Investigating Factors Influencing Fatigue and Medical Imaging Technologist Performance on Night Shift: An Initiative to Improve Healthcare Delivery
Funding: The authors received no specific funding for this work.
ABSTRACT
Introduction
It is widely recognised that night shifts can cause fatigue, negatively impact cognitive performance and increase the risk of accidents. This quality improvement project aimed to better understand factors impacting on fatigue levels of medical imaging technologists who perform night shifts at metropolitan hospitals in Australia.
Methods
All medical imaging technologists (i.e., radiographers and sonographers) employed at two Australian metropolitan hospitals who had performed night shifts within the last year were invited to complete a custom-made electronic survey. Quantitative survey responses were examined using a combination of descriptive and comparative statistics. An applied thematic analysis was used to examine qualitative findings from open-ended questions.
Results
Medical imaging technologists perceive roster patterns with more consecutive night shifts and more rostered days off following night shifts to be less fatiguing and more sustainable. Fatiguing factors, including being awake at night and longer shift lengths, were perceived as significantly more fatiguing during the first 3 days of night shifts. The self-reported time taken to return to a normal sleep routine following night shifts was a mean of 3.2 days. Workload was rated as the factor that caused the highest levels of fatigue throughout a night shift roster. The majority of participants expressed that organisation-level changes are needed to reduce fatigue levels.
Conclusion
Organisation level strategies to: (1) reduce workloads, and (2) enable rosters with more consecutive night shifts are needed to help medical imaging technologists effectively manage fatigue levels. The small sample size may limit the generalisability of findings.
1 Introduction
Performing night shifts is an essential part of many work rosters with as much as 20% of the global workforce performing either shift work or night duties as part of their roster [1]. Due to the nature of health care, an even higher percentage of health care workers are required to do night duties. Factors that influence fatigue experienced during night shifts, such as circadian and sleep homeostatic brain processes [2], are often different from the reasons a worker may experience fatigue during day and afternoon shifts [3]. Therefore, fighting fatigue during night shifts may require a different approach to that during the day.
A common organisational level strategy for combating fatigue related to night shifts involves rostering. Conflicting results into the effects of night shift on sleep patterns [4, 5] pose a challenge for managers when creating suitable work rosters to manage night shift fatigue. There is some evidence that night duty staff sleep worse during night shift rotations [4, 6]. Safe Work Australia guidelines [7] recommend keeping consecutive night shifts to a minimum based on the notion that more consecutive night shifts may be more fatiguing and therefore lead to decreased performance. However, some research contradicts this recommendation. For example, a field study examining cognitive performance demonstrated that night duty staff perform better after 7 consecutive nights at work [8]. A study by Lancman [5] also showed that sleep duration increased progressively before shifts from 1 to 5 nights in anaesthetist trainees performing 5 consecutive night shifts.
While it could be argued that lack of sleep is the cause of fatigue during night shift rotations, experts in the field have cautioned that this is an oversimplification [9]. There is limited published research examining night duty staff perceptions of the cause of their fatigue when undertaking night duties, which could lead to valuable insights into the lived experience of workers. The strategies used by staff to manage their fatigue on night shift rosters, based on their personal lived experiences, may also be invaluable to developing more effective workplace modifications and interventions. Developing a greater understanding of effective management strategies will enable increased performance of staff doing night duties, in addition to increased sustainability of night duty staff, which many worksites find difficult to retain.
Recent systematic reviews have found no research that directly investigated the effect of shift work on performance, fatigue, burnout, wellbeing and safety in research samples comprising of medical imaging technologists [10, 11]. While some research has focused on the lived experience of night shift fatigue of doctors and nurses [1, 5, 10, 12, 13], these health care professionals perform vastly different duties to medical imaging technologists. The aim of this study is to increase the knowledge base available for management of fatigue for medical imaging technologists required to perform night shift duties. For the purpose of this paper, the term medical imaging technologist is inclusive of radiographers and sonographers registered as medical radiation practitioners with the Australian Health Profession Regulation Agency (APHRA).
Due to staffing pressures brought about by the introduction of the COVID-19 virus into Australia, changes to night shift roster patterns were required at metropolitan hospitals, which enabled the direct comparison of fatigue brought about by changing roster patterns in the staff performing night duties. This enabled a rare opportunity to explore the lived experience of fatigue brought about by roster patterns, as well as other major causes of fatigue for medical imaging technologists performing night duties.
2 Methods
2.1 Participants and Procedure
An ethics waiver was obtained in order to perform a staff survey to inform quality improvement initiatives. The survey was conducted at two separate hospitals within the Metro North Hospital and Health Service in Brisbane [ethics exemption reference number LNR/2020/QRBWH/68919]. A profile of the Medical Imaging Department at each of these hospitals is displayed in Table 1. Due to changes to rostering associated with the changing health care needs attributable to COVID-19, some of the staff had recent experience with two different night duty rosters: (1) a seven-day on/seven-day off roster with 10-hour night shifts and (2) a roster with a smaller number of consecutive night shifts and a shorter eight-hour shift.
| Profile characteristics | Redcliffe Hospital | The Prince Charles Hospital |
|---|---|---|
| Number of hospital beds | 250 | 690 |
| Hospital medical imaging services |
MRI CT Interventional radiology Theatre radiology General and emergency radiography Ultrasound |
MRI CT Interventional radiology Theatre radiology General and emergency radiography Ultrasound Cath lab Electrophysiology Nuclear medicine |
| Medical imaging overnight services |
CT Theatre radiology General and emergency radiography Ultrasound |
CT General and emergency radiography |
| Size of medical imaging departmenta | 39.3 FTE | 71 FTE |
| Number of medical imaging technologists overnight | 1 | 1 |
| Number of support staff overnight | 0 | 0 |
- a Estimated number of medical imaging technologists based on rosters from the time of the study.
All staff still currently employed at both hospitals who had performed the seven consecutive night roster pattern within the last year were invited to participate in the study via email. Participants completed an electronic questionnaire comprised of two parts: (1) a demographic form and (2) a custom-made survey.
The custom-made survey contained a total of 13 questions in two sections. This survey was developed by the research team. Due to the lack of research in this area, we did not draw extensively from previous literature or any established theoretical frameworks when developing the survey. The survey was also not piloted with anyone outside of the research team. Section one of the survey explored the participants' perceptions of the seven consecutive night roster pattern, including: (1) when the staff member felt most fatigued during the week, (2) whether the staff member takes regular breaks, (3) when the staff member felt they performed the best during the week, (4) whether the roster pattern was sustainable and (5) how long it took for the staff member to return to a normal sleep routine post night shifts. An additional two questions asked participants to compare a shorter number of consecutive night shifts to the seven consecutive night roster in terms of fatigue and sustainability/burnout. A five-point Likert scale was utilised to identify how fatiguing the staff member's perceptions of the first 3 days versus the last 3 days of the night shift week were in terms of: (1) being awake at night/tiredness, (2) workload, (3) length/duration of shift and (4) number of successive shifts. The final question was an open response question asking for any recommendations for reducing fatigue or increasing sleep quality in night shift staff. A copy of the questionnaire can be viewed in Supporting Information.
3 Data Analysis
Demographic information and survey results were first examined using descriptive statistics. A within-subjects t-test was used to compare the perceptions of the impact of fatiguing factors on the first 3 days versus the last 3 days of night shifts. SPSS for Windows (version 30.0.0.0; IBM Corp) was used for this analysis.
Responses to the final open-ended question were analysed using Applied Thematic Analysis (ATA) [14] with an exploratory approach. ATA is a rigorous, yet inductive, set of analytic procedures for applied research contexts that draws from several theoretical and methodological perspectives including grounded theory, positivism, interpretivism and phenomenology [14]. The qualitative data analytic approach is primarily concerned with presenting the stories and experiences of study participants in an accurate and comprehensive way [14]. Unlike traditional thematic analyses [15, 16], ATA allows for various forms of quantification to facilitate the examination of trends or patterns derived from qualitative data [14].
The qualitative text was first analysed by a researcher with experience in ATA (author N.E.A.) [17] to develop codes and overarching themes. Both codes and themes were reviewed by a second researcher with experience performing night shifts as a medical imaging technologist (author T.G.). The number of participants whose comments were coded with a particular code (i.e., frequency count) was then generated to examine data trends.
4 Results
4.1 Participant Demographics
Seventeen staff completed the survey out of 22 potential participants. This was a response rate of 77%. Of the 17 respondents, 13 (76%) had done shorter than seven consecutive night shifts, in addition to the seven consecutive night roster pattern. However, one of these 13 participants had only performed one period of shorter than seven consecutive night shifts and hence was unwilling to contribute to the second part of the survey comparing the different rostering patterns, citing insufficient experience as the reason.
The demographics of the sample can be viewed in Table 2. 52% of the sample were in their twenties. More females than males participated (65%).
| Demographic variable | n | % |
|---|---|---|
| Hospital | ||
| The Prince Charles | 5 | 29 |
| Redcliffe | 12 | 70 |
| Gender | ||
| Male | 6 | 33 |
| Female | 11 | 65 |
| Age (years) | ||
| 20–29 | 9 | 53 |
| 30–39 | 5 | 29 |
| 40–49 | 1 | 6 |
| 50+ | 2 | 12 |
The survey responses pertaining to the perceptions of the seven day on/seven day off night shift roster are presented in Table 3. The majority of respondents (88%) indicated that they perceived the first 3 days of night shifts to be when they feel the most fatigued and only one participant felt that their peak performance occurred during these first 3 days. While most participants indicated that they only took their mandatory breaks when workload permitted (77%), they felt that the seven day on/seven day off night shift roster pattern was sustainable long-term (94%). Most participants (70%) indicated it took either 2 or 3 days to return to a normal sleep routine following night shifts. However, for two participants, a timeframe of over 5 days was needed to return to a normal sleep routine.
| Construct | Response | n | % |
|---|---|---|---|
| Perceptions on when most fatigued | During the first 3 nights | 15 | 88 |
| During the last 3 nights | 0 | 0 | |
| Consistent throughout week | 0 | 0 | |
| Other: Dependent on sleep quality | 1 | 6 | |
| Other: Dependent on workload | 1 | 6 | |
| Perceptions on when peak performance occurs | During the first 3 nights | 1 | 6 |
| During the last 3 nights | 8 | 47 | |
| Consistent throughout the week | 8 | 47 | |
| Perceptions on mandatory breaks | Takes mandatory breaks regularly | 4 | 24 |
| Takes breaks only if workload permits | 13 | 77 | |
| Perceptions of sustainability of work roster | Sustainable work roster | 16 | 94 |
| Unsure | 1 | 6 | |
| Perceptions of time taken to return to normal sleep routine following night shifts | 1 day | 0 | 0 |
| 2 days | 6 | 35 | |
| 3 days | 6 | 35 | |
| 4 days | 3 | 18 | |
| 5 days | 0 | 0 | |
| More than 5 days | 2 | 12 |
Participants' perceptions of a decreased number of consecutive night shifts, compared to a seven consecutive night roster, are displayed in Table 4. The majority of participants indicated that a roster pattern consisting of less consecutive night shifts was both more fatiguing (83%) and less sustainable in the long term (75%).
| Construct | Response | n | % |
|---|---|---|---|
| Perceptions of fatigue | Decreased number of consecutive nights were more fatiguing | 10 | 83 |
| Decreased number of consecutive nights were less fatiguing | 1 | 8 | |
| Other: Dependent on workload and staffing | 1 | 8 | |
| Perceptions of sustainability | Working decreased number of consecutive nights is not sustainable long-term | 9 | 75 |
| Working decreased number of consecutive nights is sustainable long-term | 1 | 8 | |
| Other: Sustainability dependent on staffing and turn around | 2 | 17 |
Participants' perceptions of the impact of common fatiguing factors on the first 3 days versus the last 3 days of night rosters are displayed in Table 5. There was a statistically significant difference in fatigue score ratings for the following fatigue factors: being awake at night (M = 1.82, t(16) = 4.85, p < 0.001, 95% CI: 1.03, 2.62) and the length of the night shift (M = 0.47, t(16) = 2.22, p = 0.04, 95% CI: 0.02, 0.92). The difference in fatigue scores was not statistically significant for the remaining fatigue factors including workload (M = 0.59, t(16) = 1.98, p = 0.07, 95% CI: −0.04, 1.23) and number of shifts (M = 0.35, t(16) = 1.85, p = 0.04, 95% CI: −0.05, 0.76). Participants indicated that being awake at night had a bigger impact on fatigue during the first 3 days of night rosters (M = 3.88, SD = 1.27) compared to the last 3 days (M = 2.06, SD = 1.03). Similarly, participants felt that the length of the shift on the first 3 days contributed to fatigue levels more compared to the length of shifts on the last 3 days of night rosters (M = 2.35, SD = 1.37 vs. M = 1.88, SD = 0.93). Workload was rated as the factor that caused the highest levels of fatigue. The impact of workload on fatigue levels was rated similarly for the first 3 days (M = 4.47, SD = 0.72) and the last 3 days (M = 3.88, SD = 1.32) of night rosters.
| Factor that can impact on fatigue | Time point | Perceived impacta | p |
|---|---|---|---|
| Being awake at night/tiredness | First 3 nights | 3.88 (1.27) | < 0.001 |
| Last 3 nights | 2.06 (1.03) | ||
| Workload | First 3 nights | 4.47 (0.72) | 0.07 |
| Last 3 nights | 3.88 (1.32) | ||
| Length/duration of shift | First 3 nights | 2.35 (1.37) | 0.04 |
| Last 3 nights | 1.88 (0.93) | ||
| Number of successive shifts | First 3 nights | 2.47 (1.37) | 0.08 |
| Last 3 nights | 2.12 (0.99) |
- a Values = Mean (standard deviation). Perceived impact measured on a 5-point Likert Scale 1 = Not at all fatiguing, 5 = Very fatiguing.
I don't believe the major cause of nightshift fatigue is the number of consecutive shifts/the length of the shifts but the nature of working with no help/support, repetitive manual handling with little assistance, high workload demands and the inability to take proper breaks…We are constantly pulled in all directions and spend the night running between CT, ED Xray and going to the ward for mobiles. Trying to keep on top of this workload as the sole radiographer [Medical Imaging Technologist] and the pressure to do everything right away and before 6:30 am results in a significant amount of fatigue and stress. Further to this, it is very challenging to get enough staff to help with sliding patients in CT and X-ray overnight. Pulling patients forward to achieve positioning for imaging is also extremely difficult by yourself. I find this adds to my fatigue and often results in MSK pain during night shift. (Participant 16)
| Frequency countsa, n (%) | |
|---|---|
| Theme A: Organisation level changes | 14 (82) |
| Code A: Extra staffing | 10 (59) |
| Code B: Adequate rostered days off to recover | 6 (35) |
| Code C: More consecutive nights rostered on | 4 (24) |
| Code D: Strategies to allow the taking of mandatory breaks | 4 (24) |
| Code E: Cap on number of night shifts per year | 1 (6) |
| Code F: Normal work rosters prior to night shifts | 1 (6) |
| Theme B: Improving your sleep quality | 4 (24) |
| Code G: Black out curtains | 2 (12) |
| Code H: Air conditioning | 2 (12) |
| Code I: White noise machine | 1 (6) |
| Code J: Going to the toilet before bed | 1 (6) |
| Code K: Establishing a normal sleep pattern on night shifts | 1 (6) |
| Theme C: Prioritising your physical health and mental wellbeing | 2 (12) |
| Code L: Taking mandatory breaks | 1 (6) |
| Code M: Staying hydrated | 1 (6) |
| Code N: Eating well | 1 (6) |
| Code O: Treat yourself | 1 (6) |
- a Number of participants whose comments were coded with a particular code or theme.
Even an overnight MIA [medical imaging assistant] could help with admin/phone calls etc. to manage the workload better. (Participant 13)
A number of participants advocated for more consecutive nights rostered on and adequate rostered days off to recover. Participant 7 stated: ‘A longer time than two days to recover is necessary as when we did the small number of nights with quicker turnaround during covid roster I was absolutely ruined returning to dayshift after having only two days off. The week on week off pattern is ideal for that.’ Participant 9 added: ‘Short turn around of decreased number of shifts would put increased pressure on the subsequent day shifts, as it's hard to flip the “sleep routine” in short circumstances.’ Further recommendations for rostering included reducing the number of night shifts allocated over the calendar year with participant 14 recommending ‘no more than 5 weeks per year’. In addition, participant 16 advocated for normal 5-day rosters leading into night shifts: ‘Sometimes we are rostered long stints prior to a week of nights (i.e., work 9 consecutive days, get two days off and then into a week of night shifts)—I find this exacerbates fatigue at the start of night shift week because there has not been sufficient recovery time from the long sting prior. This should be avoided.’
24% of participants felt that their organisation needed to do more to facilitate medical imaging technologists to take their mandatory breaks. Participant 8 stated: ‘More support/awareness/understanding/encouragement [is needed] to take proper breaks and not work through them or snack between patients instead of walking away from the work area etc. For night staff to feel it is acceptable to walk away from pending work to take a break without worrying about the knock on effect of having a break. It's one thing to know we should be taking our breaks but it's another to put it into practice.’ A number of participants felt that having a second medical imagining technologist rostered would allow them to take their mandatory breaks.
The remaining recommendation were strategies that workers could implement to either improve their sleep quality while on night shifts (Theme B) or prioritise their physical health and mental wellbeing (Theme C). Participant 2 recommended trying ‘to establish a regular sleeping pattern ASAP into the night shifts’. Participants 1 and 6 recommending environmental adaptions to improve sleep such as air-conditioning and black out curtains. Participant 8 emphasised the importance of diet and treating oneself on difficult nights: ‘Hydrate hydrate hydrate! Ensure you drink a lot of water to stay hydrated and help with alertness and fatigue. Keep food relatively healthy with fruit and vegie sticks with dip for example but allow yourself a “treat” or reward for the rough nights e.g., snack size chocolate or a cookie.’
5 Discussion
This study explored the lived experience of fatigue for medical imaging technologists who perform night duties. The study found that medical imaging technologist staff perceive roster patterns with more consecutive night shifts and a longer recovery time (i.e., more rostered days off following night shifts) to be less fatiguing and more sustainable. Fatiguing factors including being awake at night and longer shift lengths were perceived as significantly more fatiguing during the first 3 days of night shifts compared to the last 3 days of night shifts. In addition, only one participant felt that their peak performance occurred in the first 3 nights, compared to the last three nights of a seven consecutive night roster.
These findings seem in direct contradiction to some studies that have shown sleep and cognitive performance are impacted when health care workers are required to work consecutive night shifts [4, 18]. However, the study by Harma and colleagues [18] demonstrated that sleep is the most disturbed and there are increased odds of fatigue when rostered to shifts that range from 3 to 4 consecutive nights. Similarly, Kazemi and colleagues [8] demonstrated that individuals who worked 7 consecutive night shifts had a significantly better cognitive performance and sleep quality than those who worked 4 consecutive night shifts at a petrochemical complex. These findings can be explained in terms of circadian rhythm adaptability whereby workers who do over 4 consecutive night shifts adapt themselves to the new sleep–wake cycle leading to increased cognitive performance over the course of consecutive nights [8].
In addition, several participants in this study expressed that the seven day on/seven day off roster for night shifts was superior in terms of recovery time. Ganesan and colleagues [4] have demonstrated that sleep is more disrupted when switching from evening to day shifts than from day to night shifts. In the current study, the mean number of days taken to return to a normal sleep routine following night shifts was reported to be 3.2 days. In addition, two participants reported needing more than 5 days to return to a normal sleep pattern.
While roster patterns do seem to impact on fatigue and performance, the largest fatiguing factor identified by the workers in this study was workload. Participants indicated that workload had a similar impact on fatigue levels throughout the seven-day night roster. More than half of the sample (59%) expressed that additional staffing was needed to address fatigue and workload concerns. It is more common for staff to work independently at night and have less support including assistance with administrative duties. This may further decrease staff productivity on night shifts and introduce added distractions that are likely to further impact on performance. In this study, participants expressed that being the sole medical imaging technologist rostered on impacts on one's ability to take mandatory breaks, increases the risk of musculoskeletal injuries and elevates fatigue and stress levels.
There is a global workforce shortage for medical imaging which is exacerbated by poor retention [19]. The professional lifespan of medical imaging technologists is estimated to be approximately 27 years based on a study conducted in Switzerland [20]. Previous research exploring the lived experience of Medical Imaging Technologists revealed that challenging working patterns and the impact this has on employee health and wellbeing were one of the main reasons for leaving the workforce [21]. A recent global survey revealed that workload, under-appreciated work, and time pressures were ranked as the top three factors contributing to burnout for medical imaging technologists [22]. In addition, the prevalence of work-related musculoskeletal injuries is high within the profession. A study based in Switzerland estimated that 95% of workers experienced work-related musculoskeletal disorder symptoms within the last 12 months [23]. Perceptions of poor sleep quality, higher physically demanding workload, work pressure and stress have been identified as risk factors for developing work-related musculoskeletal disorders within the medical imaging workforce [23, 24]. The current study suggests that organisational considerations such as rostering and adequate staffing during nightshifts can address some of these concerning workforce issues and improve staff health and wellbeing.
The results of this study should be viewed with several limitations in mind. The survey was only distributed at two sites and the total sample size was small, limiting external validity. The survey used was developed for this specific study; it has not undergone testing to ensure its reliability and validity. It is possible that less familiarity with the shorter consecutive night roster may have negatively impacted perceptions. In addition, while two researchers coded the qualitative data to reduce biases, the data could be interpreted differently by others.
Nevertheless, this study adds to the small but growing literature that examines the lived experience of medical imaging technologists with the aim to improve staff health and wellbeing, leading to improved retention. Since this study was conducted, both Prince Charles and Redcliffe hospital have placed a second medical imaging technologist on night shifts and implemented a 7-day on, 7-day off roster for night shifts. Anecdotally, staff are reporting that fatigue from these shifts has been reduced, and management at these sites have reported an increase in the number of staff willing to be included in the night shift roster rotation. There is a need for further published research exploring strategies to improve the working conditions of medical radiation technologists and staff retention.
6 Conclusion
This study explored the lived experience of fatigue brought about by roster patterns, as well as other major causes of fatigue, for medical imaging technologists performing night duties. The results of this study suggest that rostering patterns can impact on fatigue levels and performance, with a 7 night on, 7 night off shift pattern being perceived as being less fatiguing and more sustainable compared to a roster with less consecutive night shifts and less successive days off afterwards. Workload was perceived as the greatest fatiguing factor across the 7 days of night shifts. The majority of participants expressed that organisation level changes are needed to reduce the fatigue of medical imaging technologists who perform night shifts. Given the small sample size, results may not be able to be generalised to other locations. Further research exploring the lived experience of medical imaging technologists is warranted to positively impact on organisational policies.
Acknowledgements
The authors would like to acknowledge the staff of The Prince Charles Hospital medical imaging and Redcliffe Hospital medical imaging and their departments for their time to complete this survey. Open access publishing facilitated by The University of Queensland, as part of the Wiley - The University of Queensland agreement via the Council of Australian University Librarians.
Conflicts of Interest
The authors declare no conflicts of interest.
Open Research
Data Availability Statement
Data related to the present work will be available upon reasonable request to the corresponding author.
