Polyurethane Implants in Revision Breast Augmentation: A Prospective 5-Year Study.

BACKGROUND: Revision surgery for aesthetic breast augmentation remains a challenging procedure. Polyurethane (PU) implants have been found to avoid capsular contracture recurrence as well as prevent implant displacement by bio-integrating into the pocket. OBJECTIVES: Our study aims to assess the use of PU in breast revision surgery and provides an algorithm. METHODS: Over a 5-year period, a prospective study was conducted involving consecutive patients undergoing implant revision. Patient demographics, previous breast procedures, and specific surgical details were documented. Post-operative outcomes were followed up. RESULTS: Out of 92 patients (184 breasts), 78 (156 breasts) were included in the analysis. The average age was 47.4, with a BMI of 22.3, and a mean follow-up of 5 years. A majority (63%) represented secondary revision cases, while 37% were tertiary cases. Implant size averaged 296 cc, with 53% placed retropectoral and 47% prepectoral. Significantly more implants in secondary cases were changed from pre- to retropectoral (p = 0.005), and in tertiary changed from retro- to prepectoral (p = 0.002). Complete capsulectomy was performed in 61.5% and partial in 25.6%. Additional lipofilling was performed in 32%, and concurrent mastopexy in 40%. Revision surgery in our series had a 1.9% acute complication rate, 4.5% longer term re-operation rate for corrections, 0.6% implant exchange rate, and no recurrent capsular contracture. CONCLUSIONS: This is the first study to provide data on outcomes of revision breast augmentation surgery with the use of PU implants. It shows that polyurethane implants offer consistent stability and have low rates of recurrent capsular contracture in revision surgery.

Evidence-Based Communication to Increase Melanoma Knowledge and Skin Checks.

Rates of melanoma-the deadliest form of skin cancer-have increased. Early detection can save lives, and patients have a critical role to play in checking their skin. We aim to identify health communication messages that best educate the public and increase intentions toward skin checks. After viewing messages intended to increase melanoma knowledge, participants correctly identified a greater proportion (74.6 vs 70.4%) of moles (mean number = 17.9, 95% confidence interval [CI] = 17.5-18.3 vs 16.9, 95% CI = 16.6-17.3; P < .001, partial eta-squared = 0.03) and had knowledge of more melanoma warning signs (mean number = 5.8, 95% CI = 5.7-5.8 vs 5.6, 95% CI = 5.5-5.7, P = .01, partial eta-squared = 0.02). After viewing messages intended to increase self-confidence in checking their skin accurately, they were also more likely to report greater intentions to do a skin check on a scale of 1-5 (mean number = 3.8, 95% CI = 3.7-3.9 vs 3.6, 95% CI = 3.4-3.7, P = .005, partial eta-squared = 0.02). Online melanoma messages aimed at increasing both melanoma knowledge and skin-check confidence may be most effective in improving the accuracy of skin self-examinations and intentions to do them.

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."

A synthesis of evidence for policy from behavioural science during COVID-19.

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations ('claims') detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms 'physical distancing' and 'social distancing'. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

Using an Elastomeric Skin Protectant to Manage Donor Site Wounds of Split-thickness Skin Grafts: A Case Series.

ABSTRACT: Split-thickness skin grafting (STSG) is a common surgical procedure to manage acute and chronic wounds. A plethora of dressings exists to treat STSG donor site wounds (DSWs). Recently, a new elastomeric skin protectant was adopted (Cavilon Advanced Skin Protectant; 3M) in the treatment of incontinence-associated dermatitis. In this report, the authors assess the effects of this elastomeric skin protectant as an alternative wound dressing for STSG donor sites.The authors report a single-center prospective case series that was performed to establish a treatment protocol. Nine consecutive patients with different indications for treatment with an STSG from May to September 2018 were included. Collected data included general patient information, comorbidities, complications, blood loss, pain during dressing change, and the duration of DSW healing.This case series showed promising results in terms of duration of DSW healing when applying the elastomeric skin protectant. The authors also observed less blood loss and less pain during dressing changes. No infections were seen during the trial.

Motivations to learn genomic information are not exceptional: Lessons from behavioral science.

Whether to undergo genome sequencing in a clinical or research context is generally a voluntary choice. Individuals are often motivated to learn genomic information even when clinical utility-the possibility that the test could inform medical recommendations or health outcomes-is low or absent. Motivations to seek one's genomic information can be cognitive, affective, social, or mixed (e.g., cognitive and affective) in nature. These motivations are based on the perceived value of the information, specifically, its clinical utility and personal utility. We suggest that motivations to learn genomic information are no different from motivations to learn other types of personal information, including one's health status and disease risk. Here, we review behavioral science relevant to motivations that may drive engagement with genome sequencing, both in the presence of varying degrees of clinical utility and in the absence of clinical utility. Specifically, we elucidate 10 motivations that are expected to underlie decisions to undergo genome sequencing. Recognizing these motivations to learn genomic information will guide future research and ultimately help clinicians to facilitate informed decision making among individuals as genome sequencing becomes increasingly available.

Efficacy, safety and tolerability of Biktarvy in HIV-1 infection: A scoping review.

Background: Biktarvy is approved for use in HIV-1 infection in both treatment-naïve and treatment-experienced individuals, after a series of successful phase III trials. However, studies on real-world evidence on its efficacy, safety and tolerability are limited. Purpose: The study aims to collate real-world evidence on the use of Biktarvy in clinical practice to identify gaps in knowledge. Research Design: Scoping review was undertaken using PRISMA guidelines and a systematic search strategy. The final search strategy used was (Bictegravir* OR biktarvy) AND (efficac* OR safe* OR effect* OR tolerab* OR 'side effect*' OR 'adverse effect*'). The last search was performed on the 12th of August 2021. Study Sample: Studies were eligible if they reported on the efficacy, effectiveness, safety or tolerability of bictegravir-based ART. Data Collection and/or Analysis: Data were collected from 17 studies that met the inclusion and exclusion criteria and summarised using a narrative synthesis. Results: The efficacy of Biktarvy in clinical practice is comparable to phase III trials. However, adverse effects and discontinuation rates were found to be higher in real-world studies. Conclusions: The cohorts in the included real-world studies showed more demographic diversity when compared to the drug approval trials, further prospective studies are required on under-represented groups such as women, pregnant people, ethnic minorities and older adults.

Operating on Anxiety: Negative Affect toward Breast Cancer and Choosing Contralateral Prophylactic Mastectomy.

BACKGROUND: Rates of contralateral prophylactic mastectomy (CPM)-removal of the healthy breast following breast cancer diagnosis-have increased, particularly among women for whom CPM provides no survival benefit. Affective (i.e., emotional) decision making is often blamed for this increase. We studied whether greater negative breast cancer affect could motivate uptake of CPM through increased cancer risk perceptions and biased treatment evaluations. METHODS: We randomly assigned healthy women with average breast-cancer risk (N = 1030; Mage = 44.14, SD = 9.23 y) to 1 of 3 affect conditions (negative v. neutral v. positive narrative manipulation) in a hypothetical online experiment in which they were asked to imagine being diagnosed with cancer in one breast. We assessed 1) treatment choice, 2) affect toward CPM, and 3) perceived risk of future breast cancer in each breast (cancer affected and healthy) following lumpectomy, single mastectomy, and CPM. RESULTS: The manipulation caused women in the negative and neutral narrative conditions (26.9% and 26.4%, respectively) to choose CPM more compared with the positive narrative condition (19.1%). Across conditions, women's CPM affect did not differ. However, exploratory analyses addressing a possible association of affect toward cancer-related targets suggested that women in the negative narrative condition may have felt more positively toward CPM than women in the positive narrative condition. The manipulation did not have significant effects on breast cancer risk perceptions. LIMITATIONS: The manipulation of affect had a small effect size, possibly due to the hypothetical nature of this study and/or strong a priori knowledge and attitudes about breast cancer and its treatment options. CONCLUSION: Increased negative affect toward breast cancer increased choice of CPM over other surgical options and might have motivated more positive affective evaluations of CPM. HIGHLIGHTS: This study used narratives to elicit different levels of negative integral affect toward breast cancer to investigate the effects of affect on breast cancer treatment choices.Increased negative affect toward breast cancer increased the choice of double mastectomy over lumpectomy and single mastectomy to treat a hypothetical, early-stage cancer.The narrative manipulation of negative affect toward breast cancer did not change the perceived risks of future cancer following any of the surgical interventions.Negative affect toward breast cancer may have biased affective evaluations of double mastectomy.

Large numbers cause magnitude neglect: The case of government expenditures.

Four studies demonstrate that the public's understanding of government budgetary expenditures is hampered by difficulty in representing large numerical magnitudes. Despite orders of magnitude difference between millions and billions, study participants struggle with the budgetary magnitudes of government programs. When numerical values are rescaled as smaller magnitudes (in the thousands or lower), lay understanding improves, as indicated by greater sensitivity to numerical ratios and more accurate rank ordering of expenses. A robust benefit of numerical rescaling is demonstrated across a variety of experimental designs, including policy relevant choices and incentive-compatible accuracy measures. This improved sensitivity ultimately impacts funding choices and public perception of respective budgets, indicating the importance of numerical cognition for good citizenship.

Excluding numeric side-effect information produces lower vaccine intentions.

Encouraging vaccine uptake is important to reducing the impact of infectious disease. However, negative attitudes and vaccine hesitancy, due in part to worry about side effects, are obstacles to achieving high vaccination rates. Provided vaccine information sheets typically include a list of side effects without numeric information about their likelihoods, but providing such numbers may yield benefits. We investigated the effect of providing numeric information about side-effect likelihood (e.g., "1%") and verbal labels (e.g., "uncommon") on intentions to get a hypothetical vaccine, reasons for the vaccination decision, and risk overestimation. In a diverse, online, convenience sample (N = 595), providing numeric information increased vaccine intentions-70% of those who received numeric information were predicted to be moderately or extremely likely to vaccinate compared to only 54% of those who did not receive numeric information (p<.001), controlling for age, gender, race, education, and political ideology. Participants receiving numeric information also were less likely to overestimate side-effect likelihood. Verbal labels had additional benefits when included with numeric information, particularly among the vaccine hesitant. For these participants, verbal labels increased vaccine intentions when included with numeric information (but not in its absence). Among the vaccine-hesitant, 43% of those provided numeric information and verbal labels were predicted to be moderately or extremely likely to get vaccinated vs. only 24% of those given a list of side effects (p<.001). We conclude that the standard practice of not providing numeric information about side-effect likelihood leads to a less-informed public who is less likely to vaccinate.

Evidence-based recommendations for communicating the impacts of climate change on health.

Climate change poses a multifaceted, complex, and existential threat to human health and well-being, but efforts to communicate these threats to the public lag behind what we know how to do in communication research. Effective communication about climate change's health risks can improve a wide variety of individual and population health-related outcomes by: (1) helping people better make the connection between climate change and health risks and (2) empowering them to act on that newfound knowledge and understanding. The aim of this manuscript is to highlight communication methods that have received empirical support for improving knowledge uptake and/or driving higher-quality decision making and healthier behaviors and to recommend how to apply them at the intersection of climate change and health. This expert consensus about effective communication methods can be used by healthcare professionals, decision makers, governments, the general public, and other stakeholders including sectors outside of health. In particular, we argue for the use of 11 theory-based, evidence-supported communication strategies and practices. These methods range from leveraging social networks to making careful choices about the use of language, narratives, emotions, visual images, and statistics. Message testing with appropriate groups is also key. When implemented properly, these approaches are likely to improve the outcomes of climate change and health communication efforts.

Climate change poses a tremendous and complex threat to human health and well-being. Efforts to communicate these threats to the public may not be as effective as desired and using evidence-based strategies could improve a wide variety of health-related outcomes for individuals and society while potentially reducing climate-related health disparities. In particular, effective communication can help people understand the crucial connection between climate change and health risks and empower them to act on that newfound knowledge and understanding. We recommend 11 communication methods that have been well tested in other domains and can be applied to the intersection of climate and health by healthcare professionals, decisionmakers, governments, the general public, and other stakeholders including those in sectors outside of health. These methods range from leveraging social networks to making careful choices about the use of language, narratives, emotions, visual images, and statistics. Message testing with appropriate groups is also key. When implemented properly, these approaches are likely to improve knowledge uptake and drive better decision making and healthier behaviors.

How are patient-related characteristics associated with shared decision-making about treatment? A scoping review of quantitative studies.

OBJECTIVES: To identify what patient-related characteristics have been reported to be associated with the occurrence of shared decision-making (SDM) about treatment. DESIGN: Scoping review. ELIGIBILITY CRITERIA: Peer-reviewed articles in English or Dutch reporting on associations between patient-related characteristics and the occurrence of SDM for actual treatment decisions. INFORMATION SOURCES: COCHRANE Library, Embase, MEDLINE, PsycInfo, PubMed and Web of Science were systematically searched for articles published until 25 March 2019. RESULTS: The search yielded 5289 hits of which 53 were retained. Multiple categories of patient characteristics were identified: (1) sociodemographic characteristics (eg, gender), (2) general health and clinical characteristics (eg, symptom severity), (3) psychological characteristics and coping with illness (eg, self-efficacy) and (4) SDM style or preference. Many characteristics showed no association or unclear relationships with SDM occurrence. For example, for female gender positive, negative and, most frequently, non-significant associations were seen. CONCLUSIONS: A large variety of patient-related characteristics have been studied, but for many the association with SDM occurrence remains unclear. The results will caution often-made assumptions about associations and provide an important step to target effective interventions to foster SDM with all patients.

Numeracy and the Motivational Mind: The Power of Numeric Self-efficacy.

BACKGROUND: Objective numeracy appears to support better medical decisions and health outcomes. The more numerate generally understand and use numbers more and make better medical decisions, including more informed medical choices. Numeric self-efficacy-an aspect of subjective numeracy that is also known as numeric confidence-also relates to decision making via emotional reactions to and inferences from experienced difficulty with numbers and via persistence linked with numeric comprehension and healthier behaviors over time. Furthermore, it moderates the effects of objective numeracy on medical outcomes. PURPOSE: We briefly review the numeracy and decision-making literature and then summarize more recent literature on 3 separable effects of numeric self-efficacy. Although dual-process theories can account for the generally superior decision making of the highly numerate, they have neglected effects of numeric self-efficacy. We discuss implications for medical decision-making (MDM) research and practice. Finally, we propose a modification to dual-process theories, adding a "motivational mind" to integrate the effects of numeric self-efficacy on decision-making processes (i.e., inferences from experienced difficulty with numbers, greater persistence, and greater use of objective-numeracy skills) important to high-quality MDM. CONCLUSIONS: The power of numeric self-efficacy (confidence) has been little considered in MDM, but many medical decisions and behaviors require persistence to be successful over time (e.g., comprehension, medical-recommendation adherence). Including numeric self-efficacy in research and theorizing will increase understanding of MDM and promote development of better decision interventions. HIGHLIGHTS: Research demonstrates that objective numeracy supports better medical decisions and health outcomes.The power of numeric self-efficacy (aka numeric confidence) has been little considered but appears critical to emotional reactions and inferences that patients and others make when encountering numeric information (e.g., in decision aids) and to greater persistence in medical decision-making tasks involving numbers.The present article proposes a novel modification to dual-process theory to account for newer findings and to describe how numeracy mechanisms can be better understood.Because being able to adapt interventions to improve medical decisions depends in part on having a good theory, future research should incorporate numeric self-efficacy into medical decision-making theories and interventions.

Age declines in numeracy: An analysis of longitudinal data.

Numeracy, the ability to understand and use basic probability and numerical concepts, is associated with diverse positive outcomes across the lifespan. Prior cross-sectional research on numeracy has generally found a negative association with age, but positive correlations with male gender, education attainment, and measures of fluid and crystallized intelligence have been more robust. Age effects on cognitive functioning are well established, but little is known about longitudinal trends of numeracy into older age. The present study investigates longitudinal age effects on numeracy using a sample of 524 adults (2008 Agerange = 20-78) from the RAND American Life Panel. Participants completed a numeracy measure in both 2008 and 2019, a span of 11 years. Using a linear mixed-effect model to predict numeracy scores, a significant interaction between the year of testing and the quadric age term shows a decline in numeracy scores beginning in later middle age, a trend that falls in between those previously found for crystallized and fluid cognitive abilities. Numeracy declines are somewhat mitigated for males and those with higher education, but the interaction of the two variables did not return a clear pattern of results. Prior research has shown that numeracy is positively related to the quality of health and financial decisions and, ultimately, more positive health and economic outcomes. The implications of age declines in numeracy are discussed in relation to health and financial decision-making, tasks that remain relevant into old age. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Predicting Future Utilization Using Self-Reported Health and Health Conditions in a Longitudinal Cohort Study: Implications for Health Insurance Decision Support.

Decision support techniques and online algorithms aim to help individuals predict costs and facilitate their choice of health insurance coverage. Self-reported health status (SHS), whereby patients rate their own health, could improve cost-prediction estimates without requiring individuals to share personal health information or know about undiagnosed conditions. We compared the predictive accuracy of several models: (1) SHS only, (2) a "basic" model adding health-related variables, and (3) a "full" model adding measures of healthcare access. The Medical Expenditure Panel Survey was used to predict 2015 health expenditures from 2014 data. Relative performance was assessed by comparing adjusted-R2 values and by reporting the predictive accuracy of the models for a new cohort (2015-2016 data). In the SHS-only model, those with better SHS were less likely to incur expenditures. However, after accounting for health variables, those with better SHS were more likely to incur expenses. In the full model, SHS was no longer predictive of incurring expenses. Variables indicating better access to care were associated with higher likelihood of spending and higher spending. The full model (R2 = 0.290) performed slightly better than the basic model (R2 = 0.240), but neither performed well at the upper tail of the cost distribution. While our SHS-based models perform well in the aggregate, predicting population-level risk well, they are not sufficiently accurate to guide individuals' insurance shopping decisions in all cases. Policies that rely heavily on health insurance consumers making individually optimal choices cannot assume that decision tools can accurately anticipate high costs.

Money matters (especially if you are good at math): Numeracy, verbal intelligence, education, and income in satisfaction judgments.

Objective numeracy, the ability to understand and use mathematical concepts, has been related to superior decisions and life outcomes. Unknown is whether it relates to greater satisfaction in life. We investigated numeracy's relations with income satisfaction and overall life satisfaction in a diverse sample of 5,525 American adults. First, more numerate individuals had higher incomes; for every one point higher on the eight-item numeracy test, individuals reported $4,062 more in annual income, controlling for education and verbal intelligence. Combined, numeracy, education, and verbal intelligence explained 25% of the variance in income while Big-5 personality traits explained less than 4%. Further, the higher incomes associated with greater numeracy were related to more positive life evaluations (income and life satisfaction). Second, extant research also has indicated that the highly numerate compare numbers more than the less numerate. Consistent with numeracy-related income comparisons, numeracy moderated the relation between income and life evaluations, meaning that the same income was valued differently by those better and worse at math. Specifically, among those with lower incomes, the highly numerate were less satisfied than the less numerate; this effect reversed among those with higher incomes as if the highly numerate were aware of and made comparisons to others' incomes. Further, no clear income satiation point was seen among those highest in numeracy, and satiation among the least numerate appeared to occur at a point below $50,000. Third, both education and verbal intelligence related to income evaluations in similar ways, and numeracy's relations held when controlling for these other relations. Although causal claims cannot be made from cross-sectional data, these novel results indicate that numeracy may be an important factor underlying life evaluations and especially for evaluations concerning numbers such as incomes. Finally, this study adds to our understanding of education and intelligence effects in life satisfaction and happiness.

Ability-related political polarization in the COVID-19 pandemic.

In two large-scale longitudinal datasets (combined N = 5761), we investigated ability-related political polarization in responses to the COVID-19 pandemic. We observed more polarization with greater ability in emotional responses, risk perceptions, and product-purchase intentions across five waves of data collection with a diverse, convenience sample from February 2020 through July 2020 (Study 1, N = 1267). Specifically, more liberal participants had more negative emotional responses and greater risk perceptions of COVID-19 than conservative participants. Compared to conservatives, liberal participants also interpreted quantitative information as indicating higher COVID-19 risk and sought COVID-related news more from liberal than conservative news media. Of key importance, we also compared verbal and numeric cognitive abilities for their independent capacity to predict greater polarization. Although measures of numeric ability, such as objective numeracy, are often used to index ability-related polarization, ideological differences were more pronounced among those higher in verbal ability specifically. Similar results emerged in secondary analysis of risk perceptions in a nationally representative longitudinal dataset (Study 2, N = 4494; emotions and purchase intentions were not included in this dataset). We further confirmed verbal-ability-related polarization findings on non-COVID policy attitudes (i.e., weapons bans and Medicare-for-all) measured cross-sectionally. The present Study 2 documented ability-related polarization emerging over time for the first time (rather than simply measuring polarization in existing beliefs). Both studies demonstrated verbal ability measures as the most robust predictors of ability-related polarization. Together, these results suggest that polarization may be a function of the amount and/or application of verbal knowledge rather than selective application of quantitative reasoning skills.

Support for legislative, technological, and organizational strategies to reduce cellphone use while driving: Psychological predictors and influences of language.

OBJECTIVE: A large body of research has established that cellphone use while driving (CUWD) is common and dangerous. However, little research has been conducted about how people react psychologically to various distraction-reduction strategies and, ultimately, support or do not support them. Understanding support for reduction is important for predicting use of technological solutions and compliance with laws and for improving communication and education about the risks of CUWD. METHODS: We measured support for a variety of legislative, technological, and organizational strategies to reduce CUWD in an online sample of American drivers (N = 648). We also developed evidence-based communication techniques, describing strategies in terms of benefits vs. costs or using freedom-invoking vs. freedom-reducing language to assess what would influence support. RESULTS: Support for CUWD reduction was generally high. It was predicted by driver characteristics and beliefs. For example, drivers who supported reducing CUWD more also had lower CUWD reactance, greater anti-CUWD beliefs, higher personal risk perceptions of CUWD, and greater self-reported distracted driving. Age and perceived ability to drive distracted did not predict overall support. However, two strategies that allow for handsfree phone use were supported more by people who engaged in more CUWD, perceived they had greater ability to CUWD, perceived more benefits to CUWD, had more positive affect to cellphones, and were younger. Communication techniques also influenced support. Specifically, the same strategy was supported more when described using benefits and permissive language instead of costs and restrictive language. CONCLUSIONS: Most respondents supported strategies to reduce CUWD, and beliefs about risks and benefits predicted this snupport. Reactance to CUWD messaging emerged as a key predictor of lower support (and of greater self-reported distracted driving), indicating that it could be an important variable to consider when designing strategies to reduce CUWD. When targeting people resistant to quitting CUWD entirely, communicators could recommend a switch to handsfree use. Communicators who emphasize benefits and use permissive language also may increase support for CUWD reduction.