Beskæftigelsesudvalget 2019-20
BEU Alm.del Bilag 104
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Article
Physical and psychosocial work environmental risk
factors for back injury among healthcare workers:
Prospective cohort study
Lars L. Andersen (PhD)
1,
*, Jonas Vinstrup (MSc)
1
, Ebbe Villadsen (MSc)
1
, Kenneth Jay (PhD)
1
,
Markus D. Jakobsen (PhD)
1
National Research Centre for the Working Environment, DK-2100 Copenhagen, Denmark.
*
Correspondence: Professor Lars L. Andersen, [email protected]
Received: date; Accepted: date; Published: date
Abstract:
The incidence of occupational back injury in the healthcare sector remains high despite
decades of efforts to reduce such injuries. This prospective cohort study investigates risk factors for
back injury during patient transfer. Healthcare workers (n=2,080) from 314 departments at 17
hospitals in Denmark replied to repeated questionnaires sent every 14 days for one year. Using
repeated-measures binomial logistic regression, controlling for education, work, lifestyle and
health, the odds for back injury (i.e. sudden onset episodes) were modeled. Based on 482 back injury
events, a higher number of patient transfers was an important risk factor, OR 3.58 (95% CI 2.51-5.10)
for 1-4 transfers per day, OR 7.60 (5.14-11.22) for 5-8 transfers per day, and OR 8.03 (5.26-12.27) for
9 or more transfers per day (reference: less than 1 per day). Lack of necessary assistive devices was
a common phenomenon during back injury events, with the top four being lack of sliding sheets
(30%), intelligent beds (19%), walking aids (18%) and ceiling lifts (13%). For the psychosocial factors,
poor collaboration between and support from colleagues increased the risk for back injury, OR 3.16
(1.85-5.39). In conclusion, reducing the physical burden in number of daily patient transfers,
providing the necessary assistive devices, and cultivating good collaboration between colleagues
are important factors in preventing occupational back injuries among healthcare workers.
Keywords:
Health Care Sector; Nurses; Occupational Injuries; Low Back Pain; Workplace
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1. Introduction
Recent data from the Global Burden of Disease Study shows that low-back pain continues to be
a leading cause of years lived with disability [1]. While low-back pain is multifactorial in origin,
several work-related factors can contribute. Heavy lifting, frequent turns, twisting and bending of
the back, are among the commonly reported work-related risk factors for low-back pain [2,3]. These
are also associated with increased risk for long-term sickness absence [4,5] and early involuntary
retirement from the labor market [6 8]. Such physical exposures are common among workers with
manual material handling as well as healthcare workers.
Healthcare workers transferring patients, e.g. nurses and nurses aides,
are frequently
experiencing back-related problems [9] often due to injuries occurring suddenly and unexpectedly
during patient transfers. Several studies show an association between patient transfer and risk of
back injury [10 14], and biomechanical studies confirms the high physical loading of the back during
such work [15 17]. Across the European Union, healthcare workers rate their own health and safety
as poorer than the rest of the working population [18], and qualitative interviews indicate that this
negatively impacts quality of life and overall satisfaction with the job [19]. Altogether, back injuries
can lead to long-term negative physical and psychological consequences [20]. Thus, several important
reasons for preventing back injuries among healthcare workers exist.
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One important initiative to prevent back injuries is ensuring consistent use of assistive devices
during patient transfer [10]. Thus, among healthcare workers in eldercare, consistent use of assistive
devices is associated with markedly decreased risk of future back injury [10]. Likewise, involving the
healthcare workers and their leaders in a participatory approach for improved use of assistive devices
have shown to reduce the incidence of injuries to about half [21]. However, to be successful in this
endeavor, a good collaboration between colleagues as well as with the leaders is probably important.
An Australian study further reported that a no lifting policy
i.e. making it obligatory to use
assistive devices during patient transfer - led to fewer back injury compensation claims [22].
However, healthcare workers often face situations where the necessary assistive devices are not
readily available [23]. Knowledge about which assistive devices that are commonly missing when
back injuries occur may help hospitals to better plan preventive strategies.
While the majority of preventive strategies at hospitals focus on ergonomic factors, improving
psychosocial factors may also be important. Thus, a recent systematic review suggests that
psychosocial factors such as high demands and low job control, effort-reward imbalance, and low
social support may be important risk factors for musculoskeletal disorders among healthcare workers
[24]. Several studies have also highlighted the role of good leadership as important for the health
status of this population [25].
The aim of this study was therefore to investigate physical and psychosocial work
environmental risk factors for back injury during patient transfer among healthcare workers in
hospitals. To encounter some of the methodological shortcomings of previous studies, e.g. recall bias
and a long time between exposure and outcome, we used a repeated measures design with
questionnaires every 14 days during a year.
2. Materials and Methods
2.1. Study design and population
The design is a prospective cohort study with a baseline questionnaire in 2017 and repeated
questionnaires every 14 days for one year. The baseline questionnaires were sent by e-mail to 7,025
employees from 389 departments at 19 hospitals in Denmark, of which 4,151 (59.1%) responded. The
only inclusion criteria at the department level was that there should be some sort of patient transfer,
i.e. excluding office and administrative departments. All hospitals were public and represented two
(North and Mid) of the five regions in Denmark (North, Mid, South, Zealand, Capital). Of the
respondents, only groups working directly with patients (nurses, nurses aids, healthcare assistants,
occupational therapists, physical therapists, midwifes and medical doctors, porters, and radiographs)
were selected for further analysis (n=3,885). Participants received a short questionnaire every 14 days
during one year after baseline. For the present analysis, we included only healthcare workers who
responded to at least three of the repeated questionnaires during the 1-year follow-up period,
yielding a final sample size of 2,080 healthcare workers spanning 314 different departments from 17
hospitals. The mean number of repeated responses during 1-year follow-up was 12.3 (SD 7.3). Table
1 shows the baseline characteristics of the included study population (N=2,080 ~ 54%) as well as of
the non-responders (N=1,805 ~ 46%) to the repeated questionnaires during follow-up.
Table 1.
Demographics, work, health and lifestyle at baseline. Results are either mean (SD) or
prevalence as percentage (%) of the study population.
Variable
N
Age (mean)
Gender (% women)
Seniority, years (mean)
NUMBER OF DAILY PATIENT TRANSFERS (%)
Less than 1
1-4
Study population Non-responders
2,080
1,805
48.2 (11.1)
44.5 (11.5)
87.1 %
86.4 %
17.9 (11.7)
15.0 (11.4)
39.3 %
28.4 %
34.3 %
30.9 %
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9 or more
PSYCHOSOCIAL WORK FACTORS (0-100, where 100 is best)
Collaboration between and support from colleagues
Influence at work
Recognition and support from management
HEALTH FACTORS
Mental health (0-100, where 100 is best)
Low-back pain intensity (0-10)
Previous back injury (%)
LIFESTYLE FACTORS
Smoking (% yes)
BMI (mean)
Leisure physical activity (%)
1. Seated
2. Light activities for at least 4 h per week
3. Physical exercise or other strenous activities for at least 4 hours per week
4. Hard physical exercise and competitions on a regular basis
17.9 %
14.4 %
18.8 %
16.1 %
80.0 (13.9)
73.5 (17.6)
69.2 (20.9)
78.0 (14.6)
70.0 (18.8)
64.3 (22.6)
82.2 (13.4)
2.4 (2.6)
10.2 %
80.3 (14.2)
2.3 (2.5)
13.0 %
8.1 %
25.4 (4.8)
6.5 %
61.7 %
28.9 %
3.0 %
10.6 %
24.8 (4.7)
7.4 %
58.4 %
29.9 %
4.3 %
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2.2. Ethical approval and data protection
The National Research Centre for the Working Environment has an agreement with the Danish
Data Protection Agency about registering all studies in-house. According to Danish law,
questionnaire- and register-based studies need neither approval from ethical and scientific
committees nor informed consent [26]. All data were de-identified and analyzed anonymously.
2.3. Predictors
In relation to the physical work demands, frequency of patient transfer was evaluated with the
following question sent every 14 days during the one year follow-up period:
How many patients have
you transferred per day at working days during the last 14 days (if you transfer the same patient more than
once per day, it
counts as more patients)
with the response options: 1) none, 2) less than one per day
(e.g. 2-3 per week), 3) 1-2 per day, 4) 3-
per day, …
9-20
per day, 13) more than 20 per day [23].
An explanation was provided regarding the meaning of a transfer including some examples;
by a
transfer is meant to help a patient move from one place to another or from one position to another, for example
1) from bed to wheelchair, 2) from chair to toilet chair, 3) help the patient move further up in the bed, 4)
accommodate the patient in the wheelchair, 5) turn the patient, 6) situations where the patient needs to get
dressed or with personal hygiene
. For the subsequent analyses, the categories were collapsed to 1) less
than once per day, 2) 1-4 per day, 3) 5-8 per day, and 4) 9 or more per day.
In relation to psychosocial work factors, participants replied at baseline to questions from the
Copenhagen Psychosocial Questionnaire [27] about 1) collaboration between and support from
colleagues (three items), 2) influence at work (two items), and 3) recognition and support from the
management (two items). Responses from the questions of each scale were averaged and normalized
on a scale of 0-100 according to the test score manual (100 is best). For subsequent analyses, we
defined 0-
as poor , .
-
as moderate and .
-
as good psychosocial work environment
for each of the three scales.
2.4. Outcome
A back injury event was evaluated with the question Have you injured your back
during a
patient transfer within the previous 14 days (think about whether the pain occurred suddenly and
unexpected during the transfer with the response categories
no,
yes, one time,
yes, two
times, and 4) yes, three or more times. For subsequent analyses, categories 2-4 were collapsed into
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yes
[10].
Those
replying yes to a back injury also received the following questions:
Sick leave:
Did you have to go on sick leave due to the back-injury?
with the response options 1)
no, and 2) yes (indicate number of sick leave days).
Assistive devices: Were the
necessary assistive devices available when the back injury
occurred? with the response options no, and yes.
Those replying no also received the question Which assistive device s were lacking when the back
injury occurred? with a
-item multiple-choice list of assistive devices.
In short, this list included the vast majority of assistive devices used during patient transfer; spanning
from common friction-reducing devices (e.g. sliding sheets, sliding boards and masterturners)
characterized by a manual approach to horizontal transfer and/or repositioning in bed, to devices
utilized when moving the patient from one room to another (e.g. walking aids, wheelchairs, gait belts
and stand-assist lifts). Finally, the more technologically-advanced devices (e.g. lifts, intelligent beds
and electric versions of the masterturner) are most commonly used when transferring old, frail and/or
bariatric patients within the room (e.g. from bed to chair).
2.5. Control variables
To control for possible confounding, we included basic variables about work, health and lifestyle
from the baseline questionnaire.
Basic variables:
Age (continuous variable) and sex (female, male).
Work-related factors beside the predictor variables:
Healthcare specific education (categorical variable, e.g.
nurse, medical doctor, physical therapist etc.), seniority (years working as healthcare worker,
continuous variable).
Health:
Mental health from SF-36 (continuous variable) [28], low-back pain
intensity during the previous month (continuous variable, 0-10) [29].
Lifestyle:
Body mass index (BMI
= weight/ height
2
, continuous variable), smoking status (daily smoker, not daily smoker, ex-smoker,
non-smoker), leisure physical activity (4-categories from sedentary to a very high level of leisure
physical activity) [30]. From the repeated short questionnaires sent every 14 days, the analysis was
controlled for the number of working days during the last 14 days (continuous variable), i.e. in the
same period as the predictor variable number of daily patient transfers , and for previous back injury
using the previous reply 14 days before.
2.6. Statistical analysis
Using repeated-measures binomial logistic regression with random effects modeling, we
estimated the risk for back injury events during follow-up. The dataset was re-arranged for the
predictor variable (number of patient transfers) to always come 14 days before the outcome variable,
and the control variable of previous back injury to come 14 days before the predictor variable. This
allowed an analysis of the prospective short-term association between exposure (patient transfer) and
the risk of back injury 14 days later, controlling for previous back injury 14 days before. The analysis
was mutually controlled for the number of patient transfers and the psychosocial variables, and also
controlled for the variables previously mentioned (2.5. Control variables). Further, it was adjusted
for clustering at the department level using the random statement of PROC GLIMMIX SAS version
9. . Using the random _residual_ statement, the analysis also took into account that each participant
provided several repeated measures during follow-up. The degrees of freedom method was set to
containment. The main results are provided as odds ratios (OR) and 95% confidence intervals (95%
CI). Other descriptive statistics are provided as means (SD) and prevalence (percentage, %).
3. Results
Table 1 shows that, at baseline, the mean age was 48 years of the responders to the repeated
questionnaire and 45 years of the non-responders, and the majority of the healthcare workers were
women. The majority had daily patient transfers. Mental health was on average normal (>80) and the
intensity of low-back pain was about 2 in both responders and non-responders. During the last year
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prior to baseline, 10.2% and 13.0% of the responders and non-responders, respectively, had
experienced at least one back injury (i.e. sudden onset episode) during patient transfer. For the
lifestyle factors, BMI was on average about 25, there were only few smokers, and the majority (about
60%) performed light physical activity during leisure.
During the 1-year follow-up period, there were 482 reported back injury events. The unadjusted
incidence of back injuries during the last 14 days was 0.3%, 2.4%, 5.4% and 7.0% among those with
less than 1, 1-4, 5-8 and 9 or more patient transfers per day, respectively (not shown in the tables). Of
the back injury events, 7.8% lead to sickness absence of 1 day or more, with an average of 3.8 days
[SD 4.0] (not shown in the tables).
Table 2 shows the fully adjusted analysis between number of daily patients transfer during the
last 14 days and the risk for back injury, as well as between the psychosocial work environmental
factors at baseline and the risk for back injury. A higher number of patient transfers was in an
exposure-response fashion - an important risk factor, OR 3.58 (95% CI 2.51-5.10) for 1-4 transfers per
day, OR 7.60 (5.14-11.22) for 5-8 transfers per day, and OR 8.03 (5.26-12.27) for 9 or more transfers per
day (reference: less than 1 per day). A trend test, i.e. using the number of patient transfers as
continuous variable, was also highly significant in relation to back injury events (P<0.001). For the
psychosocial factors, poor collaboration between and support from colleagues increased the risk, OR
3.16 (1.85-5.39). A trend test, i.e. using collaboration between and support from colleagues as
continuous variable, was also significant (P<0.01). Influence at work as well as recognition and
support from management were not significant risk factors for back injury in the present analysis.
Table 2.
Odds ratios and 95% confidence intervals for the risk of back injury events during the 1-year
follow-up period. Statistically significant findings are marked in bold.
n
%
OR (95% CI)
a
Number of daily patient transfers
b
Less than 1
13543
53.3
1
1-4
7223
28.4
3.58 (2.51 - 5.10)
5-8
2575
10.1
7.60 (5.14 - 11.22)
9 or more
2061
8.1
8.03 (5.26 - 12.27)
c
Collaboration between and support from colleagues
Good
1051
51.2
1
Moderate
917
44.7
1.09 (0.82 - 1.43)
Poor
85
4.1
3.16 (1.85 - 5.39)
c
Influence at work
Good
606
29.5
1
Moderate
1089
53.0
1.00 (0.73 - 1.36)
Poor
358
17.4
1.20 (0.81 - 1.79)
c
Recognition and support from management
Good
572
27.9
1
Moderate
928
45.2
1.27 (0.91 - 1.78)
Poor
553
26.9
1.01 (0.68 - 1.51)
a, adjusted for gender, age, number of working days last 14 days, education, seniority, previous back injury,
mental health and low-back pain intensity
b, repeated measures every 14 days during the year, i.e. accumulated n
c, measured at baseline
184
185
186
187
188
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In 26.4% of the back injury events during patient transfer, the healthcare workers reported that
one or more of the necessary assistive devices were not available. Table 3 shows which assistive
devices that were most commonly lacking when a back injury event occurred. Top four were lack of
sliding sheets (30%), intelligent beds (19%), walking aids (18%) and ceiling lifts (13%).
Table 3.
Prevalence as percentage (%) of necessary assistive devices that were lacking in relation to
back injury events among those who stated that one or more assistive devices were lacking.
Assistive device that was lacking
Sliding sheet
Percentage of back injury cases
29.6%
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Intelligent bed
Walking aids
Ceiling-lift
Floor-lift
Hospital bed
Masterturner, electric
Sling
Wheelchair
Masterturner
Stand-assist lift
Sliding boards
Standing-lift
Gait belt
Toilet-chair, electric
Toilet-chair
19.0%
17.6%
12.7%
12.0%
12.0%
12.0%
11.3%
9.9%
9.9%
8.5%
7.8%
7.8%
5.6%
4.9%
4.2%
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4. Discussion
This study investigated physical and psychosocial work environmental risk factors for back
injury during patient transfer among healthcare workers at hospitals. The main findings were that a
higher number of patient transfers as well as poor collaboration between and support from colleagues
were risk factors for back injury. In the specific situations where back injuries occurred, the healthcare
workers often lacked the necessary assistive devices, most commonly sliding sheets, intelligent beds,
walking aids and ceiling lifts.
The number of daily patient transfers was in an exposure-response fashion a risk factor for
sustaining a back injury during patient transfer. This confirms previous findings in the eldercare
sector [10], although the odds ratios were much higher in the present study. A difference between
these two studies is that the previous study only had a 1-year follow-up questionnaire and not
repeated measures. Because exposure and injury are often temporally related i.e. an unexpected
high mechanical load may cause a sudden injury using repeated questionnaires increases the chance
of finding an association between exposure and risk of injury two weeks later. However, an injury
may also be preceded by accumulated exposure that ultimately leads to the injury event where a
sudden and unexpected back pain occurs during patient transfer. To account for this we controlled
for low-back pain intensity at baseline, i.e. to account for exposure that may have led to a level of
discomfort or pain, but not (yet) resulted in an actual injury. Likewise, the analysis was controlled
for previous back injury, which is a strong predictor of future injury [31]. Lastly, we controlled for
mental health and lifestyle factors, which have also been linked to the development of low-back pain
[32 34].
Aside from physical exposure, this study also evaluated the availability of necessary assistive
devices when a back injury event occurred. Equipment availability constitutes one of the most cited
factors influencing safe patient transfer scenarios [35], and perhaps most importantly nurses
themselves perceive this as the most effective component in decreasing the frequency of lifting-
related accidents [36]. In the present analysis, we report that the most commonly lacking assistive
devices were, in descending order, sliding sheets, intelligent beds, walking aids and ceiling-lifts.
Considering that not only general use of assistive devices decreases the risk of back injury [10], but
also the fact that specific groups of assistive devices are associated with lower physical load than
others (e.g. ceiling-lifts and intelligent beds) (Vinstrup 2019 under review), it remains highly
problematic that healthcare workers consistently report lack of equipment as a reason to engage in
unsafe patient transfers. Further, considering the low cost of the sliding sheet (i.e. a friction-reducing
sheet placed underneath the patient), it seems prudent to make sure that this specific assistive device
is readily available in all departments.
Biomechanical laboratory studies have shown that muscular load during patient transfer is
lower when using the ceiling lift compared to the traditional floor lift [37]. However, another study
showed equally reduced compression forces of the low-back using the ceiling and floor lift [38].
Similarly, slings also reduce back compression forces albeit not as effectively as lifts [38], whereas
utilizing the sliding sheet has been shown to reduce the biomechanical compression force on the low-
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back [16].In contrast, two recent systematic reviews of longitudinal intervention studies found
limited evidence for preventive interventions with assistive devices to reduce musculoskeletal pain
and injuries among healthcare workers [39 41], indicating that low physical load and the availability
of assistive devices are only part of the puzzle. However, adequate implementation of the
intervention or the description hereof is often lacking in intervention studies, and whether the lack
of preventive effect is due to efficacy-failure or implementation-failure remains uncertain. While
performing multiple randomized controlled trials is unfeasible and costly, well-controlled
prospective cohort studies can provide an alternative approach to shed light on the association
between work-related factors of patient transfer and the risk for back injury.
Regarding the psychosocial work factors, we found that poor collaboration between and support
from colleagues was a risk factor for back injury. This is in line with a review showing that poor social
support may be a risk factor for musculoskeletal disorders among healthcare workers [24]. Thus,
fostering good collaboration between colleagues that can support each other seems to be important
for the local working environment. There may be several explanations for this finding: First,
supporting each other in busy periods may indirectly reduce the physical workload as well as
individual distress. Second, by solving the tasks together in teams, the individual healthcare worker
may reduce the physical workload when dealing with heavy and relatively immobile patients.
Third, it may be easier to find and use appropriate assistive devices when good collaboration between
colleagues exists. Thus, there may be several direct and indirect reasons for the importance of good
collaboration between colleagues in the prevention of back injuries.
Several studies have highlighted good leadership as important for the health of healthcare
workers [25]. Surprisingly, we did not find a significant influence of recognition and support from
the management for the risk of back injury. Nevertheless, it should be remembered that the
management can have an important indirect role by securing a good overall work environment that
facilitates collaboration between and support from other colleagues in situations where needed. In
addition, we did not find a significant association between influence at work and risk of back injury,
although we expected that healthcare workers with a higher degree of influence at work would be
able to better plan their work to avoid unnecessary high workloads and injuries. Nevertheless,
previous studies have reported inconsistent results regarding the importance of influence at work in
relation to health outcomes [42 44].
Strengths and limitations
The present study has both strengths and limitations. A strength is the repeated-measures
design, which increases the statistical power and allows investigation of the temporal associations
between exposure and risk of injury. Furthermore, recall bias is likely very limited, as the
questionnaires were sent out every 14 days. By contrast, many studies use retrospective reporting of
up to one year of exposure or outcome, which makes recall bias much more likely. A limitation of
such design is the difficulty in getting people to reply repeatedly over a year. Thus, 46% of the
baseline population chose not to participate in the repeated questionnaires during 1-year follow-up.
However, based on the baseline characteristics (Table 1) there were only minor differences between
the responders and non-responders. Furthermore, controlling for a number of confounders increase
the validity of the findings.
Regarding the sample size, we have previously found strong exposure-response associations
between manual lifting and risk of acute back pain using a repeated measures design with less than
100 workers in the supermarket sector [45]. However, to increase the generalizability of the present
study we aimed to include as many healthcare workers from as many hospitals in Denmark as
possible. With a final sample of 2,080 healthcare workers spanning 314 different departments from
17 different hospitals the results are likely generalizable to hospitals in general, although only two of
the five regions in Denmark were represented.
5. Conclusions
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In conclusion, reducing the physical burden in terms of number of daily patient transfers,
providing the necessary assistive devices, and cultivating good collaboration between colleagues are
important for preventing occupational back injuries among healthcare workers.
Author Contributions:
LLA designed and lead the study. All authors contributed to the study design, data
collection and data analysis. LLA drafted the manuscript and all co-authors provided critical feedback and
approved the final version.
Funding:
Author LLA obtained a grant from the Danish Working Environment Research Fund
(Arbejdsmiljøforskningsfonden) for this study. Grant number 26-2015-09.
Conflicts of Interest:
The authors declare no conflict of interest.
Data Sharing Statement:
Researchers interested in using the data should contact the project leader Prof. Lars L.
Andersen.
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