The Acute Optic Neuritis Network (ACON): Study protocol of a non-interventional prospective multicenter study on diagnosis and treatment of acute optic neuritis

Optic neuritis (ON) often occurs at the presentation of multiple sclerosis (MS), neuromyelitis optica spectrum disorders (NMOSD), and myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD). The recommended treatment of high-dose corticosteroids for ON is based on a North American study population, which did not address treatment timing or antibody serostatus. The Acute Optic Neuritis Network (ACON) presents a global, prospective, observational study protocol primarily designed to investigate the effect of time to high-dose corticosteroid treatment on 6-month visual outcomes in ON. Patients presenting within 30 days of the inaugural ON will be enrolled. For the primary analysis, patients will subsequently be assigned into the MS-ON group, the aquapotin-4-IgG positive ON (AQP4-IgG+ON) group or the MOG-IgG positive ON (MOG-IgG+ON) group and then further sub-stratified according to the number of days from the onset of visual loss to high-dose corticosteroids (days-to-Rx). The primary outcome measure will be high-contrast best-corrected visual acuity (HC-BCVA) at 6 months. In addition, multimodal data will be collected in subjects with any ON (CIS-ON, MS-ON, AQP4-IgG+ON or MOG-IgG+ON, and seronegative non-MS-ON), excluding infectious and granulomatous ON. Secondary outcomes include low-contrast best-corrected visual acuity (LC-BCVA), optical coherence tomography (OCT), magnetic resonance imaging (MRI) measurements, serum and cerebrospinal fluid (CSF) biomarkers (AQP4-IgG and MOG-IgG levels, neurofilament, and glial fibrillary protein), and patient reported outcome measures (headache, visual function in daily routine, depression, and quality of life questionnaires) at presentation at 6-month and 12-month follow-up visits. Data will be collected from 28 academic hospitals from Africa, Asia, the Middle East, Europe, North America, South America, and Australia. Planned recruitment consists of 100 MS-ON, 50 AQP4-IgG+ON, and 50 MOG-IgG+ON. This prospective, multimodal data collection will assess the potential value of early high-dose corticosteroid treatment, investigate the interrelations between functional impairments and structural changes, and evaluate the diagnostic yield of laboratory biomarkers. This analysis has the ability to substantially improve treatment strategies and the accuracy of diagnostic stratification in acute demyelinating ON. Trial registration: ClinicalTrials.gov, identifier: NCT05605951

The Acute Optic Neuritis Network (ACON): Study protocol of a non-interventional prospective multicenter study on diagnosis and treatment of acute optic neuritis

Optic neuritis (ON) often occurs at the presentation of multiple sclerosis (MS), neuromyelitis optica spectrum disorders (NMOSD), and myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD). The recommended treatment of high-dose corticosteroids for ON is based on a North American study population, which did not address treatment timing or antibody serostatus. The Acute Optic Neuritis Network (ACON) presents a global, prospective, observational study protocol primarily designed to investigate the effect of time to high-dose corticosteroid treatment on 6-month visual outcomes in ON. Patients presenting within 30 days of the inaugural ON will be enrolled. For the primary analysis, patients will subsequently be assigned into the MS-ON group, the aquapotin-4-IgG positive ON (AQP4-IgG+ON) group or the MOG-IgG positive ON (MOG-IgG+ON) group and then further sub-stratified according to the number of days from the onset of visual loss to high-dose corticosteroids (days-to-Rx). The primary outcome measure will be high-contrast best-corrected visual acuity (HC-BCVA) at 6 months. In addition, multimodal data will be collected in subjects with any ON (CIS-ON, MS-ON, AQP4-IgG+ON or MOG-IgG+ON, and seronegative non-MS-ON), excluding infectious and granulomatous ON. Secondary outcomes include low-contrast best-corrected visual acuity (LC-BCVA), optical coherence tomography (OCT), magnetic resonance imaging (MRI) measurements, serum and cerebrospinal fluid (CSF) biomarkers (AQP4-IgG and MOG-IgG levels, neurofilament, and glial fibrillary protein), and patient reported outcome measures (headache, visual function in daily routine, depression, and quality of life questionnaires) at presentation at 6-month and 12-month follow-up visits. Data will be collected from 28 academic hospitals from Africa, Asia, the Middle East, Europe, North America, South America, and Australia. Planned recruitment consists of 100 MS-ON, 50 AQP4-IgG+ON, and 50 MOG-IgG+ON. This prospective, multimodal data collection will assess the potential value of early high-dose corticosteroid treatment, investigate the interrelations between functional impairments and structural changes, and evaluate the diagnostic yield of laboratory biomarkers. This analysis has the ability to substantially improve treatment strategies and the accuracy of diagnostic stratification in acute demyelinating ON

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 global experiment on motivating social distancing during the COVID-19 pandemic

Finding communication strategies that effectively motivate social distancing continues to be a global public health priority during the COVID-19 pandemic. This cross-country, preregistered experiment (n = 25,718 from 89 countries) tested hypotheses concerning generalizable positive and negative outcomes of social distancing messages that promoted personal agency and reflective choices (i.e., an autonomy-supportive message) or were restrictive and shaming (i.e., a controlling message) compared with no message at all. Results partially supported experimental hypotheses in that the controlling message increased controlled motivation (a poorly internalized form of motivation relying on shame, guilt, and fear of social consequences) relative to no message. On the other hand, the autonomy-supportive message lowered feelings of defiance compared with the controlling message, but the controlling message did not differ from receiving no message at all. Unexpectedly, messages did not influence autonomous motivation (a highly internalized form of motivation relying on one’s core values) or behavioral intentions. Results supported hypothesized associations between people’s existing autonomous and controlled motivations and self-reported behavioral intentions to engage in social distancing. Controlled motivation was associated with more defiance and less long-term behavioral intention to engage in social distancing, whereas autonomous motivation was associated with less defiance and more short- and long-term intentions to social distance. Overall, this work highlights the potential harm of using shaming and pressuring language in public health communication, with implications for the current and future global health challenges

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

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 multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world

Cognitive neuroscience of metacognition

This chapter explores the neural underpinnings of metacognition – the monitoring and controlling of one’s own thoughts. After first defining metacognition and describing how it can be measured, we discuss the evidence for explicit representations of metacognitive signals, reviewing neuroimaging studies that have dissociated metacognitive from object-level processes. Further, we consider the functional value of metacognition, including the social sharing of confidence estimates for group decision-making. Finally, we review research debates that cognitive neuroscience research may help address, focusing on how metacognition is represented in the brain, the relationship between metacognition and Theory of Mind, and the nature of metacognitive deficits in psychiatric disorders