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COVID-Related Risk-Taking: Measuring Compliance with Public Health Recommendations
Abstract
Risk-taking behaviors may manifest in multiple ways, including disregarding public health recommendations. In the context of a pandemic, ignoring those recommendations may have devastating consequences for individuals, households, communities, and the healthcare system. Objective: The purpose of this study was to develop and validate a measure of COVID-related risk-taking (CrRT). Methodology: We investigated CrRT in 318 undergraduate students recruited from a Canadian university. With exploratory factor analysis (EFA), we identified a two-factor structure of CrRT: social non-avoidance and personal protection non-compliance, which is consistent with other related studies. Our scale was validated with results from multiple regression analyses showing that younger age, lower risk perception, lower stress, non-planning, and greater risk tolerance significantly predicted public health risk-taking behaviors, also validated by previous work. Results: Results from our study support the CrRT as a valid and reliable measure of pandemic-specific risk-taking. Conclusion: The CrRT may be of use to other researchers and clinicians as this pandemic continues to evolve and new ones occur.
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Introduction
Despite having very high life expectancy, Japan has relatively poor self-rated health, compared to other high-income countries. We studied trends and socioeconomic inequalities in self-rated health in Japan using nationally representative data.
Methods
The Comprehensive Survey of Living Conditions was analyzed, every 3 years (n ≈ 0.6–0.8 million/year) from 1986 to 2016. Whereas previous studies dichotomized self-rated health as an outcome, we used four categories: very good, good, fair, and bad/very bad. Proportional odds ordinal logistic regression models are used, with ordinal scale self-rated health as an outcome, and age category, survey year and occupational class or educational level as independent variables.
Results
In 2016, the age-adjusted percentages for self-rated health categorized as very good, good, fair, and bad/very bad, were 24.0, 17.1, 48.7, and 10.2% among working-age men, and 21.6, 17.5, 49.4, and 11.5% among working-age women, respectively. With 1986 as the reference year, the odds ratios (ORs) of less good self-rated health were lowest in 1995 (0.69; 95% Confidence Interval [95% CI]: 0.66–0.71 of working-age men), and highest in 2010 (1.23 [95% CI: 1.19–1.27]). The ORs of male, lower non-manual workers (compared to upper non-manual) increased from 1.12 (95% CI: 1.07–1.17) in 2010 to 1.20 (95% CI: 1.15–1.26) in 2016. Between 2010 and 2016, the ORs of working-age men with middle and low levels of education (compared to a high level of education) increased from 1.22 (95% CI: 1.18–1.27) to 1.34 (95% CI: 1.29–1.38), and from 1.47 (95% CI: 1.39–1.56) to 1.75 (95% CI: 1.63–1.88), respectively. The ORs of working-age women with middle and low levels of education also increased from 1.22 (95% CI: 1.17–1.28) to 1.32 (95% CI: 1.26–1.37), and from 1.74 (95% CI: 1.61–1.88) to 2.03 (95% CI: 1.87–2.21) during the same period.
Conclusion
Japan has the unique feature that approximately 50% of the survey respondents rated their self-rated health as fair, but with important variations over time and between socioeconomic groups. In-depth studies of the role of socioeconomic conditions may shed light on the reasons for the high prevalence of poor self-rated health in Japan.
We simulated epidemic projections of a potential COVID-19 outbreak in a residential university population in the United States under varying combinations of asymptomatic tests (5% to 33% per day), transmission rates (2.5% to 14%), and contact rates (1 to 25), to identify the contact rate threshold that, if exceeded, would lead to exponential growth in infections. Using this, we extracted contact rate thresholds among non-essential workers, population size thresholds in the absence of vaccines, and vaccine coverage thresholds. We further stream-lined our analyses to transmission rates of 5 to 8%, to correspond to the reported levels of face-mask-use/physical-distancing during the 2020 pandemic. Our results suggest that, in the absence of vaccines, testing alone without reducing population size would not be sufficient to control an outbreak. If the population size is lowered to 34% (or 44%) of the actual population size to maintain contact rates at 4 (or 7) among non-essential workers, mass tests at 25% (or 33%) per day would help control an outbreak. With the availability of vaccines, the campus can be kept at full population provided at least 95% are vaccinated. If vaccines are partially available such that the coverage is lower than 95%, keeping at full population would require asymptomatic testing, either mass tests at 25% per day if vaccine coverage is at 63–79%, or mass tests at 33% per day if vaccine coverage is at 53–68%. If vaccine coverage is below 53%, to control an outbreak, in addition to mass tests at 33% per day, it would also require lowering the population size to 90%, 75%, and 60%, if vaccine coverage is at 38–53%, 23–38%, and below 23%, respectively. Threshold estimates from this study, interpolated over the range of transmission rates, can collectively help inform campus level preparedness plans for adoption of face mask/physical-distancing, testing, remote instructions, and personnel scheduling, during non-availability or partial-availability of vaccines, in the event of SARS-Cov2-type disease outbreaks.
Although the development of vaccines against COVID-19 may mark the
rounding of the corner in the pandemic, several issues are delaying our exit out of it. The
majority of people seem to be concerned about the vaccines and unwilling to take them,
while also not being responsible enough when it comes to the rest of the guidelines. In
this paper, we wanted to examine the levels of support for different official guidelines, as
well as the reasons behind their rejection. In the representative study (N=1198) of Serbian
adults (aged 18+) conducted in September 2020 we found that most people do comply
with guidelines such as hand washing and mask-wearing, but do not want to be vaccinated.
We also found that conspiracy beliefs, trust in science and institutions, and health risk
perception all play an important role in predicting guidelines compliance along with
vaccination intentions. Path analysis confirmed that conspiracy belief indirectly predicts
health guidance compliance, lowering health risk perception and trust in science and
institutions.
Background
The COVID-19 pandemic is adversely impacting modern human civilization. A global view using a systems science approach is necessary to recognize the close interactions between health of animals, humans and the environment.
Discussion
A model is developed initially by describing five sequential or parallel steps on how a RNA virus emerged from animals and became a pandemic: 1. Origins in the animal kingdom; 2. Transmission to domesticated animals; 3. Inter-species transmission to humans; 4. Local epidemics; 5. Global spread towards a pandemic. The next stage identifies global level determinants from the physical environments, the biosphere and social environment that influence these steps to derive a generic conceptual model. It identifies that future pandemics are likely to emerge from ecological processes (climate change, loss of biodiversity), anthropogenic social processes (i.e. corporate interests, culture and globalization) and world population growth. Intervention would therefore require modifications or dampening these generators and prevent future periodic pandemics that would reverse human development.
Addressing issues such as poorly planned urbanization, climate change and deforestation coincide with SDGs such as sustainable cities and communities (Goal 11), climate action (Goal 13) and preserving forests and other ecosystems (Goal 15). This will be an added justification to address them as global priorities. Some determinants in the model are poorly addressed by SDGs such as the case of population pressures, cultural factors, corporate interests and globalization. The overarching process of globalization will require modifications to the structures, processes and mechanisms of global governance. The defects in global governance are arguably due to historical reasons and the neo-liberal capitalist order. This became evident especially in the aftermath of the COVID-19 when the vaccination roll-out led to violations of universal values of equity and right to life by some of the powerful and affluent nations.
Summary
A systems approach leads us to a model that shows the need to tackle several factors, some of which are not adequately addressed by SDGs and require restructuring of global governance and political economy.
Attachment insecurity, emotional dysregulation, and attention-deficit/hyperactivity disorder (ADHD) have all been implicated across the literature with various forms of negative life outcomes and increased risk-taking behavior (RTB). Furthermore, abundant research has demonstrated that the three seem to go together. Given these intercorrelations, it is unclear if any of them possess exclusive links with RTB independent of the others across multiple life domains. The present study examined the relations among attachment styles, emotional dysregulation, ADHD symptoms, and hypothetical RTBs across multiple real-life domains. Including a total of 155 mostly undergraduate students, we found in the main analysis that only ADHD symptoms were associated with RTB over and above all other variables. Specifically, the links between both attachment insecurity and emotional dysregulation with RTB disappeared when ADHD symptoms were included in the final model, but not vice versa. An exploratory analysis suggested that attachment insecurity was linked to romantic/sexual RTB over and above the others. These results further substantiate the link between ADHD symptoms and a general propensity for RTB and demonstrate that the link between the two seems to be inherent to the disorder and independent of its co-occurrence with attachment insecurity and emotional dysregulation.
Risk perception is important in determining health-protective behavior. During the rise of the COVID-19 epidemic, we tested a comprehensive structural equation model of risk perception to explain adherence to protective behaviors in a crisis context using a survey of 572 Italian citizens. We identified two categories of protective behaviors, labeled promoting hygiene and cleaning, and avoiding social closeness. Social norms and risk perceptions were the more proximal antecedents of both categories. Cultural worldviews, affect, and experience of COVID-19 were the more distal predictors. Promoting hygiene and cleaning was triggered by the negative affective attitude toward coronavirus and mediated by an affective appraisal of risk. The deliberate dimension of risk perception (perceived likelihood) predicted only avoiding social closeness. Social norms predicted both types of behaviors and mediated the relations of cultural worldviews. Individualism (vs. communitarianism), more than hierarchy (vs. egalitarianism), shaped the affective evaluation of coronavirus. The model was an acceptable fit to the data and accounted for 20% and 29% of the variance in promoting hygiene and cleaning, and avoiding social closeness, respectively. The findings were robust to the effect of sociodemographic factors (age, gender, education, socioeconomic status, and zone of the country). Taken together, our findings confirmed the empirical distinction between affective and deliberate processes in risk perception, supported the validity of the affect heuristic, and highlighted the role of social norms as an account for why individualistic people were less likely to follow the prescribed health-protective behaviors. Implications for risk communication are discussed.
In order to limit the disease burden and economic costs associated with the COVID-19 pandemic, it is important to understand how effective and widely distributed a vaccine must be in order to have a beneficial impact on public health. To evaluate the potential effect of a vaccine, we developed risk equations for the daily risk of COVID-19 infection both currently and after a vaccine becomes available. Our risk equations account for the basic transmission probability of COVID-19 (β) and the lowered risk due to various protection options: physical distancing; face coverings such as masks, goggles, face shields or other medical equipment; handwashing; and vaccination. We found that the outcome depends significantly on the degree of vaccine uptake: if uptake is higher than 80%, then the daily risk can be cut by 50% or more. However, if less than 40% of people get vaccinated and other protection options are abandoned—as may well happen in the wake of a COVID-19 vaccine—then introducing even an excellent vaccine will produce a worse outcome than our current situation. It is thus critical that effective education strategies are employed in tandem with vaccine rollout.
Background:
Adherence to public health instructions for the COVID-19 is important for controlling the transmission and the pandemic's health and economic impacts. The aim of this study was to determine the associated factors of non-adherence to public health and social measures instructions.
Methods:
This was a cross-sectional study conducted with 1913 participants in two provinces of DRC, Mbuji-Mayi, and Kamina. Predictors of non-adherence to COVID-19 preventive measures were identified using binary logistic regression analysis. P-value<0.05 was considered as a significant predictor.
Results:
Among 1913 participants (1057 [55.3%] male, age 34.1 [14.9] years), 36.6% were defined as non-adherents. Non-adherence was associated with never studied and primary education level [adjusted odds ratio (aOR)=1.63, CI=1.31-2.03], unemployed status [aOR=1.29, CI=1.01-1.67], living in Kamina (Haut-Lomami province) [aOR=1.63, CI=1.31-2.03], female gender of head of household [aOR=1.53, CI=1.16-2.03], no attending lectures/discussions about COVID-19 [aOR=1.61, CI=1.08-2.40], not being satisfied with the measures taken by the Ministry of Health [aOR=2.26, CI=1.78-2.81], not been regularly informed about the pandemic [aOR=2.25, CI=1.80-2.03], and bad knowledge about COVID-19 [aOR=2.36, CI=1.90-2.93].
Conclusion:
The rate of non-observance of preventive measures for the COVID-19 pandemic is high, and different factors contributed. The government has to counsel the permanent updating of messages taking into account the context and the progress of the pandemic by using several communication channels.
With the emergence of the novel SARS-CoV-2 and the disease it causes; COVID-19, compliance with/adherence to protective measures is needed. Information is needed on which measures are, or are not, being undertaken. Data collected from the COVID Impact Survey, conducted by the non-partisan and objective research organization NORC at the University of Chicago on April, May, and June of 2020, were analyzed through weighted Quasi-Poisson regression modeling to determine the association of demographics, socioeconomics, and health conditions with protective health measures taken at the individual level in response to COVID-19. The three surveys included data from 18 regional areas including 10 states (CA, CO, FL, LA, MN, MO, MT, NY, OR, and TX) and 8 Metropolitan Statistical Areas (Atlanta, GA; Baltimore, MD; Birmingham, AL; Chicago, IL; Cleveland and Columbus, OH; Phoenix, AZ; and Pittsburgh, PA). Individuals with higher incomes, insurance, higher education levels, large household size, age 60+, females, minorities, those who have asthma, have hypertension, overweight or obese, and those who suffer from mental health issues during the pandemic were significantly more likely to report taking precautionary protective measures relative to their counterparts. Protective measures for the three subgroups with a known relationship to COVID-19 (positive for COVID-19, knowing an individual with COVID-19, and knowing someone who had died from COVID-19) were strongly associated with the protective health measures of washing hands, avoiding public places, and canceling social engagements. This study provides first baseline data on the response to the national COVID-19 pandemic at the individual level in the US. The found heterogeneity in the response to this pandemic by different variables can inform future research and interventions to reduce exposure to the novel SARS-CoV-2 virus.
Social distancing during the coronavirus-disease-2019 (COVID-19) pandemic is crucial to reduce the spread of the virus. However, its effectiveness hinges on adherence by individuals who face substantial burdens from the required behavioral restrictions. Here, we investigate sources of individual variation in adhering to social distancing guidelines. In a high-powered study (N = 895), we tested direct and indirect effects of boredom and self-control on adherence. The results showed that both traits were important predictors of adherence but the underlying mechanisms differed. Specifically, individuals high in boredom perceived social distancing as more difficult, which in turn reduced their adherence (i.e., a mediated effect). In contrast, individuals high in self-control adhered more to the guidelines without perceiving them as more or less difficult; however, self-control moderated the effect of difficulty on adherence. Our results are immediately relevant to improve the efficacy of social distancing guidelines in the COVID-19 response.
Effective management of the global pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (also known as COVID-19), resulted in the implementation of severe restrictions in movement and enforcement of social distancing measures. This study aimed to understand and characterize the psychosocial effects of the COVID-19 pandemic in the general population and to identify risks and protective factors that predict changes in mental health status. In addition, the study investigated compliance with precautionary measures (PM) to halt the spread of the virus. The online anonymous survey collected information on sociodemographic data, compliance with PM, quality of life (QOL), and mental health via the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9). A total of 1642 adult participants (71.6% women, 28.4% men) completed the survey in the European island country, Cyprus. A large percentage (48%) reported significant financial concerns and 66.7% significant changes in their QOL. About 41% reported symptoms associated with mild anxiety; 23.1% reported moderate-severe anxiety symptoms. Concerning depression, 48% reported mild and 9.2% moderate-severe depression symptoms. Women, younger age (18-29), student status, unemployment status, prior psychiatric history, and those reporting greater negative impact on their QOL, were at higher risk for increased anxiety and depression symptoms (p < 0.05). The youngest age group and males also reported lower levels of compliance with PM. Higher compliance with PM predicted lower depression scores (p < 0.001) but higher anxiety for measures related to personal hygiene. The results of this study provide important data on the effects of the COVID-19 outbreak on mental health and QOL and identify a variety of personal and social determinants that serve as risks and protective factors. Furthermore, it has implications for policy makers demonstrating the need for effective mental health programs and guidance for the implementation of PM as a public health strategy.
To investigate whether socioeconomic status is associated with the self-rated health (SRH) status among Chinese.A cross sectional study including a national sample was conducted among Chinese adults in 2008. In total, 3225 participants were selected by a multistage cluster sampling method. Both general self-rated health and time-comparative self-rated health were measured by a standardized questionnaire. Logistic regression models were used to estimate the odds ratios (ORs) (95% confidence intervals, CIs) of occupation with SRH by occupation, and adjusted for age, sex, education, area, marriage, smoking, drinking, and health status.Overall, 34.4% of study participants reported "good" on the general SRH (male: 35.8%; female: 32.9%) and 26.2% reported "good" on the time-comparative SRH (male: 27.2%; female: 25.3%). The prevalence of "good" general SRH varied from 28.8% to 52.8% and the prevalence of time-comparative SHR varied from 21.7% to 33.9% in different occupations. The adjusted OR (Odd Ratio) for "good" on the general SRH was 1.35 (95% CI: 1.20-1.52) for the occupation of civil servants, 2.23 (95% CI: 1.96-2.54) for farmers, and 1.15 (95%CI: 1.01-1.31) for businessmen. The full adjusted OR of "good" on the time-comparative SRH was 1.36 (95% CI: 1.17-1.58) for students and was 1.25 (95% CI: 1.10-1.42) for civil servants.In presented study, 34.4% of the participants reported "good" on the general SRH, and 26.2% participants reported "good" on the time-comparative SRH. The prevalence of "good" general SRH and "good" time-comparative SRH varied among occupations.
Scale development and validation are critical to much of the work in the health, social, and behavioral sciences. However, the constellation of techniques required for scale development and evaluation can be onerous, jargon-filled, unfamiliar, and resource-intensive. Further, it is often not a part of graduate training. Therefore, our goal was to concisely review the process of scale development in as straightforward a manner as possible, both to facilitate the development of new, valid, and reliable scales, and to help improve existing ones. To do this, we have created a primer for best practices for scale development in measuring complex phenomena. This is not a systematic review, but rather the amalgamation of technical literature and lessons learned from our experiences spent creating or adapting a number of scales over the past several decades. We identified three phases that span nine steps. In the first phase, items are generated and the validity of their content is assessed. In the second phase, the scale is constructed. Steps in scale construction include pre-testing the questions, administering the survey, reducing the number of items, and understanding how many factors the scale captures. In the third phase, scale evaluation, the number of dimensions is tested, reliability is tested, and validity is assessed. We have also added examples of best practices to each step. In sum, this primer will equip both scientists and practitioners to understand the ontology and methodology of scale development and validation, thereby facilitating the advancement of our understanding of a range of health, social, and behavioral outcomes.
Exploratory factor analysis (EFA) is a multivariate statistical method that has become a fundamental tool in the development and validation of psychological theories and measurements. However, researchers must make several thoughtful and evidence-based methodological decisions while conducting an EFA, and there are a number of options available at each decision point, some better than others. Reviews of the professional literature have consistently found that many applications of EFA are marked by an injudicious choice of methods and incomplete reports. This article provides a systematic, evidence-based guide to the conduct of EFA studies that can be followed by researchers with modest statistical training, supplemented with an example to illustrate its application.
Not getting vaccinated or not backing up computer files are examples of passive risk taking: risk brought on or magnified by inaction. We suggest the difficulty in paying attention to absences, together with the reduced agency and responsibility that is associated with passive choices, leads to the perception of passive risks as being less risky than equivalent active risks. Using scenarios in which risk was taken either actively or passively, we demonstrate that passive risks are judged as less risky than equivalent active risks. We find the perception of personal responsibility mediates the differences between the perception of passive and active risks. The current research offers an additional explanation for omission or default biases: The passive nature of these choices causes them to appear less risky than they really are.
Background
Self-rated health (SRH), a subjective assessment of health status, is extensively used in the public health field. However, whether SRH can reflect the objective health status is still debatable. We aim to reveal the relationship between SRH and objective health status in the general population.
Methods
We assessed the relationship between SRH and objective health status by examining the prevalence of diseases, laboratory parameters, and some health-related factors in different SRH groups. Data were collected from 18,000 residents randomly sampled from the general population in five cities of China (3,600 in each city). SRH was assessed by a single-item health measure with five options: “very good,” “good,” “fair,” “bad,” and “very bad.” The differences in prevalence of diseases, laboratory parameters, and health-related factors between the “healthy” (very good plus good), “relatively healthy” (fair), and “unhealthy” (bad plus very bad) groups were examined. The odds ratios (ORs) referenced by the healthy group were calculated using logistic regression analysis.
Results
The prevalence of all diseases was associated with poorer SRH. The tendency was more prominent in cardio-cerebral vascular diseases, visual impairment, and mental illnesses with larger ORs. Residents with abnormalities in laboratory parameters tended to have poorer SRH, with ORs ranging from 1.62 (for triglyceride) to 3.48 (for hemoglobin among men) in a comparison of the unhealthy and healthy groups. Most of the health-related factors regarded as risks were associated with poorer SRH. Among them, life and work pressure, poor spiritual status, and poor quality of interpersonal relationships were the most significant factors.
Conclusions
SRH is consistent with objective health status and can serve as a global measure of health status in the general population.
The Barratt Impulsiveness Scale is one of the most commonly used scales to measure impulsivity. It has demonstrated validity in several neuropsychiatric populations and correlates with objective neuropsychological measures and impulsivity-related behaviors in healthy individuals. Neuroimaging studies show that BIS scores relate to prefrontal structure and function, as well as central serotonergic function. This study reports normative data and demographic influences in a community sample (n = 700). A 15-item short form of the BIS (BIS 15) is presented that retains the 3-factor structure (nonplanning, motor impulsivity, and attention impulsivity), and maintained good reliability and validity.
Risk perceptions are central to many health behavior theories. However, the relationship between risk perceptions and behavior, muddied by instances of inappropriate assessment and analysis, often looks weak.
A meta-analysis of eligible studies assessing the bivariate association between adult vaccination and perceived likelihood, susceptibility, or severity was conducted.
Thirty-four studies met inclusion criteria (N = 15,988). Risk likelihood (pooled r = .26), susceptibility (pooled r = .24), and severity (pooled r = .16) significantly predicted vaccination behavior. The risk perception-behavior relationship was larger for studies that were prospective, had higher quality risk measures, or had unskewed risk or behavior measures.
The consistent relationships between risk perceptions and behavior, larger than suggested by prior meta-analyses, suggest that risk perceptions are rightly placed as core concepts in theories of health behavior.
The purpose of the present study was to revise the Barratt Impulsiveness Scale Version 10 (BIS-10), identify the factor structure of the items among normals, and compare their scores on the revised form (BIS-11) with psychiatric inpatients and prison inmates. The scale was administered to 412 college undergraduates, 248 psychiatric inpatients, and 73 male prison inmates. Exploratory principal components analysis of the items identified six primary factors and three second-order factors. The three second-order factors were labeled Attentional Impulsiveness, Motor Impulsiveness, and Nonplanning Impulsiveness. Two of the three second-order factors identified in the BIS-11 were consistent with those proposed by Barratt (1985), but no cognitive impulsiveness component was identified per se. The results of the present study suggest that the total score of the BIS-11 is an internally consistent measure of impulsiveness and has potential clinical utility for measuring impulsiveness among selected patient and inmate populations.
The effort to limit the spread of the coronavirus (COVID‐19) has relied heavily on the general public's compliance with health guidelines limiting social contact and mitigating risk when contact occurs. The aim of this study was to identify latent variables underlying adherence to COVID‐19 guidelines and to examine demographic and psychological predictors of adherence. A sample of US adults (N = 1,200) were surveyed in late April to mid‐May 2020. The factor structure of adherence was examined using exploratory factor analysis. Machine learning regression models using elastic net regularization were used to examine predictors of adherence. Two factors characterized adherence: avoidance and cleaning. Elastic net models identified differential demographic and psychological predictors of these two forms of adherence. Religious affiliation, denial coping, full‐time employment, substance use coping, and being 60 or older predicted lower avoidance adherence. Behavioral and mindfulness emotion regulation skills, agreeableness, and Democrat political affiliation predicted greater avoidance adherence. For cleaning adherence, interpersonal and behavioral emotion regulation skills and conscientiousness emerged as strong predictors of greater cleaning. Efforts to promote compliance with COVID‐19 health guidelines may benefit from distinguishing avoidance and cleaning adherence and considering predictors of each of these aspects of adherence.
Objective: This study outlines the construction and initial psychometric properties of the Coronavirus Impact Scale in multiple large and diverse samples of families with children and adolescents. The scale was established to capture the impact of the coronavirus pandemic. Differences in impact between samples and internal structure within samples were assessed.Method: Five hundred, seventy-two caregivers of children and adolescents or expecting mothers in diverse clinical and research settings completed the Coronavirus Impact Scale. Samples differed in developmental stage, background, inpatient/outpatient status, and primary research or clinical setting. Model free methods were used to measure the scale’s internal structure and determine a scoring method. Differences between samples in specific item responses were measured by multivariate ordinal regression.Results: The Coronavirus Impact Scale demonstrated good internal consistency in a variety of clinical and research populations. Single, immigrant, predominantly Latinx mothers of young children reported the greatest impact across groups, with elevated impact on food access and finances. Individuals receiving outpatient or inpatient care reported greater impacts on health care access. Impact was positively associated with measures of caregiver anxiety and both caregiver- and child-reported stress at a moderate effect size.Conclusion: The Coronavirus Impact Scale is a publicly available scale with adequate psychometric properties for use in measuring the impact of the coronavirus pandemic in diverse populations.
Objectives:
This study was conducted to develop and evaluate a theoretical model to explain the relationships among participation in individual and social activities, compliance with prevention guidelines, and the perception of fatalism and fear of COVID-19.
Methods:
Cross-sectional survey of 1,067 participants who were >18 years of age living in different provinces of Turkey recruited between August 15, 2020 and October 15, 2020. We used covariant structural analysis to assess the relationships of the constructs of the theoretical model.
Results:
Significant fits were detected for Model 1 (χ2 = 924,389, p < .001, comparative fit index or CFI = 0.944), and for Model 2 (χ2 = 2,253,751, p < .001, CFI = 0.926). The predetermination and luck subdimensions reduce the fear of COVID-19, while the pessimism subdimension and compliance with preventive measures increase the fear.
Conclusion:
In public health crises such as COVID-19, it is important to plan scientific knowledge-based public education; take initiatives in accordance with the cultural, social, economic, religious, and local characteristics of the societies; and conduct public health studies covering the whole society.
Objectives:
This article examines patterns of self-rated physical and mental health by sexual orientation among middle-aged and older adults in Canada, a rapidly growing subpopulation shown to be at risk of poor health.
Method:
We use the Canadian Community Health Survey (CCHS 2015-16) to estimate logit models predicting fair/poor self-rated physical and mental health by sexual orientation among middle-aged and older adults, stratifying by sex and age group.
Results:
We find no differences in physical health for gay men and lesbian women compared to their heterosexual counterparts. However, middle-aged gay men are disadvantaged in terms of mental health, but not women. Bisexual women are disadvantaged in terms of physical health, and for mental health in some model specifications. Respondents who did not know their sexual orientation have poorer health across some measures of health and age groups.
Discussion:
Our findings add to the paucity of research on older sexual minorities in Canada. They highlight the importance of separating out sexual minority groups since bisexual women have distinct health profiles. In addition, this is the first study to examine the health of respondents who "don't know" their sexual orientation, and future research should distinguish between different explanations for their poor health.
Objective:
Researchers often perform arbitrary outcome transformations to fulfil the normality assumption of a linear regression model. This manuscript explains and illustrates that in large data settings, such transformations are often unnecessary, and worse, may bias model estimates.
Design:
Linear regression assumptions are illustrated using simulated data and an empirical example on the relation between time since type 2 diabetes diagnosis and glycated haemoglobin (HbA1c). Simulation results were evaluated on coverage; e.g., the number of times the 95% confidence interval included the true slope coefficient.
Results:
While outcome transformations bias point estimates, violations of the normality assumption in linear regression analyses do not. Instead this normality assumption is necessary to unbiasedly estimate standard errors, and hence confidence intervals and p-values. However, in large sample sizes (e.g., where the number of observations per variable is larger than 10) violations of this normality assumption do not noticeably impact results. Contrary to this, assumptions on, the parametric model, absence of extreme observations, homoscedasticity and independency of the errors, remain influential even in large sample size settings.
Conclusions:
Given that modern healthcare research typically includes thousands of subjects focussing on the normality assumption is often unnecessary, does not guarantee valid results, and worse more may bias estimates due to the practice of outcome transformations.
The following paper discusses exploratory factor analysis and gives an overview of the statistical technique and how it is used in various research designs and applications. A basic outline of how the technique works and its criteria, including its main assumptions are discussed as well as when it should be used. Mathematical theories are explored to enlighten students on how exploratory factor analysis works, an example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided. This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output.
We provide a free noncommercial SPSS program that implements procedures for (a) obtaining the polychoric correlation matrix between a set of ordered categorical measures, so that it can be used as input for the SPSS factor analysis (FA) program; (b) testing the null hypothesis of zero population correlation for each element of the matrix by using appropriate simulation procedures; (c) obtaining valid and accurate confidence intervals via bootstrap resampling for those correlations found to be significant; and (d) performing, if necessary, a smoothing procedure that makes the matrix amenable to any FA estimation procedure. For the main purpose (a), the program uses a robust unified procedure that allows four different types of estimates to be obtained at the user's choice. Overall, we hope the program will be a very useful tool for the applied researcher, not only because it provides an appropriate input matrix for FA, but also because it allows the researcher to carefully check the appropriateness of the matrix for this purpose. The SPSS syntax, a short manual, and data files related to this article are available as Supplemental materials that are available for download with this article.
Objectives:
We investigated the underlying mechanisms of the influence of socioeconomic status (SES) on mental health and self-rated health (SRH), and evaluated how these relationships might vary by race/ethnicity, age, and gender.
Methods:
We analyzed data of 44 921 adults who responded to the 2009 California Health Interview Survey. We used a path analysis to test effects of SES, neighborhood safety, and physical activity on mental health and SRH.
Results:
Low SES was associated with greater neighborhood safety concerns, which were negatively associated with physical activity, which was then negatively related to mental health and SRH. This model was similar across different racial/ethnic and gender groups, but mean levels in the constructs differed across groups.
Conclusions:
SES plays an important role in SRH and mental health, and this effect is further nuanced by race/ethnicity and gender. Identifying the psychological (neighborhood safety) and behavioral (physical activity) factors that influence mental health and SRH is critical for tailoring interventions and designing programs that can improve overall health.
The current paper reviews four research perspectives that have been used to investigate the development of risk-taking. Cognitive developmental research has investigated the development of decision-making capacities that potentially underlie risk-taking development, including sensitivity to risk, probability estimation, and perceptions of vulnerability. Emotional development research has found that affective decision-making and emotional regulation skills improve with development through adolescence. Psychobiological research has analyzed the cognitive and affective neurological and biochemical bases of risk-taking, and their development. Social developmental research has explored the effects of parent–child relationship quality, parenting strategies, and peer influences on the emergence of risk-taking tendencies. Although they have remained largely independent, it is argued throughout that factors within each of these perspectives interact to influence the probability that an individual will engage in risky activities, which should be the topic of future research.
Contenido: Introducción. Una guía para técnicas estadísticas. Revisión de estadísticas univariadas y bivariadas. Limpiando el terreno: despliegue de los datos previo al análisis. Regresión múltiple. frecuencias multidireccional. Análisis de covarianza. Análisis multivariado de varianza y covarianza. Análisis de perfiles de medidas repetidas. Análisis de función discriminante. Regresión logística. Análisis factorial y de componentes principales. Modelado de ecuación estructural. Una revisión del modelo general lineal.
Modern theories in cognitive psychology and neuroscience indicate that there are two fundamental ways in which human beings comprehend risk. The "analytic system" uses algorithms and normative rules, such as probability calculus, formal logic, and risk assessment. It is relatively slow, effortful, and requires conscious control. The "experiential system" is intuitive, fast, mostly automatic, and not very accessible to conscious awareness. The experiential system enabled human beings to survive during their long period of evolution and remains today the most natural and most common way to respond to risk. It relies on images and associations, linked by experience to emotion and affect (a feeling that something is good or bad). This system represents risk as a feeling that tells us whether it is safe to walk down this dark street or drink this strange-smelling water. Proponents of formal risk analysis tend to view affective responses to risk as irrational. Current wisdom disputes this view. The rational and the experiential systems operate in parallel and each seems to depend on the other for guidance. Studies have demonstrated that analytic reasoning cannot be effective unless it is guided by emotion and affect. Rational decision making requires proper integration of both modes of thought. Both systems have their advantages, biases, and limitations. Now that we are beginning to understand the complex interplay between emotion and reason that is essential to rational behavior, the challenge before us is to think creatively about what this means for managing risk. On the one hand, how do we apply reason to temper the strong emotions engendered by some risk events? On the other hand, how do we infuse needed "doses of feeling" into circumstances where lack of experience may otherwise leave us too "coldly rational"? This article addresses these important questions.
Volatile' Crowd of 8,000 Students Gather for Unsanctioned Queen's Homecoming
- Zoe Demarco
Demarco, Zoe. 2021. "'Volatile' Crowd of 8,000 Students Gather for Unsanctioned Queen's
Homecoming." Daily Hive News, October 16, 2021. https://dailyhive.com/vancouver
/8000-students-gather-queens-university-homecoming.
Rowdy Unsanctioned Acadia University Homecoming Parties Net Numerous Charges
- Rebecca Lau
Lau, Rebecca. 2021. "Rowdy Unsanctioned Acadia University Homecoming Parties Net
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Reckless and Destructive': Ontario University Responds to Gathering of Nearly 5,000 People
- Abby Neufeld
Neufeld, Abby. 2021. " 'Reckless and Destructive': Ontario University Responds to Gathering
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https://toronto.ctvnews.ca/reckless-and-destructive-ontario-university-responds-togathering-of-nearly-5-000-people-1.5609245.