Running head: EXTERNAL AND INTERNAL ENVIRONMENTAL ANALYSIS 1 EXTERNAL AND INTERNAL ENVIRONMENTAL ANALYSIS 2 Perform an external and internal environmental analysis for your Learning Team’s company. Write a summary of about 2,000 words that does the following: · Identifies and analyzes the most important external environmental factor in the remote, industry, and operating environments · Identifies and analyzes the most important internal strengths and weaknesses of your organization: Include an assessment of the organization’s resources. Format your paper consistent with APA guidelines External and Internal Environmental Analysis Your Name: School Name: Date External and Internal Environmental Analysis U.S. Energy Corporation (USEC) provides service in the production and development of natural gas and oil in the United States. Founded in 1966 in Wyoming and focusing on “the development of natural resource assets — acquiring properties on favorable terms, adding value through the application of its expertise in the natural resources sector, and seeking joint venture partners to assist in the development of its projects”. USEC is an independent exploration and production company that has large and diverse prospects through North Dakota and Montana as well as Texas and the Gulf of Mexico. Team B will be identifying and analyzing the external environmental factor in the remote, industry, and operating environments in addition to the internal strengths and weaknesses of USEC.Included will be an assessment of the company’s resources. Remote factors USEC economic remote factors can have a huge effect on the company. The market is one of the largest factors because this can affect the prices of natural gas and oil. The demand for natural gas and oil as well as geothermal, and molybdenum are also another factor.USECkeeps constant trends and motoring on these factors because it can affect the production. The company so far has maintained the financial part of the business without outsourcing for capital. Other economic factors are the contracts in developing and mining and the commodity derivative contracts. The commodity derivative contract, also called “economic hedges” objective is to reduce the effect of price changes on a portion of future oil production; achieve more predictable cash flows in an environment of volatile oil and gas prices, and to manage exposure to commodity price risk. The use of these derivative instruments limits the downside risk of adverse price movements. The commodity derivative prices can effect the changes in the market Demand, pipeline capacity constraints, weather, and the economic activities, and other factors. Social Factors The USEC has built a strong culture that has made it possible for the company “to create opportunities which we can then convert into positive return for shareholders”. The company does not deal directly with the consumer but the company does have stockholders and intermediates bond ...

1. Running head: EXTERNAL AND INTERNAL
ENVIRONMENTAL ANALYSIS
1
EXTERNAL AND INTERNAL ENVIRONMENTAL ANALYSIS
2
Perform an external and internal environmental analysis for
your Learning Team’s company.
Write a summary of about 2,000 words that does the following:
· Identifies and analyzes the most important external
environmental factor in the remote, industry, and operating
environments
· Identifies and analyzes the most important internal strengths
and weaknesses of your organization: Include an assessment of
the organization’s resources.
Format your paper consistent with APA guidelines
External and Internal Environmental Analysis
Your Name:
School Name:
Date
External and Internal Environmental Analysis
U.S. Energy Corporation (USEC) provides service in the
production and development of natural gas and oil in the United
States. Founded in 1966 in Wyoming and focusing on “the
development of natural resource assets — acquiring properties
on favorable terms, adding value through the application of its
expertise in the natural resources sector, and seeking joint

2. venture partners to assist in the development of its projects”.
USEC is an independent exploration and production company
that has large and diverse prospects through North Dakota and
Montana as well as Texas and the Gulf of Mexico. Team B will
be identifying and analyzing the external environmental factor
in the remote, industry, and operating environments in addition
to the internal strengths and weaknesses of USEC.Included will
be an assessment of the company’s resources.
Remote factors
USEC economic remote factors can have a huge effect on the
company. The market is one of the largest factors because this
can affect the prices of natural gas and oil. The demand for
natural gas and oil as well as geothermal, and molybdenum are
also another factor.USECkeeps constant trends and motoring on
these factors because it can affect the production. The company
so far has maintained the financial part of the business without
outsourcing for capital. Other economic factors are the
contracts in developing and mining and the commodity
derivative contracts. The commodity derivative contract, also
called “economic hedges” objective is to reduce the effect of
price changes on a portion of future oil production; achieve
more predictable cash flows in an environment of volatile oil
and gas prices, and to manage exposure to commodity price
risk. The use of these derivative instruments limits the
downside risk of adverse price movements. The commodity
derivative prices can effect the changes in the market
Demand, pipeline capacity constraints, weather, and the
economic activities, and other factors.
Social Factors
The USEC has built a strong culture that has made it possible
for the company “to create opportunities which we can then
convert into positive return for shareholders”. The company
does not deal directly with the consumer but the company does
have stockholders and intermediates bonded by contracts to sell

3. the company’s products. The company as of 2011 has employed
19 full-time well trained professionals dedicated in following
the company’s code of ethics. USECis a company with an
excellent cultural environment, and values. The company has
very low employee turnover with exceptional work ethics.
Political Factors
USEC is affected by political factors.As Pearce and Robison,
2011 states “political factors define the legal and regulatory
parameters within which firms must operate”. USEC is
obligated to follow the rules and regulation of local, state and
federal law requirements. Other laws that apply are NEPA,
Federal Water Pollution Control Act of 1972 and the Clean Air
Act.The company is follows the tax laws for assets and
liabilities, security laws for real estate, and environmental laws
for quality and pollution laws.
Technological and ecological factor
The technological factor involves the technological changes.
USEC has adopted all technological changes, including the
purchase of new equipment and improving machinery to
improve the drilling and the production. The ecological factors
are air pollution, land pollution, and water pollution. These
factors are extremely important because they can affect the
living conditions natural life. The company constructs fully
functional water pipelines on sites that dischargein compliance
with permit requirements. USEC may generate “solid” and
“hazardous” wastes subject to regulation under RCRA and
comparable state statutes, although certain mining and oil and
natural gas exploration and production wastes currently are
exempt from regulation as hazardous wastes under RCRA.
Other operations like drilling that releases restrict substances
into the environment, USEChas remedial work to mitigate
pollution from operations by closing and covering disposal pits,

4. and plugging abandoned wells.
Industry factors
USEC has made a name for itself in the market place with the
oil and gas exploration; includingproduction, geothermal
energy, and molybdenum mining projects. The gas and oil wells
operate along the coast of the Gulf of Mexico and Texas. The
entry into the oil market is highly competitive. USEC competes
with public and private exploration and development companies.
The company also competes with gas and oil operators to
acquire acreage positions. The competitors are small to mid-size
companies that have in-house petroleum exploration and
drilling.Some companies do have the personal resources,
technology, and financialsmuch greater than USEC. The
elevated barriers to entry consist of resource ownership,
government licenses, and a high start-up cost. The oil and gas
industry is a monopolist market.“Theoil industry was prone to a
natural monopoly because of the rarity of the deposits”.
Operating Factors
Execution of a business plan for the company requires the
ability to generate cash to satisfy planned operating
requirements for the next six to eight months.USEC entered into
an agreement as a participant with a private entity of two
counties in Texas. Under the terms of the agreement, USEC will
earn 19.6% net revenue interest in approximately 1,274 net
acres to USEC through a cash payment of $1.7 million. The
promoted amount will cover USEC's portion of the costs for
land, geological, and geophysical work, in addition to all dry
hole costs for an initial test well in each of the seven
prospects. Upon payout of USEC's initial well costs in each
unit, USEC's interest is reduced to 14.7% net revenue
interest. Future infill drilling will be on an as needed basis, and
USEC's interest will be 14.7% net revenue interest.
USEC is incessantly in quest of additional capital through
different alternatives, and particularly with respect to procuring

5. working capital ample for the development of natural gas and
energy projects to cause positive cash flow to sustain
operations. USEC continue to pursue numerous opportunities
their business as it relates to the oil and gas industry. USEC’s
participation with private entities has been mutually favorable
demonstrating a $1.6 million, a 24% increase in revenue;
produced an OE/D from 13.65 producing wells; received an
average of $2.8 million per month from producing wells with an
average operating cost of $431,000 per month (excluding work-
over costs), and production taxes of $294,000 before non-cash
depletion expense, for an average cash flow of $2.1 million per
month from oil and gas production.
USEC’s objective to generate capital for investors includes the
commitment amount for our senior credit facility with Wells
Fargo, NA increased from $75 million to $100 million, and the
borrowing base increased from $28 million to $30 million and
did not have any borrowings under this facility; however,
borrowed $5 million to funddrilling programs. The company
has $7.8 million in cash and cash equivalents on hand with
working capital of $11.8 million. During the quarter
ended March 31, 2012 we recorded a net loss after taxes
of $381,000 as compared to a net loss after taxes of $2.2 million
during the same period of 2011. Currently in 2012, USEC sold
an undivided 75% of undeveloped acres in its Yellowstone and
SE HR Zavanna leasehold interests for $16.7 million and $1.4
million in reimbursed well costs. The Company retained the
remaining 25% interest in the undeveloped acreage and its
original working interest and production in ten gross or two
point three wells.
Internal strength and weakness
To improve the quality of decisions and choices by management
USEC must identify its strengths that arise from the resources
and competencies available.It must also identify its weaknesses

6. that limit its capabilities and creating disadvantages related to
its competition.The following SWOT analysis identifies the
strengths and weaknesses related to the future of USEC.
The most important strengthsare assets including property
acreage and low liabilities. In the First Quarter of 2012
USEChad combined assets worth 148.22 million and total
liabilities worth 21.68 million. This is a huge asset for the
company because minimal risk is assumed with obligation for
liabilities. The company continues to keep its balance sheet
clean by selling acreage at a premium to original cost.
Acquiring favorable assets allow the company to reinvest in
itself by exploring new technologies and other forms of
producing environment friendly efficient energy.
In an interview Keith Larson the CEO of USECsaid, “the
company is looking forward to continuing to work with Crimson
in the Eagle Ford programs to identify the best practices to
economically develop the acreage. Reports 2011 Highlights and
Selected Financial Results. This is an indication of the value of
acreage held by the company as an asset.
USEC’s strength also lies in possible future revenues from
Uranium properties and the royalties held on Uranium claims.
“It currently holds a 4% net profits interest on unpatented
mining claims on Rio Tinto’s Jackpot uranium property located
on Green Mountain in
Wyoming."
USEC’s internal weaknesses include drilling operations,
equipment, and key personnel. Currently the company does not
operate most of its drilling locations and therefore cannot
control the timing of exploration and development efforts,
associated costs, or the production rate of these non-operational
assets. This is challenging for the company because it poses

7. uncertainties with timing, selection of suitable technology and
the required capital expenditures.
The price fluctuation of oil and gas industry can often cause
periodic shortages in equipment. This can severely affect the
activity levels in many operating regions. Williston Basin says,
“These types of shortages can significantly decrease the profit
margin, cash flow and operating results or delay the ability to
drill those wells and conduct those operations that the company
currently has planned and budgeted, causing to miss forecasts
and projections.”
Equipment is essential to any project and USEC must plan
better to secure equipment.It can either buy its own equipment
or enter into contract agreements to use the equipment that will
give the company access to the equipment regardless of the
competition.
The last internal weakness of the USECis that it has limited
technical staff and executive group. Often the company has to
reach out to third party consultants for professional geophysical
and geological advice in oil and gas matters. The loss of any
key employee can force business operations temporarily
immobile and replacements can be difficult because of
competitive hiring of experienced personnel in the minerals
industry. USEC must invest in employee growth and explore
opening its own research department rather than hiring third
party consultants. This may help to strengthen employee
retention and continually grow a qualified staff of personnel.
Assessment of U.S. Energy Corporation resources
In general, a company’s resources are all assets,
capabilities, competencies, organizational processes, attributes,
information, and knowledgeable that is controlled and enabled
to conceive and implement strategies designed to improve its
efficiency and effectiveness. A firm’s attributes that may be
thought of as resources are generally divided into four
categories: financial, physical, human, and organizational

8. capital.
Financial capital is all the different money sources a company
uses to implement strategies. USEC is very financially sound as
described in the operating factors section. In its current
financial situation U.S. Energy Corp. is in a very advantageous
position to continue to support its oil and gas exploration and
investments into other markets. Physical capital that is any non-
human asset-made by humans and used in production. This
usually includes all facilities, equipment, access to raw
materials, and geographic location with an affluence of drilling
ventures and a diverse portfolio of prospects.
Human capital includes all the attributes of experience, training,
intelligence, leadership, and insight of managers and workers
within a corporation. USEC has a wealth of human capital
within its organization. The company is led by Keith Larsen,
the acting CEO. Keith has over 25 years of experience in the
natural resource sector that includes project development in oil
and gas and mineral markets. Mark Larsen, COO, Steven
Youngbauer, Secretary, and Bryon Mowry, Director of
Accounting, round out the rest of the senior management team
that has a total of over 106 years of experience within this
sector.
Organizational capital is a term used to describe the efficiency
with which a business or other type of organization can utilize
resources in a manner, making it possible to implement and
sustain some type of strategy. This process often involves
identifying ways to use existing resources in new ways, or to
allocate a portion of those resources to a new project without
creating hardship for other strategies that must continue to
function, the ability to assess and use organizational capital is
important to the ongoing growth of the company. USEC has a
corporate governance strategymade of several committees that
provide oversight and direction for the company. These
committees include the Audit Committee, to provide direction

9. and review of fiscal matters; the Compensation Committee that
reviews and recommends compensation packages for the
officers of the company; the Executive Committee, and the
Nominating Committee, who considers and recommends who
may be suitable to serve as directors.
Conclusion
USEChas a long-standing reputation as the industry
leader with a long-term orientation. Disciplined management, a
nationally valued source for gas, oil, energy, and operational
excellence in natural resources and environmental cultivating;
USEC is poised to take on the challenges of the world energy
sources. The magnitude of its reserves, strong technology
orientation, and its financial strength gives it a commanding
position in the industry.
For USEC to extend the competitive advantage, a well-balanced
strategy that caters to
the short-term and long-term is critical. USEC recent move of
focusing on seven projects with a private company is well
aligned with its energy outlook and long-term investments in
relatively
high-growth areas of energy sources.
The oil andgas industry is cyclical and its profits are highly
correlated to supply and
demand dynamics and political stability in major oil producing
nations. Nevertheless, improving
global economic growth prospects and ever increasing energy
demand goes well for the company’s profit outlook. With an
nationally diversified business portfolio, the company’s leading
oil and gas reserves, envious financial strength and solid

10. dividend yields, USEC is one of
the best long-term investment plays in the energy sector and
integrated oil and as an industry.
References
2011 Annual Report. (2011). U. S. Energy Corporation.
Retrieved from http://files.shareholder.
com/downloads/USEG/1878530569x0x570365/462A4412-DE21-
4707-8C60
783E5B73822F/US_Energy_Corp_2011_Annual_Report.pdf
Beattie, A. (2010). A history of U. S. Monopolies. Retrieved
from http://www.investopedia.com/
articles/economics/08/hammer-antitrust.asp#axzz1w5KkzVRi
Pearce, J. A., II, Robinson, R. B. (2011). Strategic management:
Formulation, implementation,
and control (12th ed.). Boston, MA: McGraw-Hill/Irwin.
U.S. Energy Corp. Reports 2011 Highlights and Selected
Financial Results. (2012).
Retrievedfromhttp://investor.usnrg.com/releasedetail.cfm?Relea
seID=657392
Working With the Aging: The Case of Francine
Francine is a 70-year-old, Irish Catholic female. She worked for
40 years as a librarian in an institution of higher education and
retired at age
65. Francine has lived alone for the past year, after her partner,
Joan, died of cancer. Joan and Francine had been together for 30
years, and while
Francine personally identifies as a lesbian, she never came

11. out to her family or to her colleagues. When speaking to
all but her closest
confidantes, Francine referred to Joan as her “best friend” or
her “roommate.” Francine’s bereavement was therefore
complicated because she
did not feel she could discuss the true nature of her partnership
with Joan. She felt that there was little recognition from her
family, and even
some of her close associates, of the impact and meaning of
Joan’s death to Francine. There is a history of alcohol abuse in
Francine’s family, and
Francine abused alcohol from late adolescence into her mid-30s.
However, Francine has been in recovery for several decades.
Francine has no
known sexual abuse history and no criminal history.
Francine sought counseling with me for several reasons,
including an ongoing depressed mood, a lack of pleasure or
enjoyment in her life,
and loneliness and isolation since Joan’s death. She also
reported that she had begun to drink again and that while her
drinking was not yet at the
level it had been earlier in her life, she was concerned that she
could return to a dependence upon alcohol. Francine came to
counseling with
several considerable strengths, including a capacity to form
intimate relationships, a successful work history, a history of
having maintained her
sobriety in the past for many years, as well as insight into the
factors that had contributed to her current difficulties.
During our initial meetings, Francine stated that her goals were
to feel less depressed, to reduce or stop drinking, and to feel
less isolated. In
order to ensure that no medical issues were contributing to her
depression symptoms, I referred Francine to her primary care

12. physician for an
evaluation. Francine’s physician
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1 of 1 10/4/2016 10:47 PM
Contributions of Psychological Well-Being and Social
Support to an Integrative Model of Subjective Health
in Later Adulthood
Sophie Guindon & Philippe Cappeliez
Published online: 14 January 2010
# Springer Science+Business Media, LLC 2010
Abstract This study examined the contributions of psychological
well-being and social
support to an integrative model of subjective health among
older adults. Structural
equation modeling was used to test the proposed model of
subjective health which

13. included age, education, physical health problems, functional
status, psychological well-
being and social support. Partial support for the model was
found. Psychological well-
being had both a direct effect on subjective health and an
indirect effect mediated by
physical health problems. Social support had an indirect
association with subjective
health via its effect on psychological well-being. Functional
status had only a weak effect
on subjective health. Longitudinal data at a six-year interval
revealed the same direct and/
or indirect effects of these variables on subjective health. This
study sheds light on how
psychological and social resources are linked with subjective
health in later adulthood.
Keywords Subjective health . Older adults . Psychological well-
being . Social support
Older age is associated with an increase in chronic health
problems and physical disability,
yet the majority of older adults evaluate their health in positive
terms (e.g. Statistical
Report on the Health of Canadians 1999; Canadian Study of
Health and Aging Working
Group 2001). Subjective health is of particular interest in
gerontological research, as it
appears to predict important variables including functional
decline (Grand et al. 1988;
Idler and Kasl 1995; Kaplan et al. 1993; Mor et al. 1994) and
even mortality after other
Ageing Int (2010) 35:38–60
DOI 10.1007/s12126-009-9050-7

14. The Canadian Study of Health and Aging (CSHA) was funded
by the Seniors’ Independence Research
Program, through the National Health Research and
Development Program (NHRDP) of Health Canada
(Project No. 6606-3954-MC[S]). Additional funding was
provided by Pfizer Canada Incorporated through
the Medical Research Council/Pharmaceutical Manufacturers
Association of Canada Health Activity
Program, the NHRDP (Project No. 6603-1417-302 [R]), Bayer
Incorporated, and the British Columbia
Health Research Foundation (BCHRF Projects No. 38 [93-2] &
No. 34 [96-1]). The CSHA was
coordinated through the University of Ottawa and the Division
of Aging and Seniors, Health Canada. The
authors wish to express their appreciation to all staff across
Canada involved in the CSHA.
S. Guindon: P. Cappeliez (*)
School of Psychology, University of Ottawa, Ottawa, ON,
Canada
e-mail: [email protected]
covariant factors including objective indicators of health are
taken into account (for
reviews, see Benyamini and Idler 1999; Idler and Benyamini
1997). These observations
suggest that subjective health encompasses elements that are not
necessarily captured by
objective measures of health and underlines the relevance of
gaining a better
understanding of subjective health. In keeping with this
objective, it appears important
to identify the principal determinants of subjective health, and
in particular, those

15. variables which may affect subjective health positively in later
adulthood.
Consistent with traditional biological and Western views of
health, models of
subjective health have generally focused on physical health and
functional status (e.g.
Johnson and Wolinsky 1993; Liang 1986). Subjective health in
later adulthood is
indeed linked to physical health indicators such as number of
reported health
problems (Pinquart 2001), medications used (Benyamini et al.
2000), as well as
functional disability (Bookwala et al. 2003; Lee and Shinkai
2003; Pinquart 2001).
Sociodemographic factors have also been included in many
studies of the
determinants of subjective health. Review of the literature
reveals that the relationship
between gender and the subjective health of older adults is still
unclear (Gonzalez et
al. 2002; Henchoz et al. 2008; Saevareid et al. 2007; Prus and
Gee 2003). In particular,
several studies have found that the predictors of subjective
health may vary according
to gender (Heikkinen et al. 1997; Leinonen et al. 1999; Prager
et al. 1999; Prus and
Gee 2003; Rodin and McAvay 1992; Schulz et al. 1994). The
effect of age on
subjective health also varies from one study to the next. Results
of two meta-analyses
that included cross-sectional (Roberts 1999) and longitudinal
(Pinquart 2001) studies,
reveal a slight decrease in subjective health with increasing age,
especially among

16. adults 80 years and older. However, these results are interpreted
as the effect of
increasing health problems and functional limitations with age
(Pinquart 2001), which
suggests that age probably does not exert a direct effect on
subjective health, but rather
an indirect one through physical health and functional status.
This hypothesis has
received some empirical support (Orfila et al. 2000). In
addition, studies have shown
rather consistently that higher education is associated with
better subjective health (e.g.
Grundy and Sloggett 2003; Murrell and Meeks 2002; Prus and
Gee 2003; Von dem
Knesebeck et al. 2003; Zimmer and Amornsirisomboon 2001).
As Mossey (1995) pointed out, psychological variables can also
influence
subjective health. She proposed a model of subjective health
that includes mental
health as predictor of subjective health, alongside physical
health, functional status,
and sociodemographic variables. This model proposes that
sociodemographic
variables have a direct effect on subjective health, as well as
indirect effects through
the three other variables. The model further posits that physical
health exerts direct
and indirect effects through mental health and functional status,
which in turn both
have direct effects on subjective health. Finally, in addition to
its direct effect on
subjective health, mental health is hypothesized to have indirect
effects via physical
health and functional status. Regrettably research
simultaneously testing the

17. predictions of Mossey’s model is still lacking.
The criticism of tautological reasoning could be leveled against
this approach to the
determinants of subjective health, as physical and mental health
indicators can be
expected to share much variance with subjective health.
However, closer examination
of these constructs and their measurements reveals that they are
distinct. Specifically,
while more objective indicators of physical health (e.g. health
problems checklist or
Ageing Int (2010) 35:38–60 3939
medical antecedents) and functional status (e.g. ability to
accomplish various activities
of daily living or level of mobility) may indeed influence self-
assessment of health,
clearly the perception of one’s health transcends this
information and indeed is
influenced by a variety of personal factors such as mood, self-
perception/concept,
expectations, and comparisons with others, to name a few.
Regarding psychological
well-being, typical indicators such as life satisfaction,
happiness, self-esteem and
perception of control, are much broader and multi-facetted
concepts than subjective
evaluation of health. At the empirical level also, items referring
to perception of
physical health in typical measures of psychological well-being
constitute only a very
small fraction of the dimensions assessed by such measures.

18. It is important to note that research on the psychological
determinants of
subjective health has largely adopted a pathogenic perspective
by conceptualizing
mental health in terms of level of psychological distress and
thus focusing on factors
that undermine subjective health. Yet it has been reported that
positive indicators of
psychological well-being such as life satisfaction (Lee and
Shinkai 2003), perception
of control (Chipperfield et al. 2004), and self-esteem (Cairney
2000; Starr et al.
2003), are also associated with subjective health. In fact,
emerging evidence suggests
that positive psychological functioning may represent an
important long-term
predictor of subjective health (Benyamini et al. 2000).
However, how these
psychological factors precisely relate to subjective health
remains an open question.
While psychological well-being could directly influence self-
evaluations of health, a
growing body of research suggests that objective indicators of
physical health can also
be positively affected by various dimensions of psychological
well-being, including
positive affect (Fredrickson and Levenson 1998; Ostir et al.
2001a; Ostir et al. 2004;
Ostir et al. 2001b; Xu 2006), perception of control
(Chipperfield et al. 2004), and
healthy global psychological well-being (Keyes 2005). Notably,
experimental
research has demonstrated that the induction of positive
emotions restored

19. cardiovascular physiological activation induced by negative
emotions or stress,
which suggests that mood can exert a direct effect on the risk of
illness (Fredrickson
and Levenson 1998). Thus, it appears likely that psychological
well-being could
indirectly affect subjective health through its effect on objective
physical health.
Although findings have been inconsistent, there is also research
pointing to the
relevance of social support. Overall, positive integration within
diverse social
networks appears to be related to better subjective health (Wu
and Rudkin 2000;
Zunzunegui et al. 2004), with emotional support seemingly the
most beneficial for
subjective health (Zunzunegui et al. 2001). The positive effects
of social support on
subjective health may well be mediated by psychological
variables (Landau and
Litwin 2001; Okamoto and Tanaka 2004).
Despite the above-mentioned evidence, research on subjective
health from a
salutogenic perspective, focusing on factors that promote health
such as positive
psychological functioning and social support (Ryff and Singer
1998; Seligman and
Csikszentmihalyi 2000), has been lacking. Yet, considering the
role of these
variables could help elucidate how older adults can maintain a
favorable subjective
health despite an objective decline of physical health.
Therefore, the main objective
of the present study was to examine how psychological well-

20. being and social
support relate to subjective health among older adults. These
relationships were
tested using the framework of an integrative model of subjective
health that stems
40 Ageing Int (2010) 35:38–60
from Mossey’s model of subjective health (Mossey 1995). The
proposed model
incorporates positive indicators of psychological well-being and
social support as
predictors of subjective health.
On the basis of the literature reviewed above, and as Fig. 1
illustrates, the main
hypothesis was that psychological well-being, operationalized
as general mental
health status, life satisfaction and positive psychological
functioning, would have a
favorable direct effect on subjective health, as well as an
indirect effect through
mediation by physical health problems and functional status.
Given the less consistent
relationship between social support and subjective health, it was
hypothesized that the
effect of social support would be a favorable but indirect one,
mediated by
psychological well-being. The proposed model further posits the
following subsidiary
hypotheses : 1) age would have an indirect unfavorable effect
on subjective health,
mediated by physical health problems and functional status; 2)
education would have

21. direct and indirect favorable effects on subjective health, the
latter mediated by
physical health problems, functional status and psychological
well-being; 3) physical
health problems would have direct and indirect unfavorable
effects on subjective
Physical
Health
Problems
Functional
Status
Illness
err3
1
1
Auditory
Acuity
err2
1
Visual
Acuity
err1
1

22. Mobility
err7
1
IADL
err6
1
PADL
err5
1
1
Psychological
Well-Being
Mental
Health
err10
1
1
Positive

23. Psych. Funct.
err9
1
Life
Satisfaction
err8
1
Age
Subjective
Health
Education
res4
1
res1
1 res21
res3
1
Antece
dents
err4
1

24. Social
Support
Fig. 1 Proposed integrative model of subjective health
Ageing Int (2010) 35:38–60 4141
health, the latter mediated by functional status and
psychological well-being; and 4)
better functional status would have direct and indirect favorable
effects on subjective
health, the latter mediated by psychological well-being.
The test of this model was first performed on cross-sectional
data obtained from a
large representative sample of older adults. The predictive
power of the resulting
model was further tested using longitudinal data from the same
sample. Specifically, it
was hypothesized that the final model resulting from the cross-
sectional analysis
would also significantly predict future subjective health. Since
the research literature is
equivocal regarding gender differences in subjective health,
analyses were performed
on men and women separately in order to elucidate potential
gender differences.
Method
Participants
Data were obtained from the Canadian Study of Health and

25. Aging (CSHA Working
Group 1994), a longitudinal investigation comprising a large
nationally representa-
tive sample of adults over 64 years of age. A randomized
sample of older adults was
created from government health records in all provinces except
Ontario, where
enumeration records were used instead. The Yukon and North–
West Territories were
excluded from the CSHA due to the small number of older
adults inhabiting those
regions. Data collection for the CSHA was divided into three
phases. A total of
9,008 community-dwelling older adults and 1,255 living in
institution participated in
the first phase (CSHA-1) in 1991–1992. The latter underwent a
clinical exam for
assessment of their cognitive functioning, while the former
completed with a
qualified interviewer a standardized interview which included a
cognitive screen, the
Modified Mini-Mental State Examination (3MS; Teng and Chui
1987). Those
presenting possible cognitive impairments were further assessed
for dementia.
Community-dwelling participants who were deemed free of
dementia in CSHA-1
were invited to participate in the second phase (CSHA-2) in
1996–1997. Among the
5,703 participants from CSHA-2 (63.3% of original sample),
5,395 lived in the
community whereas 308 moved to an institutional setting. Only
the community-
dwelling sample from the CSHA-2 was retained for the present
study, given that all
the measures of interest were administered to this sample at that

26. time. Participants
from the CSHA-2 whose scores on the 3MS suggested possible
cognitive problems
were excluded from the present study as they were not required
to respond to all
measures in the interview, resulting in a total of 4,329
participants. Of this sample,
only the English-speaking participants were retained to increase
sample homogeneity.
The resulting sample consisted in 3,599 participants (2,171
women, 1,428 men)
aged between 69 and 105 (M=78.58, SD=5.76). Half of the
participants were
married (50.7%) and 39.8% were widowed. Participants
completed an average of
11.39 years of education (range from 0 to 33; SD=3.45) and
49.3% reported an
annual household income below $30,000. On average, 4
physical health problems
were reported over the past year (range 0 to 13; SD=2.32). From
this sample, a total
of 2,367 participants (1,471 women, 896 men) responded to the
subjective health
measure in the CSHA-3, which took place in 2001–2002. The
cross-sectional
42 Ageing Int (2010) 35:38–60
analyses in the current study are based on the data from CSHA-
2, and the
longitudinal analyses use data collected in CSHA-2 to predict
subjective health
assessed in CSHA-3. To simplify, CSHA-2 and CSHA-3 data

27. are referred to
respectively as Time 1 and Time 2 data in the present study.
More information on the
samples of CSHA-1 and CSHA-2 is available elsewhere
(McDowell et al. 2001).
Measures
Sociodemographic variables They included gender, age, and
years of education.
Subjective health Subjective health was assessed with the
following question:
« How would you say your health is these days? (5 = very good,
4 = pretty good, 3 =
not too good, 2 = poor, 1 = very poor) ». Use of such a single
global question is one of
the most frequent manner of measuring self-rated health, and it
is considered as a
reliable measure of subjective health for older adults. Studies
evaluating subjective
health with five response choices with older participants have
reported good test-retest
reliability, using weighted Kappa statistic (in order to account
for partial agreement
among ordered categories). Indeed, Andresen and colleagues
reported a Kappa
coefficient of 0.67 for adults aged 65 years and older, over a 2-
week interval (Andresen
et al. 2003). Crossley and Kennedy (2002) indicated a Kappa
coefficient of 0.69 for
adults aged 70 and over, for an evaluation performed before and
after another set of
health related questions. Furthermore, criterion validity for such
a measure is
supported by the demonstration of significant graded

28. relationships with health events
in adults of middle and older ages (Wurm et al. 2008).
Physical health problems Physical health problems were
assessed with four
measures. The first comprised a list of 16 health problems
common in old age.
Participants indicated whether or not they had experienced these
problems over the
past year, resulting in a cumulative index of reported health
problems.
A second 4-item measure evaluated reported medical
antecedents (i.e. heart
operation; artery or neck operation; hip replacement; diabetes);
higher scores were
indicative of a greater number of antecedents.
Given that visual and hearing impairments are relevant to
subjective health (Lee
et al. 2005), measures of visual and auditory acuity were
included, in the form of
two questions asking the participants to assess their vision (with
glasses or contacts
if worn) and hearing (with a hearing aid if worn) using a 5-point
response scale (1 =
excellent; 2 = good; 3 = fair; 4 = poor; 5 = incapable of
hearing/seeing); higher
scores reflected poorer auditory and visual acuity.
Functional status Functional status was defined as the capacity
to perform activities of
daily living (ADL) and functional mobility. Questions assessing
the capacity to perform
ADL were from the Older Americans Resources Survey
(Multidimensional functional

29. assessment 1978). Both physical ADL (PADL) and instrumental
ADL (IADL) were
assessed, each with a scale comprising seven items. Participants
indicated whether
they could perform each activity without help, with help, or if it
was impossible for
them to perform the activity. The maximum score for each scale
was 14, thus 28 for
the complete scale, with a higher score reflecting a better
functional status.
Ageing Int (2010) 35:38–60 4343
Significantly elevated correlations (tau = .83, r=.89, p<.001)
were found between
this measure and assessments of functional status by qualified
professionals,
suggesting very good criterion validity. In addition, a very good
inter-rater reliability
has been reported for this measure (.87; α=.001) (Fillenbaum
and Smyer 1981;
George and Fillenbaum 1985). Alpha coefficients of .71 and .78
were respectively
found for the PADL and IADL scales among the sample of the
present study.
Functional mobility was assessed with the Timed Up & Go Test
(TUG; Podsiadlo and
Richardson 1989, 1991). It measures the amount of time needed
for the person to lift
from a chair, walk a distance of 3 m, turn, walk back to the
chair, and sit. The TUG
allows the identification of older adults susceptible to falls with
an 87% degree of
sensitivity and reliability (Shumway-Cook et al. 2000). Elevated

30. correlation
coefficients (r=−.69 and −.70) were found between the TUG and
ADL scales among
CSHA participants, suggesting satisfactory construct validity
(Rockwood et al. 2000).
Psychological well-being Indicators of psychological well-being
included life
satisfaction, general mental health, and positive psychological
functioning. Life
statisfaction was assessed with an 11-item adaptation of the
Terrible-Delightful Scales
(Andrews and Withey 1976), evaluating on a 7-point scale (0 =
terrible; 6 = delighted)
satisfaction toward: health, family relationships, friendships,
housing, finances,
residential neighborhood, activities, religion, transportation,
life partner, as well as
general life satisfaction. A Cronbach alpha coefficient of .81
was calculated with the
sample of the present study, indicating very good internal
consistency. A similar level
of internal consistency has been reported recently (alpha=0.74)
(Chappell and Dujela
2008). An exploratory factor analysis with forced one factor
solution also indicated
significant factor loadings for all items, with a minimum factor
loading of .46.
The index of general mental health was composed of five items
from the Medical
Outcomes Study Short-Form Health Survey (SF-36) which
assesses anxiety,
depression and positive psychological well-being (Ware 1993).
Scores were
transformed so that a higher score corresponded to better mental

31. health. An alpha
coefficient of .80 was calculated for the sample of the current
study, and an
exploratory factor analysis supported the presence of one factor,
with significant
factor loadings of .55 or more for each item.
Positive psychological functioning was assessed with the
abridged version of
Ryff’s Scales of Psychological Well-being (Ryff 1989a, b),
which comprises these 6
subscales, each with three items: Self-Acceptance; Positive
Relations with Others;
Autonomy; Environmental Mastery; Purpose in Life; and
Personal Growth. Low
internal consistency coefficients, ranging from .33 to .56, have
been reported for
these abridged subscales (Ryff and Keyes 1995). Also the
factorial structure of the
abridged scale has received inconsistent support (Clarke et al.
2001; Guindon et al.
2004; Kafka and Kozma 2002).
An adaptation of Ryff’s scales to improve psychometric
properties was deemed
necessary for this study. First, an alpha coefficient of 0.64 was
calculated with the 18
items combined. Items reducing the internal consistency
coefficient were removed
one by one, resulting in the elimination of the entire Purpose in
Life subscale, two
items from the Personal Growth subscale (« I think it is
important to have new
experiences that challenge how you think about yourself and the
world» and «I gave
up trying to make big improvements or changes in my life a

32. long time ago »), and
44 Ageing Int (2010) 35:38–60
one item from the Autonomy subscale (« I tend to be influenced
by people with
strong opinions »). This resulted in a 12-item scale with alpha
coefficients of 0.67
and 0.71 for male and female participants. Confirmatory factor
analyses were
completed to test the proposed model structure consisting in one
latent variable (i.e.
positive psychological functioning) and 12 observed variables
(i.e. retained items).
As expected, significant error covariances were found between
certain items that
initially belonged to the same subscale or presented with
content overlap. Acceptable
fit indices for the model were found, χ2 (48, N=1997)=355.65,
p<.001; AGFI=.95;
CFI=.91; RMSEA=.057 and χ2 (48, N=1,332)=216.55, p<.001;
AGFI=.96;
CFI=.92; RMSEA=.051, for women and men). A cross-
validation analysis indicated
that the model structure was valid, as it did not vary
significantly between randomly-
selected samples from the original sample. This revised scale
mostly excludes
dimensions of positive psychological functioning that have been
found to be weaker
in later adulthood (i.e. Purpose in Life and Personal Growth;
Ryff 1989b, 1991, 1995;
Ryff and Keyes 1995). The revised scale therefore appears to
reunite more cohesive

33. indicators of positive psychological functioning at this stage of
life (i.e. Self-
Acceptance, Positive Relations with Others, Autonomy,
Environmental Mastery).
Social support The social support measure was based on the
Medical Outcomes Study
Social Support Survey (Ware 1993) and adapted to an older
adult population. It
includes 6 items evaluating satisfaction toward the perceived
amount of instrumental,
emotional and informational forms of support, as well as the
sense of belonging. The
presence of one factor was supported by an exploratory factor
analysis, as well as a
confirmatory factor analysis (CFI=.97, AGFI=.98, RMSEA=.05
for men; CFI=.98,
AGFI=.97 and RMSEA=.06 for women). The internal
consistency of this measure
was also deemed acceptable given its limited number of items
(alpha=0.69).
Analytic Procedure
Structural Equation Modeling (SEM) analyses were completed
with AMOS-5
(Arbuckle 2003) to assess the fit of the proposed model. The
subjective health
measure was treated as continuous, as it is not possible to
consider the categorical
nature of a variable in analyses performed by this program. The
use of categorical
variables can lead to inflated χ2 values as well as attenuated
correlation coefficients,
factor loadings, and standard error estimates mostly when
variables are abnormally

34. distributed and/or comprise less than five categories (Byrne
2001), which was not the
case with the subjective health measure. The Bootstrap
Maximum Likelihood
procedure was applied to minimize the possible impact of
abnormal data distributions
on model estimates. Model fit was evaluated with the
Comparative Fit Index (CFI),
the Adjusted Goodness-of-Fit Index (AGFI) and the Root Mean
Square Error of
Approximation (RMSEA). The chi-square statistic was not
considered due to its
hypersensitivity to sample size (Byrne 2001). An acceptable
degree of model fit is
generally reflected by AGFI and CFI indices equal to or greater
than .90, and a
RMSEA equal to or less than .08 (Byrne 2001; McDonald and
Ho 2002). A
Confirmatory Factor Analysis (CFA) was first completed to
confirm that the observed
variables included in the model measured their respective latent
variables. Given that
Ageing Int (2010) 35:38–60 4545
the fit of the measurement models was judged to be satisfactory,
the proposed
relationships (i.e. structure) between the different variables
included in the model
were subsequently tested. In order to satisfy identification
requirements of the model,
the reciprocal relationships between the Psychological Well-
Being variable and
Physical Health and Functional Status variables were evaluated

35. separately. Cross-
validation invariance analyses were subsequently completed to
ascertain the statistical
equivalence of the model between sub-samples and thus further
test its validity.
Finally, the models (for men and women samples) supported by
previous cross-
sectional SEM analyses were tested with subjective health
measured six years later
(Time 2), taking into account initial subjective health (Time 1).
Invariance analyses
were again undertaken to further test the validity of the final
longitudinal models.
Results
Preliminary Analyses
Missing data analyses revealed that 20 men (1.40%) and 42
women (1.93%) responded
to less than 50% of items, and they were excluded from
subsequent analyses. This left a
total sample of 2,129 female and 1,408 male participants.
Almost all participants
(95.94% of men and 93.87% of women) responded to 95% or
more of the items. Only
1.30% and 2.23% of missing data were found for men and
women samples, respectively.
The Expectation-Maximization algorithm was used to estimate
missing data, as this
method is considered superior to analysis of complete data
(listwise and pairwise
deletion) and mean substitution (Graham et al. 2003; Schafer
and Graham 2002).
Skewness and kurtosis indices revealed that measures were

36. overall fairly normally
distributed. Notably, the skew and kurtosis indices for the
subjective health measure at
Time 1 were, respectively, −.59 and .95 for women and −.70
and 1.76 for men. Similar
values were found for subjective health at Time 2 (−.54 and .74
for women; −.61 and
1.23 for men). However, distribution of the three measures of
functional status deviated
significantly from normal. Transformations were therefore
applied to improve
distribution of these measures and the Bootstrap procedure was
used to estimate all
parameters in subsequent SEM analyses. The latter procedure is
considered effective in
reducing the influence of abnormal data distributions in large
samples (Byrne 2001).
Scatter plots suggested satisfactory linearity. Multicollinerarity
analyses revealed an
absence of correlations above .90 between variables (see Tables
1 and 2), as well as
tolerance indices superior to 10% and variance inflation factor
ratios inferior to 10 for
each variable, which indicates that multicollinerarity was not
present (Kline 1998).
Multivariate outliers were excluded from further analyses,
resulting in a final sample
of 2,022 female and 1,336 male participants. From this sample,
1,426 female and 868
male participants evaluated their subjective health in CSHA-3
and were thus included
in the longitudinal analyses.
Cross-Sectional Test of the Integrative Model
Results of the SEM analyses revealed an acceptable degree of

37. fit for the proposed
model of subjective health for both women and men
(respectively: AGFI=.95;
46 Ageing Int (2010) 35:38–60
T
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Ageing Int (2010) 35:38–60 4747
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48 Ageing Int (2010) 35:38–60
CFI=.93; RMSEA=.057 and AGFI=.96; CFI=.92;
RMSEA=.047). Estimates for
the reciprocal relationship between Psychological Well-Being
and Functional Status

85. were however inadmissible and removed from the model. Other
non-significant paths
were also deleted from the model, with the exception of the path
Functional Status →
Subjective Health which was statistically non-significant for
men yet retained due to
its theoretical significance. Modification indices suggested a
possible relationship
between Age and Subjective Health and this path was added to
the model. Post hoc
analyses were completed following the above-mentioned
modifications to the model
and results suggested a slight improvement in model fit for
women and men
(respectively: AGFI=.95; CFI=.94; RMSEA=.052 and
AGFI=.96; CFI=.92;
RMSEA=.045). Cross-validation analyses of the modified
models revealed that
their structure did not significantly vary from one sample to the
next, which strongly
a
Fig. 2 a Final model of subjective health for women (Time 1). b
Final model of subjective health for men
(Time 1)
Ageing Int (2010) 35:38–60 4949
supported their validity. Final models of subjective health for
women and men are
respectively presented in Fig. 2a and b.
In sum, hypothesized relationships in the proposed model of

86. subjective health
were partially supported. To reiterate, the main hypotheses were
that psychological
well-being would have a direct effect on subjective health, as
well as an indirect one
through physical health and functional status, and that social
support would have an
indirect effect on subjective health via psychological well-
being.
As predicted, for both women and men respectively,
psychological well-being
exerted direct (b=.16, p<.001; b=.13, p<.01) and indirect
(b=.35, p<.001; b=.31,
p<.001) effects on subjective health, resulting in considerable
total effects (b=.51,
p<.001; b=.44, p<.001). While psychological well-being was
associated with less
physical health problems (b=−.62, p<.001 for women; b=−.57,
p<.001 for men), no
relationship was found with functional status, suggesting that
the indirect effects
occurred through physical health exclusively. As hypothesized,
social support also
b
Life
Satisfaction
Fig. 2 (continued)
50 Ageing Int (2010) 35:38–60

87. had indirect effects on subjective health (b=.23, p<.001 for
women; b=.16, p<.001
for men) through its direct positive effect on the psychological
well-being of both
women and men (b=.45, p<.001; b=.37, p<.001 respectively).
Furthermore, age
was associated with a greater number of physical health
problems (b=.32, p<.001
for women; b=.17, p<.001 for men) and a poorer functional
status (b=−.30, p<.001
for women; b=−.27, p<.001 for men). Higher education was
associated with fewer
physical health problems for both sexes (b=−.08, p<.01; b=−.11,
p<.001 for
women and men respectively), whereas it predicted better
psychological well-being
in women only (b=.16, p<.001). Not surprisingly, physical
health problems were
associated with poorer subjective health (b=−.52, p<.001 for
women; b=−.50,
p<.001 for men) and poorer functional status (b=−.54, p<.001
for women; b=−.50,
p<.001 for men). Better functional status was associated with
better subjective health
for both sexes (b=.09), yet achieved a minimal degree of
statistical significance
(p<.05) in women only. The total explained variance of
subjective health reached
43% for women and 38% for men.
Contrary to expectations, older age was directly associated with
better subjective
health (b=.18, p<.001; b=.10, p<.001 for women and men
respectively), whereas
education was not significantly associated with subjective
health for neither sexes, nor

88. with psychological well-being and functional status for men. A
very weak negative
association was found between women’s education and
functional status (b=−.07,
p<.01). Indirect positive effects were found between women’s
education and
subjective health (b=.12, p<.001). Results suggested a
unidirectional (as opposed to
reciprocal) relationship between psychological well-being and
physical health for both
sexes. Specifically, the effect of psychological well-being on
physical health was
significant, but not the reverse. Finally, as previously
mentioned, results suggested an
absence of relationship between psychological well-being and
functional status.
Longitudinal Test of the Proposed Model
Results of the longitudinal analyses suggested an appropriate
model fit for both
women and men (respectively AGFI=.95; CFI=.94;
RMSEA=.048 and AGFI=.95;
CFI=.91; RMSEA=.045). Certain non significant path
coefficients lead to the deletion
of corresponding links, and post hoc analyses again suggested
an acceptable model fit
(AGFI=.95; CFI=.94; RMSEA=.048 and AGFI=.95; CFI=.91;
RMSEA=.044 for
women and men respectively). Validity of these models was
also supported by cross-
validation analyses, which suggested that their structure did not
vary significantly
from one sub-sample to another. Final models of subjective
health at Time 2 for
women and men are presented in Fig. 3a and b respectively.

89. As predicted, subjective health measured at Time 1 was
significantly associated
with subjective health at Time 2 (b=.29, p<.001 for women;
b=.23, p<.01 for men).
For men, psychological well-being had both significant direct
(b=.15, p<.01) and
indirect effects on subjective health at Time 2, with total effects
rising significantly
(b=.34, p<.001). While the direct effect of psychological well-
being on subjective
health at Time 2 was not significant for women, significant
indirect effects were
found (b=.33, p<.001). Social support also continued to have a
small indirect
positive effect on subjective health at Time 2 (b=.15, p<.01 for
women; b=.14, p<.01
for men). A greater number of physical health problems had
both direct (b=−.30,
Ageing Int (2010) 35:38–60 5151
p<.001 for women; b=−.19, p<.01 for men) and indirect
negative effects on
subjective health at Time 2, resulting in significantly elevated
total effects (b=−.46,
p<.001 for women; b=−.30, p<.001 for men). The effect of
functional status on
both women and men’s subjective health at Time 2 was not
significant. Contrary to
expectation, age for both genders and psychological well-being
for women did not
have significant direct effects on subjective health across time.
The total explained

90. variance of subjective health at Time 2 was 28% for women and
21% for men.
Discussion
The primary aim of the present study was to examine the
contributions of
psychological well-being and social support to an integrative
model of subjective
health in older adults, concurrently and over time. Overall, both
cross-sectional and
longitudinal SEM results support the proposed integrative
model of subjective
health, as suggested by adequate model fit indices and
significant variable
.50.86.84 .59.42.55
.60 .60 .45
.58
.52
.59
.78
.96
.72
-.08
.16
.45

91. .26
-.08
-.62-.27
-.52
-.51
.16
.14
.06
.71
.38.40
.19 -.64
.76.67
.63 .64 .74
.29
-.30
.18
Psychological
Well-Being
Mental
Health

92. Positive
Psych.
Funct.
Life
Satisfaction
Age
Education
Social
Support
Illness
Auditory
Acuity
Visual
Acuity
MobilityIADLPADLAntece
dents
Physical
Health
Problems
Functional
Status
Subjective
Health

93. T1
Subjective
Health
T2
a
Fig. 3 a Final model of subjective health for women (Time 2). b
Final model of subjective health for men
(Time 2)
52 Ageing Int (2010) 35:38–60
interrelationships. It is remarkable that the contributions of the
different variables in
the model were overall very similar in men and women. This
contrasts with results
of other studies that found gender differences in the predictors
of subjective health
(e.g. Gonzalez et al. 2002; Prus and Gee 2003).
Results provide strong support for the main hypothesis that
psychological well-
being affects subjective health directly and indirectly (although
only indirect effects
were observed for women at Time 2). The direct effect of
psychological well-being
on subjective health may reflect the influence of psychological
well-being on
memory and other cognitive processes that may be involved in
the evaluation of
health, such as downward social comparisons (Henchoz et al.

94. 2008; Jylhä 1994;
Kaplan and Baron-Epel 2003; Krause and Jay 1994; Suls et al.
1991), which refer to
the tendency to maintain a positive perception of one’s health
by comparing oneself
to others in poorer health. As Wurm and her colleagues recently
pointed out (Wurm
et al. 2008), a positive view of ageing affects subjective health
and life satisfaction
even in the face of serious health problems, and thus represents
a psychological
resource that fosters resilience.
b .68 .60 .53
.70
.84 .88 .49 .95 .81 .70 .85
.55
.79.67
.84
Fig. 3 (continued)
Ageing Int (2010) 35:38–60 5353
The finding of an indirect effect of psychological well-being on
subjective health
via physical health finds an echo in emerging evidence showing
how physical health
can be positively affected by various dimensions of

95. psychological well-being
including positive affect (Fredrickson and Levenson 1998; Ostir
et al. 2001a; Ostir et
al. 2004; Ostir et al. 2001b; Xu 2006), optimism (Kubzansky et
al. 2001; Reed et al.
1999; Segerstrom et al. 1998), and perception of control
(Chipperfield et al. 2004).
As predicted, greater satisfaction with available social support
had direct and indirect
positive effects on psychological well-being and subjective
health, respectively. These
effects were found in both cross-sectional and longitudinal
analyses. It should be noted
however that the indirect effects of social support on subjective
health, although
significant, were small. Some studies that distinguished between
emotional and
instrumental support have reported that availability of
emotional support was associated
with better subjective health, whereas greater instrumental
support was associated with
poorer subjective health (Liu et al. 1995; Zunzunegui et al.
2001). It is therefore
possible that larger effects could be found for emotional support
specifically. This
hypothesis could not be tested in the present study since these
two types of support
were not distinguished in the measure of social support used. A
more detailed
understanding of the effects of social support on subjective
health might be achieved
with the use of distinct measures of these different forms of
social support.
Not surprisingly, physical health problems were significantly

96. associated with
subjective health and continued to have a significant effect at
Time 2, both directly
and indirectly through subjective health measured at Time 1. A
surprising result was
the lack of effect of physical health problems on psychological
well-being for both
sexes. Several studies have shown that psychological (or
subjective) well-being
tends to remain relatively stable and minimally affected by life
events in the long
term (DeNeve and Cooper 1998; Eid and Diener 2003; Stones et
al. 1995; Suh et al.
1996). This stability may be rooted in personality (Duberstein et
al. 2003; Suh et al.
1996) or genetic predispositions (Nes et al. 2006). The limited
effect of life events
on psychological well-being may also reflect the capacity of
human beings to adapt
to major challenges such as health problems.
As expected, age had an unfavorable effect on physical health
problems and
functional status. Consistent with results of other studies (Hays
et al. 1996; Idler
1993; Johnson and Wolinsky 1993; Landau and Litwin 2001;
Lee and Shinkai 2003;
Mulsant et al. 1997), a small yet significant relationship was
found between older
age and better subjective health at Time 1. This finding should
however be
interpreted with caution, as results were inconsistent in the
longitudinal test.
Other hypothesized links between certain variables of the model
were not

97. significant. For instance, education appeared to be associated
with greater
psychological well-being and better subjective health, but only
for women. Results
also suggested that functional status had a minimal effect on
subjective health for
both sexes, which is congruent with results of other studies
(Nybo et al. 2001; Stump
et al. 1997). It may be that older adults expect a certain degree
of physical limitations
at this stage of life and thus evaluate their health based on this
expectation rather
than that of an “ideal” or “perfect” health (Nybo et al. 2001).
Although a substantial amount of subjective health’s variance
was explained by
the final model, a certain amount of variance was left
unexplained. Other variables
excluded from the proposed model may also contribute to
explain subjective health
54 Ageing Int (2010) 35:38–60
in later life, such as potential risk factors like pain,
psychological distress, and life
stressors. On the other hand, other protective factors could also
be considered, such
as positive coping strategies, healthy lifestyle, positive affect,
personality traits (e.g.
optimism; sociability), and favorable cognitive processes such
as downward social
comparisons and positive illusions.
Some limitations of the present study need to be acknowledged.

98. A major dis-
advantage of secondary data analyses consists in the imposed
selection of measures.
Findings of this study are limited by the conceptual and
methodological restrictions of
some of its measures. For instance, the evaluation of
psychological well-being included
a measure of general mental health which contained questions
related to depression and
anxiety that are indeed more indicative of psychological distress
than well-being.
Furthermore, Ryff’s Scales of Psychological Well-being and the
social support scales
were adaptations of the original scales. Measures of physical
health and functional
status can also be criticized for being based on self-report, and
thus susceptible to
under- or over-reporting biases. While measurement of
subjective health with a single
item can also be considered an issue, there is extensive evidence
to support its use (see
above description of this measure). Although the investigation
was rendered more
rigorous with the adoption of SEM as an advanced method of
analysis, the analyses
remain correlational in nature, and thus cannot truly establish
causal relationships
between variables (Kline 1998). Nonetheless, findings from the
longitudinal analyses
provide some tentative support for such type of relationship
between the variables in
the proposed model and subjective health. Finally, it should be
recalled that
participants of the present study resided in the community, and
did not present with
significant cognitive impairments. Therefore, results may not be

99. generalizable to
older adults with differing characteristics, such as individuals
with lower autonomy.
In conclusion, results of this study emphasize the determining
role of psycho-
logical well-being, in terms of good mental health, satisfaction
with life and positive
psychological functioning, for older adults’ perceptions of their
health. The final
model illustrates how psychological well-being conceived in
this manner can
influence subjective health, both directly and indirectly through
its favorable effect
on physical health. Considering the predictive power of
subjective health on other
important outcomes such as functional decline and mortality,
implications of these
results are important. At a theoretical level, they confirm the
validity of integrative or
holistic models of subjective health, such as those proposed by
Mossey (1995) and
in the present study. Furthermore, while existing research has
mainly focused on the
negative effects of psychological distress on subjective health,
this study supports
the relevance of studying protective psychological resources
that may promote better
subjective health in later adulthood. This line of investigation
could also help
elucidate the reason many older adults rate their health
positively even when faced
with physical health problems.
At a clinical level, the results point to the need to promote
greater psychological well-

100. being in order to improve subjective health. Various types of
interventions could be
considered. In particular, findings of this study suggest that
social support may have a
significant effect on psychological well-being, and a resulting
indirect effect on
subjective health. Clinicians working with older adults should
thus be aware of the
possible needs for social support among their clients and
provide referrals to appropriate
community resources for those with limited support.
Furthermore, strategies aiming to
Ageing Int (2010) 35:38–60 5555
achieve greater psychological well-being without requiring
professional assistance have
been described in the literature (e.g. Fredrickson and Levenson
1998; Seligman et al.
2005), and could potentially also have positive effects on
subjective health in the later
stages of life. Clinical implications of this study incite the
development of social
policies that would facilitate older adults’ access to life
conditions and resources that
are likely to promote more optimal levels of psychological well-
being and, in turn,
better subjective health and associated outcomes.
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Ageing Int (2010) 35:38–60 5959
Sophie Guindon is a clinical psychologist working with adults,
in particular older adults, in hospital-
based practice. She graduated from the University of Ottawa
with a Ph.D. in clinical psychology in 2007.
Previously she had completed a Master’s degree in Psychology
at the Université de Montréal. Her clinical
and research interests relate to psychological interventions with
individuals and couples for depression and
anxiety.
Philippe Cappeliez is Full Professor at the School of
Psychology, University of Ottawa, which he initially
joined in 1984. He is also affiliated with the Elisabeth Bruyère
Research Institute (Ottawa). He obtained

115. his Ph.D. in clinical psychology at McGill University (1981),
after undergraduate and graduate studies
(Licence en psychologie) at Université Catholique de Louvain
(Belgium). He is Fellow of the Canadian
Psychological Association. He teaches cognitive-behavior
therapy and clinical psychology of aging to
graduate students in clinical psychology, and psychology of
aging and research topics in gerontology to
undergraduate students in psychology and gerontology.
Depression in older adulthood, in particular
psychological treatments such as reminiscence therapy, and the
functions of reminiscence constitute his
main research interests.
60 Ageing Int (2010) 35:38–60
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C H A P T E R14
Biological Aspects of Later
Adulthood
LeRoy was a muscular, outgoing teenager. He was physically
bigger than most of his

116. classmates and starred in basketball, baseball, and football in
high school. In football
he was selected as an all-state linebacker in his senior year. At
age16, he began
drinking at least a six-pack of beer each day, and at 17 he began
smoking. Because
he was an athlete, he smoked and drank on the sly. Since LeRoy
was good at conning
others, he found it fairly easy to smoke, drink, party, and still
play sports. That left little
time for studying, but LeRoy was not interested in that, anyway.
He had other priorities.
LeRoy received a football scholarship andwent on tocollege.He
did well in football
and majoredinpartying. His grades suffered, andwhen his
college eligibility in football
was used up, he dropped out of college. Shortly after dropping
out, he married Rachel
Rudow, a college sophomore. She soon became pregnant and
also dropped out of
A
Be
llo
/G
et
ty
Im
ag
es
613
Copyright 2012 Cengage Learning. All Rights Reserved. May
not be copied, scanned, or duplicated, in whole or in part. Due
to electronic rights, some third party content may be suppressed

117. from the eBook and/or eChapter(s).
Editorial review has deemed that any suppressed content does
not materially affect the overall learning experience. Cengage
Learning reserves the right to remove additional content at any
time if subsequent rights restrictions require it.
college.LeRoywasdevastatedafter
leavingcollege.Hehadbeenajockfor10years, the
envyof hisclassmates. Nowhecouldn’t get a job with status.
Aftera variety of odd jobs,
he obtained work as a road construction worker. He liked
working outdoors and also
liked the macho-type guys with whom he worked, smoked,
drank, and partied.
LeRoy and Rachel had three children, but he was not a good
husband. He was
seldom at home, and when he was, he was often drunk. After a
stormy seven years of
marriage that included numerous incidents of physical and
verbal abuse, Rachel
moved out and got a divorce. She and the children moved to
Florida, along with
her parents, so that LeRoy could not continue to harass her and
the children. LeRoy’s
drinking and smoking increased. He was smoking more than two
packs a day, and he
sometimes also drank a quart of whiskey.
A few years later, he fathered a child for whom he was required
to pay child
support. At age 39, he married Jane, who was only 20. They had
two children and

118. stayed married for six years. Jane eventually left because she
became fed up with being
assaulted when LeRoy was drunk. LeRoy now had a total of six
children to help support,
but he seldom saw any of them. LeRoy continued to drink and
also ate to excess.
His weight went up to 285 pounds, and by age 48 he was no
longer able to keep
up with the other construction workers. The construction
company discharged him.
The next several years saw LeRoy taking odd jobs as a
carpenter. He didn’t earn
much, and he spent most of what he earned on alcohol. He was
periodically embar-
rassed by being hauled into court for failure to pay child
support. He was also dis-
mayed because he no longer had friends who wanted to get
drunk with him. When
LeRoy was 61, the doctor discovered he had cirrhosis of the
liver and told LeRoy he
wouldn’t live much longer if he continued to drink. Since
LeRoy’s whole life centered
on drinking, he chose to continue to drink. LeRoy also noticed
that he had less energy
and frequently had trouble breathing. The doctor indicated that
he probably had
damaged his lungs by smoking and now had a form of
emphysema. The doctor
lectured LeRoy on the need to stop smoking, but LeRoy didn’t
heed that advice either.
His health continued to deteriorate, and he lost 57 pounds. At
age 64, while drunk, he
fell over backward and fractured his skull. He was hospitalized
for three and a half
months. The injury permanently damaged his ability to walk and

119. talk. He is now
confined to a low-quality nursing home. He is no longer allowed
to smoke or drink.
He is frequently angry, impatient, and frustrated. He no longer
has friends. The staff
detests working with him; his hygiene habits are atrocious, and
he frequently yells
obscenities. LeRoy frequently expresses a wish to die to escape
his misery.
Elroy Karas is 14 months younger than his brother LeRoy.
Elroy’s early years were
in sharp contrast to LeRoy’s. Elroy had a lean, almost puny,
muscular structure and did
not excel at sports. LeRoy was his parents’ favorite, and also
dazzled the young
females in school and in the neighborhood. Elroy had
practically no dates in high
school and was viewed as a prude. He did well in math and the
natural sciences. He
spent much of his time studying and reading a variety of books,
and he liked taking
radios and electrical appliances apart. At first, he got into
trouble because he was not
skilled enough to put them back together. However, he soon
became known in the
neighborhood as someone who could fix radios and electrical
appliances.
614 Understanding Human Behavior and the Social Environment
Copyright 2012 Cengage Learning. All Rights Reserved. May
not be copied, scanned, or duplicated, in whole or in part. Due
to electronic rights, some third party content may be suppressed
from the eBook and/or eChapter(s).

120. Editorial review has deemed that any suppressed content does
not materially affect the overall learning experience. Cengage
Learning reserves the right to remove additional content at any
time if subsequent rights restrictions require it.
He went on to college and studied electrical engineering. He
had no social life but
graduated with good grades in his major. He went to graduate
school and obtained a
master’s degree in electrical engineering. On graduating, he was
hired as an engi-
neer by Motorola in Chicago. He did well there and in four
years was named man-
ager of a division. Three years later, he was lured to RCA with
an attractive salary
offer. The group of engineers he worked with at RCA made
some significant advances
in television technology.
At RCA, Elroy began dating a secretary, Elvira McCann, and
they were married
when he was 36. Life became much smoother for Elroy after
that. He was paid well and
enjoyedannual vacationswith Elvira
tosuchplacesasHawaii,Paris,and theBahamas.
Elroy and Elvira wanted to have children, but could not. When
Elroy was in his early
40s, they adopted two children, both from South Korea. They
bought a house in the
suburbs and a sailboat. Elroy and Elvira occasionally had some
marital disagreements
but generally got along well. In their middle adult years, oneof
their adopted sons, Kim,
was tragically killed by an intoxicated automobile driver. That

121. death was a shock and
very difficult for the whole family to come to terms with. But
the intense grieving gradu-
ally lessened, and after a few years Elroy and Elvira put their
lives back together.
Now, at age 67, Elroy is still working for RCA and loving it. In
a few years, he
plans to retire and move to the Hawaiian island of Maui. Elroy
and Elvira have already
purchased a condominium there. Their surviving son, Dae, has
graduated from college
and is working for a life insurance company. Elroy is looking
forward to retiring so that
he can move to Maui and spend more time on his hobbies—
photography and
making model railroad displays. His health is good, and he has a
positive outlook
on life. He occasionally thinks about his brother and sends him
a card on his birthday.
Since Elroy never had much in common with LeRoy, he seldom
visits him.
A Perspective
Lateradulthood isoften theageof recompense (our return for
thewaywelivedearlier).
Howwelive inouryoungeryears largelydetermineshowwewill live
inour lateryears.
Learning Objectives
This chapterwill:
A. Define later adulthood.
B. Describe the physiological and mental changes that occur in
later adulthood.