A cross-sectional study factors associated with resilience among medical staff in radiology departments during COVID-19, Riyadh, Kingdom of Saudi Arabia

Abstract

Objectives

This study aims to assess the level of resilience of medical workers in radiology departments in Riyadh, Kingdom of Saudi Arabia, during the COVID-19 outbreak and to explore associated factors.

Setting

Medical staff, including nurses, technicians, radiology specialists and physicians, working in radiology departments at government hospitals in Riyadh, Saudi Arabia during the COVID-19 outbreak.

Design

A cross-sectional study.

Participants

The study was conducted among 375 medical workers in radiology departments in Riyadh, Kingdom of Saudi Arabia. The data collection took place from 15 February 2022 to 31 March 2022.

Results

The total resilience score was 29.37±6.760 and the scores of each dimension showed that the higher mean score was observed in the domain of ‘flexibility’, while the lowest was observed in ‘maintaining attention under stress’. Pearson’s correlation analysis showed that there was a significant negative correlation between resilience and perceived stress (r=–0.498, p<0.001). Finally, based on multiple linear regression analysis, factors affecting resilience among participants are the availability of psychological hotline (available, B=2.604, p<0.050), knowledge of COVID-19 protective measures (part of understanding, B=−5.283, p<0.001), availability of adequate protective materials (partial shortage, B=−2.237, p<0.050), stress (B=−0.837, p<0.001) and education (postgraduate, B=−1.812, p<0.050).

Conclusions

This study sheds light on the level of resilience and the factors that contribute to resilience in radiology medical staff. Moderate levels of resilience call for health administrators to focus on developing strategies that can effectively help cope with workplace adversities.

Correspondence to Mochammad Fahlevi; [email protected]

STRENGTHS AND LIMITATIONS OF THIS STUDY

• The study used a robust and well-defined methodology, ensuring the validity and reliability of the results.

• A diverse population of medical workers in radiology departments was included, which improves the generalisability of the findings.

• Data collection took place over a relatively short period, which may limit the applicability of the results to various stages of the pandemic or other timeframes.

• The study focused exclusively on the methods, rather than the results, which helps maintain objectivity and reduces the potential for bias in the analysis.

• The limitation of five bullet points may not encompass all relevant strengths and weaknesses of the study's methods, overlooking some key aspects.

Introduction

At the end of December 2019, an outbreak of an unknown disease called pneumonia of unknown cause occurred in Wuhan, Hubei province, China.¹ Since then, a global outbreak of SARS was confirmed due to infection with a novel coronavirus termed SARS-CoV-2 (COVID-19).² On 11 March 2020, WHO declares it a pandemic due to the rapid increase in cases globally. By then, 114 countries reported confirmed cases,² and the incidence was increasing rapidly worldwide. COVID-19 hit the Middle East in late January 2020, starting with the United Arab Emirates, when a Chinese family arriving for vacation tested positive for the disease, from that day forward, cases started to appear all over the region.³ The Kingdom of Saudi Arabia (KSA) was the last Gulf country to identify cases of COVID-19.^3–5 On 2 March 2020, the Ministry of Health (MOH) confirmed the first case of COVID-19 in Saudi Arabia.^{6 7}

Respiratory infections can be transmitted via droplets of differing sizes: droplet particles >5–10 µm in diameter are referred to as respiratory droplets, while droplet nuclei are <5 μm in diameter.⁸ COVID-19 virus is primarily transmitted between people via respiratory droplets and contact routes.^{9 10} Droplet transmission occurs when a person comes into close contact (within 1 m) with someone who is coughing or sneezing and is thus at risk of having his/her mucosae (mouth and nose) or conjunctiva (eyes) exposed to potentially infective respiratory droplets. Transmission may also occur through fomites in the infected person’s immediate environment.¹¹ As a result, the COVID-19 virus can be transmitted through direct contact with infected people as well as indirect contact with surfaces in the immediate environment or objects used on the infected person (eg, a stethoscope or thermometer). Droplet nuclei are considered to be <5 µm in diameter particles that can float in the air for extended periods and be transmitted to others over distances >1 m. Airborne transmission, on the other hand, refers to the presence of microbes within droplet nuclei.

When it comes to COVID-19, certain situations and settings where procedures or support treatments that produce aerosols are carried out, turning the patient to the prone position, disconnecting the patient from the ventilator and non-invasive positive-pressure ventilation may be potential risk factors for airborne transmission.¹² WHO continues to advise droplets and contact precautions for those caring for patients with COVID-19. In situations and settings where aerosol-generating procedures and support treatment are carried out by risk assessment, WHO continues to advise taking airborne precautions.¹³

In many cases, coronavirus causes pulmonary infection. Early and accurate identification of chest imaging characteristics is contributory to early diagnosis, timely isolation and treatment.¹⁴ Therefore, patients with fever or cough must go through radiological investigations and imaging examinations,¹⁵ such as chest radiography and CT, which play a significant support role in the diagnosis of respiratory manifestations in COVID-19,¹⁶ along with the patient’s clinical history and blood biomarkers.¹⁷ Therefore, one location within the hospital that is of explicit risk for COVID-19 spread to occur is the radiology department,¹⁸ it is also the most likely site for hospital cross-infection.¹⁹ Medical staff in radiology departments are among the frontline healthcare workers who might be exposed to COVID-19, as they come into physical contact with patients while positioning them for radiological examinations.²⁰ Thus, it is crucial to adopt optimal infection control procedures within the radiology department to minimise the further spread of the virus to radiographers and other medical personnel.

COVID-19 is detected and monitored using a variety of diagnostic methods, including chest CT scan, reverse transcription PCR testing, immunological biomarkers, chest radiographs and ultrasound.²¹ Radiographs use electromagnetic radiation to create a two-dimensional image that can show multifocal peripheral lung consolidation and changes.²² In patients with COVID-19, ultrasound scans can identify pulmonary consolidation and a thickened pleural line by generating an image from high-frequency sound waves.²³ By combining a number of radiograph images taken at various angles to create a three-dimensional image, CT scans can create cross-sectional images of various body parts^{24 25} and its use in infectious disease is well established, particularly in the assessment of acute respiratory distress syndrome.²⁶ According to the literature, CT scans can help diagnose COVID-19 by identifying its associated pneumonia.²⁷ While CT scan is the primary imaging technique used to diagnose COVID-19,²⁸ it is not without its drawbacks. Some of them are radiation exposure, the risk of healthcare workers being exposed to COVID-19 and the risk of radiology suite contamination.^{21 29} By applying stringent infection control procedures and regular testing, the risk of infection transmission to patients from CT scans should be diminished.³⁰

Resilience refers to a positive adjustment or the ability to maintain or regain mental health in the face of adversity.^31–33 In response to the pandemic, healthcare professionals have made a commitment to the service of others despite the impact on their emotional and physical well-being due to insecurities, differing work demands and increased work hours.^33–35 Moreover, significant amounts of variance in work may indirectly create a considerable amount of anxiety and stress among medical staff.^{16 36} However, the pandemic has brought a risk of infection and a high mortality rate as well as psychological and mental trauma to the public and medical personnel.³⁷ Healthcare workers with high levels of resilience are significantly less likely to experience anxiety, depression and burnout syndrome than those with low levels of resilience.³⁸ Moreover, with an increase in resilience, the nurses can cope with adverse conditions, better adaptation and achievements are increased and as a result, they experience a better quality of working experience, which minimises the burnout among them.³⁹ Measures taken to increase resilience can reduce the expected stress of an influenza outbreak, such as SARS, on the medical staff as well as benefit the physical and psychological health of the medical staff.⁴⁰ Furthermore, a high-risk appraisal can decrease resilience in hospital workers, whereas strengthening coping ability and relieving the intensity of negative emotions experienced increased resilience during the outbreak of Middle East Respiratory Syndrome.⁴¹

COVID-19 broke out rapidly and fiercely. Because CT diagnostic radiography is a key diagnostic technique for early clinical screening of COVID-19, medical staff in radiology departments are under a lot of pressure and will be stressed out as a high-risk group with a higher likelihood of having close contact with patients with COVID-19, they will experience more mental stress and be more prone to negative emotions. If medical personnel lack resilience, they will be unable to recover from stressful situations, but they will also be more likely to develop emotional distress and acquire psychological issues in severe circumstances.⁴² This study aims to (1) measure and assess the level of resilience of medical staff in radiology departments during the outbreak of COVID-19 as frontline healthcare workers, and to (2) investigate factors connected to it, to provide a foundation for more effective risk assessment and psychological intervention.

In a multicountry study conducted by Nashwan et al,⁴³ researchers investigated the stigma faced by healthcare providers taking care of patients with COVID-19. This study highlights the potential impact of stigma on healthcare professionals’ well-being, including those working in radiology departments. In the context of a cross-sectional study focusing on factors associated with resilience among medical staff in radiology departments during COVID-19 in Riyadh, KSA, it is crucial to consider the role of stigma as a potential stressor that may influence the resilience and coping mechanisms of medical professionals. The findings from the study by Nashwan et al emphasise the importance of addressing and mitigating stigma in healthcare settings to promote the mental health and overall well-being of healthcare providers during challenging times, such as the COVID-19 pandemic.

The Saudi vision 2030 was cascaded into strategic objectives to enable effective implementation through Vision Realisation Programmes, one of these programmes is The Health Sector Transformation Programme, which was newly established to ensure the continued development of healthcare services in the Kingdom and focus efforts on this vital sector. The programme depends on the principle of value-based care, one of its objectives is to improve the quality of health services by implementing and following the best evidence-based international standards.⁴⁴ In light of the literature, supporting the mental well-being and resilience of frontline healthcare workers is imperative to ensure global recovery from the COVID-19 pandemic⁴⁵ as well as to maintain a high quality of patient care.⁴⁶ Resilient health professionals can healthily respond to stress to focus and deal with a problem, then move on, or ‘bounce back’ after challenges. Resilience is a key to enhancing the quality of care, quality of caring and sustainability of the healthcare workforce.⁴⁷ Accordingly, by measuring the level of resilience of medical staff in radiology departments during the outbreak of COVID-19 as frontline healthcare workers and investigating factors connected to it, the findings of this study should make an important contribution to building a foundation for more effective risk assessment and psychological intervention which is crucial to achieving high-quality healthcare.

This study was conducted in Saudi Arabia because the country’s Vision 2030 emphasises the improvement of healthcare services and quality, and supporting the mental well-being and resilience of frontline healthcare workers is vital for patient care and global recovery from the COVID-19 pandemic. This study aims to assess the level of resilience of medical staff (nurses, technicians, radiology specialists and physicians) in radiology departments during the outbreak of COVID-19 in government hospitals in Riyadh, Saudi Arabia. Moreover, the study aims to explore and investigate the factors connected to it, to provide a foundation for more effective risk assessment and psychological intervention.

Methods

Data collection

This study uses a quantitative approach in explaining research analysis.⁴⁸ The study’s timeline was limited, and its purpose was to assess the level of resilience of medical staff in radiology departments during the COVID-19 outbreak, as well as to explore and investigate the factors associated with it, to establish a foundation for more effective risk assessment and psychological intervention. The cross-sectional design is particularly well suited for this goal because it is less time-consuming and allows for the easy collection of data at a single point in time so that the results of it can be used as a foundation for further research.⁴⁹

A cross-sectional study using the convenience sampling method was conducted in Riyadh city between 15 February 2022 and 31 March 2022. An anonymous self-administered online-based questionnaire was distributed to radiology personnel through social media platforms and formally by email in one secondary hospital. To ensure the confidentiality of the study, we took several precautions while using the online survey. Participant responses were collected anonymously, with no personally identifiable information recorded. Furthermore, the survey platform employed secure data encryption to protect the integrity of the responses. Access to the survey data was limited to the research team members, and the findings were reported in aggregate form to maintain participant privacy.

The total received responses number was 410. The study has included both male and female medical staff members, aged 18 years and above, nurses, technicians, radiology specialists and physicians working in the radiology departments of government hospitals who actively work in Riyadh, KSA, and being informed about the study and willing to participate in the survey. Whereas the exclusion criteria were medical staff members working in other departments than radiology as well as working outside the city of Riyadh, working in private hospitals or clinics, undergraduate medical students and submissions that were inconsistent with the actual situation. Finally, 375 radiology medical staff members’ responses were included. An anonymous, self-administered online-based survey was distributed via social media platforms as well as formally by email in one secondary hospital in Riyadh. The included respondents’ questionnaire responses were examined and screened against the rejection criteria. The acquired data were transcribed into the SPSS database after double-checking.

Instruments

In our study, we have received permission from the original authors to use specific assessment tools. This information has been incorporated into the ‘Methods’ section. Here, we provide an overview of the tools used, as well as their significance within our research context.

Demographic characteristics

The first section of our study focuses on respondents’ demographic and personal characteristics. These include gender, age, marital status, current living area, education level, job category, type of hospital, contact with confirmed or suspected COVID-19 cases at work and history of COVID-19 infection. Additionally, the section evaluates participants’ knowledge of COVID-19 protective measures, availability of adequate protective materials at the workplace, access to psychological hotlines and their level of concern about contact with suspected or confirmed cases at work.

Connor-Davidson Resilience Scale

We used the Arabic version of the Connor-Davidson Resilience Scale (CD-RISC) to assess an individual’s ability to adapt and respond to life adversities, traumas, tragedies, threats or other significant life stresses.⁵⁰ The scale consists of 10 statements describing various aspects of resilience, with a focus on flexibility, sense of self-efficacy, emotion regulation, optimism and cognitive maintaining attention under stress. Total scores range from 0 to 40, with higher scores indicating greater resilience and lower scores suggesting less resilience or difficulty bouncing back from adversity. The scale has a Cronbach’s α coefficient of 0.879.

Perceived Stress Scale

The Arabic version of the Perceived Stress Scale (PSS) was used in our study to evaluate participants’ perception of stress.⁵¹ The PSS is a widely used psychological tool that measures the extent to which individuals find certain situations in their lives to be stressful. It encompasses two dimensions: positively stated items reflecting greater control and lower stress levels, and negatively stated items indicating loss of control and high stress levels. PSS scores are calculated by reversing responses to positively stated items and summing the values across all 10 items. Total scores range from 0 to 16, with higher scores signifying increased stress levels. The Cronbach’s α coefficient of the scale in our study was 0.660.

Statistical analysis

The statistical analysis was conducted using IBM SPSS Statistics V.25. Descriptive statistics results were shown as mean and SD to explore and describe the continuous data characteristics, whereas frequencies and percentages for categorical data characteristics. Analysis of variance or independent sample t-test was used for single-factor analysis, Pearson’s correlation analysis was used for correlation analysis and multiple linear regression analysis was used for multivariate analysis. The main reason for choosing this statistical analysis is to get a complete picture in explaining the dependent variable, especially with multivariate regression, which explains the dependent variable of several predictors and show the strength of its influence.

R=a+B1G+B2APH+B3KCPM+B4AAPM+B5S+B6E+B7CACS+e

Where R=resilience; a=intercept; G=gender; APH=availability psychological hotline; KCPM=knowledge of COVID-19 protective measures; AAPM=availability of adequate protective materials; S=stress; E=education; CACS=concern about contact with suspected and e=error.

Patient and public involvement

Patients and/or the public were not involved in the design, conduct, reporting, or dissemination plans of this research.

Results

In this study, an anonymous, self-administered online-based questionnaire was distributed to radiology personnel through social media platforms and formally by email in a secondary hospital. The distribution of the survey among the radiology personnel through social media made it impossible for us to know the exact number of messages sent, we do not have an exact number of people who received this survey containing messages.

Participants’ characteristics

Table 1 shows that more than half (53.6%) of the participants are females, while 46.4% are males. Regarding age groups of participants, those who are 18–30 years constitute 62.9% of the study sample, those who are 31–40 years constitute 28.3% and those who are 41–50 years of age constitute 5.3% of the study sample. In addition, more than half (60.3%) of participants are not married (single, divorced or widowed), while 39.7% are married. Regarding educational level, 67.7% of participants have a bachelor’s degree, 19.5% have a diploma and 12.8% have a postgraduate degree.

Table 1

Sample distribution according to the participants’ demographic factors (n=375)

Variables	Number	Percentage (%)
Gender
Male	174	46.4
Female	201	53.6
Age group (years)
18–30	236	62.9
31–40	106	28.3
41–50	20	5.3
>50	13	3.5
Marital status
Married	149	39.7
Not married	226	60.3
Educational level
Diploma	73	19.5
Bachelor	254	67.7
Postgraduate education	48	12.8

Online supplemental table 1 shows that 19.5% of the participants were technicians, 71.2% were specialists and 6.7% were physicians. In terms of work locations, 45.3% of participants worked in MOH hospitals, 32.3% worked in military hospitals and 22.4% worked in university hospitals. Online supplemental table 2 shows that 83.2% of participants had contact with confirmed/suspected cases at work, while 16.8% of them did not. In addition, more than half (50.9%) of participants had COVID-19 before, while 49.1% of them did not. Moreover, 90.4% of participants had a very understanding of COVID-19 protective measures and 8.3% of them had partial understanding. Furthermore, 49.9% of participants had very abundance, 31.7% had partial abundance and 14.9% of them had partial shortage of adequate protective materials.

Online supplemental figure 1 shows that only 17.3% of participants had psychological hotline available at the workplace, while 31.5% of them did not, and the majority did not know whether it was available or not. Online supplemental figure 2 shows that 51.5% of participants had concerns about contact with suspected/confirmed COVID-19 cases at work, while 48.5% of them did not.

Participants’ resilience and perceived stress

Online supplemental table 3 shows the mean and SD of each item in the resilience domain. The total mean score of resilience among the study participants was 29.36 out of 40. Item number 6 “I believe that I can achieve my goals even with obstacles” got the highest score, followed by the item number 9 “I consider myself a strong person when dealing with life’s challenges and difficulties”. The lowest mean score was item number 8 “Failure doesn’t get me frustrated easily”. The scores for each dimension are shown in online supplemental table 4.

Online supplemental table 4 shows subdomains of resilience among nurses. The range for each subdomain is illustrated in the table. The mean score for flexibility was 6.32 out of 8, and the mean score of self-efficacy was 9.13 out of 12. The mean score of regulate emotion was 2.72 out of, and the mean score of optimism was 8.73 out of 12, while the mean score of attention under stress was 2.47 out of 4. The higher man score was observed in the domain of ‘flexibility’, followed by ‘self-efficacy’, while the lowest mean score was observed in the domain of ‘maintaining attention under stress’.

Online supplemental table 5 shows the mean and SD of each item in the stress domain. The total mean score of the stress of study participants was 6.73 out of 16. The item number 4 “In the last month, how often have you felt difficulties were piling up so high that you could not overcome them” got the highest score, while the lowest mean score was noted in the item number 2 “In the last month, how often have you felt confident about your ability to handle your personal problems”.

Pearson’s correlation shows that there is a significant inverse correlation between stress and resilience (r=–0.498, p<0.001) as illustrated in online supplemental table 6. High stress led to significantly lower resilience (p<0.05).

Related factors for resilience

Table 2 shows that there is a significant difference in the mean score of resilience regarding participants’ gender (p<0.05). Male participants have a significantly higher mean score of resilience than female participants. Furthermore, there is a significant difference in the mean score of resilience regarding participants’ concern about contact with suspected or confirmed COVID-19 cases (p<0.05). Participants who are not concerned about contact with suspected or confirmed COVID-19 cases have a significantly higher mean score of resilience than participants who do. On the other hand, there is no significant difference in the mean score of resilience regarding participants’ marital status, contact with confirmed or suspected cases at work or infection with COVID-19 before (p>0.05).

Table 2

Factors affecting resilience among study participants

	N	Mean	SD	t statistics	P value*
Gender
Male	174	30.18	6.74	2.186 (373)	0.029
Female	201	28.66	6.71
Marital status
Married	149	29.73	6.56	0.845 (373)	0.399
Not married	226	29.12	6.88
Contact with confirmed/suspected cases at work
Yes	312	29.59	6.66	1.477 (373)	0.140
No	63	28.22	7.15
Had COVID-19 before
Yes	184	29.02	6.75	−0.973 (373)	0.331
No	191	29.70	6.76
Participants concerned about contact with suspected/confirmed COVID-19 cases
Yes	193	27.55	7.39	−5.543 (373)	0.000
No	182	31.28	5.40

*Independent sample t-test.

Table 3 shows that there is a significant difference in the mean score of resilience regarding participants’ education (p<0.05). Post hoc test showed that the difference has been noted between the two groups ‘diploma’ and ‘postgraduate education’ in favour of those who have a diploma. The difference has been noted also between bachelor and postgraduate education in favour of those who have bachelor’s degrees (p<0.05).

Table 3

Factors affecting resilience among study participants

Participants	N	Mean	SD	F/t statistics	P value*
Age group (years)
18–30	236	29.11	6.92	0.407 (3, 371)	0.748
31–40	106	29.98	6.76
41–50	20	29.10	5.83
>50	13	29.30	5.15
Education
Diploma	73	30.78	5.89	7.488 (2, 372)	0.001
Bachelor	254	29.57	6.39
Postgraduate education	48	26.12	8.71
Job title
Technician	73	30.56	6.03	1.469 (3, 371)	0.223
Specialist	267	28.92	6.95
Physician	25	29.76	7.00
Nurse	10	31.40	4.81
Workplace
MOH hospital	170	28.61	6.81	3.245 (2, 372)	0.040
University hospital	84	29.09	7.56
Military hospital	121	30.61	5.90
Availability of psychological hotline
Yes	65	31.95	6.58	8.725 (2, 372)	0.000
No	118	27.70	7.14
Do not know	192	29.51	6.30

*One-way analysis of variance.

MOH, Ministry of Health.

The table also shows that there is a significant difference in the mean score of resilience regarding participants’ workplace (p<0.05). Post hoc test showed that the difference has been noted between the two groups ‘MOH hospital’ and ‘Military hospital’ in favour of those who are working in Military hospitals (p<0.05).

Moreover, there is a significant difference in the mean score of resilience regarding the availability of psychological hotline (p<0.05). Post hoc test showed that the difference has been noted between the two groups ‘yes’ and ‘no’ in favour of those who have availability of psychological hotline. Those who have the availability of psychological hotline have higher mean score of resilience than those who do not. On the other hand, there is no significant difference in the mean score of resilience regarding participants’ age and job category (p>0.05).

Table 4 shows that there is a significant difference in the mean score of resilience regarding participants’ knowledge of COVID-19 protective measures (p<0.05). A post hoc test showed that a difference has been noted between the two groups ‘part of understanding’ and ‘very understanding’ in favour of those who are very understanding (p<0.05). Moreover, there is a significant difference in the mean score of resilience regarding the availability of adequate protective materials (p<0.05). A post hoc test showed that the difference has been noted between the two groups ‘partial shortage’ and ‘very abundance’ in favour of those who have ‘very abundance’ of adequate protective materials (p<0.05).

Table 4

Factors affecting resilience among study participants

Participants	N	Mean	SD	F/t statistics	P value*
Knowledge of COVID-19 protective measures
Lack of understanding	5	25.00	10.14	33.256 (2, 372)	0.000
Part of understanding	31	20.83	7.97
Very understanding	339	30.21	6.00
Availability of adequate protective materials
Very shortage	13	29.53	7.53	15.758 (3, 371)	0.000
Partial shortage	56	24.17	9.08
Partial abundance	119	29.42	5.68
Very abundance	187	30.87	5.73

*One-way analysis of variance.

Multiple linear regression analysis

In this section, we use dummy and ordinal variables, coefficients and SEs under the standardised coefficient.

Based on the model which has been produced from multiple linear regression in table 5, factors affecting resilience among participants are: (1) availability of psychological hotline; (2) knowledge of COVID-19 protective measures; (3) availability of adequate protective materials; (4) stress and (5) education. Resilience=35.661+2.604 (A)−5.823 (PU)−2.237 (PS)−0.837 (S)−1.812 (PG), meaning that participants who have (A) availability of psychological hotline have a resilience score that is 2.604 points higher than participants with those who do not have availability of psychological hotline, participants who have (PU) part of understanding have a resilience score that is −5.283 points lower than participants with those who have very understanding, participants (PS) with a partial shortage of protective materials have a resilience score that is −2.237 points lower than participants partial abundance, participants with (S) high stress level have a resilience score that is −0.837 points lower than participants with a low stress level and participants with (PG) a postgraduate degree have a resilience score that is −1.812 points lower than participants with a bachelor degree.

Table 5

Factors affecting resilience from multiple linear regression

Variable	B	SE	t statistics	P value	95% CI
Constant	35.661	1.044	34.159	0.000	33.608	37.714
Gender
Female
Male	0.109	0.579	0.189	0.850	−1.029	1.247
Availability of psychological hotline
Not available
Available	2.604	0.859	3.031	0.003	0.914	4.293
Do not know	0.302	0.645	0.469	0.640	−0.966	1.571
Knowledge of COVID-19 protective measures
Very understanding
Lack of understanding	−3.664	2.520	−1.454	0.147	−8.619	1.291
Part of understanding	−5.283	1.126	−4.690	0.000	−7.498	−3.068
Availability of adequate protective materials
Partial abundance
Very shortage	−1.174	1.637	−0.717	0.474	−4.394	2.046
Partial shortage	−2.237	0.937	−2.387	0.017	−4.080	−0.394
Very abundance	0.187	0.660	0.283	0.777	−1.112	1.486
Stress	−0.837	0.098	−8.579	0.000	−1.029	−0.645
Education
Bachelor
Diploma	1.057	0.737	1.435	0.152	−0.392	2.506
Postgraduate	−1.812	0.879	−2.061	0.040	−3.542	−0.083
Concern about contact with suspected/conformed case of COVID-19
Not concerned	−1.015	0.605	−1.678	0.094	−2.204	0.175

Discussion

Resilience score

In the present study, the total resilience score of the medical staff in the radiology departments was 29.37, which was lower than the 32.26 score of 439 Saudi nursing students during the COVID-19 pandemic,⁵² also lower than the scores of resilience that ranges between 31.3 and 32.6 for first responders in the USA from four emergency response professions during COVID-19.⁵³ In contrast, it was higher than the scores of frontline medical workers during the COVID-19 in Hubei Province, China (26.36) and frontline medical workers in other regions in China (27.47).⁵⁴ According to Connor,⁵⁵ CD-RISC scores appear to be influenced by the region where data were obtained and the nature of the sample. Thus, scores may vary according to country, and differences in cultures and healthcare systems do not make the findings generalisable. As a result, analysing data from around the world can help researchers better understand this phenomenon during the pandemic.⁵⁶ An international study⁵⁷ was conducted among 904 nurses across Japan, the Republic of Korea, the Republic of Turkey and the USA. It stated that CD-RISC-10 scores can be categorised as low (0–10), intermediate (11–30) and high (31–40). Similarly, it was reported that an overall CD-RISC range=35.5–92.8 was considered ‘moderate’ in a recent systematic review by Baskin and Bartlett⁵⁶ that aimed to examine resilience among healthcare workers during the COVID-19 pandemic across different countries. The findings of this study indicated that the resilience level of medical staff in radiology departments during the COVID-19 outbreak was moderate or intermediate, given the fact that it has been 2 years since the Saudi MOH confirmed the first case of COVID-19 in Saudi Arabia, and it is expected that healthcare workers have gained better resilience. The reason could be that the study was conducted when the emergence of the Omicron variant was relatively new. The Saudi MOH announced the first case of the Omicron variant in the country on 1 December 2021. The Omicron variant is thought to be at least three times more infectious than the original SARS‐CoV‐2.⁵⁸ The appearance of a new infectious threat presented healthcare workers with a new source of stress and worry, as they have been already dealing with uncertainty since the outbreak of COVID-19.⁵⁹ This uncertainty extended beyond the possibility of infection to the pandemic’s potential socioeconomic impact.⁶⁰ Notably, their inability to tolerate uncertainty may underpin that their resilience level is not high.

Gender on resilience

Based on multiple linear regression analysis of related factors for resilience, the results showed that the availability of the psychological hotline, knowledge of COVID-19 protective measures, availability of adequate protective materials, perceived stress and education were all statistically significant factors related to the radiology departments’ medical staff’s resilience. The study findings revealed that there is a significant difference in the mean score of resilience regarding participants’ gender (p 0.05). Male participants have a significantly higher mean score of resilience than female participants. According to the study by Nicholls et al, women’s resilience was significantly lower than men’s resilience.⁶¹ Another study indicated that women had higher levels of psychological distress than men and that women’s resilience had less of an influence on their psychological distress than men’s resilience.⁶² The explanation for that would be attributable to differences in perspectives and responses to difficulties between men and women. Women are more vulnerable and sensitive, and their antistress ability is also limited, making them potentially incapable of psychological adaptation. As a result, they should receive additional attention and emotional assistance.⁶³

Knowledge of COVID-19 protective measures on resilience

This study also found that there is a significant difference in the mean score of resilience regarding participants’ knowledge and understanding of COVID-19 protective measures (p<0.05). Participants with a better understanding of COVID-19 protective measures reported higher resilience, suggesting that a complete understanding of those measures is required to improve resilience of medical staff. Furthermore, healthcare workers who recently received training on how to wear personal protective equipment were less likely to contract COVID-19.⁶⁴ According to Khalid et al,⁶⁵ by mastering effective protective measures the risk of infection can be significantly minimised, and the psychological security of medical personnel improved; with psychological security, medical workers can swiftly get rid of fear, terror and other unpleasant feelings and persevere through the epidemic. Therefore, training medical professionals in radiology departments on how to defend themselves from COVID-19 is necessary, rather than relying solely on the team’s knowledge and self-learning. Instead, instructions should be designed to promote clear and consistent behavioural norms on unified, professional and scientific preventative actions that are appropriate for the outbreak. As a result, the adverse effects of difficulty on individuals can be reduced while adaptation and growth are enhanced.⁶³ Regarding the availability of adequate protective materials, in this study, there is a significant difference in the mean score of resilience among participants where the high resilience was reported by the group with a ‘very abundance’ of adequate protective materials. In times of pandemics, the most basic requirement for medical personnel’s safety is adequate protective equipment. The findings also revealed that when medical personnel faced a shortage of protective equipment, their resistance suffered. Fang et al have highlighted the necessity of having adequate medical supplies during the COVID-19 pandemic.⁶⁶In addition to a lack of protective materials, there will be a loss of psychological security, and pessimism and helplessness will impair psychological ‘healing’ by reducing the ability to mobilise protective factors, causing risk factors to become stronger over time. As a result, efforts by hospitals to assure a supply of protective materials are critical if medical workers in radiology departments are to preserve a higher level of resilience.⁶³

Availability of adequate protective materials on resilience

In a study conducted by Firew et al,⁶⁷ almost half of the sample (healthcare workers) reported that protective materials were available all the time (47.60%). Those reporting protective materials were available all the time displayed a 45% reduction in the probability of infection, those reporting that protective materials were available most of the time displayed a 33% reduction in the probability of infection and one of the factors that contributed to infection in healthcare workers was the unavailability of protective materials and training. Those who had inadequate access to protective materials or inadequate protective materials training were at higher risk of developing COVID-19 symptoms. Similarly,⁶⁸ Cai et al found that protective materials were reported being effective when available in sufficient amounts, but a risk factor for stress when insufficient. A qualitative study of frontline nurses in Wuhan indicated that physical health and safety were one of their top priorities. Protective materials were also mentioned as a protective factor in this study.⁶⁹ The results also showed that regarding the availability of a psychological hotline, there is a significant difference in the mean score of resilience (p<0.05), whereas those who have availability of a psychological hotline have a higher mean score of resilience than those who do not. According to Duan et al,⁷⁰ individuals with high resilience are better able to maximise both internal resources (eg, perseverance and self-efficacy) and external resources (eg, social support) to minimise the negative effects of adversity. Lack of psychological support was found to have an important role in reducing nurses’ resilience during the COVID-19 pandemic.⁷¹ On the other hand, the majority of participants (51.2%) do not know whether it is available or not, this could be attributed to what has been noticed by Gilleen et al⁷² that healthcare workers may not appropriately prioritise their mental health, and existing formal support mechanisms require healthcare workers to initiate contact with the resource. This requires an individual to recognise and act on their potential need.⁷³ Similarly, Xiang et al⁷⁴ reported that although some healthcare workers might need psychosocial support, they rarely seek help. Healthcare workers involved in the care of patients with COVID-19 should undergo regular evaluations of stress, depression and anxiety levels to support their well-being.⁷⁴ The requirement of creating awareness of the need for professional support among the radiology workforce in dealing with stress and other psychological disorders that might arise during the COVID-19 pandemic and similar crisis has also been acknowledged by Elshami et al.⁷⁵

Concern about resilience on contact with suspected COVID-19 cases

The present study found that there is a significant difference in the mean score of resilience regarding participants’ concern about contact with suspected or confirmed COVID-19 cases (p 0.05). Participants who are not concerned about contact with suspected or confirmed COVID-19 cases have a significantly higher mean score of resilience than participants who are concerned. Similarly, it was reported by Jo et al⁵⁷ that lower resilience was reported by nurses who expressed greater fear and concerns of contracting COVID‐19 (B=−0.5, p<0.001). Moreover, in a study conducted among healthcare workers by Zhang et al,⁷⁶ more than half of the participants (56.9%) were afraid that they would be infected with COVID-19. The occupational risk of working in high-risk professions like healthcare was found to be a noteworthy predictor of COVID-19 concern.⁷⁷ It was linked to higher levels of COVID-19 concern. According to the study by Quadros et al,⁷⁸ various domains of COVID-19 infection concerns and fear have been identified: people are fearful of being infected, either for themselves or for their loved ones; fear of suffering economic losses, and being unemployed; fear of engaging in social withdrawal to learn more about the pandemic; fear of making decisions on whether or not to visit parents or look for information on death rates.^{79 80} Higher threat perception of the outbreak affects resilience and mental well-being.

Education on resilience

Regarding participants’ education, in the present study, there is a significant difference in the mean score of resilience (p<0.05), the highest resilience was reported by those who have a diploma, the difference has also been noted between the two groups having bachelor’s degree and postgraduate education in favour of those who have bachelor’s degrees (p<0.05). These findings are in contrast with what has been reported by Yin and Zeng⁶⁹ that higher education increased resilience, and by Afshari et al⁷¹ that an increase in education would lead to an increased level of resilience. But in line with the findings of Zhang et al⁸¹ where master’s (35.19±9.10) and doctoral students (31.00±11.29) had lower CD-RISC-10 scores compared with undergraduates. This might be attributed to less experience in those with higher levels of academic education compared with health practitioners who have lower levels of education and are more proficient at analysing issues and somehow dealing with problems,⁸² which is also consistent with the findings of Sun et al⁸³ who gave another possible explanation that clinicians with advanced degrees mostly work on the front lines, where they face challenging jobs and heavy pressure and even though their education levels have typically improved, competition for title promotion is intense, with frequent incidents of uncivilised behaviour such as medical disputes, insults, physical harm and so on adding to the mental strain.

Stress on resilience

The results showed that there is a significant inverse correlation between stress and resilience (r=–0.498, p<0.001), where high stress leads to significantly lower resilience (p<0.05). These results are in line with a previous study that showed higher levels of resilience were associated with hope and reduced stress.⁸⁴ A recent study documented that the safety of medical staff during the pandemic and lack of treatment for COVID-19 were the main factors that induced stress in all medical staff. After self-interpretation of stressful circumstances, perceived stress reflects an individual’s psychological experience.⁸⁵ The findings revealed that higher perceived stress was associated with lower medical staff resilience. Another study discovered that having high resilience helps people better manage their life’s stressors and responsibilities.⁸⁶ It is easy to predict that as self-perceived stress rises, an individual’s adaptability to stress would drop, as will their capacity to self-recover following psychological adjustment, indicating a lack of resilience. As a result, hospital administrators should take whatever steps are necessary to reduce the stress levels of their radiology departments’ medical staff.⁶³

Limitation

The study has the following limitations. First, only medical staff in the radiology departments in Riyadh were included, and further study is needed in other regions in Saudi Arabia to improve the generalisation of the findings. Second, the related factors included in this study only accounted for 41.5% of the total variation in the equation, and more relevant factors that are clinically valuable need to be included in future studies to provide a more comprehensive basis for the implementation of scientific and effective interventions in the future. Finally, only medical staff in radiology departments have been studied, and it was impossible to determine whether their resilience differed from that of staff in other departments.

Conclusion

This study sheds light on the level of resilience and the factors that contribute to resilience in radiology medical staff. Because of the positive effect of resilience on the mental health of medical staff, moderate levels of resilience calls for health administrators to focus on developing strategies that can effectively help cope with workplace adversities, and targeted interventions can be performed to increase resilience. It is also possible to improve their mental health and resilience in the epidemic of infectious diseases by increasing social and organisational support, which will increase the quality-of-care services. The findings can be used to implement worksite interventions aimed at improving the resilience of radiology personnel.

When the outbreak of COVID-19 suddenly appeared, it was difficult for medical staff in radiology departments to make full preparations and establish enough confidence to cope with and maintain good resilience to adapt psychologically. As a result, we must make some preparations during normal times. It is critical to ensure that radiology departments at all hospital levels are well prepared for public health emergencies, rather than just large-scale hospitals. In terms of hospital administration, it is necessary to improve daily study and practice of scientific and systematic response measures for all types of public health emergencies, which can raise awareness of self-protection among medical staff in radiology departments, allowing them to respond calmly to an outbreak. Furthermore, regular training for medical professionals in radiology departments, especially women, should be actively conducted to develop their psychological antistress ability and enable them to change negative emotions into good emotions quickly and efficiently under stress. All the above-mentioned factors contribute to medical staff in radiology departments remaining resilient during an emergency.

Data availability statement

Data are available on reasonable request.

Ethics statements

Patient consent for publication

Not applicable.

Ethics approval

This study was approved by King Saud University (KSU), Riyadh, Kingdom of Saudi Arabia (reference no: KSU-HE22-086). All the participants were asked to voluntarily take part in the study, clarifying that their identity will remain anonymous and assured confidentiality of their responses.

Footnote

Twitter @mr_leviosa

Contributors Conceptualisation: FKA and NSAH; methodology: MF; software: MAA and MF; validation: MMA and PH; formal analysis: MF and MMA; investigation: NSAH; resources: MF; data curation: PH; writing—original draft preparation: FKA and NSAH; writing—review and editing: MF and MMA; visualisation: PH; supervision: MF and MAA; project administration: MF and NSAH; funding acquisition: MMA. All authors listed have made a substantial, direct and intellectual contribution to the work and approved it for publication.

Funding This study was funded by King Saud University through the Researcher Supporting Project (RSP2023R481), King Saud University, Riyadh, Saudi Arabia.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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