Embed Size (px)
Citation preview
ISBN NUMBER FOR CHEMECA2019 IS 978-1-925627-33-6 Paper no. 169
Chemeca 2019
29 September – 2 October 2019, Sydney, Australia
The Future of Risk Identification in a Rapidly Changing Sociotechnical Work Environment
Joann Kirby1, Maureen Hassall1, Xidong Xu2, Jason Armstrong3
1School of Chemical Engineering, University of Queensland (1), Brisbane, Australia
2Boeing Engineering Test and Technology (2), Seattle, USA
3Boeing Research and Technology (3), Brisbane, Australia
ABSTRACT
Contemporary research indicates increasing rapid and significant changes impacting
sociotechnical work systems will require different approaches to effectively manage risks.
Future research activities, research contexts and research personnel may be quite different
from past and current practices. How people interact with technology and their work
environments will change rapidly and it will be essential to have risk management approaches
that can effectively adapt to address future risks. Research suggests traditional risk
management approaches may not necessarily help researchers identify contemporary and
emergent risks. However, there seems to be a lack of research done to develop approaches that
help manage future risks in research and development environments. Therefore, to help ensure
research worker safety performance into the future, there is a need to explore various socio-
technical elements that impact risk identification, assessment, and management.
This paper comprises research conducted as part of a PhD program to develop an approach
for researchers to use to identify, predict, assess, and manage risks that may arise from their
412
work with future technology without stifling technology innovativeness. The presentation will
discuss a study conducted to identify the range of possible risks that may impact researchers
in the future. Participants from different research contexts were asked, via a survey, to identify
what things might threaten health and safety of workers in their area of research in the next 5
to 10 years. The results from the survey were combined with results from a review of literature
to reveal both continuing and new risks that have the potential to impact workers health and
safety in the future. The presentation will conclude with a discussion of the next steps in the
research that will be conducted to develop and empirically test approaches intended to help
front-line workers more effectively identify, assess and manage foreseeable and emergent risks
without stifling innovativeness.
INTRODUCTION
Researchers are at the forefront of technology innovation which requires them to work in a rapidly
changing sociotechnical environment. The nature of this work environment can expose researchers to
unexpected safety risks. To ensure the safety of researchers it is necessary understand how they identify
and manage safety risks and whether these approaches will identify unexpected safety risks that might
arise from working in a rapidly changing sociotechnical environment. To investigate current practices
used to identify and manage risks in research environments, a systematic review of literature was
completed. The results of the literature review were used to develop a survey that asked researchers
what were the objectives of their work and what might threaten the health and safety of workers in their
area of research into the future.
METHOD
Literature Review
The systematic literature review was conducted by doing a search of the Scopus data base (11th January,
2018) through the UQ Library using the key words “lab safety” and “risk identification”, “safety” and
“research work”, and “research staff safety” and “risk identification”. It was necessary to do a
413
combination of different word searches as to ensure no relevant material was missed. The steps used to
refine the studies in this review are shown in Figure 1.
Figure 1: Flowchart of included studies
Survey Development
A four part survey was developed that investigated participant demographics, work environments
including current and future threats, and various areas of risk identification and methods for improving
risk identification. In this paper we are only concerned with the results concerning future threats to
research worker health and safety. The survey was pilot tested with members of the UQR!SK research
group, and revised by the authors before delivery to the test participant group. The final survey, received
ethics approval from The University of Queensland. The survey participants consisted of full time
research staff, post-doctoral researchers and PhD students from an industry based research group.
414
RESULTS
Literature Review
The three separate searches only resulted in 48 relevant documents, primarily since 2000, with the most
papers published in 2012 as can be seen in Figure 2.
Figure 2: Systematic Literature Review Search Results
The literature reviewed focused on current risk issues that workers are exposed to and how better to
prepare for, and or mitigate the risks to minimise the harm to, or caused by workers. The techniques
described covered a range of established risk identification and management methods including but not
limited to, administrative controls (Whitehurst et al., 2012), previous incident causes (Barreto &
Ribeiro, 2012), failure mode effect analysis (FMEA) (Kessels-Habraken, Van der Schaaf, De Jonge,
Rutte, & Kerkvliet, 2009; Kunac & Reith, 2005), hazard and operability study (HAZOP) (Cullen, 2007),
and likelihood versus consequence risk analysis (Leggett, 2012). Although not all the literature was
directly related to a research environment it did cover many different work environments which could
be relevant to understanding the possible range of risk challenges that people could face as they conduct
their research in many different work environments. The work environments included aeronautical
(Barreto & Ribeiro, 2012; Lyons, 2012), manufacturing (Pieper, 2012), agriculture (Lundqvist &
Svennefelt, 2012), construction (Gillen, Kools, Sum, McCall, & Moulden, 2004), railway (Blewett,
Rainbird, Dorrian, Paterson, & Cattani, 2012), mining (Bahn, 2013), educational institutions (Kremer,
0
10
20
30
40
50
60
0
2
4
6
8
10
12
1994 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Cu
mu
lati
ve P
ape
rs
Nu
mb
er
of
Pu
blic
atio
ns
Year of Publication
Systematic Literature Review Search Results
Research Staff safety & Risk ID Safety and Research Work
Lab Safety & Risk Identification Cumulative Total
415
Ryan, & Switzer, 2009; Naufel & Beike, 2013), fly-in fly-out (FIFO) (Langdon, Biggs, & Rowland,
2016) and medical facilities (Brady & Goldenhar, 2014; Mojica et al., 2016).
Survey
24 participants completed the question “In the next 5 to 10 years, what things might threaten the health
and safety of workers in your area of research”. The main concerns were in the categories of
Ergonomics (37%), Human Machine Interface (17%) and Organisational (17%), the results for the six
main areas are shown in
Figure 3. Each main area was divided into sub-areas as shown in Figure 4, the top three concerns were:
miscellaneous ergonomic issues, training and repetitive strain injuries (RSI).
Figure 3: Main Impact Categories to Safety Objectives
Ergonomics37%
Exposure9%
HMI17%
Organisational17%
People16%
Travel6%
416
Figure 4: Current and Future Risks responses that could impact safety objectives
DISCUSSION
Literature Review
A common theme was the recognition of how experience can play a significant role in risk perception
and how this influences risk identification and the decision making process (Cann, MacEachen, &
Vandervoort, 2008; Jørgensen, Jan Duijm, & Troen, 2011; Kremer et al., 2009; Rossouw & Niemczyk,
2013). Jørgensen, Jan Duijm, & Troen, (2011) recognised that small to medium enterprises (SMEs) are
particularly vunerable to a lack of expertise as they lack the knowledge base of larger enterprises. There
is also concern that in some work situations which have not had a significant incident, can result in staff
developing a level of risk tolerance (Stevenson, McRae, & Mughal, 2008). To overcome knowledge
gaps and to develop expertise, it is beneficial to conduct risk identification activities by assembling
teams with a diverse range of skills and experience (Cullen, 2007). In a study of underground mine
workers (Bahn, 2013), it was found that novices identified the smallest amount of hazards, but long
serving supervisors also struggled to identify the hazards; the study recommended the use of a hazard
identification list as a tool for the miners. Kremer et al. (2009), proposed a hazard identification
algorythm to assist novice researchers identify laboratory risks based on a combination of FMEA and
standard operating procedures (SOP), however this model still had a requirement of a review by an
experienced person. It is vital that an inexperienced person entering a new work environment be
0
2
4
6
8
10
12
Current and Future Impact Resonse Sub-categories
417
adequately trained and supervised (Mulcahy, Boylan, Sigmann, & Stuart, 2017; Ouédraogo, Groso, &
Meyer, 2011a). Mulcahy et al. (2017), has suggested that the use of bowtie diagrams would be an
appropriate means of communicating the hazards and risks in laboratories that are being used by
multiple entities. The use of a multi strategy approach using proactive and reactive techniques was noted
as bringing the best outcomes in identifying and mitigating risks (Badri, Nadeau, & Gbodossou, 2012;
Blewett et al., 2012; Mojica et al., 2016).
It is was recognised that having a good culture within the work environment is condusive to sharing
ideas and feeling comfortable to speak up and report issues (Agnew, Hyten, & Sevin, 2017; Blewett et
al., 2012; Farrington-Darby, Pickup, & Wilson, 2005). Agnew et al (2017), reports that personal values
plays a vital role in the way lone workers self manage risk, as many researchers work in isolation it is
important to develop good behaviours through an established company safety culture. In some
industries developing a good safety culture presents a challenge; the study of railway maintenance
workers completed by Farrington-Darby et al. (2005), indicated that “safety was not percieved as just
the responsibility of those who performed the work”, with participants admitting to sometimes taking
an easier action to perform certain tasks regardless of the associated risks.
There was a general recognition that research performed in a laboratory environment presented many
challenges due to the uncertainty of the work and the high level of inexperience (Groso, Ouedraogo, &
Meyer, 2012; Sims, 2005). Ouedraogo, Groso & Meyer (2011), modelled a “Lab Criticity Index” using
traditional hazard and risk identification processes and explored if this model could be improved by
using an analytical hierarchy process (Ouédraogo, Groso, & Meyer, 2011b), but did not directly address
how it could be used when developing novel technology.
There was recognition that a rapidly changing socio-technical work environment could introduce
psychological stress to the people experiencing theses changes (Fonseca, Gomes, & Barros, 2012), but
no real strategy on how to manage workers psycholoical health was recommended. However, even
though the research reviewed covered a broad range of strategies for risk identification in varied
contexts it did not address how to deal with the uncertainty associated with developing new technology
or the way that work environments and how researchers work in them are changing. There is a need to
418
explore how to best equip research staff to identify risk in a rapidly changing and non-tradition work
environment and develop a strategy that allows them to be agile enough to keep pace with the
technology they are developing while keeping themselves and those around them safe from harm.
Survey
The main concern to the research participant group was the effect of ergonomics, in particular the effect
of poor posture, eye strain and repetitive strain injuries on their future health and wellbeing. This is
indicative that most research is now extensively completed using computers in an office environment.
Training rated the second highest responses from the sub categories listed. Participants recognised the
importance of ongoing and specialised training to ensure research workers remain safe in an ever
evolving workplace. Participants stated that human machine interface poses a significant risk in the
future with main concerns in the area of automation of equipment and processes, and the use of
simulation technology. It is becoming common place for people to be trained using simulators and
virtual reality in the work place (de Visser, Watson, Salvado, & Passenger, 2011; van Wyk & de
Villiers, 2009). This type of training removes the trainee from the line of fire and can be particularly
useful for learning high risk activities such as pilot training (McLean, Lambeth, & Mavin, 2016) and
surgery (Morais, Ashokka, Paranjothy, Siau, & Ti, 2017) and is emerging as a possible training tool in
the laboratory environment (Ghali, Chekired, & Karray). However, the long term health effects from
the use simulation technology are still being investigated (Aardema, Connor, Côté, & Taillon, 2010;
Counotte et al., 2017).
To consolidate the results it is intended to roll the survey out to a larger group of participants from
various research backgrounds. This will complemented by conducting face to face interviews to elicit
in-depth insight to the future safety concerns of research workers. The next phase of the research will
be to conduct fore-sighting exercises through facilitated focus groups with an aim to identify the
emergent risks challenges of future research staff.
CONCLUSION
419
The literature and the survey have shown that researchers are facing a variety of risks that are evolving
with rapidily changing socio technical work environments. Although there was some agreement in
between the literature and the survey results, a larger study is required to validate the future safety
concerns and emergent risk challenges of research workers.
ACKNOWEDGEMENTS
This research was supported by an Australian Government Research Training Program (RTP)
scholarship and by an Industry Top-up Award from Boeing Research and Technology Australia.
REFERENCES
Aardema, F., Connor, K., Côté, S., & Taillon, A. (2010). Virtual reality induces dissociation and lowers
sense of presence in objective reality. Cyberpsychology, behavior and social networking, 13(4),
429. doi:10.1089/cyber.2009.0164
Agnew, J., Hyten, C., & Sevin, B. (2017). Lone Worker Safety. Professional Safety, 62(1), 22-24.
Badri, A., Nadeau, S., & Gbodossou, A. (2012). Proposal of a risk-factor-based analytical approach for
integrating occupational health and safety into project risk evaluation. Accident Analysis &
Prevention, 48, 223-234. doi:http://dx.doi.org/10.1016/j.aap.2011.05.009
Bahn, S. (2013). Workplace hazard identification and management: The case of an underground mining
operation. Safety Science, 57, 129-137. doi:10.1016/j.ssci.2013.01.010
Barreto, M. M., & Ribeiro, S. L. O. (2012). Aircraft accident investigation: The decision-making in
initial action scenario (Vol. 41, pp. 4931-4935).
Blewett, V., Rainbird, S., Dorrian, J., Paterson, J., & Cattani, M. (2012). Keeping rail on track:
Preliminary findings on safety culture in Australian rail (Vol. 41, pp. 4230-4236).
Brady, P. W., & Goldenhar, L. M. (2014). A qualitative study examining the influences on situation
awareness and the identification, mitigation and escalation of recognised patient risk. BMJ
Quality & Safety, 23(2), 153. doi:10.1136/bmjqs-2012-001747
Cann, A. P., MacEachen, E., & Vandervoort, A. A. (2008). Lay versus expert understandings of
workplace risk in the food service industry: A multi-dimensional model with implications for
participatory ergonomics. Work, 30(3), 219-228.
Counotte, J., Pot-Kolder, R., van Roon, A. M., Hoskam, O., van Der Gaag, M., & Veling, W. (2017).
High psychosis liability is associated with altered autonomic balance during exposure to Virtual
Reality social stressors. Schizophrenia Research, 184, 14-20. doi:10.1016/j.schres.2016.11.025
Cullen, L. (2007). Human factors integration – Bridging the gap between system designers and end-
users: A case study. Safety Science, 45(5), 621-629. doi:10.1016/j.ssci.2007.01.002
de Visser, H., Watson, M. O., Salvado, O., & Passenger, J. D. (2011). Progress in virtual reality
simulators for surgical training and certification. The Medical journal of Australia, 194(4), S38.
420
Farrington-Darby, T., Pickup, L., & Wilson, J. R. (2005). Safety culture in railway maintenance. Safety
Science, 43(1), 39-60. doi:10.1016/j.ssci.2004.09.003
Fonseca, C. S., Gomes, C. N., & Barros, F. S. (2012). Screening stress factors survey in an institute of
advanced studies: Health and safety integrated plans (Vol. 41, pp. 5844-5846).
Ghali, M., Chekired, M., & Karray, M.
Gillen, M., Kools, S., Sum, J., McCall, C., & Moulden, K. (2004). Construction workers' perceptions
of management safety practices: A qualitative investigation. Work, 23(3), 245-256.
Groso, A., Ouedraogo, A., & Meyer, T. (2012). Risk analysis in research environment. Journal of Risk
Research, 15(2), 187-208. doi:10.1080/13669877.2011.634513
Jørgensen, K., Jan Duijm, N., & Troen, H. (2011). Demonstration of risk profiling for promoting safety
in SMEs. International Journal of Workplace Health Management, 4(2), 179-193.
doi:10.1108/17538351111143330
Kessels-Habraken, M., Van der Schaaf, T., De Jonge, J., Rutte, C., & Kerkvliet, K. (2009). Integration
of prospective and retrospective methods for risk analysis in hospitals. International Journal
for Quality in Health Care, 21(6), 427-432. doi:10.1093/intqhc/mzp043
Kremer, G. G., Ryan, T. J., & Switzer, S. (2009). A risk assessment method and safety plan for a
university research lab (Vol. 16, pp. 263-268).
Kunac, D., & Reith, D. (2005). Identification of Priorities for Medication Safety in Neonatal Intensive
Care. Drug Safety, 28(3), 251-261. doi:10.2165/00002018-200528030-00006
Langdon, R., Biggs, H. C., & Rowland, B. (2016). Australian fly-in, fly-out operations: Impacts on
communities, safety, workers and their families Work (Vol. 55, pp. 413-427).
Leggett, D. J. (2012). Identifying hazards in the chemical research laboratory. Process Safety Progress,
31(4), 393-397. doi:10.1002/prs.11518
Lundqvist, P., & Svennefelt, C. A. (2012). Health and safety strategy in Swedish agriculture (Vol. 41,
pp. 5304-5307).
Lyons, R. (2012). Complexity analysis of the Next Gen Air Traffic Management System: Trajectory
based operations (Vol. 41, pp. 4514-4522).
McLean, G. M. T., Lambeth, S., & Mavin, T. (2016). The Use of Simulation in Ab Initio Pilot Training.
The International Journal of Aviation Psychology, 26(1-2), 36-45.
doi:10.1080/10508414.2016.1235364
Mojica, E., Izarzugaza, E., Gonzalez, M., Astobiza, E., Benito, J., & Mintegi, S. (2016). Elaboration of
a risk map in a paediatric Emergency Department of a teaching hospital. Emergency Medicine
Journal, 33(10), 684. doi:10.1136/emermed-2015-205336
Morais, R. J., Ashokka, B., Paranjothy, S., Siau, C., & Ti, L. K. (2017). Echocardiography for
Intraoperative Decision Making in Mitral Valve Surgery—A Pilot Simulation-Based Training
Module. Journal of Cardiothoracic and Vascular Anesthesia, 31(5), 1728-1732.
doi:https://doi.org/10.1053/j.jvca.2017.05.027
Mulcahy, M. B., Boylan, C., Sigmann, S., & Stuart, R. (2017). Using bowtie methodology to support
laboratory hazard identification, risk management, and incident analysis. Journal of Chemical
Health and Safety, 24(3), 14-20. doi:10.1016/j.jchas.2016.10.003
Naufel, K. Z., & Beike, D. R. (2013). The Ethical Treatment of Research Assistants: Are We Forsaking
Safety for Science? Journal of Research Practice, 9(2).
421
Ouédraogo, A., Groso, A., & Meyer, T. (2011a). Risk analysis in research environment – Part I:
Modeling Lab Criticity Index using Improved Risk Priority Number. Safety Science, 49(6),
778-784. doi:10.1016/j.ssci.2011.02.006
Ouédraogo, A., Groso, A., & Meyer, T. (2011b). Risk analysis in research environment – Part II:
Weighting Lab Criticity Index using the Analytic Hierarchy Process. Safety Science, 49(6),
785-793. doi:10.1016/j.ssci.2010.12.011
Pieper, R. (2012). How to evaluate the risks of work equipment and installations for health and safety?
Research and activities of the German Committee for Plant Safety and consequences for
regulation (Vol. 41, pp. 3321-3324).
Rossouw, J. P., & Niemczyk, E. K. (2013). A Dual Perspective on Risks and Security within Research
Assistantships. Journal of Research Practice, 9(2).
Sims, B. (2005). Safe Science: Material and Social Order in Laboratory Work. Social Studies of Science,
35(3), 333-366. doi:10.1177/0306312705052362
Stevenson, L., McRae, C., & Mughal, W. (2008). Moving to a Culture of Safety in Community Home
Health Care. Journal of Health Services Research & Policy, 13(1_suppl), 20-24.
doi:10.1258/jhsrp.2007.007016
van Wyk, E., & de Villiers, R. (2009). Virtual reality training applications for the mining industry (pp.
53-63).
Whitehurst, J. M., Schroder, J., Leonard, D., Horvath, M. M., Cozart, H., & Ferranti, J. (2012). Towards
the creation of a flexible classification scheme for voluntarily reported transfusion and
laboratory safety events. Journal of biomedical semantics, 3, 4. doi:10.1186/2041-1480-3-4
BIOGRAPHY
Jo Kirby
Jo is a Chartered Chemical Engineer with 16 years’ experience working as both a process design
engineer and commissioning engineer on many major projects. Jo has held a number of different
positions on Engineers Australia’s professional committees, including chair Women in Engineering
(WIEQ), Deputy Chair Joint Chemical Engineering Committee (JCEC) Qld, Qld Division Committee,
Chair of Women in Engineering National Committee (WIENC) and member of the EA Chemical
College Board. Jo is currently completing an industry partnered PhD at the University of Queensland
School of Chemical Engineering.
Maureen Hassall
Maureen is an Associate Professor and project manager of UQ R!SK at The University of
Queensland. Her research and consulting work focuses on developing and applying innovative,
422
practical and effective user-centred solutions that address the range of current and future risks faced
by industry. Maureen also provides risk management and human factors advice, education and
training direct to industry and to undergraduate, Masters and PhD students at the university. She holds
bachelor degrees in engineering and psychology, a MBA and PhD in Cognitive Systems Engineering.
Prior to joining UQ, Maureen worked for more than 15 years in mining, processing and
manufacturing industries in Australia, New Zealand and Canada.
Xidong Xu
Xidong is an Associate Technical Fellow in the Boeing EHS (Environment, Health and Safety)
organization supporting workplace safety and aviation safety across Boeing ET&T (Engineering, Test
& Technology). He has led various projects including human factors R&D and hazard analysis for the
safety of United States’ Next Generation Air Transportation System (NextGen). More recently, he has
been playing a critical role in using a systems approach to improve performance in safety, quality,
environment, and systems engineering across Boeing. Other parts of his career include aviation safety
and human factors R&D in the BR&T (Boeing Research & Technology) Airspace Operations &
Efficiency (AOE) group, the BCA (Boeing Commercial Airplanes) Aviation Safety group, NASA
Ames Research Center, University of Illinois at Urbana-Champaign, Central Michigan University, and
Swiss Federal Institute of Technology (ETH) in Zurich. He was a faculty member at the Civil Aviation
University of China teaching air traffic control.
Jason Armstrong
423
Jason received his PhD at a NASA Research & Training Centre in the USA in conjunction with
Kansas State University. That work involved automation & experimental design of immunological
payloads for three space shuttle missions and included himself flying on NASA zero gravity
aircraft missions. Following on from this he worked in robotics in the US and from the late 1990s
to 2011 he worked in venture capital. This included CEO and board roles, and in 2005 he led a
company through an IPO on the ASX.
Currently, Jason leads Boeing Research in Brisbane with a portfolio across: human factors,
materials/manufacturing, simulation & autonomy.
424
