Due the spread of coronavirus (COVID-19), many marketing organizations in the UK may have to start operating remotely in 2020. A survey published in mid-March revealed that 73 percent of marketers believe that they are more efficient when working remotely and 68 percent believe that they work more hours at home. Yet just a quarter believe that working from home will intrude on their personal life. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

In 2021, approximately 37 percent of workers in Great Britain wished to work from home some of the time after the Coronavirus pandemic is over, with one in five wanted to work from home all the time. Despite this, 37 percent of British workers advised they never want to work from home, with seven percent not sure.

This project adopts two main research instruments - two online questionnaires (2 surveys of circa 1400 UK ‘new’ homeworkers each, June-July 2020 & Dec-February 2021). The second instrument is a series of semi-structed interviews (4 x Interviews with 80 ‘new’ homeworkers across UK, May 2020 – July 2021).

The COVID-19 outbreak has forced companies to embrace home-based working (HBW) at such speed that they have had little opportunity to consider the impact on their workers. It can be argued that the crisis has led to the most significant, intensive social experiment of digital, HBW that has ever occurred. The current situation, which involves the whole household being based at home, is an unprecedented challenge which may be at least an intermittent fixture, for the next eighteen months (BBC Futures, 25/03/20).

The press have suggested that this revolution might also offer an opportunity for many companies to finally build a culture that allows long-overdue work flexibility ... many employees for companies who have sent all staff home are already starting to question why they had to go into the office in the first place (The Guardian, 13/02/20). These optimistic takes on the current patterns of work focus on HBW's emancipatory potential, offering flexibility, the lubrication of work and family responsibilities and the promise of increased productivity. Yet, this new world order, where the home becomes a multi-occupational, multi-person workplace and school, not only challenges boundaries but also conceptions of the domestic space.

The impact of homeworking is likely to present significant variation depending on organisational support, the worker's role, socio-economic status, employment status, as well as household composition and size of living space. There are significant concerns regarding intensified HBW, including poor work-life balance, enhanced domestic tensions and disproportionately negative impacts on those in lower socio-economic groupings. Moreover, HBW increases the proportion of time women (most often) spend on housework and childcare, reproducing and reinforcing gender roles within the new 'work-space'

We will examine in-depth this radical shift in working arrangements and how it impacts on the wellbeing and productivity of workers and their households. Using a combination of in-depth interviews with sixty participants, representing the spectrum of this novel group of homeworkers, as well as a large-scale survey, this project (Working@Home) will provide unrivalled insights into the experience of home-working for the UK population and will serve as a permanent record of the lives of citizens in this unprecedented time.

The research will be key in understanding the expectations that organisations have placed on workers, as well as the robustness of support systems that have been put in place, taking into account the rapid advancement of home working systems with almost no preparation and only limited existing support structures or expertise. The findings will provide a benchmark for the resilience of both individuals and businesses and demonstrate the potential for the robustness of the infrastructure in the return to a 'new normal' after the crisis.

In order to ensure that the findings from the project are accessible to all, we are developing a website (workingathome.org.uk) that will host up to date information on the progress of the project, details of the project team, guidance for participants as well as information regarding our webinar series. The project aims to produce guidance to individuals, organisations and policy makers on how to best manage the ongoing medical emergency from a home-working perspective as well as providing guidance for any future pandemic scenario.

An October 2021 report examined the number of job losses in the out-of-home leisure economy due to the coronavirus (COVID-19) pandemic in the United Kingdom in 2020. According to the study's estimates, the food-led subsector suffered the most from within the out-of-home leisure industry, having lost roughly 241 thousand jobs in the first year of the pandemic.

Data on working population's location of work patterns, well-being and attitudes to future working from home plans broken down by age, sex, income and region. Data are based on the COVID-19 module of the Opinions and Lifestyle Survey, collected between 21 April and 16 May 2021.

In February 2025, approximately 14 percent of workers in Great Britain worked from home exclusively, with a further 26 percent working from home and travelling to work, while 37 percent only travelled to work. During this time period, the share of people only travelling to work was highest in March 2022, at 60 percent of respondents, with the peak for only working from home occurring in June 2020. In general, hybrid working has become steadily more popular than fully remote working, with the highest share of people hybrid working in November 2023, when 31 percent of people advising they were hybrid working. What type of workers are most likely to work from home? In 2020, over half of people working in the agriculture sector mainly worked from home, which was the highest share among UK industry sectors at that time. While this industry was one of the most accessible for mainly working at home, just six percent of workers in the accommodation and food services sector mainly did this, the lowest of any sector. In the same year, men were slightly more likely to mainly work from home than women, while the most common age group for mainly working from home was those aged 75 and over, at 45.4 percent. Over a long-term period, the share of people primarily home working has grown from 11.1 percent in 1998, to approximately 17.4 percent in 2020. Growth of Flexible working in the UK According to a survey conducted in 2023, working from home either on a regular, or ad-hoc basis was the most common type of flexible working arrangement offered by organizations in the UK, at 62 percent of respondents. Other popular flexible working arrangements include the ability to work flexible hours, work part-time, or take career breaks. Since 2013, for example, the number of employees in the UK that can work flextime has increased from 3.2 million, to around 4.2 million by 2024. When asked why flexible work was important to them, most UK workers said that it supported a better work-life balance, with 41 percent expressing that it made their commute to work more manageable.

Due the spread of coronavirus (COVID-19), many marketing organizations in the United Kingdom (UK) may have to start operating remotely in 2020. A survey published in mid-March revealed that 62 percent of marketers fear that their organization could be compromised by the need to work from home. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Opinions and Lifestyle Survey (COVID-19 module), 3 to 14 November 2021

The increase in the extent of working-from-home determined by the COVID-19 health crisis has led to a substantial shift of economic activity across geographical areas; which we refer to as a Zoomshock. When a person works from home rather than at the office, their work-related consumption of goods and services provided by the locally consumed service industries will take place where they live, not where they work. Much of the clientèle of restaurants, coffee bars, pubs, hair stylists, health clubs, taxi providers and the like located near workplaces is transferred to establishment located near where people live. These data are our calculations of the Zoomshock at the MSOA level. They reflect estimats of the change in the number of people working in UK neighbourhoods due to home-working.

The COVID-19 shutdown is not affecting all parts of the UK equally. Economic activity in local consumer service industries (LCSI), such as retail outlets, restaurants, hairdressers, or gardeners has all but stopped; other industries are less affected. These differences among industries and their varying importance across local economies means recovery will be sensitive to local economic conditions and will not be geographically uniform: some neighbourhoods face a higher recovery risk of not being able to return to pre-shutdown levels of economic activity. This recovery risk is the product of two variables. The first is the shock, the effect of the shutdown on local household incomes. The second is the multiplier, the effect on LCSI economic activity following a negative shock to household incomes. In neighbourhoods where many households rely on the LCSI sector as a primary source of income the multiplier may be particularly large, and these neighbourhoods are vulnerable to a vicious circle of reduced spending and reduced incomes. This project will produce data measuring the shock, the multiplier, and the COVID-19 shutdown recovery risk for UK neighbourhoods. These variables will be estimated using individual and firm level information from national surveys and administrative data. The dataset, and corresponding policy report, will be made public and proactively disseminated to guide local and national policy design. Recovery inequality is likely to be substantial: absent intervention, existing regional inequalities may be exacerbated. This research will provide a timely and necessary input into designing appropriate recovery policy.

In 2020, approximately 5.6 million people worked mainly from home in the United Kingdom, an increase of around 1.69 million people when compared with 1998, when just 2.9 million workers mainly worked from home. As a share of all workers in the United Kingdom, this was the equivalent of 17.4 percent of the UK workforce, compared with 14.2 percent in 1998. Rise of the hybrid workforce More recent figures on working location trends in Great Britain, indicate that as of June 2024, around 14 percent of workers had worked from home exclusively in the last seven days, with a further 41 percent only travelling to work. Just over a quarter of British workers, however, had both worked from home and travelled to work in the last seven days. Although less common than only travelling to work, hybrid working has generally been more popular than only working at home since around Spring 2022, and is possibly one of the most enduring impacts that COVID-19 had on the labor market. Demographics of homeworkers While advancements in internet connectivity and communication software have enabled more people to work from home than ever before, there are still obvious disparities in the share of homeworkers by industry. Over half of the UK’s agriculture workforce in 2020 regularly worked from home, compared with just 5.6 percent of those that worked in accommodation or food service. In the same year, the region with the highest share of people working from home was South West England at 18.3 percent, while Northern Ireland had the lowest at just 9.4 percent.

*The dataset is a collection of data undertaken by the members of Work Package 2 (WP2), of the ASPIRE COVID-19 project, funded by the Economic and Social Research Council (ESRC), as part of UK Research and Innovation’s rapid response to COVID-19 [grant number ES/V004581/1]. Full details of the main study are available via ResearchRegistry (researchregistry5911) and via UKRI Gateway (https://gtr.ukri.org/projects?ref=ES%2FV004581%2F1). This dataset contains interviews (n=13) with leads (stakeholders in maternal and neonatal care) in relevant national governmental, professional, and service user organisations in the Netherlands (See section WP2 – point 3). *13 anonymised semi-structured interviews – transcribed (NL only). *The relevant UK dataset can be found here: https://doi.org/10.17030/uclan.data.00000319

UK policy is for safe, personalised maternity care. However, during COVID-19 tests and visits have been reduced in some places, and some women with worrying symptoms are not going to hospital. Other places are trying new solutions, including remote access technologies. Some Trusts have reduced community maternity services, including home and birthcentre births; barred birth companions in early labour; and separated mothers, babies, and partners during labour, and in neonatal units. There are reports of women giving birth at home without professional help, possibly due to fear of infection, or of family separation. In contrast, the Netherlands has a policy of increased community maternity services during COVID-19. We want to find out how best to provide care for mothers, babies, and partners during and after a pandemic. We will look at what documents and national leads say about service organisation in the UK and the Netherlands, and at women's and parents experiences. We will also look in detail at what happened in 8 UK Trusts during the pandemic. We will find out how their services have been organised during COVID-19, what parents and staff think, and what the outcomes are, including infections. We will then share the findings with key stakeholders to agree a final organisational model that can be used to ensure safe, personalised routine and crisis maternity care, now, and in future. This will include useful resources and links relating to innovative best practices that we find out about during the study.

BackgroundLong-term health conditions can affect labour market outcomes. COVID-19 may have increased labour market inequalities, e.g. due to restricted opportunities for clinically vulnerable people. Evaluating COVID-19’s impact could help target support.AimTo quantify the effect of several long-term conditions on UK labour market outcomes during the COVID-19 pandemic and compare them to pre-pandemic outcomes.MethodsThe Understanding Society COVID-19 survey collected responses from around 20,000 UK residents in nine waves from April 2020-September 2021. Participants employed in January/February 2020 with a variety of long-term conditions were matched with people without the condition but with similar baseline characteristics. Models estimated probability of employment, hours worked and earnings. We compared these results with results from a two-year pre-pandemic period. We also modelled probability of furlough and home-working frequency during COVID-19.ResultsMost conditions (asthma, arthritis, emotional/nervous/psychiatric problems, vascular/pulmonary/liver conditions, epilepsy) were associated with reduced employment probability and/or hours worked during COVID-19, but not pre-pandemic. Furlough was more likely for people with pulmonary conditions. People with arthritis and cancer were slower to return to in-person working. Few effects were seen for earnings.ConclusionCOVID-19 had a disproportionate impact on people with long-term conditions’ labour market outcomes.

In 2020, employees who mainly worked from home had a sickness absence rate of 0.74 percent, as opposed to the 2.2 percent sickness absence rate of employees who never worked from home. The sickness absence rate for those employees that mainly work from home has been steadily declining since 2011. At the height of the first wave of the Coronavirus pandemic, in April 2020, almost half of UK workers were working from home, and just 31 percent of people were traveling to work.

In 2020, nearly 77 percent of employees with entry-level qualifications said that they were never working from home , as opposed to the 11.7 percent of higher degree qualified employees who said they were mainly working from home. At the height of the first wave of the Coronavirus pandemic, in April 2020, almost half of UK workers were working from home, and just 31 percent of people were traveling to work.

Abstract copyright UK Data Service and data collection copyright owner.

The Opinions and Lifestyle Survey (OPN) is an omnibus survey that collects data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).

Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules.

The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain.

From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers.

In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, 2019-2023: Secure Access. Other Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093).

From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable.

The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.

ONS Opinions and Lifestyle Survey, 2019-2023: Secure Access

The aim of the COVID-19 Module within this study was to help understand the impact of the coronavirus (COVID-19) pandemic on people, households and communities in Great Britain. It was a weekly survey initiated in March 2020, and since August 2021, as COVID-19 restrictions were lifted, the survey has moved to fortnightly data collection, sampling around 5,000 households in each survey wave. The study allows the breakdown of impacts by at-risk age, gender and underlying health condition. The samples are randomly selected from those that had previously completed other ONS surveys (e.g., Labour Market Survey, Annual Population Survey). From each household, one adult is randomly selected but with unequal probability: younger people are given a higher selection probability than older people because of under-estimation in the samples available for the survey.

The study also includes data for the Internet Access Module from 2019 onwards. Data from this module for previous years are available as End User Licence studies within GN 33441. Also included are data from the Winter Lifestyle Survey for January and February 2023.

Latest edition information

For the eleventh edition (March 2024), data and documentation for the main OPN survey for waves DN (June 2023) to EB (December 2023) have been added. Data and documentation for the Winter Lifestyle Survey for January-February 2023 have also been added.

The questions and topics covered by the main OPN survey have changed over time. Topics covered have included:

• health conditions
• concerns about work
• working from home
  
• understanding information about COVID-19
• actions undertaken to prevent the spread of the virus
• coping whilst staying at home and community support networks
• indicators of well-being and loneliness
• ways pandemic has effected life, work and finances
  
• caring responsibilities
• returning to school or college
  
• leaving home
• modes of transport used
• cost of living
  
• problems with companies
• vaccinations
  
• individual characteristics (e.g., age, gender, health conditions, qualifications, ethnicity, employment,...

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.

This collection of reports looks at the post COVID-19 consumer and how its affecting the consumer industry. The report included are: Future of Work in Consumer, Automated Home in Consumer, Direct-to-Consumer in Consumer Goods and Conversational Commerce in FMCG and City Growth Engines in Consumer. Read More

Abstract copyright UK Data Service and data collection copyright owner.BackgroundThe Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The Annual Population Survey, also held at the UK Data Archive, is derived from the LFS.The LFS was first conducted biennially from 1973-1983, then annually between 1984 and 1991, comprising a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter. From 1992 it moved to a quarterly cycle with a sample size approximately equivalent to that of the previous annual data. Northern Ireland was also included in the survey from December 1994. Further information on the background to the QLFS may be found in the documentation.The UK Data Service also holds a Secure Access version of the QLFS (see below); household datasets; two-quarter and five-quarter longitudinal datasets; LFS datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.LFS DocumentationThe documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned (the latest questionnaire available covers July-September 2022). Volumes are updated periodically, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.LFS response to COVID-19From April 2020 to May 2022, additional non-calendar quarter LFS microdata were made available to cover the pandemic period. The first additional microdata to be released covered February to April 2020 and the final non-calendar dataset covered March-May 2022. Publication then returned to calendar quarters only. Within the additional non-calendar COVID-19 quarters, pseudonymised variables Casenop and Hserialp may contain a significant number of missing cases (set as -9). These variables may not be available in full for the additional COVID-19 datasets until the next standard calendar quarter is produced. The income weight variable, PIWT, is not available in the non-calendar quarters, although the person weight (PWT) is included. Please consult the documentation for full details.Occupation data for 2021 and 2022 data filesThe ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.2024 ReweightingIn February 2024, reweighted person-level data from July-September 2022 onwards were released. Up to July-September 2023, only the person weight was updated (PWT23); the income weight remains at 2022 (PIWT22). The 2023 income weight (PIWT23) was included from the October-December 2023 quarter. Users are encouraged to read the ONS methodological note of 5 February, Impact of reweighting on Labour Force Survey key indicators: 2024, which includes important information on the 2024 reweighting exercise.End User Licence and Secure Access QLFS dataTwo versions of the QLFS are available from UKDS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes country and Government Office Region geography, 3-digit Standard Occupational Classification (SOC) and 3-digit industry group for main, second and last job (from July-September 2015, 4-digit industry class is available for main job only).The Secure Access version contains more detailed variables relating to:age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent childfamily unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of familynationality and country of originfiner detail geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district, and other categories;health: including main health problem, and current and past health problemseducation and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeshipsindustry: including industry, industry class and industry group for main, second and last job, and industry made redundant fromoccupation: including 5-digit industry subclass and 4-digit SOC for main, second and last job and job made redundant fromsystem variables: including week number when interview took place and number of households at addressother additional detailed variables may also be included.The Secure Access datasets (SNs 6727 and 7674) have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. Weighting variablesUsers should note that this quarter includes the 2023 person and income weights, PWT23 and PIWT23. Main Topics:The QLFS questionnaire comprises a 'core' of questions which are included in every survey, together with some 'non-core' questions which vary from quarter to quarter.The questionnaire can be split into two main parts. The first part contains questions on the respondent's household, family structure, basic housing information and demographic details of household members. The second part contains questions covering economic activity, education and health, and also may include a few questions asked on behalf of other government departments (for example the Department for Work and Pensions and the Home Office). Until 1997, the questions on health covered mainly problems which affected the respondent's work. From that quarter onwards, the questions cover all health problems. Detailed questions on income have also been included in each quarter since 1993. The basic questionnaire is revised each year, and a new version published, along with a transitional version that details changes from the previous year's questionnaire. Four sampling frames are used. See documentation for details.

“Home Office Monetization – Demand Dynamics, Solutions and Bundling Approaches for Telcos in the New Working Environment” is a new Global Outlook Report by GlobalData that provides an executive-level overview of the trends, telco business and residential value propositions and positioning strategies for the Home Office Hub. It delivers qualitative and quantitative insights into the impact of COVID-19 on home workers and telco solutions. It analyzes key demands of the home office trends and provides insights into telco activity, positioning and value propositions. Read More

BackgroundThe COVID-19 pandemic changed the way many industries work, including contact centres, with some employees working from home and new on-site restrictions/measures in place representing even greater challenges for employers around staff engagement and wellbeing. This study aimed to understand the interplay of individual, social, environmental and organisational factors influencing physical activity and sedentary behaviour in UK contact centre employees, how the pandemic impacted these factors, and their relevance for the future of hybrid working.MethodsIndividual interviews (n = 33) were conducted with participants (staff working full and part time, on site and from home) from four UK contact centres. A topic guide based on the ecological model was developed to understand current barriers and facilitators to physical activity and (reducing) sedentary behaviour during and outside of working hours. Thematic analysis was carried out using a codebook and a deductive coding approach to identify themes.ResultsThree key insights are provided. First, participants felt they were generally sitting more and moving less since the first UK-wide lockdown. Second, factors which negatively impacted on these behaviours were evident across all levels of the ecological model. These included individual and social barriers (e.g., lack of motivation and preferable physical activity options) as well as environmental and organisational barriers (e.g., poor home office setup, back-to-back virtual meetings). There were a mix of new and existing barriers (exacerbated by the pandemic) and several of these were linked to homeworking. Third, organisational support requirements (e.g., homeworking ergonomic support) and existing facilitators (such as the provision of informational support and flexible working arrangements) were identified.ConclusionSolutions to reduce sedentary behaviours and increase physical activity in contact centres need to address barriers from the individual to the organisational level. Whilst the study was undertaken in the UK, the results are like to be applicable globally.Trial registrationClinical trial registration: The trial for the wider project has been registered on the ISRCTN database: http://www.isrctn.com/ISRCTN11580369.