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Volunteering and Well-Being: Do Self-Esteem, Optimism, and Perceived Control Mediate the Relationship?

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Volunteers play a vital role in modern societies by boosting the labor force within both the public and private sectors. While the factors that may lead people to volunteer have been investigated in a number of studies, the means by which volunteering contributes to the well-being of such volunteers is poorly understood. It has been suggested through studies that focus on the absence of depression in volunteers that self-esteem and sense of control may be major determinants of the increased well-being reported by volunteers. This is consistent with the homeostatic model of subjective well-being, which proposes that self-esteem, optimism, and perceived control act as buffers that mediate the relationship between environmental experience and subjective well-being (SWB). Using personal well-being as a more positive measure of well-being than absence of depression, this study further explored the possible mediating role of self-esteem, optimism, and perceived control in the relationship between volunteer status and well-being. Participants (N = 1,219) completed a 97-item survey as part of the Australian Unity Wellbeing project. Variables measured included personal well-being, self-esteem, optimism, and a number of personality and psychological adjustment factors. Analyses revealed that perceived control and optimism, but not self-esteem, mediated the relationship between volunteer status and personal well-being.
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Nonprofit and Voluntary Sector
http://nvs.sagepub.com/content/38/1/144
The online version of this article can be found at:
DOI: 10.1177/0899764008317971
May 2008
2009 38: 144 originally published online 23Nonprofit and Voluntary Sector Quarterly
Chambers and Robert Cummins
David Mellor, Yoko Hayashi, Mark Stokes, Lucy Firth, Lucy Lake, Michael Staples, Sue
Well-Being
Volunteering and Its Relationship With Personal and Neighborhood
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144
Nonprofit and Voluntary
Sector Quarterly
Volume 38 Number 1
February 2009 144-159
© 2009 Sage Publications
10.1177/0899764008317971
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Volunteering and Its
Relationship With Personal
and Neighborhood Well-Being
David Mellor
Yoko Hayashi
Mark Stokes
Deakin University
Lucy Firth
University of Melbourne
Lucy Lake
Barrett Consulting
Michael Staples
Crisis Support Services
Sue Chambers
National Trust of Australia
Robert Cummins
Deakin University
Although a relationship between volunteering and well-being has been demonstrated in
numerous studies, well-being has generally been poorly operationalized and often
defined by the relative absence of pathology. In this study, the authors take a positive
approach to defining well-being and investigate the relationship between volunteering
and personal and neighborhood well-being. The theoretical approach incorporates ele-
ments of the homeostatic model of well-being. A sample of 1,289 adults across
Australia completed a questionnaire that assessed personal and neighborhood well-
being, personality factors, and the psychosocial resources implicated in the homeosta-
tic model of well-being. Analyses reveal that volunteers had higher personal and
neighborhood well-being than nonvolunteers and that volunteering contributed addi-
tional variance in well-being even after psychosocial and personality factors were
accounted for. The findings are discussed in terms of previous research and the home-
ostatic model of well-being, and it is argued that the relationship between volunteering
and well-being is robust.
Keywords: volunteering; personal well-being; neighborhood well-being; psychoso-
cial resources
W
ith funding from governments often limited to the more essential public ser-
vices, volunteering plays a critical compensatory role within today’s society.
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Mellor et al. / Volunteering and Well-Being 145
Volunteer work involves a certain degree of planning and commitment with few of
the material benefits that normally result from paid work. Yet a significant number
of people are involved in some form of volunteering. In Western countries, the per-
centage of individuals older than 18 years of age engaged in volunteer activities
ranges from 27% in Canada to 48% in the United States (Penner, 2004). The per-
centage in Australia falls in the middle of this range (Strategic Policy and Research
Division, 2004). Although volunteering undoubtedly benefits those who are the
recipients of such services, given the popularity of volunteer work, it also appears
plausible to consider that there could be some benefits for those individuals who vol-
unteer as well.
Past research in the area of volunteering has attempted to answer the question of per-
sonal benefit through investigating predictors of, or exploring possible consequences of,
volunteering. One focus has been on the relationship between volunteering and physi-
cal health. A number of longitudinal studies (e.g., Moen, Dempster-McClain, &
Williams, 1992; Musick, Herzog, & House, 1999; Oman, Thoresen, & McMahon,
1999; Sabin, 1993; Yum & Lightfoot, 2005) have investigated the impact of volun-
teering on morbidity and mortality in large samples of older members of the commu-
nity. The results of these studies have been interpreted to indicate that volunteering
helps people stay healthy and live longer. However, these findings are subject to pos-
sible moderating and mediating effects, such that certain groups may benefit more
from volunteering, or psychosocial factors such as attending religious services regu-
larly may link volunteering to reduced morbidity and mortality. Despite this, Wilson
and Musick (1999) pointed out that all these studies “point in the same direction—
that volunteer work does help people live longer” (p. 152).
Psychological well-being has also been investigated as a possible benefit of vol-
unteering. However, it has been implicated as both a predictor and an outcome of the
individual’s involvement in volunteer activities (Krause, Herzog, & Baker, 1992;
Musick & Wilson, 2003; Van Willigen, 2000; Wheeler, Gorey, & Greenblatt, 1998).
Consideration of well-being as a predictor proposes that individuals with higher
levels of well-being are more likely to engage in volunteer work than those with
lower levels of well-being. Certainly cross-sectional studies have found that, com-
pared to nonvolunteers, volunteering is associated with higher levels of well-being,
as indicated by such markers as higher life satisfaction, fewer depressive symptoms,
and better physical health (Shmotkin, Blumstein, & Modan, 2003; Wheeler et al.,
1998). However, it is hard to tease out the causal direction of the relationship, and
longitudinal studies do seem to offer some insight into this reciprocal association
between volunteering and well-being, with each showing some impact on the other
(Li & Ferraro, 2005; Thoits & Hewitt, 2001).
Although these studies have definitely contributed some insights into the rela-
tionship between volunteering and well-being, two critical limitations are that the
conceptualization of well-being has often lacked clarity and the concept has been
used in inconsistent ways. For instance, in Thoits and Hewitt’s (2001) study, scales
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of life satisfaction and happiness were used to assess general well-being, scales of
self-esteem and mastery were used to measure psychological well-being, and scales
of physical health and depression were used to evaluate health-related well-being.
Other studies have used measures of depression to reflect the negative mental health
aspect of well-being (e.g., Krause et al., 1992; Musick & Wilson, 2003). However,
although studies have operationalized well-being in a variety of ways and their find-
ings provide converging support for the proposition that volunteering is related to
well-being, the majority of studies have tended to overlook the importance of pro-
viding a clear conceptual definition of well-being and the rationale for operational-
izing it as they have. They have rarely provided an explicit definition and theoretical
grounds of operationalizing well-being. This is unfortunate, as inconsistency in how
well-being is defined and operationalized limits what can be inferred from findings
of different studies. It is also surprising that despite research growth in the area of
well-being in past decades, volunteer research appears to have been largely over-
looked by literature in this area.
As reflected by the emergence of “positive psychology” (Seligman, 2002), the
concept of positive well-being has been increasingly capturing the attention of
researchers in recent years. Such renewed interest in people’s well-being, in addi-
tion or in contrast to the traditional focus on their ill-being, has expanded the idea
of what it means to live well and added novel attention to the potential significance
of inquiring into people’s subjective views of their well-being (e.g., Aspinwall &
Staudinger, 2003; Keyes & Haidt, 2003). Incorporating findings and conceptualiza-
tions from this well-being literature, the present study looks at two different aspects of
well-being—personal and neighborhood well-being—in relation to volunteering.
The concept of personal well-being (PWB) is defined as people’s own views of
their well-being and involves both cognitive and affective components (Diener &
Lucas, 1999). The emotional component of subjective well-being (SWB) is often
referred to as pleasant affect and happiness, and the cognitive component is described
in terms of cognitive judgment of life satisfaction (Diener, Suh, Lucas, & Smith,
1999). Affective and cognitive components are considered as empirically separate, yet
related, such that together they comprise the overall subjective evaluations of people’s
lives (Diener & Lucas, 1999). The study of SWB has a great implication for psy-
chology, as it provides insight into how people feel and think about their lives (Diener,
Oishi, & Lucas, 2003). Consistent with this view, SWB has been widely used in much
recent psychological research (Keyes, Shmotkin, & Ryff, 2002; Ryan & Deci, 2001).
PWB, as defined by the International Wellbeing Group (2005), is a practical
approach to understanding a person’s own view of their well-being as comprising mul-
tiple life domains that contribute to the whole experience of life quality. It is measured
through satisfaction with seven domains—standard of living, health, achieving in life,
relationships, safety, connection to community, and future security—that are derived
from an extensive review of research literature in the area of quality of life (Cummins,
McCabe, Romeo, & Gullone, 1994). Thus, although PWB may be considered as
146 Nonprofit and Voluntary Sector Quarterly
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Mellor et al. / Volunteering and Well-Being 147
another facet of SWB, as it is about people’s appraisals of their life, it goes beyond this
general life judgment by taking the seven specific life domains into account.
Nevertheless, when all the life domains are aggregated, PWB can be viewed as con-
ceptually equivalent to SWB, the overall appraisal of people’s life.
Cummins (2000) has proposed a model that depicts PWB as the outcome from a
combination of personality, which is proposed to provide affect balance; cognition
involving the “second order cognitive determinants” of self-esteem, optimism, and
control; and interaction with the environment. At least since the time of Hall (1973),
it has been proposed that PWB can be defined through these three elements. More
recently, subjective quality of life has been confirmed as having a strong trait com-
ponent (e.g., see McNeil, Stones, & Kozma, 1986) that explains about half of the
PWB variance (Tellegen et al., 1998).
It has now been established that when population means are used as data, people are
satisfied with their lives within the range of 70% to 80% of the measurement scale max-
imum score (percentage of scale maximum; Cummins, 1995). Cummins (1998) and
Cummins, Gullone, and Lau (2002) have argued that this restricted normative range
indicates that SWB is actively managed by a homeostatic system, in which self-esteem,
optimism, and perceived control play a role. Under normal conditions, external chal-
lenging events have little impact on SWB. However, this situation changes as the levels
of challenge reach levels that threaten homeostatic defeat. Under such conditions, and
most particularly if defeat is achieved, the challenging forces wrest control of SWB
away from the homeostatic system, and SWB falls (Cummins, Hughes, et al., 2007).
The other aspect of well-being that is explored in this study is neighborhood well-
being (NWB). NWB, or community well-being as it is sometimes called, can be
defined as people’s subjective experiences of living in a given community (Salt,
2002). Recently, NWB was proposed as a multidimensional construct involving
social or relational elements: trust; participation; common goals and reciprocity; as
well as material elements of security, the natural environment, and availability of
resources (Holloway, 2003). Such NWB largely reflects the social aspect of well-
being, which is considered by several researchers to be an essential building block
of overall well-being (e.g., Keyes & Waterman, 2003; Ryff & Singer, 1998). People
are embedded in their social situation: They live in a society, and socializing with
other members of their society is a critical part out of their lives. Considering the
social nature of our lives, it seems reasonable to incorporate this aspect into the over-
all model of well-being. That is, so long as our lives are embedded within a given
social context, the extent to which how we feel and think about living in such a con-
text is an important factor in determining our well-being as a whole (Keyes, 1998).
Therefore, investigating the social aspect in conjunction with the personal aspect of
well-being appears to be a vital process in understanding the overall picture of a
well-lived life.
Despite its conceptual relevance to overall well-being, research that has investigated
the social aspect of well-being, particularly NWB, is extremely scarce. Within this limited
literature, the social aspect of well-being has been found to be significantly related to both
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148 Nonprofit and Voluntary Sector Quarterly
affective and cognitive components (i.e., positive affect, happiness, and life satisfaction)
of SWB (Keyes, 1998, 2005). A study of volunteering gives a relevant ground for this rel-
atively unexplored area, because it involves a form of social engagement and activity, and
as well, it has been linked to the personal aspect of well-being.
Therefore, the present study attempted to address two gaps in the literature. First,
it embeds the concept of SWB within a theoretical framework to investigate its rela-
tionship with volunteering more theoretically. Second, it investigates for the first
time, the construct of NWB and its relationship with volunteering. Based on past
findings and theoretical literature, two hypotheses were explored: first, that volun-
teers would have significantly higher levels of SWB and NWB than nonvolunteers;
and second, that volunteering would significantly predict personal and NWB, even
in the presence of psychological resources.
Method
Participants
The participants were initially contacted through the Australian Unity Well-being
Index project. This project, which commenced in 2001, monitors the SWB of the
Australian population. Each new survey involves 2,000 people, new to the project,
who are 18 years old or older and fluent in English. Each sample has an even gender
composition and is representative of the geographic distribution of the population.
All reports and raw data from these surveys are available from http://www.deakin
.edu.au/research/acqol/index_wellbeing/index.htm.
At the end of an initial telephone interview, participants are asked whether they would
be willing to be involved with the project on a future occasion. Those who reply “yes”
are then followed-up with a paper questionnaire and recontacted on an annual basis
thereafter. The participants for the present study comprised those people from Surveys 5
and 10 who were being followed up on the second and first occasion, respectively.
The combined sample comprised 1,219 adults aged 18 to 88 years (M = 53.01,
SD = 15.02), with 701 females (57.5%) and 518 males (42.5%) located in postcodes
classified as “highly accessible” (n = 941), “accessible” (n = 205), “moderately acces-
sible” (n = 47), “remote” (n = 21), and “very remote” (n = 5), using the Accessibility/
Remoteness Index of Australia classifications (Commonwealth Department of Health
and Aged Care and National Key Centre for Social Applications of Geographic
Information Systems, 2001).
Measures
Participants completed a 97-item questionnaire that included measures of SWB
(personal and neighborhood), perceived control, optimism, self-esteem, volun-
teerism, and demographic questions.
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SWB was measured using the Personal Well-Being Index (PWI; International
Wellbeing Group, 2005) and the Neighborhood Well-Being Index (NWI; Holloway,
2003). The PWI consists of seven items, each prefaced with “How satisfied are you
with . . .” The stems are as follows: “your standard of living,” “your health,” “your
achievements in life,” “your personal relationships,” “how safe you feel,” “feeling
part of your community,” and “your future security.” Participants respond on an 11-point
scale ranging from very dissatisfied (0) to very satisfied (10), with neutral (5) as a
midpoint. Responses to each item are added to obtain the PWI score. The International
Wellbeing Group reported a reliability coefficient of .82 for this scale.
The NWI includes six items that ask respondents to indicate their degree of sat-
isfaction with trust, participation, common goals, natural environment, availability
of resources, and reciprocity in their neighborhood using the same format as the
PWI. The NWI scale has been shown to have good internal reliability with a
Cronbach’s alpha of .89 (Holloway, 2003).
Perceived Control strategies (primary and secondary control) were measured by
three item scales based on a selection of the items developed by Holloway (2003)
and reported by Chambers, Hollway, Parsons, and Wallage (2003). Each scale begins
with the statement, “When something bad happens to me” followed by stems such
as “I ask others for help or advice” (primary control) and “I remind myself some-
thing good may come of it” (secondary control). Participants indicated their agree-
ment with each item on an 11-point scale ranging from 0 = strongly disagree,5 =
neutral, to 10 = strongly agree. Chambers et al. (2003) reported Cronbach’s alphas
of .88 for primary, and .90 for secondary scales based on nine item scales for each
type. In this study, Cronbach’s alpha was .63 for primary control and .76 for secondary
control. A composite perceived control scale based on six perceived control items
was computed. This scale had a Cronbach’s alpha of .71.
Self-esteem was measured with the Rosenberg Self-Esteem Scale (Rosenberg,
1986). This scale is made up of 10 items. Five items are positively worded, and 5
negatively worded items are reverse scored. Item examples are, “I feel that I have a
number of good qualities” and “At times I feel that I am no good at all.” In this study,
an 11-point Likert-type scale response format was used, with 0 = strongly disagree,
5 = neutral, and 10 = strongly agree. Self-esteem scores are obtained by adding all
item responses, after the negatively worded item responses have been recoded. High
scores indicate a strong sense of self-esteem. The scale has sound psychometric
properties, with test-retest correlations typically being in the range of .82 to .88 and
Cronbach’s alpha for various samples being in the range of .77 to .88 (Rosenberg,
1986). In this study, alpha was .86.
Optimism was measured using the three positively worded items of the Revised Life
Orientation Test (Scheier & Carver, 1985): “In uncertain times, I usually expect the
best,” “I’m always optimistic about my future,” and “Overall, I expect more good things
to happen to me than bad.” Participants were asked to indicate the degree to which they
agreed with each of these items on an 11-point scale, ranging from 0 = strongly
Mellor et al. / Volunteering and Well-Being 149
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disagree,5 = neutral, to 10 = strongly agree. The three items have been previously
shown to have a Cronbach’s alpha of .68 (Lai, 1994). In this study, Cronbach’s alpha
was .82.
Volunteer status was determined by participants’ reponse to a single item that
asked, “Do you work as a volunteer outside your home?” A respondent who ticked
“yes” was classified as a volunteer, and a respondent who ticked “no” was classified
as a nonvolunteer. A total of 470 participants (39%) indicated that they worked as
volunteers. To further describe the profile of volunteers, the survey included mea-
sures of extraversion and neuroticism (Gosling, Rentfrow, & Swann, 2003), depres-
sion, anxiety, and stress (Lovibond & Lovibond, 1995).
Volunteers were also asked to provide an estimate of the hours of volunteer work
they did each week both in and outside their neighborhood and to indicate their level
of agreement with five statements about their voluntary work: “I am satisfied with the
time I spend in volunteer work,” “I am satisfied with the type of volunteer work I do,
“I volunteer because it benefits other people,” “My friends approve of my volunteer
activities,” and “I would feel guilty if I didn’t volunteer.” The responses used an
11-point scale ranging from 0 = strongly disagree,5 = neutral, to 10 = strongly agree.
Procedure
Surveys with a cover letter were sent to the participants who then completed them
and returned them in a reply-paid envelope. The questionnaires were designed to
take approximately 20 minutes to complete. Of the 3,113 questionnaires sent, 1,219
completed questionnaires were returned (39% response rate). Of these, the data of
13 participants were excluded from the analyses due to their failure to provide a
response on the volunteer activity question.
Results
Data were analyzed with SPSS for Windows statistical package (SPSS Inc, 2003).
After checking for accuracy of input and out-of-range values, 12 cases were deleted
due to there being missing data on more than two variables. Missing value analyses
were then conducted, which showed that all variables had less than 5% missing val-
ues. These were replaced by expectation maximization. Univariate outliers were
recoded to the mean plus/minus 3.29 SD for the scale, and remaining multivariate
outliers (n = 21) were deleted. Linearity and homoscedasticity were assessed as a
part of multiple regression analysis. Although an observation of a residual plot sug-
gests that the data did not conform stringently to these assumptions, as the sample
size is relatively large, no data transformation was conducted. After screening, 1,179
cases remained for the analyses. Scores on scales measuring the variables of interest
were converted to a standard 0 to 100 percentage point range (Cummins, 1995).
150 Nonprofit and Voluntary Sector Quarterly
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Mellor et al. / Volunteering and Well-Being 151
The profiles of volunteers and nonvolunteers were examined in relation to the
demographic variables and other measures. As the number of participants from remote
and very remote places (n = 26) was as expected very small, these were grouped with
the “moderately accessible” participants to form a “less accessible” group, thus pro-
viding three categories based on the remoteness of the geographic location where
participants lived: highly accessible, accessible, and less accessible.
Table 1 presents details of volunteer group differences. There were no significant
volunteer group effects for gender or income, but there were for the demographic vari-
ables of age and location. The significant age effect was based on a substantial increase
from 29% to 56% for volunteer participation rate across the age groups. There was also
a significant trend for higher proportions of volunteer participants in less accessible
locations (51.5%) than in accessible (44.2%) or highly accessible (37.4%) locations.
Volunteers reported that they spent about 4 hours each week in voluntary activity. They
were highly satisfied with the time spent volunteering (79 percentage points), the type
of volunteer work (84 points), the benefits of the volunteer work for other people (85
points), and friends’ approval of their volunteering (74 points), but indicated low agree-
ment for the item “I would feel guilty if I did not volunteer” (47 points).
As can be seen in Table 1, as hypothesized there was a significant difference
between the two groups in their PWB and NWB. Volunteers reported higher levels
of well-being in both PWB (M = 75.88, SD = 13.38) and NWB (M = 65.53, SD =
18.42), compared to nonvolunteers (PWB: M = 72.07, SD = 14.62; NWB: M = 61.98,
SD = 18.48). These differences were significant for both PWB, F(1, 1177) = 20.45,
p < .01, and NWB, F(1, 1177) = 10.47, p < .01. There were no interaction effects for
Volunteer Status × Location, F(2, 1157) = .53, p = .57, for PWB; and F(2, 1157) = .31,
p = .74, for NWB. Similarly, there were no interaction effects for Volunteer Status ×
Age, F(6, 1138) = .80, p =.57, for PWB; and F(6, 1138) = 1.33, p = .24, for NWB.
The analysis also established that there were substantial differences in the psycho-
logical profiles of the volunteers and the nonvolunteers. Volunteers were more likely
to be extroverted and optimistic and to perceive a greater sense of control in their
lives than nonvolunteers. They were also likely to be less neurotic than nonvolun-
teers. There was no difference between the groups with regard to self-reported
depression, anxiety, stress, and self-esteem.
The second hypothesis was tested by two hierarchical multiple regressions using
volunteering, personality traits, and psychological resources as predictors of PWB
and NWB. In both analyses, all variables except for volunteering were included in
the first step, and then volunteering was entered at the second step. Table 2 shows
the results of these analyses. The first analysis indicated that volunteering is a sig-
nificant predictor of PWB (β=–.08, p < .01). It contributed an additional 0.6%
(ΔR²
=
.006, p < .01) of the variance in PWB, even when contributions of other fac-
tors such as personality traits and psychological resources were accounted for.
Furthermore, optimism, self-esteem, depression, anxiety, and perceived control also
contributed significantly to PWB. Similarly, the second regression analysis also
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152 Nonprofit and Voluntary Sector Quarterly
suggested that volunteering is a significant predictor of NWB (β=–.06, p < .05). It
contributed an additional 0.3% (ΔR²
=
.003, p < .05) of the variance in NWB, even
when contributions of other factors were accounted for. Among other variables that
were included in this regression, optimism, self-esteem, depression, stress, and per-
ceived control were also significant predictors of NWB.
Table 1
Descriptive Results for Volunteer and Nonvolunteer Groups
Volunteer Nonvolunteer Test
Measure n % of Age Group n % of Age Group χ
2
Age Group 20.07**
18-25 14 29.2 34 70.8
26-45 33 31.1 73 68.9
36-45 83 38.8 131 61.2
46-55 93 35.1 172 64.9
56-65 115 41.4 163 58.6
65-75 80 45.7 95 54.3
76+ 46 56.1 36 43.9
Total 464 39.7 709 60.3
n % of Location n % of Location χ
2
Location
(Accessibility/
Remoteness
Index of
Australia) 7.74*
Highly accessible 343 37.3 566 72.7
Accessible 88 44.2 111 55.8
Less accessible 37 52.1 34 48.9
Total 468 39.7 711 60.3
MSDMSDF(1, 1177)
Personal well-being 75.88 13.38 72.07 14.62 20.45**
Neighborhood well-being 65.53 18.42 61.98 19.48 10.47**
Extraversion 56.84 25.55 52.61 25.86 7.60**
Neuroticism 27.04 20.08 29.93 21.92 5.26*
Depression 16.36 19.12 18.53 19.51 3.55
Optimism 69.80 17.62 66.59 18.47 8.81**
Anxiety 12.40 16.52 12.86 16.04 0.23
Stress 22.36 19.66 24.64 20.73 3.55
Self-esteem 76.68 15.75 75.57 17.40 1.24
Control 71.54 15.22 69.36 15.05 5.86*
*p < .05. **p < .01.
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Mellor et al. / Volunteering and Well-Being 153
Discussion
This study set out to investigate the relationship between volunteering and
PWB and NWB. As predicted by our first hypothesis, volunteers in this large
sample reported significantly higher well-being in both areas than their nonvolun-
teering counterparts did. This is consistent with a large body of previous research
(e.g., Li & Ferraro, 2005; Shmotkin et al., 2003; Thoits & Hewitt, 2001; Wheeler
et al., 1998) that has shown a relationship between volunteering and various mea-
sures that tap into the construct of PWB. However, that this relationship extends to
perceived NWB has not been previously documented. As noted earlier, NWB can be
argued to reflect the social aspect of well-being, which is considered by several
researchers (e.g., Keyes & Waterman, 2003; Ryff & Singer, 1998) to be an essential
building block of overall well-being. Our findings suggest that volunteering then is
related to the overall construct of subjective life quality. Furthermore, this relation-
ship exists across age groups and geographical locations, and no particular subgroup
benefits more from volunteering than other subgroups.
Our second hypothesis predicted that volunteering would have an impact on per-
sonal and NWB, even in the presence of psychosocial resources and personality
traits that are known to be predictive of well-being. The analyses indicated that for
both PWB and NWB, volunteering accounted for a significant amount of the vari-
ance, after the contribution of other predictors had been accounted for. This is an
important finding because it establishes that the relationship between volunteering
and well-being is not accounted for by other measured factors associated with both
well-being and volunteering.
Table 2
The Results of Hierarchical Multiple Regression Analyses
Personal Well-Being Neighborhood Well-Being
ΔR
2
ΔF βΔR
2
ΔF β
Step 1 .48 134.91** .18 33.08**
Extraversion .02 .04
Neuroticism –.03 .04
Optimism .21** .20**
Self-esteem .19** .12**
Depression –.19** .11*
Stress –.05 –.19**
Anxiety –.08* –.01
Control .14** .16**
Step 2 .006 14.19** .003 4.97*
Volunteer –.08** –.06*
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Although not the primary foci of this study, our data also provided other descriptors
of volunteers. Older people are more likely to volunteer than younger people. There
was a consistent significant pattern whereby each successive age grouping in our sam-
ple had a greater proportion of volunteers than those preceding it. Perhaps this finding
maybe due to generational differences in attitudes to society, whereby older people have
a more collective (social) orientation than younger people, or it may simply be due to
older people having progressively more time and personal resources to volunteer.
In a similar way, our data suggest that the less accessible location in which a per-
son lives, the more likely one is to volunteer, with more than half of those participants
in the least accessible locations volunteering, compared to less than a third in the most
accessible (urban) locations. It should be noted though that our least accessible category
was created by collapsing the remote, very remote, and moderately accessible cate-
gories of the Accessibility/Remoteness Index of Australia system. Nevertheless, it
seems that the more urban the community in which one lives, the less likely one is to
engage in volunteer activity. This is consistent with the common perception that
Australian rural and regional communities have a stronger social fabric structured
around sporting clubs and “mateship” than urban communities do.
Volunteers also exhibited more positive psychological attributes than nonvolun-
teers did. They were more extroverted, less neurotic, more optimistic, and had
greater perceived control than nonvolunteers. Although the direction of these asso-
ciations cannot be determined from this study, it is reasonable to argue that person-
ality factors such as higher extroversion and lower neuroticism are stable and
enduring, and may have predisposed or led the individual into volunteering, rather
than being a result of volunteer activity. On the other hand, perceived control and
optimism could either increase the likelihood of volunteering or be affected by
engagement in volunteering.
An interesting observation relates to the normal range of the PWI, in which com-
munity mean scores range between 73.4 and 76.4 points (Cummins, Woerner, Tomyn,
Gibson, & Knapp, 2007). Although the value for the volunteers lies comfortably within
this range (75.88 points), the value for the nonvolunteers lies below the range (72.07).
The reliability of this result is supported by the smaller standard deviation of the vol-
unteer group (13.38 vs. 14.62), precisely as required by homeostasis theory (Cummins,
2003). That is, as group means fall below the normal range, this indicates that such
groups contain a greater proportion of members in homeostatic distress. Their low
well-being enhances the tail of the distribution, and therefore the variance rises.
This picture of the volunteers as the less distressed group is also supported by an
inspection of the two multiple regressions. Again, according to theory (Cummins,
Lau, & Davern, in press), under benign conditions when homeostasis is operating
normally, the forces challenging such management should have little relationship
with SWB. After all, this is the purpose of the management system. However, this sit-
uation changes as the levels of challenge reach levels that threaten homeostatic defeat.
Under such conditions, and most particularly if defeat is achieved, the challenging
154 Nonprofit and Voluntary Sector Quarterly
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Mellor et al. / Volunteering and Well-Being 155
forces wrest control of SWB away from the homeostatic system. Such forces then show
a much stronger relationship with SWB at the expense of homeostasis. This picture is
consistent with the pattern seen in the two regressions. In the benign condition (volunteers),
the variables (other than volunteering) predict 48% of the variance in SWB. However,
in the nonvolunteer group, the explained variance drops to just 18%.
This is an interesting finding, because it hints that low well-being may decrease
the probability of volunteering. This direction of causation is rarely, if ever,
addressed by authors in this area, who almost inevitably emphasize the positive. For
example, Rozario, Morrow-Howell, and Hinterlong (2004) report that volunteer
activity correlates with higher perceived health. But such findings actually make
more sense in the negative—that nonvolunteers have low perceived health and that
is one of the factors inhibiting them from undertaking such activity.
This orientation leads to a very different view of the volunteering universe. It
posits that volunteering, a helpful activity within one’s community, is a normal
behavior that confers mutual benefits to the volunteer and to the recipients of his or
her labor. However, such behavior is contingent on the adequacy of personal
resources. By its very nature, volunteering requires motivation and the expenditure
of energy, which are in short supply for people who are themselves distressed. This
prediction has received support from a recent study of family carers in Australia
(Cummins, Hughes, et al., 2007). This large survey of more than 4,000 carers found
that just 7.8% were engaged in voluntary activity outside the home, compared with
over 30% in the general population (Strategic Policy and Research Division, 2004).
The carers were also a highly distressed group, with a median rating of moderate
depression and the lowest level of SWB so far determined in Australia (58.5 points).
It is therefore a reasonable causal interpretation that their lack of personal resources
inhibited the natural tendency to engage in volunteer activities outside their home.
This argument could also be made in relation to the findings of longitudinal stud-
ies that have found that volunteers have lower morbidity and lower mortality rates
that nonvolunteers do (e.g., Moen et al., 1992; Musick et al., 1999; Oman et al.,
1999; Sabin, 1993; Yum & Lightfoot, 2005). It may be that those older people who
do not volunteer have, for various reasons, fewer personal resources than volunteers
do, and this inhibits their tendency to engage in volunteer activity. This lack of per-
sonal resources and lower well-being may also be predisposing them to health prob-
lems that lead to higher morbidity and mortality rates. Thus, rather than seeing
volunteering as playing an enhancement role (Yum & Lightfoot), lack of engage-
ment in volunteering might be viewed as a risk factor.
Limitations of This Study
One limitation of this study is that it is cross-sectional in nature and the casual
direction of the relationship between volunteering and well-being cannot therefore be
determined. Strengths of the study are the use of a more theoretically based conceptual-
ization of well-being than that used in previous studies on this topic and the substantial
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156 Nonprofit and Voluntary Sector Quarterly
and reasonable representative sample size. A future longitudinal study including a
sample of people who do not volunteer but later on do so and who do volunteer but
later on do not would go some way to answering the question of causality.
A further limitation of this study was that a definition of volunteerism was not
provided in the questionnaire. A diverse range of definitions describing volunteerism
is apparent in the literature, and opinions are also likely to vary in the general pop-
ulation (Stukas & Dunlap, 2002). This study used the question, “Do you work as a
volunteer outside your home?” to which responses could reflect a great range of sit-
uations. Further research on volunteers might consider the inclusion of a clear and
comprehensive definition and a greater range of domains within the construct of vol-
unteerism so that a more elaborate understanding of the relationship between volun-
teering and well-being can be established.
Conclusion
The association between SWB and volunteer activity has been identified in a
number of previous studies. This study suggests that NWB is also associated with
volunteer activity, although the direction of this relationship could not be deter-
mined. Importantly, volunteering accounted for variance in both forms of well-being
even after the contribution of other cognitive and personality determinants had been
partialled out. This suggests that the relationship is worthy of further exploration.
The homeostatic model of well-being provides framework for this endeavor.
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Mellor et al. / Volunteering and Well-Being 159
David Mellor, PhD, is an associate professor in the School of Psychology at Deakin University. He is
involved in a range of research projects, including the Australian Unity Wellbeing project and several
projects associated with the well-being of older Australians.
Yoko Hayashi, has recently submitted her doctoral thesis at the School of Psychology at Deakin
University. The thesis was on meaning in life during midlife development.
Mark Stokes, PhD, is an associate professor in the School of Psychology at Deakin University. He is
actively involved in a number of research programs, including projects on sexuality and autism, evolu-
tionary models of behavior, and subjective well-being.
Lucy Firth, PhD, is director of strategic policy with the Department of Health and Community Service,
Northern Territory, Australia. She has extensive research experience in the area of economics and tech-
nology and has a particular interest in the economic impacts of technologies on people’s lives, especially
in the areas of health and quality of life.
Lucy Lake, is a consultant psychologist within a global human resource consulting firm, Barrett
Consulting. Her expertise lies within staff recruitment and development, focusing on improving staff
morale and assessing this impact on job satisfaction and well-being.
Michael Staples, is a counselor with Crisis Support Services, Mensline Australia and Beyondblue, the
national depression initiative. He is also a family relationships advisor at a Family Relationship Centre.
Sue Chambers, PhD, recently retired from her position of senior lecturer in psychology at Deakin
University. As a member of the Deakin research team studying well-being, she focused on defining neigh-
borhood well-being and its relationship to personal well-being.
Robert Cummins, PhD, has been a chair in the School of Psychology at Deakin University since 1997.
His special area of interest is research into quality of life, and he is recognized as an international author-
ity in this field.
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... Research has substantiated this assumption (for reviews, see Anderson et al., 2014;Piliavin & Siegl, 2015;Wilson, 2012), particularly for older volunteers in organizations that provide a supportive environment (Musick & Wilson, 2003;Van Willigen, 2000; but see Bjälkebring et al., 2021). Among other things, improvements in internal control beliefs and social relationships have been discussed as likely pathways from volunteering to a higher SWB (Brown et al., 2012;Fried et al., 2004;Krause et al., 1992;Mellor et al., 2008;Müller et al., 2014;Musick & Wilson, 2003;Pilkington et al., 2012). However, empirical tests of these pathways in a longitudinal framework are scarce and have not addressed moderating factors, such as age (for an exception, see Müller et al., 2014) or type of volunteering. ...
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