In the context of COVID-19, RAND and the Robert Wood Johnson Foundation partnered again to build from the National Survey of Health Attitudes to implement a longitudinal survey to understand how these health views and values have been affected by the experience of the pandemic, with particular focus on populations deemed vulnerable or underserved, including people of color and those from low- to moderate-income backgrounds. The questions in this COVID-19 survey focused specifically on experiences related to the pandemic (e.g., financial, physical, emotional), how respondents viewed the disproportionate impacts of the pandemic, whether and how respondents' views and priorities regarding health actions and investments are changing (including the roles of government and the private sector), and how general values about such issues as freedom and racism may be related to pandemic views and response expectations. This study includes the results for Wave 4 for the general population. Demographic information includes sex, marital status, household size, race and ethnicity, family income, employment status, age, and census region.

In 2020, ** percent of young people surveyed in the United Kingdom (UK) have experienced feelings of self-loathing since the outbreak of the COVID-19 pandemic, while a further ** percent reported experiencing insomnia. Furthermore, ** percent of young people said they had experienced panic attacks since the pandemic.

The National Ambulatory Medical Care Survey (NAMCS), conducted by the National Center for Health Statistics (NCHS), collects data on visits to physician offices to describe patterns of ambulatory care delivery in the United States. As part of NAMCS, the Physician Induction Interview collects information about practice characteristics at physician offices. Partway through the 2020 NAMCS, NCHS added questions to the Physician Induction Interview to assess physician experiences related to COVID-19 in office-based settings. The data include nationally representative estimates of experiences related to COVID-19 among office-based physicians in the United States, including: shortages of personal protective equipment (PPE) in the past 3 months; the ability to test for COVID-19 in the past 3 months; providers testing positive for COVID-19 in the past 3 months; turning away COVID-19 patients in the past 3 months; and telemedicine or telehealth technology use before and after March 2020. Estimates were derived from interviews with physicians in periods 3 and 4 of 2020 NAMCS and periods 1 through 4 of 2021 NAMCS, which occurred between December 15, 2020 and May 6, 2022. The data are considered preliminary, and the results may change with the final data release.

According to a July 2020 study, roughly ** percent of respondents worldwide were excited about the potential of technology to further personalize their travel experiences. The country with the highest share of respondents that believed this was Thailand with ** percent. Meanwhile, only ** percent of German respondents shared the same excitement.

During a 2020 survey among children in the United States aged 9-17 years, it was found that Instagram and Snapchat were the platforms where 26 percent of the children had potentially harmful experiences. These were also the platforms where 16 percent of the participants had an online sexual interaction.

As of May 31, some 22 percent of respondents in the United States stated that someone they know had been tested for COVID-19.

The California Violence Experiences Survey (CalVEX) offers insight into experiences of physical violence (inclusive of gun violence), sexual violence (including harassment and assault), and intimate partner violence among California adults. It also summarizes mental health outcomes and protective and risk factors for violence. The sample includes 2,115 adult (age 18+) state resident respondents surveyed in March 2020.

As of May 31, some 47 percent of respondents in the United States stated that they had self-isolated / quarantined since the pandemic.

This dataset contains the text transcripts of interviews conducted with participants about their experiences of reading and thinking critically.

Participants were asked about their experiences of reading, including ways they evaluated what they read; their experiences of transportation into the texts they read; their epistemological orientation; their opinions on how reading may relate to critical thinking.

This study formed one component of a wider PhD research project on fiction reading and critical thinking.

This study investigated readers’ experiences of critical thinking and reading, comparing fiction and nonfiction. As previous research has shown links between fiction reading and increased social and cognitive capacities, and such capacities are argued to be necessary for critical thinking, this study sought to explore a potentially unique relationship between reading fiction and critical thinking, as distinct from nonfiction. In depth interviews were conducted with participants who self-identified as readers (N = 12). Each reader was interviewed twice, first in a general discussion of their reading and critical thinking experiences, and secondly with reference to a text they selected to read.

The research questions guiding this study were: a. In what ways do readers experience an influence of what they read on how they think critically? b. In what ways do readers’ experiences pertaining to question a. differ between fiction and nonfiction reading? Are there any unique associations for fiction? c. How do readers’ experiences of transportation (being immersed into the text) while reading relate to the ways in which they think critically about a text?

Ethical approval for this project was granted by the UCL Ethics Committee: 15397/003

This dataset consist of a thematic analysis to help understand the 2020 matric learners' experiences during the covid-19 pandemic. The data is categorised into codes based on the learner's experiences which form four themes. A descriptive qualitative case study was used for this research were five matric students were interviewed to gain insight into their lockdown experiences.

Abstract copyright UK Data Service and data collection copyright owner.

As the UK went into the first lockdown of the COVID-19 pandemic, the team behind the biggest social survey in the UK, Understanding Society (UKHLS), developed a way to capture these experiences. From April 2020, participants from this Study were asked to take part in the Understanding Society COVID-19 survey, henceforth referred to as the COVID-19 survey or the COVID-19 study.

The COVID-19 survey regularly asked people about their situation and experiences. The resulting data gives a unique insight into the impact of the pandemic on individuals, families, and communities. The COVID-19 Teaching Dataset contains data from the main COVID-19 survey in a simplified form. It covers topics such as

• Socio-demographics
• Whether working at home and home-schooling
• COVID symptoms
• Health and well-being
• Social contact and neighbourhood cohesion
• Volunteering

The resource contains two data files:

• Cross-sectional: contains data collected in Wave 4 in July 2020 (with some additional variables from other waves);
• Longitudinal: Contains mainly data from Waves 1, 4 and 9 with key variables measured at three time points.

Key features of the dataset

• Missing values: in the web survey, participants clicking "Next" but not answering a question were given further options such as "Don't know" and "Prefer not to say". Missing observations like these are recorded using negative values such as -1 for "Don't know". In many instances, users of the data will need to set these values as missing. The User Guide includes Stata and SPSS code for setting negative missing values to system missing.

• The Longitudinal file is a balanced panel and is in wide format. A balanced panel means it only includes participants that took part in every wave. In wide format, each participant has one row of information, and each measurement of the same variable is a different variable.

• Weights: both the cross-sectional and longitudinal files include survey weights that adjust the sample to represent the UK adult population. The cross-sectional weight (betaindin_xw) adjusts for unequal selection probabilities in the sample design and for non-response. The longitudinal weight (ci_betaindin_lw) adjusts for the sample design and also for the fact that not all those invited to participate in the survey, do participate in all waves.

• Both the cross-sectional and longitudinal datasets include the survey design variables (psu and strata).

A full list of variables in both files can be found in the User Guide appendix.

Who is in the sample?

All adults (16 years old and over as of April 2020), in households who had participated in at least one of the last two waves of the main study Understanding Society, were invited to participate in this survey. From the September 2020 (Wave 5) survey onwards, only sample members who had completed at least one partial interview in any of the first four web surveys were invited to participate. From the November 2020 (Wave 6) survey onwards, those who had only completed the initial survey in April 2020 and none since, were no longer invited to participate

The User guide accompanying the data adds to the information here and includes a full variable list with details of measurement levels and links to the relevant questionnaire.

• Socio-demographics;
• Whether working at home and home-schooling;
• COVID symptoms;
• Health and well-being;
• Social contact and neighbourhood cohesion;
• Volunteering.

The Touch Test was commissioned by Wellcome Collection and BBC Radio 4 and research carried out by Goldsmiths, University of London. This survey investigated attitudes towards and experiences of touch - a relatively understudied domain compared with other sensory modalities. A large participant sample was recruited, comprising a broad demographic across age, gender, nationality, ethnicity, and employment status. Our key research questions addressed particular gaps in existing knowledge, and included 1) What are people's attitudes and experiences towards touch and how do they vary across different groups? 2) How does touch relate to health and wellbeing throughout adulthood? 3) What is the relationship between touch and the type, size, closeness, and frequency of contacts in a respondent’s social network? 4) What is the topography of social touch (where is it / is it not appropriate to touch someone) and how does this vary between demographic groups? 5) How does touch relate to sleep, and how might this relationship contribute to health and wellbeing? 6) How does touch contribute to medical experiences (e.g. willingness to have interactions with healthcare professionals; perceptions of outcomes of medical treatments)? 7) How open are we to using technology as a tool to provide or augment our tactile experiences (e.g. for medical treatments; for long-distance relationships)?

Abstract

Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at http://www.fao.org/in-action/voices-of-the-hungry/fies/en/ .

The FIES-based indicators are compiled using the FIES survey module, containing 8 questions. Two indicators can be computed:
1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2), 2. The proportion of the population experiencing severe food insecurity.

These data were collected by FAO through the Gallup World Poll. General information on the methodology can be found here: https://www.gallup.com/178667/gallup-world-poll-work.aspx. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.

Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available in the documentations tab. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

Individuals of 15 years or older with access to landline and/or mobile phones.

Kind of data

Sample survey data [ssd]

Sampling procedure

A simple stratified sample design was used for selection of landline phone samples. Within each explicit stratum (Prefecture) in the case of landline, sample of specified size was drawn using pure Random Digit Dial (RDD) procedures. Sampling was done independently within each stratum. Mobile phone samples were drawn using pure RDD procedures across all mobile phone providers proportional to the share of each provider. For respondents contacted by landline telephone, random respondent selection within the household was performed by asking for the person in the household aged 15 and older who had the next birthday. Respondents contacted by mobile telephone were screened for those aged 15 and older; no additional selection procedure was performed. For the purpose of data collection, the total initial sample was split into random subsamples (replicate samples) and released sequentially based on the progress of interviewing in different strata. The goal was to release an optimum amount of sample each time to achieve a high response rate while completing the targeted number of interviews within the field period. Exclusions: NA Design effect: 1.22

Mode of data collection

Other [oth]

Cleaning operations

Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.

Sampling error estimates

The margin of error is estimated as 3.4. This is calculated around a proportion at the 95% confidence level. The maximum margin of error was calculated assuming a reported percentage of 50% and takes into account the design effect.

This dataset reports downloads of metadata records and documents from the Development Experience Clearinghouse (DEC).

According to a survey conducted in Thailand in December 2020, about 36 percent of the online platform users stated that the Video-on-Demand streaming services were the personalized entertainment at an affordable price. Meanwhile, around 25.2 percent of the respondents stated that they received quality contents, which cannot be found on free television, from the VoD services.

Abstract

Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at http://www.fao.org/in-action/voices-of-the-hungry/fies/en/ .

The FIES-based indicators are compiled using the FIES survey module, containing 8 questions. Two indicators can be computed: 1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2), 2. The proportion of the population experiencing severe food insecurity.

These data were collected by FAO through the Gallup World Poll. General information on the methodology can be found here: https://www.gallup.com/178667/gallup-world-poll-work.aspx. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.

Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available under the "DOCUMENTATION" tab above. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

Individuals of 15 years or older with access to landline and/or mobile phones.

Kind of data

Sample survey data [ssd]

Sampling procedure

A simple stratified sample design was used for selection of landline phone samples. Within each explicit stratum (district) in the case of landline, sample of specified size was drawn using list-assisted Random Digit Dial (RDD) procedures. In the case of mobile, within each explicit stratum, sample of specified size was drawn using pure RDD procedure. Sampling was done independently within each stratum. All sampled phone numbers were pre-screened for working status.

For respondents contacted by landline telephone, random respondent selection within the household was performed by enumerating the persons in the household aged 15 and older and selecting one at random. Respondents contacted by mobile telephone were screened for those aged 15 and older; no additional selection procedure was performed.

For the purpose of data collection, the total initial sample was split into random subsamples (replicate samples) and released sequentially based on the progress of interviewing in different strata. The goal was to release an optimum amount of sample each time to achieve a high response rate while completing the targeted number of interviews within the field period Exclusions: NA Design effect: 1.91

Mode of data collection

Other [oth]

Cleaning operations

Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.

Sampling error estimates

The margin of error is estimated as 4.3. This is calculated around a proportion at the 95% confidence level. The maximum margin of error was calculated assuming a reported percentage of 50% and takes into account the design effect.

When the COVID-19 pandemic began, U.S. college students reported increased anxiety and depression. This study examines mental health among U.S college students during the subsequent 2020–2021 academic year by surveying students at the end of the fall 2020 and the spring 2021 semesters. Our data provide cross-sectional snapshots and longitudinal changes. Both surveys included the PSS, GAD-7, PHQ-8, questions about students’ academic experiences and sense of belonging in online, in-person, and hybrid classes, and additional questions regarding behaviors, living circumstances, and demographics. The spring 2021 study included a larger, stratified sample of eight demographic groups, and we added scales to examine relationships between mental health and students’ perceptions of their universities’ COVID-19 policies. Our results show higher-than-normal frequencies of mental health struggles throughout the 2020–2021 academic year, and these were substantially higher for female college students, but by spring 2021, the levels did not vary substantially by race/ethnicity, living circumstances, vaccination status, or perceptions of university COVID-19 policies. Mental health struggles inversely correlated with scales of academic and non-academic experiences, but the struggles positively correlated with time on social media. In both semesters, students reported more positive experiences with in-person classes, though all class types were rated higher in the spring semester, indicating improvements in college students’ course experiences as the pandemic continued. Furthermore, our longitudinal data indicate the persistence of mental health struggles across semesters. Overall, these studies show factors that contributed to mental health challenges among college students as the pandemic continued.

To study the impact of COVID-19 pandemic on frontline healthcare workers in the United States over time, the Healthcare Worker Exposure Response and Outcomes (HERO) Registry was created in 2020 to form a virtual research community of healthcare workers (and later, their family members and community members). The registry was intended for healthcare workers interested in completing research studies related to the COVID-19 pandemic and its impacts on their lives. Observational data were collected at various timepoints between April 2020 and September 2022 via web-based questionnaires available on the HERO Registry online portal. This collection contains 39 sets of data from over 50,000 HERO Registry members. Datasets represent separate surveys with distinct survey designs and sampling criteria. Surveys focused on health history, workplace experiences, COVID-19 exposure, social support, mental health, and the respondents' willingness to remain in or leave the healthcare field. Datasets 24 through 39 represent "hot topics" such as vaccines, vaccine willingness and uptake, childcare and school arrangements, and staffing shortages. Datasets for registry administration, respondent demographics, and survey eligibility criteria are also included.