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

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

Scientific evidence regularly guides policy decisions 1, with behavioural science increasingly part of this process 2. In April 2020, an influential paper 3 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

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

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

DATA AVAILABILITY : All data and study material are provided either in the Supplementary information or through the two online repositories (OSF and Tableau Public, both accessible via https://psyarxiv.com/58udn). No code was used for analyses in this work.Scientific evidence regularly guides policy decisions, with behavioural science increasingly part of this process. In April 2020, an influential paper 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 National Science Foundation; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brazilian Federal Agency for the Support and Evaluation of Graduate Education); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brazilian Federal Agency for the Support and Evaluation of Graduate Education); the Ministry of Science, Technology and Innovation | Conselho Nacional de Desenvolvimento Científico e Tecnológico (National Council for Scientific and Technological Development); National Science Foundation grants; the European Research Council; the Canadian Institutes of Health Research.http://www.nature.com/naturehj2024Gordon Institute of Business Science (GIBS)Non

Outcomes following negative prostate biopsy for patients with persistent disease after radiotherapy for prostate cancer

PURPOSE: When faced with biochemical recurrence after definitive radiotherapy for prostate cancer, clinicians must determine whether the recurrence is local or systemic. Post radiotherapy prostate biopsies to detect persistent local disease are difficult to interpret histopathologically and are subject to sampling error. Our study examines outcomes for patients with a negative prostate biopsy performed for rising prostate-specific antigen (PSA) levels after prostate radiation. MATERIALS AND METHODS: We performed a retrospective review of 238 prostate cancer patients with a negative biopsy following definitive radiotherapy. Seventy-five of these patients had biochemical recurrence at the time of biopsy. A negative biopsy was defined as the absence of prostate cancer without radiation-treatment effect in the specimen. RESULTS: Patients underwent biopsy at a mean of 41 months after the completion of radiation. They had a mean PSA of 6. Patients were followed for an average of 63 months. Thirty-two patients (43%) developed metastasis, and 11 (15%) died of prostate cancer despite a negative post-radiation biopsy. Five of nine patients (56%) with sequential biopsies had a positive second biopsy. CONCLUSIONS: Patients with PSA recurrence and a negative post-radiation biopsy have a high chance of persistent local disease, progression, and death from prostate cancer. Furthermore, an initial negative biopsy does not rule-out local recurrence. Patients with biochemical recurrence after radiotherapy for prostate cancer need to be evaluated earlier for local recurrence

The incidence of fluoroquinolone resistant infections after prostate biopsy--are fluoroquinolones still effective prophylaxis?

PURPOSE: Fluoroquinolones have been shown to decrease infective complications after prostate biopsy. However, fluoroquinolone resistance is emerging. We quantified contemporary rates of infective complications and the incidence of fluoroquinolone resistant infections after prostate biopsy under fluoroquinolone prophylaxis. MATERIALS AND METHODS: We retrospectively evaluated the records of 1,273 patients who underwent prostate biopsy at New York Harbor Veterans Affairs Hospital from January 2004 to December 2006. Patients received levofloxacin or gatifloxacin. Using the Veterans Affairs computerized patient record system we reviewed all patient visits within 1 month after prostate biopsy. Visits were queried for infective symptoms. Positive cultures were evaluated for resistance patterns. The annual and overall incidence of infective complications and fluoroquinolone resistant infections was calculated. RESULTS: Of 1,273 patients 31 (2.4%) presented with infective symptoms after biopsy. The overall incidence of fluoroquinolone resistant infections was 1.2% (15 cases). When stratified by year, there were statistically significant increases in the incidence of infective complications and fluoroquinolone resistance from 2004 to 2006. Of the positive cultures those from 89% of patients yielded Escherichia coli and 90% were fluoroquinolone resistant. Fluoroquinolone resistant E. coli were also resistant to gentamicin in 22% of cases, trimethoprim/sulfamethoxazole in 44%, piperacillin in 72% and ampicillin in 94%. However, 100% sensitivity was demonstrated for amikacin, ceftazidime and ceftriaxone. CONCLUSIONS: Fluoroquinolones are still effective as antibiotic prophylaxis for prostate biopsies but there is an increase in infective complications and fluoroquinolone resistance. When patients present with post-prostate biopsy infective symptoms, almost 50% are associated with fluoroquinolone resistant pathogens. Empirical treatment with ceftriaxone, ceftazidime or amikacin should be initiated until culture specific therapy can be implemented