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  1. Last 7 days
    1. 2020-10-09

    2. Weisz, E., & Cikara, M. (2020, October 9). Strategic Regulation of Empathy. https://doi.org/10.31234/osf.io/2kr46

    3. 10.31234/osf.io/2kr46
    4. Empathy is an integral part of socio-emotional well-being, yet recent research has highlighted some of its downsides. Here we examine literature that establishes when, how much, and what aspects of empathy promote specific outcomes. After reviewing a theoretical framework which characterizes empathy as a suite of separable components, we examine evidence showing how dissociations of these components affect important socio-emotional outcomes and describe emerging evidence suggesting that these components can be independently and deliberately modulated. Finally, we advocate for a new approach to a multi-component view of empathy which accounts for the interrelations among components. This perspective advances scientific conceptualization of empathy and offers suggestions for tailoring empathy to help people realize their social, emotional, and occupational goals.
    5. Strategic Regulation of Empathy
    1. 2020-10-12

    2. Meeter, M., Bele, T., Hartogh, C. d., Bakker, T., de Vries, R. E., & Plak, S. (2020, October 11). College students’ motivation and study results after COVID-19 stay-at-home orders. https://doi.org/10.31234/osf.io/kn6v9

    3. 10.31234/osf.io/kn6v9
    4. Due to the COVID-19 pandemic, many institutions of higher education had to close their campuses and shift to online education. Here, we investigate how stay-at-home orders impacted students. We investigated results obtained by 15,125 bachelor students at a large Dutch research university during a semester in which the campus was closed and all education had shifted online. Moreover, we surveyed 166 students of the bachelor of psychology program of the same university. Results showed that students rated online education as less satisfactory than campus-based education, and rated their own motivation as having gone down. This was reflected in a lower time investment: lectures and small-group meetings were attended less frequently, and student estimates of hours studied went down. Lower motivation predicted this drop in effort. Moreover, a drop in motivation was related to fewer credits being obtained during stay-at-home orders. However, on average students reported obtaining slightly more credits than before, which was indeed found in an analysis of administered credits. In a qualitative analysis of student comments, it was found that students missed social interactions, but reported being much more efficient during online education. It is concluded that whereas student satisfaction and motivation dropped during the shift to online education, increased efficiency meant results were not lower than they would normally have been.
    5. College students’ motivation and study results after COVID-19 stay-at-home orders
    1. 2020-10-13

    2. Florida, R & Mellander, C. (2020) The Geography of COVID-19 in Sweden. Working Paper Series in Economics and Institutions of Innovation, Royal Institute of Technology.

    3. The Geography of COVID-19 in Sweden
    4. This paper examines the geographic factors that are associated with the spread of COVID-19 in Sweden. The country is a useful case study to examine because it did not impose mandatory lockdowns, and thus we would expect the virus to spread in a more unimpeded way across communities. A growing body of research has examined the role of factors like density, household size, air connectivity, income, race and ethnicity, age, political affiliation, temperature and climate, and policy measure like lockdowns and physical distancing among others. The research examines the effects of some of these factors on the geographic variation of COVID-19 cases and on deaths, across both municipalities and neighborhoods. Our findings show that the geographic variation in COVID-19 is significantly but modestly associated with variables like density, population size, and the socio-economic characteristics of places, and somewhat more associated with variables for household size. What matters more is the presence of high-risk nursing homes and the onset of infections with places that were hit earlier by COVID-19 cases experiencing more severe outbreaks. Still, all these variables explain little of the geographic variation in COVID-19 across Sweden. There appears to be a high degree of randomness in the geographic variation of COVID-19 across Sweden and the degree to which some places were hit harder than others.
  2. Oct 2020
    1. von Gaudecker, H., Holler, R., Janys, L., Siflinger, B. M., & Zimpelmann, C. (2020). Labour Supply during Lockdown and a “New Normal”: The Case of the Netherlands. IZA Discussion Paper, 13623.

    2. 2020-08

    3. We document the evolution of hours of work using monthly data from February to June 2020. During this period, the Nether­lands ex­pe­ri­enced a quick spread of the SARS-CoV-2 virus, enacted a lockdown for a period of six weeks and gradually opened there­after. We show that during lock-down, sub­sti­tutabil­ity between work from home and at the workplace or essential worker status are key to maintain a large fraction of pre-​crisis hours of work. These pandemic-​specific mech­a­nisms become much less important as social dis­tanc­ing re­stric­tions are eased in May and June. Labor supply recovers quickly in sectors affected heavily during lockdown, but goes down in other areas of the economy. The latter is unlikely caused by pandemic-​induced supply changes; di­min­ished demand is a more plausible ex­pla­na­tion. Analyzing take-up of economic support programs, we find sug­ges­tive evidence that wage subsidies and other programs helped limit the early-​stage impact of the crisis along the extensive margin.
    4. Labour Supply during Lockdown and a “New Normal”: The Case of the Nether­lands
    1. Tani, M., Cheng, Z., Mendolia, S., Paloyo, A. R., & Savage, D. (2020). Working Parents, Financial Insecurity, and Child-​Care: Mental Health in the Time of COVID-19. IZA Discussion Paper, 13588.

    2. 2020-08

    3. The COVID-19 pandemic and the policy measures to control its spread – lockdowns, physical dis­tanc­ing, and social isolation – has coincided with the de­te­ri­o­ra­tion of people’s mental well-​being. We use data from the UK Household Lon­gi­tu­di­nal Study (UKHLS) to document how this phe­nom­e­non is related to the situation of working parents who now have to manage competing time demands across the two life domains of work and home. We show that the worsening of mental health in the United Kingdom is worse for working parents, and that it is es­pe­cially related to the increased financial in­se­cu­rity and the time spent on childcare and home schooling. We find that this burden is not shared equally between men and women, and between richer and poorer house­holds. In crafting public policy responses to the pandemic, better outcomes can be achieved if pol­i­cy­mak­ers are cognizant of these in­equal­i­ties. Keywords
    4. Working Parents, Financial In­se­cu­rity, and Child-​Care: Mental Health in the Time of COVID-19
    1. 2020-10-07

    2. Shauna Brail on Twitter. (n.d.). Twitter. Retrieved October 9, 2020, from https://twitter.com/shaunabrail/status/1313818873163067392

    3. Next week we'll launch the mobility dashboard. In the meantime, our intro video tells the story of the full initiative, supported by a Mitacs Research Trainee Award and produced by research assistant extraordinaire, Katherine Hovdestad
    4. We had hoped to access publicly-collected mental health data-however, it's not available yet though researchers are working on it. The pandemic has revealed the importance of data, and yet despite quantity of data collected, making that data useable & accessible is a challenge.
    5. The dashboard highlights the current status of increasing COVID-19 cases/hospitalizations amidst the context of other public health measures: few school outbreaks, surgical backlogs, shortened ER waits, fewer visits to supervised injection sites + more overdose-related deaths
    6. Toronto After the First Wave: Tracking Toronto's experience and response to COVID-19 in Fall 2020, our first dashboard focuses on measures of public health https://torontoafterthefirstwave.com/dashboards/health/
    1. 2020-10

    2. Burel, Gregoire; Farrell, Tracie; Mensio, Martino; Khare, Prashant and Alani, Harith (2020). Co-Spread of Misinformation and Fact-Checking Content during the Covid-19 Pandemic. In: Proceedings of the 12th International Social Informatics Conference (SocInfo), LNCS.

    3. Co-Spread of Misinformation and Fact-Checking Content during the Covid-19 Pandemic
    4. In the context of the Covid-19 pandemic, the consequences of misinformation are a matter of life and death. Correcting misconceptions and false beliefs are important for injecting reliable information about the outbreak. Fact-checking organisations produce content with the aim of reducing misinformation spread, but our knowledge of its impact on misinformation is limited. In this paper, we explore the relation between misinformation and fact-checking spread during the Covid-19 pandemic. We specifically follow misinformation and fact-checks emerging from December 2019 to early May 2020. Through a combination of spread variance analysis, impulse response modelling and causal analysis, we show similarities in how misinformation and fact-checking information spread and that fact-checking information has a positive impact in reducing misinformation. However, we observe that its efficacy can be reduced, due to the general amount of online misinformation and the short-term spread of fact-checking information compared to misinformation
    1. 2020-10-06

    2. Alexandra Freeman on Twitter. (n.d.). Twitter. Retrieved October 8, 2020, from https://twitter.com/alex_freeman/status/1313533304696639489

    3. Numbers need context. People don’t normally think in numbers. When forced to put a number on risks of people dying from COVID-19 if they caught it, they over-estimate (and the effect of the number format they are asked to use is evident). But they do know the major risk factors.
    4. People liked ‘positive framing’ (how many likely survive), but the numbers were rated a bit harder to understand. Probably safest to stick with familiar ‘likelihood of dying’. A visual scale helps: despite the difficulties of a linear scale, it was more trusted over log scale.
    5. hen our advice on how to communicate the numbers: Percentages seem clearest format, but also convey the smallest feeling of risk. For balance maybe include an ‘x out of 1000’ translation, which gives a larger feeling of risk. Do not describe as ‘your risk’ – maybe ‘risk result’
    6. 2) What are you trying to communicate? The risk of catching it and dying from it, or the risk of dying from it if you catch it? Whichever it is, be very clear 3) Who are your audience? UK public keen for this information in our surveys, and GPs don’t want to be ‘gatekeepers’
    7. Preprint out – our work on communicating personal risks from COVID-19: https://doi.org/10.1101/2020.10.05.20206961… In summary, for those developing personal risk calculators: 1) Are you trying to change behaviour or simply inform people? It changes your communication approach. UK public opinion
    1. 2020-10-07

    2. Travelling Tabby on Twitter. (n.d.). Twitter. Retrieved October 8, 2020, from https://twitter.com/travellingtabby/status/1313882542425112579

    3. Can you look at the age groups Scotland publishes to avoid the 15-19 hiding the school kids. They had data up to the 27th Sept 0-4, 5-11, 12-17 and the whole group 2-17 but it’s hard to find.
    4. A couple of charts showing the age of the new positive cases in England/Scotland over the past week, per 1m pop Englands figures are quite high in comparison because of the backlog issue, but it looks like 15-24 year olds are behind the bulk of the new cases (uni outbreaks)
    1. Tufekci, Z. (2020, September 30). UThis Overlooked Variable Is the Key to the Pandemic. The Atlantic. https://www.theatlantic.com/health/archive/2020/09/k-overlooked-variable-driving-pandemic/616548/

    2. 2020-09-30

    3. There’s something strange about this coronavirus pandemic. Even after months of extensive research by the global scientific community, many questions remain open.Why, for instance, was there such an enormous death toll in northern Italy, but not the rest of the country? Just three contiguous regions in northern Italy have 25,000 of the country’s nearly 36,000 total deaths; just one region, Lombardy, has about 17,000 deaths. Almost all of these were concentrated in the first few months of the outbreak. What happened in Guayaquil, Ecuador, in April, when so many died so quickly that bodies were abandoned in the sidewalks and streets?* Why, in the spring of 2020, did so few cities account for a substantial portion of global deaths, while many others with similar density, weather, age distribution, and travel patterns were spared? What can we really learn from Sweden, hailed as a great success by some because of its low case counts and deaths as the rest of Europe experiences a second wave, and as a big failure by others because it did not lock down and suffered excessive death rates earlier in the pandemic? Why did widespread predictions of catastrophe in Japan not bear out? The baffling examples go on
    4. This Overlooked Variable Is the Key to the Pandemic
    1. 2020-09-29

    2. Carter, J. (2020, September 29). The American Public Still Trusts Scientists, Says a New Pew Survey. Scientific American. https://www.scientificamerican.com/article/the-american-public-still-trusts-scientists-says-a-new-pew-survey/

    3. Public trust of the scientific community in the United States is as strong as ever, according to a new poll just released today by the Pew Research Center, confirming polling results dating back to the 1970s. Thirty-eight percent of those polled in Pew’s survey in the U.S. say that they have a lot of trust in scientists to do what is right for the public. Those polled also place a lot of trust in scientific institutions as compared to others in the U.S. Pew’s data show respondents only ranked the military as more trustworthy than scientific institutions, while ranking lower trust in others like the national government, news media and business leaders.
    4. The American Public Still Trusts Scientists, Says a New Pew Survey
    1. 2020-09-29

    2. Surkova, E., Nikolayevsskyy, V., Drobniewski, F. (2020). False-positive COVID-19 results: hidden problems and costs. The Lancet Respiratory Medicine. https://doi.org/10.1016/S2213-2600(20)30453-7

    3. 10.1016/S2213-2600(20)30453-7
    4. RT-PCR tests to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA are the operational gold standard for detecting COVID-19 disease in clinical practice. RT-PCR assays in the UK have analytical sensitivity and specificity of greater than 95%, but no single gold standard assay exists.1Watson J Whiting PF Brush JE Interpreting a covid-19 test result.BMJ. 2020; 369m1808PubMed Google Scholar,  2Mayers C Baker K Impact of false-positives and false-negatives in the UK's COVID-19 RT-PCR testing programme.https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/895843/S0519_Impact_of_false_positives_and_negatives.pdfDate: June 3, 2020Date accessed: August 8, 2020Google Scholar New assays are verified across panels of material, confirmed as COVID-19 by multiple testing with other assays, together with a consistent clinical and radiological picture. These new assays are often tested under idealised conditions with hospital samples containing higher viral loads than those from asymptomatic individuals living in the community. As such, diagnostic or operational performance of swab tests in the real world might differ substantially from the analytical sensitivity and specificity.2
    5. False-positive COVID-19 results: hidden problems and costs
  3. Sep 2020
    1. 2020-09-28

    2. Natalie E. Dean en Twitter: “VACCINE EFFICACY 101: A biostatistician's primer. Ten tweets to cover:- How is vaccine efficacy calculated?- Distinguishing between infection, disease, & severe disease.- Measuring reduced infectiousness.- Vaccine efficacy vs. effectiveness!n” / Twitter. (n.d.). Twitter. Retrieved September 30, 2020, from https://twitter.com/nataliexdean/status/1310613702476017666

    3. 9) Household studies can be very useful here, where we follow the household contacts of infected vaccinated individuals and infected unvaccinated individuals, and compare how frequently they are infected. Pioneering work from my mentor @betzhallo. http://courses.washington.edu/b578a/readings/PreziosiHalloranVaccine2003.pdf…
    4. 10) Finally, vaccine efficacy vs. effectiveness? We like to reserve "efficacy" for estimates from randomized trials, where everyone receives the vaccine as intended (proper cold chain, no missed doses). We distinguish this idealized measure from real-world "effectiveness." END
    5. 8) A vaccine that prevents infection entirely provides indirect protection to others. If I can't get infected, I can't infect you. But it is possible to have a vaccine that prevents disease but individuals can still be infectious.
    6. 7) So far I have talked about how well a vaccine directly protects the vaccinated individual. Another important type of vaccine effect is the ability of a vaccine to reduce infectiousness to others. This is known as indirect protection, and is related to herd immunity.
    7. 6) Preventing infection entirely is the hardest to achieve. And of course a vaccine that prevents infection will also prevent disease and severe disease. But we can have vaccines where people are still infected but their disease severity is lessened.Quote Tweet
    8. 5) Most Phase 3 trials are measuring efficacy to prevent disease as the primary analysis, with efficacy against infection and against severe disease as secondary analyses.Quote Tweet
    9. 4) Though we talk about vaccine efficacy as a single number, there are actually several different types of vaccine efficacy, such as: - Efficacy to prevent infection (sterilizing immunity) - Efficacy to prevent disease - Efficacy to prevent severe disease
    10. 3) Vaccine efficacy of 50% roughly means you have a 50% reduced risk of becoming sick compared to an otherwise similar unvaccinated person. Or you have a 50% chance of becoming sick given that you were exposed to enough infectious virus to make an unvaccinated person sick.
    11. 2) Vaccine efficacy (VE) measures the relative reduction in infection/disease for the vaccinated arm versus the unvaccinated arm. A perfect vaccine would eliminate risk entirely, so VE = 1 or 100%. This can be calculated from the risk ratio, incidence rate ratio, or hazard ratio.
    12. VACCINE EFFICACY 101: A biostatistician's primer Ten tweets to cover: - How is vaccine efficacy calculated? - Distinguishing between infection, disease, & severe disease. - Measuring reduced infectiousness. - Vaccine efficacy vs. effectiveness!
    1. 2020-04-28

    2. Digital transformation is a buzzword that has been around for some time. For many, digital transformation started to kick into full gear in the 1990s as personal computers started to become more prevalent. This is when businesses looked at providing more digital experiences for customers and end users and also began transforming the way they worked internally to keep up with the pace of technology. While nearly every industry is undergoing or at least considering digital transformation, according to McKinsey, “the average digital transformation ... stands a 45 percent chance of delivering less profit than expected.” Nonetheless, businesses are still investing in these initiatives; IDC estimates that worldwide spending on the technologies and services that enable digital transformation will reach $2.3 trillion in 2023. So, why should you embark or continue on a digital transformation journey? And what is digital transformation, exactly? As the president of a company that offers software development and digital transformation services, I'll attempt to outline what success looks like and how to get there.
    3. What's Powering Digital Transformation?
    1. 10.1007/s40471-020-00245-2
    2. 2020-09-23

    3. Caniglia, E.C., Murray, E.J. (2020) Difference-in-Difference in the Time of Cholera: a Gentle Introduction for Epidemiologists. Current Epidemiology Reports. https://doi.org/10.1007/s40471-020-00245-2

    4. Purpose of ReviewThe goal of this article is to provide an introduction to the intuition behind the difference-in-difference method for epidemiologists. We focus on the theoretical aspects of this tool, including the types of questions for which difference-in-difference is appropriate, and what assumptions must hold for the results to be causally interpretable.Recent FindingsWhile currently under-utilized in epidemiologic research, the difference-in-difference method is a useful tool to examine effects of population level exposures, but relies on strong assumptions.SummaryWe use the famous example of John Snow’s investigation of the cause of cholera mortality in London to illustrate the difference-in-difference approach and corresponding assumptions. We conclude by arguing that this method deserves a second look from epidemiologists interested in asking causal questions about the impact of a population level exposure change on a population level outcome for the group that experienced the change.
    1. 10.1101/2020.09.15.20191957
    2. 2020-09-18

    3. Smith, E. L., Potts, W.W. H., Amlot R., Fear, T. N., Michie, S., Rubin, J. (2020).Adherence to the test, trace and isolate system: results from a time series of 21 nationally representative surveys in the UK (the COVID-19 Rapid Survey of Adherence to Interventions and Responses [CORSAIR] study).medRxiv. https://doi.org/10.1101/2020.09.15.20191957

    4. Objectives: To investigate rates of adherence to the UKs test, trace and isolate system over time. Design: Time series of cross-sectional online surveys. Setting: Data were collected between 2 March and 5 August 2020. Participants: 42,127 responses from 31,787 people living in the UK, aged 16 years or over, are presented (21 survey waves, n≈2,000 per wave). Main outcome measures: Identification of the key symptoms of COVID-19 (cough, high temperature / fever, and loss of sense of smell or taste), self-reported adherence to self-isolation if symptomatic, requesting an antigen test if symptomatic, intention to share details of close contacts, self-reported adherence to quarantine if alerted that you had been in contact with a confirmed COVID-19 case. Results: Only 48.9% of participants (95% CI 48.2% to 49.7%) identified key symptoms of COVID-19. Self-reported adherence to test, trace and isolate behaviours was low (self-isolation 18.2%, 95% CI 16.4% to 19.9%; requesting an antigen test 11.9%, 95% CI 10.1% to 13.8%; intention to share details of close contacts 76.1%, 95% CI 75.4% to 76.8%; quarantining 10.9%, 95% CI 7.8% to 13.9%) and largely stable over time. By contrast, intention to adhere to protective measures was much higher. Non-adherence was associated with: men, younger age groups, having a dependent child in the household, lower socio-economic grade, greater hardship during the pandemic, and working in a key sector. Conclusions: Practical support and financial reimbursement is likely to improve adherence. Targeting messaging and policies to men, younger age groups, and key workers may also be necessary.
    5. Adherence to the test, trace and isolate system: results from a time series of 21 nationally representative surveys in the UK (the COVID-19 Rapid Survey of Adherence to Interventions and Responses [CORSAIR] study)
    1. 10.31234/osf.io/wqdx8
    2. Gurung, R. A. R., & Stone, A. (2020, September 14). You Can’t Always Get What You Want and It Hurts: Learning During the Pandemic. https://doi.org/10.31234/osf.io/wqdx8

    3. 2020-09-14

    4. Colleges and universities around the world switched to remote teaching in early 2020. In this study we assessed the experiences of students who experienced different operationalizations of remote teaching during the first full term of instruction during the COVID pandemic. Students (N = 649) in 11 sections of Introductory Psychology participated in an online assessment of their learning after completing their final exam. We examined the level of alignment between student preferences (e.g., for synchronous lectures) with the format of the classes they were in (e.g., featuring synchronous lectures) and used this measure of fit (aligned, misaligned, no preference) and students’ modality based self-efficacy as predictors of learning. Self-efficacy predicted final exam scores and students’ ratings of the skills learned, value of science, student learning outcomes, class behaviors, and attitudes toward their class. Fit predicted differences in attitude and class related behaviors (e.g., studying). Self-efficacy also predicted the extent to which students changed their learning behaviors during the pandemic. Our results provide educators with key ways to prepare for additional remote teaching.
    5. You Can’t Always Get What You Want and It Hurts: Learning During the Pandemic
    1. Leicester UCU en Twitter: “Universities are conducting an experiment, an experiment that involves human beings (university staff and students) and a life-threatening virus. But experimental subjects must give informed consent. (That's basic research ethics.)” / Twitter. (n.d.). Twitter. Retrieved September 26, 2020, from https://twitter.com/leicesterucu/status/1309107917879156737

    2. 2020-09-24

    3. Members of host communities are also part of this experiment, of course. (We should have mentioned this above.) University leaders haven't sought their consent either.
    4. But university leaders, including at @uniofleicester, are neither informing us of the risks, nor seeking our consent to participate in this experiment. (This important point was just made by a member in our emergency general meeting.)
    5. Universities are conducting an experiment, an experiment that involves human beings (university staff and students) and a life-threatening virus. But experimental subjects must give informed consent. (That's basic research ethics.)
    1. 2020-09-14

    2. Racine, S. E., Miller, A. E., Mehak, A., & Trolio, V. (2020, September 14). Examining Risk and Protective Factors for Psychological Health during the COVID-19 Pandemic. https://doi.org/10.31234/osf.io/ys8fn

    3. 10.31234/osf.io/ys8fn
    4. Examining Risk and Protective Factors for Psychological Health during the COVID-19 Pandemic
    5. Background: The coronavirus disease 2019 (COVID-19) pandemic has impacted the lives of people globally, and the significant mental health consequences of this pandemic are beginning to be documented. In addition to sociodemographic and COVID-19 specific factors, psychological risk and protective mechanisms likely influence individual differences in mental health symptoms in the context of the COVID-19 pandemic. We examined associations between a broad set of risk and protective factors with symptoms of depression, anxiety, alcohol problems, and eating pathology, and investigated interactions between objective stress due to COVID-19 and risk/protective variables in predicting psychopathology. Methods: Participants were 877 adults (73.7% female) recruited via internet sources from around the globe, but primarily residing in North America (87.4%). Results: Structural equation modelling revealed that certain risk and protective factors (e.g., loneliness, latent protective factor, mindfulness) were broadly related to psychopathology, whereas others showed unique relations with specific forms of psychopathology (e.g., greater repetitive thinking and anxiety; low meaning and purpose and depression). COVID-19 objective stress interacted with risk factors, but not protective factors, to predict greater anxiety symptoms, but not other forms of psychopathology. Limitations: This is a cross-sectional study of non-randomly recruited participants who reported high levels of income and education. Rates of problematic alcohol use were low. Conclusions: Findings contribute to our understanding of psychological mechanisms underlying individual differences in psychopathology in the context of a global stressor. Strategies that reduce loneliness and increase mindfulness will likely impact the greatest number of mental health symptoms.
    1. Austin S. (2020) This Lawyer Ran Errands for His High-Risk Wife. Then an Epidemiologist Rated His Every Move.https://elemental.medium.com/this-lawyer-ran-errands-for-his-high-risk-wife-then-an-epidemiologist-rated-his-every-move-f9a926ad96ec

    2. Wouldn’t it be nice, as you go about your confusing, nerve-wracking, Covid-19-avoiding days, to have an epidemiologist on call to answer your many questions? Consider the Covid Audit the next best thing. This project, a collaboration between Elemental and the Epidemiologic Covid-19 Response Corps at the Boston University School of Public Health, asks real people to document what they’re doing to avoid Covid-19 and gives friendly feedback on actions you can take to support both public health — and your own. This week’s reviewers are response corps members Sarah Lincoln and Ivanna Rocha, graduate students in the Master of Public Health program at BU.
    3. This Lawyer Ran Errands for His High-Risk Wife. Then an Epidemiologist Rated His Every Move.
    1. Koehler, A. and Lempel, H. (2020, August27). Researchquestionsthatcouldhaveabigsocialimpact,organisedby discipline. https://80000hours.org/articles/research-questions-by-discipline/

    2. People frequently ask us what high-impact research in different disciplines might look like. This might be because they’re already working in a field and want to shift their research in a more impactful direction. Or maybe they’re thinking of pursuing an academic research career and they aren’t sure which discipline is right for them.Below you will find a list of disciplines and a handful of research questions and project ideas for each one.
    3. Research questions that could have a big social impact, organised by discipline
  4. Aug 2020
    1. 2020-08-13

    2. Hull, T., Levine, J., Bantilan, N., Desai, A., & Majumder, M. S. (2020, August 13). Digital phenotyping of complex psychological responses to the COVID-19 pandemic. https://doi.org/10.31234/osf.io/qtrpf

    3. 10.31234/osf.io/qtrpf
    4. Background: The novel coronavirus disease 2019 (COVID-19) has negatively impacted mortality, economic conditions, and mental health. A large scale study on psychological reactions to the pandemic to inform ongoing population-level symptom tracking and response to treatment is currently lacking. Methods: Average intake scores for standard depression and anxiety symptom scales were tracked from January 1, 2017 to June 9, 2020 for patients seeking treatment from a digital mental health service to gauge the relationship between COVID-19 and self-reported symptoms. We applied natural language processing (NLP) to unstructured therapy transcript data from patients seeking treatment during the height of the pandemic in the United States between March 1, 2020 and June 9, 2020 to identify words associated with COVID-19 mentions. This analysis was used to identify symptoms that were present beyond those assessed by standard depression and anxiety measures. Results: Depression and anxiety symptoms reported by 169,889 patients between January 1, 2017 and June 9, 2020 were identified. There was no detectable change in intake depression symptom scores. Intake anxiety symptom scores increased 1.42 scale points [95% CI: 1.18, 1.65] between March 15, 2020 and April 1, 2020, when scores peaked. In the transcript data of these 169,889 patients, plus an expanded sample of 49,267 patients without symptom reports, term frequency-inverse document frequency (tf-idf) identified 2,377 positively correlated and 661 negatively correlated terms that were significantly (FDR<.01) associated with mentions of the virus. These terms were classifiable into 24 symptoms beyond those included in the diagnostic criteria for anxiety or depression. Conclusions: The COVID-19 pandemic may have increased intake anxiety symptoms for individuals seeking digital mental health treatment. NLP analyses suggest that standard symptom scales for depression and anxiety alone are inadequate to fully assess and track psychological reactions to the pandemic. Symptoms of grief, trauma, obsession-compulsion, agoraphobia, hypochondriasis, panic, and non- suicidal self-injury should be monitored as part of a new COVID-19 Syndrome category.
    5. Digital phenotyping of complex psychological responses to the COVID-19 pandemic
    1. 2020-08-12

    2. Varma, M. M., Chen, D., Lin, X. L., Aknin, L. B., & Hu, X. (2020, August 12). Prosocial behavior promotes positive emotion during the COVID-19 pandemic. https://doi.org/10.31234/osf.io/vdw2e

    3. 10.31234/osf.io/vdw2e
    4. The COVID-19 pandemic poses significant threat to humans’ physical and mental wellbeing. In response, there has been an urgent “call to action” for psychological interventions that enhance positive emotion and psychological resilience. Extending upon past research documenting the wellbeing benefits of generous action, we conducted two online pre-registered experiments (N =1,623) during the pandemic in which participants were randomly assigned to engage in other- or self-beneficial action. Specifically, participants made charitable donations or gained money for themselves (Experiment 1); purchased COVID-19-related or COVID-19-unrelated items for someone else or for themselves (Experiment 2). Results showed that prosocial behavior led to greater positive affect, meaningfulness, empathy and social connectedness. Affect benefits were detectable whether prosocial spending was COVID-19-related or not. These findings provide support for one strategy to bolster wellbeing during the pandemic – generous action – which may also promote cooperation and social cohesiveness needed to contain and overcome the virus.
    5. Prosocial behavior promotes positive emotion during the COVID-19 pandemic
    1. 2020-08-12

    2. Ponizovskiy, V., Grigoryan, L., & Hofmann, W. (2020, August 12). Why is right-wing media consumption associated with lower compliance with COVID-19 measures?. https://doi.org/10.31234/osf.io/5b3cn

    3. 10.31234/osf.io/5b3cn
    4. Exposure to right-wing media has been shown to relate to lower perceived threat from COVID-19, lower compliance with prophylactic measures against it, and higher incidence of infection and death. What features of right-wing media messages account for these effects? In a preregistered cross-sectional study (N = 554) we test a model that differentiates perceived consequences of two CDC recommendations—washing hands and staying home—for basic human values. People who consumed more right-wing media perceived these behaviors as less beneficial for their personal security, for the well-being of close ones, and the well-being of society at large. Perceived consequences of following the CDC recommendations mediated the relationship between media consumption and compliance with recommendations. Implications for public health messaging are discussed.
    5. Why is right-wing media consumption associated with lower compliance with COVID-19 measures?
    1. 2020-08-12

    2. Martarelli, C., Pacozzi, S., Bieleke, M., & Wolff, W. (2020, August 12). High trait self-control and low boredom proneness help COVID-19 homeschoolers. https://doi.org/10.31234/osf.io/z2avp

    3. 10.31234/osf.io/z2avp
    4. In response to the coronavirus disease 2019 (COVID-19) schools around the world have been closed to protect against the spread of coronavirus. In several countries, homeschooling has been introduced to replace classroom schooling. With a focus on individual differences, the present study examined 138 schoolers (age range = 6 to 21 years) regarding their self-control and boredom proneness. The results showed that both traits were important in predicting adherence to homeschooling. Schoolers with higher levels of self-control perceived homeschooling as less difficult, which in turn increased homeschooling adherence. In contrast, schoolers with higher levels of boredom proneness perceived homeschooling as more difficult, which in turn reduced homeschooling adherence. These results partially hold when it comes to studying in the classroom. However, boredom threatened adherence only in the homeschooling context. Our results indicate that boredom proneness is a critical construct to consider when educational systems switch to homeschooling during a pandemic.
    5. High trait self-control and low boredom proneness help COVID-19 homeschoolers
    1. 2020-08-03

    2. Gupta S, Kane A. (2020, August 3). Do some people have protection against the coronavirus?. CNN. Retrieved August 12, 2020, from https://edition.cnn.com/2020/08/02/health/gupta-coronavirus-t-cell-cross-reactivity-immunity-wellness/index.html

    3. We're now more than seven months into the coronavirus pandemic that has upended the lives of most of Earth's inhabitants. And while it is true that the scientific community has learned many things about the SARS-CoV-2 virus and the disease it causes, Covid-19, there are also many gaps in our understanding.
    4. Do some people have protection against the coronavirus?
    1. 2020-08-05

    2. Khan MS, Fonarow GC, Friede T, et al. Application of the Reverse Fragility Index to Statistically Nonsignificant Randomized Clinical Trial Results. JAMA Netw Open. 2020;3(8):e2012469. doi:10.1001/jamanetworkopen.2020.12469

    3. 10.1001/jamanetworkopen.2020.12469
    4. Importance  Interpreting randomized clinical trials (RCTs) and their clinical relevance is challenging when P values are either marginally above or below the P = .05 threshold.Objective  To use the concept of reverse fragility index (RFI) to provide a measure of confidence in the neutrality of RCT results when assessed from the clinical perspective.Design, Setting, and Participants  In this cross-sectional study, a MEDLINE search was conducted for RCTs published from January 1, 2013, to December 31, 2018, in JAMA, the New England Journal of Medicine (NEJM), and The Lancet. Eligible studies were phase 3 and 4 trials with 1:1 randomization and statistically nonsignificant binary primary end points. Data analysis was performed from August 1, 2019, to August 31, 2019.Exposures  Single vs multicenter enrollment, total number of events, private vs government funding, placebo vs active control, and time to event vs frequency data.Main Outcomes and Measures  The primary outcome was the median RFI with interquartile range (IQR) at the P = .05 threshold. Secondary outcomes were the number of RCTs in which the number of participants lost to follow-up was greater than the RFI; the median RFI with IQR at different P value thresholds; the median reverse fragility quotient with IQR; and the correlation between sample sizes, number of events, and P values of the RCT and RFI.Results  Of the 167 RCTs included, 76 (46%) were published in the NEJM, 50 (30%) in JAMA, and 41 (24%) in The Lancet. The median (IQR) sample size was 970 (470-3427) participants, and the median (IQR) number of events was 251 (105-570). The median (IQR) RFI at the P = .05 threshold was 8 (5-13). Fifty-seven RCTs (34%) had an RFI of 5 or lower, and in 68 RCTs (41%) the number of participants lost to follow-up was greater than the RFI. Trials with P values ranging from P = .06 to P = .10 had a median (IQR) RFI of 3 (2-4). When compared, median (IQR) RFIs were not statistically significant for single-center vs multicenter enrollment (5 [4-13] vs 8 [5-13]; P = .41), private vs government-funded studies (9 [5-13] vs 8 [5-13]; P = .34), and time-to-event primary end points vs frequency data (9 [5-14] vs 7 [4-13]; P = .43). The median (IQR) RFI at the P = .01 threshold was 12 (7-19) and at the P = .005 threshold was 14 (9-21).Conclusions and Relevance  This cross-sectional study found that a relatively small number of events (median of 8) had to change to move the primary end point of an RCT from nonsignificant to statistically significant. These findings emphasize the nuance required when interpreting trial results that did not meet prespecified significance thresholds.
    5. Application of the Reverse Fragility Index to Statistically Nonsignificant Randomized Clinical Trial Results
    1. Pink, S. L., Stagnaro, M., Chu, J., Mernyk, J., Voelkel, J. G., & Willer, R. (2020, August 10). Five Experimental Tests of the Effects of Short Messages on Compliance with COVID-19 Public Health Guidelines. https://doi.org/10.31234/osf.io/g93zw

    2. 2020-08-10

    3. 10.31234/osf.io/g93zw
    4. Preventing the spread of COVID-19 requires persuading the vast majority of the public to significantly change their behavior in numerous, costly ways. However, it is unclear which persuasive strategies are most effective at convincing people who are not fully compliant to take recommended actions, such as wearing a mask and staying home more often. In five studies (N = 5,351) conducted from March - July 2020, we evaluated 56 short messages aimed at convincing people to comply with public health guidelines. In two within-subjects studies, participants rated the persuasiveness of many short messages drawn from both past research on persuasion and original crowdsourcing. In three pre-registered, between-subjects experiments, we tested whether the four top-rated messages from the previous studies led people who were not fully compliant to increase their intentions to comply. We do not find consistent effects of any message, though a message emphasizing civic responsibility to reciprocate healthcare workers’ sacrifices performed best in three of five studies. Overall, these findings suggest that short messages are largely ineffective in increasing compliance with public health guidelines during advanced stages of the pandemic.
    5. Five Experimental Tests of the Effects of Short Messages on Compliance with COVID-19 Public Health Guidelines
    1. 10.31234/osf.io/2gkht
    2. 2020-08-11

    3. McCarrick, D. J., Bilalic, M., Neave, N., & Wolfson, S. (2020, August 11). Home Advantage during the COVID-19 Pandemic in European football. https://doi.org/10.31234/osf.io/2gkht

    4. The home advantage (HA) is a robust phenomenon in soccer whereby the home team wins more games and scores more goals than the away team. One explanation is that the home crowd spurs on home team performance and causes the referee to unconsciously favour the home team. The Covid-19 pandemic provided a unique opportunity to assess this explanation for HA, as European soccer leagues played part of the 2019/2020 season with crowds present and concluded with crowds absent. Using multi-level modelling we compared team performance and referee decisions pre-Covid (crowd present) and post-Covid (crowd absent) across 9,528 games from 15 leagues in 11 countries. HA (goals scored and points gained) was significantly reduced post pandemic, which reflected the inferior performance of the home team. In addition, referees awarded significantly fewer sanctions against the away teams, and home teams created significantly fewer attacking opportunities when they played without fans.
    5. Home Advantage during the COVID-19 Pandemic in European football
    1. Zeynep Tufekci en Twitter: “What the person just chosen to lead the "Technical Advisory Group on Behavioural Insights and Sciences for Health" for WHO wrote on February 28 ("if you're worried about COVID, it's irrational panic") and what I wrote one day before ("We have to get ready so we can lessen risk").” / Twitter. (n.d.). Twitter. Retrieved August 09, 2020, from https://twitter.com/zeynep/status/1289217618172243971

    2. 2020-07-31

    3. Weirdly, some of the "it's just the flu" folks moved to the opposite end of the spectrum, and are amplifying an exaggerated sense of doom and helplessness. Not saying things are great; just saying groupthink will groupthink. It really is hard to fight.
    4. Anyway, I do wish them luck, honestly, because we need them to do the job right. So much depends on it. At a minimum, I hope there is some reflection on why some people were so wrong. Being wrong is normal and reasonable and even helpful as long as one learns from it, and openly.