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Peer-reviewed

Research Article

The varying impacts of COVID-19 and its related measures in the UK: A year in review

Roles Conceptualization, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft

* E-mail: [email protected]

Affiliation Department of Sociology, University of Oxford, Oxford, United Kingdom

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Roles Funding acquisition, Writing – review & editing

  • Muzhi Zhou, 
  • Man-Yee Kan

PLOS

  • Published: September 29, 2021
  • https://doi.org/10.1371/journal.pone.0257286
  • Peer Review
  • Reader Comments

Fig 1

We examine how the earnings, time use, and subjective wellbeing of different social groups changed at different stages/waves of the pandemic in the United Kingdom (UK). We analyze longitudinal data from the latest UK Household Longitudinal Survey (UKHLS) COVID study and the earlier waves of the UKHLS to investigate within-individual changes in labor income, paid work time, housework time, childcare time, and distress level during the three lockdown periods and the easing period between them (from April 2020 to late March 2021). We find that as the pandemic developed, COVID-19 and its related lockdown measures in the UK had unequal and varying impacts on people’s income, time use, and subjective well-being based on their gender, ethnicity, and educational level. In conclusion, the extent of the impacts of COVID-19 and COVID-induced measures as well as the speed at which these impacts developed, varied across social groups with different types of vulnerabilities.

Citation: Zhou M, Kan M-Y (2021) The varying impacts of COVID-19 and its related measures in the UK: A year in review. PLoS ONE 16(9): e0257286. https://doi.org/10.1371/journal.pone.0257286

Editor: Florian Fischer, Charite Universitatsmedizin Berlin, GERMANY

Received: October 13, 2020; Accepted: August 27, 2021; Published: September 29, 2021

Copyright: © 2021 Zhou, Kan. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All data files are available from the UK Data Service database (study number(s) 6641, 8644). Dat file URL: https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=8644 https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=6641 .

Funding: This work is supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (awardee: Man-Yee Kan, grant number 771736). Funding website: https://ec.europa.eu/programmes/horizon2020/en . The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

More than one year has passed since the United Kingdom (UK) officially announced its first national lockdown on 23 March 2020 due to the rapid spread of COVID-19. The outbreak of COVID-19 and the massive lockdown measures have greatly changed people’s lives. When people were instructed to stay at home and maintain physical distancing, the lives of millions of people were affected. For months, many people were unable to go to work or school, nor could they meet friends and relatives. What was unexpected was that people in the UK experienced a total of three national lockdowns over the past year. Now, people’s lives are far from what they were before the first lockdown, and the pandemic is still not over.

Recent evidence has shown that the COVID-19 pandemic and related social and economic measures, such as physical distancing and business closure, have differential impacts on various social groups. In the UK, for example, women and parents are found to have experienced a larger reduction in subjective wellbeing [ 1 , 2 ]. Black, Asian, and minority ethnic (BAME) immigrants were more likely to experience economic hardship immediately after the first national lockdown [ 3 ]. In addition, among those who were known to have COVID-19, people of BAME background in the UK had a death rate that was higher than that of white people [ 4 ]. As Damian Barr said in his poem, “we are in the same storm, but we are not all in the same boat [ 5 ]”.

These earlier findings identified the existence of immediate unequal impacts for different social groups, but our understanding of the longer-term impacts of COVID-19 and related measures remains limited. We know little about how the impacts might have changed since the first lockdown. The COVID-19 pandemic has already lasted for more than one year, and the UK has experienced three national lockdowns. Early research was confined by data that covered only two time points—such as before and shortly after the announcement of the first lockdown. Little is known about to how unequal social impacts reveal themselves at different stages of the COVID-19 pandemic, especially with repeated lockdowns. This omission hinders our understanding of how COVID-19 and COVID-induced social policies, such as physical distancing measures, working from home, and the closure of certain businesses, which have been changing on a weekly or even daily basis, progressively affect people’s lives. Documenting the development of the impacts of COVID-19 and COVID-induced measures is important for us to understand the consequences of this rapidly developing pandemic and help policymakers plan for future waves and future pandemics.

We need more comprehensive and up-to-date research on how inequalities have changed as the COVID-19 pandemic develops with repeated waves and the various measures to contain it were implemented over the past year. We conducted analyses on a nationally representative population data from the latest UK Household Longitudinal Survey (UKHLS), which was conducted before the first lockdown in March 2020, during the first lockdown from April to June 2020, during the ease of the first lockdown (June to September 2020), and during the later two lockdowns (November 2020, and from January 2021 to March 2021). In this paper, we contribute to COVID-19 research by providing a dynamic picture of how people’s labor earnings, time use, and wellbeing changed across different stages of the pandemic. We further investigated whether and the extent to which the inequalities in these outcomes based on gender, ethnicity, and educational level have changed over the past year.

In what follows, we first review the latest works on the impact of COVID-19 and COVID-induced measures on people’s lives, focusing on three dimensions of social inequality: gender, race/ethnicity, and education. We then outline the development of the COVID-19 pandemic and the lockdown measures in the UK from March 2020 to April 2021. Next, we introduce the data and its longitudinal design, which enables us to compare the information of the same individuals before the start of this pandemic and at different time points over the past year. Finally, we will report the results of fixed-effect regression analyses and discuss our conclusions.

The impacts of COVID-19 and its related measures

The COVID-19 pandemic has developed for over one year. In many countries, repeated waves of COVID-19 have been observed. The primary aim of COVID-19 induced measures is to contain the virus by reducing physical contacts between people. Many of these measures immediately affect people’s behaviors, but others could have longer-term impacts. For example, the closure of businesses and work-from-home guidance tremendously altered people’s working patterns. Reductions in paid work time and earnings have been immediately recorded in countries that have introduced lockdown measures such as Australia [ 6 ], the UK [ 3 , 7 ], and the United States (US) [ 8 ]. When more people stayed at home and the option of outsourcing domestic work was reduced due to business closure or the fear of contracting COVID-19, it is not surprising to see that people spent substantially more time on unpaid domestic work than they had in the past [ 6 , 7 , 9 , 10 ].

People’s feelings also changed. The contraction of COVID-19 is associated with a series of symptoms such as a high temperature, continuous cough and a loss or change to the sense of smell or taste. Serious cases will result in hospital admission and death. In the UK, the case-fatality rate is estimated to be 2.1% [ 11 ]. Daily news reporting the surging number of new cases and deaths brings in a high level of worry about health and security [ 2 ]. In addition, loss of employment, financial strain, and social isolation are well-known factors that negatively affect mental health [ 12 – 14 ]. Not surprisingly, soon after the start of the pandemic, worsened subjective wellbeing was observed in Australia [ 6 , 15 ], the UK [ 2 , 16 , 17 ], and the US [ 18 ]. Once daily increase of COVID-19 cases declined and the lockdown restrictions began to be lifted, people’s subjective wellbeing started to recover. As Pierce et al. [ 2 ] noted by using the first five waves of the same UKHLS COVID study data as in this paper, “[b]etween April and October 2020, the mental health of most UK adults remained resilient or returned to pre-pandemic levels.” However, “[a]round one in nine individuals had deteriorating or consistently poor mental health.”

This COVID-19 pandemic and its related measures have raised increasing concerns of exacerbated social inequalities. Since long before the pandemic, gender inequalities have existed in the labor market. In the UK, the labor force participation rate for men is higher than that for women, and men are also much more likely to work full time [ 9 , 19 ]. Women are more likely to be at-home workers. Reasons for this inequality include inflexible workplace expectations, gender norms expecting men to be the primary earners and women the primary caregivers, and discrimination in the labor market. When people are required to work from home, the spatial boundary between market work and family life is blurred. Many studies have investigated whether the changes in time use due to lockdown measures are the same for women and men. Between March and May 2020 (UK 1st lockdown), British men were found to be more likely to be furloughed or dismissed from work than women [ 20 ]. However, studies focusing on the labor market performance of parents reveal a different pattern. In the UK, during the first lockdown period from April to May 2020, among parents with children aged between 4 and 15, mothers were found to be more likely to be laid off, furloughed, or quit their jobs [ 21 ]. Similarly, in Australia [ 6 ], Canada [ 22 ], and the US [ 23 ], mothers with young children experienced a larger change in their paid work time or were more likely to leave their jobs. On the other hand, several studies have reported improvements in the domestic division of labor: the increase in domestic work was larger for men than for women during the lockdown period in Australia [ 6 ], Canada [ 24 ], France [ 25 ], and the US [ 26 ]. However, contrary results were reported in Germany [ 27 ] and Spain [ 28 ]. The decline in subjective wellbeing also differs between women and men. In the UK and Australia, women were found to experience a larger reduction in subjective wellbeing than men [ 1 , 2 , 6 , 9 , 29 ].

In the UK, BAME immigrants were more likely to experience economic hardship just after the first lockdown [ 3 ]. Compared with their white counterparts, BAME immigrants were also found to suffer a larger decline in subjective wellbeing at the beginning of the March 2020 lockdown in the UK [ 3 , 30 ]. In the US state of Indiana, Black Americans were more than three times more likely to lose their jobs than whites [ 31 ]. In contrast, another study highlights that white Britons in middle-income jobs were more likely to experience job loss, primarily driven by the fact that many BAME people are employed in key sectors such as the health and social care services, which were exempt from the lockdown measures and instead had a surge in work demands, during the first UK lockdown [ 20 ]. Notably, in the UK, people of BAME backgrounds had a death rate that was higher than that of white people after they were confirmed to have COVID-19 [ 4 ].

People with less education and lower income suffered substantially during the pandemic. They were particularly hit hard with a higher chance of losing their jobs and earnings in countries such as Canada [ 32 ], the UK [ 20 ], and the US [ 31 ]. Many of the less educated are trapped in lower-skilled occupations with tight financial constraints. Consequently, the less educated group reported a heightened level of distress during the first lockdown in the UK [ 33 ]. However, one US study reports that the decline in subjective wellbeing up to April 2020 was larger among the more educated, possibly because the more educated might have felt a greater loss of control and wealth due to COVID-19-related uncertainties [ 18 ]. Another study conducted in the US between April 2020 and June 2021 pointed out that part of the reason for the deterioration of mental health results should be attributed to the concurrent presidential election and unrest in domestic politics [ 34 ].

Again, the current literature has focused extensively on the impacts of the relatively early stage of this pandemic. In particular, studies that have employed the same British data source as the present study have examined the changes in earnings, time use, and subjective wellbeing during the implementation of the first national lockdown in late March 2020 [ 3 , 7 , 9 , 10 , 20 ]. Pierce et al.’s work [ 2 ] on subjective wellbeing is an exception. Their work examined the recovery of subjective wellbeing when the first lockdown measures were eased from June to October 2020. However, their study did not cover the later lockdowns in November 2020 and January 2021. In this article, we will provide a first-year review of COVID-19 development in the UK and document how people have responded to the first lockdown, the ease of the first lockdown, and the later two lockdowns. This evaluation will reveal whether people responded similarly to repeated lockdowns and whether these changes in earnings, time use, and feelings are temporary or long-lasting.

Timeline of the lockdown measures in the UK

On 31 January 2020, the first two positive cases of COVID-19 were confirmed in the UK. On 5 March 2020, the first patient who tested positive for COVID-19 died. On 23 March 2020, the Prime Minister placed the UK on lockdown to slow down the outbreak of this pandemic. These measures included physical distancing, school closures, working from home, and closure of non-essential businesses, including pubs and cafes. Key sectors, including health and social care, education and childcare, and key public services, were allowed to operate.

To maintain employment and to protect individuals and businesses from economic hardship, a coronavirus job retention scheme was implemented for the period between late March and the end of October 2021 to cover 80 percent of the regular salary of furloughed employees, up to a maximum of £2,500 per month [ 35 ]. In April, the UK had more than 10,000 deaths related to COVID-19. In May, phased reopening of shops and schools was announced, and those who were unable to work from home were expected to return to the workplace.

Beginning on 1 June 2020, schools were open for all Reception, Year 1 and Year 6 pupils, but the summer holiday soon arrived. Nonessential businesses reopened gradually beginning on 15 June. Beginning on 4 July, pubs, cinemas, restaurants reopened. Physical distancing rules were relaxed from a “two-meter” to a “one-meter plus” rule. In August, restrictions were eased further, although the pandemic was far from over.

The UK variant of the coronavirus (scientific name B.1.1.7, WHO name Alpha) was first identified in September 2020 and was considered to be more transmissible and potentially deadlier. In late September, people were required to work from home with a 10 pm curfew for the hospitality sector. In October, England entered a 3-tier system where different regions were classified into different tiers depending on the level of the spread of the virus. Soon after, the second national lockdown came into force on 5 November and lasted until 2 December. People were told to stay at home. Other measures included the closure of the hospitality sector and nonessential shops, but schools were open, and people could leave their home for outdoor exercise. After 2 December, the UK then entered a stricter 3-tier restriction system.

However, this 3-tier system did not last long. After Scotland announced a lockdown, on 4 January 2021, a third national lockdown was announced. Schools were closed again, and people were urged to stay at home. This time, the measures were stricter than those in the second lockdown. They included “Stay at home at all times, wherever possible,” “Not allowed to meet others from outside your household (or support bubble),” “All retail and hospitality venues must close,” and “Personal care services have to close.” Schools were closed to most pupils, except for the children of critical workers and the most vulnerable children. Nurseries were kept open.

Since 8 March, schools in the UK have been completely reopened. Nonessential retail and personal care services have been reopened since 12 April. People have been allowed to meet outdoors, as a number of restrictive measures have been lifted since 17 May. A complete easing will occur on 19 July 2021. The Prime Minister has pledged that all adults in the UK will be offered their first dose of a COVID-19 vaccine by the end of July.

By 16 April 2021, the recorded number of deaths related to COVID-19 had reached over 127,000 in the UK. Fig 1 displays the spread of COVID-19 and related deaths in the UK during the research period. A more detailed timeline of the UK lockdowns can be found at [ https://www.instituteforgovernment.org.uk/sites/default/files/timeline-lockdown-web.pdf ]. Fig 1 shows the development of the COVID-19 pandemic in the UK based on data provided by the UK government.

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Note: Data source: https://coronavirus.data.gov.uk/details . Crude death rate is new deaths within 28 days of a positive test per 100,000 population.

https://doi.org/10.1371/journal.pone.0257286.g001

Data and methods

Data and sample.

We use data from the first eight waves of the UKHLS COVID study data and the preceding two waves (2017/18 and 2018/19) of the UKHLS main survey [ 36 ]. The UKHLS is a household panel survey and started its first wave in 2009 with a nationally representative sample of 51,000 adults (aged 16 and above) from approximately 40,000 households. Individuals were followed up annually and were interviewed face-to-face. This research is based completely on the UKHLS data that are publicly available through the UK Data Service (Study numbers: 6614 and 8644) and are completely anonymous.

Regarding the COVID study, households who participated in previous UKHLS surveys were contacted to fill in a monthly online questionnaire beginning in April 2020. The complementary telephone survey started in May 2020. Participation in the survey was voluntary. Approximately 16,000 respondents (aged 16 and above) completed this first wave of the COVID survey with a response rate of 42%. Currently, data from the first eight waves of surveys conducted in the last week in April, May, June, July, September, November in 2020 and the last week in January and March in 2021 are available.

Our analytic sample contains individuals who have participated in the UKHLS main survey and at least one of the eight waves of the COVID study. The respondents all had access to the internet or telephone to participate in the surveys. This requirement might have caused a sample selection bias. In a supplementary analysis, the sample from the COVID study is found to be socioeconomically advantaged in terms of employment, occupation, education, and homeownership compared to the full UKHLS sample. If we assume that one’s socioeconomic status has a protective effect on the negative consequences of the COVID-19 and related lockdown measures, the reported results may underestimate the potential negative impacts of the COVID-19 and the related lockdown. Nonetheless, one paper discusses this issue of nonrandom sample selection and demonstrates that the bias due to sample selection is very limited once weight is considered [ 37 ]. In the following analysis, we apply the individual weights, which were adjusted for “unequal selection probabilities and differential nonresponse” and are supplied in the data [ 38 ]. Based on the User Guide for the data, these weights “scale respondents to the eligible population in the UKHLS wave 9 sample, adjusted for death, incapacity and emigration occurring between wave 9 and the start of the COVID-19 web survey.” [ 38 ] This approach has been used in previous work analyzing the same data [ 2 , 3 , 20 ].

Our sample includes respondents of prime working age (between 20 and 65) in 2020. Two percent of the UKHLS COVID sample has missing values in the predictors to be used in regressions. The numbers of observations with no missing predictors are 10484, 9008, 8478, 8210, 7642, 7083, 7019, and 7525 in the first eight waves of the COVID study. The final sample for each regression is dependent on the outcome variables with nonmissing values (some outcome variables are not asked in certain waves) and the selection of subgroups (for example, people who had a job before the pandemic). Please refer to S1 Table for more details of the sample selection process. The focus on within-individual changes in the outcome variables indicates that the respondents should be followed up for more than one wave. Previous analyses using the same data and selecting the individuals interviewed for more than one wave do not find that this selection would bias the results [ 39 ].

Monthly labor income, weekly paid work hours, subjective wellbeing, weekly housework hours, and weekly childcare hours are the five dependent variables or outcomes of interest.

Monthly labor income.

Respondents’ labor income in January or February 2020 (before the lockdown) was collected retrospectively in the COVID survey. Respondents also provided their current labor income in each month thereafter. We calculate the natural log of the labor income. Those who had a job in January or February 2020 were selected to predict this outcome.

Weekly paid work hours.

Respondents retrospectively reported their current paid work hours per week and their usual working hours in January or February 2020. During the period of the COVID-19 pandemic, the question asked was “How many hours did you work, as an employee or self-employed, last week?” During the prepandemic period, the question was “During January and February 2020, how many hours did you usually work per week?” Those who had a job in January or February 2020 were selected to predict this outcome.

Subjective wellbeing.

Subjective wellbeing is the mental wellbeing reported by the respondents in a General Health Questionnaire (GHQ). The value is the sum of 12 items (GHQ-12) scored on a Likert scale from 0 to 3: “ability to concentrate,” “losing sleep,” “playing a useful role in life,” “capability of making decisions,” “feeling under stress,” “overcoming difficulties,” “ability to enjoy activities,” “ability to face problems,” “feeling unhappy or depressed,” “losing confidence,” “believing in self-worth,” and “feeling generally happy.” The overall scale ranges from 0 (least distressed) to 36 (most distressed). This measurement is a validated and widely used measure of nonspecific mental distress in surveys [ 40 ]. The same information was collected in earlier waves of the main survey of the UKHLS and in each wave of the COVID study. The full sample was used to predict this outcome.

Weekly housework hours.

Respondents’ weekly housework hours were collected by the question “Thinking about last week, how much time did you spend on housework, such as time spent cooking, cleaning and doing the laundry?” Information about housework hours before the COVID survey was derived from the earlier UKHLS waves (the latest one was collected in the years between 2018 and 2019). The full sample was used to predict this outcome.

Weekly childcare hours.

Respondents’ childcare hours were collected by the question “About how many hours did you spend on childcare or home-schooling last week?” This information is only available in the COVID survey. Only those who had a child younger than 16 years old in the household (referred to as parents in later analyses) were asked this question, and these respondents are used for analyses.

Independent variables.

We include the wave dummies, which represent the time point when information was collected to examine the dynamics in those outcome variables.

The key socioeconomic independent variables are constant for the same individual across the waves. These variables are gender (52.7% females), whether an individual is Black, Asian or another minority ethnic (10.1%) or not (reference group: whites), and educational level (university degree holders 32.2%). The underrepresentation of ethnic minority groups is common in a panel survey sample (the 2011 census reported that 85.6% of the working-age people were from white ethnic groups) because of the selection of people with repeated observations to satisfy the requirement of the fixed-effect models. People with disadvantaged backgrounds are known to be more likely to drop out in repeated surveys [ 41 ]. The later regression analysis has considered this sample selection issue using weights, as discussed above. Moreover, attrition in panel surveys is not found to have a significant impact on the estimations in predicting income [ 42 ], time use [ 43 ], or attitudes [ 44 ].

Whether the respondent had a positive COVID-19 test outcome was asked in each wave. We included this variable in the model to control for the impact of contracting COVID-19 so that the period indicators could better represent the spread of COVID-19 and COVID-19-related policy change at the macro-level. This variable has four categories: “having no test” (reference, 89.7%), “tested positive” (0.8%), “tested negative” (9.0%), and “result pending” (0.5%).

All models controlled for respondents’ partnership status (whether they live with a partner) and parenthood status (the presence of a child younger than age 16 in the household) to account for potential changes in the family status that are correlated with the outcomes [ 45 , 46 ].

Analytical strategies

We applied linear fixed-effect regressions to predict the five outcomes. By interacting the month indicator with gender, BAME group, and education levels, we examined how the change in income, time use, and wellbeing differed across individuals in the three different sociodemographic groups in different periods of the pandemic. The reference time point is January and February 2020 for earnings and weekly paid work hours outcomes. The reference time point is the year 2018/2019 for the subjective wellbeing (distress level) and weekly housework hours outcomes. For weekly childcare hours, the reference time point is April 2020, which was during the first national lockdown. The outcome variables compare the information reported by the same individuals at each time point and hence reveal within-person changes. This analytic approach enabled us to investigate trajectories of the outcome variables over the past year conditional on the same individual.

The fixed-effect regression method takes full account of the time-constant individual characteristics that are correlated with both the independent variable and the outcome variables. This is achieved by demeaning the dependent and independent variables using person-specific means [ 47 ].

The samples in the UKHLS main survey and the COVID survey are probability samples of postal addresses. The samples are clustered and stratified. Accordingly, clustered standard errors are used to consider this sampling design [ 48 ].

These analyses were conducted in Stata/SE 16.1. Replication codes are available at https://github.com/jomuzhi/ukcovidunderstandingsociety .

Descriptive results

We first report the weighted mean values of the key outcomes in Table 1 . Please note that the information was collected at the end of each survey month.

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https://doi.org/10.1371/journal.pone.0257286.t001

First, among those who worked before this pandemic (between January and February 2020), there was a clear reduction in their average earnings when the pandemic started in the UK. Their income recovered by almost ten percent in May from the April level, which should have been mainly driven by the implementation of the job retention scheme . Some workers who could not work from home, such as those working on construction sites, also returned to the workplace in May. Since then, average monthly net earnings have remained at approximately the level of £1,550. Notably, since the first lockdown, people’s take-home earnings has never returned to their prepandemic level but never fell below 90% of the pre-pandemic level.

Before the pandemic, those who worked in January and February 2020 worked 34.7 hours per week on average. A record low of 21.9 hours per week was observed in April 2020. The persistent decline in paid work time over the past year is evident, although working hours have recovered gradually since May and reached a peak of approximately 30 hours per week in September 2020. The later two national lockdowns (November 2020 and January 2021) did not reduce the working hours as much as the first national lockdown. Weekly paid work hours were maintained at approximately 28 hours.

People felt more distressed beginning in March 2020. The worst number of 13.4 was recorded in the last two rounds of lockdown-November 2020 and January 2021, when new cases and deaths grew sharply at the beginning of these lockdowns.

People’s housework hours increased and reached the highest level of 12.3 hours per week in April and May 2020. Then, housework time declined gradually and was maintained at 10.5 hours per week. Compared with the figure recorded in September 2020 when most lockdown restrictions were eased, the figure in January 2021 did not change significantly, even though a stricter lockdown was in place. This finding concurs with the small reduction in paid work hours from September 2020 to January 2021.

The average childcare hours per week reached 16.7 hours for parents in April, but this figure gradually declined to approximately 13 hours per week before the third national lockdown. In January 2021, childcare hours only increased 0.5 hours per week over the September figure, even though schools were closed to most pupils during the third lockdown. Overall, people’s time use had become less responsive to repeated lockdowns.

Changes in earnings, paid work time, subjective wellbeing, housework and childcare time

Fig 2 reports within-individual changes in earnings, paid work hours, distress level, and housework hours across waves. The red lines indicate the time point when the national lockdowns started to enforce. Please note that the information was collected at the end of each survey month. Detailed coefficients are reported in S2 Table .

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https://doi.org/10.1371/journal.pone.0257286.g002

Respondents’ earnings stayed lower than the pre-pandemic level over the entire year, with the largest decline (~9%) recorded in late April, the first month after the announcement of the first national lockdown. Earnings recovered slightly after the gradual relaxation of restrictive measures and the implementation of the job retention scheme. Following the third lockdown, when almost the same strict measures as the first lockdown were imposed, we found a similar level of decline in earnings (~8%) compared with the prepandemic period, as in the first lockdown. One year after the onset of the pandemic in the UK, our sample still experienced a 7.4% decline in earnings compared with the pre-pandemic level.

Paid work hours remained much lower than the prepandemic level over the entire year. The largest drop of nearly 13 hours was observed in the first month after the March 2020 lockdown. Then, paid work hours recovered and have never returned to the same lowest point. People worked the longest hours in September 2020, when restrictive measures were minimal. Interestingly, despite the implementation of the second and the stricter third national lockdowns, paid work hours dropped only slightly compared to the September figure and were even higher than the July 2020 figure, even though all shops were allowed to open back in July 2020. This observation suggests an increased adaptation to the work-from-home practice. After the first lockdown, more firms announced a long-term strategy to allow employees to work from home [ 49 ]. Accordingly, people have increased their paid work time even though they might still work from home.

In this pandemic, people’s subjective well-being has been damaged. The distress level (a higher score indicating more distress) stayed higher than the prepandemic level over the past year. In the three-month period after the first lockdown, a high level of distress was recorded. An improvement in subjective wellbeing was observed from July and before the enforcement of the second lockdown. The November lockdown brought a further decline in subjective wellbeing, which is consistent with the findings in one earlier study [ 2 ]. The distress level in November 2020 and January 2021 was even higher than that in the first lockdown period. It appears that people were much less optimistic and suffered tremendously as the pandemic dragged longer. People became slightly less negatively affected in their subjective wellbeing in March 2021, although the level was only similar to that in April 2020. One year after the onset of the pandemic in the UK, respondents’ subjective wellbeing returned to the level of April 2020, which was one month after the announcement of the first national lockdown.

The increase in housework hours was the highest during the first lockdown. Compared with the housework hours during the easing period in September 2020, the January 2021 lockdown was not associated with an increase in people’s housework time. This change echoes the relatively high level of paid work time in the later two lockdown periods.

Next, we examine childcare time since the first national lockdown. In Fig 3 , we can see that beginning in April 2020 (during the first lockdown period), childcare hours have been dropping. The lowest level was observed in September 2020, when schools completely reopened. Interestingly, childcare hours in January 2021 were similar to those in September 2020, despite the closure of schools to most children in January 2021.

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https://doi.org/10.1371/journal.pone.0257286.g003

Differential impacts on women and men

Figs 4 and 5 report whether changes in the five indicators differ between women and men. For monthly net earnings and weekly paid work hours, we analyzed an additional sample that includes only non-key workers. We will examine whether a disproportionate number of female workers in certain key sectors, such as health and social care, drive the results.

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https://doi.org/10.1371/journal.pone.0257286.g004

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https://doi.org/10.1371/journal.pone.0257286.g005

First, the reduction in earnings for female workers (those who worked in Jan/Feb 2020) was smaller than that for male workers during the first lockdown in April 2020 (p = 0.011). Since then, there has been no difference between women and men in changes in earnings, reflecting the faster recovery of men’s earnings. Differential impacts on women and men were not found among non-keyworkers. Therefore, the higher proportion of women working in key sectors, which were operating much more actively than other sectors during the first lockdown period, should be the main reason for the gender difference in the earning decline during the first lockdown.

During the first lockdown, the decline in paid work hours was smaller for female workers than for male workers, disregarding their keyworker status (p<0.001). The gender difference in the reduction in paid work hours decreased as the first lockdown ended and became statistically insignificant at the 0.05 level from July to September 2020, indicating a faster recovery of paid work time for men than for women. The differential impacts of gender on paid work hours observed in the first lockdown were not observed in later lockdowns among non-keyworkers.

In Fig 5 , the growth in distress level was much higher for women than for men in the first month of the first lockdown (p<0.001). Then, women’s subjective wellbeing recovered, and men’s distress levels began to rise. These findings suggest that men’s response to this pandemic lagged behind that of women in terms of their subjective wellbeing in the first lockdown. The distress level of both women and men was reduced to the lowest level from July to September 2020, when life in general had returned to normal. Once the cases of COVID-19 surged and lockdown restrictions were reimposed in November 2020 (p = 0.056) and January 2021 (p = 0.061), women again suffered from a larger increase in distress levels than men. The distress level of women reached a similar high point across the three lockdowns. For men, their distress level was higher in the later lockdowns than in the first lockdown, when the cases of COVID-19 and its related deaths worsened.

We do not observe a gender-specific impact on housework time. The gender gap in housework time was maintained over the past year.

Differential impacts on BAME people and white people

Figs 6 and 7 report whether changes in the five indicators differ between BAME people and whites. For monthly net earnings and weekly paid work hours, we analyzed an additional sample that includes only non-key workers.

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https://doi.org/10.1371/journal.pone.0257286.g006

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https://doi.org/10.1371/journal.pone.0257286.g007

Compared with whites, the earnings of the BAME group were particularly negatively affected by the pandemic. The differential impacts on earnings persisted across almost all months over the past year, except during the third lockdown. The gap was large even when most lockdown restrictions were eased in September 2020 (p = 0.003). The earning gap between the BAME group and whites was even larger among non-key workers. Over the past year, the decline in market working time was similar for the BAME group and whites in both the full and the non-key worker samples. In March 2021, the reduction in paid work time decreased less for the BAME group than for the whites (p = 0.006).

Regarding the distress level ( Fig 7 ), the increase for the BAME group was larger than that for whites during the first lockdown, but the difference was not statistically significant at the 0.05 level due to the large standard error of the estimates of the BAME group. Beginning in September 2020, the changes in the distress levels were similar for the BAME group and whites. The increase in housework hours seems to be larger for the BAME group, but the large standard errors prevent us from drawing a reliable conclusion.

Differential impacts on degree and non-degree holders

Figs 8 and 9 report whether changes in the five indicators differ between degree and non-degree holders. For monthly net earnings and weekly paid work hours, we analyzed an additional sample that includes only non-key workers.

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https://doi.org/10.1371/journal.pone.0257286.g008

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https://doi.org/10.1371/journal.pone.0257286.g009

As expected, the decline in earnings and paid work hours was particularly acute among non-degree holders. These differential impacts were even larger among non-key workers. When the spread of the virus decreased and most of the restrictive measures eased from July to September 2020, the difference in the impacts on non-degree and degree holders became smaller but was sustained. For paid work hours, the difference was insignificant between July and September 2020 for both the full and the non-keyworker samples. Once restrictive measures were reimposed, the difference became substantial again (p<0.001).

As Fig 9 shows, there was no significant difference in the change in subjective wellbeing between degree and non-degree holders before January 2021. However, degree holders experienced a larger increase in distress level during the third national lockdown that started in January 2021 (p = 0.028), but the differential effect disappeared in March 2021.

We do not observe a statistically significant difference in the changes in housework time between the two groups.

Changes in weekly childcare hours since April 2020

Fig 10 reports whether changes in the weekly childcare hours differ across these groups.

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https://doi.org/10.1371/journal.pone.0257286.g010

Our findings show that women and men, BAME people and whites, and degree and non-degree holders did not differ significantly in changes to their childcare time since April 2020. However, there is a tendency that the reduction in childcare time in September, which should be associated with pupils returning to schools after summer vacation, was larger for mothers and the more educated group, suggesting that women and the more educated might have spent more time taking care of children at home.

For more details of the results, please refer to S2 – S5 Tables. The within-individual R-squares are small when predicting earnings, subjective wellbeing, housework time, and childcare time. Small within-individual R-squares are not uncommon in fixed-effect regressions, especially when predicting housework time and subjective wellbeing [ 50 , 51 ]. These results suggest that a limited number of individuals have changed their partnership and parenthood status and COVID-test results, but their outcome variables—earnings, time use, and subjective wellbeing-have changed considerably over the past year. The inclusion of more time-varying variables might be able to improve the explanatory power. Those variables could be whether furloughed, whether participated in the job retention scheme, or whether went back to work/school. However, the purpose of this paper is to provide an overall net impact of COVID-19 and its related measures on an individual instead of focusing on a specific policy or the spread of COVID-19. Given the focus on the trajectories of earnings, time use, and subjective wellbeing at different stages of the pandemic, we do not include those time-varying variables suggested above.

Discussion and conclusion

In this article, we have utilized the latest UK COVID panel data to provide a comprehensive analysis of the dynamics of earnings, time use, and subjective wellbeing at different stages of the pandemic over the past year. Our research, with a much extended time scope, surpasses past UK studies that only followed a short period after the first lockdown imposed in March 2020 [for example, 3, 7, 9, 20]. Our analysis has incorporated multiple domains of outcomes across several social groups. We aim to examine how the spread of COVID-19 and COVID-induced policies have had unequal and dynamic impacts on different social groups in the UK. Our findings offer important insights into whether inequalities in changes in income, time use and wellbeing are likely to be long lasting or temporary.

Overall, the initial outbreak of COVID-19 and the first national lockdown brought the largest change in earnings and time use. The later two lockdowns together with the repeated new highs of the COVID-19 cases and deaths impacted people’s subjective wellbeing the most. Although strict measures that aimed to reduce people’s physical contact were imposed in the later two lockdowns, people’s time use did not respond as strongly as they did during the first lockdown. Among the five indicators, none had returned to their prepandemic level until late March 2021. It remains uncertain when and whether earnings, working patterns, family life, and subjective wellbeing will return to the prepandemic level.

Female workers experienced less reduction in their earnings than male workers, which is largely due to the relatively high proportion of women working in key sectors, especially in the health and social care industry. Women have made an important contribution to the fight against COVID-19 by working in key sectors. However, even among non-key workers, the decline in paid work hours was smaller for women but only during the first lockdown period. These findings concur with earlier research that reported that men in the UK were more likely than women to be laid off or furloughed during the first lockdown [ 20 ]. Once lockdown measures were gradually lifted beginning in June 2020, men’s paid work time recovered faster than that of women. This finding is similar to previous work on the gendered impact of natural disasters on market labor [ 52 ]. In summary, our analysis has shown that in the UK, men’s paid work time was more responsive to the restrictive measures of the first lockdown, but women’s and men’s paid work time responded similarly in the later two lockdowns.

The subjective wellbeing of women was more sensitive to the outbreak of COVID-19 and related lockdown measures than that of men. For example, the increase in women’s distress level was substantial in April, but it then gradually improved until the next lockdown. Men’s responses lagged behind of those of women. Past COVID-19 research has highlighted the gender difference in social networks, where women tend to have more friends [ 29 ]. The larger exposure to news related to COVID-19 for those with more close friends might be the factor that explains the diverging trajectories of women’s and men’s subjective wellbeing [ 53 , 54 ]. Theses differential impacts became smaller in later two lockdowns, as the pandemic had developed for a certain period. At the beginning of the pandemic, women and men seemed to have perceived the danger of this infectious disease differently.

The gender gap in housework time was maintained over the past year. Overall, the gender-specific changes in earnings, paid work time, and subjective wellbeing were mainly observed when strict restrictions were in place, and the gender gap returned to its prepandemic level once those measures were lifted.

People of a BAME background experienced a larger loss in earnings than whites. This finding is consistent with an earlier finding on BAME immigrants in the UK [ 3 ]. We have further shown that the enlarged earning gaps between BAME and white people persisted almost over the entire year.

Persistently enlarged earning gaps were observed between non-degree and degree holders. The gap was even larger among non-key workers. Non-degree holders suffered from a larger reduction in earnings across all months over the past year. This gap was particularly large during the national lockdown periods. A similar observation was found for weekly paid work hours. The spread of COVID-19 and lockdown restrictions are associated with an enlarged gap in paid work time between non-degree and degree holders. This effect on paid work time is likely to be temporary because differential impacts were not observed from July to September 2020, when lockdown measures were mostly lifted.

One limitation of this study is that some changes could be brought by seasonal fluctuations beyond COVID-19 and its related restrictions. For example, people’s paid work time in winter may differ from that in summer. General psychological health was usually worse in winter than in summer [ 55 ]. The ideal solution is to compare information collected in the same month before the pandemic and in 2020. However, this approach is not possible with the current data. If the current survey retains the current monthly or bimonthly data collection frequency, future work can compare the same month in 2020 and the years after to examine pandemic and post-pandemic differences. We have also included the measure of the spread of COVID-19 (daily new cases or daily new death rates, as shown in Fig 1 ) to examine whether the outcomes are affected by the macrolevel development of the COVID-19 pandemic in the UK. We do not find strong evidence showing that those measures are associated with the outcomes. Our results reveal the trajectories of earnings, time use, and subjective wellbeing at different time points over the past year but cannot identify the exact impact of a specific lockdown restrictive policy. There could be other non-COVID-19-related policy updates that occurred in parallel over the past year that may have had an impact on the same outcomes. Nonetheless, the trends of the observed changes in income, time use, and subjective wellbeing corresponded closely to the different waves of the pandemic and the lockdown timeline. Therefore, the major sources of those changes should be related to the spread of COVID-19 and its related lockdown measures.

In conclusion, our findings suggest that the long-lasting pandemic and the related restrictions to contain the virus over the past year have produced persistent negative consequences for earnings, work patterns, and subjective wellbeing. The spread of COVID-19 and the national lockdowns at different stages had distinct patterns and measures, and their impacts on labor earnings, time use and subjective well-being varied. Time use patterns became less sensitive to the later lockdowns, but the distress levels reached a new high with repeated lockdowns in multiple waves of the pandemic. The differential impacts of the lockdown measures based on gender became insignificant once lockdown measures were lifted. However, some social groups, including BAME and white people and non-degree holders and degree holders, experienced persistently enlarged gaps in earnings. The negative impacts of the spread of COVID-19 and its related measures vary not only in their extent but also in their speed among different social groups. Further research should be conducted to understand factors that have driven these social inequalities and to monitor how inequalities based on gender, educational level, and ethnic minority status might be persistent or even exacerbated in the long term.

Supporting information

S1 table. samples and sample selection..

https://doi.org/10.1371/journal.pone.0257286.s001

S2 Table. Baseline model: Changes in the five indicators across waves.

https://doi.org/10.1371/journal.pone.0257286.s002

S3 Table. Gender and period interaction model results.

https://doi.org/10.1371/journal.pone.0257286.s003

S4 Table. Ethnicity and period interaction models.

https://doi.org/10.1371/journal.pone.0257286.s004

S5 Table. Education and period interaction model results.

https://doi.org/10.1371/journal.pone.0257286.s005

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Essay and dissertation writing skills

Planning your essay

Writing your introduction

Structuring your essay

  • Writing essays in science subjects
  • Brief video guides to support essay planning and writing
  • Writing extended essays and dissertations
  • Planning your dissertation writing time

Structuring your dissertation

  • Top tips for writing longer pieces of work

Advice on planning and writing essays and dissertations

University essays differ from school essays in that they are less concerned with what you know and more concerned with how you construct an argument to answer the question. This means that the starting point for writing a strong essay is to first unpick the question and to then use this to plan your essay before you start putting pen to paper (or finger to keyboard).

A really good starting point for you are these short, downloadable Tips for Successful Essay Writing and Answering the Question resources. Both resources will help you to plan your essay, as well as giving you guidance on how to distinguish between different sorts of essay questions. 

You may find it helpful to watch this seven-minute video on six tips for essay writing which outlines how to interpret essay questions, as well as giving advice on planning and structuring your writing:

Different disciplines will have different expectations for essay structure and you should always refer to your Faculty or Department student handbook or course Canvas site for more specific guidance.

However, broadly speaking, all essays share the following features:

Essays need an introduction to establish and focus the parameters of the discussion that will follow. You may find it helpful to divide the introduction into areas to demonstrate your breadth and engagement with the essay question. You might define specific terms in the introduction to show your engagement with the essay question; for example, ‘This is a large topic which has been variously discussed by many scientists and commentators. The principle tension is between the views of X and Y who define the main issues as…’ Breadth might be demonstrated by showing the range of viewpoints from which the essay question could be considered; for example, ‘A variety of factors including economic, social and political, influence A and B. This essay will focus on the social and economic aspects, with particular emphasis on…..’

Watch this two-minute video to learn more about how to plan and structure an introduction:

The main body of the essay should elaborate on the issues raised in the introduction and develop an argument(s) that answers the question. It should consist of a number of self-contained paragraphs each of which makes a specific point and provides some form of evidence to support the argument being made. Remember that a clear argument requires that each paragraph explicitly relates back to the essay question or the developing argument.

  • Conclusion: An essay should end with a conclusion that reiterates the argument in light of the evidence you have provided; you shouldn’t use the conclusion to introduce new information.
  • References: You need to include references to the materials you’ve used to write your essay. These might be in the form of footnotes, in-text citations, or a bibliography at the end. Different systems exist for citing references and different disciplines will use various approaches to citation. Ask your tutor which method(s) you should be using for your essay and also consult your Department or Faculty webpages for specific guidance in your discipline. 

Essay writing in science subjects

If you are writing an essay for a science subject you may need to consider additional areas, such as how to present data or diagrams. This five-minute video gives you some advice on how to approach your reading list, planning which information to include in your answer and how to write for your scientific audience – the video is available here:

A PDF providing further guidance on writing science essays for tutorials is available to download.

Short videos to support your essay writing skills

There are many other resources at Oxford that can help support your essay writing skills and if you are short on time, the Oxford Study Skills Centre has produced a number of short (2-minute) videos covering different aspects of essay writing, including:

  • Approaching different types of essay questions  
  • Structuring your essay  
  • Writing an introduction  
  • Making use of evidence in your essay writing  
  • Writing your conclusion

Extended essays and dissertations

Longer pieces of writing like extended essays and dissertations may seem like quite a challenge from your regular essay writing. The important point is to start with a plan and to focus on what the question is asking. A PDF providing further guidance on planning Humanities and Social Science dissertations is available to download.

Planning your time effectively

Try not to leave the writing until close to your deadline, instead start as soon as you have some ideas to put down onto paper. Your early drafts may never end up in the final work, but the work of committing your ideas to paper helps to formulate not only your ideas, but the method of structuring your writing to read well and conclude firmly.

Although many students and tutors will say that the introduction is often written last, it is a good idea to begin to think about what will go into it early on. For example, the first draft of your introduction should set out your argument, the information you have, and your methods, and it should give a structure to the chapters and sections you will write. Your introduction will probably change as time goes on but it will stand as a guide to your entire extended essay or dissertation and it will help you to keep focused.

The structure of  extended essays or dissertations will vary depending on the question and discipline, but may include some or all of the following:

  • The background information to - and context for - your research. This often takes the form of a literature review.
  • Explanation of the focus of your work.
  • Explanation of the value of this work to scholarship on the topic.
  • List of the aims and objectives of the work and also the issues which will not be covered because they are outside its scope.

The main body of your extended essay or dissertation will probably include your methodology, the results of research, and your argument(s) based on your findings.

The conclusion is to summarise the value your research has added to the topic, and any further lines of research you would undertake given more time or resources. 

Tips on writing longer pieces of work

Approaching each chapter of a dissertation as a shorter essay can make the task of writing a dissertation seem less overwhelming. Each chapter will have an introduction, a main body where the argument is developed and substantiated with evidence, and a conclusion to tie things together. Unlike in a regular essay, chapter conclusions may also introduce the chapter that will follow, indicating how the chapters are connected to one another and how the argument will develop through your dissertation.

For further guidance, watch this two-minute video on writing longer pieces of work . 

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Academic writing

Advice and resources to support you with effective academic writing.

Approaches to writing

Assignment writing is a process which involves planning, drafting and reviewing what you are going to say. You will find you need to review your initial plan and edit it as you go along. You should expect to have to redraft some sections of writing.

You should also check any guidance given to you as part of your course , as conventions vary between subject areas.

One of the hardest things can be to get started writing an assignment. Sometimes this is a question of taking the time to reflect on what you are being asked to do in the assignment brief. 

Getting started with an assignment

The handout Getting started suggests a way in which you can break down your task, think about aspects of it and commit some of your initial ideas to paper. It also suggests ways you can start to adapt this method to suit you. Alternatively you may prefer to use a prompt list to start to analyse your title.

Getting started (pdf)       Getting started (Word rtf)

Essay title prompts (pdf)       Essay title prompts (Word rtf)

You will want to respond to the assignments you have been set as well as you can. This means paying attention to key words in the question or assignment brief. These are sometimes known as command or directive words because they tell you what to do. The document Directive words provides definitions of some of the commonly used words.

Directive words (pdf)       Directive words (Word rtf)   Directive words – British Sign Language translation (Media Hopper video)

Getting your ideas in order

In any written assignment you will be expected to organise and structure information which is synthesised from a range of sources. You will need to make notes from your readings to help you consolidate and connect your research to your question. The Reading at university page has strategies to help you develop effective skills for making notes from reading.

Reading at university

Making notes means you end up with lots of bits of writing which you need to link together for your reader. Sometimes it can be hard to know what to select and how to identify relationships between ideas and concepts.

There are suggestions in the Getting your ideas in order handout of practical ways in which you might reorganise your material in response to the task set. Playing around with the order can help you arrive at a line reasoning that will convince the reader. Aim to experiment and find out what works for you.

Getting your ideas in order (pdf)           Getting your ideas in order (Word rtf)

Essay parts and paragraphs

If you have been asked to write an academic essay, and you haven't done this before, you may be unsure of what is expected. The Parts of an essay handout gives a brief introductory overview of the component parts of an essay.

Parts of an essay (pdf)           Parts of an essay (Word rtf)

Paragraphs are the building blocks of an essay and are a way of organising your thinking and making your meaning clear in your writing for your reader . The handout Developing writing in paragraphs encourages you to think about the way you shape your paragraphs and when to move on to a new one.

Developing writing in paragraphs (pdf)          Developing writing in paragraphs (Word rtf) 

Build an argument as you go

Identifying and writing about good evidence is not enough. You need to build an argument. An argument is:

Using reasons to support a point of view, so that known or unknown audiences may be persuaded to agree. Cottrell, S. (2011) Critical thinking skills: developing effective analysis and argument. 2nd edn. Basingstoke: Palgrave Macmillan, p52.

You can develop your argument as you read and write by creating a working hypothesis or basic answer in response to the assignment brief.  

Building an argument as you go (pdf)            Building an argument as you go (Word rtf)

As you move through your studies lecturers will expect more from your written work. They will expect the accurate attribution of ideas from others (including academic and other authors, and the ideas of those who teach you). There is general advice and resources for referencing and citations (and avoiding plagiarism) on the Referencing and citations page.

Referencing and citations

Your marker(s) will expect written pieces to be logically structured with fluid expression of thought, and with deeper and more critical engagement with the subjects and ideas you are reading and learning about. 

Aim to become familiar with the level of writing required by reading good quality examples.  At an advanced level you are aiming to write to the style you read in academic journals. 

As your written tasks become longer and more complex it can be helpful to reflect on your own writing process.

Reflect on your writing process (pdf)            Reflect on your writing process (Word rtf)

Different types of academic writing

Academic writing is much more than just an essay. You might be asked to write a lab or business report, a policy brief, a blog post, a journal article or a reflection piece for example. These tend to be subject and task specific so you need to check the assignment brief and any criteria for details of their purpose, formatting, structure, things to include etc.

Reflective academic writing

In some subjects, assessment may be based on critical reflection. This can be a challenge as it is a very particular style and form of writing which you may not have come across before. As well as check your assignment brief for specifics, the University’s Employability Consultancy have created a Reflection Toolkit of resources, models and questions to help you develop your reflective writing skills.

The Reflection Toolkit

School-level support

Take advantage of any writing development sessions organised through or learning materials offered by your School, Deanery or course. These will help you develop the specific writing skills you need for your discipline or subject area.

Writing your own title

If you have to write your own title in response to the brief you have been set, you need to think about how to frame this.  The Formulating your own title handout suggests some aspects to consider.

Formulating your own title (pdf)          Formulating your own title (Word rtf)

Differences from non-academic writing

If you are studying during a career break, or part-time while still working, you need to be aware that academic writing is a very different skill from other forms of writing you may have done in the workplace. Academic writing tends to be more formal, requiring succinct prose rather than bullet points, and it is more about the argument than simply conveying, or describing, information. Writing for assessment requires you to think carefully about your assignment and criteria, your argument and content, use of your subject specific conventions (e.g. language, style etc.), and your audience.

Your written work needs to be grounded in and backed up by appropriate and informed opinion and sources, rather than solely by personal opinion and experience. Academic written work will also make fewer absolute statements. Language is often more tentative or cautious.

Academic Phrasebank is a collection of general phrases taken from academic sources created by John Morley at the University of Manchester. The phrases are sorted into writing and assignment themes such as being critical and writing conclusions.

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How to get published in an academic journal: top tips from editors

Journal editors share their advice on how to structure a paper, write a cover letter - and deal with awkward feedback from reviewers

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Writing for academic journals is highly competitive. Even if you overcome the first hurdle and generate a valuable idea or piece of research - how do you then sum it up in a way that will capture the interest of reviewers?

There’s no simple formula for getting published - editors’ expectations can vary both between and within subject areas. But there are some challenges that will confront all academic writers regardless of their discipline. How should you respond to reviewer feedback? Is there a correct way to structure a paper? And should you always bother revising and resubmitting? We asked journal editors from a range of backgrounds for their tips on getting published.

The writing stage

1) Focus on a story that progresses logically, rather than chronologically

Take some time before even writing your paper to think about the logic of the presentation. When writing, focus on a story that progresses logically, rather than the chronological order of the experiments that you did. Deborah Sweet, editor of Cell Stem Cell and publishing director at Cell Press

2) Don’t try to write and edit at the same time

Open a file on the PC and put in all your headings and sub-headings and then fill in under any of the headings where you have the ideas to do so. If you reach your daily target (mine is 500 words) put any other ideas down as bullet points and stop writing; then use those bullet points to make a start the next day.

If you are writing and can’t think of the right word (eg for elephant) don’t worry - write (big animal long nose) and move on - come back later and get the correct term. Write don’t edit; otherwise you lose flow. Roger Watson, editor-in-chief, Journal of Advanced Nursing

3) Don’t bury your argument like a needle in a haystack

If someone asked you on the bus to quickly explain your paper, could you do so in clear, everyday language? This clear argument should appear in your abstract and in the very first paragraph (even the first line) of your paper. Don’t make us hunt for your argument as for a needle in a haystack. If it is hidden on page seven that will just make us annoyed. Oh, and make sure your argument runs all the way through the different sections of the paper and ties together the theory and empirical material. Fiona Macaulay, editorial board, Journal of Latin American Studies

4) Ask a colleague to check your work

One of the problems that journal editors face is badly written papers. It might be that the writer’s first language isn’t English and they haven’t gone the extra mile to get it proofread. It can be very hard to work out what is going on in an article if the language and syntax are poor. Brian Lucey, editor, International Review of Financial Analysis

5) Get published by writing a review or a response

Writing reviews is a good way to get published - especially for people who are in the early stages of their career. It’s a chance to practice at writing a piece for publication, and get a free copy of a book that you want. We publish more reviews than papers so we’re constantly looking for reviewers.

Some journals, including ours, publish replies to papers that have been published in the same journal. Editors quite like to publish replies to previous papers because it stimulates discussion. Yujin Nagasawa, c o-editor and review editor of the European Journal for Philosophy of Religion , philosophy of religion editor of Philosophy Compass

6) Don’t forget about international readers

We get people who write from America who assume everyone knows the American system - and the same happens with UK writers. Because we’re an international journal, we need writers to include that international context. Hugh McLaughlin, editor in chief, Social Work Education - the International Journal

7) Don’t try to cram your PhD into a 6,000 word paper

Sometimes people want to throw everything in at once and hit too many objectives. We get people who try to tell us their whole PhD in 6,000 words and it just doesn’t work. More experienced writers will write two or three papers from one project, using a specific aspect of their research as a hook. Hugh McLaughlin, editor in chief, Social Work Education - the International Journal

Submitting your work

8) Pick the right journal: it’s a bad sign if you don’t recognise any of the editorial board

Check that your article is within the scope of the journal that you are submitting to. This seems so obvious but it’s surprising how many articles are submitted to journals that are completely inappropriate. It is a bad sign if you do not recognise the names of any members of the editorial board. Ideally look through a number of recent issues to ensure that it is publishing articles on the same topic and that are of similar quality and impact. Ian Russell, editorial director for science at Oxford University Press

9) Always follow the correct submissions procedures

Often authors don’t spend the 10 minutes it takes to read the instructions to authors which wastes enormous quantities of time for both the author and the editor and stretches the process when it does not need to Tangali Sudarshan, editor, Surface Engineering

10) Don’t repeat your abstract in the cover letter We look to the cover letter for an indication from you about what you think is most interesting and significant about the paper, and why you think it is a good fit for the journal. There is no need to repeat the abstract or go through the content of the paper in detail – we will read the paper itself to find out what it says. The cover letter is a place for a bigger picture outline, plus any other information that you would like us to have. Deborah Sweet, editor of Cell Stem Cell and publishing director at Cell Press

11) A common reason for rejections is lack of context

Make sure that it is clear where your research sits within the wider scholarly landscape, and which gaps in knowledge it’s addressing. A common reason for articles being rejected after peer review is this lack of context or lack of clarity about why the research is important. Jane Winters, executive editor of the Institute of Historical Research’s journal, Historical Research and associate editor of Frontiers in Digital Humanities: Digital History

12) Don’t over-state your methodology

Ethnography seems to be the trendy method of the moment, so lots of articles submitted claim to be based on it. However, closer inspection reveals quite limited and standard interview data. A couple of interviews in a café do not constitute ethnography. Be clear - early on - about the nature and scope of your data collection. The same goes for the use of theory. If a theoretical insight is useful to your analysis, use it consistently throughout your argument and text. Fiona Macaulay, editorial board, Journal of Latin American Studies

Dealing with feedback

13) Respond directly (and calmly) to reviewer comments

When resubmitting a paper following revisions, include a detailed document summarising all the changes suggested by the reviewers, and how you have changed your manuscript in light of them. Stick to the facts, and don’t rant. Don’t respond to reviewer feedback as soon as you get it. Read it, think about it for several days, discuss it with others, and then draft a response. Helen Ball, editorial board, Journal of Human Lactation

14) Revise and resubmit: don’t give up after getting through all the major hurdles

You’d be surprised how many authors who receive the standard “revise and resubmit” letter never actually do so. But it is worth doing - some authors who get asked to do major revisions persevere and end up getting their work published, yet others, who had far less to do, never resubmit. It seems silly to get through the major hurdles of writing the article, getting it past the editors and back from peer review only to then give up. Fiona Macaulay, editorial board, Journal of Latin American Studies

15) It is acceptable to challenge reviewers, with good justification

It is acceptable to decline a reviewer’s suggestion to change a component of your article if you have a good justification, or can (politely) argue why the reviewer is wrong. A rational explanation will be accepted by editors, especially if it is clear you have considered all the feedback received and accepted some of it. Helen Ball, editorial board of Journal of Human Lactation

16) Think about how quickly you want to see your paper published

Some journals rank more highly than others and so your risk of rejection is going to be greater. People need to think about whether or not they need to see their work published quickly - because certain journals will take longer. Some journals, like ours, also do advance access so once the article is accepted it appears on the journal website. This is important if you’re preparing for a job interview and need to show that you are publishable. Hugh McLaughlin, editor in chief, Social Work Education - the International Journal

17) Remember: when you read published papers you only see the finished article

Publishing in top journals is a challenge for everyone, but it may seem easier for other people. When you read published papers you see the finished article, not the first draft, nor the first revise and resubmit, nor any of the intermediate versions – and you never see the failures. Philip Powell, managing editor of the Information Systems Journal

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  • Published: 08 February 2024

Evaluating the impact of the supporting the advancement of research skills (STARS) programme on research knowledge, engagement and capacity-building in a health and social care organisation in England

  • Gulshan Tajuria   ORCID: orcid.org/0000-0001-5559-0333 1 , 2 ,
  • David Dobel-Ober   ORCID: orcid.org/0000-0001-8457-4148 1 ,
  • Eleanor Bradley   ORCID: orcid.org/0000-0001-5877-2298 3 ,
  • Claire Charnley 1 ,
  • Ruth Lambley-Burke   ORCID: orcid.org/0000-0003-0416-6908 1 ,
  • Christian Mallen   ORCID: orcid.org/0000-0002-2677-1028 1 , 2 ,
  • Kate Honeyford 1 &
  • Tom Kingstone   ORCID: orcid.org/0000-0001-9179-2303 1 , 2  

BMC Medical Education volume  24 , Article number:  126 ( 2024 ) Cite this article

302 Accesses

Metrics details

To evaluate the impact a novel education programme - to improve research engagement, awareness, understanding and confidence - had on a diverse health and social care workforce. Barriers and facilitators to engagement were explored together with research capacity-building opportunities and ways to embed a research culture. The programme is entitled ‘Supporting The Advancement of Research Skills’ (STARS programme); the paper reports findings from a health and social care setting in England, UK.

A four-level outcome framework guided the approach to evaluation and was further informed by key principles of research capacity development and relevant theory. Quantitative data were collected from learners before and after engagement; these were analysed descriptively. Semi-structured online interviews were conducted with learners and analysed thematically. A purposive sample was achieved to include a diversity in age, gender, health and social care profession, and level of attendance (regular attendees, moderate attendees and non-attenders).

The evaluation spanned 18 half-day workshops and 11 seminars delivered by expert educators. 165 (2% of total staff at Midlands Partnership University NHS Foundation Trust (MPFT)) staffs booked one or more education sessions; 128 (77%) including Allied Health Professionals (AHPs), psychologists, nursing and midwifery, and social workers attended one or more session. Key themes of engagement with teaching sessions, relevance and impact of training and promoting a research active environment were identified with relevant sub-themes. Positive impacts of training were described in terms of research confidence, intentions, career planning and application of research skills as a direct result of training. Lack of dedicated time for research engagement, work pressures and time commitments required for the programme were key barriers. Facilitators that facilitated engagement are also described.

Conclusions

Findings demonstrate the impact that a free, virtual and high-quality research education programme had at individual and organisational levels. The programme is the product of a successful collaboration between health and social care and academic organisations; this provides a useful framework for others to adapt and adopt. Key barriers to attendance and engagement spoke to system-wide challenges that an education programme could not address in the short-term. Potential solutions are discussed in relation to protecting staff time, achieving management buy-in, recognising research champions, and having a clear communication strategy.

Peer Review reports

Research has played a pivotal role in the advancement of health and social care by, for example, informing early diagnosis, the development and testing of new treatments for prevention, cure, recovery and palliative care [ 1 ]. The importance of research is heralded by key health and social care bodies in the UK, the context for this paper. The UK Government policy paper on clinical research delivery identifies the need to: ‘support healthcare professionals to develop research skills relevant to their clinical role and to design studies in ways which ensure delivering research is a rewarding experience, rather than an additional burden’ [ 2 ]. The Chief Nursing Officer for England’s strategic plan for research also emphasises the importance of developing a culture where research is relevant to all nurses, either through direct involvement or the use of research evidence as a key element in professional decision-making [ 3 ]. Similarly, the Royal College of Physicians [ 4 ] states that healthcare providers should see research as an integral element in care delivery, and to emphasise its ongoing commitment to social care research, the NIHR became the ‘National Institute for Health and Care Research’ in April 2022. The response from the research community to the Covid-19 pandemic has further boosted the impetus and appetite for health and social care to embed global and multi-disciplinary research strategies for the future [ 5 ].

Having sufficient research capacity and capability is important to enabling health and social care services and workers to translate research into practice [ 6 ]. However, inequalities exist in so far as research is not perceived as accessible and inclusive by all. Several studies describe workplace barriers including time [ 4 , 7 , 8 ] resources, such as access to published research [ 8 , 9 ] and lack of research knowledge, experience and expertise, both in terms of carrying out their own research and putting the findings of published research into practice [ 9 ]. Some professional groups describe lack of access to relevant training as a barrier to developing research knowledge and skills, (e.g. nurses [ 8 , 9 , 10 ]). Fry and Attawet [ 8 ] also identified a lack of organisational and management support for research linked to the absence of a culture that promotes research as an integral part of clinical practice. Thus, to nurture research engagement an individual (bottom-up) and service-level (top-down) approach to research capacity development (RCD) is necessary [ 11 ].

A recent evaluation of National Institute for Health and Care Research (NIHR) funding awards suggested that whilst funding could be transformative and contribute to a healthy research culture in health and care organisations, issues of inequality were identified by professionals working in specialisms with less research experience or expertise. These were in organisations without connections to more research-intensive universities and by those working in non-medical professional groups (e.g. Allied Health Professionals (AHPs), nurses) [ 12 ]. This was further highlighted by a study with social care staff, which found they valued research but showed low levels of engagement and skill [ 13 ]. Authors would like to highlight here that they recognise that social care staff and social workers provide different functions. Social workers aim, “to provide support for people to help them to deal with the personal and social issues which affect their lives”… whereas “Social care is one of the terms which is used to refer to the strategies which are used to help to care for people who are in need” [ 14 ]. Even though these terms may be used sometimes interchangeably they are different in terms of qualification required to attain the title and the duties they perform. A growing evidence base identifies the key mechanisms to support Research Capacity Development (RCD) in health and social care. A rapid evidence review [ 15 ] highlighted intrinsic factors (e.g. attitudes and beliefs) and extrinsic factors (such as recognition of research skills acquisition within career progression and professional development via professional bodies, creation of personal awards); and observation of impacts on practice as helpful to encourage NHS staff to engage with researcher development.

Context to the STARS programme

MPFT is a health and social care NHS trust with a track record in research delivery and is in the process of developing research leadership. At the time of writing, the NHS Trust had not achieved university hospital status, although it works closely with two universities which developed the STARS programme in partnership (see Fig.  1 and Supplementary File 1 for a full overview of the structure of the programme). The STARS programme provides a useful resource to address disparities in research engagement between different professional groups in health and social care. Despite more opportunities for research having been generated for nurses and AHPs by organizations such as the NIHR Collaborations for Leadership in Applied Health Research and Care (CLAHRCs) and Clinical Research Networks (CRNs), disparities persist between non-academic clinicians and the opportunities available to certain clinical specialities [ 16 , 17 , 18 ]. Challenges and barriers to research training engagement highlighted in this paper are likely to have global relevance [ 19 ]. Thus, more broadly, offering programmes such as STARS may also help address global disparities in research engagement given the UK has the highest percentage of doctors (28.6%) and nurses (15%) who are trained in foreign countries [ 20 ]. STARS was designed in consultation with staff to identify existing barriers to engagement in research training, provide all staff with improved access to high-quality research training to enhance their confidence in research and enable the best use of empirical evidence in practice. The STARS programme was launched in January 2021.

figure 1

Supporting the advancement of research skills (STARS) programme

This paper reports findings from the evaluation which aimed to evaluate the delivery of the STARS programme to assess delivery outcomes, understand learner experiences, facilitators and barriers to engagement, and future opportunities

The approach to evaluation of this training programme was informed by Kirkpatrick’s four-level outcome framework: reaction (was training enjoyed?), learning (did learning occur?), behaviour (did behaviour change?) and results (was performance effected?) [ 21 ]. As this is a new programme, data was gathered against the first three levels of Kirkpatrick’s evaluation model. Contemporary criticisms and revisions of the model were incorporated to better understand the chains of evidence and wider contextual factors that may influence the delivery of a new programme [ 22 ], such as the STARS programme.

Data collection

Quantitative data.

Data including information such as highest educational qualification, job role, the reason for attending and the line manager’s approval to attend the training was collected at the point learners registered for a teaching session. Data indicating service areas, rate of dropouts, staff backgrounds, highest and lowest rate of attendance was collected from the attendance record. Data was also collected using a brief post-session feedback (see Supplementary material - Learner Evaluation Form) form, which included a likert scale question inviting learners to rate the quality of the training.

Statistical analysis

Quantitative analysis was performed at a descriptive level, using Microsoft Excel (2016).

Qualitative methods

Semi-structured interviews were conducted with programme participants to explore learner experiences (aligned with Kirkpatrick’s reaction level), outcomes (learning) and intentions to apply research knowledge ( intended behaviours). Flexible interview formats were offered to encourage participation, such as online interviews and providing responses via email. Interviews were facilitated using a topic guide (see Supplementary material - STARS Interview Guide) that was iteratively revised.

Recruitment and sampling

A purposive sample of participants was identified using data from the programme booking form and attendance records:

Regular attenders: Those who attended a minimum of five teaching sessions across the whole programme or a single pathway.

Occasional attenders: Those who attended very few (1–2) sessions across the whole programme.

Non-attenders: Those who registered to attend, but eventually didn’t attend, to explore barriers to engagement.

Participants were invited by email for a maximum 30-minute interview. All potential participants were emailed a participant information sheet. They were given time to read the information and a contact name for any questions related to their participation, before being asked to confirm their participation in the study.

Description of sample

Thirty-six staff members were categorised as regular attenders; all were invited to take part in an interview. Two individuals declined to participate citing a lack of relevance, as they left their learning events halfway; two individuals declined due to work pressure following illness; three were ‘out of office’ according to email replies, and no response was received from 14 individuals. The remaining 15 agreed to participate in an interview with 10 choosing to use Microsoft Teams and five to provide written responses- ‘email interviews’. This method is becoming increasingly used to help supplement other forms of data and support involvement of healthcare professionals, who may have limited time/capacity for research but valuable knowledge to share [ 23 , 24 ]. Participants represented a diverse range of professional backgrounds, including: AHPs, psychologists, nursing and midwifery, and social workers; this reflected the broad range of learners on the programme. A semi-structured interview guide was used. The interviews were audio recorded and later transcribed in full by the lead author (GT).

Occasional ( n  = 17) and non-attenders ( n  = 13) were invited to participate in an interview. These were staff members who had booked several teaching sessions (1–12) but either did not attend any with/without apologies ( n  = 30) or attended only one or two. Seven email addresses were not valid as the staff had either left the service or changed role; four had an automated ‘out of office’ response set; four staff declined to participate and there was no response from 11 email addresses. Five staff agreed to be interviewed. A brief topic guide was used with questions aiming to find out just the reason/s behind non-attendance in the training. As these interviews were brief, non-verbatim notes were taken by the interviewer and included in analysis. At the end of each of these interviews, the notes were validated with the interviewee.

Qualitative analysis

The data analysis followed a thematic approach [ 22 ] to identify key themes. Data-driven coding was conducted to establish meaning from the words of participants; coding was also informed, a-priori, by the levels of the evaluation framework [ 25 ]. Initial coding was done by GT and TK who read all transcripts to support familiarisation before generating an initial set of codes. Right from initial codes to final themes, other than the authors, the wider STARS team gave input in various Team meetings. Similar codes were then compared and grouped to identify initial themes; these were reviewed to shape a preliminary set of main themes. Preliminary themes were shared and discussed with the team before finalising.

Quantitative findings

Over the 12-month evaluation period, a total of 18 half-day workshops were delivered, six from the research in clinical practice pathway; four from the research delivery pathway; eight from the research leader pathway (refer to Fig.  1 ); and 11 seminars to support the development of key skills. In total, 165 (2% of total staff at MPFT) staff members booked one or more teaching session. 128 (77%) attended one or more teaching session. On average, sessions in the research in practice pathway were attended by 25 staff; 12 in research delivery pathway; 21 in the research leader pathway; and 17 in seminars.

Qualifications, backgrounds and expectations

According to the booking form, attenders represented a range of professional groups.

Nursing registered − 29 (23%).

AHPs − 23 (17%).

Additional clinical services (all healthcare services) − 21 (16%).

Additional professional scientific and technical (such as pharmacist, qualified psychological therapist, social worker etc.) -15 (12%).

Medical profession − 14 (11%).

Other (e.g. research staff) − 26 (20%).

Approximately 85% of staff had reported prior educational qualifications, the majority included: 20% ( n  = 33) bachelor’s, 19% ( n  = 31) master’s, 3% ( n  = 5) doctoral degrees, 6% ( n  = 10) diplomas and nearly 2% ( n  = 3) MBBS (Bachelor of Medicine, Bachelor of Surgery); remaining attenders did not provide information on their educational background.

Explanations for booking the training and number of staff

At the time of booking the course, staff were asked to provide reasons and expectations from STARS sessions using an open text box. Descriptive analysis of responses is presented in Table  1 :

A better understanding of research in practice, additional support for academic work and the development of research in trust were the most common reasons provided (Table  1 ).

Post session evaluation feedback

Learners demonstrated their learning from the sessions in a variety of ways and more often using the session specific feedback. In total, 195 feedback forms were completed and covered 24 sessions. The number of ratings completed per session ranged from 1 to 25. 136 (70%) learners rated the session they attended as ‘very good’, 52 (27%) rated as ‘good’, 4 (2%) rated ‘adequate’ and 2 (1%) rated ‘poor’. Qualitative findings, presented below, help us to make sense of the session ratings.

Qualitative findings

The main themes and sub-themes from the analysis of qualitative data from interviews are summarised in Table  2 and described with illustrative quotes in the following sections.

Engagement with teaching sessions

The reasons given by staff attending the training in booking forms (Table  1 ) and discussed in interviews were reflected to a large extent in the way participants chose the teaching sessions they attended. Eight interviewees had received research training as part of their degree-level qualifications; one was currently involved in conducting research at work.

Factors considered while selecting teaching sessions

Some staff were much focused on what they wanted to take from teaching sessions and booked selectively; however, some wanted to attend all, indiscriminately, due to unequal access in such training opportunities in the past and/or in their departments:

“I wanted to do them all because my concern is that they might not be offered again because we’ve never had them in social care… we’ve never had researchers come and talk to us in social care and social work unless you go to Uni.” P 4.

Some staff described their learning as focused on intrinsic factors such as:

“It’s always good to update because I think you find your own way in doing things like informed consent. P 11.

For other staff, learning on the programme was driven by extrinsic factors like:

“Social work and social care does have a huge gap in terms of research participation. We are trying to develop that within the organization and regionally” P 13.

Relevance of a teaching session to the current role was considered before booking by staff who either had knowledge or were currently involved in doing research but the staff without previous opportunities like this booked relatively indiscriminately. Intrinsic factors such as personal interest and career progressions and extrinsic factors such as organisational development were additional reasons to attend the teaching sessions.

Barriers to attendance

Getting data from those who did not attend after booking proved difficult. Four staff declined to take part in evaluation interviews because of work pressure or illnesses; this may reflect some of the reasons for non-attendance. Another five agreed to take part in short interviews to discuss their lack of attendance with the programme. All interviewees pointed towards time pressure as the main issue.

Qualitative data from the interviews with the regular attenders about barriers to attending some of the training after booking revealed similarities in reasons as the non-attenders. A general lack of time due to staff shortages highlighted the role of the line manager’s approval in attending the training as discussed by two staff members:

“some sessions that I could not attend as my manager didn’t think I should attend so many sessions, because of the pressures of the service following the covid backlogs etc” P 5.

One staff member briefly raised the issues of empowerment where some staff might find it difficult to get the line manager’s approval to attend such training:

“And perhaps you need to get the buy in from the managers, because there’s an awful, awful lot of staff that aren’t really empowered to be able to go off and do this and then influence their work” P 7.

Communication and marketing of the new training was highlighted as a barrier to attendance by staff from one of the departments:

“I think one was probably in the promotion, I came across it by chance…that’s something to do with our organization because it kind of sits slightly outside of MPFT, so I think sometimes that messaging doesn’t always get through” P3 .

Prioritising paid training over STARS training was also a reason for one of the staff to miss some of the teaching sessions:

“I’ve missed some STARS trainings because of attending other trainings which are paid training or conferences that have cost money. So obviously I’ve prioritized them over some of the STARS training” P 9.

Barriers to engagement

Providing training across different professional groups highlighted difficulties in understanding respective languages. Two respondents reported that some content used clinical language that was difficult to understand:

“There’s also an element of understanding research and how it can be applied there’s probably an element of language as well, so it’s not just clinical…or health orientated, it’s also care. So it is just understanding that language barrier so that social work and social care staff know that it’s appropriate for everybody in the organization” P 13.

For one staff member the pace of delivering the graphic and statistical information teaching was very fast and difficult to understand:

“Sometimes it felt like the presenters for some statistical information went too fast when that was the area that most people are weaker on, so perhaps some courses tried to fit too much into one session” P 5.

A couple of staff discussed the workshops as disengaging due to long presentations and less interaction:

“the ones where you will just kind of like listening for three hours. They were really hard to stay engaged with” P 9.

For two staff the breakout rooms were not as helpful as explained by one:

“it can be awkward when you’re with people you don’t know and haven’t got a full grasp of the subject, and trying to think of contributions” P 5.

One staff also highlighted how attending the training from a shared office space can be problematic compared to a private space:

“As when doing it in the office, it’s harder to engage in group discussions due to fear of disrupting other colleagues” P 2.

Other ways of delivering the training were also suggested due to long commitments for the workshops. Two participants suggested that three-hour workshops were too long when delivered online; face-to-face learning was preferred:

“it would be nice to have it when we can to have some classroom based stuff because again, it just feels more natural to ask questions and you get to have those conversations in breaks” P 1.

And according to one participant, the training could be delivered using pre-recorded content:

“If there was a way to like the website on the Internet, all these links that you could click on to watch re-watch everything so you know where to go to one place to see all” P 6.

However, for two participants the recordings of teaching sessions were not as good as attending in real-time, as explained by one:

“You’re not the one engaging in it like because obviously you’re just watching it after the fact, so I don’t sit through the whole thing…If you’ve got questions, there’s nowhere to ask those questions” P 9.

Facilitators to engagement

Online synchronous delivery of the teaching sessions was valued by all interview participants, in the context of the Covid-19 pandemic. Use of breakout rooms for small group discussion and interaction was considered useful by most of the interview participants, for example:

“that was quite nice that you’d catch up with people that you were in the breakout rooms and could get to know a bit more about what they were doing and so I found that quite helpful from like a networking perspective” P 10.

Most of the staff members discussed keeping the recorded videos for future reference as very helpful:

“I know I’m not going to have time to apply myself to do in any sort of research at the moment with how things are at work, but I’ve got all the recordings and so could go back to those” P 10.

To summarise, barriers to attend the training included a lack of time on the participants’ end and lack of promotion. Perceived value due to no direct cost associated with the training was also revealed as a reason to miss a session after booking. Pace, professional-specific language, length of teaching and shared office space were highlighted as some of the barriers to engagement. Regarding facilitators to attend and maintain engagement, all staff were happy with online delivery and the availability of recordings was useful. However, mixed opinions were shared about the usefulness of breakout rooms given the range of professional groups that the staff belonged to.

Relevance and impact of training

Staff described various benefits to their research practice since attending STARS sessions, such as, writing and publishing a short report; working on a literature review; signing on to a university course; successfully receiving regulatory research approvals; and completing preliminary work to attend a professional doctorate or equivalent.

Training content relevance and suitability

All interview participants commented on the programme content and described it as comprehensive and well-balanced in terms of topics and delivery:

“I think it was really well balanced. The presenters came from diverse backgrounds and research was treated holistically by all, so everything felt relevant” P 12.

Impact on knowledge, skills and attributes

One participant described how learning was helpful to understand key areas in greater depth:

“I have an understanding of some critical appraisal and things like that, but it was probably more surface level and the STARS programme helped me to develop that quite significantly” P 1.

For another staff it helped with attending and presenting at different teaching sessions:

“So I’ve attended the regional teaching partnership programs we’ve presented our [name] project across [organisation] who are now looking at setting up a regional program. We’ve presented at NIHR events so yeah, definitely useful” P 13 .

The teaching sessions had a prompt impact on the knowledge and skills of those staff who already had some knowledge of research and also those who had identified specific opportunities to put into practice.

Applying new learning

Some learning on the training had wider applications that went beyond research, topics such as informed consent:

“Things like the informed consent training because for all our new staff that’s a major part of research. So from that we’ve drafted kind of a memoirs and processes formally based on sort of training materials on how an informed consent should be conducted so that we know that everybody starting at the same level” P 11.

Learning on one particular workshop helped to build a participant’s confidence in reading, making sense, and talking about research followed by conducting their own literature review:

“I used the literature review knowledge that I gained to do a very comprehensive literature review. Very rapid, quite comprehensive and then presented it. So I was able to put it into practice straight away” P 3 .

Overall, most of the participants mentioned using the new learning in practice but only a few staff members were able to provide practical examples.

Promoting a research-active environment

Staff discussed how they were using more resources from the organisation such as websites, the local research department, and library services in creating a research identity for themselves and contributing towards a research-active environment within and across their respective departments.

Research career pathways

The STARS programme helped to awaken ambitions for research and staff showed how keen they were on getting involved in doing research. Participants described doing their own research as a better option when other routes for progression were limited in their department:

“where I’m at in my role, there isn’t really anywhere to go unless you want to be a team leader, which isn’t really what I want to do. I really enjoy the patient facing side of things, and so I’ve always kind of said I’d be more interested in more specialized role or doing some research” P 10.

STARS was also useful in the stages of career development and for some it was helpful in starting the new paths as discussed by one:

“It’s either doing a feasibility or that sort of level today as part of a master’s course or doing their pre doctoral the NIHR sort of work to get a project effectively ready” P 6.

However, there was also a sense of being unfulfilled among some of the participants:

“I’d like to progress in it, but it’s where do I take it because I don’t know what opportunities are out there and how to apply for anything really” P 4.
“I’m really interested in doing some research in the area that I work in because I feel like there’s lots of improvements and things that could be made with how we do things and for the clients to get the most out of the service…I think with the STARS stuff I’ve sort of parked it so I’ve got it all saved together in a folder like ready so I can go and access it” P 10.

STARS opened up different routes for career progression for some staff. On the other hand, staff without immediate opportunities to get involved in research reported experiencing frustration because of the fact that there were no obvious opportunities for them to put their improved skills into practice. Success stories (going on a pre-doctoral path; progression for those who were already doing their master’s/doctorate etc.) of those who had some research base highlights the initiation of research identities.

Workforce satisfaction

In addition to feeling motivated to complete their academic qualifications, two staff members discussed how much they valued the STARS training and one participant described staying in their job, in order to access the training:

“I’ve not come across any other type of research training that is like is what the STARS programme offered. I purposely stayed within my role to access this stars training” P 9.

Improving awareness about research support services

The staff interviewees appreciated the associations to other support and resources that they had found out about while attending the STARS training. This included the library services and the R&I team:

“And the fact that our library helps us is phenomenal…So it’s given me a lot of knowledge about the wide organization and just how invested we are in research and that there are people [R&I] to help” P 7.

The STARS programme has been developed with contributions from different departments in order to make it suitable for all staff members to access and understand. This was reflected in the discussion where the interviewees appreciated the other links and resources.

The current paper reports findings from a mixed-methods study, which aimed to evaluate the delivery of a novel research training programme to health and social care staff in a single organisation in England (MPFT). The mixed methods approach generated key data against three of Kirkpatrick’s framework (reaction, learning and behaviour). Quantitative findings demonstrated good engagement with the programme from a diverse range of professional groups; a broad range of reasons were given for engagement. All of which demonstrates the broad appeal and initial reaction to the programme offer, particularly among professional groups who may not ordinarily engage in research (e.g. social care, nursing and midwifery staff). Ratings of session quality were very positive with 97% of ratings either very good or good. Qualitative findings highlighted three key themes: engagement with training, relevance, and impact of training, and promoting a research-active environment. Within these themes, positive reactions to training (e.g. appreciation, satisfaction, collaboration with others, access to new resources), evidence of learning (e.g. understanding critical appraisal) and change in behaviour through practical application (e.g. conducting a literature review) and sharing learning (e.g. networking) were identified. However, barriers still exist for many, including research terminology, limited capacity and the need for wider promotional campaigns.

Comparisons with findings from previous research in other areas and with elements of Gee and Cooke [ 26 ] framework for Research Capacity Development in health care are made, particularly within the areas of Close to Practice (CTP), Infrastructure (INF) and Skills and Confidence Building, which closely align with our findings and help support transferability to other contexts whilst also realising that a training programme can only do so much.

Close to practice

Gee and Cooke’s [ 26 ] ‘Close to Practice’ principle covers themes such as keeping research relevant to health care and informing day-to-day practice The current programme tried to be inclusive of all professional types (i.e. being close to practice); however, as identified in the engaging with teaching sessions theme, some language barriers were highlighted by staff from social care backgrounds who felt excluded due to the clinical/academic language used to deliver the training session – which may have obscured the relevance of the content for this group of learners. Still, the way the STARS programme supports this principle is evident in the content, which addresses both the main strands of the UK and English health policy, driving increased health and care involved in research:

the routine use of research findings in day to day practice;

increased involvement in research activity within the health service.

(referred to by Wakefield et al. [ 13 ] as ‘using research’ and ‘doing research’). The findings of the current evaluation demonstrated that participants’ reasons for booking onto the programme usually included one or both elements. Participants’ motivations also mirrored those found by Dimova et al. [ 15 ], presenting expectations that the STARS content supported both individual career development and organisational objectives such as high-quality patient care. In line with Ariely et al. [ 27 ] and Abramovich and McBride [ 28 ] booking but not attending the current training sessions was an indication toward the perceived low value of the training considering it was completely free for the staff. As the training is free to attend for the staff & managers with no direct impact on teams’ budgets, the priority to attend was given to paid trainings over STARS, sometimes.

Support infrastructure

Gee and Cooke’s [ 26 ] ‘Developing a support infrastructure’ principle covers ‘building additional resources and/or processes into the Trust’s organizational system to enable the smooth and effective running of research projects and for research capacity building’. The findings from the current evaluation, particularly under the ‘Promoting a research-active environment’ them, also showed how a wide-ranging in-house research skills training programme open to all staff can help build resources and processes within a healthcare provider that can support greater research activity.

In terms of processes, distinctive features of this training programme were that it was delivered in-house and entirely online. While the move to online training was necessitated by the pandemic (COVID-19), the evaluation showed that online training has the potential to become the delivery method of choice, particularly for in-house training for organisations covering a wide geographical area. Evaluations comparing online synchronous learning to traditional face-to-face learning have generally shown that (though with certain limitations) online approaches can be effective (George et al. [ 29 ], found this was the case for post registration medical education). In line with previous research, the current evaluation has also shown that an online-only training programme has challenges but can have a positive impact on applying research skills and developing confidence among healthcare staff [ 29 , 30 ].

Participants’ feedback identified the importance yet challenge of incorporating interactivity into online training [ 31 , 32 , 33 ]. Feedback on the length of the teaching sessions demonstrated that long sessions (in this case two hours or longer) could reduce engagement [ 33 , 34 ].

The literature on barriers to health and social care staff carrying out either or both of these activities (research finding use or research activity) identified four main barriers:

lack of time and/or resources;

lack of organisational or management support in other ways;

lack of skills, knowledge, and confidence to undertake research or put evidence into practice and.

lack of opportunities to develop these skills.

The first two of these are linked to infrastructure, resources and processes. The findings of the STARS evaluation showed mixed evidence in this respect. On one hand, the evaluation echoed previous research [ 7 , 8 ] that lack of time or staffing pressures was a major barrier to healthcare staff gaining research skills. Lack of protected time for research activities remains an important barrier to embedding a research-active environment into an organisation. As suggested by King et al. [ 11 ] the current evaluation was also conducted keeping in mind the long-term impacts on the organisational level. The STARS evaluation found the issue of management support, also identified previously [ 8 ], and affected both attendance and opportunities to put skills learnt into practice. On the other hand, the evaluation produced at least one positive example of a manager supporting an attendee in putting skills learnt into practice, resulting in changes in practice.

Research skills and confidence in the workforce

Gee and Cooke’s [ 26 ] ‘skills’ principle covers the provision of training and development opportunities to enable the health and care workforce to develop the skills and confidence to both ‘use’ and ‘do’ research. This principle speaks to the second theme of ‘Relevance and impact of training’ and matches the third and fourth barriers to doing and using research from the research literature mentioned above. This evaluation focused on how the STARS training programme addressed this principle and these barriers.

In terms of the provision of opportunities, the analysis of benefits reported by participants suggest that taking part in the programme contributed to improved skills and confidence in both the ‘using’ and ‘doing’ areas. Comments from the interviews also showed how the STARS programme had addressed the barrier of a lack of opportunities to develop these skills, with two (social care) participants commenting that STARS represented an opportunity not traditionally available to staff from their sector. This helps address one of Wakefield et al’s [ 13 ] recommendations about access to research training opportunities.

Previous research [ 8 , 10 , 13 ] showed that a lack of research skills, confidence and opportunities to gain them were issues associated with non-medical staff groups, particularly nurses, AHPs and social workers. However, the opportunity to gain knowledge and new skills through STARS was valued and staff had plans of using them in the future, echoing the results reported by Bullock et al. [ 35 ] The analysis of demographic data for the STARS programme was based on broad nationally defined staff categories (United Kingdom Electronic Staff Record (ESR) categories – see ‘A Guide to the Staff Group, Job Role and Area of Work classifications used in ESR’); it was difficult to separate, for example, social workers from other staff categories who usually have higher degrees, a high level of research skills, confidence and knowledge. However, the high level of take-up from nursing and midwifery and AHPs suggest that the STARS programme had been of interest to staff groups that previous research had identified as lacking skills, confidence and training opportunities to make evidence-based practice and research activity part of their working culture.

Comments received in the STARS evaluation raised the dilemma of whether it was possible to make content available and relevant to groups of participants with very different professional backgrounds and levels of research knowledge and experience; or whether attempting to achieve this meant the course content did not meet any group’s needs well. The evaluation found both positives and negatives in this respect – gains from sharing the training with colleagues from very different areas and perspectives versus content failing to suit the needs of the participants, very different prior research and professional knowledge and so inhibiting learning in some cases. Previous research was found, evaluating multidisciplinary training provisions that either spanned a range of professional groups working in the same area or students at a similar stage of education studying in different subject areas [ 7 , 9 , 10 , 12 ]. However, no previous research was found evaluating training programmes that matched the STARS participants’ mix of both professional backgrounds and work areas (spanning a range of inpatient and community health and social care settings as well as support services).

Strengths and limitations

The current evaluation contains both quantitative and qualitative primary data from engagers and non-engagers in a novel research education and training programme for a broad range of health and social care professionals. Qualitative methods were designed to be flexible and pragmatic to capture views from busy health and social practitioners; however, emailed responses did not support in-depth exploration. As the interviewer was also a staff member of the same organisation there might have been some undisclosed responses. Findings report key the components of training that worked/did not work; this information could eventually be used to improve future training in this setting and others. As the participants of the STARS programme and current evaluation are located within a health and social care NHS trust in England, the conclusions are relevant to similar settings only. However, findings seem relevant to non-UK health and social care workers. For example, Withington et al. described how their targeted training and mentoring model enhanced research capacity among social workers [ 19 ] Also similar to finding in STARS collaborative approaches have also been discussed as essential by Nystrom et al., in in health and social care context in Sweden to ensure support, trust and understanding among those working in healthcare system [ 36 ]. Despite this limitation, the findings highlight how a research training programme can be tailored around the needs of staff and run virtually during a pandemic.

This evaluation covered a 12-month period in which the STARS programme was rolled out for the first time at MPFT. Findings demonstrate the positive impact that access to free, high-quality, online research education can have in terms of enhancing research awareness and confidence across a diverse range of professional types; some of whom reported unequal access to such training in the past (e.g., social care, nursing and midwifery). Service-level barriers remain that a novel training programme cannot address (e.g., competing burden of clinical roles). It is too early to assess longer-term outcomes relating to the fourth level of Kirkpatrick’s framework (performance) or research culture at an organisation-level; further follow-up research is needed. The STARS programme demonstrates what strong collaboration between NHS and academic institutions can produce and provides a training model that can be adopted and adapted elsewhere to nurture research-active environments and promote research capacity building within and beyond the UK.

Availability of data and materials

The anonymised quantitative raw data from evaluation registers and qualitative data from interviews is available on reasonable requests. The corresponding and first author, GT, should be contacted if someone wants to request the data from this study.

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Acknowledgements

The authors acknowledge and sincerely thank the members of the STARS working group for their contributions in delivering the project.

The authors thank CRN I&I strategic funding programme for funding the STARS program.

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Gulshan Tajuria, David Dobel-Ober, Claire Charnley, Ruth Lambley-Burke, Christian Mallen, Kate Honeyford & Tom Kingstone

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Author GT conducted data collection and analysis with support from authors DD-O, EB and TK, author CC supported with literature for background and discussion and all authors were involved in the original conception of the idea and read and approved the final manuscript.

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This study was classified through the Health Research Authority (HRA) automated systems as not requiring ethical approval, as per the UK Policy Framework for Health and Social Care Research28 [ 37 ]. The study was reviewed by the Research and Innovation department form the authors’ organisation (MPFT) prior to being placed on the local evaluation register (ref: e2021-10) and it followed GDPR principles with regard to data management and was conducted in compliance with the Declaration of Helsinki29 [ 38 ]. A written informed consent was obtained from all participants before participation in the study. All prospective participants received information about the study and were asked to return a signed copy of the consent form via email. Additionally, at the start of each interview, participants were asked to confirm verbally that they consented to take part; this was audio recorded, as were the interviews. The author is happy to share the consent forms if needed but those would need to redact to maintain anonymity.

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Tajuria, G., Dobel-Ober, D., Bradley, E. et al. Evaluating the impact of the supporting the advancement of research skills (STARS) programme on research knowledge, engagement and capacity-building in a health and social care organisation in England. BMC Med Educ 24 , 126 (2024). https://doi.org/10.1186/s12909-024-05059-0

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DOI : https://doi.org/10.1186/s12909-024-05059-0

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