Determinants of Return to Work After Occupational Injury

Abstract

The promotion of return to work (RTW) following occupational injury benefits injured workers, their families, enterprises and the society. The identification of the potential determinants would be helpful in improving RTW rate and minimizing the duration of absenteeism following injury.
The aim of the study was to identify the potential determinants of RTW following work-related injury.
A historical cohort of workers with occupational injury in a state-owned locomotive vehicles company in central China was followed up on the outcomes of RTW. Demographic, employment and medical information was retrieved from the company archival documents; and post-injury information was interviewed by structured questionnaires. Univariate analysis and Cox Regression Model were used to examine the associations between potential determinants and outcomes of RTW.
Three hundred of the 323 cases (92.9%) eventually returned to work after the median absence of 43 days. Factors from socio-demographic, clinical, economic, and psychological domains affected RTW in the univariate analyses. The multivariate analysis indicated that age, injury severity, injury locus, injury nature, pain in the injury locus, self-report health status and pre-injury monthly salary were significant determinants of RTW.
There were multidimensional factors affecting RTW after occupational injury. Proper clinical treatment and rehabilitation, as well as economic and social support to facilitate workers' RTW would be the priorities upon intervention. Future studies should be conducted in larger representative samples to confirm the findings and to develop a multidisciplinary intervention strategy towards promoting RTW.

Full text

Determinants of Return to Work After Occupational Injury
Yonghua He •Jia Hu •Ignatius Tak Sun Yu •
Wei Gu •Youxin Liang
Published online: 18 February 2010
ÓSpringer Science+Business Media, LLC 2010
Abstract Introduction The promotion of return to work
(RTW) following occupational injury benefits injured
workers, their families, enterprises and the society. The
identification of the potential determinants would be
helpful in improving RTW rate and minimizing the dura-
tion of absenteeism following injury. Objectives The aim of
the study was to identify the potential determinants of
RTW following work-related injury. Methods A historical
cohort of workers with occupational injury in a state-
owned locomotive vehicles company in central China was
followed up on the outcomes of RTW. Demographic,
employment and medical information was retrieved from
the company archival documents; and post-injury infor-
mation was interviewed by structured questionnaires.
Univariate analysis and Cox Regression Model were used
to examine the associations between potential determinants
and outcomes of RTW. Results Three hundred of the 323
cases (92.9%) eventually returned to work after the median
absence of 43 days. Factors from socio-demographic,
clinical, economic, and psychological domains affected
RTW in the univariate analyses. The multivariate analysis
indicated that age, injury severity, injury locus, injury
nature, pain in the injury locus, self-report health status and
pre-injury monthly salary were significant determinants of
RTW. Conclusions There were multidimensional factors
affecting RTW after occupational injury. Proper clinical
treatment and rehabilitation, as well as economic and social
support to facilitate workers’ RTW would be the priorities
upon intervention. Future studies should be conducted in
larger representative samples to confirm the findings and to
develop a multidisciplinary intervention strategy towards
promoting RTW.
Keywords Determinants Return to work 
Work-related injury
Introduction
Work is a defining feature of human beings at working age.
Occupational injury may severely damage work ability,
leading to absence from duty and even unemployment.
According to a hospital-based study, the rate of return-to-
work (RTW) following work injury in south China was
about 80% [1]. The reported RTW rates for 71 worldwide
studies varied widely from 29 to 100% with a median rate
of 67% [2]. Delayed RTW has become a challenging social
problem in many societies, significantly affecting socio-
economic status and individual well-being [3]. The pro-
motion of RTW following occupational injury is important
Y. He J. Hu Y. Liang (&)
School of Public Health/Fudan-Liberty Mutual SafeWork
Center/WHO Collaborating Center for Occupational Health,
Fudan University, P.O. Box 288, No. 130, Dong’an Road,
200032 Shanghai, People’s Republic of China
e-mail: yxliang@shmu.edu.cn
Y. He
e-mail: hyhup@shmu.edu.cn
J. Hu
e-mail: 062102091@fudan.edu.cn
I. T. S. Yu
Center for Occupational and Environmental Health Studies,
School of Public Health and Primary Care, The Chinese
University of Hong Kong, Hong Kong, SAR,
People’s Republic of China
e-mail: iyu@cuhk.edu.hk
W. Gu
Huashan Hospital, Fudan University, 200040 Shanghai,
People’s Republic of China
e-mail: gerryvip@163.com
123
J Occup Rehabil (2010) 20:378–386
DOI 10.1007/s10926-010-9232-x

to injured workers, their families, enterprises and the
society. The identification of factors that predict chronic
disability following injuries would guide the intervention
strategy to reduce the proportion of workers progressing
from injury to disability, to minimize the duration of work
absence, and to elevate the rate of RTW [4–6].
About 100 determinants of RTW outcomes were iden-
tified in previous studies [7–9], but very few studies of
relevance have been reported from developing countries,
including China, which is undergoing a unique economy
reform with social infrastructure being changed. All these
changes would have definitely affected employment situ-
ation, medical insurance system and social well-being.
Based on the multi-domain model focusing on the indi-
vidual, medical, economic and social factors in the RTW
process [10,11], we presented the outcomes of RTW after
work-related injury, and explored the possible link amongst
various determinants and the outcomes of RTW in central
China.
Methods
Subjects
This is a retrospective cohort study based on employees
with work-related injury in a large scale state-owned
company. As one of the main manufacturing bases of
locomotive vehicles in China, the company was established
in 1936 and had invested assets more than 2.55 billion
RMB (about US $375 million) with a total of 16,538
employees in 2007. The Division of Labor and Social
Security affiliated to the company has been set up since
2004, when the State Council Work-related Injury Insur-
ance Regulation was put into effect.
An injury case was officially identified and registered by
the Department of Labor and Social Security of the local
authority if the direct medical cost was more than 200 RMB
(about US $30), and the record was archived in a company
Occupational Injury Document. All injuries occurring dur-
ing the period between October 2004 and June 2008 were
included. Only those 55 years and younger for females and
60 and younger for males were included in the study as
these are the official retirement thresholds. Workers who
suffered from work-related injury two or more times were
only be investigated for the first injury event; cases of fatal
accident did not excluded from this study.
Data Collection
The study was approved by Institutional Review Board
(IRB) of Fudan University School of Public Health. An
experienced nurse of the research team was responsible for
getting access to the company archival document. Infor-
mation including demographic characteristics (e.g., gender,
birth date, marital status) and clinical status (injured body
part, nature, cause, and severity scale) was extracted from
the company’s Occupational Injury Document. The edu-
cation level, job title, average monthly salary of the last
3 months before injury, compensation provided by the
local authority for the injury (yes, no), monthly job leave
compensation, and RTW outcomes including duration of
sick leave, job title and task, and monthly salary after RTW
[12] were collected from the record file of the Personnel
and Finance Office of the company.
This study was reviewed by IRB and all subjects com-
pleted and informed consent prior to participation. The pre-
injury data included number of family members being
supported, life style (e.g., smoking and/or drinking habit:
no, sometimes, often), and job satisfaction (poor, fair,
well). The post-injury data included self-perceived health
status (poor, fair, well), pain in the injured locus (yes, no),
other health problems (meaning diseases unrelated to the
injury: yes, no), worrying about recurrence of injury (yes,
no), successful RTW, and the satisfaction to RTW if hav-
ing had RTW. Four options on how RTW was achieved
were offered to those who returned to work: (1) by one-
self—denoting the case asked the employer directly for
job; (2) by relatives/family members/trade union—denot-
ing the case asked help for a job from relatives, family
members or the trade union; and (3) by other ways.
Successful RTW in the study was defined as staying on
the job for at least 1 month and was paid not less than the
local standard of minimum monthly wage (ranged 530–610
RMB, equivalent to US $76–90, during 2004–2008) within
7 months after the date when injury occurred. The duration
of absenteeism was defined as the period between the date
when the work-related injury occurred and the first date of
resuming work for those with successful RTW.
The severity scale of injury was not always rated by the
Department of Labor and Social Security of local author-
ities. Based on the Declaration Form of Work-related
Injury,Case Registration Record, and medical history
provided by the Division of Labor and Social Security of
the company, the severity for all cases was identified by
five certified experts according to the State Standard for
Identifying Work Ability: Gradation of Disability Caused
by Work-related Injuries and Occupational Diseases. The
injury severity was scaled from Level 1 (the most serious)
to Level 10 (the least serious). Cases with severity lower
than Level 10 were grouped as ‘‘Lower than Level 10’’.
Statistical Analyses
The descriptive results were presented by median, and
mean ±standard deviation (SD) for the continuous
J Occup Rehabil (2010) 20:378–386 379
123

variables, or by percentage for categorical variables. The
age, working experience and salary were ranked as 5, 6 and
6 subgroups, respectively, with roughly equal number of
cases in each group. The education level was regarded
ordinal and categorized as junior middle school and below,
senior middle school, and college. The technical title was
also treated as ordinal, with operator as the lowest level.
Pearson Chi-Square was employed to test the propor-
tions of RTW among the categories of the independent
variables. As the duration of absence was found not to be
normally distributed with Shapiro–Wilk Test, Mann–
Whitney Utest of 2 Independent Samples or Jonckheere–
Terpstra Test of kIndependent Samples Nonparametric
Tests were applied to the comparison of the absence
duration among the categorical variables of sub-groups.
Cox Regression [13] was employed to estimate the hazard
ratios (HR) of the independent variables for which the
uninvariate analysis returned a P-value \0.05, including
variables for both before and after injury. A subject would
be considered to exit from the cohort when he/she suc-
cessfully returned to work, or censored on the last date of
follow-up if lost to follow-up. LR Forward stepwise
regression was carried out, and the probabilities for entry
and removal were 0.05 and 0.10, respectively.
The data were double entered and checked with EpiData
3.1; and the statistic analyses were performed on SPSS
16.0 (SPSS Inc., IL, USA). The Pvalue was set at 0.05, 2-
tailed.
Results
Characteristics of the Subjects
A total of 335 workers suffered from work-related injuries
in the company during the recruitment period. Eight
workers experienced injury twice, and only the first injury
of each was included in the study. Fatal accidents hap-
pened to 2 workers and they were not included. Another
worker was excluded as a result of being involved in a law
dispute. Among the 332 recruited subjects, 9 cases were
lost to follow-up, with a successful follow-up rate of
97.3%. The cases who were lost to follow-up were all
married male and at the average age of 36.8 ±5.4. Three
of them were mechanic and the others were senior
mechanic. Five of them were with injury of level 10 and
the others lower than level 10. A total of 16,563 person-
days of the follow up were observed among the 323
injured workers, ranging from 14 days to 1,374 days for
individual workers.
The median age of the 323 participants at injury was
37.5 years old and the median working experience was
18.4 years (Table 1). All cases were employed full time
before injury. About 80% of them were male and married.
Of these subjects, around 50% had senior middle school
education with a job title of senior mechanic; and 50% had
injury severity at level 10 and 34.1% at ‘‘Lower than Level
10’’.
Outcomes of RTW After Work-Related Injury
During the follow-up period of 7 months after the onset
date of the occupational injury, three hundred cases
(92.9%) successfully returned to work after median
absence duration of 43.0 days (Table 2). Eight workers
attempted to return, but could not maintain their job for at
least 1 month. Fourteen workers did not try to work again,
and one worker enjoyed the full amount of disablement
benefit according to national regulations because of severe
injury. More than 80% of the 300 workers returned to full
time jobs in the original work sites and earned not less than
before the injury, and were generally satisfied with RTW.
Returning to the original job, full-time work, high satis-
faction with RTW and active asking for RTW were sig-
nificantly associated with shorter absenteeism.
Table 1 Characteristics of the study cohort (n=323)
Characteristics Median Mean ±SD
Age 37.5 37.8 ±8.7
Working years pre-injury 18.4 18.4 ±9.5
Monthly salary pre-injury
(RMB)
1,600 1,739 ±569
N (%)
Gender Female 64 (19.8)
Male 259 (80.2)
Marital status Single/divorced/
widowed
59 (18.3)
Married 264 (81.7)
Education level Junior middle school
and below
75 (23.2)
Senior middle school 192 (59.4)
College 56 (17.3)
Technical job title Operator 58 (18.0)
Mechanic 89 (27.6)
Senior mechanic 137 (42.4)
Technician 21 (6.5)
Senior technician 18 (5.6)
Pre-injury occupational group Manager 12 (3.7)
Technician 273 (84.5)
Laborer 38 (11.8)
Injury severity Higher than Level 9 11 (3.4)
Level 9 30 (9.3)
Level 10 172 (53.3)
Lower than Level 10 110 (34.1)
380 J Occup Rehabil (2010) 20:378–386
123

Univariate Analyses on Potential Determinants
of RTW Outcomes
The chance of RTW and the duration of absence were
significantly associated with technical title, injury severity,
injury locus, self-perceived health status, pain in the injury
locus, worrying about re-injury or RTW, if the severity had
been rated by the local authority, satisfaction with pre-
injury job, monthly salary pre-injury, and during the absent
days, as well as age and education level. Workers with less
serious injury, better self perceived health status, and better
monthly salary promoted during the absent days versus pre-
injury got more chance of successfully RTW. Free from
pain, high satisfaction with pre-injury job, and severity not
being rated by the authority were associated with higher
rate of RTW.
The duration of absence was significantly affected by
injury nature, being complicated with other disease,
achieving in compensation from the local authority, and the
number of dependent family member. Workers with less
serious injury and better self report health status took
shorter sick leaves. Being free from pain or other disease,
not worrying about re-injury or RTW, injury severity not
being rated or not compensated by the authority, and the
number of dependent family members B2 were associated
with shorter absent days.
Cox Regression Analyses of Potential Determinants
of RTW
Factors remaining in the final model included age, injury
severity, locus, nature, pain, self-reported health status, and
monthly salary pre-injury. The psychological factors were
excluded from the model. Younger age, minor injury
severity, free from pain in injury locus, good health status,
and higher income pre-injury were found to be significantly
beneficial to RTW. Different injury loci and natures had
varied effects on the absence duration and rate of RTW
(Table 3).
Discussion
We followed-up a cohort of over 300 workers with work-
related injuries in a locomotive vehicle production factory
in China and found that most of the injuries were mild and
the majority of injured workers were able to return to the
same job and at the same workshop as pre-injury with no
Table 2 Outcomes of RTW
after work-related injury
*P\0.05; ** P\0.01,
compared on duration of
absence
RTW Absence duration
N(%) Median Mean ±SD
Same work site as before
No 6 (1.9) 66.5 52.7 ±31.7
Yes 294 (91.0) 42.5 49.1 ±38.8
Same job title as before**
No 17 (5.3) 87 127.9 ±132.0
Yes but modified 13 (4.3) 64 139.4 ±301.5
Yes 270 (83.6) 42 52.3 ±52.7
Full time work*
No 26 (8.0) 69 87.4 ±80.9
Yes 274 (84.8) 44 58.6 ±90.3
Monthly salary versus pre-injury
Lower 27 (8.4) 85 102.2 ±101.4
Same 243 (75.2) 41 56.9 ±91.7
Higher 30 (9.3) 46.5 56.9 ±37.1
Satisfaction with RTW**
Poor 8 (2.5) 51.5 84.8 ±93.0
Fair 136 (42.1) 61 71.6 ±112.7
High 156 (48.3) 36 50.7 ±61.4
Way for getting RTW**
By oneself 254 (78.6) 41 51.9 ±60.3
By relatives/family members/trade union 24 (7.4) 78 89.3 ±83.3
Others 22 (6.8) 89.5 127.1 ±221.6
Total
Successful RTW 300 (92.9) 43 49.2 ±38.6
J Occup Rehabil (2010) 20:378–386 381
123

Table 3 Univariate analyses
between potential predicators
and work absence
Domain/factor RTW status Duration of absence
RTW (%) Not RTW Median Mean ±SD
Socio-demographic
Age*
*30 56 (95.5) 3 38 43.6 ±31.6
31–35 64 (94.6) 3 43 47.1 ±37.0
36–40 70 (96.4) 4 43.5 49.8 ±42.0
41–45 54 (83.6) 2 35 44.6 ±39.7
46*56 (92.2) 11 59 60.8 ±40.1
Education level*
Junior middle school and below 67 (89.3) 8 63 55.2 ±33.7
Senior middle school 180 (93.8) 12 37 47.7 ±41.7
College 53 (94.6) 3 41 46.5 ±33.1
Technical title**
,
***
Operator 50 (86.2) 8 58.5 57.6 ±33.8
Junior Mechanic 84 (94.4) 5 56 54.0 ±39.4
Senior Mechanic 130 (94.9) 7 34 43.4 ±38.5
Junior Technician 20 (95.2) 1 47.5 47.2 ±42.2
Senior Technician 16 (88.9) 2 39 46.5 ±41.6
Clinical
Injury severity**
Higher than Level 9 8 (72.7) 3 72 76.9 ±34.5
Level 9 24 (80.0) 6 68 67.2 ±36.8
Level 10 159 (92.4) 13 61 59.9 ±38.2
Lower than Level 10 109 (99.1) 1 16 27.5 ±29.2
Injury locus*
Maxillofacial 54 (98.2) 1 14 26.9 ±32.3
Trunk 20 (90.9) 2 39 48.6 ±38.5
Upper limbs 120 (95.2) 6 61 60.9 ±37.8
Lower limbs 81 (91.0) 8 38 47.0 ±37.2
Multi-locus 25 (80.6) 6 42 48.6 ±39.9
Injury nature***
Fracture 109 (89.3) 13 70 71.2 ±32.3
Contusion/compression 115 (97.5) 3 16 35.4 ±37.2
Cutting/avulsion 31 (88.6) 4 47 50.2 ±38.5
Burn 16 (94.1) 1 22 22.7 ±14.4
Multiple injuries 6 (85.7) 1 50.5 59.3 ±52.2
Others 23 (95.8) 1 25.5 75.5 ±236.6
Self-perceived health status**
,
***
Poor 15 (60.0) 10 60 55.1 ±30.6
Fair 119 (91.5) 11 50 54.7 ±37.9
Well 166 (98.8) 2 35.5 44.7 ±39.4
Pain**
,
***
No 185 (98.9) 2 25 38.1 ±35.5
Yes 115 (84.6) 21 65 67.0 ±36.8
Complicated with other diseases*
No 286 (93.2) 21 42 47.8 ±37.8
Yes 14 (87.5) 2 68.5 77.9 ±45.2
382 J Occup Rehabil (2010) 20:378–386
123

salary lowered down. The outcome of RTW was mainly
predicated by age, injury severity, injury locus and nature,
pain, self-perceived health status and income pre-injury.
Age was the only socio-demographic factor examined in
our study that remained in the Cox model. Workers of age
346 years had significant lower RTW rate than younger
workers, and this could be due to the labor policy of
encouraging older workers to retire earlier to ensure
vacancies for younger people. For gender, marital status
and life style, there were no evidence from our findings to
completely agree with some other studies [14,15]. The
difference could be partially attributed to the fact that the
labor policy in China did not allow discrimination of
employment and payment according to gender and marital
status. Furthermore, the state-owned company ensured a
friendly relationship between labor and management,
which might be advantaged to workers’ RTW after injury
(Table 4).
Injury severity was generally reported as the key factor
affecting RTW [12,16–18]. Less serious injuries were
associated with a better chance of RTW and shorter sick-
ness absence in the current study. Though pain in the injury
locus was reported not necessary linked with disability in
other studies [19], our results showed that it was signifi-
cantly associated with successful RTW and sick leave
duration, as indicated in some similar studies [18,20].
As the typical and representative factor of the economic
domain, pre-injury monthly salary was the only economic
factor affecting RTW in the multi-variable analysis. The
other three economic factors (whether compensation was
given, change in salary during sick leave, number of
dependents in family) were not selected into the final
Table 3 continued
*P\0.05; ** P\0.01,
compared on RTW rate.
*** P\0.01, compared on
duration of absence
Domain/factor RTW status Duration of absence
RTW (%) Not RTW Median Mean ±SD
Psychological
Worrying about re-injury*
,
***
No 163 (96.4) 6 30 41.3 ±38.3
Yes 137 (89.0) 17 61 58.5 ±37.1
Worrying about RTW**
,
***
No 228 (95.8) 10 35.5 43.9 ±37.3
Yes 72 (84.7) 13 65 65.8 ±38.3
Satisfaction with pre-injury job*
,
***
Poor 18 (90.0) 2 33 52.2 ±48.8
Fair 131 (89.7) 15 44 50.8 ±35.9
High 151 (96.2) 6 42 47.4 ±39.8
Socio-economic
Severity rated*
,
***
No 249 (95.0) 13 33 42.3 ±36.8
Yes 51 (83.6) 10 83 82.9 ±28.5
Compensation achieved***
No 251 (93.3) 18 35 45.0 ±38.9
Yes 49 (90.7) 5 72 70.4 ±29.2
Monthly salary pre-injury**
,
***
*1,200 51 (23.5) 12 122.5 99.1 ±136.4
1,201–1,500 82 (90.1) 9 46.5 54.4 ±39.5
1,501–1,800 32 (97.0) 1 62.5 58.4 ±43.6
1,801–2,100 52 (100.0) 0 26.5 36.7 ±34.3
2,101–2,400 43 (100.0) 0 30 40.3 ±37.1
2,401*40 (97.6) 1 31.5 38.4 ±30.9
Monthly salary during absence**
,
***
Decreased 71 (83.5) 14 61 58.5 ±37.4
Same 223 (96.1) 9 38 46.1 ±38.8
Increased 6 (100.0) 0 54 54.2 ±32.3
No. of dependent family members***
B2 218 (92.8) 17 37.5 44.7 ±37.3
[2 82 (93.2) 6 63 61.0 ±39.9
J Occup Rehabil (2010) 20:378–386 383
123

model for successful RTW. Financial constraint was con-
sidered to weigh in the employee’s decision balance, and
contribute to the decision of going back to work too soon
[21]. In China, like other developing countries, family
economic situation was not good enough and the social
security was not perfect, so people were apt to retain their
job for living after suffering from work-related injuries.
Higher monthly salary resulted in higher chance of RTW
and shorter duration of sick leave in our study. It was
possible that workers with higher salary generally pos-
sessed more social support benefiting their RTW. Similar
to another study on predictors of time lost from work fol-
lowing a distal radius fracture [22], compensation was a
significant predictor in univariate analyses, but was
Table 4 Cox Regression of
potential determinants for return
to work
a
Higher hazard ratio means
higher chance of returning to
work
*P\0.05; ** P\0.01
Regression
coefficient
Standard
error
Hazard
ratio
a
95% CI for
hazard ratio
Socio-demographic
Age
46*Reference
*30 0.207 0.207 2.392** 1.594–3.591
31–35 0.197 0.197 2.197** 1.492–3.234
36–40 0.189 0.189 1.598* 1.103–2.317
41–45 0.203 0.203 2.252** 1.512–3.354
Clinical
Injury severity
Lower than Level 10 Reference
Higher than Level 9 0.427 0.427 0.097** 0.042–0.223
Level 9 0.276 0.276 0.330** 0.192–0.568
Level 10 0.185 0.185 0.424** 0.295–0.609
Injury locus
Upper limbs Reference
Maxillofacial 0.191 0.191 2.340** 1.609–3.403
Trunk 0.261 0.260 1.608 0.965–2.675
Lower limbs 0.151 0.1517 1.145 0.852–1.539
Multi-locus 0.241 0.241 0.946 0.590–1.516
Injury nature
Fracture Reference
Contusion/compression 0.191 0.191 1.298 0.893–1.888
Cutting/avulsion 0.223 0.223 1.241 0.802–1.922
Burn 0.325 0.325 5.422** 2.866–10.258
Multiple injuries 0.443 0.443 0.803 0.337–1.916
Others 0.274 0.274 2.016* 1.178–3.450
Pain
Yes Reference
No 0.143 0.143 1.826** 1.379–2.419
Self-perceived health status
Good Reference
Bad 0.322 0.322 0.346** 0.184–0.650
Fair 0.154 0.154 0.865 0.640–1.117
Socio-economic
Monthly salary pre-injury
*1,200 Reference
1,201–1,500 0.186 0.186 1.569* 1.090–2.258
1,501–1,800 0.243 0.243 1.691* 1.050–2.724
1,801–2,100 0.216 0.216 2.207** 1.445–3.372
2,101–2,400 0.232 0.232 2.404** 1.525–3.789
2,401*0.241 0.241 2.035** 1.270–3.259
384 J Occup Rehabil (2010) 20:378–386
123

excluded from multivariate models. Regretfully, there have
not been many studies on the association between eco-
nomic factors and RTW, partly because of the social
security systems varied among regions [14].
Workers’ psychological status was important to RTW,
but it might be alleviated by some other positive factors
such as good social support and work scheme adjusting
[23], and consequently excluded from the multivariate
model.
Most of our subjects received RTW by actively asking
for work, and only a small fraction of them received RTW
at the assistance of relatives and so on. It suggested that a
more complete social support system should be available to
offer help towards RTW. It has been shown that company
policy could be an important factor affecting RTW [24],
and workers themselves, social support and labor organi-
zations might work together to play an even more effective
role in prompting RTW. RTW promotion approaches, e.g.,
early contact between employees and employers on work
accommodation (offer and acceptance), guiding ergonomic
worksite visit [16,25], offering job training [15], and
providing consulting by RTW coordinators [26] or man-
agers [27] were reported to be critical effective intervention
on RTW.
A great number of studies examined predictors of RTW,
but not all of these studies had consistent results because of
differences in target population, selection criteria, study
design, data analysis, prognostic indicator, and follow-up
protocol [10,28]. It should be noted that a few limitations
existed in the present study. Firstly, the subjects in the
study were recruited from a large state-owned company,
where the social security system was more reliable than
small and medium scaled non-state companies [29,30].
Consequently, the results might only be applicable to large
state-owned companies. Secondly, some information on
pre-injury life style, job satisfaction and self-perceived
health status was collected sometime after the injury, and
inherent recall bias and measure errors could not be totally
avoided. Thirdly, many important predictors for RTW,
such as treatment/rehabilitation and organizational factors,
were not examined in the current study, and confounding of
our results due to such factors could not be excluded.
The results of the present study indicated that demo-
graphic, clinical and economic factors were significant in
determining RTW after work-related injuries, suggesting
that interventions towards promoting RTW should be
multidimensional [19,31]. Clinical treatment and rehabil-
itation [32], economic and social support to facilitate
workers’ RTW would be the priority for the intervention
[24,33]. Future research should further confirm the find-
ings in a larger representative population towards devel-
oping multidisciplinary intervention strategy conducive to
promoting RTW following work injuries.
References
1. Li K, Tang D, Lu X. Investigation on reemployment and epide-
miology for various groups of injured workers. Chinese J Rehabil
Med. 2006;21:64–6.
2. Athanasou JA. Return to work following whiplash and back
injury: a review and evaluation. Med Leg J. 2005;73:29–33.
3. Waddell G, Aylward M, Sawney P. Back pain, incapacity for
work and social security benefits: an international literature
review and analysis. London: R Soc Med Press; 2002.
4. Sullivan MJ, Feuerstein M, Gatchel R, Linton SJ, Pransky G.
Integrating psychosocial and behavioral interventions to achieve
optimal rehabilitation outcomes. J Occup Rehabil. 2005;15:
475–89.
5. Crook J, Moldofsky H. The probability of recovery and return to
work from work disability as a function of time. Qual Life Res.
1994;3:S97–109.
6. Kim J, June K, Yang BM, Park E, Park KM. Time dependent
factors affecting the duration of work disability after compen-
sated low-back pain in South Korea. Ind Health. 2006;44:503–9.
7. Niclas K, John WF, Lisa KD, Terry JA, Sandra JS. Determinants
of duration of disability and return-to-work after work-related
injury and illness: challenges for future research. Am J Ind Med.
2001;40:464–84.
8. Seland K, Cherry N, Beach J. A study of factors influencing
return to work after ankle fractures. Am J Ind Med. 2006;49:197–
203.
9. Oleinick A, Gluck JV, Guire KE. Factors affecting first return to
work following a compensable occupational back injury. Am J
Ind Med. 1996;30:540–55.
10. Pransky G, Gatchel R, Linton JS, Loisel P. Improving return to
work research. J Occup Rehabil. 2005;15:453–7.
11. Crook J, Milner R, Schultz IZ, Stringer B. Determinants of
occupational disability following a low back injury: a critical
review of the literature. J Occup Rehabil. 2002;12:277–95.
12. Pransky G, Benjamin K, Hill-Fotouhi C, Fletcher EK, Himmel-
stein J. Occupational upper extremity conditions: a detailed
analysis of work-related outcomes. J Occup Rehabil. 2002;12:
131–8.
13. Sears MJ, Heagerty JP. Including injured workers without com-
pensated time loss in Cox regression models: analyzing time loss
using all available data. J Occup Rehabil. 2008;18:225–32.
14. Lund T, Labriola M, Christensen KB, Bultmann U, Villadsen E.
Return to work among sickness-absent Danish employees: pro-
spective results from the Danish Work Environment Cohort
Study/National Register on Social Transfer Payments. Int J
Rehabil Res. 2006;29:229–35.
15. Ahlgren A, Bergroth A, Ekholm J. Work resumption or not after
rehabilitation? A descriptive study from six social insurance
offices. Int J Rehabil Res. 2004;27:171–80.
16. Franche RL, Severin NS, Sheilah HJ, Cote P, Vidmar M, Lee H.
The impact of early workplace-based return-to-work strategies on
work absence duration: a 6-month longitudinal study following
an occupational musculoskeletal injury. J Occup Environ Med.
2007;49:960–74.
17. Loisel P, Durand MJ, Baril R, Gervais J, Falardeau M.
Inter-organizational collaboration in occupational rehabilitation:
perceptions of an interdisciplinary rehabilitation team. J Occup
Rehabil. 2005;15:581–90.
18. Corbiere M, Sullivan MJL, Stanish DW, Adams H. Pain and
depression in injured workers and their return to work: a longi-
tudinal study. Can J Behav Sci. 2007;39:23–31.
19. Burton WN, Pransky G, Conti DJ, Chen CY, Edington DW. The
association of medical conditions and presenteeism. J Occup
Environ Med. 2004;46:S38–45.
J Occup Rehabil (2010) 20:378–386 385
123

20. Kovacs MF, Muriel A, Castillo MD, Medina MJ, Royuela A, The
Spanish Back Pain Research Network. Fear avoidance beliefs
influence duration of sick leave in Spanish low back pain patients.
Spine. 2007;32:1761–6.
21. Pransky G, Benjamin K, Hill-Fotouhi C, Himmelstein J, Fletcher
KE, Katz JN, et al. Outcomes in work-related upper extremity
and low back injuries: results of a retrospective study. Am J Ind
Med. 2000;37:400–9.
22. MacDermid CJ, Roth HJ, McMurtry R. Predictors of time lost
from work following a distal radius fracture. J Occup Rehabil.
2007;17:47–62.
23. Pirjo J, Keijo P, Tapani K, Sirkka KK. The reality of returning to
work and training: experiences from a long-term unemployment
project. Int J Rehabil Res. 2004;27:215–27.
24. Tate DG, Habeck RV, Schwartz G. Disability management: a
comprehensive framework for prevention and rehabilitation in the
workplace. Rehabil Lit. 1986;47:230–5.
25. Schweigert MK, McNeil D, Doupe L. Treating physicians’ per-
ceptions of barriers to return to work of their patients in Southern
Ontario. Occup Med. 2004;54:425–9.
26. Shaw W, Hong QN, Pransky G, Loisel P. A literature review
describing the role of return-to-work coordinators in trial pro-
grams and interventions designed to prevent workplace disability.
J Occup Rehabil. 2008;18:2–15.
27. Lyth JR, Miller M. Case managers facilitate successful return to
work in difficult cases utilizing return-to-work tools and therapist
partnerships. Lippincott’s Case Manag. 2005;10:108–10.
28. Linton SJ, Gross D, Schultz I, Main C, Cote P, Pransky G, et al.
Prognosis and the identification of workers risking disability:
research issues and directions for future research. J Occup
Rehabil. 2005;15:459–74.
29. Peters J, Pickvance S, Wilford J, MacDonald E, Blank L. Pre-
dictors of delayed return to work or job loss with respiratory ill-
health: a systematic review. J Occup Rehabil. 2007;17:317–26.
30. Amick BC, Lerner D, Rogers WH, Rooney T, Kate JN. A review
of health-related work outcome measures and their uses, and
recommended measures. Spine. 2000;25:3152–60.
31. Katz NJ, Amick CB, Keller R, Fossel HA, Ossman J, Soucie V,
et al. Determinants of work absence following surgery for carpal
tunnel syndrome. Am J Ind Med. 2005;47:120–30.
32. Kominski FG, Pourat N, Roby HD, Cameron EM. Return to work
and degree of recovery among injured workers in California’s
workers’ compensation system. J Occup Environ Med. 2008;50:
296–305.
33. Huang YH, Shaw SW, Chen YP. Worker perceptions of organi-
zational support and return-to-work policy: associations with
post-injury job satisfaction. Work. 2004;23:225–32.
386 J Occup Rehabil (2010) 20:378–386
123