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.

The psychology and policy of overcoming economic inequality.

Recent arguments claim that behavioral science has focused - to its detriment - on the individual over the system when construing behavioral interventions. In this commentary, we argue that tackling economic inequality using both framings in tandem is invaluable. By studying individuals who have overcome inequality, "positive deviants," and the system limitations they navigate, we offer potentially greater policy solutions.

Well-being is more than happiness and life satisfaction: a multidimensional analysis of 21 countries.

BACKGROUND: Recent trends on measurement of well-being have elevated the scientific standards and rigor associated with approaches for national and international comparisons of well-being. One major theme in this has been the shift toward multidimensional approaches over reliance on traditional metrics such as single measures (e.g. happiness, life satisfaction) or economic proxies (e.g. GDP). METHODS: To produce a cohesive, multidimensional measure of well-being useful for providing meaningful insights for policy, we use data from 2006 and 2012 from the European Social Survey (ESS) to analyze well-being for 21 countries, involving approximately 40,000 individuals for each year. We refer collectively to the items used in the survey as multidimensional psychological well-being (MPWB). RESULTS: The ten dimensions assessed are used to compute a single value standardized to the population, which supports broad assessment and comparison. It also increases the possibility of exploring individual dimensions of well-being useful for targeting interventions. Insights demonstrate what may be masked when limiting to single dimensions, which can create a failure to identify levers for policy interventions. CONCLUSIONS: We conclude that both the composite score and individual dimensions from this approach constitute valuable levels of analyses for exploring appropriate policies to protect and improve well-being.

Global mental health: an improved measure of well-being in multiple languages.

BACKGROUND: An increasing number of international organisations and national governments have committed to well-being promotion. Unfortunately, important questions regarding how to assess well-being are still unresolved, making policy implementation and evaluation difficult. METHODS: This research expanded on Huppert and So's (Soc Indic Res. 110, 837-861 2013) multidimensional subjective well-being framework by investigating the replicability of the model in two non-European regions (South America, represented by Brazil and Colombia, and Eastern Africa, represented by Uganda), and the United Kingdom. Additionally, previous limitations of the framework were also addressed. ESS Round Six items were crucially improved in terms of temporal and response scale consistency. Bayesian approximate measurement invariance was applied on a sample of 381 young adult participants to test for consistency across countries. RESULTS: The Huppert & So (Soc Indic Res. 110, 837-861 2013) model was found to fairly replicate across non-European regions, where meaningful differences in well-being patterns across regions were observed. Additionally, estimated well-being was related with other well-being measures (Five Ways): Learn and Connect were the strongest predictors of general well-being, with Take Notice and Give being associated with specific aspects of it. CONCLUSIONS: Based on this narrow sample of young adults, it appears the ten-item measure proposed by Huppert & So (Soc Indic Res. 110, 837-861 2013) is useful for assessing population mental health outside of Europe. This is only an initial attempt to assess qualities, so further testing should be done before applying at scale for identifying policy opportunities to address well-being of populations.

Nudging New York: adaptive models and the limits of behavioral interventions to reduce no-shows and health inequalities.

BACKGROUND: Missed healthcare appointments (no-shows) are costly and operationally inefficient for health systems. No-show rates are particularly high for vulnerable populations, even though these populations often require additional care. Few studies on no-show behavior or potential interventions exist specifically for Federally Qualified Health Centers (FQHCs), which care for over 24 million disadvantaged individuals in the United States. The purpose of this study is to identify predictors of no-show behavior and to analyze the effects of a reminder intervention in urban FQHCs in order to design effective policy solutions to a protracted issue in healthcare. METHODS: This is a retrospective observational study using electronic medical record data from 11 facilities belonging to a New York City-based FQHC network between June 2017 to April 2018. This data includes 53,149 visits for 41,495 unique patients. Seven hierarchical generalized linear models and generalized additive models were used to predict no-shows, and multiple regression models evaluated the effectiveness of a reminder. All analyses were conducted in R. RESULTS: The strongest predictor of no-show rates in FQHCs is whether or not patients are assigned to empaneled providers (z = - 91.45, p < 10- 10), followed by lead time for appointments (z = 23.87, p < 10- 10). These effects were fairly stable across facilities. The reminder had minimal effects on no-show rates overall (No show rate before: 41.6%, after: 42.1%). For individuals with appointments before and after the reminder, there was a small decrease in no-shows of 2%. CONCLUSIONS: The limited effects of the reminder intervention suggest the need for more personalized behavioral interventions to reduce no-shows. We recommend that these begin with increasing the use of empaneled providers for preventive care appointments and reducing the lag time between setting the appointment and the actual date of the appointment, at least for individuals with a high rate of no-show. By complementing these with low-intensity, low-cost behavioral interventions, we would expect greater impacts for improved access to care, contributing to the well-being of vulnerable populations.

Depressive Symptoms and Sexually Transmitted Disease: Evidence from a Low-Income Neighborhood of New York City.

We examined the association between sexually transmitted disease (STD) and depressive symptoms. Our analysis utilized the 2015 cross-sectional Washington Heights Community Survey. Multivariable binary logistic regression analysis was used to examine the primary association between having a history of STD and patient health questionnaire-9 (PHQ-9) score while adjusting for potential confounders. Then in separate models, we adjusted for the interaction of social factors with PHQ-9 score to test for modification effect on the primary association. In this low-income neighborhood, STD history was not significantly associated with PHQ-9 score in the overall logistic regression model for the primary association. However, in interaction models, STD and depressive symptoms were associated in sub-groups defined by social factors, namely being Hispanic [odds ratio (OR) 1.08; 95% confidence interval (CI) 1.02-1.15], foreign-born (OR 1.08; 95% CI 1.02-1.15), and having low to moderate social support (OR 1.09; 95% CI 1.02-1.15). Our results demonstrate a need for targeted interventions to be applied to vulnerable subgroups identified.

Mindfulness-based cognitive therapy in COPD: a cluster randomised controlled trial.

A considerable proportion of patients with chronic obstructive pulmonary disease (COPD) entering pulmonary rehabilitation (PR) report psychological distress, which is often accompanied by poor physical health status. Mindfulness-based cognitive therapy (MBCT) has been shown to improve psychological and physical outcomes in other chronic diseases. We therefore evaluated the efficacy of MBCT as an add-on to a standard PR programme in COPD.COPD patients eligible for PR were cluster randomised to receive either an 8-week, group-based MBCT programme as an add-on to an 8-week PR programme (n=39), or PR alone (n=45). The primary outcomes of psychological distress and physical health status impairment were measured with the Hospital Anxiety and Depression Scale (HADS) and the COPD Assessment Test (CAT) before randomisation (T1), mid- (T2) and post-intervention (T3), and at 3 (T4) and 6 (T5) months' follow-up .A statistically significant time×arm effect was found for the HADS (Cohen's d=0.62, 95% CIs (d)=0.18-1.06, p=0.010). The treatment effect on the CAT failed to reach statistical significance (d=0.42, 95% CIs (d)=-0.06-0.90, p=0.061).MBCT showed a statistically significant and durable effect on psychological distress, indicating that MBCT may be an efficacious add-on to standard PR programmes in COPD.

The use of single armed observational data to closing the gap in otherwise disconnected evidence networks: a network meta-analysis in multiple myeloma.

BACKGROUND: Network meta-analysis (NMA) allows for the estimation of comparative effectiveness of treatments that have not been studied in head-to-head trials; however, relative treatment effects for all interventions can only be derived where available evidence forms a connected network. Head-to-head evidence is limited in many disease areas, regularly resulting in disconnected evidence structures where a large number of treatments are available. This is also the case in the evidence of treatments for relapsed or refractory multiple myeloma. METHODS: Randomised controlled trials (RCTs) identified in a systematic literature review form two disconnected evidence networks. Standard Bayesian NMA models are fitted to obtain estimates of relative effects within each network. Observational evidence was identified to fill the evidence gap. Single armed trials are matched to act as each other's control group based on a distance metric derived from covariate information. Uncertainty resulting from including this evidence is incorporated by analysing the space of possible matches. RESULTS: Twenty five randomised controlled trials form two disconnected evidence networks; 12 single armed observational studies are considered for bridging between the networks. Five matches are selected to bridge between the networks. While significant variation in the ranking is observed, daratumumab in combination with dexamethasone and either lenalidomide or bortezomib, as well as triple therapy of carfilzomib, ixazomib and elozumatab, in combination with lenalidomide and dexamethasone, show the highest effects on progression free survival, on average. CONCLUSIONS: The analysis shows how observational data can be used to fill gaps in the existing networks of RCT evidence; allowing for the indirect comparison of a large number of treatments, which could not be compared otherwise. Additional uncertainty is accounted for by scenario analyses reducing the risk of over confidence in interpretation of results.

Evidence on global medical travel.

The potential benefits of travelling across national borders to obtain medical treatment include improved care, decreased costs and reduced waiting times. However, medical travel involves additional risks, compared to obtaining treatment domestically. We review the publicly-available evidence on medical travel. We suggest that medical travel needs to be understood in terms of its potential risks and benefits so that it can be evaluated against alternatives by patients who are seeking care. We propose three domains -quality standards, informed decision-making, economic and legal protection - in which better evidence could support the development of medical travel policies.

Les avantages potentiels de la traversée de frontières nationales pour recevoir un traitement médical résident notamment dans une meilleure prise en charge, des coûts moindres et des temps d'attente réduits. Il est cependant plus risqué de voyager pour bénéficier de soins médicaux que de recevoir un traitement à l'intérieur du pays. Nous avons analysé les données scientifiques publiquement disponibles concernant le tourisme médical. Il nous apparaît essentiel de considérer le tourisme médical en fonction de ses risques et de ses avantages potentiels afin que les patients qui nécessitent des soins puissent le comparer aux autres solutions possibles. Nous estimons que l'amélioration de la qualité des données scientifiques dans trois domaines ­ normes de qualité, prise de décision éclairée et protection économique et juridique ­ favoriserait l'élaboration de politiques relatives au tourisme médical.

Los posibles beneficios de cruzar las fronteras nacionales para obtener tratamientos médicos incluyen una mejora de la atención, una disminución de los costes y una reducción de los tiempos de espera. Sin embargo, el turismo sanitario implica riesgos adicionales en comparación con obtener el tratamiento en el país. Se revisaron los datos públicos sobre el turismo sanitario. Nuestra sugerencia es que el turismo sanitario se entienda en términos de sus posibles riesgos y beneficios, de modo que aquellos pacientes que busquen atención médica puedan evaluarlos frente a otras alternativas. Proponemos tres ámbitos (normas de calidad, toma de decisiones informada y protección económica y legal) en los cuales unos datos más claros podrían apoyar el desarrollo de las políticas para el turismo sanitario.

mHealth and global mental health: still waiting for the mH2 wedding?

BACKGROUND: Two phenomena have become increasingly visible over the past decade: the significant global burden of disease arising from mental illness and the rapid acceleration of mobile phone usage in poorer countries. Mental ill-health accounts for a significant proportion of global disability-adjusted life years (DALYs) and years lived with disability (YLDs), especially in poorer countries where a number of factors combine to exacerbate issues of undertreatment. Yet poorer countries have also witnessed significant investments in, and dramatic expansions of, mobile coverage and usage over the past decade. DEBATE: The conjunction of high levels of mental illness and high levels of mobile phone usage in poorer countries highlights the potential for "mH(2)" interventions--i.e. mHealth (mobile technology-based) mental health interventions--to tackle global mental health challenges. However, global mental health movements and initiatives have yet to engage fully with this potential, partly because of scepticism towards technological solutions in general and partly because existing mH(2) projects in mental health have often taken place in a fragmented, narrowly-focused, and small-scale manner. We argue for a deeper and more sustained engagement with mobile phone technology in the global mental health context, and outline the possible shape of an integrated mH(2) platform for the diagnosis, treatment, and monitoring of mental health. SUMMARY: Existing and developing mH(2) technologies represent an underutilised resource in global mental health. If development, evaluation, and implementation challenges are overcome, an integrated mH2 platform would make significant contributions to mental healthcare in multiple settings and contexts.

A 27-country test of communicating the scientific consensus on climate change.

Communicating the scientific consensus that human-caused climate change is real increases climate change beliefs, worry and support for public action in the United States. In this preregistered experiment, we tested two scientific consensus messages, a classic message on the reality of human-caused climate change and an updated message additionally emphasizing scientific agreement that climate change is a crisis. Across online convenience samples from 27 countries (n = 10,527), the classic message substantially reduces misperceptions (d = 0.47, 95% CI (0.41, 0.52)) and slightly increases climate change beliefs (from d = 0.06, 95% CI (0.01, 0.11) to d = 0.10, 95% CI (0.04, 0.15)) and worry (d = 0.05, 95% CI (-0.01, 0.10)) but not support for public action directly. The updated message is equally effective but provides no added value. Both messages are more effective for audiences with lower message familiarity and higher misperceptions, including those with lower trust in climate scientists and right-leaning ideologies. Overall, scientific consensus messaging is an effective, non-polarizing tool for changing misperceptions, beliefs and worry across different audiences.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.

Statistics anxiety, state anxiety during an examination, and academic achievement.

BACKGROUND: A large proportion of students identify statistics courses as the most anxiety-inducing courses in their curriculum. Many students feel impaired by feelings of state anxiety in the examination and therefore probably show lower achievements. AIMS: The study investigates how statistics anxiety, attitudes (e.g., interest, mathematical self-concept) and trait anxiety, as a general disposition to anxiety, influence experiences of anxiety as well as achievement in an examination. SAMPLE: Participants were 284 undergraduate psychology students, 225 females and 59 males. METHODS: Two weeks prior to the examination, participants completed a demographic questionnaire and measures of the STARS, the STAI, self-concept in mathematics, and interest in statistics. At the beginning of the statistics examination, students assessed their present state anxiety by the KUSTA scale. After 25 min, all examination participants gave another assessment of their anxiety at that moment. Students' examination scores were recorded. Structural equation modelling techniques were used to test relationships between the variables in a multivariate context. RESULTS: Statistics anxiety was the only variable related to state anxiety in the examination. Via state anxiety experienced before and during the examination, statistics anxiety had a negative influence on achievement. However, statistics anxiety also had a direct positive influence on achievement. This result may be explained by students' motivational goals in the specific educational setting. CONCLUSIONS: The results provide insight into the relationship between students' attitudes, dispositions, experiences of anxiety in the examination, and academic achievement, and give recommendations to instructors on how to support students prior to and in the examination.

The persistence of cognitive biases in financial decisions across economic groups.

While economic inequality continues to rise within countries, efforts to address it have been largely ineffective, particularly those involving behavioral approaches. It is often implied but not tested that choice patterns among low-income individuals may be a factor impeding behavioral interventions aimed at improving upward economic mobility. To test this, we assessed rates of ten cognitive biases across nearly 5000 participants from 27 countries. Our analyses were primarily focused on 1458 individuals that were either low-income adults or individuals who grew up in disadvantaged households but had above-average financial well-being as adults, known as positive deviants. Using discrete and complex models, we find evidence of no differences within or between groups or countries. We therefore conclude that choices impeded by cognitive biases alone cannot explain why some individuals do not experience upward economic mobility. Policies must combine both behavioral and structural interventions to improve financial well-being across populations.

Psychometric evaluation and experimental validation of the statistics anxiety rating scale.

The Statistics Anxiety Rating Scale (STARS) was adapted into German to examine its psychometric properties (n = 400). Two validation studies (n = 66, n = 96) were conducted to examine its criterion-related validity. The psychometric properties of the questionnaire were very similar to those previously reported for the original English version in various countries and other language versions. Confirmatory factor analysis indicated 2 second-order factors: One was more closely related to anxiety and the other was more closely related to negative attitudes toward statistics. Predictive validity of the STARS was shown both in an experimental exam-like situation in the laboratory and during a real examination situation. Taken together, the findings indicate that statistics anxiety as assessed by the STARS is a useful construct that is more than just an expression of a more general disposition to anxiety.

Unstandard Deviation: The Untapped Value of Positive Deviance for Reducing Inequalities.

Behavioral science is increasingly used in public policy to understand and address various manifestations of inequalities. Yet evidence from effective population-level interventions is limited. One framework, known as positive deviance, emphasizes individuals from disadvantaged circumstances who have significantly better outcomes than are typical for their group. Studying their behaviors and outcomes helps to understand what might explain their overall success. These insights could also be used to help others from these circumstances experience positive outcomes. Because positive deviance has been markedly understudied, we present a framework for doing so specifically within behavioral science for public policies aimed at reducing inequalities. Using examples from real-world and experimental insights on choices and outcomes of positive deviants, we encourage further study of their choices and trajectories over time to produce valuable insights. We propose that leveraging those findings would inform public policy by introducing interventions that are more ecologically sound and population-relevant and thus have a better chance at benefiting those who start off under adverse circumstances.

Short-sighted decision-making by those not vaccinated against COVID-19.

Widespread vaccination is necessary to minimize or halt the effects of many infectious diseases, including COVID-19. Stagnating vaccine uptake can prolong pandemics, raising the question of how we might predict, prevent, and correct vaccine hesitancy and unwillingness. In a multinational sample (N = 4,452) recruited from 13 countries that varied in pandemic severity and vaccine uptake (July 2021), we examined whether short-sighted decision-making as exemplified by steep delay discounting-choosing smaller immediate rewards over larger delayed rewards-predicts COVID-19 vaccination status. Delay discounting was steeper in unvaccinated individuals and predicted vaccination status over and above demographics or mental health. The results suggest that delay discounting, a personal characteristic known to be modifiable through cognitive interventions, is a contributing cause of differences in vaccine compliance.

Role of Military Forces in the New York State Response to COVID-19.

Importance: Military forces in the State of New York, comprising the Army National Guard, Air National Guard, Naval Militia, and State Guard, with contributions from the Army Corps of Engineers, have made major contributions to the state response to the COVID-19 pandemic. Observations: Operation COVID-19 began on March 10, 2020, and will continue uninterrupted at least through June 2022, making it the longest and largest domestic mobilization in state history. More than 7000 service members served across 200 COVID-19 mission sites, administering more than 4 million vaccines, producing more than 35 million testing kits, delivering more than 54 million meals, and administering more than 1.5 million tests. Conclusions and Relevance: Because of the role of states in delivering relief, testing, care, vaccination, and other community support during the COVID-19 pandemic, this article illuminates the role of New York military forces in responding to COVID-19. The aim is to provide details for the public health community, as well as to share lessons for the continued mission and future pandemic responses.

The globalizability of temporal discounting.

Economic inequality is associated with preferences for smaller, immediate gains over larger, delayed ones. Such temporal discounting may feed into rising global inequality, yet it is unclear whether it is a function of choice preferences or norms, or rather the absence of sufficient resources for immediate needs. It is also not clear whether these reflect true differences in choice patterns between income groups. We tested temporal discounting and five intertemporal choice anomalies using local currencies and value standards in 61 countries (N = 13,629). Across a diverse sample, we found consistent, robust rates of choice anomalies. Lower-income groups were not significantly different, but economic inequality and broader financial circumstances were clearly correlated with population choice patterns.

Predictors of adherence to public health behaviors for fighting COVID-19 derived from longitudinal data.

The present paper examines longitudinally how subjective perceptions about COVID-19, one's community, and the government predict adherence to public health measures to reduce the spread of the virus. Using an international survey (N = 3040), we test how infection risk perception, trust in the governmental response and communications about COVID-19, conspiracy beliefs, social norms on distancing, tightness of culture, and community punishment predict various containment-related attitudes and behavior. Autoregressive analyses indicate that, at the personal level, personal hygiene behavior was predicted by personal infection risk perception. At social level, social distancing behaviors such as abstaining from face-to-face contact were predicted by perceived social norms. Support for behavioral mandates was predicted by confidence in the government and cultural tightness, whereas support for anti-lockdown protests was predicted by (lower) perceived clarity of communication about the virus. Results are discussed in light of policy implications and creating effective interventions.