ABSTRACT
Developing messaging to encourage minorities to adhere to health recommendations has been a complex task for governments worldwide during the COVID-19 crisis. Here, we propose and tests a new typology of messages among minorities that can be used to mobilize compliance and engagement. This typology comprises three messaging treatments emphasizing personal, ingroup, and intergroup benefits. We examine, via an experimental field study, whether there is a difference in the effect of these messages on two policy outcomes, social distancing and vaccine hesitancy, among the Arab minority living in Israel. The findings suggest that social messages, i.e., ingroup and intergroup messages, positively affect social distancing, while self-messaging harms social distancing compliance. Regarding vaccine intake, within the social messages tested, intergroup-focused messages were more effective than ingroup-focused messages for vaccination intentions only among citizens with low trust in the government. We discuss the findings in detail and propose new avenues in theory and practice to foster health policy compliance among minorities.
ABSTRACT
The coronavirus pandemic has fundamentally shifted the way human beings interact, both as individuals and groups, in the face of such a widespread outbreak. This paper seeks to investigate the effects of COVID-19 on intergroup emotions and attitudes within an intractable intergroup conflict, specifically, through the lens of the Korean conflict. Using a two-wave, cross-sectional design, this study was able to track the profound psychological changes in intergroup emotions and attitudes both prior to the pandemic and during its onslaught. Results of these two wave representative samples show that South Korean citizens demonstrated higher levels of fear of their neighbors in North Korea after the outbreak of COVID-19 than before. In turn, this led to increased societal support of hostile government policies towards North Koreans. Conversely, the same participants exhibited higher levels of empathy towards North Koreans during the pandemic, which led to a higher willingness to collaborate with their outgroup. This dual effect on intergroup emotions within intractable conflicts brings forth new avenues from which societies may be able to restrain the destructive influence of the COVID-19 threat on intergroup relations-as well as harvesting its constructive potential for reconciling warring intergroup relations. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
ABSTRACT
Conspiracy theories widely influence our social and political lives. A recent example is the broad impact such theories had on government's efforts to halt the spread of the COVID-19 pandemic. In that context, public's compliance and willingness to get vaccinated was found to be substantially and negatively affected by the belief in conspiracy theories, among various factors. In the present study, we tested whether some countries are more susceptible to conspiracy theories than others. We examined, for the first time, the idea that the degree of intensity of conflict predicts the degree of belief in COVID-19 conspiracy theories. A multilevel analysis across 66 countries (N = 46,450) demonstrated that people living in countries with higher conflict intensity tended to be more susceptible to COVID-19 conspiracy beliefs. These findings are the first large-scale comparative evidence of the profound psychological effects of conflicts on the involved societies. (PsycInfo Database Record (c) 2022 APA, all rights reserved) Impact Statement The belief in COVID-19 conspiracy theories has severe implications on public's health. Thus, it is important to better understand the reasons behind such beliefs. The present study provides new information which helps to better understand the contexts in which conspiracy belief thrive. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
ABSTRACT
Conspiracy theories widely influence our social and political lives. A recent example is the broad impact such theories had on government's efforts to halt the spread of the COVID-19 pandemic. In that context, public's compliance and willingness to get vaccinated was found to be substantially and negatively affected by the belief in conspiracy theories, among various factors. In the present study, we tested whether some countries are more susceptible to conspiracy theories than others. We examined, for the first time, the idea that the degree of intensity of conflict predicts the degree of belief in COVID-19 conspiracy theories. A multilevel analysis across 66 countries (N = 46,450) demonstrated that people living in countries with higher conflict intensity tended to be more susceptible to COVID-19 conspiracy beliefs. These findings are the first large-scale comparative evidence of the profound psychological effects of conflicts on the involved societies.
ABSTRACT
Most previous studies that examined the effect of anxiety on hostility towards a distinct group have focused on cases in which we hate those we are afraid of. The current study, on the other hand, examines the relationship between anxiety in one domain and hostility towards a distinct group that is not the source of that anxiety. We focus here on symptoms of anxiety during the COVID-19 pandemic, which have become increasingly frequent, and show that the implications of such mental difficulties are far-reaching, posing a threat to relationships between ideological groups. In two studies conducted in both Israel and the United States, we found that high levels of anxiety during the COVID-19 epidemic are associated with higher levels of hatred towards ordinary people from the respective political outgroups, lower levels of willingness to sustain interpersonal relations with these people (i.e., greater social distancing), and greater willingness to socially exclude them. This relationship was mediated by the perception of threat posed by the political outgroup. This study is the first to show that mental difficulty driven by an external threat can be a fundamental factor that explains levels of intergroup hostility.
ABSTRACT
At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.
ABSTRACT
The coronavirus pandemic has fundamentally shifted the way human beings interact, both as individuals and groups, in the face of such a widespread outbreak. This paper seeks to investigate the effects of COVID-19 on intergroup emotions and attitudes within an intractable intergroup conflict, specifically, through the lens of the Korean conflict. Using a two-wave, cross-sectional design, this study was able to track the profound psychological changes in intergroup emotions and attitudes both prior to the pandemic and during its onslaught. Results of these two wave representative samples show that South Korean citizens demonstrated higher levels of fear of their neighbors in North Korea after the outbreak of COVID-19 than before. In turn, this led to increased societal support of hostile government policies towards North Koreans. Conversely, the same participants exhibited higher levels of empathy towards North Koreans during the pandemic, which led to a higher willingness to collaborate with their outgroup. This dual effect on intergroup emotions within intractable conflicts brings forth new avenues from which societies may be able to restrain the destructive influence of the COVID-19 threat on intergroup relations ? as well as harvesting its constructive potential for reconciling warring intergroup relations.
ABSTRACT
Climate change attributable to human activities has created a global threat to humanity and the natural world. However, there is a tendency for people to view climate change as a threat primarily affecting those in far-away places and there is reluctance to engage in pro-environmental action, which is often costly. It is therefore crucial to understand the factors that shape willingness to engage in pro-environmental behavior. Existing research suggests that personal experience with the consequences of climate change may increase pro-environmental action, however it is unknown whether personal experiences in other non-environmental domains may have similar effects. The circumstances of the Covid-19 pandemic allowed us to conduct a quasi-natural experiment to examine the effects of personal experience with a different global threat, namely Covid-19, on environmental responses. Across two studies conducted among UK and US participants, we found that personal experience of Covid-19 was associated with pro-environmental behavioral intentions, and that this relationship was mediated by increased environmental concern. We found that personal experience with Covid-19 was associated with stronger self-transcendence values of universalism and benevolence, which played a further mediating role between personal experience with the virus and environmental concern. These findings suggest that personal experience with at least some global threats, even when not directly related to climate change, may increase concern for distant others and also sensitize people to environmental issues and motivate pro-environmental action.
ABSTRACT
Previous studies have shown that external threats, such as financial crises and natural disasters, might fuel negative attitudes, emotions, and behaviors towards outgroup members. However, it is unclear what types of outgroups are likely to be targeted when an external threat is taking its toll. In this study, we examine two types of outgroups that might be at risk of becoming victims of intergroup hostility. The first is the “ultimate scapegoat” outgroup which has a long history of negative relations with the ingroup. The second is the "context-dependent" outgroup which is viewed as an outgroup only in certain contexts. We utilized the COVID-19 crisis and the highly diverse social makeup of Israeli society to explore the extent to which each type of outgroup would be targeted. Results from our study (N = 664), conducted during the first peak of COVID-19 in Israel, show that higher levels of exposure to COVID-19 predicted lower willingness to aid outgroups and that outgroup dehumanization mediated this association. However, this held true only when the target outgroup was a context-dependent outgroup. When the target group was the ultimate scapegoat, exposure to COVID-19 did not predict ingroup willingness to aid them. Our findings contribute to our theoretical and practical knowledge on how intergroup hostility proliferates during external threats and, as such, are valuable to scholars, practitioners, and policymakers working to reduce intergroup tensions during large-scale crises.
ABSTRACT
Previous studies have shown that external threats, such as financial crises and natural disasters, might fuel negative attitudes, emotions, and behaviors towards outgroup members. However, it is unclear what types of outgroups are likely to be targeted when an external threat is taking its toll. In this study, we examine two types of outgroups that might be at risk of becoming victims of intergroup hostility. The first is the "ultimate scapegoat" outgroup which has a long history of negative relations with the ingroup. The second is the "context-dependent" outgroup which is viewed as an outgroup only in certain contexts. We utilized the COVID-19 crisis and the highly diverse social makeup of Israeli society to explore the extent to which each type of outgroup would be targeted. Results from our study (N = 664), conducted during the first peak of COVID-19 in Israel, show that higher levels of exposure to COVID-19 predicted lower willingness to aid outgroups and that outgroup dehumanization mediated this association. However, this held true only when the target outgroup was a context-dependent outgroup. When the target group was the ultimate scapegoat, exposure to COVID-19 did not predict ingroup willingness to aid them. Our findings contribute to our theoretical and practical knowledge on how intergroup hostility proliferates during external threats and, as such, are valuable to scholars, practitioners, and policymakers working to reduce intergroup tensions during large-scale crises.
ABSTRACT
BACKGROUND: As the SARS-CoV-2 pandemic continues, little guidance is available on clinical indicators for safely discharging patients with severe COVID-19. OBJECTIVE: To describe the clinical courses of adult patients admitted for COVID-19 and identify associations between inpatient clinical features and post-discharge need for acute care. DESIGN: Retrospective chart reviews were performed to record laboratory values, temperature, and oxygen requirements of 99 adult inpatients with COVID-19. Those variables were used to predict emergency department (ED) visit or readmission within 30 days post-discharge. PATIENTS (OR PARTICIPANTS): Age ≥ 18 years, first hospitalization for COVID-19, admitted between March 1 and May 2, 2020, at University of California, Los Angeles (UCLA) Medical Center, managed by an inpatient medicine service. MAIN MEASURES: Ferritin, C-reactive protein, lactate dehydrogenase, D-dimer, procalcitonin, white blood cell count, absolute lymphocyte count, temperature, and oxygen requirement were noted. KEY RESULTS: Of 99 patients, five required ED admission within 30 days, and another five required readmission. Fever within 24 h of discharge, oxygen requirement, and laboratory abnormalities were not associated with need for ED visit or readmission within 30 days of discharge after admission for COVID-19. CONCLUSION: Our data suggest that neither persistent fever, oxygen requirement, nor laboratory marker derangement was associated with need for acute care in the 30-day period after discharge for severe COVID-19. These findings suggest that physicians need not await the normalization of laboratory markers, resolution of fever, or discontinuation of oxygen prior to discharging a stable or improving patient with COVID-19.
Subject(s)
COVID-19 , Adolescent , Adult , Aftercare , Humans , Patient Discharge , Retrospective Studies , SARS-CoV-2ABSTRACT
Worldwide, testing capacity for SARS-CoV-2 is limited and bottlenecks in the scale up of polymerase chain reaction (PCR-based testing exist. Our aim was to develop and evaluate a machine learning algorithm to diagnose COVID-19 in the inpatient setting. The algorithm was based on basic demographic and laboratory features to serve as a screening tool at hospitals where testing is scarce or unavailable. We used retrospectively collected data from the UCLA Health System in Los Angeles, California. We included all emergency room or inpatient cases receiving SARS-CoV-2 PCR testing who also had a set of ancillary laboratory features (n = 1,455) between 1 March 2020 and 24 May 2020. We tested seven machine learning models and used a combination of those models for the final diagnostic classification. In the test set (n = 392), our combined model had an area under the receiver operator curve of 0.91 (95% confidence interval 0.87-0.96). The model achieved a sensitivity of 0.93 (95% CI 0.85-0.98), specificity of 0.64 (95% CI 0.58-0.69). We found that our machine learning algorithm had excellent diagnostic metrics compared to SARS-CoV-2 PCR. This ensemble machine learning algorithm to diagnose COVID-19 has the potential to be used as a screening tool in hospital settings where PCR testing is scarce or unavailable.