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87 results for “Risk perceptions”
A comparative dataset on public perceptions of multiple risks during the COVID-19 pandemic in Italy and Sweden
<p>These datasets are the result of two nation-wide surveys conducted in Italy and Sweden in August 2020 and in november 2020. The surveys (which are identical in the two rounds) explore the respondents' risk perception, preparedness, knowledge, and experience regarding a set of hazards, namely: epidemics, floods, droughts, earthquakes, wildfires, terror attacks, domestic violence, economic crises, and climate change. </p> <p>The data files include the questionnaire survey (the Italian and Swedish versions as well as the English translation) and the two datasets of all the answers to the two surveys. Each column in the dataset refers to an item in the survey (e.g. a question or a sub-question), and each row represents a single respondent. </p> <p>For additional information on the August 2020 dataset, see <a href="https://www.nature.com/articles/s41597-020-00778-7">Mondino et al. (2020)</a>.</p>
Monitoring knowledge, risk perceptions, preventive behaviours and trust to inform pandemic outbreak response.
<p>The study is part of the large project promoted by WHO Regional Office for Europe called “<em>Monitoring knowledge, risk perceptions, preventive behaviours and trust to inform pandemic outbreak response</em>” and carried out in over 30 countries of the WHO European Region (Registered ISRCTN on 11/05/2021, ID: ISRCTN26200758). In Italy, the survey was conducted administering an online questionnaire developed <em>ad hoc</em> by the WHO in four waves (January-May 2021) to a sample of 10.000 individuals aged 18-70 years. A detailed sampling plan was developed to obtain a representative sample of the Italian adult population. The following variables were taken into account for stratification of the participants: gender by age (four age groups: 18-34 years, 35-44 years, 45-54 years, 55-70 years); geographical area (four areas: North West, North East, Centre, South and Islands); size of living centers (two classes: above and below 100,000 inhabitants); level of education (up to lower middle school, beyond lower middle school); and employment situation (employed, not employed). At the end of each survey’s wave, a weighting procedure has been applied to accurately restore the proportionality of the total sample examined with the reference population, according to the most recent data of the Italian Statistics Institute (ISTAT, 12/31/2019). In particular, data have been weighted for the main socio-demographic and geographic variables (e.g., sex by age by geographical area, occupation, educational qualification, geographical area by size of living centers). The sample size made it possible to maintain a sampling error of less than 2% (at the significance level of 95%) and to control the error of estimates within groups or subgroups of interest. The interviews were conducted by Doxa S.p.a. and carried out with the CAWI technique (Computer Assisted Web Interviewing) on an online panel and on the Confirmit software platform used by Doxa S.p.a. The average administration time was about 18-20 minutes. This study was approved by the Ethics Committee of the IRCCS San John of God Fatebenefratelli of Brescia (n° 72-2020), and all participants provided written informed consent.</p> <p>The primary objectives are to:</p> <p>● Monitor variables that are critical for population behaviour to control transmission of the novel coronavirus, including risk perceptions, knowledge, self-efficacy, confidence in institutions, behaviours, rumours, affect, worry, resilience, trust in/use of information sources and more.<br> ● Document changes over time in these factors to understand the effect of the pandemic process, new developments, events or measures taken.<br> ● Monitor possible issues, e.g. related to misinformation or distrust, as they emerge, to allow early response.<br> ● Identify relationships between variables to identify levers for effective and appropriate responses.<br> ● Explore the relationship of psychological variables (e.g. worry, resilience, trust, affect) with the epidemiological situation and the events and measures taken.<br> ● Identify gaps between perceived and actual knowledge.<br> ● Evaluate the effectiveness of pandemic response measures, and the acceptance and effectiveness of policies and restrictions implemented, including the easing of such restrictions.<br> The secondary objectives are to:<br> ● Contribute to post-outbreak evaluation, thereby contributing to the continued regional/global efforts to better understand mechanisms of crisis response.<br> ● If additional research capacity is available, the data can be triangulated with data on media reporting, COVID-19 cases and other.● If additional research capacity is available, the data can be triangulated with data on media reporting, imported or confirmed cases, etc.: The relationship between psychological variables and characteristics of the outbreak situation can be explored (i.e. how closely the perceived risk mirrors reported cases, relative import risk, media reports).<br> This approach allows a citizen-centred approach where insights into population perceptions and behaviours inform COVID-19 actions, alongside epidemiological data and considerations of economic, cultural, ethical, structural political nature and other.</p> <p>The WHO questionnaire includes 21 different thematic areas noteworthy for the investigation of COVID-19 experience. The questionnaire was translated into specific country language by each recruiting site, following the WHO’s guidelines for translations of tools into other languages. The process included the following steps: forward translation, panel experts, back-translation, pre-test and cognitive interviews and, finally, development of the final version. Variables being surveyed include the following:<br> • Socio-demography;<br> • COVID-19 personal experience;<br> • Health literacy;<br> • COVID-19 risk perception;<br> • Probability and Severity;<br> • Preparedness and Perceived self-efficacy;<br> • Prevention – own behaviours;<br> • Affect;<br> • Trust in sources of information;<br> • Use of sources of information;<br> • Frequency of Information;<br> • Trust in institutions (perceptions);<br> • Policies, interventions (perceptions);<br> • Conspiracies (perceptions);<br> • Resilience (perceptions);<br> • Testing and tracing;<br> • Fairness (perceptions);<br> • Lifting restrictions (pandemic transition phase);<br> • Unwanted behaviour;<br> • Wellbeing;<br> • COVID-19 vaccine.</p> <p> </p>
Risk-perception, attitudes and behavioural intentions to spend on experiences in the post-Corona crisis: data from Italy, Denmark, China and Japan
<p>A cross-sectional survey conducted in Japan (n=1,111), Denmark (n=1,028), China (n=1,019) and Italy (n=1,014) during 10-24th of July 2020.</p> <p>Data format: sav (SPSS) and csv.</p>
Dataset: Cross-Sectional National Survey on Risk Perception and Tourism Behaviour (SNF NRP 78)
<p>The data set contains scales (<em>rating items</em>) on the willingness of the Swiss resident population to take risks in connection with touristic travel during the coronavirus pandemic. The data includes a selection of items of the <em>Domain-Specific Risk-Taking Scale</em> (<em>DOSPERT) </em>(Weber et al., 2002). The data contains measures of the <em>health belief model</em> (<em>HBM</em>; Rosenstock, 1960, see also Champion & Skinner, 2008) that is used both in health research and in tourism research to explain and predict the preventive health behaviour of individuals. Furthermore, the data covers all three elements of the t<em>heory of planned behaviour (</em>Ajzen, 1991). This is a representative data set for the Swiss population aged 18 and above. A trilingual and national survey of the Swiss resident population was carried out in the period from March to May 2021. A letter of invitation to participate in the study was sent by post to a total of 4,530 randomly selected persons residing in Switzerland. The address data was provided by the Federal Statistical Office (BfS). Of the total of 4,530 people contacted, 164 were reported as unreachable (no longer at the address, deceased, or due to old age). A total of 1,683 persons participated in the survey. This corresponds to a response rate of 39%. The structure of the respondents corresponds to that of the Swiss resident population 18 years of age and older with regard to gender, age, and language region.</p> <p>Ajzen, I. (1991). The theory of planned behavior. <em>Organizational Behavior and Human Decision Processes</em>, <em>50</em>(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T</p> <p>Weber, E., Blais, A.-R., & Betz, N. E. (2002). A domain-specific risk-attitude scale: Measuring risk perceptions and risk behaviors. <em>Journal of Behavioral Decision Making</em>, <em>15</em>, 263–290. https://doi.org/10.1002/bdm.414</p> <p>Champion, V. L., & Skinner, C. S. (2008). The health belief model. In K. Glanz, B. Rimer, & K. Viswanath (Eds.), <em>Health behavior and health education: Theory, research, and practice</em> (4th ed., pp. 45–65). San Francisco, CA: Jossey-Bass.</p> <p>Rosenstock, I. M. (1960). What research in motivation suggests for public health. <em>American Journal of Public Health, 50</em>(3), 295-302. https://doi.org/10.2105/AJPH.50.3_Pt_1.295</p>
Figure 3 in Public risk perceptions associated with Asian carp introduction and corresponding response actions
Figure 3. The proportion of participants perceiving risk associated with eleven different management responses to a potential invasion of Asian carp in Michigan as being low, medium or high risk, 2017 (n = 2,788).
Figure 2 in Public risk perceptions associated with Asian carp introduction and corresponding response actions
Figure 2. Percentage of participants perceiving risk associated with nine different socioeconomic risks from a potential Asian carp invasion in Michigan, 2017 (n = 2,788). Colorcoded peaks on the radar indicate a higher percentage of participants perceived that socioeconomic risk as being more salient to the biological invasion compared to other risks depicted with the same color.
Figure 1 in Public risk perceptions associated with Asian carp introduction and corresponding response actions
Figure 1. Proportion of participants perceiving five different types of environmental impacts from a potential invasion of Asian Carp in Michigan as being low, medium or high risk, 2017 (n = 2,788).
consumer risk perception toward pesticide stained tomatoes in Uganda
<p>A data set for measuring consumer risk perception towards pesticide-stained tomatoes in Uganda (sample 4 major regions in Uganda)</p>
Knowledge and perceptions of risk factors for maternal mortality among postnatal mothers in Hohoe Municipality of Volta Region, Ghana
<p>This de-identified limited dataset from which the manuscript if spread. It dataset from primary research conducted to assess knowledge of postnatal mothers about clinical risk factors and perceptions about socio-cultural and health system-related factors affecting maternal mortality.</p>
Does Investor Risk Perception Drive Asset Prices in Markets? Experimental Evidence.
<p>Extract the .zip-file into one folder (sub-folders for the raw data will be created). Then run the GIMS_DataAnalysis.R for the main results, GIMS_DataAnalysis_Return.R for the RETURN results, GIMS_DataAnalysis_2Assets.R for the EXPERIENCE results, and GIMS_DataAnalysis_2Markets.R for the 2MARKETS results.</p>
Additional Resources for Understanding End-User Perception of Transfer Risks in Smart Contracts
<p>This contains further resources for the work titled "Understanding End-User Perception of Transfer Risks in Smart Contracts", which is set to appear in CHI 2025.</p> <p>This work details an investigation into user understanding of transfer risks in ERC-20 blockchain smart contracts. An example transfer risk is a user being unable to transfer due to their account being blacklisted by the owner of the contract.</p> <p>A large portion of this work focuses on the most popular Ethereum smart contract (USD Tether). This details responses to a 110-participant survey on smart contract users, establishing their knowledge of transfer risks and various other perceptions. Included also are the results of statistical tests on these responses, the follow-up message to the respondents and more.</p> <p>Another portion of this work investigates the presence of transfer risks in other top ERC-20 contracts. The results of this investigation is also found here.</p> <p>This also includes results of blockchain analytics to establish the top ERC-20 addresses, as well as code used for processing.</p>
Climate change incidence, risk perception, and food security nexus
<p>This dataset supports the manuscript "Climate change incidence, risk perception, and food security among smallholders in Tigray, Ethiopia". The dataset contains three folders and a file from three data sources: (1) the Ethiopia Rural Socioeconomic Survey (ERSS)/Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA), a three-round panel data for Ethiopia, filtered for Tigray region; (2) an ERSS follow-up survey on the beliefs and opinions of respondents on climate change conducted in August 2019 in Tigray; and (3) 4km x 4km monthly grided Climate data (Rainfall, Max & min temperature). The files include socioeconomic data and household features, beliefs and opinions on climate change, and climatological data (monthly rainfall, maximum and minimum temperatures). The dataset covers 34 Enumeration Areas (EA) of the ERSS/LSMS-ISA and represents the region. It can be useful for studies on climate change risk perception and adaptation, environmental protection, and drivers of food insecurity in Tigray, Ethiopia. The data were processed using user-written codes in STATA v.17.</p>
Survey of risk perception, trust, and behavioral intention during the COVID-19 pandemic
<p>Early public health strategies to prevent the spread of COVID-19 in the United States relied on non-pharmaceutical interventions (NPIs) as vaccines and therapeutic treatments were not yet available. Implementation of NPIs, primarily social distancing and mask wearing, varied widely between communities within the US due to variable government mandates, as well as differences in attitudes and opinions. To understand the interplay of trust, risk perception, behavioral intention, and disease burden, we developed a survey instrument to study attitudes concerning COVID-19 and pandemic behavioral change in three states: Idaho, Texas, and Vermont. We designed our survey (<em>n </em>= 1034) to detect whether these relationships were significantly different in rural populations. The best fitting structural equation models show that trust indirectly affects protective pandemic behaviors via health and economic risk perception. We explore two different variations of this social cognitive model: the first assumes behavioral intention affects future disease burden while the second assumes that observed disease burden affects behavioral intention. In our models we include several exogenous variables to control for demographic and geographic effects. Notably, political ideology is the only exogenous variable which significantly affects all aspects of the social cognitive model (trust, risk perception, and behavioral intention). While there is a direct negative effect associated with rurality on disease burden, likely due to the protective effect of low population density in the early pandemic waves, we found a marginally significant, positive, indirect effect of rurality on disease burden via decreased trust (<em>p</em> = 0.095). This trust deficit creates additional vulnerabilities to COVID-19 in rural communities which also have reduced healthcare capacity. Increasing trust by methods such as in-group messaging could potentially remove some of the disparities inferred by our models and increase NPI effectiveness.</p>
Impact of disease characteristics and knowledge on public risk perception of Zoonoses
<p>Zoonoses represent a global public health threat. Understanding lay perceptions of risk associated with these diseases can better inform proportionate policy interventions that mitigate their current and future impacts. While individual zoonoses (e.g. Bovine Spongiform Encephalopathy) have received scientific and public attention, we know little about how multiple zoonotic diseases vary relative to each other in lay risk perceptions. To this end, we examined public perceptions of eleven zoonoses across twelve qualitative attributes of risk among the UK public (n = 727, volunteer sample), using an online survey. We found that attribute ratings were predominantly explained via two basic dimensions of risk related to public knowledge and dread. We also show that, despite participants reporting low familiarity with most of the diseases presented, zoonoses were perceived as essentially avoidable. These findings imply that infection is viewed as dependent upon actions under personal control which has significant implications for policy development.</p>
Missing the (tipping) point: the effect of information about climate tipping points on public risk perceptions in Norway [Dataset]
<p>This is all the data used for the redaction of the research paper "Missing the (tipping) point: the effect of information about climate tipping points on public risk perceptions in Norway".</p> <p> </p> <p>The dataset is contained in Excel files (.xlsx) and code for statistical analysis can be found in R files (.R)</p>
Differences in volcanic risk perception among Goma's population before the Nyiragongo eruption of May 2021, Virunga volcanic province (DR Congo)
<p>A short presentation of a study published focussing on the Differences in volcanic risk perception among Goma’s population before the Nyiragongo eruption of May 2021, Virunga volcanic province (DR Congo).</p>
Risk perception among Goma population before the 2021 Nyiragongo eruption
<p>Data sets on risk perception components (perceived severity and perceived vulnerability) associated to socio-demographic profile of the population of Goma as well as their psychological and cognitive factors related to volcanic risk. </p>
Survey of risk perception, trust, and behavioral intention during the COVID-19 pandemic
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Climate change incidence, risk perception, and food security nexus
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Linking behavior and predation data improves inference on interspecific risk perception in carnivores
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