventions should decrease the risk in high-risk groups. Nonetheless, when making guidelines, interventions were introduced without reaching the predefined threshold of desired risk reduction. Professionals weighed other aspects besides risk reduction, as financial aspects and practical consequences for daily practice in this guideline-making process.

Conclusion

Professionals are willing to change policies at much lower level of anticipated effectiveness than defined upfront. Although objectively presented data structured group discussions, decisions in guideline development are affected by several other factors than risk reduction alone.

Impact of COVID-19 forecast visualizations on pandemic risk perceptions

People worldwide use SARS-CoV-2 (COVID-19) visualizations to make life and death decisions about pandemic risks. Understanding how these visualizations influence risk perceptions to improve pandemic communication is crucial. To examine how COVID-19 visualizations influence risk perception, we conducted two experiments online in October and December of 2020 (N = 2549) where we presented participants with 34 visualization techniques (available at the time of publication on the CDC’s website) of the same COVID-19 mortality data. We found that visualizing data using a cumulative scale consistently led to participants believing that they and others were at more risk than before viewing the visualizations. In contrast, visualizing the same data with a weekly incident scale led to variable changes in risk perceptions. Further, uncertainty forecast visualizations also affected risk perceptions, with visualizations showing six or more models increasing risk estimates more than the others tested. Differences between COVID-19 visualizations of the same data produce different risk perceptions, fundamentally changing viewers’ interpretation of information.

Sudden cardiac death in cardiomyopathies: acting upon "acceptable" risk in the personalized medicine era

Patients with cardiomyopathies are confronted with the risk of sudden cardiac death (SCD) throughout their lifetime. Despite the fact that SCD is relatively rare, prognostic stratification is an integral part of physician-patient discussion, with the goal of risk modification and prevention. The current approach is based on a concept of "acceptable risk." However, there are intrinsic problems with an algorithm-based approach to risk management, magnified by the absence of robust evidence underlying clinical decision support tools, which can make high- versus low-risk classifications arbitrary. Strategies aimed at risk reduction range from selecting patients for an implantable cardioverter defibrillator (ICD) to disqualification from competitive sports. These clinical options, especially when implying the use of finite financial resources, are often delivered from the physician's perspective citing decision-making algorithms. When the burden of intervention-related risks or financial costs is deemed higher than an "acceptable risk" of SCD, the patient's perspective may not be appropriately considered. Designating a numeric threshold of "acceptable risk" has ethical implications. One could reasonably ask "acceptable to whom?" In an era when individual choice and autonomy are pillars of the physician-patient relationship, the subjective aspects of perceived risk should be acknowledged and be part of shared decision-making. This is particularly true when the lack of a strong scientific evidence base makes a dichotomous algorithm-driven approach suboptimal for unmitigated translation to clinical practice.

Public Health Messaging during the COVID-19 Pandemic and Beyond: Lessons from Communication Science

The COVID-19 pandemic has made it clear that effective public health messaging is an indispensable component of a robust pandemic response system. In this article, we review decades of research from the interdisciplinary field of communication science and provide evidence-based recommendations for COVID-19 public health messaging. We take a principled approach by systematically examining the communication process, focusing on decisions about what to say in a message (i.e., message content) and how to say it (i.e., message executions), and how these decisions impact message persuasiveness. Following a synthesis of each major line of literature, we discuss how science-based principles of message design can be used in COVID-19 public health messaging. Additionally, we identify emerging challenges for public health messaging during the COVID-19 pandemic and discuss possible remedies. We conclude that communication science offers promising public health messaging strategies for combatting COVID-19 and future pandemics.