Differences in comprehending and acting on pandemic health risk information: a qualitative study using mental models.

BACKGROUND: A worldwide pandemic of a new and unknown virus is characterised by scientific uncertainty. However, despite this uncertainty, health authorities must still communicate complex health risk information to the public. The mental models approach to risk communication describes how people perceive and make decisions about complex risks, with the aim of identifying decision-relevant information that can be incorporated into risk communication interventions. This study explored how people use mental models to make sense of scientific information and apply it to their lives and behaviour in the context of COVID-19. METHODS: This qualitative study enrolled 15 male and female participants of different ages, with different levels of education and occupational backgrounds and from different geographical regions of Norway. The participants were interviewed individually, and the interview data were subjected to thematic analysis. The interview data were compared to a expert model of COVID-19 health risk communication based on online information from the Norwegian Institute of Public Health. Materials in the interview data not represented by expert model codes were coded inductively. The participants' perceptions of and behaviours related to health risk information were analysed across three themes: virus transmission, risk mitigation and consequences of COVID-19. RESULTS: The results indicate that people placed different meanings on the medical and scientific words used by experts to explain the pandemic (e.g., virus transmission and the reproduction number). While some people wanted to understand why certain behaviour and activities were considered high risk, others preferred simple, clear messages explaining what to do and how to protect themselves. Similarly, information about health consequences produced panic in some interviewees and awareness in others. CONCLUSION: There is no one-size-fits-all approach to public health risk communication. Empowering people with decision-relevant information necessitates targeted and balanced risk communication.

Investigating a psychological model of mental conditions and coping during the COVID-19 pandemic driven by participatory methods.

BACKGROUND: There is evidence of increased mental health problems during the early stages of the COVID-19 pandemic. We aimed to identify the factors that put certain groups of people at greater risk of mental health problems. METHODS: We took a participatory approach, involving people with lived experience of mental health problems and/or carers, to generate a set of risk factors and potential moderators of the effects of COVID on mental health. An online cross-sectional survey was completed by 1464 United Kingdom residents between 24th April and 27th June 2020. The survey had questions on whether respondents were existing mental health service users and or carers, level of depression (PHQ9) and anxiety (GAD7), demographics, threat and coping appraisals, perceived resilience (BRS), and specific coping behaviours (validated as part of this study). The relationship between responses and coping strategies was measured using tetrachoric correlations. Structural equation modelling was used to test the model. RESULTS: A model significantly fit our data (rel χ2 = 2.05, RMSEA = 0.029 95%, CI (0.016, 0.042), CFI = 0.99, TLI = 0.98, SRMR = 0.014). Age and coping appraisal predicted anxiety and depression. Whereas, threat appraisal and ethnicity only predicted anxiety, and resilience only predicted depression. Additionally, specific coping behaviours predicted anxiety and depression, with overlap on distraction. CONCLUSIONS: Some, but not all, risk factors significantly predict anxiety and depression. While there is a relationship between anxiety and depression, different factors may put people at greater risk of one or the other during the pandemic.

Mental Models of Illness during the Early Months of the COVID-19 Pandemic.

The COVID-19 pandemic and its profound global effects may be changing the way we think about illness. In summer 2020, 120 American adults were asked to diagnose symptoms of COVID-19, a cold, and cancer, and to answer questions related to the diagnosis, treatment, prevention, time-course, and transmission of each disease. Results showed that participants were more likely to correctly diagnose COVID-19 (91% accuracy) compared to a cold (58% accuracy) or cancer (52% accuracy). We also found that 7% of participants misdiagnosed cold symptoms as COVID-19, and, interestingly, over twice as many participants (16%) misdiagnosed symptoms of cancer as COVID-19. Our findings suggest a distinct mental model for COVID-19 compared to other illnesses. Further, the prevalence of COVID-19 in everyday discourse-especially early in the pandemic-may lead to biased responding, similar to errors in medical diagnosis that result from physicians' expertise. We also discuss how the focus of public-health messaging on prevention of COVID-19 might contribute to participants' mental models.

Maternal and newborn health for the urban poor: the need for a new mental model and implementation strategies to accelerate progress.

BACKGROUND: Urbanization challenges the assumptions that have traditionally influenced maternal and newborn health (MNH) programs. This landscaping outlines how current mental models for MNH programs have fallen short for urban slum populations and identifies implications for the global community. We employed a three-pronged approach, including a literature review, key informant interviews with global- and national-level experts, and a case study in Bangladesh. MAIN BODY: Our findings highlight that the current mental model for MNH is inadequate to address the needs of the urban poor. Implementation challenges have arisen from using traditional methods that are not well adapted to traits inherent in slum settings. A re-thinking of implementation strategies will also need to consider a paucity of available routine data, lack of formal coordination between stakeholders and providers, and challenging municipal government structures. Innovative approaches, including with communications, outreach, and technology, will be necessary to move beyond traditional rural-centric approaches to MNH. As populations continue to urbanize, common slum dynamics will challenge conventional strategies for health service delivery. In addition, the COVID-19 pandemic has exposed weaknesses in a system that requires intersectoral collaborations to deliver quality care. CONCLUSION: Programs will need to be iterative and adaptive, reflective of sociodemographic features. Integrating the social determinants of health into evaluations, using participatory human-centered design processes, and innovative public-private partnerships may prove beneficial in slum settings. But a willingness to rethink the roles of all actors within the delivery system overall may be needed most.

Changes in social contacts in England during the COVID-19 pandemic between March 2020 and March 2021 as measured by the CoMix survey: A repeated cross-sectional study.

BACKGROUND: During the Coronavirus Disease 2019 (COVID-19) pandemic, the United Kingdom government imposed public health policies in England to reduce social contacts in hopes of curbing virus transmission. We conducted a repeated cross-sectional study to measure contact patterns weekly from March 2020 to March 2021 to estimate the impact of these policies, covering 3 national lockdowns interspersed by periods of less restrictive policies. METHODS AND FINDINGS: The repeated cross-sectional survey data were collected using online surveys of representative samples of the UK population by age and gender. Survey participants were recruited by the online market research company Ipsos MORI through internet-based banner and social media ads and email campaigns. The participant data used for this analysis are restricted to those who reported living in England. We calculated the mean daily contacts reported using a (clustered) bootstrap and fitted a censored negative binomial model to estimate age-stratified contact matrices and estimate proportional changes to the basic reproduction number under controlled conditions using the change in contacts as a scaling factor. To put the findings in perspective, we discuss contact rates recorded throughout the year in terms of previously recorded rates from the POLYMOD study social contact study. The survey recorded 101,350 observations from 19,914 participants who reported 466,710 contacts over 53 weeks. We observed changes in social contact patterns in England over time and by participants' age, personal risk factors, and perception of risk. The mean reported contacts for adults 18 to 59 years old ranged between 2.39 (95% confidence interval [CI] 2.20 to 2.60) contacts and 4.93 (95% CI 4.65 to 5.19) contacts during the study period. The mean contacts for school-age children (5 to 17 years old) ranged from 3.07 (95% CI 2.89 to 3.27) to 15.11 (95% CI 13.87 to 16.41). This demonstrates a sustained decrease in social contacts compared to a mean of 11.08 (95% CI 10.54 to 11.57) contacts per participant in all age groups combined as measured by the POLYMOD social contact study in 2005 to 2006. Contacts measured during periods of lockdowns were lower than in periods of eased social restrictions. The use of face coverings outside the home has remained high since the government mandated use in some settings in July 2020. The main limitations of this analysis are the potential for selection bias, as participants are recruited through internet-based campaigns, and recall bias, in which participants may under- or overreport the number of contacts they have made. CONCLUSIONS: In this study, we observed that recorded contacts reduced dramatically compared to prepandemic levels (as measured in the POLYMOD study), with changes in reported contacts correlated with government interventions throughout the pandemic. Despite easing of restrictions in the summer of 2020, the mean number of reported contacts only returned to about half of that observed prepandemic at its highest recorded level. The CoMix survey provides a unique repeated cross-sectional data set for a full year in England, from the first day of the first lockdown, for use in statistical analyses and mathematical modelling of COVID-19 and other diseases.

Changes in General and Virus-Specific Anxiety During the Spread of COVID-19 in Israel: A 7-Wave Longitudinal Study.

We compared 3 hypothetical trajectories of change in both general and coronavirus disease 2019 (COVID-19)-specific anxiety during the first wave of the spread in the state of Israel: panic (very high anxiety, either from the outset or rapidly increasing), complacency (stable and low anxiety), and threat-sensitive (a moderate, linear increase compatible with the increase in threat). A representative sample of 1,018 Jewish-Israeli adults was recruited online. A baseline assessment commenced 2 days prior to the identification of the first case, followed by 6 weekly assessments. Latent mixture modeling analyses revealed the presence of 3 trajectories: 1) "threat-sensitivity" (29% and 66%, for general and virus-specific anxiety, respectively), 2) panic (12% and 25%), and 3) complacency (29% and 9%). For general anxiety only, a fourth class representing a stable mid-level anxiety was identified ("balanced": 30%). For general anxiety, women and the initially anxious-both generally and specifically from the spread of the virus-were more likely to belong to the panic class. Men and older participants were more likely to belong to the complacency class. Findings indicate a marked heterogeneity in anxiety responses to the first wave of the spread of COVID-19, including a large group evincing a "balanced" response.

Examining Patients' Capacity to Use Patient Portals: Insights for Telehealth.

BACKGROUND: The increase in telehealth in response to the coronavirus disease 2019 pandemic highlights the need to understand patients' capacity to utilize this care modality. Patient portals are a tool whose use requires similar resources and skills as those required for telehealth. Patients' capacity to use patient portals may therefore provide insight regarding patients' readiness and capacity to use telehealth. OBJECTIVE: The aim of this study was to examine factors related to patients' capacity to use a patient portal and test the impact of these factors on patients' portal use. RESEARCH DESIGN AND SUBJECTS: Using data from a large-scale pragmatic randomized controlled trial of patient portal use, 1081 hospitalized patients responded to survey items that were then mapped onto the 4 dimensions of the Engagement Capacity Framework: self-efficacy, resources, willingness, and capabilities. MEASURES: The outcome variable was frequency of outpatient portal use. We evaluated associations between Engagement Capacity Framework dimensions and patient portal use, using regression analyses. RESULTS: Patients with fewer resources, fewer capabilities, lower willingness, and lower overall capacity to use patient portals used the portal less; in contrast, those with lower perceived self-efficacy used the portal more. CONCLUSIONS: Our findings highlight differences in patients' capacity to use patient portals, which provide an initial understanding of factors that may influence the use of telehealth and offer important guidance in efforts to support patients' telehealth use. Offering patients training tailored to the use of telehealth tools may be particularly beneficial.

Risk perception related to COVID-19 among the Iranian general population: an application of the extended parallel process model.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) has emerged as a major global public health challenge. This study aimed to investigate on how people perceive the COVID-19 outbreak using the components of the Extended Parallel Process Model (EPPM) and to find out how this might contribute to possible behavioral responses to the prevention and control of the disease. METHODS: This cross-sectional study was conducted in Iran during March and April 2020. Participants were recruited via online applications using a number of platforms such as Telegram, WhatsApp, and Instagram asking people to take part in the study. To collect data an electronic self-designed questionnaire based on the EPPM was used in order to measure the risk perception (efficacy, defensive responses, perceived treat) related to the COVID-19. Descriptive statistics, chi-square, t-test and analysis of variance (ANOVA), were used to explore the data. RESULTS: A total of 3727 individuals with a mean age (SD) of 37.0 (11.1) years participated in the study. The results revealed significant differences in efficacy, defensive responses and perceived treat among different population groups particularly among those aged 60 and over. Women had significantly higher scores than men on some aspects such as self-efficacy, reactance, and avoidance but men had higher perceived susceptibility scores compared to women. Overall 56.4% of participants were engaged in danger control (preventive behavior) while the remaining 43.6% were engaged in fear control (non-preventive behavior) process. CONCLUSION: More than half of all participants motivated by danger control. This indicated that more than half of participants had high perceived efficacy (i.e., self-efficacy and response efficacy). Self-efficacy scores were significantly higher among participants who were older, female, single, lived in rural areas, and had good economic status. The results suggest that socioeconomic and demographic factors are the main determinants of the COVID-19 risk perception. Indeed, targeted interventions are essential for controlling the pandemic.

A ratio scale for social distance.

Choosing a larger-later reward over a smaller-sooner reward may be thought of as altruism toward one's future self. A question that arises in this connection is: What is the relation between delay and social discounting? To begin to answer this question, social and delay discount functions need to be comparable. Delay is ordinarily measured on a ratio scale (time), which allows for meaningful division and addition. Social distance is ordinarily measured on an ordinal scale (rank order of social closeness). To convert social distance to a ratio scale we use a psychophysical distance function obtained via magnitude estimation (Stevens, 1956). The distance functions obtained are well described by a power function (median exponent = 1.9); we show how they may be used to rescale ordinal to ratio social discount functions.

Descriptive Norms and Prototypes Predict COVID-19 Prevention Cognitions and Behaviors in the United States: Applying the Prototype Willingness Model to Pandemic Mitigation.

BACKGROUND: Early in the COVID-19 pandemic, prevention behavior adoption occurred in a rapidly changing context. In contrast to expectancy-value theories, the Prototype Willingness Model (PWM) is well-suited for investigating novel and socially informed behaviors. PURPOSE: We explored whether PWM social cognitions predicted coronavirus prevention behaviors. METHOD: A representative sample of United States adults (N = 738; Mage = 46.8; 51.8% women; 78% white; April 2020) who had not had COVID-19 reported PWM predictor variables (perceived vulnerability, prevention descriptive norms, prototypes engaging in prevention behavior, and prevention behavioral intentions). Two weeks later, participants reported their prevention behaviors (handwashing, mask-wearing, social distancing, etc.) and future public health behavioral willingness (contact tracing, temperature checks, etc.). RESULTS: Controlling for putative demographic, past behavior, and coronavirus-contextual (e.g., local infection rates) covariates, mediation models indicated that higher norms and favorable prototypes were associated with greater prevention behavioral intentions, which in turn predicted increased prevention behavior, F(18, 705) = 92.20, p < .001, R2 = .70. Higher norms and favorable prototypes associated both directly and indirectly (through greater prevention behavioral intention) with greater willingness to engage in emerging public health behaviors, F(15, 715) = 21.49, p < .001, R2 = .31. CONCLUSIONS: Greater descriptive norms and favorable prototypes for prevention behavior predicted: (a) future prevention behaviors through increases in behavioral intentions and (b) willingness to participate in emerging public health behaviors. These results held across demographic groups, political affiliation, and severity of regional outbreaks. Public health efforts to curb pandemics should highlight normative prevention participation and enhance positive prototypes.

How CEOs respond to mortality salience during the COVID-19 pandemic: Integrating terror management theory with regulatory focus theory.

The COVID-19 pandemic has caused hundreds of thousands of deaths in the U.S. As chief strategists of their respective firms, how do Chief Executive Officers (CEOs) react to mortality salience associated with the number of new daily COVID deaths in the U.S.? To answer this question, we integrate terror management theory (TMT) with regulatory focus theory to examine how CEOs respond to mortality salience. Based on a sample of CEOs of S&P 500 firms, we found that mortality salience was associated with CEOs' increased other-orientation, and this association was more pronounced among those with high prevention focus. Mortality salience also was associated with CEOs' decreased self-orientation, particularly among those with high promotion focus. We also found that CEOs' self-orientation was negatively related to the likelihood of their firms' making community donations. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Incentives can spur COVID-19 vaccination uptake.

Recent evidence suggests that vaccination hesitancy is too high in many countries to sustainably contain COVID-19. Using a factorial survey experiment administered to 20,500 online respondents in Germany, we assess the effectiveness of three strategies to increase vaccine uptake, namely, providing freedoms, financial remuneration, and vaccination at local doctors. Our results suggest that all three strategies can increase vaccination uptake on the order of two to three percentage points (PP) overall and five PP among the undecided. The combined effects could be as high as 13 PP for this group. The returns from different strategies vary across age groups, however, with older cohorts more responsive to local access and younger cohorts most responsive to enhanced freedoms for vaccinated citizens.

COVID-19 sentiment analysis via deep learning during the rise of novel cases.

Social scientists and psychologists take interest in understanding how people express emotions and sentiments when dealing with catastrophic events such as natural disasters, political unrest, and terrorism. The COVID-19 pandemic is a catastrophic event that has raised a number of psychological issues such as depression given abrupt social changes and lack of employment. Advancements of deep learning-based language models have been promising for sentiment analysis with data from social networks such as Twitter. Given the situation with COVID-19 pandemic, different countries had different peaks where rise and fall of new cases affected lock-downs which directly affected the economy and employment. During the rise of COVID-19 cases with stricter lock-downs, people have been expressing their sentiments in social media. This can provide a deep understanding of human psychology during catastrophic events. In this paper, we present a framework that employs deep learning-based language models via long short-term memory (LSTM) recurrent neural networks for sentiment analysis during the rise of novel COVID-19 cases in India. The framework features LSTM language model with a global vector embedding and state-of-art BERT language model. We review the sentiments expressed for selective months in 2020 which covers the major peak of novel cases in India. Our framework utilises multi-label sentiment classification where more than one sentiment can be expressed at once. Our results indicate that the majority of the tweets have been positive with high levels of optimism during the rise of the novel COVID-19 cases and the number of tweets significantly lowered towards the peak. We find that the optimistic, annoyed and joking tweets mostly dominate the monthly tweets with much lower portion of negative sentiments. The predictions generally indicate that although the majority have been optimistic, a significant group of population has been annoyed towards the way the pandemic was handled by the authorities.

COVID-19 anti-Asian racism: A tripartite model of collective psychosocial resilience.

Anti-Asian racism has spiked since the outbreak of the coronavirus 2019 (COVID-19) pandemic, creating compounded threats to Asian Americans' psychological wellbeing on top of other pandemic stressors (e.g., fears of infection, financial insecurity, or quarantine isolation). COVID-19 anti-Asian racism signifies the relevance of race and racism during public health crises and highlights the importance of examining the psychological impacts of racialized stress and avenues for resilience during a pandemic. This article describes a conceptual model that emphasizes the importance of rechanneling the experience of COVID-19 anti-Asian racism toward resilience. Specifically, the proposed model identifies a tripartite process of collective psychosocial resilience, comprised of (a) critical consciousness of discrimination as a common fate, (b) critical consciousness-informed racial/ethnic identity, and (c) advocacy, for empowering Asian Americans and protecting them against the harmful effects of COVID-19 anti-Asian racism during and beyond the pandemic. Theoretical and empirical underpinnings of the proposed tripartite process for cultivating resilience against COVID-19 anti-Asian racism are delineated. Practice implications and future research directions, as informed and revealed by the conceptual model, are discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Factors impacting resilience as a result of exposure to COVID-19: The ecological resilience model.

Despite the severe psychological impact of the COVID-19 pandemic, some individuals do not develop high levels of psychological distress and can be termed resilient. Using the ecological resilience model, we examined factors promoting or hindering resilience in the COVID-19 pandemic. Of the 1034 participants (49.9±16.2 years; females 51.2%) from Italian general population, 70% displayed resilient outcomes and 30% reported moderate-severe anxiety and/or depression. A binary regression model revealed that factors promoting resilience were mostly psychological (e.g., trait resilience, conscientiousness) together with social distancing. Conversely, factors hindering resilience included COVID-19-anxiety, COVID-19-related PTSD symptoms, intolerance of uncertainty, loneliness, living with children, higher education, and living in regions where the virus was starting to spread. In conclusion, the ecological resilience model in the COVID-19 pandemic explained 64% of the variance and identified factors promoting or hindering resilient outcomes. Critically, these findings can inform psychological interventions supporting individuals by strengthening factors associated with resilience.

Management of work stress and burnout among community nurses arising from the COVID-19 pandemic.

The COVID-19 pandemic has increased workload demands for many NHS staff including those working in the community. Nurse managers can make a difference by being authentic leaders, nurturing a supportive organisation where the workload is managed participatively and self-kindness is legitimate. Unfortunately some staff may experience burnout and this article presents a personal management plan to address the symptoms of burnout and aid recovery, although it cannot promote a total recovery if the cause of the symptoms remains unaddressed.

Older People's Personal Strengths During the First Wave of the COVID-19 Pandemic.

BACKGROUND: Although several biopsychosocial variables could play an important role as risk and protective factors of mental health, COVID-19 outbreak studies among older people have seldom focused on protective factors. The purpose of this study was to analyze how older adults' personal strengths predict their well-being and emotional distress. METHOD: 783 Spanish people aged 60 and over completed a survey that included sociodemographic characteristics, perceived health, direct or indirect infection by COVID-19, resilience, gratitude, experiential avoidance, family functioning, emotional distress and well-being. Structural Equation Modelling (SEM) was performed. SEM invariance was also used to analyze whether there were differences between older people affected by COVID-19 and those not affected. RESULTS: The best model supports the mediation effect of resilience, gratitude and experiential avoidance on older people's well-being and emotional distress. Whether participants or relatives had been infected by the virus or not did not affect the results. CONCLUSIONS: Variables used as criteria in older adults are related to well-being and emotional distress, but only indirectly and mediated by resilience, gratitude and experiential avoidance. This confirms the importance of considering psychological strengths in older people's well-being. Interventions focused on these personal resources should be considered.

The combined effect of Covid-19 and neighbourhood deprivation on two dimensions of subjective well-being: Empirical evidence from England.

OBJECTIVES: The Covid-19 pandemic is hitting societies hard, and people living in disadvantaged circumstances are among the most affected. We investigate the combined effects of the Covid-19 crisis and living in a deprived neighbourhood on two dimensions of subjective well-being: hedonic (i.e. mental health) and evaluative (i.e. life satisfaction) subjective well-being. METHODS: We use longitudinal data from the Understanding Society UK panel. We combine data gathered in the main survey between 2015 and 2019 with very recent data from the Covid-19 online survey between April and July 2020. Leveraging a sample of nearly 9,600 English individuals, we first run a set of cross-sectional OLS regressions to analyse changes over time in the relationship between neighbourhood deprivation and subjective well-being. Then, as our main model of interest, we use a fixed effect difference-in-differences model to provide more robust evidence. RESULTS: Since the beginning of the crisis, both levels of hedonic and evaluative well-being have decreased as a result of the pandemic and lockdown. However, for those living in more deprived neighbourhoods the level of hedonic well-being decreased more than for those living in better areas. We found no such difference for evaluative well-being. CONCLUSION: Our results highlight the importance of reducing neighbourhood inequalities as the spatial clustering of disadvantages has increased by the pandemic.