Intolerance of uncertainty, fear of contamination and perceived social support as predictors of psychological distress in NHS healthcare workers during the COVID-19 pandemic

ABSTRACT Psychological distress has been repeatedly quantified over the course of the pandemic, however this has not always included broader healthcare workers, and has mostly focused on prevalence and occupational factors. This study investigated intolerance of uncertainty (IOU), fear of contamination and perceived social support as key predictors of psychological distress in healthcare professionals, between the 10th and 23 June 2020, during the first wave of the COVID-19 pandemic. This study was a cross-sectional, online survey design. Opportunity sampling was used to recruit to the study, primarily using social media sites and snowballing techniques. The final sample included 342 National Health Service (NHS) healthcare workers. IU (p < .001), gender (p < .001), fear of contamination (p = .007), perceived social support (p = .012), and age (p = .017) significantly predicted psychological distress in the sample and accounted for 36.2% of variance in psychological distress scores. IOU accounted for 28.2% of this variance. A two-way post hoc ANOVA, looking at gender and profession, showed a significant main effect of gender on psychological distress scores (F(1,218) = 7.156, p = .008, ηp 2 = .032), with females reporting significantly higher psychological distress scores compared to males. In conclusion, higher levels of intolerance of uncertainty, fear of contamination and lower levels of perceived social support significantly influenced higher scores of psychological distress. These factors should be considered when adapting and delivering evidence-based interventions to healthcare staff during this crisis.


Introduction
Coronavirus Infectious Disease 2019 (SARS CoV-2, COVID-19) spread rapidly and prolifically across the globe from December 2019. During and beyond the pandemic, lack of adequate protection and high pressure on UK NHS personnel has been widely reported (Lluch et al., 2022). It is vital the psychological impact on healthcare workers (HCW) is assessed; research investigating not only prevalence, but mechanisms of distress have been identified as key targets in psychological research (Holmes et al., 2020;Xiang et al., 2020). Lack of adequate protection and high pressure on UK NHS services has been widely reported, with emerging research detailing preliminary results of the impact on doctors (Roberts et al., 2021) and other health professionals (Vindrola-Padros et al., 2020).
Uncertainty associated with the proliferation of COVID-19 has been exacerbated by a lack of information, inconsistent guidance around infection control measures and false claims (Mukhtar, 2020). This is likely heightened for NHS professionals who are used to working to strict and evidence-based guidelines. Furthermore, the multi-wave nature of the pandemic is likely increasing uncertainty over when life will return to 'normal'. Uncertainty and fear of infection are understandable responses; both factors are already associated with poorer psychological health during COVID-19 (Rettie & Daniels, 2020;Xiang et al., 2020). Intolerance of Uncertainty (IOU) reflects an inability to cope with negative, or ambiguous, situations (Buhr & Dugas, 2002) and a preference for predictable situations (Birrell et al., 2011).
Research in two community samples has outlined the influence that intolerance of uncertainty can have on health anxiety and concerns about COVID-19 (Tull et al., 2020;Wheaton et al., 2021). Intolerance of uncertainty was associated with body vigilance, perceived likelihood of contracting a serious illness and the possibility of severe consequences from it (Tull et al., 2020). IOU was more relevant to health anxiety than the actual risk of participants contracting, and dying from, COVID-19, for those that had high levels of dispositional IOU (Tull et al., 2020). These findings indicate the possible role of dispositional IOU influencing distress during a time of great uncertainty. This should be investigated in healthcare workers, who are one group at greater risk of exposure to COVID-19, contracting, and experiencing severe consequences of, COVID-19. Freeston et al.'s (2020) model of uncertainty distress within the context of Coronavirus, proposes that individuals with a greater dispositional trait of IU experience increased adverse reactions to threat and uncertainty in the 'real-world', resulting in distress. In line with this model and recent publications, uncertainty surrounding exposure to COVID-19 may possibly increase threat perception and psychological distress in healthcare workers with higher dispositional IOU.
The novel and uncertain nature of COVID-19 during the first wave is likely to have given rise to infection and contamination related fears, particularly in those with repeated exposure to COVID-19, such as HCW. Fear of contamination has been a key psychological factor in previous pandemic research (Blakey & Abramowitz, 2017;Blakey et al., 2015). For individuals who have an increased fear of contamination regarding COVID-19 heightened infection control measures may influence contamination fears (Wheaton et al., 2012). When considering those most at risk, fear of contamination may have a stronger influence towards distress in healthcare workers who are frequently being exposed to COVID-19. In previous research, nurses reported more contamination concerns and emotional distress than allied health professionals, doctors and staff without patient contact (Nickell et al., 2004), highlighting the possibility that healthcare roles and degree of exposure may be relevant in understanding who is most at risk psychologically.
Whilst fear may be a 'normal' response to a pandemic (Haig-Ferguson et al., 2021), social support is a known protective factor against stress resulting from adverse circumstances (Maunder et al., 2004) and has been linked to fewer psychological consequences in HCW (Brooks et al., 2018;Marjanovic et al., 2007). Emerging research has reflected low levels of support being associated with higher psychological distress in the current pandemic (Elbay et al., 2020;Xiao et al., 2020). This may be related to frontline workers having to live apart from their families during the pandemic (Kang et al., 2020), impacting access to social support. Given the pivotal role of restricted access to social support over the pandemic and during lockdown (Brooks et al., 2020), a better understanding of the relative importance of social support could enhance our understanding of how this relates to other key factors such as the context of uncertainty and fear.
A call to action early in the pandemic outlined that research must prioritise identification of the psychological impact of the pandemic on healthcare workers and how best to support them (Holmes et al., 2020). Given high rates of psychological distress in HCW (Roberts et al., 2021) this study sought to examine the degree of relationship between these three variables across a broad range of HCW professions;: uncertainty around COVID-19 may give rise to fear of contamination in healthcare workers, particularly in the first wave due to limited understanding of transmission of a novel virus and inadequate PPE; one of the key factors that may mitigate against psychological harms is social support, however this has been greatly confounded by government restrictions. This study widens the scope to include and compare different NHS professional groups and considers a key support mechanism at a time when it was its most relevant, emergence from lockdown. By understanding the presence and influence of these psychological factors on distress across a range of healthcare professions, while considering other personal characteristics, we can better understand and address psychological need across the UK NHS workforce.

Design and procedure
An online cross-sectional design was used to survey HCW between 10 th and 23 June 2020, using opportunity sampling methods. Recruitment took place as the first lockdown restrictions began to ease. This study received ethical approval from its associated institution (reference: 20-116). National Research Ethics Committee approval was not required.

Participants
HCW were eligible to participate in the study if they had been employed in the NHS when COVID-19 was declared a pandemic (11 March 2020), and their role included patient contact (i.e. not administration staff). Overall, 408 consented to take part, 63 withdrew (15.4%), three were excluded due to incomplete data or not meeting inclusion criteria, leaving 342 participants.

Independent variables
Demographic data, data on profession, exposure to COVID-19, redeployment, size of household and presence of pre-existing mental health conditions was also collected. IOU was measured using the 12-item Intolerance of Uncertainty Scale (Carleton et al., 2007) which demonstrated excellent internal consistency in the present sample (Cronbach's α = .89).
Fear of contamination was measured using the 10-item Contaminations Obsessions and Washing Compulsions subscale of the Padua Inventory (PI-WSUR; Burns et al., 1996). This scale had good internal consistency in the present study (Cronbach's α = .91).
The 12 item Multidimensional Scale of Perceived Social Support (MSPSS; Zimet et al., 1988) measured social support. The MSPSS had excellent internal consistency in the present sample (Cronbach's α = .96).

Dependent variables
Psychological distress was measured using the short version of the Depression Anxiety Stress Scale (DASS-21; Lovibond & Lovibond, 1995). High internal consistency has been reported for all subscales (Cronbach's α = .91, .80 and .84) and demonstrates the utility as an overall measure of distress (Sinclair et al., 2012). In the current sample, this measure presented excellent internal consistency (Cronbach's α = .94).

Results
Data were analysed using SPSS Version 25. Preliminary analyses assessed suitability of data for planned bivariate and multiple stepwise regression analyses. Studentized residuals and Cook's distance highlighted no influential outliers. There was 0.28% data missing data from the validated measures, mean imputation was used due to low rate of missing data (Kang, 2013). Shapiro-Wilk normality tests indicated non-normally distributed data therefore Spearman's Rank correlations were performed for all continuous variables. Scatterplots highlighted linear relationships between the independent and dependent variables with no multicollinearity. Homoscedasticity was illustrated through visual inspection of the studentized residuals versus unstandardized predicted values plot, indicating that the variance in psychological distress scores was well explained by the predictor variables.
The sample were predominantly female (75.4) white (84.2) with 14% of the sample from black and Asian ethnic minorities directly proportionate to the general population (Office for National Statistics, 2011). The mean age of participants was 40.10 (SD = 11.92) (see , Table 1 for further details).
The mean scores for IOU, fear of contamination and perceived social support were M = 27.96 (SD = 8.60), M = 9.39 (SD = 8.45) and M = 5.75 (SD = 1.23), respectively. Data from the key psychological variables were similar to existing data. Mean psychological distress scores (M = 26.63, SD = 23.63) were significantly higher than scores taken from normative data (M = 18.86; Henry & Crawford, 2005; t(341) = 6.09, p < .001), with 11% of participants reaching the predefined cut off of ≥60 (Beaufort et al., 2017). Nurses reported the highest mean score of psychological distress (M = 40.00, SD = 25.69), followed by support staff (M = 38.31, SD = 29.38). Doctors reported the lowest mean score of psychological distress (M = 19.59, SD = 18.88). Table 2 depicts the relationships between study variables. Age and exposure demonstrated significant relationships with psychological distress (r s = −.29, n = 319, p = < .001; r s = .13, n = 319, p = .022, respectively). The absence of a significant relationship between social support and the size of household (r s = .02, n = 262, p = .706) indicated these factors should be considered separately and were not controlled for. IOU and fear of contamination both demonstrated significant positive correlations with psychological distress (r s = .5, n = 342, p = < .001; r s = .29, n = 342, p < .001, respectively). Those with lower perceived social support reported more psychological distress (r s = −.23, n = 342, p = < .001). IOU was also significantly and positively correlated with fear of contamination (r s = .31, n = 342, p = .000) and significantly and negatively correlated with perceived social support (r s = −.15, n = 342, p = .004). The number of participants per professions were too small to perform an ANOVA to examine group differences. As the sample of doctors (n = 125) and nurses (n = 98) were similar, a Mann-Whitney U test was performed, indicating significantly lower psychological distress levels in doctors (M = 19.59; SD = 18.88), compared to nurses (M = 30.40; SD = 25.69), (U = 4309.50, p < .001). As profession was not significant in the regression model and the gender split for nurses was skewed (9 males, 88 females, 1 not reported) a post-hoc two-way ANOVA was performed, indicating a significant effect of gender on psychological distress scores (F(1,218) = 7.16, p = .008, η p 2 = .03). There was no significant effect of profession on gender (F(1, 218) = .06, p = .806, η p 2 = .00) or psychological distress scores (F(1, 218) = 2.73, p = .100, η p 2 = .01). A multiple stepwise regression was performed, with psychological distress as the criterion variable and age, gender, ethnicity, IOU, fear of contamination and perceived social support as predictors. Age and gender were predetermined as predictor variables, due to the pre-existing evidence that implicates these variables to influence psychological distress (Sirois & Owens, 2021). Ethnicity was recoded into BAME and white for the regression, as the emerging literature describes a disproportionate impact of COVID-19 on BAME communities as a whole (Bailey & West, 2020;Moorthy & Sankar, 2020), as opposed to specific ethnicities. Five significant predictors accounted for 36% of the variance of psychological distress, including IOU, fear of contamination, social support, gender and age (R 2 = .36, F(1, 281) = 5.40, p = .021). IOU accounted for 28.1% of the variance (R 2 = .28, F(1, 285) = 111.59, p < .001) with gender accounting for an additional R 2 change of 3.8% (β = .20, p < .001) other variables accounting for less than 2% (see , Table 3). Profession, exposure and ethnicity were excluded.

Discussion
Healthcare workers (HCW) who were less able to tolerate uncertainty, more fearful of contamination and felt they had limited social support were experiencing more psychological distress, with IOU accounting for the majority of the variance of psychological distress. This is consistent with previous studies and ongoing research examining the key role of uncertainty during the COVID-19 pandemic, which now extends as a relevant factor to HCW. Furthermore, the sample of this study was inclusive to all NHS workers with patient contact, rather than a specific profession as has commonly been the case Roberts et al., 2021).
IOU was identified as the key factor that accounted for the majority of the variance of psychological distress, consistent with findings in other non-HCW based studies (Freeston et al., 2020;Rettie & Daniels, 2020). Our key findings support Freeston et al.'s (2020) argument that uncertainty is the largest exacerbator of psychological distress during the pandemic. IOU has been positively associated with poorer mental well-being, including health anxiety and COVID-19 concerns, during the pandemic (Satici et al., 2020;Tull et al., 2020;Wheaton et al., 2021). Our findings offer clear evidence that IOU must be targeted in interventions with HCW particularly given high levels of continued uncertainty within their working environments.
This study delineates the contribution and influence of other psychological and social variables: fear of contamination and perceived social support were significant predictors of distress but marginal in their contribution. Freeston et al.'s (2020) model also considers the influence of threat on distress. The obvious threat in this context is becoming infected with coronavirus and passing it onto others (Shanafelt et al., 2020) with a recent longitudinal study indicating fear of infecting others as the most influential factor in relation to psychological distress and trauma in doctors (Roberts et al., 2021); our findings indicated that fear of contamination and IOU are significantly related in this high-risk environment, but direction of influence is difficult to disentangle in a cross-sectional study.
At the time of the study knowledge and transmission of coronavirus was poorly understood, a potentially exacerbating time for fear of contamination, however recent research identifies fear of contamination as a key factor despite increased understanding and management of COVID-19 (Daniels & Rettie, 2022), and our findings demonstrate the role of FoC within the context of uncertainty during the pandemic. Our study was limited in that it did not assess whether fear of contamination was related to fear of HCW becoming ill themselves or fear of transmitting the infection to others; the latter of which has been identified as a predictor of distress in HCW (Roberts et al., 2021). It would be beneficial to further understand the role of fear of contamination within the context of uncertainty.
The protective role of social support has been illustrated in emerging research (Elbay et al., 2020;Hu et al., 2020) and supports the 'buffering' hypothesis that posits contextappropriate support during times of stress can protect psychological wellbeing (Cohen & Wills, 1985), we see in our sample that social support has an inverted linear relationship with fear of contamination and intolerance of uncertainty. Perceived social support has been shown to have a negative association with psychological distress in healthcare workers (Ortiz-Calvo et al., 2022). Our findings further confirm this relationship and outline the need to further investigate different sources of social support for healthcare workers, such as support from colleagues, friends, relatives. The benefits of different forms of social support are subjective; it is important that future research does not just collect data on levels of social support but, essentially, how satisfied individuals perceive themselves to be with different sources of social support. Considering the likert scale response and our mean score for social support, our findings may indicate that was some satisfaction with the support that our participants felt they had. Researching this further is imperative when it comes to offering sources of social support that will have the most protective influence over distress.
Nevertheless, the present findings clearly demonstrate the need to ensure healthcare workers continue to have personal and protective equipment provided when needed and that sources of social support are increased to help alleviate the psychological impact that the pandemic has had on many healthcare workers. Our findings provide key evidence on how we may be able to help prevent distress in healthcare workers, and a positive focus for NHS trusts to increase their resources for staff. This is vital when considering current staff retention difficulties and huge numbers of vacancies throughout the NHS. Alternative opportunities for accessing social support in workplace environments should be considered, particularly if lockdown measures are used in the future.
In addition to the key findings, women and younger participants also reported higher distress scores, which is consistent with previous studies (Daniels & Rettie, 2021;Rettie & Daniels, 2020), despite a skewed gender divide. Other research during the pandemic has noted that frequently research samples often consist of greater number of females and younger participants (Conversano et al., 2020). Females reporting higher levels of distress in pandemic research is in line with the existing evidence base indicating females are more vulnerable to developing mental health difficulties (Altemus et al., 2014). While factors such as gender and age cannot be modified, gender may be a risk factor for developing distress in HCWs and should be acknowledged as such (Sirois & Owens, 2021). Research has posited that older individuals may display more resilience towards adverse situations, such as pandemics, and indicate that interventions may need to be focused on younger populations at first (Conversano et al., 2020).
Our findings did not identify ethnicity (BAME or white) as a significant influencing factor on psychological distress despite higher rates of mortality in the BAME group, contradicting recent findings (Moorthy & Sankar, 2020;Roberts et al., 2021), where BAME ethnicities have been associated with worsened mental health due to the pandemic, however our binary categorisation may have oversimplified analysis. These findings, and positively skewed lower rates of psychological distress in this sample in comparison to other studies (Hu et al., 2020;Kumar et al., 2020;Zhang et al., 2020) may be explained by regional variation; almost 75% of our sample were in South West England where rates of COVID-19 were much lower than the national average in the first wave. However, this has dramatically changed through the second wave of COVID-19 and rates of distress may now be much higher.
While our findings provide useful insight into the experience of HCW, it is limited by cross-sectional design and a regional preponderance. Due to the unprecedent and unique nature of this multi-wave pandemic, the most meaningful work will come from longitudinal designs which can examine more closely these and other constructs and potential mediator roles. However, our findings make a cogent contribution to a rapidly developing international evidence base by identifying key potential mechanisms and targets for treatment, in the context of the huge uncertainty surrounding the early stages of the COVID-19 pandemic. Intolerance of uncertainty, fear of contamination and social support are all modifiable constructs that can be targeted in interventions, unlike the majority of demographic variables that other research has investigated. Furthermore, it is vital to understand the need for psychological intervention across healthcare professions and this study is one of the few to provide evidence on this. Our findings provide evidence on how therapies such as CBT can be adapted to provide targeted support for healthcare workers in future pandemics and other adverse circumstances.
Future longitudinal large-scale research should investigate coping strategies used by HCW and assess whether these mediate the relationship between key psychological factors and distress, as found in the general UK population (Rettie & Daniels, 2020). Our findings should be used to understand better the difficulties faced by healthcare workers and help develop and refine interventions better suited to need. With a strong evidence base for Cognitive Behaviour Therapy for anxiety and depression (Kendrick & Pilling, 2012) interventions should incorporate IOU, reducing negative problem orientation and decreasing the use of cognitive avoidance strategies (Robichaud, 2013). Psychological therapies such as CBT do successfully target fear of contamination (Veale, 2007). Indeed, the adaptations required to address IU and fear of contamination are evidence-based and can be drawn upon in a standard yet refined course of CBT. Further, protected opportunities for accessing social support need to be implemented throughout the NHS, however further work is needed to implement this successfully.

Conclusion
This study highlights the important influence of IOU on psychological distress in HCW. Fear of contamination and social support were key factors in understanding psychological distress in our NHS workforce. Evidence-based CBT can be adapted to address these well-understood constructs. It is imperative that future work now focuses on appropriate pathways of care for HCW that are tailored to the unique needs of NHS frontline clinicians Roberts et al., 2021).

Acknowledgments
Thanks are extended to Rupert Beck and the PMGUK COVID-19 UK Doctors Forum for supporting the study through advertising and dissemination of the study participation link.

Disclosure statement
No potential conflict of interest was reported by the author(s).

Funding
The author(s) reported there is no funding associated with the work featured in this article.