The percentage of adults (aged 16 and over) that responded to the question "How often do you feel lonely?" with "Always or often" or "Some of the time"

Rationale At the beginning of 2018, the Prime Minister highlighted the issue of loneliness, announcing a Minister for Loneliness and committing to develop a national strategy to help tackle loneliness and a national measure for loneliness.

The national strategy, A Connected Society: A Strategy for Tackling Loneliness, was published on 15 October 2018. The commitments made by the Department of Health and Social Care (DHSC) and NHS England in the strategy identify loneliness to be a serious public health concern.

In keeping with the Loneliness Strategy, loneliness is defined here as: “a subjective, unwelcome feeling of lack or loss of companionship. It happens when we have a mismatch between the quantity and quality of social relationships that we have, and those that we want.” This is based on a definition first suggested by Perlman and Peplau in 1981(1).

Loneliness is a feeling that most people will experience at some point in their lives. When people feel lonely most or all of the time, it can have a serious impact on an individual’s well-being and their ability to function in society. Feeling lonely frequently is linked to early deaths and its health impact is thought to be on a par with other public health priorities like obesity or smoking.

Lonely people are more likely to be readmitted to hospital or have a longer stay. There is also evidence that lonely people are more likely to visit a General Practitioner or Accident and Emergency and more likely to enter local authority funded residential care.

At work, higher loneliness among employees is associated with poorer performance on tasks and in a team, while social interaction at work has been linked to increased productivity.

Loneliness can affect anyone of any age and background. It is important to measure loneliness because the evidence on loneliness is currently much more robust and extensive on loneliness in older people, but much less for other age groups including children and young people.

If more people measure loneliness in the same way, we will build a much better evidence base more quickly. That’s why the Prime Minister asked the Office for National Statistics (ONS) to develop national indicators of loneliness for people of all ages, suitable for use on major studies.

When reporting the prevalence of loneliness, ONS advise using the responses from the direct question, “How often do you feel lonely?” The inclusion of the direct loneliness measure in the Public Health Outcomes Framework (PHOF) will help inform and focus future work on loneliness at both a national and local level, providing a focus to support strategic leadership, policy decisions and service commissioning.

In this first set of data on loneliness prevalence at a local authority level, we have merged the two most frequent categories of feeling lonely (often or always and some of the time). This is due to small sample sizes and the limitations of this data will be explained in more detail in the caveats section.

This will be replaced next year by a 2-year pooled dataset which will have large enough sample sizes to report chronic loneliness. Presenting the data this year will help local authorities to work preventatively to tackle chronic loneliness by showing whether a local area has higher than national average levels of loneliness.

(1) Perlman D and Peplau LA (1981) 'Toward a Social Psychology of Loneliness', in Gilmour R and Duck S (eds.), Personal Relationships. 3, Personal Relationships in Disorder, London: Academic Press, pp. 31–56.

Definition of numerator Weighted number of respondents aged 16 and over, with a valid response to the question "How often do you feel lonely" that answered "Always or often" or "Some of the time". Active Lives Adult Survey data is collected November to November.

Definition of denominator Weighted number of respondents aged 16 and over, with a valid response to the question "How often do you feel lonely?".Denominator values in the Download data are unweighted counts. All analyses for this indicator have been weighted to be representative of the population of England.Active Lives Adult Survey data is collected November to November.

Caveats

Due to the sample size at local authority level, the "often or always" category is merged with the next most severe category of loneliness (people who respond as feeling lonely “some of the time”).

Standard practice is to report the two categories separately. However, data from other sources shows a degree of volatility in the ratio between these categories at the local authority (LA) level.

Therefore, there is a risk that when two local authorities are both reported as having 25% of people feeling lonely (often or always combined with some of the time), the actual figures for "often or always" might differ significantly. For example, one LA might have 24% often and always while another has only 3%, which would not be apparent in the combined category.

This could lead to underestimation or overestimation of chronic loneliness levels by local authorities.

In the past months, many countries have adopted varying degrees of lockdown restrictions to control the spread of the COVID-19 virus. According to the existing literature, some consequences of lockdown restrictions on people’s lives are beginning to emerge. To inform policies for the current and/or future pandemics, particularly those involving lockdown restrictions, this study adopted a data-driven Machine Learning approach to uncover the short-term effects of lockdown on people’s physical and mental health. An online questionnaire launched on 17 April 2020 was completed by 2,276 people from 66 countries. Focusing on the UK sample (N=382), 10 aggregated variables representing participant’s living environment, physical and mental health were used to train a RandomForest model to predict the week of survey completion. Using an index of importance to identify the best predictor among the 10 variables, self perceived loneliness was identified as the most influential variable. Subsequent statistical analysis showed a significant U-shaped curve for loneliness levels, with a decrease during the 4th and 5th lockdown weeks. The same pattern was replicated in the Greek sample (N = 129). This suggests that for the very first period of time, the adopted lockdown measures affected people’s evaluation of their social support leading to a decreased sense of loneliness.

Context

Available research shows that social connections are important for our well-being. Having support from family and friends is important for our happiness and health, and is also instrumental to our ability to share information, learn from others, and seize economic opportunities.

In this dataset we can explore data on loneliness and social connections across countries and over time, and review available evidence on how and why social connections and loneliness affect our health and emotional welfare, as well as our material well-being.

Despite the fact that there is a clear link between social connections and well-being, more research is needed to understand causal mechanisms, effect sizes and changes over time.

Researches show here, oversimplified narratives that compare loneliness with smoking, or that claim we are living a ‘loneliness epidemic’, are wrong and unhelpful.

Content

Dr. Vivek Murthy, former Surgeon General of the United States, recently wrote: “Loneliness and weak social connections are associated with a reduction in lifespan similar to that caused by smoking 15 cigarettes a day”.

This ‘15 cigarettes a day’ figure has been reproduced and reported in the news many times, under headlines such as “Loneliness is as lethal as smoking 15 cigarettes per day”.

It is indeed quite a shocking comparison since around 7 million deaths globally are attributed to smoking every year, and back-of-the-envelope calculations published in medical journals say one cigarette reduces your lifespan by 11 minutes.

Here we can dig deeper to try to understand what the data and research tell us about the link between social relations and health. In a nutshell, the reading of the evidence is as follows:

• There is a huge amount of evidence showing individuals who report feelings of loneliness are more likely to have health problems later in their life.
• There is credible theory and explanation of biological mechanisms, whereby isolation can set off unconscious surveillance for social threat, producing cognitive biases, reducing sleep and affecting hormones.
• It’s very likely there is a causal link, but there is no credible experimental evidence that would allow us to have a precise estimate of the magnitude of the causal effect that loneliness has on key metrics of health, such as life expectancy.
• The fact that we struggle to pin down the magnitude of the effect of loneliness on health doesn’t mean we should dismiss the available evidence. But it does show that more research is needed.

Observational studies: A first look at the data

Measuring loneliness

Psychologists and social neuroscientists often refer to loneliness as painful isolation. The emphasis on painful is there to make a clear distinction between solitude – the state of being alone – and subjective loneliness, which is the distressing feeling that comes from unmet expectations of the types of interpersonal relationships we wish to have.

Researchers use several kinds of data to measure solitude and loneliness. The most common source of data are surveys where people are asked about different aspects of their lives, including whether they live alone, how much time they spend with other people in a given window of time (e.g. ‘last week’) or specific context (e.g. ‘at social events, clubs or places of worship’); and whether they experience feelings of loneliness (e.g. ‘I have no-one with whom I can discuss important matters with’). Researchers sometimes study these survey responses separately, but often they also aggregate them in a composite index.

Surveys confirm that people respond differently to questions about subjective loneliness and physical social isolation, which suggests people do understand these as two distinct issues.

The fact that we see such high levels of loneliness, with substantial divergence across countries, explains why this is an important and active research area. Indeed, there are literally hundreds of papers that have used survey data to explore the link between loneliness, solitude, and health. Below is an overview of what these studies find.

# # https://ourworldindata.org/uploads/2019/12/historical-one-person-households-652x550.png" alt="image100"> # # https://ourworldindata.org/uploads/2019/07/happiness-and-friends-v3-e1564090552891.png" alt="image101"> # #

Acknowledgements

https://ourworldindata.org/

Inspiration

• In this dataset we can explore data on loneliness and social connections across countries and over time, and review available evidence on how and why social connections and loneliness affect our health and emotional welfare, as well as our material well-being.

Some references

• https://population.un.org/Household/index.html#/countries/300
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5547349/

Personal well-being, loneliness and what people in Great Britain felt were important issues; indicators from the Opinions and Lifestyle Survey (OPN).

Young adults between the ages of 18-24 are the loneliest age-group in the UK and other Western countries yet little is known about the causes and experiences of their loneliness. In particular, young adults of lower socio-economic status (SES) living in the most deprived areas are loneliest in the United Kingdom. Therefore, the aim of the data collected included exploring the causes and experiences of loneliness in young adults with these qualities and circumstances from their own perspective (part 1). The data also includes exploration of how these young adults conceptualise and experience their neighbourhood and how they impact upon their loneliness and social connectedness (part 2). This is qualitative data collected from forty-eight participants between June and August 2019 from 48 participants. A recruitment agency was employed to access the quota sample required. Participants were living in/recruited from four of the most deprived boroughs of London, UK: Newham (n = 16), Hackney (n = 16), Tower Hamlets (n = 16), and Barking & Dagenham (n = 16). There were two parts to the study. Part 1 included the free association task, in which participants were first presented with a piece of paper that contained a grid of four empty boxes and asked to express what they associated with “the experience of loneliness” by way of images and/or words. They were further instructed to elaborate one image/idea per box. After completion of the free association task, participants were asked to elaborate on the content of each box, in turn, in an interview. This started with “can we talk about what you have put in box 1, please?” Prompts such as “can you tell me more about that?” were used to ensure thoughts and feelings about the experience of loneliness were fully explored and emerged naturalistically without injection of content via researcher questioning. The interviews lasted for an average of 60 min. Most interviews took place at the participants’ homes though some at a local café, park or similar places if home was not an option. As for part 2, which was immediately after part 1, participants were asked to write or draw one place in their neighbourhood where they feel most socially connected and one where they feel most lonely. Beneath each of the two places they were further instructed to write what it is about that place that makes them feel the way they do. Participants were then asked to elaborate on the content of the association they had produced in an interview. This began with “can we talk about what you’ve put in box one (for the most socially connected place), please?” Prompts including “can you tell me more about that?” and “how does that make you feel in this space?” were used to ensure respondents’ thoughts and feelings about their chosen places were fully explored and emerged naturalistically without input from the researcher questioning. The same process ensued for the second box asking about the loneliest place. Each interview lasted between 20 and 30 minutes. The corresponding image/output for each participant for both parts 1 and 2 is presented.

Percentage of persons aged 15 years and over by frequency with which they feel lonely, by gender, for Canada, regions and provinces.

Percentage of persons aged 15 years and over by frequency with which they feel lonely, by gender and other selected sociodemographic characteristics: age group; immigrant status; visible minority group; Indigenous identity; persons with a disability, difficulty or long-term condition; LGBTQ2+ people; highest certificate, diploma or degree; main activity; and urban and rural areas.

U.S. Household Mental Health & Covid-19

Assessing the Impact of the Pandemic

By US Open Data Portal, data.gov [source]

About this dataset

This dataset offers a closer look into the mental health care received by U.S. households in the last four weeks during the Covid-19 pandemic. The sheer scale of this crisis is inspiring people of all ages, backgrounds, and geographies to come together to tackle the problem. The Household Pulse Survey from the U.S. Census Bureau was published with federal agency collaboration in order to draw up accurate and timely estimates about how Covid-19 is impacting employment status, consumer spending, food security, housing stability, education interruption, and physical and mental wellness amongst American households. In order to deliver meaningful results from this survey data about wellbeing at various levels of society during this trying period – which includes demographic characteristics such as age gender race/ethnicity training attainment – each consulted household was randomly selected according to certain weighted criteria to maintain accuracy throughout the findings This dataset will help you explore what's it like on the ground right now for everyone affected by Covid-19 - Will it inform your decisions or point you towards new opportunities?

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How to use the dataset

This dataset contains information about the mental health care that U.S. households have received in the last 4 weeks, during the Covid-19 pandemic. This data is valuable when wanting to track and measure mental health needs across the country and draw comparisons between regions based on support available.

To use this dataset, it is important to understand each of its columns or variables in order to draw meaningful insights from the data. The ‘Indicator’ column indicates which type of indicator (percentage or absolute number) is being measured by this survey, while ‘Group’ and 'Subgroup' provide more specific details about who was surveyed for each indicator included in this dataset.

The Columns ‘Phase’ and 'Time Period' provide information regarding when each of these indicators was measured - whether during a certain phase or over a particular timespan - while columns such as 'Value', 'LowCI' & 'HighCI' show us how many individuals fell into what quartile range for each measurement taken (e.g., how many people reported they rarely felt lonely). Similarly, the column Suppression Flag helps us identify cases where value has been suppressed if it falls below a certain benchmark; this allows us to calculate accurate estimates more quickly without needing to sort through all suppressed values manually each time we use this dataset for analysis purposes. Finally, columns such as ‘Time Period Start Date’ & ‘Time Period End Date’ indicate which exact dates were used for measurements taken over different periods throughout those dates specified – useful when conducting time-series related analyses over longer periods of time within our research scope)

Overall, when using this dataset it's important to keep in mind exactly what indicator type you're looking at - percentage points or absolute numbers - as well its associated group/subgroup characteristics so that you can accurately interpret trends based on key findings had by interpreting any correlations drawn from these results!

Research Ideas

• Analyzing the effects of the Covid-19 pandemic on mental health care among different subgroups such as racial and ethnic minorities, gender and age categories.
• Identifying geographical disparities in mental health services by comparing state level data for the same time period.
• Comparing changes in mental health care indicators over time to understand how the pandemic has impacted people's access to care within a quarter or over longer periods

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. ...

The goal of the present study was to examine whether lonely individuals differ from nonlonely individuals in their overt visual attention to social cues. Previous studies showed that loneliness was related to biased post-attentive processing of social cues (e.g., negative interpretation bias), but research on whether lonely and nonlonely individuals also show differences in an earlier information processing stage (gazing behavior) is very limited. A sample of 25 lonely and 25 nonlonely students took part in an eye-tracking study consisting of four tasks. We measured gazing (duration, number of fixations and first fixation) at the eyes, nose and mouth region of faces expressing emotions (Task 1), at emotion quadrants (anger, fear, happiness and neutral expression) (Task 2), at quadrants with positive and negative social and nonsocial images (Task 3), and at the facial area of actors in video clips with positive and negative content (Task 4). In general, participants tended to gaze most often and longest at areas that conveyed most social information, such as the eye region of the face (T1), and social images (T3). Participants gazed most often and longest at happy faces (T2) in still images, and more often and longer at the facial area in negative than in positive video clips (T4). No differences occurred between lonely and nonlonely participants in their gazing times and frequencies, nor at first fixations at social cues in the four different tasks. Based on this study, we found no evidence that overt visual attention to social cues differs between lonely and nonlonely individuals. This implies that biases in social information processing of lonely individuals may be limited to other phases of social information processing. Alternatively, biased overt attention to social cues may only occur under specific conditions, for specific stimuli or for specific lonely individuals.

Older adults’ experiences of loneliness over the lifecourse

This data set contains unique information about older adults’ experiences of loneliness across the lifecourse and the relationship with current loneliness. A lifecourse approach to understanding loneliness in later life links this outcome to long term biological, behavioural, psycho-social, and environmental processes, and exposures. This approach examines adult health outcomes and disparities and distinguishes between the timing (critical exsposure and number of exposures (cumulative disadvantage).

Our sample consists of 6,708 people aged 65 years and older, resident in the UK, who participated in the BBC Loneliness Experiment in spring 2018. Loneliness was assessed using the 3 item UCLA Loneliness Scale, using a threshold score of 6+ to define loneliness. Participants were asked if they had experienced loneliness in 5 life-stages ranging from childhood to old age and, if so, at which stage of life they had they experienced loneliness most intensely. The data set also includes details of age, gender,marital status, time spent alone, parent andcaer status, self-rated health and financial status and neighbourhood trust.

We show that 71% reported they had experienced loneliness at some previous stage in their life.
Having had three or more prior life stage experiences of loneliness was an independent risk factor for current loneliness. This aligns with the cumulative disadvantage model of life course exsposures as the odds of experiencing loneliness in later life increased with the number of prior experiences, demonstrating a dose-response relationship. In further research we will examine the importance of the number and timing of previous loneliness experiences and investigate the strategies used to cope with loneliness across the lifecourse as a pathway to developing more effective and personalised loneliness interventions.

The analysis of these data is published in Archives of Gerontology and Geriatrics: 10.1016/j.archger.2022.104740

This article explores the often-hidden experience of unwanted loneliness among youth in an increasingly digital world, where opportunities for connection abound yet true intimacy remains elusive. Using a reflexive ethnographic approach, this study examines how young people in Alicante, Spain, navigate loneliness within both digital and physical spaces. The research integrates multiple methods, including: (1) questionnaires administered to 268 participants, (2) in-depth interviews with 16 young people who later took part in focus groups, (3) UCLA Loneliness Scale assessments with 44 participants before and after the study, and (4) ethnographic field notes. This study focuses on two key dimensions of loneliness: unidentified loneliness (when individuals do not recognize their own isolation) and unacknowledged loneliness (when they feel alone but refuse to verbalize it). Through the life stories of five focal participants, the findings reveal how cultural, social, and gendered dynamics shape youth loneliness, often masking it behind digital interactions. Reflexive ethnography proves essential in engaging deeply with these narratives, shedding light on the contradictions between hyperconnectivity and social disconnection. Ultimately, this research highlights the need for safe, authentic spaces that allow young people to confront and articulate their loneliness without stigma.

PurposeSocial restrictions and government-mandated lockdowns implemented worldwide to kerb the SARS-CoV-2 virus disrupted our social interactions, behaviours, and routines. While many studies have examined how the pandemic influenced loneliness and poor mental health, such as depression, almost none have focussed on social anxiety. Further, how the change in social restrictions affected change in mental-health and well-being has not yet been explored.MethodsThis is a longitudinal cohort study in community dwellers who were surveyed across three timepoints in the first six months of the pandemic. We measured loneliness, social anxiety, depression, and social restrictions severity that were objectively coded in a sample from Australia, United States, and United Kingdom (n = 1562) at each time point. Longitudinal data were analysed using a multivariate latent growth curve model.ResultsLoneliness reduced, depression marginally reduced, and social anxiety symptoms increased as social restrictions eased. Specific demographic factors (e.g., younger age, unemployment, lower wealth, and living alone) all influenced loneliness, depression, and social anxiety at baseline. No demographic factors influenced changes for loneliness; we found that those aged over 25 years reduced faster on depression, while those younger than 25 years and unemployed increased faster on social anxiety over time.ConclusionWe found evidence that easing social restrictions brought about additional burden to people who experienced higher social anxiety symptoms. As country-mandated lockdown and social restrictions eased, people are more likely report higher social anxiety as they readjust into their social environment. Mental health practitioners are likely to see higher levels of social anxiety in vulnerable communities even as social restrictions ease.

ACS DEMOGRAPHIC AND HOUSING ESTIMATES RACE ALONE OR IN COMBINATION WITH ONE OR MORE RACES - DP05 Universe - Total population Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 The concept “race alone or in combination” includes people who reported a single race alone (e.g., Asian) and people who reported that race in combination with one or more of the other major race groups (e.g., White, Black or African American, American Indian and Alaska Native, Native Hawaiian and Other Pacific Islander, and Some Other Race). The “race alone or in combination” concept, therefore, represents the maximum number of people who reported as that race group, either alone, or in combination with another race(s). The sum of the six individual race “alone or in combination” categories may add to more than the total population because people who reported more than one race were tallied in each race category.

Very young children, people with somatic and psychological disabilities and the over-75s are vulnerable to heat stress. The largest most vulnerable group within this is seriously lonely over-75s. The thirst stimulus of the elderly is reduced, so that they drink less and heat and dehydration are lurking. This is especially risky for lonely elderly people, because because of their loneliness there may be too few people who draw their attention to drinking and cooling sufficiently.

Physical activity is a behavior that promotes physical and mental health; yet physical activity has decreased during the COVID-19 pandemic. To promote health during times of challenge, it is important to identify potential barriers to this key health behavior, such as loneliness. This brief report extends previous research on physical activity and loneliness that mainly focused on between-person differences to examine their time-varying associations at the within-person level using repeated daily life assessments. From April 2020 to August 2020, data were collected from a sample of 139 community-dwelling Canadian adults (Mage = 40.65 years, SD = 18.37; range = 18–83 years). Each evening for 10 consecutive days, participants reported their loneliness, number of steps, and minutes of moderate-to-vigorous physical activity. Results revealed that, in line with our hypotheses, on days when participants reported more loneliness they also engaged in less moderate-to-vigorous physical activity than on less lonely days (estimate = −0.24, p = 0.007); there was a significant negative association between loneliness and daily number of steps (estimate = −18.42, p = 0.041). In contrast, at the between-person level, overall loneliness was not associated with overall physical activity engagement after accounting for within-person differences and control variables (age, sex, day in study). From an intervention perspective, our findings suggest that it is promising to tackle loneliness on a day-to-day basis to increase physical activity one day at a time. This may be especially relevant during times mandating social-distancing, but also at other times when individuals experience greater feelings of loneliness.

BackgroundThe COVID-19 pandemic has led governments worldwide to implement unprecedented response strategies. While crucial to limiting the spread of the virus, “social distancing” may lead to severe psychological consequences, especially in lonely individuals.MethodsWe used cross-sectional (n = 380) and longitudinal (n = 74) designs to investigate the links between loneliness, anxiety, and depression symptoms (ADS) and COVID-19 risk perception and affective response in young adults who implemented social distancing during the first 2 weeks of the state of epidemic threat in Poland.ResultsLoneliness was correlated with ADS and with affective response to COVID-19’s threat to health. However, increased worry about the social isolation and heightened risk perception for financial problems was observed in lonelier individuals. The cross-lagged influence of the initial affective response to COVID-19 on subsequent levels of loneliness was also found.ConclusionThe reciprocal connections between loneliness and COVID-19 response may be of crucial importance for ADS during the COVID-19 crisis.

Data come from the follow-up of the main study “Inclusive ageing in place” (IN-AGE), regarding frail older people aged 65 years and over (males and females). The main study was a cross-sectional qualitative survey carried out in 2019 by face-to-face interviews to frail older people without cognitive impairment, and living at home, alone or with a private personal care assistant (PCA), in three Italian Regions: Lombardy (North), Marche (Centre) and Calabria (South). Both peripheral/degraded areas of urban sites and fragile rural locations were included, with regard to social and material vulnerability aspects (e.g. high presence of frail older people living alone, poor provision of services). The follow up was carried out in July-September 2020, and it was aimed to explore and compare effects of lockdown, due to the first wave of the COVID-19 pandemic (February-May 2020), on frail older people living alone at home in Brescia and Ancona, two urban cities located respectively in the Northern and Central Italy. This country was the Western epicenter of the first wave of the pandemic, that differently affected the two cities as for infections, with a more severe impact on the former one. The dataset (41 respondents, vs 48 in the main survey) regards available social networks (family, friends, neighbors), use of communication technology (mobile, smartphone, PC/tablet), and perceived loneliness. Also, fears due to the pandemic were reported. A semi-structured interview was administered by telephone due to social distancing imposed by the pandemic. Participants were asked to report and motivate possible changes due to the pandemic. A simple quantitative analysis (frequency distribution/bivariate analysis) of closed responses was carried out by using Microsoft Excel software 2019. Findings showed that seniors increased mainly telephone (TEL) contacts especially in Ancona. In both cities fears for the infection emerged too, and mainly in Ancona than Brescia several cases of worsened perceived loneliness were detected. Despite the exploratory nature of the study, with a not-representative (small) sample of the target population, and notwithstanding some differences among cities, findings stressed the risk of isolation and loneliness of seniors living alone. This risk was buffered by the use of communication technology during the lockdown, but more interventions allowing a sustainable healthy ageing (HA) in place, enhancing healthy behaviors especially in emergency situations, are needed. The dataset is provided in open format (xlsx) and includes the following: a “numeric” dataset regarding the unlabeled dimensions used for statistics elaboration; a codebook with both the complete variables list and variables labels we used. The dataset was produced within the framework of the IN-AGE project, funded by Fondazione Cariplo, Grant N. 2017-0941.

Overview

The Associated Press is sharing data from the COVID Impact Survey, which provides statistics about physical health, mental health, economic security and social dynamics related to the coronavirus pandemic in the United States.

Conducted by NORC at the University of Chicago for the Data Foundation, the probability-based survey provides estimates for the United States as a whole, as well as in 10 states (California, Colorado, Florida, Louisiana, Minnesota, Missouri, Montana, New York, Oregon and Texas) and eight metropolitan areas (Atlanta, Baltimore, Birmingham, Chicago, Cleveland, Columbus, Phoenix and Pittsburgh).

The survey is designed to allow for an ongoing gauge of public perception, health and economic status to see what is shifting during the pandemic. When multiple sets of data are available, it will allow for the tracking of how issues ranging from COVID-19 symptoms to economic status change over time.

The survey is focused on three core areas of research:

• Physical Health: Symptoms related to COVID-19, relevant existing conditions and health insurance coverage.
• Economic and Financial Health: Employment, food security, and government cash assistance.
• Social and Mental Health: Communication with friends and family, anxiety and volunteerism. (Questions based on those used on the U.S. Census Bureau’s Current Population Survey.) ## Using this Data - IMPORTANT This is survey data and must be properly weighted during analysis: DO NOT REPORT THIS DATA AS RAW OR AGGREGATE NUMBERS!!

Instead, use our queries linked below or statistical software such as R or SPSS to weight the data.

Queries

If you'd like to create a table to see how people nationally or in your state or city feel about a topic in the survey, use the survey questionnaire and codebook to match a question (the variable label) to a variable name. For instance, "How often have you felt lonely in the past 7 days?" is variable "soc5c".

Nationally: Go to this query and enter soc5c as the variable. Hit the blue Run Query button in the upper right hand corner.

Local or State: To find figures for that response in a specific state, go to this query and type in a state name and soc5c as the variable, and then hit the blue Run Query button in the upper right hand corner.

The resulting sentence you could write out of these queries is: "People in some states are less likely to report loneliness than others. For example, 66% of Louisianans report feeling lonely on none of the last seven days, compared with 52% of Californians. Nationally, 60% of people said they hadn't felt lonely."

Margin of Error

The margin of error for the national and regional surveys is found in the attached methods statement. You will need the margin of error to determine if the comparisons are statistically significant. If the difference is:

• At least twice the margin of error, you can report there is a clear difference.
• At least as large as the margin of error, you can report there is a slight or apparent difference.
• Less than or equal to the margin of error, you can report that the respondents are divided or there is no difference. ## A Note on Timing Survey results will generally be posted under embargo on Tuesday evenings. The data is available for release at 1 p.m. ET Thursdays.

About the Data

The survey data will be provided under embargo in both comma-delimited and statistical formats.

Each set of survey data will be numbered and have the date the embargo lifts in front of it in the format of: 01_April_30_covid_impact_survey. The survey has been organized by the Data Foundation, a non-profit non-partisan think tank, and is sponsored by the Federal Reserve Bank of Minneapolis and the Packard Foundation. It is conducted by NORC at the University of Chicago, a non-partisan research organization. (NORC is not an abbreviation, it part of the organization's formal name.)

Data for the national estimates are collected using the AmeriSpeak Panel, NORC’s probability-based panel designed to be representative of the U.S. household population. Interviews are conducted with adults age 18 and over representing the 50 states and the District of Columbia. Panel members are randomly drawn from AmeriSpeak with a target of achieving 2,000 interviews in each survey. Invited panel members may complete the survey online or by telephone with an NORC telephone interviewer.

Once all the study data have been made final, an iterative raking process is used to adjust for any survey nonresponse as well as any noncoverage or under and oversampling resulting from the study specific sample design. Raking variables include age, gender, census division, race/ethnicity, education, and county groupings based on county level counts of the number of COVID-19 deaths. Demographic weighting variables were obtained from the 2020 Current Population Survey. The count of COVID-19 deaths by county was obtained from USA Facts. The weighted data reflect the U.S. population of adults age 18 and over.

Data for the regional estimates are collected using a multi-mode address-based (ABS) approach that allows residents of each area to complete the interview via web or with an NORC telephone interviewer. All sampled households are mailed a postcard inviting them to complete the survey either online using a unique PIN or via telephone by calling a toll-free number. Interviews are conducted with adults age 18 and over with a target of achieving 400 interviews in each region in each survey.Additional details on the survey methodology and the survey questionnaire are attached below or can be found at https://www.covid-impact.org.

Attribution

Results should be credited to the COVID Impact Survey, conducted by NORC at the University of Chicago for the Data Foundation.

AP Data Distributions

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Data supporting the article “The cost of living alone”

This study examines the relationship between virtual social interaction and people’s social behaviors and psychology using algorithm matching technologies and questionnaire surveys. The focus is on interpersonal communication on virtual social platforms. The findings indicate that engaging in virtual social networking is often accompanied by a high level of loneliness. Users who experience social anxiety in the real world tend to feel more lonely, and this loneliness is exacerbated by presenting an unreal version of oneself and having distrust in virtual social networking. Users with higher anxiety and loneliness levels are more likely to use the algorithm matching function of virtual social networking, engage in false self-presentation, and have less trust in the platform. Since the inherent flaws of virtual social networking cannot be eliminated solely through algorithm matching, a potential solution is to introduce more offline to online social functions for strangers. This exploration of actual matching on social platforms may help reduce users’ loneliness.