Forestry
An International Journal of Forest Research
Forestry 2015; 88, 391 – 406, doi:10.1093/forestry/cpv011
Advance Access publication 2 May 2015
Beyond physical health and safety: supporting the wellbeing of workers
employed in the forest industry
Melinda R. Mylek* and Jacki Schirmer
Centre for Research and Action in Public Health, University of Canberra, Canberra ACT, 2601, Australia
*Corresponding author. Tel.: +61 0262012864; E-mail: [email protected]
Received 12 August 2014
A healthy, productive and resilient workforce is important to any industry, and supporting the wellbeing of workers
is a key factor in achieving this. Worldwide, the forest industry is amongst the most physically dangerous industries
to work in. Workplace health and safety strategies have traditionally focused on improving the physical safety of
forestry workplaces. It is equally important to consider the broader wellbeing of workers, not only to ensure
their quality of life, but also to support a healthy and sustainable workforce with low turnover. To do this, it is critical
to understand the work-related factors that affect worker wellbeing. We examine this via a survey of workers in the
Australian forest industry. We find that work-related factors known to influence wellbeing in other industries, such
as income, job security and workplace culture, are strongly correlated with forest worker wellbeing, that negative
perceptions of the forest industry by those outside it are associated with lower levels of worker wellbeing and that
the extent to which a forest industry worker has a strong work-related social identity is associated with their wellbeing. Our findings highlight the importance of implementing workplace strategies that consider wellbeing in
broader terms than the traditional focus on physical safety.
Introduction
Wellbeing refers to a person’s overall quality of life (Costanza et al.,
2007) and is affected by diverse social, physical, psychological and
spiritual factors (Cummins et al., 2003; Larson et al., 2006; Costanza et al., 2007). These include a person’s physical and mental
health, social capital, self-efficacy, equality and equity of access
to resources, standard of living, freedom, personal safety and
security, and health of the natural environment (Cummins et al.,
2003; Larson et al., 2006).
Many of these factors can be influenced by a person’s workplace. Understanding wellbeing in the workplace is important for
any industry, not only because it helps improve the quality of life
of workers but because it assists organizations to increase productivity, successfully recruit staff, improve staff retention and foster an
industry that is resilient to conflict and change (Stiglitz, 2002;
Diener and Seligman, 2004; Parks and Steelman, 2008; McCarthy
et al., 2011; Schirmer et al., 2011). People whose workplace contributes positively to their wellbeing have demonstrably higher levels
of workplace productivity, lower levels of stress, lower absenteeism
and higher job satisfaction (Martin, 2004; Parks and Steelman,
2008; McCarthy et al., 2011).
The forest industry is one of the most dangerous industries to
work in worldwide (Crowe, 1982; ILO, 1998; Blombäck, 2002;
McCormack, 2002). While the physical health of workers in the
forest industry is important and has received substantial attention
in the past, there is a significant lack of robust data on the broader
wellbeing of forest industry workers. This paper contributes to
addressing this gap in understanding and in particular to
identifying the work-related factors associated with higher and
lower levels of subjective wellbeing in forest industry workers.
We first review current knowledge on worker wellbeing. As there
is limited literature specifically targeted at the broader wellbeing of
forest industry workers, we draw on the growing literature on
worker wellbeing in general and include forest industry-specific evidence where it is available. We then describe the methods we used
to survey Australian forest industry workers about their wellbeing.
Our results focus on understanding when and how working in the
forest industry is likely to influence worker wellbeing (positively or
negatively). We draw on these findings to identify key areas in
which action can be taken to improve wellbeing of workers in the
industry and assist in developing a healthier, more productive
and resilient industry workforce.
The study context
Our study draws on data from a 2012-2013 survey of workers in the
Australian forest industry. We focus on examining the wellbeing of
workers in four different industry sectors: (1) forest growers or
managers of forests and plantations (referred to as forest managers), (2) harvesting, haulage and roading contractors (referred
to as contractors), (3) wood- and paper-manufacturing workers
and (4) others such as consultants, people working in nurseries,
people working for departments not specific to forest management and contractors engaged in silvicultural management (referred to as ‘other’ workers). We focus on these categories
because they involve different types of job task and because they
are relevant not only within Australia but more broadly: the most
# Institute of Chartered Foresters, 2015. All rights reserved. For Permissions, please e-mail: [email protected].
391
Forestry
recent available global statistics estimate that in 2006 the forest industry (wood production, wood processing and pulp and paper industries) employed 13.7 million people worldwide (FAO, 2009).
While global data on forest industry employment distribution are
limited and measured using different categories (Lebedys, 2004),
in 2000 it was estimated that about two-thirds of the people
employed in forestry were in the wood- and paper-manufacturing
sectors, and one-third was in forest growing and management.
In Australia, decades of increasing mechanization means that
most of the 61 400 jobs in the forest industry are in wood and
paper product manufacturing (51 800 people), and only 9600
jobs are in forest growing, management and harvesting (ABARES,
2014). This is a typical employment structure in regions with a
highly mechanized forest industry, such as North America, Europe,
New Zealand and parts of South America and South Africa. In lessmechanized forest industryoperations, common in developing countries, a greater proportion of employment will occur in forest growing
and harvesting, whereas in more mechanized industries, a greater
proportion is generated by the processing of harvested timber.
Increasing mechanization and improved safety provisions in
particularly risky occupations within the industry have resulted in
declining rates of physical injury in recent decades (Vayrynen,
1984; Kirk et al., 1997; Axelsson, 1998; Bell, 2002; Synwoldt and
Gellerstedt, 2003; Bell and Grushecky, 2006), but despite this
many roles in the industry still expose workers to high risk of physical injury or disease. For example, operating heavy machinery has
risk of injury together with sedentary-related disease risks associated with spending long hours sitting while operating machinery
(Vayrynen, 1984; Slappendel et al., 1993; Hagen et al., 1998; Lilley
et al., 2002; Nieuwenhuis and Lyons, 2002; Heaney, 2007; Sarathy,
2008). Additionally, forest industry changes such as evolving
markets, shifting social expectations, political change and
restructuring have been associated with changes in work procedures, work hours and expectations. These have in turn been associated with an increase in physical injury rates, most notably in
British Columbia (Heaney, 2007; Lawson, 2010). Patterson (2007)
argued that economic pressures create an atmosphere in which
timber workers are willing to accept higher risk of physical injury
rather than risk a reduction in economic return.
Employment and wellbeing
Wellbeing is influenced by many different aspects of a person’s life,
of which their workplace is only one. A person’s work can influence
their wellbeing in multiple ways, and over the years, the field of
workplace health and safety has expanded from an initial focus
on physical health and safety, to considering the overall wellbeing
of workers, which includes both physical and mental health (e.g.
Kusel, 1996; Sparks et al., 2001; Stiglitz, 2002; Cotton and Hart,
2003; Diener and Seligman, 2004; McCarthy et al., 2011). Below,
we briefly review key workplace-related factors known to influence
wellbeing of workers.
Physical injury and disease prevention
Prevention of injury and disease in the workplace has long been a
focus of worker wellbeing programmes, typically through initiatives
that improve workplace safety, reduce exposure to disease risks
and support workers to achieve appropriate nutrition and exercise
(Parks and Steelman, 2008; McCarthy et al., 2011).
There are no reliable global statistics on accident rates in the
forest industry, as common criteria for reporting incidents have
not been adopted worldwide, and many countries fail to report
incidents altogether (Ackerknecht, 2010). However, there is evidence that the forest industry is amongst the most physically dangerous to work in worldwide (Crowe, 1982; Blombäck, 2002;
McCormack, 2002). In multiple countries, including Australia,
New Zealand, British Columbia and the USA, workers employed in
logging, wood processing and forest management have higher
than average rates of physical injury (Slappendel et al., 1993;
Myers and Fosbroke, 1994; Driscoll et al., 1995; Bentley et al.,
2002, 2005; Lilley et al., 2002; Heaney, 2007; Sarathy, 2008;
Alamgir et al., 2014; Moseley et al., 2014). For example, in 2012,
British Columbia reported an average injury rate of 5 per cent
within the forest industry, compared with the average injury rate
for all of British Columbia of 2.3 per cent (WorkSafe BC, 2014). In
Australia during 2005 –2006, the agriculture, forestry and fishing
industry reported an injury rate of 10.9 per cent, which was
nearly 60 per cent higher than average accident rates for all Australian workers (6.9 per cent) (Safe Work Australia, 2009).
392
Formal working conditions: going beyond safety
Other working conditions also affect worker wellbeing. The following conditions in particular are documented to influence worker
wellbeing:
† Long work hours, or irregular work hours, negatively impact wellbeing, particularly through reducing time for home life (Tausig
and Fenwick, 2001; McCarthy et al., 2011).
† A worker’s income is a key contributor to their own and their
family’s wellbeing (Kusel, 1996; Diener and Seligman, 2004;
McCarthy et al., 2011), both through contributing to standard
of living and via the status and recognition associated with
being paid an income (Stiglitz, 2002).
† Security of employment has important effects on work-related
stress, job satisfaction and overall wellbeing (Stiglitz, 2002).
Lower levels of security – for example, casual jobs, fixed-term
contracts or job insecurity more broadly – are associated with
lower wellbeing and lower work motivation (Sparks et al., 2001).
† The autonomy a worker has contributes to their wellbeing:
workers who feel able to control and direct their own work typically have higher job satisfaction, commitment, performance and
motivation, whereas lower levels of control are associated with
emotional distress, absenteeism and lower overall wellbeing
(Daniels and Guppy, 1994; Kusel, 1996; Sparks et al., 2001).
In general, if working conditions create stress they have the potential to reduce a person’s overall wellbeing (Cotton and Hart, 2003).
This area of worker wellbeing has not been explored in the forest industry literature; however, these issues were found to apply in a
2011 study of forest industry workers in Tasmania, Australia,
where uncertainty and downsizing in the forest industry was associated with increased stress levels and lower wellbeing (Schirmer
et al., 2011).
Informal working conditions: workplace relationships
and identity
A person’s work often contributes to their sense of meaning
or purpose in life, and to their self-identity, and through this
Beyond physical health and safety
influences their enjoyment of and satisfaction with life, and
their overall wellbeing (Ryff and Singer, 1998; Stiglitz, 2002;
Martin, 2004; McCarthy et al., 2011). Workplace culture,
work-related self-efficacy and work-related self-identity all
have important effects on a person’s wellbeing and their
ability to cope with workplace stressors. Wellbeing is typically
higher for those who feel fairly and respectfully treated by
their managers and peers, who have trusting relationships in
their workplace, who feel supported, valued, appreciated or
recognized and feel a sense of accomplishment and confidence
in their work (Schaubroeck and Merrit, 1997; Stiglitz, 2002;
Martin, 2004; McCarthy et al., 2011; Schirmer et al., 2011).
We found no studies that explicitly examined identity in the
forest industry, although Schirmer et al. (2011) acknowledge
the potential for changes in the forest industry to influence
worker identity.
External influences
The issues discussed earlier are largely produced by working
conditions within the workplace. However, many factors that
influence the forest industry are external to the individual workplace but have effects on those workplaces and hence potential
to influence worker wellbeing. This aspect of worker wellbeing
remains relatively unexplored, but a small number of studies in
the forest industry suggest external influences have potential
to profoundly influence worker wellbeing (e.g. Schirmer et al.,
2011).
External influences range from changes in markets for forest industry products to changes in government regulations governing
how the industry can operate. It is not possible to examine all of
these in a single study. We chose to focus on one external influence
that is common to the forest industry in many countries: public
contention about the industry. The forest industry in Australia
and internationally is commonly the subject of social conflict,
something that sets the forest industry apart from many other industries (Hillier, 2003; Lane, 2003; Schirmer, 2007; Yasmi et al.,
2009; Mola-Yudego and Gritten, 2010; Affolderback, 2011;
Schirmer, 2013; Dare et al., 2014). This conflict involves public
campaigns criticising parts of the forest industry, with a range of
concerns raised about the ecological, social and economic
impacts of timber harvesting and associated activities, and
conflicts recorded in multiple locations globally (Mola-Yudego
and Gritten, 2010).
This conflict has potential to affect worker wellbeing in many
ways, some of which have been noted in previous studies. Dunk
(1994) argued that social conflict increases stress and job insecurity in the forest industry, through reducing timber resources,
increasing costs of production and consequently reducing employment opportunities. Both Dunk (1994) and Schirmer et al.
(2011) noted that conflict and structural change in the industry
can affect worker’s identity and their self-esteem. Issues such
as stress, job insecurity, changes in identity and self-esteem
are all associated with reduced wellbeing. As with all factors
influencing worker wellbeing, the extent to which contention
surrounding the industry affects wellbeing will depend on a
range of factors, including (but not likely limited to) the nature
of the contention, the level of exposure a worker has to this
conflict as part of their workplace role and the support provided
in the workplace.
Methods
We surveyed Australian forest industry workers, defined as those employed
in jobs associated with the growing, harvesting and processing of timber
into wood or paper products.
Survey design
Survey questions were developed based on a review of international literature on worker wellbeing. The draft survey was piloted by nine forest industry workers and revised based on the results.
Two validated wellbeing measures were used in the survey to gain an
understanding of forest worker wellbeing: a general health measure and
a life satisfaction measure. The survey also asked participants about the
type of work they were involved in, physical risks associated with their
work, work-related injury and disease, formal and informal working conditions and external influences to their workplace. These measures are
described in more detail below and summarized in Table 1.
Wellbeing measures
First, respondents were asked to rate their own general health on a 5-point
scale ranging from 1 (excellent) to 5 (poor), in response to the question ‘how
would you rate your general health?’ This measure is used internationally in
health surveys as part of the SF-36 survey and has been found to have high
validity as a single item measure of general health (DeSalvo et al., 2006).
Second, respondents were asked about their life satisfaction. A common
approach to measuring a person’s subjective wellbeing is to ask how satisfied they are with different aspects of their life. A person’s life satisfaction
has been found in multiple studies to be strongly linked to a range of
health outcomes and is a strong predictor of both mental and physical
health (O’Brien et al., 2012). Respondents were asked a subset of the questions used in the well-validated Personal Wellbeing Index (PWI), also known
as the International Wellbeing Index, used in 46 countries (International
Wellbeing Group, 2013). The PWI scale measures seven domains of satisfaction, asking a person how satisfied they are with their standard of
living, health, what they are achieving in life, relationships, safety, community connectedness and future security. The items are measured on a 0- to
10-point scale, where 0 is ‘completely dissatisfied’ and 10 is ‘completely
satisfied’. The mean score is calculated across the seven items to create
an overall life satisfaction index. In this study, we measured four dimensions from the PWI that consistently contribute to the overall life satisfaction index and also have direct relevance to a person’s workplace:
satisfaction with standard of living; what they are achieving in life, community connectedness and future security.
Work-related injury and disease
To identify the work-related factors likely to be influencing wellbeing, we
first examined workplace injury and disease. We focused on work-related
injury, as it is more readily measured in a survey compared with workrelated disease, which workers may not be as aware of. The survey asked
participants whether they had experienced a work-related injury or illness
in the past 12 months, and the extent to which they were exposed to
known injury and disease risk factors in their workplace in the form of workrelated stress, dangerous equipment, noise or long working hours.
Respondents were also asked whether they had access to counselling
services, physical health checks and flu shots in their workplace.
Formal working conditions
Respondents were asked a range of questions related to their formal
working conditions, meaning the conditions set in their contracts or
required by their workplace. This included questions about their satisfaction
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Survey measure
Abbreviation Survey items
General health rating GENHEALTH
‘How would you rate your general health?’
Life satisfaction
index
LIFESAT
Work-related injury
and disease risk
INJ
Thinking about your own life and personal circumstances, how satisfied are you
with the following?: your life as a whole, your standard of living, what you are
currently achieving in life, feeling part of your community and your present
financial situation
Have you experienced a work-related injury in the past 12 months?
INJRISK
PROV
SCHED
Formal working
conditions
INC
How satisfied are you with the following aspects of your current work?: the
amount of income I receive from my work
AUT
How satisfied are you with the following aspects of your current work?: the
amount of control I have over decisions affecting how I can undertake my
work
How satisfied are you with the following aspects of your current work?: the
balance between my work life and home life
How satisfied are you with the following aspects of your current work?: the
level of job security I have
I feel confident I will still have my job one year from now
WL
SEC1
SEC2
Informal working
conditions
Is your health/wellbeing at risk from any of the following at your workplace?:
the physical conditions at my workplace, the number of hours I work, the
equipment I have to use, the level of noise in the workplace, work-related
stress, the action of environmental protestors, my job overall and other
Does your workplace provide access to any of the following?: physical health
checks (e.g. sun checks and mobility checks), Flu shots, counselling and other
Work schedule (e.g. shift work) and access to counselling/flu shots/physical
health checks
Which of the following best describes your current work schedule?
Response options
Source
5-point scale: excellent, very good,
good, fair or poor
0- to 10-point scale, where 0 is
‘completely dissatisfied’ and 10 is
‘completely satisfied’
DeSalvo et al. (2006)
Yes, no, unsure
Schirmer et al. (2011) –
measures adapted
for this survey
5-point scale: no risk, small risk,
moderate risk, big risk, very big risk
Yes, no, unsure
Regular daytime schedule, regular
evening/night shift, a rotating shift
(changes from days to evenings/
nights) or irregular schedule (your
hours change a lot)
0- to 10-point scale, where 0 is
‘completely dissatisfied’ and 10 is
‘completely satisfied’
Schirmer et al. (2011) –
measures adapted
for this survey
7-point scale, where 1 is ‘strongly
disagree’ and 7 is ‘strongly agree’
SEC3
SEC4
CULT1
The future of my part in the forest, wood and paper industries is highly uncertain
The future of the forest, wood and paper industries in my state is highly uncertain
My ideas are encouraged and listened to by others in the workplace
7-point scale, where 1 is ‘strongly
disagree’ and 7 is ‘strongly agree’
CULT2
I can raise concerns I have about my business or its activities with other
in my workplace
I am encouraged to discuss and examine all possible solutions to problems
when they arise
CULT3
International Wellbeing
Group (2013)
Schirmer et al. (2011) –
measures adapted
for this survey
Forestry
394
Table 1 Summary of measures used in the forest worker wellbeing survey
CULT4
PUB1
In general, the public respect the forest, wood and paper industries
PUB2
PUB3
In general, my local community respects the forest, wood and paper industries
I feel many people view me negatively because I work in the forest, wood and
paper industries
I feel many people view me positively because I work in the forest, wood and
paper industries
The government manages the forest, wood and paper industries well
The government cares about the future of the forest, wood and paper industries
I can trust people in government to look after the interests of the forest, wood
and paper industries
When someone praises the forest, wood and paper industries, it feels like a
personal compliment
When a story in the media criticizes the forest, wood and paper industries,
I take it personally
When someone criticizes the forest, wood and paper industries, it feels like a
personal insult
CULT5
SUPP1
SUPP2
EFF1
EFF2
EFF3
EFF4
ID1
ID2
External influences
PUB4
GOV1
GOV2
GOV3
PERS1
PERS2
PERS3
5-point scale, where 1 is ‘not
attached’ and 5 is ‘very strongly
attached’
7-point scale, where 1 is ‘strongly
disagree’ and 7 is ‘strongly agree’
Schirmer et al. (2011) –
measures adapted
for this survey
395
Beyond physical health and safety
ID3
ID4
ID5
ID6
ID7
In my business/work team, you are expected to do what you are told
without question
I cannot suggest new ideas at work because my workmates would make
fun of me, or criticize me
I have access to support from others within the forest, wood and paper
industries to help me through difficult times
Members of the forest, wood and paper industries help each other out in
difficult times
I do my work well
I feel like I do not have much to offer my workplace
I often feel I am a useless member of my workplace
I often feel I am an effective member of my workplace
I have important things in common with the people I work with
Being in the forest, wood and paper industries often makes me feel a
sense of belonging
I enjoy being part of the forest, wood and paper industries
The forest, wood and paper industries are important
Being part of the forest, wood and paper industries is important to me
I often regret that I work in the forest, wood and paper industries
Level of attachment to the industry
Forestry
with their income, the level of control they have over their work, their work–
life balance and their job security.
Informal working conditions
Respondents were asked about informal workplace conditions, including
workplace culture (feeling fairly and respectfully treated, having trusting
relationships and feeling valued, appreciated and recognized), access to
support within the workplace and the industry, work-related identity (or
how work moulds a person’s self-identity) and work-related efficacy. Workrelated efficacy was defined as a worker’s confidence and ability to carry out
what they set out to do. People with higher levels of work-related efficacy
are argued to have better behavioural and psychological outcomes in
stressful situations (Schaubroeck and Merrit, 1997).
External influences
We examined workers’ exposure to social contention about the industry by
asking (1) whether workers felt the industry was adequately supported by
government, and by the general public, (2) perceptions about the fairness
of decisions made by government about the industry and (3) how
workers personally experienced hearing negative or positive views about
the industry as a whole.
Survey delivery
The survey was conducted online during October 2012 to January 2013,
with participants able to request a paper copy by calling a free phone
number if they preferred. Participants were recruited using two methods:
(1) Managers of forest industry businesses (including state-owned forest
growers) were asked to distribute emails and flyers about the survey
to workers employed in their business, and to other contacts they had
in the forest industry. In total, 103 businesses, employing a total of
3035 workers, agreed to distribute the survey. The businesses included
10 forest management businesses (businesses that grow and manage
trees through to harvesting), 41 contracting businesses (including
harvest and haulage contractors, silvicultural contractors and forestry
consultants) and 55 wood and paper processing businesses (some
businesses undertook more than one of these activities, e.g. forest
management and processing, so these numbers add up to more than
the 103 businesses in total who agreed to distribute the survey). It is
likely not all of these businesses distributed information about the
survey to their workers, and the proportion that did is unknown. Business managers were asked to send up to two reminders about the
survey, as a way of increasing response rate (Schirmer, 2009) and
(2) The survey was promoted in relevant Australian forest industry and
trade news, including the IFA Bulletin (produced by the Institute of Foresters Australia), Australian Forests & Timber Magazine, Timber News,
Australian Timberman, Timber Communities Australia website, The
Log (Australian Forest Contractors Association) and the Canopy
e-newsletter of the Australian Forest Products Association. The
number of forest industry workers that read these publications is not
documented, so the total number of people reached via this advertising
is unknown.
The survey was targeted at workers in the states of New South Wales and
Victoria, the two states with the largest employment in the forest industry,
but was open to any forest industry worker in Australia.
Survey response
A total of 310 valid survey responses were received. A further 34 partial
responses were received but were not included in analysis of the results.
In total, 46 per cent of respondents were from the state of New South
Wales, 44.3 per cent from Victoria and the remainder from South Australia
396
(5 per cent), Tasmania (2.3 per cent), Western Australia (1 per cent),
Queensland (1 per cent) and the Australian Capital Territory (0.3 per cent)
(n ¼ 297).
Because the forest industry includes a diversity of occupations, survey
respondents were classified into four types of jobs within the industry,
each of which involves different tasks and differing exposure to wellbeing
risks:
† Forest managers: growers/managers of forests or plantations (including
most professional foresters, as well as some forest operations supervisors) (51.2 per cent of respondents),
† Contractors: harvest, haulage and roading contractors (12.2 per cent of
respondents),
† Wood- and paper-manufacturing workers: workers employed in wood
and paper processing (28.1 per cent of respondents) and
† Other workers: other jobs principally involving expert consultants, people
working in nurseries, people working in forest policy and regulatory agencies and contractors engaged in silvicultural management (referred to as
‘other’ workers) (8.6 per cent of respondents).
The survey was not sent to a known sample of people, and therefore, it is not
appropriate to estimate a response rate to the survey. This is consistent with
increasing recognition of the lack of robustness of response rates as a
measure of the quality or representativeness of a survey (Johnson and
Wislar, 2012). There is increasing recognition that the degree to which
sampled respondents are different from the survey population as a whole
is more important in evaluating the representativeness of a survey than
response rates. Given this, we assess the representativeness of responses
to the survey by comparing respondents to known characteristics of the
Australian forest industry workforce from the 2011 ‘Australian Census of
Population and Housing’ and ABARES, 2014 ‘Australia’s forests at a
glance’ (Table 2). The figures reported by ABARES (2014) in Table 2 do not
exactly match the sectors defined in this study, as the national statistics
are not clear-cut and fail to record some industry sectors. Therefore, the
comparison between our study and the statistics on employment in different industry sectors reported in ABARES (2014) is indicative only. The limitations of ABARES’ industry sector figures are discussed in detail in Schirmer
et al. (2013b).
Overall, the comparisons suggest that our survey responses were typical
of people working in the industry, with two principal exceptions. First,
respondents had on average completed a higher level of education than
is typical of the workforce as a whole, a common bias in surveys. Second,
the survey respondents included a smaller proportion of wood- and papermanufacturing workers than the industry as a whole. This was in part deliberate: to enable comparison of wellbeing of workers in different sectors, it
was necessary to over-sample forest managers and contractors, as they represent a relatively small proportion of the workforce. To ensure the difference in ratios of types of workers did not result in biased analysis, our
analysis explicitly compared these groups at all stages to identify any differences between them.
We also considered whether our sample might be biased towards those
with a strong interest in wellbeing issues. We assessed this by comparing
the mean general health score of our respondents with that of forest industry workers in the Household, Income and Labour Dynamics in Australia
(HILDA) survey, wave 11. HILDA is a large national survey conducted annually, and each year includes a small number of forest industry workers.
HILDA results are unlikely to be biased bya particular interest in forest industry wellbeing. HILDA survey participants employed in wood product manufacturing had an average general health score of 2.6 when asked to rate
their general health on a 5-point scale ranging from 1 (excellent) to 5
(poor) (n ¼ 34), and those in pulp and paper manufacturing a score of 2.4
(n ¼ 48). In our survey, which analysed wood- and paper-manufacturing
workers as a single category, comparable workers scored a mean of 2.5,
suggesting our sample was not biased towards those with particularly
high or low general health.
Beyond physical health and safety
Table 2 Characteristics of forest industry workers who completed the survey
Information
Respondent characteristics
Australian forest industry characteristics
Gender
76.7% male
23.3% female (n ¼ 294)
Median age range: 40 –44 years old (n ¼ 296)
81.7% male1
18.3% female1
Median age range: 45–49 (40 –44 years was the
second most common age group)1
Has post-school qualification: 50.9%1
15.6% forest managers/growers, harvest contractors
and silvicultural contractors2
Age
Formal education
Industry sectors
1
2
Has post-school qualification: 71.1% (n ¼ 293)
72.0% forest managers/growers, contractors (including harvest,
haulage and roading contractors) and ‘others’ (including
silvicultural services)
28.0% wood- and paper-manufacturing sector
84.4% wood- and paper-manufacturing sector2
Australian Bureau of Statistics. 2011 ‘Australian Census of Population and Housing’. http://www.abs.gov.au/census.
ABARES, 2014 Australia’s forests at a glance 2014: with data to 2012–2013, Australia.
Data analysis
Our analysis included initial exploration of the data followed by the development of scales measuring key aspects of work-related wellbeing, exploration of bivariate relationships between these scales and the overall
wellbeing of workers, and regression analysis to identify which of these
aspects had the strongest relationship to the overall wellbeing of workers.
Microsoft Excelw and the Statistical Package for Social Sciencesw (SPSS)
Version 21 were used for all data analysis.
The extent of missing data was assessed for the 310 valid surveys
received. Across all variables, the proportion of missing data ranged from
1.3 per cent to 8.0 per cent; for the majority of variables, ,5 per cent of
data were missing. Given the low level of missing data, we decided not to
impute missing data (Schafer, 1999).
Our survey included several different items measuring work-related
dimensions that are thought to influence wellbeing. Many of these items
were measuring the same underlying construct. Principal components analysis (PCA) was used to better understand the underlying structure of the set
of individual items and to develop scales from them.
Thirty-two items relating to working conditions, workplace culture and
external influences were subjected to PCA using the direct oblimin rotation
in SPSS. Prior to performing PCA, the suitability of data for PCAwas assessed.
Inspection of the correlation matrix identified that the majority of coefficients were 0.3 or above, with no coefficients of .0.8. This indicates that
none of the items were highly inter-correlated. However, as the items are
related, it is appropriate to allow the items to correlate in the analysis.
Therefore, an oblique rotation (direct oblimin) was used rather than an orthogonal rotation, which would assume that the underlying constructs are
completely independent (Tabachnick and Fidell, 2007). The Kaiser– Meyer –
Oklin value was 0.817, exceeding the recommended minimum value of 0.6
(Kaiser, 1970), and the Bartlett’s Test of Sphericity (Bartlett, 1954) reached
statistical significance of 0.000, supporting the factorability of the correlation matrix. PCA revealed the presence of eight components with eigenvalues exceeding 1. On inspection of the component correlation matrix, we
observed the strength of relationship between components ranged from
20.29 to 0.32, indicating the components were not highly correlated with
each other. The PCA was highly robust, as indicated by the key fit statistics
as recommended by Bartlett (1954), Kaiser (1970), Hutcheson and Sofroniuo (1999) and Field (2013). Results of the PCA and details of the newly
formed scales are presented in Table 3.
These scales were used in further analysis to identify any correlations
between work-related factors and forest worker wellbeing. In addition to
these scales, individual items relating to income, work autonomy and
work– life balance were also used for analysis.
The two wellbeing measures used in our survey are existing validated
scales well published and used elsewhere and were therefore not subjected
to PCA.
We then explored relationships between each scale and worker wellbeing using bivariate analysis. As most data typically used ordinal measures, Spearman’s rho (rs) was used to identify any correlations between
variables where one or both were ordinal; Kruskal–Wallis tests (H) were
used to identify significant differences between ordinal and continuous
variables for two or more independent groups and Pearson chi-square
tests (X 2) were used to identify significant differences between two
nominal data sets. When a bivariate test was significant, data were
further explored by observing the descriptive statistics to identify where
the differences were.
Following PCA and further bivariate analysis, we used multiple regression analysis to identify which work-related factors explained the greatest
amount of variance in workers’ overall life satisfaction. Preliminary analysis
found no violations of the assumptions of normality, linearity, homoscedasticity or multicollinearity in the variables included in the regression analysis. VIF values ranged from 1.17 to 1.97, and tolerances ranged from 0.51
to 0.86, well outside the thresholds of .10 and ,0.10, respectively, considered indicative of likely multicollinearity (O’brien, 2007). Multiple regression
analysis tested whether income, job autonomy, work–life balance, job security, work-related efficacy, workplace culture, feelings of support, workrelated identity, feelings about public perceptions about the industry, personal impacts of the industry’s reputation and views about government
management predicted a worker’s life satisfaction. The life satisfaction
measure was chosen as the dependent variable over general health as it
is linked to a range of health outcomes and is a strong predictor of both
mental and physical health (O’Brien et al., 2012).
As the analysis was of a cross-sectional study of workers at a single point
in time, the analyses we present demonstrate associations between workrelated factors and wellbeing, but not causal directions. In this paper, we
report all associations identified and interpret potential causal directions
based on referring to the broader literature on the effects of workplaces
on worker wellbeing. However, longitudinal studies are needed to better
demonstrate the validity of many of these hypothesized causal relationships. This limitation is important to recognize throughout presentation of
our findings.
Results
We first explored whether workers in different parts of the industry
report different wellbeing. Second, we examined whether specific
workplace conditions were associated with differing levels of wellbeing, focusing on working conditions, workplace culture, workrelated identity, feelings of support and work-related efficacy.
Third, we examined whether workers who were affected by external influences on the industry reported different wellbeing.
397
Forestry
Table 3 Factor analysis and scale development
Component Scale name
1
2
3
4
5
6
7
8
Work-related
identity
External influence –
Public perception
Workplace culture
Workplace condition
– job security
External influence –
government
management
Work-related
efficacy
External influence –
personal impacts
Support
Variance Component correlation3
explained
1
2
3
Individual items
forming the scale
(see Table 1 for
abbreviations)
Component
eigenvalue
ID1 to 6
ID71
PUB1 to 4
6.882
21.5%
1.000
0.094 20.270
0.080 20.005
0.261
0.291
0.323
3.577
11.2%
0.094
1.000 20.071
0.173
0.147 20.003
0.106
CULT1 to 5
SEC12
SEC2 to 4
GOV1 to 3
2.320
1.947
7.3%
6.1%
20.270 20.071 1.000 20.220 20.046 20.291 20.051 20.173
0.080 0.173 20.220 1.000 0.147 0.107 20.007 0.114
1.830
5.7%
20.005
0.132 20.046
0.147
1.000
0.008 20.111
0.148
EFF1 to 4
1.596
5.0%
0.261
0.147 20.291
0.107
0.008
1.000
0.095
0.029
PERS1 to 3
1.464
4.6%
0.291 20.003 20.051 20.007 20.111
0.095
1.000
0.122
SUPP1 to 2
1.115
3.5%
0.323
0.029
0.122
1.000
0.106 20.173
4
5
0.114
6
0.132
0.148
7
8
1
Scale adjusted to a 7-point scale when combined with other items.
Scale adjusted to a 7-point scale when combined with other items.
3
These figures show the correlation between factors 1 and 8, using Pearson’s R.
Extraction method: Principal Component Analysis.
Rotation method: Oblimin with Kaiser Normalisation.
2
Wellbeing of forest industry workers: does job type matter?
Table 4 compares the wellbeing of forest industry workers in the different sectors using the general health and life satisfaction measures. Where data are available, we compare our results with the
Australian workforce as a whole.
People in different industrysectors reported significantly different
general health (p ¼ 0.002, n ¼ 286), with the poorest health scores
reported by wood- and paper-manufacturing workers (mean score
2.5) and harvest/haulage contractors (2.4) (Table 4). The average
self-reported health of employed Australians in HILDA was 2.4, suggesting that in some parts of the forest industry workforce – namely,
forest management – general health of workers is better than that is
typical for Australian workers, whereas in others it is comparable.
Respondents’ life satisfaction results were also compared with
those for employed people in the HILDA survey, which includes
three of the four items we asked on life satisfaction. To enable
direct comparison with HILDA in Table 4, we calculated overall wellbeing using the same items used in the HILDA survey.
Forest industry workers of all types had a lower mean score on
the item ‘satisfaction with life in general’ than the average for
the Australian workforce, with similar patterns on most other satisfaction items. This suggests that forest industry workers have
lower wellbeing overall than the Australian workforce. However,
as the questions in HILDA are asked in a different survey context,
it is also possible that the questions answered in our survey prior
to the wellbeing question had a priming effect. This means participants in our study may have responded differently to the wellbeing
questions than would have been the case if they had been asked
the questions identically to the HILDA survey. Further examination
398
of our data suggests that it is unlikely the priming effect explains all
the difference, as the scores for some forest industry sectors are
similar to the average for the Australian working population,
whereas the scores for others are lower.
Despite this uncertainty over the validity of directly comparing
the life satisfaction of forest industry workers with the broader Australian workforce, it is still valid to compare the difference in life satisfaction reported by workers in different sectors of the forest
industry in our study. Wood- and paper-manufacturing workers
reported the lowest satisfaction with all dimensions of their life
except one (feeling part of the community). Satisfaction with
standard of living was significantly higher for forest managers
compared with others (p ¼ 0.013, n ¼ 293), whereas harvest/
haulage contractors reported higher overall life satisfaction than
other workers (p ¼ 0.045, n ¼ 294) (Table 4).
The following sections of this paper explore how formal and
informal working conditions and external influences affect forest
worker wellbeing. The general health and life satisfaction
measures underpin these analyses.
Work-related injury and disease
In total, 11.4 per cent of survey respondents had experienced a
work-related injury in the past 12 months (n ¼ 308). Injury rates
were highest in the wood- and paper-manufacturing sector
(16.9 per cent, n ¼ 83), followed by harvest/haulage contracting
(13.5 per cent, n ¼ 37), other workers (11.5 per cent, n ¼ 26) and
forest management (7.8 per cent, n ¼ 153). The rate of injury for
all sectors was higher than the average injury rate of 5.8 per cent
Beyond physical health and safety
Table 4 Wellbeing of forest industry workers compared with the Australian working population
Health/wellbeing measure
Mean scores1
Bivariate analysis
Whole
forest
industry
Forest
Managers
Contractors
Wood-/papermanufacturing
workers
Other
workers
Australian
working
population2
Difference between
industry sectors3
(H, p, n)4
Rating of general health5
2.2
n ¼ 286
2.1
n ¼ 147
2.4
n ¼ 36
2.5
n ¼ 78
2.1
n ¼ 25
2.4
n ¼ 9743
15.036**, 0.002,
286
Satisfaction with your life as a whole6
7.41
n ¼ 294
7.85
n ¼ 294
7.08
n ¼ 293
6.49
n ¼ 294
6.59
n ¼ 294
6.83
n ¼ 294
7.55
n ¼ 152
8.09
n ¼ 152
7.24
n ¼ 152
6.49
n ¼ 152
6.98
n ¼ 152
7.00n ¼ 152
7.83
n ¼ 36
8.00
n ¼ 36
7.56
n ¼ 36
6.89
n ¼ 36
6.44
n ¼ 36
7.06
n ¼ 36
7.03
n ¼ 80
7.39
n ¼ 80
6.67
n ¼ 79
6.38
n ¼ 80
5.74
n ¼ 80
6.38
n ¼ 80
7.24
n ¼ 25
7.68
n ¼ 25
6.72
n ¼ 25
6.36
n ¼ 25
7.12
n ¼ 25
6.88
n ¼ 25
7.9
n ¼ 11 233
Not asked in
HILDA
Not asked in
HILDA
6.8
n ¼ 11 233
6.6
n ¼ 11 233
7.1
n ¼ 11 233
5.179, 0.159, 293
Satisfaction with your standard of living6
Satisfaction with what you are currently
achieving in life6
Satisfaction with feeling part of your
community6
Satisfaction with your present financial
situation6
Overall life satisfaction score7
10.717*, 0.013, 293
6.014, 0.111, 293
1.121, 0.772, 293
15.120**, 0.002,
293
8.031*, 0.045, 294
1
Average score across all survey respondents.
Data source from The HILDA survey, wave 11.0.
3
The industry sectors compared were as follows: (1) growers/managers of forests or plantations, (2) harvest, haulage and roading, (3) wood- and papermanufacturing workers and (4) other workers (principally consultants, nursery workers, forest policy and regulatory agency workers and contractors
engaged in silvicultural activities).
4
Kruskal– Wallis H statistic (H), level of statistical significance (p) and number of responses (n).
5
Measured on a scale of 1 –5, where 1 ¼ excellent, 2 ¼ very good, 3 ¼ good, 4 ¼ fair and 5 ¼ poor.
6
Measured on a scale of 0 –10, where 0 is ‘completely dissatisfied’ and 10 is ‘completely satisfied’.
7
The overall life satisfaction score was calculated as the average of a respondent’s score for the following items (all measured 0 –10): (1) satisfaction with
your life as a whole, (2) satisfaction with feeling part of your community and (3) satisfaction.
*Correlation is significant at the 0.05 level.
**Correlation is significant at the 0.01 level.
2
across the Australian workforce in 2009–2010 (Safe Work Australia,
2012). The most common work-related injuries reported by survey
respondents were lower back injuries, strains and sprains, and
cuts and open wounds, particularly to hands and fingers. This is
consistent with typical injuries in (1) agriculture, forestry and
fishing and (2) manufacturing sectors more broadly (Safe Work
Australia, 2012).
Figures recorded by Safe Work Australia include any injury,
illness or disease which first occurred in the 12 months prior to
their survey, where a person suffered either physically or mentally
from a condition that has arisen out of, or in the course of, employment. These criteria are broadly similar to the question asked in our
survey, although we specified less about when and how an injury
should have occurred to be considered a work-related injury compared with the Safe Work Australia definitions. Any measurement
differences are unlikely to be large, suggesting the injury rate for
people working in the forest, wood and paper industries is higher
than the national average.
The majority of respondents indicated having access to counselling services at their workplace (68.7 per cent, n ¼ 310) and
physical health checks (64.7 per cent, n ¼ 309). Fewer (38.2 per
cent) had access to flu shots at their workplace (n ¼ 115). Forest
management workplaces were most likely to offer access to all
of these services whereas contracting businesses typically
offered physical health checks but not counselling or flu shots
and manufacturing workplaces were least likely to offer access to
physical health checks.
Those who worked a rotating shift were significantly more likely
to have experienced a workplace injury in the last 12 months (37.5
per cent) compared with those who worked set, non-rotating hours
(9.2 per cent) (X2 ¼ 14.654, p ¼ 0.005, n ¼ 302). This is consistent
with trends in the broader workforce, where shift workers have
more than twice the injury rates of non-shift workers (Safe Work
Australia, 2012). The majority of those who worked a rotating
shift (93.8 per cent) were wood- and paper-manufacturing
workers. This explains, in part, the high injury rates for this sector
of the forest industry.
When asked about injury and disease risks in the workplace
(Table 5), the greatest health risk identified was work-related
stress, highlighting the importance of considering broader
399
Forestry
400
Table 5 Survey respondents’ exposure to workplace injury and disease risk
Survey item
Mean scores1
Contractors Wood-/papermanufacturing
workers
Other
workers
Difference
between industry
sectors2 (H, p, n)6
Work schedule3
(all sectors)
(H, p, n)6
Overall life
satisfaction4 (all
sectors) (rs, p, n)7
General health5
(all sectors)
(rs, p, n)7
2.20
2.34
n ¼ 303 n ¼ 153
1.97
n ¼ 37
2.14
n ¼ 81
1.88
n ¼ 25
7.005, 0.072, 296
3.285, 0.511,
299
20.166**, 0.005,
288
0.085, 0.154,
281
2.02
n ¼ 306
1.77
n ¼ 304
1.74
n ¼ 304
2.13
n ¼ 154
1.70
n ¼ 152
1.46
n ¼ 153
1.81
n ¼ 37
1.70
n ¼ 37
1.70
n ¼ 37
1.99
n ¼ 83
1.94
n ¼ 83
2.36
n ¼ 83
1.84
n ¼ 25
1.56
n ¼ 25
1.46
n ¼ 24
5.964, 0.113, 299
7.046, 0.133,
302
13.183**, 0.010,
300
26.162**, 0.000,
300
20.215**, 0.000,
291
20.280**, 0.000,
289
20.237**, 0.000,
289
0.094, 0.113,
283
0.193**, 0.001,
281
0.134*, 0.025,
281
2.64
n ¼ 306
2.02
n ¼ 291
2.73
n ¼ 154
1.96
n ¼ 149
2.38
n ¼ 37
2.76
n ¼ 37
2.66
n ¼ 83
1.82
n ¼ 77
2.52
n ¼ 25
1.81
n ¼ 21
4.052, 0.256, 299
5.462, 0.243,
302
0.699, 0.136,
287
20.345**, 0.000,
291
0.003, 0.958, 276
0.169**, 0.004,
283
0.098, 0.109,
268
2.26
2.30
n ¼ 303 n ¼ 152
2.08
n ¼ 37
2.30
n ¼ 82
2.08
n ¼ 25
20246, 0.523, 296
7.899, 0.095,
299
20.258**, 0.000,
288
0.171**, 0.004,
280
All
sectors
Health and wellbeing is at risk from
the physical conditions at the
work place/in the places they
work8
Health and wellbeing is at risk from
the number of hours they work8
Health and wellbeing is at risk from
the equipment they have to use8
Health and wellbeing is at risk from
the level of noise in the
workplace8
Health and wellbeing is at risk from
work-related stress8
Health and wellbeing is at risk from
the actions of environmental
protestors8
Health and wellbeing is at risk from
their job overall8
1
Bivariate analysis
Forest
managers
6.653, 0.084, 297
44.346**, 0.000,
297
10.881*, 0.012,
284
Average score across all survey respondents.
The industry sectors compared were as follows: (1) growers/managers of forests or plantations, (2) harvest, haulage and roading), (3) wood- and paper-manufacturing workers and (4)
other workers (principally consultants, nursery workers, forest policy and regulatory agency workers and contractors engaged in silvicultural activities).
3
Groups compared were workers with the following work schedules: (1) regular daytime schedule, (2) regular evening/night shift, (3) a rotating shift (changes from days to evenings/nights) or
(4) irregular schedule (your hours change a lot) (see Table 1 for details – ‘SCHED’).
4
Individual life satisfaction items measured on a scale of 0 to 10, where 0 is ‘completely dissatisfied’ and 10 is ‘completely satisfied’ (see Table 1 for details – ‘LIFESAT’). The overall life satisfaction score was calculated by averaging the score for all items.
5
Measured on a scale of 1 –5, where 1 ¼ excellent, 2 ¼ very good, 3 ¼ good, 4 ¼ fair and 5 ¼ poor (see Table 1 for details – ‘GENHEALTH’).
6
Kruskal– Wallis H statistic (H), level of statistical significance (p) and number of responses (n).
7
Spearman’s rho (rs), level of statistical significance (p) and number of responses (n).
8
Measured on a scale of 1 –5, where 1 ¼ no risk, 2 ¼ small risk, 3 ¼ moderate risk, 4 ¼ big risk and 5 ¼ very big risk.
*Correlation is significant at the 0.05 level.
**Correlation is significant at the 0.01 level.
2
Beyond physical health and safety
Table 6 Survey respondents’ workplace conditions and their wellbeing
Workplace condition being
measured1,2
Mean score2
All
sectors
Satisfaction with income
6.37
n ¼ 307
Satisfaction with job autonomy
5.91
n ¼ 310
Satisfaction with work - life balance
6.07
n ¼ 307
Feelings of job/industry security into
3.80
the future
n ¼ 298
Workplace culture
5.48
n ¼ 302
Work-related efficacy
6.06
n ¼ 306
Feelings of support within the industry 4.50
n ¼ 295
Work-related identity
5.60
n ¼ 296
External influence – public
4.1
perceptions
n ¼ 301
External influence – personal impacts 4.79
n ¼ 297
External influence – Government
3.02
management
n ¼ 397
Bivariate analysis (all sectors)
Forest
managers
Contractors Wood-/papermanufacturing
workers
Other
Overall life
workers satisfaction3
(rs, p, n)5
General health4
(rs, p, n)5
6.94
n ¼ 153
6.03
n ¼ 155
6.06
n ¼ 154
3.50
n ¼ 155
5.56
n ¼ 151
6.08
n ¼ 154
4.60
n ¼ 151
6.0
n ¼ 151
3.81
n ¼ 153
4.83
n ¼ 149
3.03
n ¼ 154
6.41
n ¼ 37
6.59
n ¼ 37
6.43
n ¼ 37
3.47
n ¼ 37
5.72
n ¼ 36
6.21
n ¼ 36
4.53
n ¼ 37
6.20
n ¼ 36
4.44
n ¼ 36
5.19
n ¼ 37
3.10
n ¼ 37
6.69
n ¼ 26
6.15
n ¼ 26
6.46
n ¼ 26
3.40
n ¼ 25
5.48
n ¼ 25
6.05
n ¼ 25
4.38
n ¼ 24
5.60
n ¼ 24
3.27
n ¼ 24
4.87
n ¼ 25
2.64
n ¼ 26
0.367**, 0.000, 292
20.199**, 0.001, 284
0.245**, 0.000, 295
20.133*, 0.024, 287
0.357**, 0.000, 293
20.153**, 0.010, 285
0.245**, 0.000, 291
20.065, 0.274, 283
0.359**, 0.000, 288
20.148*, 0.013, 280
0.368**, 0.000, 291
20.123*, 0.039, 283
0.260**, 0.000, 281
20.035, 0.565, 273
0.404**, 0.000, 282
20.098, 0.107, 274
0.149*, 0.011, 287
0.137*, 0.022, 279
0.148*, 0.013, 283
0.002, 0.976, 276
0.074, 0.208, 291
20.074, 0.215, 283
5.25
n ¼ 84
5.38
n ¼ 85
5.87
n ¼ 83
3.79
n ¼ 80
5.27
n ¼ 84
5.95
n ¼ 84
4.35
n ¼ 77
5.60
n ¼ 79
4.71
n ¼ 82
4.55
n ¼ 80
3.13
n ¼ 82
1
See Tables 1 –3 for description of how each of the variables below was measured.
Average score across all survey respondents.
3
Individual life satisfaction items measured on a scale of 0 – 10, where 0 is ‘completely dissatisfied’ and 10 is ‘completely satisfied’ (see Table 1 for details –
‘LIFESAT’). The overall life satisfaction score was calculated by averaging the score for all items.
4
Measured on a scale of 1 –5, where 1 ¼ excellent, 2 ¼ very good, 3 ¼ good, 4 ¼ fair and 5 ¼ poor (see Table 1 for details – ‘GENHEALTH’).
5
Spearman’s rho (rs), level of statistical significance (p) and number of responses (n).
*Correlation is significant at the 0.05 level.
**Correlation is significant at the 0.01 level.
2
wellbeing in addition to specific injury risk factors such as exposure
to noise or risky equipment.
Some workplace injury and disease risks also varied depending
on the sector people worked in. Noise risk was higher in woodand paper-manufacturing than other sectors of the industry
(p ¼ 0.000, n ¼ 297), and risk associated with environmental protestors was higher for harvest/haulage contractors than other
sectors (p ¼ 0.012, n ¼ 284). These correlations are not overly
surprising, given that manufacturing workers are regularly
exposed to noisy machinery, and environmental protests are
more likely to focus on forest stands where timber harvest is occurring, thus resulting in interaction principally with harvest/
haulage contractors.
All injury and disease risks were significantly correlated with a
worker’s life satisfaction, except for risk associated with the
actions of environmental protestors. The majority were also correlated with respondents’ general health. In general, the more
workers felt they were exposed to risk in their work, the lower the
life satisfaction and general health they reported (Table 5).
Formal working conditions: income, work hours,
job autonomy and job security
Consistent with broader literature, factors such as job autonomy,
work –life balance and satisfaction with income were strongly
and significantly correlated with wellbeing (both life satisfaction
and general health). In general, workers who felt they had more
control over their work, reported better work –life balance and
were more satisfied with their income, also reported higher life satisfaction and general health. Job security was significantly and
positively correlated with life satisfaction, but not with general
health (Table 6).
When income, job autonomy, work– life balance and job
security were compared across the industry sectors (forest managers, contractors, wood- and paper-manufacturers and ‘other’
workers), forest managers were most likely to be satisfied with
their income, contractors were slightly more satisfied with their
job autonomy than the other industry sectors, ‘other’ workers
were most satisfied with their work –life balance and wood- and
401
Forestry
paper-manufacturing workers felt more secure in their jobs than
those working in other industry sectors.
Table 7 Predictors of life satisfaction in forest workers: multiple
regression results
Informal working conditions: workplace culture,
work-related efficacy and identity
Variable
Our results suggest that workplaces with a positive culture, where
workers feel confident to express their views, also have workers
with higher wellbeing (Table 6). Workplace culture was significantly
and positively correlated with both life satisfaction and general
health, with workers who reported more positive workplace
culture also typically reporting more positive life satisfaction and
general health. Wood- and paper-manufacturing workers reported
the lowest scores for workplace culture compared with forest managers, contractors and ‘other’ workers.
Access to support from others in the workplace was also important: workers who felt supported were significantly more likely to
report higher levels of life satisfaction, although support levels
were not correlated with general health. Forest managers were
more likely to feel supported in their workplace compared with contractors, wood- and paper-manufacturing workers and ‘other’
workers. Wood- and paper-manufacturing workers felt least
supported.
Workers who reported higher work-related efficacy reported
significantly higher life satisfaction and general health than
those with lower work-related efficacy. Contractors reported
higher levels of work-related efficacy than forest managers,
wood- and paper-manufacturing workers and ‘other’ workers,
whereas wood- and paper-manufacturing workers reported the
lowest levels of work-related efficacy.
Workers who had a positive work-related social identity were
significantly more likely to report higher levels of life satisfaction,
but not general health. Contractors reported stronger and more
positive work-related social identity compared with forest managers, wood- and paper-manufacturing workers and ‘other’
workers. Wood- and paper-manufacturing workers and ‘other’
workers reported less-strong and less-positive work-related
social identity compared with the other industry sectors.
External influences
Those who reported higher levels of support for the industry by the
general public and local community also typically reported higher
general health and life satisfaction, whereas personal impacts of
the industry’s reputation were only correlated with life satisfaction.
Government management and fairness of decisions made about
the industry were not correlated with either wellbeing measure.
‘Other’ workers felt lower levels of support from the public and
from the government than forest managers, contractors and
wood- and paper-manufacturing workers. Contractors indicated
the highest levels of personal impact when the industry is praised
or criticized compared with the other industry sectors (Table 6).
Regression analysis
The bivariate data analysis presented thus far suggested that a
wide range of work-related factors may influence forest worker
wellbeing. Regression analysis was used to further examine
which factors were most influential. The variables included in the
analysis (Table 7) explained 40.2 per cent of the variability in life
402
B
Std Err B b
Work–life balance
0.127 0.040
Income
0.137 0.043
Work-related identity
0.298 0.129
Workplace culture
0.230 0.104
Job security
0.105 0.069
Work-related efficacy
0.155 0.117
Government
0.068 0.065
management
Personal impact
0.058 0.064
Public perception
0.026 0.078
Job autonomy
20.007 0.039
Support
0.010 0.074
t
0.204
0.207
0.159
0.160
0.090
0.080
0.058
Significance
3.196
3.145
2.314
2.208
1.531
1.317
1.047
0.002**
0.002**
0.022*
0.028*
0.127
0.189
0.296
0.051
0.909 0.364
0.019
0.331 0.741
20.012 20.175 0.861
0.008
0.130 0.897
*p , 0.05; **p , 0.01.
satisfaction scores, F(11,95) ¼ 13.821, p ¼ 0.000, R 2 ¼ 0.402.
Those that added statistically significantly to the prediction (p ,
0.05) were work –life balance, income, work-related identity and
workplace culture (Table 7). Those that did not add significantly
to the prediction were job security, work-related efficacy, job autonomy, feelings of support, feelings about public perceptions
about the industry, personal impacts of the industry’s reputation
and views about government management.
Discussion
There is a large gap in understanding of how workplace conditions
influence the wellbeing of forest industry workers. While our study
has limitations, such as a bias in our survey sample towards more
highly educated workers or those more interested in wellbeing
issues, it nevertheless begins to address this gap, identifying
whether and when various workplace conditions are associated
with measurable differences in the wellbeing of Australian forest
industry workers.
The industry continues to have higher than average injury rates,
confirming the importance of continuing a strong emphasis on
physical health and safety of workers. Our findings also show
that other workplace conditions are important to the broader wellbeing of workers. Improving wellbeing in the industry requires a
focus on job types that appear to have higher wellbeing risk, and
on targeting the work-related factors most strongly associated
with variation in worker wellbeing.
There is a large gap in reliable, consistently reported, and up to
date global statistics on forest industry risks and health incidents,
and even less so on broader wellbeing issues within the industry.
As such, we cannot estimate how applicable the results of this Australian study are to other regions around the world. We believe that
the findings are likely to have highest relevance to regions such as
North America, Europe and New Zealand, in which effective governance and regulations ensures basic physical health and safety
needs are addressed and workers have a reasonable income, and
in which there are similarly mechanized and technologically
advanced forest industries. They are also likely to have relevance
Beyond physical health and safety
in other regions, but in some countries, cultural differences or lack
of basic regulatory oversight will likely mean that other factors such
as physical safety, workplace conditions and pay rates may be
more important to a worker’s wellbeing than the factors identified
in this study. Further work is needed to better identify when and
how much different work-related factors influence wellbeing in
different contexts.
Job type matters: wellbeing risks in different forest
industry sectors
Our findings highlight substantial variation in the wellbeing risks
that exist in different parts of the Australian forest industry. They
suggest a need to focus health and wellbeing programmes to
workers in the wood- and paper-manufacturing sector in particular, who reported lower levels of wellbeing compared with those
working in other parts of the forest industry and had higher injury
rates, greater exposure to a number of wellbeing risk factors and
poorer formal and informal working conditions.
Workers in other industry sectors have fewer and more specific
workplace wellbeing risks. Those working in forest management
were more exposed to wellbeing risk in the form of feeling poorly
perceived by those outside the industry. They were also less connected to their community, suggesting reduced access to social
capital, which is important to a person’s wellbeing (Helliwell and
Putnam, 2004; Schirmer et al., 2013a). While wellbeing is already
relatively strong for most forest managers, this suggests improving
wellbeing in the workplace could be achieved through providing
training in strategies for coping with negative reactions to the
forest industry by external stakeholders and working conditions
that facilitate and support the building of community connections.
While contractors reported higher levels of satisfaction with
most workplace conditions that influence wellbeing, they were
less likely to be satisfied with their job security compared with
forest managers, wood- and paper-manufacturing workers and
‘other’ workers, providing one potential avenue for improving workrelated wellbeing for this group.
Further work is needed to identify how the structure of the forest
industry influences worker health and wellbeing, for example,
whether the wellbeing of those in different jobs varies in different
ways depending on how relationships between groups such as
forest managers and contractors are structured.
Supporting wellbeing: addressing different types
of wellbeing risks
Physical health and safety remains an essential focus in the forest
industry in Australia. Forest industry workers reported higher rates
of injury than the national workforce average. In particular, injury
rates were significantly higher for rotating shift workers compared
with regular shift workers, consistent with conditions in the broader
workforce (Safe Work Australia, 2012). Rotating shifts, as well as
long working hours, can have detrimental effects on worker wellbeing, both physically and psychologically (Sparks et al., 2001).
This suggests a need to identify options for addressing the
greater injury risk presented by rotating shift work in the forest industry, including whether it is possible to design shifts in a more
optimal way to reduce injury rates.
While physical injury and disease are significant wellbeing
risks, many other workplace conditions can influence wellbeing.
Workplaces that focus solely on physical safety are missing opportunities to address other factors that can potentially undermine
the effectiveness of safety measures put in place. For example, in
our study, workers were more likely to identify being exposed to
work-related stress than to risk of physical injury, suggesting a
need to focus on addressing sources of workplace stress. Stress
can be a consequence of multiple work-related factors, and
further work is needed to identify common sources of stress in
forest industry workplaces. Investing in stress management programmes has been promoted for some decades in the broader
worker wellbeing literature as a way of improving worker wellbeing:
recent metareviews have found that there is growing evidence for
the effectiveness of particular types of workplace intervention
programmes that address stress, ranging from teaching skills in
self-management to relaxation programmes (Murphy, 1996; van
derKlink et al., 2001; Giga et al., 2003; Richardson and Rothstein,
2008). Richardson and Rothstein (2008) found that relaxation and
meditation techniques, a popular stress management approach
used because of its simplicity, lower cost and ease of implementation, were not highly effective, with higher effectiveness resulting
from approaches involving cognitive-behavioural interventions (proactive and reactive interventions that encourage workers to take
charge of their negative thoughts, feelings and resulting behaviour,
by altering their thoughts and emotions to become more adaptive).
Our results are consistent with other literature that has found
that improving formal working conditions can have important
effects on worker wellbeing. Improving job security, encouraging
more independent control over individual’s work and enabling
flexibility to achieve positive work –life balance are all strategies
likely to support higher worker wellbeing. This may be just as effective as increasing income, suggesting managers of forestry workplaces have multiple strategies they can use to improve
wellbeing even in times when there are limited possibilities for
growing incomes (Diener and Seligman, 2004; Thompson and
Prottas, 2006; McCarthy et al., 2011). For example, promoting positive work –life balance can give workers a sense of greater control
over their work schedule, including timing of their work, number
of hours they work and the location in which they work, which
has a positive effect on their work –life balance (Kelly et al., 2011).
Informal working conditions, such as the culture of a workplace,
access to support within the workplace, work-related efficacy and
work-related identity, are equally important considerations when
implementing initiatives to improve worker wellbeing. Improving
workplace culture can occur through mechanisms such as promoting a workplace where workers feel confident to express their views,
where workers listen to each other, and in which workers enjoy
working in and feel supported by their workplace. This can be
more challenging for employers compared with changing formal
conditions but is a growing focus of workplace interventions (Eisenberger et al., 1990; Grawitch et al., 2006; Thompson and Prottas,
2006; Huhtala et al., 2011).
External influences on the industry have potential to influence
the wellbeing of workers. However, our findings suggest these
associations are not as strong as those between worker wellbeing
and workplace conditions such as income, job security or workplace culture. While there was some association between external
influences and wellbeing, in our regression analysis, they were not
significant predictors of overall wellbeing. This finding needs
further exploration in future studies. One possible explanation is
that having positive internal workplace conditions (formal and
403
Forestry
informal) is protective of wellbeing of workers: in other words, ensuring the workplace provides positive working conditions may
provide workers with the resources to cope effectively and constructively with negative or challenging external industry influences. If this is the case, it suggests that to support worker
wellbeing during times when external influences present potential
wellbeing threats, workplaces should first focus attention on the
factors that are strongly correlated with wellbeing and that can
be readily influenced by employers, such as working conditions
and workplace culture. In arguing this, we are not suggesting
that workplaces ignore external influences: it is still critical to
engage with external criticism of the industry (Schirmer, 2013).
While this aspect of worker wellbeing remains relatively unexplored, a growing literature is examining how best to support
primary industries to adapt successfully to external influences
such as climate change, government policy change, social conflict
and other factors (e.g. Marshall, 2010). Supporting wellbeing of
workers within the workplace can help workers to respond constructively to industry-wide changes, and to criticism of the industry, which have potential to negatively affect individual workplaces,
and by doing so can support longer term successful adaptation to
change across the industry. This raises a broader point: shifting
focus from injury risk to broader wellbeing has benefits not just
for workers who may experience an improved quality of life.
Workers with greater wellbeing, and with positive and productive
workplace conditions, are more likely to be able to adapt successfully to change; to proactively identify injury and disease risks and
address them before they result in negative outcomes; and are
more likely to remain in their workplace (Stiglitz, 2002; Diener
and Seligman, 2004; Parks and Steelman, 2008; McCarthy et al.,
2011; Schirmer et al., 2011), helping reduce turnover rates of
workers in the industry. A focus on worker wellbeing can therefore
help support successful adaptation to change and innovation
across the forest industry more broadly.
Conclusion
Supporting the wellbeing of forest industry workers has a range of
potential benefits for both workers and the industry as a whole.
While it is well known that the forest industry is one of the most
physically dangerous industries to work in, there is a substantial
gap in understanding about how other working conditions influence broader wellbeing of workers in the forest industry globally.
In our study of Australian forest industry workers, we found that
factors known to influence worker wellbeing in other industries,
particularly injury and disease risks, rotating shift work and
formal and informal working conditions, were strongly and significantly associated with forest worker wellbeing. This highlights the
importance of considering a variety of factors that affect worker
wellbeing and suggests that there are many opportunities
beyond physical health and safety in which individual workplaces,
as well as the industry as a whole, can improve worker wellbeing. In
particular, the Australian forest industry and forest industry workplaces elsewhere with similarities to those in our study could
benefit from focussing on: improvements in rotating shift work
schedules to reduce injury rates; implementation of workplace
stress management initiatives; introduction of training strategies
for coping with negative reactions to the forest industry by external
stakeholders; facilitation and support of building community
404
connections; introducing measures to increase job security; encouraging more positive work –life balance in the workplace and
fostering positive workplace culture where workers feel respected
and listened to.
One forest industry sector in particular, the wood- and papermanufacturing sector, had lower levels of wellbeing, higher rates
of injury and greater exposure to work-related wellbeing risks.
There is a need to focus health and wellbeing programmes to
this sector in particular.
External influences, such as public attitudes to the forest industry,
were also associated with worker wellbeing, but not as strongly as internal workplace conditions (formal or informal). This suggests workplaces may be able to support workers to maintain wellbeing during
times when external influences present wellbeing threats, through
focusing on providing high quality workplaces that enable workers
to develop constructive adaptive strategies. This in turn can
support successful adaptation to change by the industry as a whole.
While this study is focussed on workers in the Australian forest industry, the results are likely to be applicable in similarly mechanized
forest industries around the world. Further work is needed to understand how best to support wellbeing of forest industry workers
beyond physical health and safety, not only in Australia but also globally. Previous studies on forest industry wellbeing have largely
focused on injury risk, an understandable focus given high rates of
injury in the sector, but a broader focus can be used to build wellbeing programmes that better support the workforce, in turn assisting with retaining existing workers and recruiting new workers.
Acknowledgements
The authors thank the forest industry businesses and workers who
participated in the study, often contributing considerable amounts of
their time to do so; their willingness to take part and promote the survey
is greatly appreciated; the forest industry groups and associations that
assisted in the promotion of this survey to its members and the three
anonymous reviewers of this paper. This paper uses unit record data from
the HILDA survey. The HILDA Project was initiated and is funded by the
Australian Government Department of Social Services (DSS) and is
managed by the Melbourne Institute of Applied Economic and Social
Research (Melbourne Institute). The findings and views reported in this
paper, however, are those of the author and should not be attributed to
either DSS or the Melbourne Institute. Ethical clearance was obtained
from the University of Canberra Human Research Ethics Committee,
Project Number 12-141.
Conflict of interest statement
None declared.
Funding
This work was supported by the Cooperative Research Centre for Forestry,
Hobart, Australia.
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