Skip to main content
NCBI home page
SAGE - PMC COVID-19 Collection logoLink to SAGE - PMC COVID-19 Collection
. 2022 Jul 6;23(2):165–188. doi: 10.1177/14680173221109483

Working conditions and well-being in UK social care and social work during COVID-19

Jermaine Ravalier 1,✉, Paula McFadden, Patricia Gillen, John Mallett, Patricia Nicholl, Ruth Neill 2, Jill Manthorpe 3, John Moriarty, Heike Schroder, Denise Curry 4
PMCID: PMC9264376  PMID: 38603207

Abstract

Summary

Stress and mental health are among the biggest causes of sickness absence in the UK, with the Social Work and Social Care sectors having among the highest levels of stress and mental health sickness absence of all professions in the UK. Chronically poor working conditions are known to impact employees' psychological and physiological health. The spread of the COVID-19 pandemic has affected both the mode and method of work in Social Care and Social Work. Through a series of cross-sectional online surveys, completed by a total of 4,950 UK Social Care and Social Workers, this study reports the changing working conditions and well-being of UK Social Care and Social Workers at two time points (phases) during the COVID-19 pandemic.

Findings

All working conditions and well-being measures were found to be significantly worse during Phase 2 (November–January 2021) than Phase 1 (May–July 2020), with worse psychological well-being than the UK average in Phase 2. Furthermore, our findings indicate that in January 2021, feelings about general well-being, control at work, and working conditions predicted worsened psychological well-being.

Applications

Our findings highlight the importance of understanding and addressing the impact of the pandemic on the Social Care and Social Work workforce, thus highlighting that individuals, organizations, and governments need to develop mechanisms to support these employees during and beyond the pandemic.

Keywords: Social work, social care, stress, health, mental health

Introduction

The spread of COVID-19 placed global health and social care systems under intense strain. In the first months of the pandemic in the United Kingdom (UK) health and social care, including social work employees, had significantly higher rates of COVID-19 infections than the general population (Office for National Statistics, 2020). While much attention was on severe pressures in the National Health Service (NHS) across the UK, it became evident that social care and social work services were being severely affected, with the UK's 18,075 care homes, in particular, experiencing substantial deaths and infections among residents and staff (Bell et al., 2020). Other parts of social care and social work were also affected such as home care (domiciliary services) and frontline social work services leading to criticism that attention to the social care sector had come far too late (Comas-Herrera et al., 2020). UK-wide National data covering March–December 2020 revealed that those who worked in social care occupations had statistically significantly higher rates of death involving COVID-19 when compared with rates of death involving COVID-19 in the population among those of the same age and sex (79.0 deaths per 100,000 males; 150 deaths) and women (35.9 deaths per 100,000 females; 319 deaths) (Office for National Statistics, 2021). These risks have been reported internationally (Roxby et al., 2020; World Health Organization, 2020), reflecting the interpersonal nature of social work and social care employment and the prevalence of COVID-19 among older age groups and disadvantaged communities (e.g., Berg-Weger & Morley, 2020; Ladhani et al., 2020) using social care and social work services. This, combined with social workers in the UK having among the worst working conditions of any UK occupational sector (Ravalier, 2019), means that greater investigation of the impact of working conditions on staff is required.

In the UK, the term social care can be used as an overarching term to describe an employment sector that covers the provision of care and support to children, their families, and adults and is distinct from clinical health care provided by the NHS. It is also used separately to describe the workforce that is skilled but not professionally qualified in social work (a graduate profession in the UK). The nonsocial work workforce is large, with the majority of social care workers working in care homes (including care homes that employ registered nurses), domiciliary care, and day services for adults. Additionally, children's social care staff provide children's residential care, with support for families and children around their well-being and safeguarding, and adoption and fostering. Unlike the NHS, the social care sector is largely independent (private and not-for-profit providers) and there is a multiplicity of employers. In England, adult social care (ASC) is provided by around 18,500 organizations working in 39,000 locations (Social Care Institute for Excellence, 2020). While the social care system is complex and fragmented, social work across the UK in contrast is largely a statutory function and local government is the main employer of these graduate professionals in all parts of the UK except Northern Ireland where the main employers are its integrated Health and Care Trusts. In the UK, social work is a protected title with social workers engaging generally in undergraduate or postgraduate training prior to being able to practice. As such, while social workers and social care workers often work with similar service user populations, their roles and functions are generally distinct from each other.

In the UK COVID-19 context, there have been several studies of the social care and social work workforces covering different parts of the sector. For example, one has run a series of quarterly surveys of children's nursery managers (private, not-for-profit, and local government) in England, Scotland, and Wales (see Bonetti et al., 2021). This found many nursery staff had been “furloughed” (temporarily laid off with 80% remuneration) from their jobs in the early part of the pandemic as children were unable to attend nurseries unless their family (parents or carers) were key workers or there were concerns about the child. As the pandemic continued these staff were being reengaged but staff shortages remained.

In local government, a series of monthly surveys of all local authorities in England, Wales, and Northern Ireland have been collecting key workforce data on how the sector is responding to COVID-19 starting from the week ending May 1, 2020. The survey is completed by heads of human resources (HR), or a nominated contact and spans a wide range of local authority staff including social workers with questions taking an HR perspective such as recruitment, sickness absence, redeployment, and availability of personal protective equipment and latterly vaccine uptake (see Local Government Association, 2021). While its HR respondents provide data about all local authority staff, including planners and environmental health staff, the reports highlight some long-standing social work trends and concerns such as high levels of vacancies in children's social work services.

Further evidence from social workers themselves has been collected by the British Association of Social Workers (British Association of Social Work [BASW], 2021) in its survey of social workers that ran between November 30 and December 31, 2020, across the four nations of the UK. A total of 1119 social workers responded. This survey found that nearly a third of those responding (30.7%) agreed or strongly agreed that they had felt under pressure to work while unwell (for reasons that may have included COVID-19-related infection) and that nearly three-quarters (71.5%) agreed or strongly agreed with the statement that workplace morale (not defined) in their place of employment had been adversely affected by the COVID-19 crisis.

Turning to social care, a review in the early months of the pandemic in the UK (Sanders, 2020) noted that much literature and resources were focused on the NHS rather than social care and that some of the social care's endemic problems were affecting its COVID-19 response, such as high levels of stress and poor working conditions. Raw data from England from the ASC (ASC-workforce dataset) in February 2020 have been used to represent the period before measures were introduced to reduce the impact of COVID-19 (the first UK lockdown started on March 23, 2020). Using this information relating to around 27,400 workers from 1,100 establishments (social care employers), Skills for Care (2021) has been able to compare the COVID-19 period (March 2020 to February 2021) with the pre-COVID-19 period in England. It found that the percentage of days lost due to sickness pre-COVID-19 was 2.8% but during the COVID-19 period, the figure (including people unable to work because they were self-isolating or shielding) stood at 5.9%. Figures related to sickness absence were highest for care workers (6.8%) and lowest for registered managers (2.3%). These studies are an important and informative context to the present study that compares social care and social work staff responses to two phases of an online survey.

Chronic workplace stress and working conditions

Chronic stress is defined as that which lasts over an extended period of time. Various studies have demonstrated that chronic stress and poor working conditions have a continuously deleterious effect on both the psychological and physiological health and well-being of employees, and subsequently impact at both an organizational level and an individual level, in terms of health/social care employees, service user, and patient outcomes (Flower et al., 2005; Gaskell, 2010). At an individual employee level chronically poor working conditions and stress at work are risk factors for the development of cardiovascular disease (see, e.g., Marmot et al., 1991; Rosengren et al., 2004), and metabolic syndrome (a risk factor for developing conditions such as Type 2 diabetes; Chandola et al., 2006) and other physiological outcomes. These impacts on individual employees, therefore, have implications for employers, service users, and their colleagues with stress being the prime reason for sickness absence in the UK (Health and Safety Executive, 2020; Office for National Statistics, 2021; Ravalier, 2019).

The job demands-resources model

The job demands-resources (Bakker et al., 2003) model of well-being at work is a widely applied theoretical model of work stress and well-being. It suggests that conditions at work can be categorized as either demands or resources. Demands add a load (physical or mental) to the individual and are thus conditions that can negatively contribute to the experience of well-being at work. Examples of demands include workload and task variability (Minnotte, 2016). However, resources (such as peer support, coaching, mentoring, and developmental opportunities) offered at work buffer against the negative effects of demands experienced. Should demands outweigh the resources available to the individual over an extended period then negative organizational outcomes such as stress-related sickness absences (Schaufeli et al., 2009), job dissatisfaction, burnout (Schaufeli & Bakker, 2004), presenteeism, and higher turnover intentions (Ravalier, 2019) may occur.

Working conditions in social care

In the UK, the health and social care sectors have among the highest levels of stress-related sickness absence in the country (Health and Safety Executive, 2020), with stress, depression, and anxiety accounting for over half of all health-related sickness absence days lost. The profession of social work is objectively one of the most stressful occupations in the UK (Ravalier, 2019; Ravalier et al., 2021). Chronic stress and poor working conditions affect the intention to leave both the employer and the profession. In addition to impacting the well-being of individuals and their employing organizations, literature has shown that high levels of stress and poor working conditions also affect the care provided to service users (Ravalier, 2019; Ravalier et al., 2021). For example, Flower et al. (2005) found that children with more than one social worker (related to high turnover intentions) were 60% less likely to be found a permanent placement.

This present study aimed to investigate the possible changing working conditions and well-being of social care and social workers across the UK during the COVID-19 pandemic, and the influence of their working conditions on their well-being across two time points.

Materials and methods

Methods and participants

A cross-sectional study consisting of two online surveys collected approximately six months apart investigated the changes in working conditions and well-being of UK social work and social care workers. This was part of the wider project “Health and social care workers’ quality of working life and coping while working during the COVID-19 pandemic,” launched in May 2020 (see McFadden et al., 2021). Here we report findings from the first two phases of data collection (May to July 2020 and November 2020 to January 2021). This approach was taken to gain a representative understanding of the impacts of COVID-19 on frontline health and social care workers in the UK (England, Ireland, Scotland, and Wales), with the focus of this present publication on all social work and social care workers. Recruitment was undertaken via an opportunity and snowball sampling method through emails and newsletters to UK-based social work and social care national bodies, who subsequently passed on participation requests to members, as well as social media (e.g., Twitter) posts. Ethical approval was obtained from (Ravalier, 2019).

Table 1 illustrates respondents’ demographics during Phases 1 and 2. In Phase 1, the online survey collector was open for responses between May and July 2020, and between November 2020 and January 2021 for Phase 2. The demographic profile of respondents between Phases 1 and 2 was relatively similar: the majority of female respondents were White in ethnicity and did not have a disability. The only divergence between Phases 1 and 2 was that most respondents were older in Phase 2 than respondents in Phase 1. These demographic characteristics of the respondents in our study are similar to that of the UK social care and social work workforce as a whole. Most (86%) UK child and family social workers are female, and 25% are aged 40–49. However, our social work sample is overrepresented by White respondents with approximately 78% of UK social workers being White (gov.uk, 2021). With respect to social care, Skills for Care (2020) reports that 82% of the ASC workforce is female in England, with an average age of 44, and 79% of White ethnicity.

Table 1.

Respondents’ demographic information separated by occupation.

Age Gender Ethnicity Do you consider yourself disabled?
Female Male White Black Other Yes No
All social care and social work Phase 1
(n = 2,525)		 40–49 years
733 (29.0%)		 2,162 (85.7%) 353 (14.0%) 2,371 (94.0%) 82 (3.2%) 72 (2.8%) 188 (8.3%) 2,028 (80.3%)
Phase 2
(n = 2,425)		 50–59 years
702 (28.9%)		 2,103 (86.7%) 319 (13.2%) 2,312 (95.5%) 43 (1.7%) 70 (2.8%) 234 (10.7%) 1,901 (86.6%)
Social work Phase 1
(n = 1,280)		 40–49 years
329 (28.1%)		 1,092 (85.3%) 182 (14.2%) 1,172 (92.0%) 48 (3.8%) 60 (4.2%) 114 (8.9%) 1,027 (80.2%)
Phase 2
(n = 1,172)		 50–59 years
378 (29.5%)		 1,001 (85.4%) 169 (14.4%) 1,094 (93.4%) 27 (2.3%) 51 (4.3% 126 (10.8%) 915 (78.1%)
Social Care Phase 1
(n = 1,245)		 40–49 years
369 (29.6%)		 1,070 (85.9%) 171 (13.7%) 1,199 (96.5%) 18 (1.5%) 28 (2.0%) 74 (5.9%) 1,001 (80.4%)
Phase 2
(n = 1,253)		 50–59 years
387 (30.9%)		 1,102 (87.9%) 150 (12.0%) 1,218 (97.5%) 12 (1.0%) 23 (1.5%) 108 (8.6%) 986 (78.7%)
Open in a new tab

Table 2 shows the occupational demographics of respondents. The majority were employed on permanent contracts, with fewer redeployed into different roles due to the COVID-19 pandemic in Phase 2, than in Phase 1. Most respondents had between 11 and 20 years of experience in their role, there were overall fewer days lost due to sickness absence in Phase 2 than in Phase 1, although more of this absence occurred due to COVID-19 in Phase 2 than in Phase 1.

Table 2.

Respondents’ occupational demographics separated by occupation.

Permanent contract? COVID redeployed? Experience (range) Sick days
Yes Yes None 1–20 days Due to COVID
All social care and social work Phase 1 2,218 (88.8%) 304 (12.0%) 11–20 years
665, (26.6%)		 1,192 (48.2%) 1,083 (43.8%) 208 (17.4%)
Phase 2 2,198 (92.0%) 166 (6.8%) 11–20 years
748, (31.3%)		 1,249 (52.9%) 857 (36.2%) 347 (33.3%)
Social work Phase 1 1,137 (89.5%) 163 (12.7%) 11–20 years
353, (27.6%)		 607 (48.1%) 557 (44.1%) 85 (13.7%)
Phase 2 1,058 (92.0%) 73 (6.2%) 11–20 years
365, (31.7%)		 599 (43.5%) 402 (35.3%) 134 (11.4%)
Social care Phase 1 1,081 (88.0%) 141 (11.3%) 11–20 years
312 (25.4%)		 585 (48.3%) 526 (43.5%) 123 (21.4%)
Phase 2 1,140 (91.0%) 93 (7.5%) 11–20 years
383 (30.9%)		 650 (53.2%) 455 (37.3%) 213 (39.7%)
Open in a new tab

Materials

We report on two separate measures, in addition to a series of demographic questions, used within this study. The dependent variable, the Short Warwick–Edinburgh Mental Well-being Scale (SWEMWBS; Stewart-Brown et al., 2009) is a seven-item measure of mental well-being. Respondents are asked to state how often over the previous two weeks they had had particular experiences or thoughts. Questions are answered on a five-point Likert scale from 1 (none of the time) to 5 (all of the time), with higher scores indicative of better mental well-being. SWEMWBS has strong reliability (e.g. Cronbach's alpha .90 among hospital patients, Vaingankar et al., 2017; and .84 among the general population, Ng Fat et al., 2017) and validity and is suitable for use with the general public (Ng Fat et al., 2017).

Secondly, the independent variable work-related quality of life (WRQoL; Van Laar et al., 2007) scale, split into its six subscales, was used to assess the quality of working life and working conditions. The six subscales are job career satisfaction (six items), stress at work (two items), general well-being (six items), home–work interface (three items), control at work (three items), and working conditions (three items), as well as the overall WRQoL. Each subscale has good reliability (Cronbach's alpha of each subscale scored between .75 and .88, with overall scoring of .91; Easton & Van Laar, 2018) and validity, as does the overall measure (see, e.g., Easton & Van Laar, 2018). All WRQoL questions are answered on a five-point Likert scale from 1 (strongly disagree) to 5 (strongly agree). Item scores were totaled for each subscale so that higher scores indicated better quality of working life, apart from the stress at work subscale where higher scores indicated higher stress levels.

Demographic questions covered age, gender, ethnicity, and whether the respondent considers themselves to have a disability, part/full-time contract, and amount of experience in the role. Three further questions were asked to better understand whether the pandemic had impacted their working lives: whether they had been redeployed due to COVID-19, how many sick days they had taken in the previous year, and whether any sick days taken had been due to COVID-19.

Analytical strategy

Quantitative data were analyzed using IBM SPSS 24.0 (IBM, Armonk, NY, USA). Firstly, mean and standard deviation descriptive statistics were calculated for the sample as a whole at each time point and separated by job role (social work and social care). Secondly, a series of independent sample t-tests were conducted to determine differences in scoring on each measure between Phases 1 and 2 for all respondents as well as separated by occupation. Finally, three regression analyses were undertaken to investigate the impact of working conditions on well-being in Phase 2 for all respondents, and separated by occupation.

Results

Descriptive statistics

Table 3 shows mean scoring at Phases 1 and 2 on each of the variables included within the study, separated by occupation. Mean scoring on each measure was worse in Phase 2 than it was in Phase 1 for all variables, suggesting worsened scoring over the study period. Similarly, across most variables, social workers’ mean scoring was higher than that of social care workers, indicating better well-being and working conditions in both Phases 1 and 2. Exceptions include higher scoring for social care workers on work stress at both time points (indicating better levels of work stress), well-being at Phase 2 (indicating better well-being scoring), and working conditions at Phases 1 and 2 (indicating better general working conditions). UK norm scoring on the SWEMWBS has been found to be 23.7 for males and 23.6 for females (Ng Fat et al., 2017), indicating our sample as a whole had poorer psychological well-being than the national average.

Table 3.

Mean and standard deviations (in brackets) for short Warwick–Edinburgh mental well-being scores and quality of working life subscales for social work and social care professionals at two time points.

All respondents
mean (SD)		 Social work
mean (SD)		 Social care
mean (SD)
Short Warwick–Edinburgh mental well-being scale (mean, SD) Phase 1 21.10 (3.86) 21.20 (3.36) 21.08 (3.93)
Phase 2 19.96 (3.48) 20.08 (3.17) 19.94 (3.52)
Quality of working life (Mean, SD) Total Phase 1 79.95 (15.42) 80.52 (13.45) 79.86 (15.73)
Phase 2 73.46 (16.25) 73.71 (15.25) 73.42 (16.42)
Career satisfaction Phase 1 21.74 (4.85) 22.41 (3.97) 21.63 (4.97)
Phase 2 20.59 (5.05) 21.26 (4.42) 20.48 (5.14)
Work stress Phase 1 5.33 (2.02) 4.74 (1.81) 5.42 (2.03)
Phase 2 4.58 (1.77) 4.09 (1.78) 4.66 (1.76)
Well-being Phase 1 20.40 (4.62) 20.67 (4.27) 20.36 (4.68)
Phase 2 18.52 (4.95) 18.44 (4.70) 18.53 (4.99)
Home–work interface Phase 1 11.28 (2.69) 11.30 (2.57) 11.28 (2.71)
Phase 2 10.20 (2.93) 10.53 (2.81) 10.15 (2.94)
Control at work Phase 1 10.41 (2.67) 10.56 (2.51) 10.38 (2.70)
Phase 2 9.23 (302) 9.63 (2.91) 9.16 (3.04)
Working conditions Phase 1 10.86 (2.47) 10.69 (2.38) 10.89 (2.49)
Phase 2 10.27 (2.73) 9.72 (2.74) 10.36 (2.73)
Open in a new tab

Independent sample t-tests

A series of independent sample t-tests were undertaken to determine whether significant differences were found between all social care and social work combined respondents in Phases 1 and 2. Significant differences were found between Phases 1 and 2 on all measures utilized. As such, the SWEMWBS (t = 8.48, p < .05); total WRQoL (t = 11.12, p < .05), career satisfaction (t = 6.34, p < .001), work stress (t = 10.80, p < .001), well-being (t = 10.80, p < .05), home–work interface (t = 10.62, p < .001), control (t = 11.32, p < .001), and working conditions (t = 6.21, p < .001) all respondents scored significantly lower (i.e., worse) in Phase 2 than respondents in Phase 1.

Furthermore, independent sample t-tests were undertaken for each of the two social care roles: social workers and social care workers on each of these measures. Within the social work occupation, two of the measures included demonstrated changes from Phase 1 to Phase 2. As such, each control at work (t = 3.57, p = .005) and working conditions (t = 3.91, p < .05) were significantly different. For social care workers, all measures other than job career satisfaction saw significant worsening from Phase 1 to Phase 2. As such, for each of the SWEMWBS scores (t = 7.75, p < .001), total WRQoL (t = 10.05, p < .001), work stress (t = 10.16, p < .001), general well-being (t = 9.60, p < .001), home–work interface (t = 10.25, p < .001), control at work (t = 10.78, p < .001), and working conditions (t = 5.09, p < .001) all scored significantly worse.

Regression analyses

Table 4 shows the findings from a regression analysis looking at the impact of WRQoL variables (career satisfaction, stress at work, working conditions, control at work, general well-being, and home–work interface) on psychological well-being (as measured by the Warwick–Edinburgh Mental Well-being Scale [WEMWBS]) in Phase 2 for all UK social care worker respondents. The model was significant (p < .001), accounting for 63% of the variance in the model. Each general well-being, control at work, and working conditions were significant predictors of psychological well-being (p < .001). variance inflation factor (VIF) is above .2, and tolerance <10, for each variable indicates no collinearity (Field, 2013).

Table 4.

Linear regression of phase 2 findings on the impact of working conditions on short Warwick–Edinburgh mental well-being scores for social care workers.

Significantly related factors Coefficient estimates t p Tolerance VIF R 2 Adjusted R2
Warwick–Edinburgh mental well-being scale Job career satisfaction .01 .52 NS .30 3.39 .63 .63
Stress at work .01 .29 NS .77 1.30
Working conditions −.13 −3.58 <.001 .37 2.74
Control .33 10.25 <.001 .39 2.58
General well-being .45 26.29 <.001 .51 1.95
Home–work interface .05 1.91 NS .60 1.66
Open in a new tab

NS = not significant.

A further regression (Table 5) was conducted to investigate the influence of WRQoL variables on the WEMWBS on social workers in Phase 2. Here the model was also significant (p < .001) and accounted for 55% of the variance. General well-being was the only factor significantly related to WEMWBS (p < .001). Again, no collinearity is detected.

Table 5.

Linear regression of phase 2 findings looking at the impact of working conditions on Warwick–Edinburgh mental well-being scores for social workers.

Significantly related factors Coefficient estimates t P Tolerance VIF R 2 Adjusted R2
Warwick–Edinburgh mental well-being scale Job career satisfaction .02 .34 NS .43 2.31 .56 .55
Stress at work .12 1.29 NS .74 1.36
Working conditions .05 .69 NS .46 2.15
Control at work .06 .82 NS .49 2.02
General well-being .45 10.00 <.001 .49 2.05
Home–work interface −.06 −.87 NS .59 1.71
Open in a new tab

NS = not significant.

Finally, a third regression analysis was undertaken with all respondents in Phase 2 (see Table 6). Again the model is significant (<.001), accounting for 61% of the variance. Each general well-being, control at work (both p < .001), and working conditions (p < .005) were significantly related to well-being outcomes. However, VIF calculations for general well-being were below 2.00, suggesting possible collinearity within this model and thus findings should be taken with caution.

Table 6.

Linear regression of phase 2 findings looking at the impact of working conditions on Warwick–Edinburgh mental well-being scores for all social care and social work respondents.

Significantly related factors Coefficient estimates t P Tolerance VIF R 2 Adjusted R2
Warwick–Edinburgh mental well-being scale Job career satisfaction .14 .72 NS .32 3.16 .61 .61
Stress at work .04 .96 NS .77 1.30
Working conditions −.10 −3.07 <.005 .30 2.54
Control at work .29 9.79 <.001 .40 2.48
General well-being .45 27.83 <.001 .52 1.93
Home–work interface .04 .03 NS .61 1.65
Open in a new tab

NS = not significant.

Discussion

Summary of findings and comparison with other literature

We aimed to investigate the changes in working conditions and well-being of social work and social care workers across the UK at two time points during the COVID-19 pandemic; Phase 1 (May–July 2020) and Phase 2 (November 2020–January 2021). To the authors’ knowledge, this is the first study comparing working conditions and well-being in the social care and social work workforce during the pandemic as previously many studies have only addressed elements of the sector or have studied health and social care/work professionals during this time. Our results showed significant differences between Phase 1 and Phase 2 on all measures examined. Study respondents had a mean score of 21.1 in Phase 1 and 19.96 in Phase 2 for psychological well-being (SWEMWBS). In contrast, the UK population norm scoring for the SWEMWBS was 23.7 for males and 23.6 for females (Ng Fat et al., 2017) with a general population mean of 23.61 (Ng Fat et al., 2017). These findings indicate our sample has poorer psychological well-being than the pre-COVID-19 national average. Additionally, our findings indicate that general well-being, control at work, and working conditions were significant predictors of psychological well-being (p < .001). This demonstrates the importance of ensuring that good working conditions are in place for the social work and care workforce to support or sustain their psychological well-being, although this was of course difficult to achieve during the pandemic (Ravalier, 2019).

Similar to others’ findings from related sectors across the UK and beyond, we found that the social care workforce was under severe pressure during the height of the pandemic and subsequently as demand has increased following its first waves (Johnson et al., 2020; Reddington et al., 2021). Lockdowns, government restrictions, and social distancing guidelines threatened relationship-based practices that social care and social workers traditionally rely upon (Farkas & Romaniuk, 2020; Golightley & Holloway, 2020). Face-to-face contacts were minimized and communication largely moved online for social workers with home working commonplace for over a year (Abrams & Dettlaff, 2020; Ravalier, 2019). However, while there is far less home working among social care workers, they have seen high levels of illness among their service users, huge changes to their service users’ lives and social contacts, and have had to adapt to constant and changing infection control measures. These changes could have a negative psychological impact due to prolonged stress, higher job demands, changing responsibilities, and limited resources worsened by the COVID-19 pandemic (Harrikari et al., 2021; Holmes et al., 2021; Miller & Reddin Cassar, 2021). These stresses highlight possible reasons for the deterioration between Phases 1 and 2 within this present study.

Our findings reflect those from a study of the overall health and social care workforce (Aughterson et al., 2021) which also highlighted that psychological well-being has been negatively impacted during the COVID-19 pandemic. This qualitative study found that increasing workload and changing conditions left the health and social care workforce often fatigued while faced with communication challenges and increased work-related stressors. These findings coincide with the recent BASW (2021), which reported that 58.8% of social workers surveyed considered that working during the crisis had negatively impacted their mental health while 68.3% said it was more difficult working at home than in the office. Such problems are not confined to social work but are evident in the general workforce population that has been able to work from home. From The Netherlands, in a survey of the general working population that took place in June–July 2020, Pluut and Wonders (2020) reported that COVID-19 had heightened the levels of blurred work–life boundaries reducing happiness and well-being.

Some social workers began to feel less positive and less able to cope with their work as the pandemic progressed (Johnson et al., 2020). However, achieving a perfect balance of good working conditions and good psychological well-being can be difficult for this workforce. The findings from this present study indicate that work stress, maintaining a balance in the home–work interface, and feeling of control of work and working conditions, were all significantly lower as the pandemic continued. These findings are consistent with other research which suggests that work–life balance can be difficult in this profession as it is currently organized in the UK, particularly if working practices changed (e.g., working at home/remotely) and with less team support, opportunities, and resources available (Schieman et al., 2021). Combined with previous research, this study highlights that more is needed to support the social work workforce during the pandemic across individual, organizational, and policy levels if well-being and WRQoL are to improve.

Turning to social care work our findings suggest many similar responses, although by Phase 2 nearly 40% of social care workers had taken sick leave owing to COVID-19 suggesting a very high level of exposure to the virus possibly arising from their inability to work from home and substantial contact with people who were infected (see Table 2). Levels of work stress were higher for social care workers than for social workers but for both, they were higher in Phase 2 than in Phase 1. Interestingly, while social care workers were not so likely to be home working, as Table 3 shows, they experienced problems with their home/work interface perhaps indicative of their fears of bringing the infection to their family at home and having to work increased hours or unpredictably which may have caused difficulties in maintaining a work/life balance as well as being more likely to have witnessed or known of pandemic sufferers and mortality. Another small social care survey (Hussein, 2020) reported that most (81%) of 296 social care workers saw their workload heavily increase since the onset of COVID-19 with 56% of this workforce facing longer work hours and 42% less satisfied with their job. Spilsbury et al. (2021) and White et al. (2021) have highlighted the considerable uncertainties among care home workers during the first months of the pandemic about their safety while others have commented that COVID-19 amplified the difficulties of care homes in terms of their resourcing and wider support (Gordon et al., 2020). An Italian study suggested that during the first outbreak of COVID-19 care home workers were under increased pressure due to the pandemic which led to the development of psychiatric symptoms at different levels (Riello et al., 2020). These authors found an increasing prevalence of anxiety and recommended interventions for improving staff well-being and resilience. Despite this, and perhaps explaining why the well-being of social care workers was not worse than might be expected, there have been reports of how the pandemic increased the workforce's untapped capacity; “Managers reported that the skills and determination of care home staff was a source of resilience. Managers spoke of pride in their teams, who worked with tenacity and creativity, and recognized skills that had previously not been required” (Marshall et al., 2021, p. 5).

Limitations of the study

This study addresses the gap in research investigating the changes in working conditions and well-being of social work and social care workers across the UK during the COVID-19 pandemic. Strengths of this study include the robust sample size and the use of well-established, reliable outcomes measures of SWEMWBS and WRQoL. Furthermore, given the unpredictable nature of the COVID-19 crisis, this study is important in capturing the difference in the WRQoL and well-being over the duration of the pandemic which is crucial in helping identify the challenges related to the social care workforce. This is a strength of the cross-sectional design, which allows for association across multiple outcomes to be examined to understand prevalence (Wang & Cheng, 2020). However, several limitations are important to acknowledge.

Firstly, recruitment was undertaken via an opportunistic and snowball sampling methodology through emails, newsletters, and social media posts. A snowballing sampling strategy can introduce sampling bias as it is a nonprobability method and tends to generate a sample that is unbalanced by selected demographic groups while opportunity sampling can be unrepresentative (Leighton et al., 2021; Sadler et al., 2010). Secondly, data were collected online using a self-report survey, which may increase the risk of selection bias, social desirability bias, or recall bias (Rosenman et al., 2011). However, this was the most appropriate and ethical way to safely gather data on a large scale during the pandemic and allows better access to information (Nayak & Narayan, 2019).

Thirdly, while the cross-sectional design helped gain a representative understanding of the impacts that the COVID-19 pandemic has had on social work and social care workers in the UK, the study design means we cannot determine causality. Furthermore, our findings of this study cannot rule out other environmental drivers that influenced the WRQoL and well-being and therefore must be viewed tentatively. Fourthly, the results suggested possible collinearity within this model and thus findings should be viewed with caution as this could have led to an inflation of the variance of regression parameters (Dormann et al., 2013). Finally, most of the sample at both time periods were female (over 85%), therefore any generalization to male social care workers and social workers must be considered tentatively. However, this higher representation of females involved in the study is largely reflective of the majority composition of the social work and social care profession (Batra et al., 2020; Holmes et al., 2021). Additionally, over 94% of the sample were White, this makes the findings of this study less generalizable to other ethnicities. Furthermore, most of the sample were from Northern Ireland and England in Phase 1 (90%) with a smaller sample of respondents from Scotland and Wales (10%). In Phase 2, the distribution of response rates per country was more balanced, with Wales having a higher response rate than in Phase 1, at 31% of the total sample. Northern Ireland made up 34%, England 22%, and Scotland 13%. Levels of response rate make the findings of this present study more or less generalizable to the social work and care workforce in the included countries. The authors therefore do not make generalizable claims in the data but see the value of the research as a snapshot at time points during the pandemic phases.

Implications and future research

Despite the limitations of this study, the results have several important implications to consider. Our findings have highlighted that WRQoL and well-being deteriorated between Phase 1 and Phase 2. This demonstrates the importance of understanding that the social work and care workforce was already one of the most stressful areas of employment within the UK and at risk of severe mental health problems due to work pressures and caseloads or care work. Therefore, the major implication of this study is to highlight that individuals, organizations, and government departments need to limit stressors on social work and care employees for any future crisis, but also to address the widespread stressors that were evident prepandemic and seem to account in part for high staff turnover and vacancy rates which affect continuity and quality of care and support.

More specifically, there is evidence that long-lasting stressors impacting work–life balance also often led to burnout and lower well-being (Holmes et al., 2021; Peinado & Anderson, 2020). Already in England, the Local Government Association has highlighted that 94% of County Councils find it difficult to recruit children's social workers (Local Government Association, 2021), while the high turnover rate of social care workers remains (Skills for Care, 2020). The findings of the present study suggest that with decreasing well-being and quality of working life, the social care workforce may be at a greater risk of burnout and thus accelerated exit from the sector.

Employing organizations need to develop strategies that offer support and coping strategies to counteract increased stress which impedes well-being and quality of working life. This could build on evidence that negative psychological impact may be able to be reduced when good two-way communication and the introduction of early support systems and reflection time are in place, reducing the severity of work-related stressors (Evanoff et al., 2020; Greenberg et al., 2020). Compassionate employers and a positive, supportive workplace could overcome the pressure in social work and care work and improve well-being and WRQoL (Cook et al., 2020; Kalliath et al., 2020). Other means of achieving a better work–life balance to improve well-being must involve a health-promoting lifestyle with training and development opportunities, self-care, flexible working hours, and fewer excess demands and working responsibilities (Miller & Reddin Cassar, 2021). Kalliath et al. (2020) have suggested that promoting work–family measures among the social care workforce can contribute to positive work outcomes. The potential of these workplace supports also are evidenced in this current study and formed one of the “good practice recommendations” in the main study report which emerged from the data (Ravalier, 2019).

Future research could investigate how burnout influences well-being and WRQoL and the role positive coping strategies play in improving the well-being and WRQoL of the social work and care workforce. Furthermore, more in-depth work is necessary to better understand the impact of COVID-19 and its legacy on working conditions and psychological well-being to provide further clarification of the quantitative data collected in this present study. This would allow for a better understanding of the WRQoL at both individual and organizational levels to be able to develop further recommendations to mitigate the negative impact of the pandemic and its legacy on the well-being of social work and care workers.

Conclusions

In summary, the UK social care system is complex and fragmented with a workforce that has been both severely overwhelmed yet resilient, while social workers may be under pressure due to increased service demands following the height of the pandemic. The results from this study provide the social work and social care workforce with a voice that evidences the impact of the COVID-19 pandemic (May 2020–January 2021) on working conditions and well-being. Notably, the study found that mental well-being and WRQoL worsened as the pandemic continued and the UK started to experience the second period of lockdown following rising numbers of deaths and infections. Findings showed significant differences between Phase 1 and Phase 2 on all measures examined. The results of this study have the potential to inform recommendations and interventions to improve working conditions within the social care and work professions, whose experiences, while different at some levels, were similar in respect to the stressors they encountered.

Acknowledgements

The authors would like to thank all respondents, the Northern Ireland Social Care Council (NISCC), and the Southern Health and Social Care Trust in Northern Ireland for seed funding for the survey. Moreover, thanks to Community Care ©, Northern Ireland Practice and Education Council for Nursing and Midwifery, Royal College of Nursing, Royal College of Midwifery, Royal College of Occupational Therapists, British Dietetic Association, College of Podiatry, and the NISCC for advertising and promoting the study.

Ethics: The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Filter Ethics Committee in the School of Nursing at Ulster University (Ref No. 2020/5/3.1, April 23, 2020, Ulster University; Ulster University IRAS Ref No. 20/0073).

Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by seed funding from the Northern Ireland Social Care Council and the Southern Health and Social Care Trust in Northern Ireland, and the NIHR Policy Research Programme grant to the NIHR Policy Research Unit in Health and Social Care Workforce at King's College London (grant number NIHR PRP).

Authors’ contributions: All authors contributed to the development of the survey, dissemination, and write-up of this article. Ravalier conducted data analysis, with all other authors checking and commenting on the analysis. McFadden led the team in gaining funding, with Manthorpe subsequently supporting to lead to a wider team.

Contributor Information

Jermaine Ravalier, School of Science, Bath Spa University, Newton St Loe, Bath, UK.

Ruth Neill, University of Ulster, Londonderry, Northern Ireland, UK.

Jill Manthorpe, King’s College London, London, UK.

Denise Curry, Queen’s University Belfast, Belfast, Northern Ireland, UK.

References

  1. Abrams L. S., Dettlaff A. J. (2020). Voices from the frontlines: Social workers confront the COVID-19 pandemic. Social Work, 65(3), 302–305. 10.1093/sw/swaa030 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Aughterson H., McKinlay A. R., Fancourt D., Burton A. (2021). Psychosocial impact on frontline health and social care professionals in the UK during the COVID-19 pandemic: A qualitative interview study. BMJ Open, 11(2), e047353. 10.1136/bmjopen-2020-047353 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bakker A. B., Demerouti E., De Boer E., Schaufeli W. B. (2003). Job demands and job resources as predictors of absence duration and frequency. Journal of Vocational Behavior, 30, 893–917. 10.1016/S0001-8791(02)00030-1 [DOI] [Google Scholar]
  4. Batra K., Singh T. P., Sharma M., Batra R., Schvaneveldt N. (2020). Investigating the psychological impact of COVID-19 among healthcare workers: A meta-analysis. International Journal of Environmental Research and Public Health, 17(23), 9096. 10.3390/ijerph17239096 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bell D., Comas-Herrera A., Henderson D., Jones S., Lemmon E., Moro M., Murphy S., O’Reilly D., Patrignani P. (2020). COVID-19 mortality and long-term care: a comparison. https://ltcCOVID.org/wp-content/uploads/2020/08/COVID-19-mortality-in-long-term-care-final-Sat-29-v1.pdf
  6. Berg-Weger M., Morley J. E. (2020). Loneliness and social isolation in older adults during the COVID-19 pandemic: Implications for gerontological social work. The Journal of Nutrition, Health and Aging, 24, 456–458. 10.1007/s12603-020-1366-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Bonetti S., Cottell J., Ziolkowski S., Broadbery J. (2021). The COVID-19 pandemic and the early years workforce: Staffing decisions in an uncertain environment. https://epi.org.uk/publications-and-research/the-COVID-19-pandemic-and-the-early-years-march-2021/
  8. British Association of Social Work (BASW) (2021). Social work during the COVID-19 pandemic: Initial findings. https://www.basw.co.uk/system/files/resources/basw_social_working_during_the_COVID_19_pandemic_initial_findings_26.01.21.pdf
  9. Chandola T., Brunner E., Marmot M. (2006). Chronic stress at work and the metabolic syndrome: Prospective study. BMJ, 332(7540), 521–525. 10.1136/bmj.38693.435301.80 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Comas-Herrera A., Glanz A., Curry N., Deeny S., Hatton C., Hemmings N., Humphries R., Lorenz-Dant K., Oung C., Rajan S., Suarez-Gonzalez A. (2020). The COVID-19 long-term care situation in England. https://ltcCOVID.org/wp-content/uploads/2020/11/COVID-19-Long-Term-Care-situation-in-England-19-November-3.pdf
  11. Cook L. L., Zschomler D., Biggart L., Carder S. (2020). The team as a secure base revisited: Remote working and resilience among child and family social workers during COVID-19. Journal of Children’s Services, 15(4), 259–266. 10.1108/JCS-07-2020-0031 [DOI] [Google Scholar]
  12. Dormann C. F., Elith J., Bacher S., Buchmann C., Carl G., Carré G., Marquéz J. R. G., Gruber B., Lafourcade B., Leitao P. J., Münkemüller T. (2013). Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36(1), 27–46. 10.1111/j.1600-0587.2012.07348.x [DOI] [Google Scholar]
  13. Easton S., Van Laar D. (2018). User manual for the work-related quality of life (WRQoL) scale: A measure of quality of working life (2nd edn). University of Portsmouth. [Google Scholar]
  14. Evanoff B. A., Strickland J. R., Dale A. M., Hayibor L., Page E., Duncan J. G., Gray D. L. (2020). Work-related and personal factors associated with mental well-being during the COVID-19 response: Survey of health care and other workers. Journal of Medical Internet Research, 22(8), e21366. 10.2196/21366 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Farkas K. J., Romaniuk J. R. (2020). Social work, ethics and vulnerable groups in the time of coronavirus and COVID-19. Society Register, 4(2), 67–82. 10.14746/sr.2020.4.2.05 [DOI] [Google Scholar]
  16. Field A. (2013). Discovering statistics using IBM SPSS statistics (4th edn). London: SAGE. [Google Scholar]
  17. Flower C., McDonald J., Sumski M. (2005). Review of turnover in Milwaukee county private agency welfare ongoing case management staff. The consortium of community, agency, and university partnerships to improve public child welfare. Children and Family Research Centre, University of Illinois. [Google Scholar]
  18. Gaskell C. (2010). ‘If the social worker had called at least it would show they cared’. Young care leavers’ perspectives on the importance of care. Children & Society, 24(2), 136–147. 10.1111/j.1099-0860.2009.00214.x [DOI] [Google Scholar]
  19. Golightley M., Holloway M. (2020). Editorial: Unprecedented times? Social work and society post-COVID-19. British Journal of Social Work, 50(5), 1297–1303. 10.1093/bjsw/bcaa110 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Gordon A. L., Goodman C., Achterberg W., Barker R. O., Burns E., Hanratty B., Martin F. C., Meyer J., O’Neill D., Schols J., Spilsbury K. (2020). Commentary: COVID in care home – challenges and dilemmas in healthcare delivery. Age and Ageing, 49(5), 701–705. 10.1093/ageing/afaa113 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Gov.uk (2021). Children’s social work workforce. https://explore-education-statistics.service.gov.uk/find-statistics/children-s-social-work-workforce
  22. Greenberg N., Docherty M., Gnanapragasam S., Wessely S. (2020). Managing mental health challenges faced by healthcare workers during COVID-19 pandemic. BMJ, 368. https://doi.org/https://doi.org/10.1136/bmj.m1211 [DOI] [PubMed] [Google Scholar]
  23. Harrikari T., Romakkaniemi M., Tiitinen L., Ovaskainen S. (2021). Pandemic and social work: Exploring Finnish social Workers’ experiences through a SWOT analysis. British Journal of Social Work, 51(5), 1644–1662. 10.1093/bjsw/bcab052 [DOI] [Google Scholar]
  24. Health and Safety Executive (2020). Work-related stress, anxiety or depression statistics in Great Britain, 2020. https://www.hse.gov.uk/statistics/causdis/stress.pdf
  25. Holmes M. R., Rentrope C. R., Korsch-Williams A., King J. A. (2021). Impact of COVID-19 pandemic on posttraumatic stress, grief, burnout, and secondary trauma of social workers in the United States. Clinical Social Work Journal, 49(4), 495–504. 10.1007/s10615-021-00795-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Hussein S. (2020). Pulse survey: The impact of COVID-19 on social care workers’ workload, wellbeing and ability to provide care safely: Findings from the UK. Health Foundation. https://ltcCOVID.org/2020/11/09/the-impact-of-COVID-19-on-social-care-workers-workload-wellbeing-and-ability-to-provide-care-safely-findings-from-the-uk/#:∼:text=A%20summary%20of%20key%20findings%3A&text=A%20staggering%2081%25%20indicated%20increased,the%20onset%20of%20COVID%2D19.&text=Half%20of%20the%20respondents%20felt,they%20were%20providing%20had%20increased [Google Scholar]
  27. Johnson C., Coburn S., Sanders-Early A., Felton J., Winterbotham M., McLaughlin H., Pollock S., Scholar H., McCaughan S. (2020). Longitudinal study of local authority child and family social workers. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/906778/Longitudinal_study_of_local_authority_child_and_family_social_workers_Wave_2.pdf
  28. Kalliath P., Kalliath T., Chan X. W., Chan C. (2020). Enhancing job satisfaction through work–family enrichment and perceived supervisor support: The case of Australian social workers. Personnel Review, 49(9), 2055–2072. 10.1108/PR-06-2018-0219 [DOI] [Google Scholar]
  29. Ladhani S. N., Chow J. Y., Janarthanan R., Fok J., Crawley-Boevey E., Vusirikala A., Fernandez E., Perez M. S., Tang S., Dun-Campbell K., Wynne-Evans E. (2020). Increased risk of SARS-CoV-2 infection in staff working across different care homes: Enhanced COVID-19 outbreak investigations in London care homes. Journal of Infection, 81(4), 621–624. 10.1016/j.jinf.2020.07.027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Leighton K., Kardong-Edgren S., Schneidereith T., Foisy-Doll C. (2021). Using social media and snowball sampling as an alternative recruitment strategy for research. Clinical Simulation in Nursing, 55, 37–42. 10.1016/j.ecns.2021.03.006 [DOI] [Google Scholar]
  31. Local Government Association (2021). COVID-19 workforce survey, week ending 5 March 2021. https://www.local.gov.uk/publications/COVID-19-workforce-survey-week-ending-5-march-2021
  32. Marmot M. G., Stansfeld S., Patel C., North F., Head J., White I., Brunner E., Feeney A., Marmot M. G., Smith G. D. (1991). Health inequalities among British civil servants: The Whitehall-II study. The Lancet, 337(8754), 1387–1394. 10.1016/0140-6736(91)93068-K [DOI] [PubMed] [Google Scholar]
  33. Marshall F., Gordon A., Gladman J., Bishop S. (2021). Care homes, their communities, and resilience in the face of the COVID-19 pandemic: Interim findings from a qualitative study. BMC Geriatrics, 21, 102. 10.1186/s12877-021-02053-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. McFadden P., Ross J., Moriarty J., Mallett J., Schroder H., Ravalier J., Manthorpe J., Currie D., Harron J., Gillen P. (2021). The role of coping in the wellbeing and work-related quality of life of UK Health and Social Care workers during COVID-19. International Journal of Environmental Research and Public Health, 18, 815. 10.3390/ijerph18020815 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Miller J. J., Reddin Cassar J. (2021). Self-care among healthcare social workers: The impact of COVID-19. Social Work in Health Care, 60(1), 30–48. 10.1080/00981389.2021.1885560 [DOI] [PubMed] [Google Scholar]
  36. Minnotte K. L. (2016). Extending the job demands-resources model: Predicting perceived parental success among dual-earners. Journal of Family Issues, 37(3), 416–440. 10.1177/0192513X13518777 [DOI] [Google Scholar]
  37. Nayak M. S. D. P., Narayan K. A. (2019). Strengths and weakness of online surveys. IOSR Journal of Humanities and Social Science, 24(5), 31–38. 10.9790/0837-2405053138 [DOI] [Google Scholar]
  38. Ng Fat L., Scholes S., Boniface S., Mindell J., Stewart-Brown S. (2017). Evaluating and establishing norms for mental wellbeing using the short Warwick-Edinburgh mental well-being scale (SWEMWBS): Findings from the health survey for England. Quality of Life Research, 26(5), 1129–1144. 10.1007/s11136-016-1454-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Office for National Statistics (2021). Coronavirus (COVID-19) related deaths by occupation, England and Wales: Deaths registered between 9 March and 28 December 2020. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/causesofdeath/bulletins/coronavirusCOVID19relateddeathsbyoccupationenglandandwales/deathsregisteredbetween9marchand28december2020
  40. Office for National Statistics (ONS.gov.uk) (2020). COVID-19 and the impact on social care. https://blog.ons.gov.uk/2020/07/09/COVID-19-and-the-impact-on-social-care/
  41. Peinado M., Anderson K. N. (2020). Reducing social worker burnout during COVID-19. International Social Work, 63(6), 757–760. 10.1177/0020872820962196 [DOI] [Google Scholar]
  42. Pluut H., Wonders J. (2020). Not able to lead a healthy life when you need it the most: Dual role of lifestyle behaviors in the association of blurred work-life boundaries with well-being. Frontiers in Psychology, 11(607294). 10.3389/fpsyg.2020.607294 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Ravalier J. M. (2019). Psycho-social working conditions and stress in UK social workers. British Journal of Social Work, 49, 371–390. 10.1093/bjsw/bcy023 [DOI] [Google Scholar]
  44. Ravalier J. M., McFadden P., Boichat C., Clabburn O., Moriarty J. (2021). Social worker well-being: a large mixed-methods study. British Journal of Social Work, 51, 297–317. [Google Scholar]
  45. Reddington M., Ahmadiyankooshkghazi M., Bakhshalian E., Kennedy O., Elmi F. (2021). The standards for employers of social workers: Social work health check report. https://kinetiq-uk.co.uk/wp-content/uploads/2021/02/National-Standards-for-Employers-of-Social-Workers.pdf
  46. Riello M., Purgato M., Bove C., MacTaggart D., Rusconi E. (2020). Prevalence of post-traumatic symptomatology and anxiety among residential nursing and care home workers following the first COVID-19 outbreak in northern Italy. Royal Society Open Science, 7(9). 10.1098/rsos.200880 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Rosengren A., Hawken S., Ounpuu S., Sliwa K., Zubaid M., Almahmeed W. A., Blackett K. N., Aitthi-Amorn C., Sato H., Tusuf S. (2004). Association of psychological risk factors with risk of acute myocardial infarction in 11,119 cases and 13,648 controls from 52 countries (the INTERHEART studies): A case-control study. The Lancet, 364(9438), 953–962. 10.1016/S0140-6736(04)17019-0 [DOI] [PubMed] [Google Scholar]
  48. Rosenman R., Tennekoon V., Hill L. G. (2011). Measuring bias in self-reported data. International Journal of Behavioural and Healthcare Research, 2(4), 320–332. 10.1504/IJBHR.2011.043414 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Roxby A. C., Greninger A. L., Hatfield K. M., Lynch J. B., Dellit T. H., James A., Taylor J., Page L. C., Kimball A., Arons M., Munanga A. (2020). Outbreak investigation of COVID-19 among residents and staff of an independent and assisted living community for older adults in Seattle, Washington. JAMA Internal Medicine, 180(8), 1101–1105. 10.1001/jamainternmed.2020.2233 [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Sadler G. R., Lee H. C., Lim R. S. H., Fullerton J. (2010). Recruitment of hard-to-reach population subgroups via adaptations of the snowball sampling strategy. Nursing & Health Sciences, 12(3), 369–374. 10.1111/j.1442-2018.2010.00541.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Sanders R. (2020). COVID-19: Stress, anxiety, and social care worker’s mental health, Dundee IRISS.https://www.iriss.org.uk/resources/esss-outlines/COVID-19-stress-anxiety-and-social-care-workers-mental-health
  52. Schaufeli W. B., Bakker A. B. (2004). Job demands, job resources, and their relationship with burnout and engagement: A multi-sample study. Journal of Organizational Behavior, 25(3), 293–315. 10.1002/job.248 [DOI] [Google Scholar]
  53. Schaufeli W. B., Bakker A. B., Van Rhenen W. (2009). How changes in job demands and resources predict burnout, work engagement, and sickness absenteeism. Journal of Organizational Behavior, 30(7), 893–917. 10.1002/job.595 [DOI] [Google Scholar]
  54. Schieman S., Badawy P. J., Milkie M. A., Bierman A. (2021). Work-Life conflict during the COVID-19 pandemic. Socius, 7. 10.1177/2378023120982856 [DOI] [Google Scholar]
  55. Skills for Care (2020). The state of the adult social care sector and workforce in England. https://www.skillsforcare.org.uk/adult-social-care-workforce-data/Workforce-intelligence/publications/national-information/The-state-of-the-adult-social-care-sector-and-workforce-in-England.aspx
  56. Skills for Care (2021). Days due to sickness, monthly tracking. https://skillsforcare.org.uk/adult-social-care-workforce-data/Workforce intelligence/publications/Topics/COVID-19/days-lost-due-to-sickness.aspx
  57. Social Care Institute for Excellence (SCIE) (2020). Beyond COVID: New thinking on the future of adult social care. https://www.scie.org.uk/care-providers/coronavirus-COVID-19
  58. Spilsbury K., Devi R., Griffiths A., Akrill C., Astle A., Goodman C., Gordon A., Hanratty B., Hodkinson P., Marshall F., Meyer J., Thompson C. (2021). Seeking answers for care homes during the COVID-19 pandemic (COVID SEARCH). Age and Ageing, 50(2), 335–340. 10.1093/ageing/afaa201 [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Stewart-Brown S., Tennant A., Tennant R., Platt S., Parkinson J., Weich S. (2009). Internal construct validity of the Warwick-Edinburgh mental well-being scale (WEMWBS): A Rasch analysis using data from the Scottish health education population survey. Health and Quality of Life Outcomes, 7, Article No. 15. 10.1186/1477-7525-7-15 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Vaingankar J. A., Abdin A. E., Chong S. A., Sambasivam R., Seow E., Jeyagurunathan A., Picco L., Stewart-Brown S., Subramaniam M. (2017). Psychometric properties of the short Warwick Edinburgh mental well-being scale (SWEMWBS) in service users with schizophrenia, depression and anxiety spectrum disorders. Health and Quality of Life Outcomes, 15(1), 153. 10.1186/s12955-017-0728-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Van Laar D., Edwards J. A., Easton S. (2007). The work-related quality of life scale for healthcare workers. Journal of Advanced Nursing, 60(3), 325–333. 10.1111/j.1365-2648.2007.04409.x [DOI] [PubMed] [Google Scholar]
  62. Wang X., Cheng Z. (2020). Cross-sectional studies: Strengths, weaknesses, and recommendations. Chest, 185(1, Suppl), S65–S71. 10.1016/j.chest.2020.03.012 [DOI] [PubMed] [Google Scholar]
  63. White E. M., Wetle T. F., Reddy A., Baier R. R. (2021). Front-line nursing home staff experiences during the COVID-19 pandemic. Journal of the American Medical Directors Association, 22(1), 199–203. 10.1016/j.jamda.2020.11.022 [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. World Health Organization (2020). Statement—older people are at highest risk from COVID-19, but all must act to prevent community spread. https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-COVID-19/statements/statement-older-people-are-at-highest-risk-from-COVID-19,-but-all-must-act-to-prevent-community-spread

Articles from Journal of Social Work (London, England) are provided here courtesy of SAGE Publications

RESOURCES