The Gerontologist
Vol. 50, No. 1, 36–47
doi:10.1093/geront/gnp067

© The Author 2009. Published by Oxford University Press on behalf of The Gerontological Society of America.
All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.
Advance Access publication on June 23, 2009

Examining Resilience of Quality of Life in the
Face of Health-Related and Psychosocial
Adversity at Older Ages: What is “Right”
About the Way We Age?
Zoe Hildon, MA, PhD,1,2 Scott M. Montgomery, PhD,3,4 David Blane, MSc, MD,5
Richard D. Wiggins, PhD,6 and Gopalakrishnan Netuveli, PhD5
terized resilient outcomes relative to qol, included
good quality relationships (5.105, confidence interval [CI] 95% 1.323–19.699), integration in the community (10.800, 95% CI 1.227–95.014),
developmental coping (3.397, 95% CI 1.079–
10.690), and adaptive coping styles (3.211, 95%
CI 1.041–9.910). Implication: Overall results
indicate that policies that offer access to protection
and help minimize adversity exposure where possible will promote resilience.

Purpose: This article examines resilience at older
ages, focusing on the relationships between quality
of life (qol) and adversity. Our objectives are to identify (a) the basis of adversity, (b) the characteristics of
resilient individuals, and (c) the attributes that attenuate the full impact of adversity. Design and
Methods: Resilience is defined as flourishing despite adversity. Analysis is carried out in a subsample
of the Boyd Orr cohort (aged between 68 and 82
years) using questionnaire data. Adversity was identified as circumstances that produce a significant average decrease in qol (CASP-19 scores). Participants
were classified into resilient and vulnerable groups
based on high or low qol (CASP-19 scores dichotomized at the median) in the face of significant adversity. Shared characteristics that define these outcomes
are reported. Attributes that attenuate the negative
impact of adversity were analyzed using stratified
logistic regression. Results: Adversity was typified by functional limitation; life getting worse in the
domains of health, stress, and general living circumstances; and experiencing a negative life event. The
resilient tended to report fewer multiple adversities.
Indicators of protective attributes, which also charac-

Key Words: Protection, Sociodemographic factors,
Social networks, Community-related factors, Coping

When Nietzsche (1888/1984) famously noted
“that which does not kill us makes us stronger,”
he was saying something about the ability to
weather adversity—to steel oneself against hardship, to move beyond it, and, in short, to be resilient. Despite the ease with which this expression
rolls off the tongue, most of us, from our own experiences, know this expression to be wanting.
Sometimes one does not emerge the better from
adversity, other times resilience will apply to only
one domain of our lives and not carry through to
others. Resilience is clearly a splintered concept
but nevertheless very relevant to understanding
successful aging in Britain today.
Within the gerontological literature, successful
aging has traditionally been conceived in terms of
physiological and cognitive robustness or the staving off of decline in health (Bowling & Dieppe,
2005; e.g., Rowe & Kahn, 2000). Nevertheless,
Harris (2008, p. 43) has recently argued that

1
Address correspondence to Zoe Hildon, Department of Clinical, Educational and Health Psychology, Centre for Outcomes Research and
Effectiveness, University College London, 1-19 Torrington Place, London
WC1E 7HB, UK. E-mail: z.Hildon@UCL.ac.uk
2
Department of Clinical, Educational and Health Psychology, Centre
for Outcomes Research and Effectiveness, University College London, UK.
3
Department of Medicine, Clinical Epidemiology Unit, Karolinska University Hospital, Sweden.
4
Clinical Research Centre, Örebro University Hospital, Sweden.
5
Department of Primary Care and Social Medicine, Division of Epidemiology, Public Health and Primary Care, Imperial College London, UK.
6
Social Science Research Unit, Institute of Education, University of
London, UK.

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The Gerontologist

be better equipped to manage adversity; the second tries to capture the processes explaining how
resilience is achieved (Jacelon, 1997; Richardson,
2002). Analysis identifying resilient characteristics
tends to be person focused, grouping people with
resilient outcomes and examining the factors that
define them (e.g., Garmezy, 1985; Werner &
Smith, 1977). As Masten (2001, p. 232) puts it, in
a bid “to capture the configural patterns of adaptation that naturally occur, in much the same ways
that classification systems for mental disorder organize symptoms into patterns that have been observed to occur together.” This analysis is an
effective way of answering the fundamental research question: who are the resilient?
In contrast, variable-focused analyses have been
used as a starting point for considering resilient
processes. These approaches tend to examine the
relationship or interplay between adversity and
protection, which lead to better-than-expected
outcomes (Luthar, Ciccheti, & Becker, 2000;
Roosa, 2000), addressing the question, which factors are effective in attenuating the negative impact of adversity? Analysis that consider variables
that are mobilized in the face of significant adversity provides one way of identifying more immediate actions, iterative or habitual/routine, performed
to achieve resilient ends. Such analysis can suggest
practices or assets that are particularly effective
when adversity is present. Presumably because
they buffer, transform, or negate the full potential
impact of psychosocial and health-related crises.
Studies examining resilience and protective relationships that focus on older ages (Becker &
Newsom, 2005; Butler & Ciarrochi, 2007; Kinsel,
2005; Netuveli, Montgomery, Hildon, Wiggins, &
Blane, 2006; Ryff, Singer, Love, & Essex, 1998;
Staudinger,Freund,Linden,&Maas,1999;Wagnild&
Young, 1990; Windle & Woods, 2004) as well as
those on resilience at younger ages have tended to
lack focus on the detail of adversity (Hildon et al.,
2008). Resilience-centered research, which has considered older populations, has poorly defined the
adversity construct or assumed that old age itself is
necessarily adverse. Within analyses identifying protective factors promoting resilience at older ages, the
precise role of these stated factors are rarely specified or interpreted. Furthermore, although resilient
characteristics and the attributes or associated processes that negotiate the impact of adversity have
been examined in relation to younger ages, to our
knowledge these features of resilience have not been
systematically analyzed for older populations.

“perhaps we have been striving for the wrong goal.
The true quest as we age should not be for successful
aging [as traditionally defined], but our goal should
be for resilience, an undervalued and not fully examined concept in aging.” A position backed up
by the looming reality that, despite ever-hopeful
models describing the postponement of morbidity
as we grow older (Fries, 1980), a disease-free old
age is after all unrealistic for most of us (Kind,
Dolan, Gudex, & Williams, 1998; Martin, Meltzer,
& Elliot, 1988). Resilience at older ages addresses
this certainty and conceptually disputes commonly
held assumptions about the elderly individuals.
For instance, resilience overrides the idea that
once health begins to deteriorate and disability sets
in, aging successfully is no longer possible. This is
because resilience as a phenomenon is characterized by its improbability and is defined by the presence of hardship, as achieving better-than-expected
outcomes or flourishing despite adversity (Garmezy,
1985; Hildon, Smith, Netuveli, & Blane, 2008;
Masten, Best, & Garmezy, 1990; Rutter, 1987;
Werner, 1990; Werner & Smith, 1977, 1982). Accordingly, the tradition and foci of research on resilience can be seen to have emerged “more by
accident than by intent” (Grotberg, 1997, p. 118).
Study Aims
Historically, research on the topic of resilience
originated from studies of risk and development in
children and young people (Werner, 1990, 1995).
As researchers scrutinized the effects of deprivation
and other adversities, seeking to better understand
the effects of vulnerability, they were surprised to
discover instead that many young people were not
beaten down or defeated by socioeconomic or psychosocial adversity. Researchers then began asking
not just about what was wrong with young people
facing hardship but also what was “right” with
them? (Werner, 1990). The presently reported
study aims to break down and answer this question in relation to older ages, a stage of life that
research on resilience has comparatively neglected
(Rowe & Kahn, 2000; Schoon, 2006), focusing on
the relationships between quality of life (qol) and
health-related or psychosocial adversity.
Lessons From the Literature
The tradition of resilience-focused research has
broadly used two forms of analysis. The first seeks
to identify characteristics of resilient people, lists
or constellations of factors that identify who might
Vol. 50, No. 1, 2010

37

Study Objectives and Research Questions

Table 1. Comparison of Boyd Orr Sample Used in Present
Analyses (N = 174), With Population of Britain Aged 70–84
Years in the 2001 Census

Consequently, we undertake analyses from the
established resilience tradition, identifying individual and social indicators that characterize resilient
outcomes or point toward resilient processes at
older ages. Our objectives are to (a) examine adversity a priori; (b) identify sociodemographic factors, social networks and community-related
factors, and styles of coping, which are predominantly associated with resilient qol outcomes when
compared with vulnerable ones. In sum, we have
three main research questions we ask relative to
qol at older ages: What typifies psychosocial and
health-related adversity? Who are the resilient? and
Which individual or social attributes are effective
in attenuating the negative impact of adversity?

Population
characteristics
Female
Male
Women, married currently
Men, married currently
Higher educationa
Owner occupier
Limiting long-standing illness
Self-assessed health “good”
or “fairly good”

Present Boyd
Orr sample
(%)

Census
population
(%)

54.1
45.9
47.3
80.0
11.6
80.7
40.6
84.1

57.8
42.2
39.1
70.1
11.5
74.8
51.1
70.6

Note: aQualifications beyond Levels 1–3 of National Key
Learning Targets (General Certificate of Secondary Education,
O Level, A Level, National Vocational Qualifications Levels
1–3), including graduate and postgraduate academic qualifications and some vocational or professional qualifications.

Population Sample

Study Participants

remains broadly representative of the British population in terms of sex, academic qualifications, and
housing tenure. The 33 sample members excluded
because of missing data tended to be older (56% of
the excluded 33 were older than 75 years, compared
with 43% of the included), were marginally less
likely to be owner occupiers (77% compared with
83%), and were more likely to report their income
as enough or more than enough to meet their needs
(90% compared with 84%).

The cohort we have examined is a stratified subsample of surviving traced members of the Boyd Orr
cohort. Originally, between 1937 and 1939, 1,352
families and 7,920 individuals took part in the study.
In 1997, a subsample of the child participants, aged
between 5 and 14 years at the time of the first survey, was randomly selected (from a possible n =
3,762 cases) using household food expenditure per
capita data to stratify the original sample, which
had been weighted toward financial deprivation.
These individuals were resurveyed between
1997 and 1999 (n = 294) and were found to be
broadly representative of their age peers at the
1991 census (Blane, Berney, Davey Smith, Gunnell,
& Holland, 1999), with the exception of ethnicity,
that is, all study participants were White European
British (for further details of the Boyd Orr cohort,
see Blane, 2005). Subsequent resurveys have
gathered health and qol data. Most recently,
between 2003 and 2005, the data for the current
analysis were collected by postal questionnaire
and home visits from 253 potential respondents
(attrition due to death of 14% of the 1997–1998
respondents).
The results reported in the current study are
based on 174 of the 253 who had complete questionnaire information (nonresponse due to refusal,
n = 22; loss through moves and ill health, n = 24;
item nonresponse, n = 33). Participants are aged between 68 and 82 years, the mean age was 75 years.
Although respondents were somewhat healthier
and more likely to be married (Table 1), this sample

Measures

Resilience of qol
Our primary outcome measure was resilience
defined as better-than-average qol in the face of
significant adversity. Quality of life was measured
using a validated continuous scale to capture this
concept: the CASP-19 self-completion questionnaire
(Hyde, Wiggins, Higgs, & Blane, 2003; Wiggins,
Higgs, Hyde, & Blane, 2004). As the name implies,
this measure has 19-items that reflect the four
dimensions of control, autonomy, self-realization,
and pleasure. These four domains are argued to
theoretically constitute qol at older ages (Higgs,
Hyde, Wiggins, & Blane, 2003). Each item is scored
0–3 using a 4-point Likert scale, producing a scale
range of 0 to 57; the higher the score the better the
qol. We defined better-than-average qol as a value
of CASP-19 above the median. The median cutoff
for CASP-19 was chosen because it is seen to realistically capture flourishing or unexpected positive
38

The Gerontologist

work (Blane, 2005). This score was dichotomized
at the median point of 54 years.

outcomes, as behavior that falls within or is higher
than the expected average for a normative cohort
(Masten & Powell, 2003).

Social Networks

Psychosocial and Health-Related Adversity

Social networks were measured using a number
of items. First, we measured the type of contact
provided by friends and family, including the
quality of relationships, which was measured by
aggregating a seven-item 3-point score. The seven
items were having people that make me happy,
can be relied on, accept me, support and encourage
me, make me feel loved, will see me taken care
of, and make me feel an important part of their
lives. This score was ranked and dichotomized
for use in the analysis. Other types of contact
were measured dichotomously (yes/no) in relation
to family and friends providing practical support
or emotional support, or being available to
socialize.
Density of contact was measured in several
ways. First, we asked about the number of close
confiding relationships; having more than two
close confiding relationships was considered high
density. We also asked respondents to count the
number of friends and family they were close to;
this total was dichotomized into high and low
at the median (which was 5 and 6, respectively)
to determine if respondents had a wide circle of
family and/or friends. Frequency of contact was
measured by frequency of telephone contact or
meeting up with other people; this was measured
separately for friends and family. If contact was
reported in the past week, this was considered
frequent.

The adversities we examine are being limited by
illhealth or (in the past 5 years) deteriorating
health, having more stress, changing life circumstances, being worse off financially, and experiencing a negative or difficult event such as bereavement.
The adversities were measured in several ways.
Study participants were asked about change during the previous 5 years in health, financial circumstances, levels of stress, and general living
circumstances. Respondents who answered to one
or more of these items “a bit worse now” or “a lot
worse now” were categorized as having been exposed to adversity, as were participants who reported limitations from their illness and a negative
life event.
Negative life events were recorded using an
open-ended question, coded subsequently for bereavement, the illness of a loved one, and other
events experienced as difficult. Hildon and colleagues (2008) have shown that the same event,
for example, bereavement (the most commonly reported negative event in old age) or retirement can
both be experienced as acute and chronic. For example, when daily routines with partners are fixed,
trying to continue these postbereavement or indeed
not being able to postretirement can serve to produce constant (chronic) reminders of loss. Therefore, the negative events variable is seen to be able
to capture both acute and chronic effects on qol at
the time of the survey. In compiling this variable,
care was taken to exclude events such as financial
problems and personal health problems, which
were already measured. Although there is undoubtedly an overlap between these changes and events,
all adversities were judged sufficiently distinct to
test as a cumulative variable.

Community-Related Factors
A good sense of community was identified by
summing four items developed to capture this
domain (Wiggins et al., 2004): “having a lot of
friendly neighbors,” “people looking out for each
other,” “a good community spirit,” and “having a
good mix of people.” Integration in the community was computed by identifying those who reported involvement in paid employment, voluntary
work (full time or part time), or community
organizations.

Sociodemographic Factors
Sociodemographic information was compiled
from current and previous waves of data collection. This includes a measure for weekly food expenditure per capita as a measure of family income
in childhood, dichotomized at the median point of
165 pence. In addition, we consider life course exposure to hazards score, which aggregates the
number of years exposure to poor diet, occupational fumes and dust, and physically arduous
Vol. 50, No. 1, 2010

Coping Styles
Coping was measured using a 20-item coping
scale developed based on existing literature
(Lazarus, 1980; Staudinger et al., 1999), focus
39

Because adversities constitute changes or events that
tend to reduce qol, individuals who maintain the
average qol experience for the cohort and better can
be seen to be managing exceptionally well or flourishing. The natural comparator to resilient outcomes
was identified as vulnerable outcomes, measured as
below-average qol (CASP-19 below the median),
in the face of at least one validated adversity. Crosstabulation of resilient and vulnerable outcomes with
individual and social attributes allowed us to compare
the characteristics and levels of adversity exposure of
both groups; chi-square test was used to test whether these associations were statistically significant.

groups, expert consensus, and factorial analyses
(see Appendix). The coping styles were as follows:
1.

2.

3.

Avoidance: coping, which sidesteps engaging
in solutions or problem solving by, for instance, focusing on negative feelings, for example, feeling like life has no meaning, stuck
with a problem, or pretending that problems
are not happening. This seems to equate with
being overwhelmed by adversity.
Adaptation: solution-driven coping, for example,
teaching oneself how to live with a problem,
which could be equated to integrating adversity.
Development: again, solution-driven coping,
for example, learning from a problem, which
could be equated to moving beyond adversity
in a positive way.

Examining Attributes That Attenuate the Negative
Impact of Adversity
To identify which individual or social variables
might be effective in attenuating the negative impact
of adversity on qol, logistic regression analyses were
carried out using CASP-19 as the dichotomous dependent variable. This consisted of stratified analyses comparing the role of sociodemographic, social
networks, and community, along with coping styles
in subgroups of low and high adversity exposure.
High exposure is taken to mean reporting two or
more adversities and low exposure to mean reporting only one or no exposures to adversity. All analyses were adjusted for age, sex, and income but
variables were not mutually adjusted.
There are four possible relationships that can be
identified by this analysis. The first is that the tested variable significantly improves qol in the subgroup exposed to high levels of adversity but not
when adversity is low. This association can be interpreted as attenuating the effect of adversity on
qol or promoting resilience; its effect kicking in
only in the presence of adversity. Should a variable
significantly improve qol in both subgroups, the
factor could be considered to be generally protective, independent of adversity. Alternatively, a
variable may significantly improve qol only in the
low-adversity group, thus having only a weak protective effect. Last, a variable may have no significant association with qol in both subgroups, which
demonstrates its lack of overall importance in
terms of protection and resilience.

Scores for each of the three dimensions were
calculated by summing the endorsements given for
each of their items. All three items were ranked
and dichotomized into high and low for use in subsequent analysis.
Methods of Analysis
Analyses were carried out using SPSS 14.0 for
Windows.
Examining Health-Related and Psychosocial
Adversity
We first tested whether the five selected adversities were associated with below-average qol. For
this purpose, we tested the difference in the mean
CASP-19 score between the participants who were
not exposed to adversity and those who were exposed to a limiting illness, deteriorating health, more
stress, changing life circumstances, being worse off
financially, and experiencing a negative life event.
This was achieved by considering mean CASP-19
and the five p values using Student’s t test. Only the
adversity variables that showed significant reduction in CASP-19 scores, which were hence validated
as producing an average adverse effect, were used in
subsequent analysis. The cumulative impact of these
adversities on CASP-19 scores was examined to
assess if the impact of adversities was additive.

Results

Examining Resilient Characteristics

Describing the Sample

Resilient outcomes were identified by betterthan-average qol (CASP-19 on or above the median)
and exposure to one or more validated adversities.

The mean score for the CASP-19 scale was 40.3
(scores ranged from 14 to 56). The distribution of
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The Gerontologist

about 40% and psychosocial about 20%). The
combo chart (Figure 1) shows the mean differences
in CASP-19 scores between those exposed to a
particular adversity and those who were not. Generally, exposure to an adversity was associated
with −8 points difference in mean CASP-19 scores.
The maximum drop occurred in those who felt life
in general was worse (−11.24 points) and the smallest drop was for finance getting worse (−2.13
points), which was also the only difference that did
not reach statistical significance. We did not use
the financial adversity variable in analysis beyond
this point.
Analysis of the combined effects of adversity
showed that as the number of adversities increased,
the impact on qol also increased (Figure 2). This
suggests that the five adversities validated by the
earlier analysis also had additive effects. For example, the mean CASP-19 score was lower by
more than one third (38%) for those exposed to
five adversities compared with those exposed to
one adversity.

CASP-19 scores was negativity skewed; however,
repeat analyses using raw CASP-19 scores and a
score transformed for normality showed no differences between them (results not shown). Moreover, there were no outliers in our data so that no
single observation can be seen to influence results.
In terms of the sociodemographic descriptors, not
previously reported, 64.4% of this sample had
nonmanual occupations (measured using the Registrar General’s Social Class occupational classification schema) and 74% reported access to a car.
The mean number of years of exposure to hazard
over the life course was 62.6 (scores ranged from
0 to 188), and mean household expenditure per
capita in childhood (in pence) was 180.1 (scores
ranged from 75 to 452).
In relation to social networks, 83.2% of sample
participants with complete data reported relying
on family for practical support and 85.1% reported relying to them for emotional support; only
28.7% relied on friends for practical support and
19.2% for emotional support. In contrast, 70.7%
reported socializing with friends and 51.7% with
family. About 79.3% of participants reported
meeting or speaking to a family member in the past
week and 63.2% reported this type of contact with
friends. Mean counts for having a wide circle of
family was 4.3 (counts ranged from 0 to 30) and
was 5.7 for having a wide circle of friends (counts
ranged from 0 to 26). About 28.7% of the sample
reported having several (more than two) close confiding relationships, and the mean of scores for the
quality of relationships scale was 19.5 (scores
ranged from 9 to 21).
Relative to community factors, 60.3% of participants with complete data reported integration
in the community; the mean score for reporting a
good sense of community was 2.3 (scores ranged
from 0 to 4). Last, relative to coping styles, the
sample mean for scores summing developmental
coping was 5.3 (scores ranged from 0 to 9); the
mean for adaptive coping styles scoring was 2.7
(scores ranged from 0 to 5); and the mean for
scores summing avoidant coping items was 1.5
(scores ranged from 0 to 6).

Who Are the Resilient?
Of the 174 respondents with complete data, 55
(31%) were classified as resilient, 79 (45%) were
classified as vulnerable, and 40 (24%) showed a
normative response. The vulnerable group tended
to report being exposed to a greater number of
adversities—More than one exposure was reported
by 87.3% of the vulnerable compared with only
47.3% of the resilient (p < .001).
The sociodemographic profile of the resilient
and the vulnerable groups was very similar with
the exception of age: The resilient were significantly younger compared with the vulnerable (Table 2).
There was some suggestion that women might also
dominate the resilient group (65.5% women among
the resilient as compared with 49.4% in the vulnerable, p = .065).
Several aspects of social relations were more
prevalent among the resilient than the vulnerable
(Table 3), including good quality of relationships
(p = .021), practical support from family (p = .019),
several close confiding relationships (p = .005),
having a wide circle of family (p = .030) and friends
(p = .020), contact in the past week with family
(p = .049) and friends (p = .019), and social integration in the community (p = .049).
Coping styles were found to characterize both
resilient and vulnerable outcomes (Table 4). More
than 60% of the resilient used highly developmental

What Typifies Psychosocial and Health-Related
Adversity?
The adversities varied in their prevalence with
124 of 174 reporting at least one negative life event
(Figure 1). However, other adversities affected
smaller proportions of the sample (health related
Vol. 50, No. 1, 2010

41

Figure 1. Prevalence of adversities and their impact on CASP-19 scores; the gray square signifies statistically nonsignificant difference in means.

results. None of the sociodemographic variables
including age suggested an effect whereby the full
impact of adversity was attenuated. However, having enough or more income than needed seemed to
reduce qol in those who were exposed to higher
levels of adversity (0.998, 95% confidence interval
[CI]: 0.282–0.769). In contrast, two variables relative to social networks and community as well as

(p = .010) and highly adaptive (p = .044) coping
styles compared with about 45% of the vulnerable
who reported using both these types of strategies. In
contrast, highly avoidant coping styles were far
more prevalent (67%) in the vulnerable group as
compared with the resilient group (46%, p = .018).
Which Individual or Social Attributes Are Effective
in Attenuating the Negative Impact of Adversity?

Table 2. Prevalence of Sociodemographic and Life Course
Factors in the Resilient (n = 55) and Vulnerable
(n = 79) Groups

Analyses examining factors that attenuate the
negative impact of adversity are based on n = 95
cases for high exposure to adversity and n = 79
cases for low exposure to adversity. These small
numbers might explain the relative lack of positive

Sociodemographic
and life course factors
Aged younger than 75
years
Female
Married or cohabiting
Higher educationa
Owner occupier
Nonmanual occupationb
Car access
Enough or more than
enough income
Low life course hazard
exposure
High childhood per
capita food
expenditure

Resilient
(%)

Vulnerable
(%)

p value

65.5

46.8

.033

65.5
58.2
45.5
83.6
65.5
74.1
87.8

49.4
70.9
48.1
81.0
65.8
72.2
77.6

.065
.128
.763
.697
.965
.806
.154

49.1

52.6

.693

49.1

50.6

.861

Note: aQualifications beyond Levels 1–3 of National Key
Learning Targets (General Certificate of Secondary Education,
O Level, A Level, National Vocational Qualifications Levels
1–3), including graduate and postgraduate academic qualifications and some vocational or professional qualifications.
b
Based on the Registrar General’s Social Class occupational
classification schema.

Figure 2. Quality of life (mean CASP-19 score) in the presence
of increasing number of adversities; means and 95% confidence intervals.

42

The Gerontologist

Table 4. Prevalence of Coping Styles in the Resilient (n = 55)
and Vulnerable (n = 79) Groups

Table 3. Prevalence of Social Networks and Community
Factors in the Resilient (n = 55) and Vulnerable
(n = 79) groups
Social networks and
community factors
Good quality of
relationships
Practical support
from family
Practical support
from friends
Emotional support
from family
Emotional support
from friends
Socializes with family
Socializes with friends
Several close confiding
relationships
Wide circle of family
Wide circle of friends
Frequent contact
with family
Frequent contact
with friends
Good neighborhood
community spirit
Integrated into
community

Resilient
(%)

Vulnerable
(%)

p value

66.0

45.5

.021

92.6

77.2

.019

22.2

35.4

88.9

87.3

.788

25.9

15.2

.125

59.3
75.9
81.5

50.6
68.4
58.2

.327
.343
.005

58.5
58.5
75.5

39.2
38.0
58.7

.030
.020
.049

63.0

42.1

.019

48.1

32.9

.077

85.5

70.9

.049

High developmental
coping
High adaptive coping
High avoidant coping

Vulnerable
(%)

p value

67.3

44.2

.010

63.5
46.2

45.5
67.1

.044
.018

is almost double the reported prevalence range for
resilience in the literature (Tusaie & Dyer, 2004).
Due to sample size limitations, we were forced to
use a generous threshold (better than average) to
represent flourishing, as a result the prevalence of
resilient outcomes in our sample may be somewhat
inflated. To some extent, the same bias could be
attributed to the findings that describe resilient
characteristics of older people or to the prevalence
of attributes defining the resilient and the vulnerable groups. However, such limitations are not seen
to compromise the analysis of factors that attenuate the impact of adversity (regression analysis).
Analysis and use of the adversity construct presented us with further dilemmas; adversities can
cluster within individuals, thus creating an overlap
between the adversities we used. In children, this
had been shown to be the case and without much
specificity between adversities in causing negative
adult outcomes (Kessler, Davis, & Kendler, 1997).
Therefore, our use of adversities additively is justified and was supported by the data that showed a
strong gradient relative to CASP-19 scores as these
adversities compounded. The disadvantage of this
approach was that we were unable to detect whether adversity-specific resilience exists.
Just one of the six adversities tested, financial
circumstances worsening, did not reach statistical
significance, only marginally affecting CASP-19
scores, and was excluded from further analysis.
This lack of negative association may be due to a
generational effect: the Boyd Orr generation grew
up under the shadow of World War II and were
likely to have experienced far more poverty in
childhood than more recent generations. This
could have made them inherently more adaptable
to such changes; the steeling effect alluded in the
quote by Nietzsche at the beginning of this article.
Financial circumstances were examined further
as a component of protection in subsequent analysis (having enough or more than enough income).
Paradoxically, the better off had less probability of
having better-than-average qol. This might be a

the two solution-driven coping styles were found
to attenuate the expected negative impact of high
adversity exposure, having seemingly no effect
when adversity was low (Table 5).
These factors included good quality of relationships (5.105, 95% CI 1.323–19.699), integration
in the community (10.800, 95% CI 1.227–95.014),
highly adaptive coping style (3.211, 95% CI
1.041–9.910), and highly developmental coping
style (3.397, 95% CI 1.079–10.690). Such attributes can be argued to promote resilience because
they are mobilized to buffer, transform, or negate
the full potential impact of clearly present adversity. No variables produced generally protective
effects (improved outcomes in both strata). Having a wide circle of family and friends improved
outcomes only in the low–adversity exposure strata (respectively, 5.988, 95% CI 1.401–25.593;
5.073, 95% CI 1.294–19.888), as did having several close confiding relationships (5.811, 95% CI
1.347–25.059).
Discussion
Resilience, as we define it here, was found in
almost one third of the Boyd Orr participants. This
Vol. 50, No. 1, 2010

Resilient
(%)

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Coping styles

43

Table 5. Factors That Confer a Protective Effect in the High–Adversity Exposure Strata (n = 95) But Have No Effect in the
Low–Adversity Exposure Strata (n = 79)a
Levels of adversity
Protective factors
Good quality of relationships
Integration in the community
High developmental coping
High adaptive coping

High, odds ratio (95% confidence interval)

Low, odds ratio (95% confidence interval)

5.105 (1.323–19.699)
10.800 (1.227–95.014)
3.397 (1.079–10.690)
3.211 (1.0 41–9.910)

3.843 (0.917–16.097)
2.976 (0.791–11.197)
3.823 (0.858–17.040)
2.065 (0.543–7.856)

a
Note: All characteristics were examined, only significant findings are reported here.

they also knew to draw on them when needed. Research has shown that existential concerns and
agency that produce this dynamic are equally present in older cognitively impaired populations, who
are active participants in producing and sustaining
qol (Hennessy, 2004).
Although psychologically resilient was primarily characterized by the capacity of adaptation and
development, sociologically resilient can be defined
by a process of exchange. Netuveli, Wiggins,
Montgomery, Hildon, and Blane (2008) described
resilience as the process that converts social goods
into good outcomes. In their longitudinal study of
resilience as bouncing back, the authors found that
social support before and during adversity promoted resilience. Social capital is widely seen as
the combination of social relationships that gives
access support (Gray, 2009). Our findings about
good quality of relationships and integration within the community are in agreement with Netuveli
and colleagues’ and seem to point toward social
capital as a key variable in the resilience process.
Like in the present study, Netuveli and colleagues
also found that the potential for resilience was reduced by concomitant adversities.
In lieu of the stratified approach we chose, other
authors have used interaction testing to identify relationships between adversity and personal attributes that produce resilience. Interaction testing
has been termed notoriously unstable (Luthar et
al., 2000) and for this reason can be difficult to
interpret. Roosa (2000) argues that in certain highrisk samples, interaction can be disguised as main
effects. Specifically, should researchers find a main
effect associated with positive adaptation in a highrisk group that is distinct from results on a mainstream (low risk) group, as was the case with our
data, this relationship suggests an interaction. The
data set was rich in a range of measures that formed
the basis of exploratory analysis but limited by
small sample size. We recommend more focused
quantitative research drawing on a larger sample

manifestation of a kind of disappointment paradox (Osika & Montgomery, 2008) whereby expected benefits from an advantageous factor are
overshadowed by the disappointment of being exposed to an adversity. This negative result suggests,
in terms of resilience at older ages, that insufficient
income may not be as threatening and indeed sufficient income may not be as protective as other,
perhaps less tangible, circumstances.
Accordingly, socioeconomic variables (e.g.,
home ownership) were not associated with resilient outcomes, in contrast to the range of social
network and community and coping characteristics that did characterize resilience. Several of these
seemingly protective characteristics also appeared
to attenuate the full impact of adversity that was
clearly present and threatening (two or more reports of adversity): two of them were psychological (developmental and adaptive coping style) and
two were social (good quality of relationships and
integration in the community). Because analysis of
resilient characteristics showed that the resilient
were more likely to have access to these forms of
protection in the first place, the resilient can be
viewed as more advantaged than the vulnerable
from the outset. It is also interesting that avoidant
coping was associated with vulnerability.
These combined results, taken with the finding
that the vulnerable reported more adversities than
the resilient participants (who were nevertheless
also exposed to significant adversity), suggest that
balancing processes are at work. And, that a
threshold of adversity, enough to define resilience
but not enough to engender vulnerability, is pivotal to these processes. Moreover, balancing processes seemingly hinge on avoiding multiple
adversity exposures as well as the capacity to acquire and use psychological and social resources to
offset potentially vulnerable outcomes. Indeed,
Werner and Smith (1982) found that a distinguishing feature of resilient children was not only that
they had access to social support networks but
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The Gerontologist

and experiences, which help to replace losses
prompted by bereavement or leaving work. In this
vein, we recommend greater funding provision to
enable active retirement, particularly for the retiring
disabled populations, who are more often unable to
access community resources (Llewellyn, 2004).
Polices that focus on productive aging and giving older people legitimate roles postretirement are
at present difficult to formulate. Many of the tasks
taken on by older people, such as grandchild care
and domestic duties, are characterized by their informal nature; some might argue that this is perhaps one of the best things about such practices.
We would argue that in terms of resilience, the role
of policy is to enable social engagement as a positive aspect of aging; productivity in old age seems
only to generate beneficial transactions when freely
chosen (Hildon et al., 2006). Overall therefore,
perhaps the greatest challenge for resilience-centered research is to move beyond findings into the
mainstream, where the benefits of social capital
and harnessing protective coping are understood
by both practitioner and lay people, with the result
that ultimately, the focus on the “right” way to acquire and use available resources is integrated and
understood as a key aspect of successful aging.

size and more diverse elderly populations to substantiate/refute our findings. Because quantitative
analysis can suggest process but may not always
fully capture the subtleties or dynamics that define
them, we also recommend qualitative or mixedmethods analysis.
Early in the study of resilience, Werner (1995,
p. 84) noted that “if we want to help vulnerable
youngsters become more resilient we need to decrease their exposure to potent risk factors and increase their competencies … as well as sources of
support they can draw on.” In the same vein, relative to older ages and given the findings on the central role increased adversity plays in resilience and
vulnerability, our recommendations for policy are
similarly two pronged: we must find effective ways
to minimize adversity and its impact where possible,
and to promote systems and services that can deliver support when necessary (Hildon et al., 2008).
Policies to increase the potential for resilience at
older ages should include a focus on improving
access to good quality social relationships and integration in the community as well as enabling and
engaging positive coping strategies. Such polices
should be geared toward helping to maintain enjoyable and supportive social relations and activities
(Blane, Wiggins, Montgomery, Hildon, & Netuveli,
2009), and facilitating self-management which
builds and draws on positive coping patterns
(Skinner & Vaughan, 1983). Interventions that stress
self-care through building on problem-solving coping strategies have proved particularly successful
in promoting resilient outcomes (Hill-Briggs &
Gernmell, 2007; Laforest et al., 2008). As for socially
focused policies, these include the recent extension
of the London Freedom Pass to all older people in
England or facilitating gradual retirements and
part-time voluntary positions for older people.
It is tempting to focus policy frameworks for
older ages around care issues surrounding the
Fourth Age, at which time the onset of disability has
become severe. However, enabling older people to
sustain and develop new places in the community,
through the Third Age (known as the period postretirement before the onset of severe disability), is
equally important. For example, by making student
loans available to retirees (Hildon, Netuveli, &
Blane, 2006), or by creating nationalized schemes
that channel prospective volunteers’ skills, retirements can be improved. Such policies would enable
resilience to be attained and acquired resources
would carry through to the onset of severe disability,
for example, new and enriching social networks
Vol. 50, No. 1, 2010

Funding
Economic and Social Research Council Grant L326253061.

Acknowledgments
We gratefully acknowledge the Boyd Orr respondents for their continued participation and commitment.

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Received December 3, 2008
Accepted March 16, 2009
Decision Editor: William J. McAuley, PhD

Appendix:
Method of Development and Analysis of a Coping
Index
Focus Groups
The coping items were developed and evaluated
using focus groups. Focus group members were
aged 68–84 years and lived in Fife (6 participants,
1 man and 5 women), Wirral (8 participants, 4
men and 4 women), and London (6 participants, 2
men and 4 women), which are areas containing
sizeable clusters of Boyd Orr cohort members. Initially, ways of coping were explored by guiding
discussion using open-ended questions about ways
of dealing with specific adversities such as health
problems or bereavement. Transcripts were analyzed
for the types of coping styles that were described
and a draft list of coping items complied.
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Drawing on the Literature and Expert Consensus

three, and four factors. The best fit was obtained
with the three-factor solution (root mean square
error approximation = 0.03; see Table A1 for factor
loadings).
Furthermore, using the same data, we did a confirmatory factor analysis using the three-factor
structure. The analysis showed moderate fit (Tucker
Lewis Index [TLI] = 0.84), which improved (TLI =
0.91) after modifying the model so that one item,
“life has no meaning,” was allowed to correlate with
all factors. We used the three factors from the EFA
as separate explanatory variables in our analyses.

In the second focus group, specific items in this
draft were discussed. These items were then reworked based on feedback and existing literature
on coping, including Staudinger and colleagues’
(1999) study exploring facets of psychological resilience and Lazarus’s (1980) classic conception of
coping as problem-solving or emotion-regulatory
functions. Items were finalized based on discussion
from a panel of four experts in gerontology and
social medicine and feedback from the last focus
group that discussed the clarity—rewording, order,
and applicability—of specific items.

Factor Labeling
These factors represent (a) avoidance, or ways
of not engaging with adversity, such as feeling stuck
with the problem; (b) adaptation, or ways of integrating adversity, for instance, by teaching oneself
how to live with a problem; and (c) developmental
coping, or moving beyond adversity in a positive
way, such as learning from a problem (see Appendix
Table 1 for item loadings). Scores for each of the
three dimensions were calculated by summing the
endorsements given for each of their items. All
three items were ranked and dichotomized into
high and low for use in subsequent analysis.

Factor Analysis
Once the item list was compiled and data gathered, we examined the resulting 20-item index. We
explored its structure by exploratory factor analysis
(EFA) using promax rotation. Because the items
were binary, we used MPlus version 4 for the analysis.
We also chose promax (oblique) over varimax (orthogonal) rotation because the former allows for
factors to be correlated, which is a valid assumption
as we have no reason to believe coping skills are
independent of each other. The EFA tested two,

Appendix
Table 1 Factor Loadings for the 20 Items Describing Coping
a

Component labels and item loadings
Coping items

Development

Learn from the experience
Be able to adapt to this change
Bounce back
Throw myself into activities
Past successes mean I will solve this problem too
Plan how to deal with the situation
Sense of humor will get me through
Seek information
Be stronger
Able to help others if they experience similar events
Teach myself to live with this problem
I will never really recover
Be appreciative of the simple things in life
Draw strength from faith
Get through this on my own
Numb my feelings with drugs and alcohol
Pretend it has not happened
Improve with the support of others
I will be stuck with the problem
There is no meaning to life

Adaptation

Avoidance

0.782
0.652
0.598
0.496
0.682
0.780
0.767
0.572
0.735
0.804
0.850
0.717
0.522
0.494
0.418
0.496
0.524
0.607
0.802
0.848

Note: aThe loadings are of factors generated by promax rotation, highest loadings are indicated and lower factor loadings
omitted for convenience.

Vol. 50, No. 1, 2010

47