Journal of Gerontology: SOCIAL SCIENCES
2007, Vol. 62B, No. 4, S257–S266

Copyright 2007 by The Gerontological Society of America

Recovering From Spousal Bereavement in Later Life:
Does Volunteer Participation Play a Role?
Yunqing Li
New Jersey Department of Health and Senior Services, Trenton.
Objectives. Volunteering is an important component of social life but may be interrupted by life events. This research
investigated how widowhood influences subsequent volunteer participation as well as the potential moderating effect
volunteer participation may have in coping with the death of a spouse.
Methods. Analysis of three waves (1986–1994) of longitudinal data from the Americans’ Changing Lives study tested
(a) the effect of widowhood on volunteer participation, (b) the influence of the timing since becoming widowed on
volunteering and personal well-being, and (c) the interaction effects of volunteering and widowhood on personal wellbeing. A cross-sectional time-series design is used to test relationships with people aged 50 years and older at baseline.
Results. Compared with their continually married counterparts, people who experienced spousal loss reported greater
likelihood of pursuing volunteer roles, not immediately but a few years after the death of their spouse. Volunteer roles
adopted after spousal loss protected against depressive symptoms, and increases in volunteer hours enhanced self-efficacy.
Discussion. These patterns highlight the compensatory function of volunteer participation that helps to offset the
negative impact of widowhood on well-being in later life.

W

IDOWHOOD is one of the most stressful events in the
life course. The loss of a spouse initiates considerable
personal changes in well-being and social participation.
Research has shown that widowhood has negative impacts on
depression, anxiety, personal mastery, purpose in life, and life
satisfaction (Carr et al., 2000; Umberson, Wortman, & Kessler,
1992; Wilcox et al., 2003; Williams, 2003). Although some
forms of social participation are likely to decrease after the loss
of spouse, it is also possible that widowed persons seek more
social involvement outside of the marital relationship to
compensate for their loss (Ferraro, 1984).
A number of studies have examined the association between
widowhood and social engagement (Brown, House, & Smith,
2006; Ferraro, Mutran, & Barresi, 1984; Umberson et al., 1992;
Utz, Carr, Nesse, & Wortman, 2002). Aspects of social
engagement such as friendship support, formal social participation, and informal social interaction have received considerable attention. Volunteer participation per se has received less
attention, although it has been studied as a component of formal
social participation (Utz et al., 2002).
The effect of widowhood on volunteering merits attention,
given the ample evidence of a beneficial effect of volunteering
on mental health (Morrow-Howell, Hinterlong, Rozario, &
Tang, 2003; Musick & Wilson, 2003; Thoits & Hewitt, 2001;
Van Willigen, 2000). Might volunteer participation protect
against decrements in personal well-being among bereaved
spouses? Volunteer activities may provide a fresh outlet for
widows seeking social engagement, thereby mediating the
association between widowhood and personal well-being.
I designed the present research to examine the
relationships among widowhood, formal volunteering, and
indicators of personal well-being such as depressive symptoms
and self-efficacy in later life. The questions I sought to answer
included the following: (a) whether widowhood affects volunteer

participation over time, (b) whether the length of time one
has been widowed affects the change of volunteer participation as
well as depressive symptoms and self-efficacy, and (c) whether
volunteer participation before and after one is widowed protects
against subsequent depressive symptoms and the loss of selfefficacy. I based the analyses on three waves of data from the
Americans’ Changing Lives study (ACL; House, 1995).

Selective Compensation
An early sociological perspective that delineates a possible
relationship between widowhood and social participation in
later life is activity theory. It argues that people will adjust
better in later life if they are actively involved in social and
leisure activities and find substitutes for role losses (Havighurst,
Neugarten, & Tobin, 1968). Older adults see their new roles as
compensatory efforts for preserving their activity levels. These
arguments were further elaborated in a compensation model of
the adjustment to widowhood (Ferraro, 1984). Compensation
refers to behavioral and psychological efforts to maintain
adequate functioning in the face of loss (Carstensen, Hanson, &
Freund, 1995, p. 108). It may invoke new role involvement to
compensate for deficits in social integration after spousal loss.
Closely related to activity theory in several ways, socioemotional selectivity theory emphasizes selective compensation
in the face of loss. Over the life course, and especially in later
life, people selectively withdraw from social relations, but they
maintain those social relations that are most predictive and
supportive and that promote social support and feelings of
social embeddedness (Lang & Carstensen, 1994). Highly
consistent with the selective optimization with compensation
model (Baltes & Baltes, 1990), selectivity theory can be
considered the application of selective optimization with
compensation to the social realm (Carstensen, 1991, p. 213).
Through selective optimization, losses in personal life are

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countered by increasing investment in emotional meaningful
social interactions and events. People adopt social participations that strengthen self-identity while abandoning those that
carry less relevance to emotional well-being. The relatively
selective involvement in social activities after spousal loss
ensures that people optimize social and emotional capital
and minimize risks. A positive and well-regulated emotional
climate represents an important goal near the end of life
(Carstensen, 1995, p. 155).
Previous research has shown that many individuals experiencing widowhood compensate for their lost social ties and
interactions by seeking alternative means of social participation
(Knoke & Thomson, 1977). Active religious and volunteer
participation (Utz et al., 2002), informal helping (Brown et al.,
2006), and informal social interaction (Umberson et al., 1992)
are important in adjusting to bereavement. Social support from
friends and relatives often encourages bereaved persons to
increase their volunteer activities (Gallagher, 1994), which
provide a viable alternative to social disengagement for older
adults who have experienced spousal loss (Hunter & Linn,
1981). Volunteer work may contribute to better emotional
health by providing new and meaningful roles to offset the loss
of the marital role (Pillemer & Glasgow, 2000). Providing
support to others is a primary evolutionary function of close
relationships (Brown, House, Brown, & Smith, 2004). In a
marital relationship, a spouse is the primary target of helping
behaviors. The loss of a spouse often creates the opportunity
and the need to engage in helping activities outside the
relationship, which yields considerable adaptive advantages
because contributing to others’ well-being may help people feel
useful (Brown et al., 2006). This is especially important for
the newly bereaved because they tend to receive a high level
of social support, which may make them feel over-benefited
in social exchanges. Based upon the selective compensation
theory and volunteering literature, I contend that augmented
volunteer activities may be a compensatory device to help
reduce the risk of social isolation after spousal loss.

Social Consequences of Widowhood
Despite the longstanding theoretical interest in social compensation after role loss, few studies have actually examined
the relationship between loss of spouse and volunteering. To
my knowledge, Utz and colleagues (2002) conducted the only
published study to date that included a formal volunteering
indicator. They showed that people did not significantly
increase their formal social participation in the first 6 months
after becoming widowed. Because formal social participation in
their study was a scale developed by summing three items—
volunteer hours, frequency of formal meeting attendance, and
religious service attendance—the relationship between widowhood and subsequent volunteer participation is still unclear.
Another recent study on giving support to others after spousal
loss in late life also showed that it is unlikely that the newly
widowed significantly change their levels of helping behavior
within the first 6 months (Brown et al., 2004). Both of these
studies focused on short-term follow-up.
Research on widowhood has suggested that the amount of
time elapsed since one became widowed is an important factor
in assessing the consequence of this stressful life event (Carr,
2006). The deleterious effects of spousal loss on well-being are

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usually immediate and acute, but they typically attenuate over
time (Carr & Utz, 2002; Umberson et al., 1992). The initial
grief experience involves numbness, yearning, disorganization,
and despair (Parkes, 1970). The first year after the death of
a spouse is rife with change—from the initial outpouring of
sympathy from family members and intimate friends, to a deep
sense of abandonment, and then to a reengagement in social life
(Backman & Dixon, 1992; Ferraro, 1984). In the early stages of
¨
loss people also focus on practical challenges such as money
management and settling the estate. These patterns suggest that
older bereaved persons may only have the time and emotional
wherewithal to volunteer in the longer term following widowhood. Research has shown that the likelihood of reengaging
increases between 1 to 4 years after widowhood (Ferraro et al.,
1984). Four years allows a reasonable amount of time for
people to recover from the spousal loss and reorganize their
behavior. Therefore, I hypothesized that widowhood would be
associated with an increase in volunteer participation between
1 to 4 years after the death of one’s spouse. The bereaved people would either become volunteers or increase their level of
volunteer participation if they were already volunteers.

Benefits of Volunteering
It is possible that volunteer participation mitigates the
negative impacts of widowhood on personal well-being (Cohen
& Wills, 1985; Wheaton, 1985). Volunteer participation is
likely to reduce stress because it contributes to positive
emotions (Pillemer & Glasgow, 2000) and facilitates social
support and social interactions (Musick & Wilson, 2003).
Positive emotions speed recovery from cardiovascular stress
(Fredrickson, Mancuso, Branigan, & Tugade, 2000). Social
support and social interactions provide social and psychological
resources that help people compensate for losses associated
with negative life events (Carstensen et al., 1995). Moreover,
volunteer activities are likely to bolster self-regulation of health
behaviors (Williams, 2004). In later life, spouses are the
primary source of health regulation. The loss of a spouse makes
a widowed person especially vulnerable to health risks such as
lack of exercise, improper nutrition, and alcohol abuse. By
providing a sense of meaning in life, volunteer participation
may encourage individuals to engage in health-promoting
behaviors and, thus, reduce the negative impact of widowhood
on personal well-being.
Little existing research has explicated the role of formal
volunteering during recovery from spousal bereavement in later
life. One study showed that voluntary association membership
has a stress-buffering effect on depressive symptoms in the
presence of multiple stressors in life (Rietschlin, 1998). In
another study, providing informal help to others appeared to
buffer against the risk of depression following bereavement
(Brown et al., 2006). However, these studies did not examine formal volunteer activities. It is also not clear in the
volunteering literature whether formal volunteering promotes
self-efficacy after bereavement. Research on the effect of
volunteering on self-efficacy is relatively scarce, probably due
to the fact that self-efficacy is more of a personality characteristic than of an indicator of psychological well-being
(Thoits & Hewitt, 2001). Self-efficacy refers to ‘‘beliefs about
one’s ability to bring about desired outcomes’’ (Miller
& Lachman, 1999, p. 22). It emphasizes a sense of control

VOLUNTEERING AND WIDOWHOOD IN LATER LIFE

and is often used interchangeably with control. It is critically
important that people maintain a sense of control in their lives
after spousal loss. Because volunteering is an efficacious action,
one would expect that it bolsters the feeling of control.
Consequently, I hypothesized that formal volunteer participation would act as a coping resource to buffer the negative
impacts of widowhood on both depressive symptoms and selfefficacy. It is reasonable to expect an immediate increase in
depressive symptoms and a decrease in self-efficacy following
spousal loss. However, I hypothesized that between 1 to 4 years
after widowhood, volunteer activity would reduce depressive
symptoms and enhance self-efficacy.
The purpose of this research was threefold. First, by investigating the effect of widowhood on volunteer participation
in later life, this study examined a relatively understudied
research topic on the social consequences of widowhood.
Second, I strived to understand whether active volunteer participation would help to ease the psychosocial adjustment to
widowhood in later life. Third, this research problem provided
a meaningful opportunity to consider the utility of compensatory models of adjustment in later life. By doing so, this
research sought to better understand the functions of social
integration during major transitions in later life.

METHODS

Sample
This research used data from the ACL study, which is
a multistage stratified area probability sample of persons 24
years of age or older who lived in the continental United States.
Baseline data were collected in 1986 (N ¼ 3,617) and included
an oversampling of Black adults (n ¼ 1,174) and persons 60
years of age or older (n ¼ 1,669). Two follow-up interviews
were successfully completed in 1989 and 1994. All interviews
were face to face and were conducted in the home of the
respondent.
I based this analysis upon respondents who were 50 years
of age and older and who were either currently married or
currently widowed at baseline. Because only 9 widowed
respondents remarried between 1986 and 1994, I excluded
them from the analytic sample. In a sample restricted to older
adults, widowhood is more prevalent and is likely to have
occurred after children reached adolescence or adulthood
(Elder, Johnson, & Crosnoe, 2003). The analytic sample
included 1,731 respondents, of whom 1,366 were reinterviewed
in 1989. In 1994, 1,137 of the baseline respondents were
relocated and reinterviewed. The respondents in 1994 included
92 people who had been interviewed in 1986 but had not
responded in 1989. The living nonresponse rate was 14.3% at
Wave 2 (W2) and 10.3% at Wave 3 (W3). By the end of W3,
24% of the analytic sample had died. All analyses in the present
study were weighted to adjust for the oversampling of special
populations and sample attrition that occurred between waves.

Missing Data
Previous research has shown substantial nonrandom attrition
in this longitudinal sample (Li & Ferraro, 2005). People who
did not complete the 8-year study had less education, lower
income, greater functional impairment, more depressive symp-

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toms, and lower levels of both formal and informal social
integration. To account for nonrandom attrition, I used two
different methods. First, I used a two-step Heckman maximum likelihood estimation model (Berk, 1983; Heckman,
1979) to account for possible sample selection bias from attrition that occurred before W2. Attrition consisted of all people
who had died by W2, and people who did not respond at
W2 and who either died afterwards or did not respond at W3.
This type of missing data is usually non-ignorable (Allison,
2001). In the first step, I obtained a hazard instrument from the
Heckman selection model. This hazard instrument represented
the probability of attrition of a person who remained in the
sample. People scoring high on this variable had higher likelihood of becoming missing. In the second step, I added this
hazard instrument to the regression model as a covariate. A
statistically significant hazard instrument suggests serious
sample selection bias. However, by controlling for the hazard
instrument, I adjusted the model coefficients to account for the
nonrandom attrition.
Second, I used multiple imputation through the Markov
Chain Monte Carlo method to impute values for three other
types of living nonresponse. Multiple imputation is a preferred
technique for completing missing data that one can assume is
missing at random. The multiple imputation generated five
independent data sets without missing data (Schafer, 1997).
Later, I conducted identical regression analyses on each data set
and combined the results to produce less biased estimations of
parameter estimates and standard errors (Rubin, 1987). The
values imputed included the W2 values for the people who
were widowed at Wave 1 (W1) but did not respond at W2, the
W2 values for people who did not respond at W2 but were
relocated and reinterviewed at W3, and the W3 values for
people who were widowed at W2 but did not respond at W3. I
did not impute values for people who were married before they
became missing because I could not predict their marital status
at the subsequent waves. I imputed a total of 203 cases for
either W2 or their W3 values. By restoring these cases, about
10% of the total sample, I achieved much stronger statistical
power in my model estimates. After multiple imputation, the
sample size for W2 was 1,516 and for W3 was 1,179.

Analytic Approach
My analyses were based on a standard cross-sectional timeseries design. I reformatted the ACL three-wave data into two
survey waves, with information on the respondent at the current
survey wave (Time 2) and the previous wave (Time 1). The
1,179 respondents who completed all three waves of the ACL
study contributed two observations after the ACL data were
pooled. Time 1 (T1) and Time 2 (T2) for their first observation
were 1986 and 1989, and for their second observation were
1989 and 1994. An additional 337 respondents who participated only in W1 and W2 of the ACL data collection each
contributed one observation. T1 and T2 for their observation
were 1986 and 1989. The final sample size under the new data
format was 2,695. I adjusted the robust standard errors for the
clustering of observations within individuals using sample
weight and the clustering of the primary sampling units
available in the ACL study. I estimated all models in STATA
8.0 (StataCorp, 2003).

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One of the advantages of this approach is that it uses the
maximum amount of information about the respondents.
Because attrition was gradual over time, except for persons
who left the study before the first follow-up interview in 1989,
all other respondents are included in the analysis and contributed at least one observation. The second advantage is
an increase in statistical power in the analysis. For example,
after I reformatted the data, people who had become widowed
either between 1986 and 1989 (n ¼ 93) or between 1989 and
1994 (n ¼ 108) were grouped into the same category ‘‘widowed
between T1 and T2.’’ The increase in the number of respondents widowed between measurements enhances statistical power to detect significant effects of widowhood on
changes in volunteer participation and well-being (Ferraro &
Wilmoth, 2000).

Measures
Depressive symptoms. —In the ACL study, depressive
symptomatology consisted of 11 items from the Center for
Epidemiologic Studies–Depression scale (Radloff, 1977). The
items measured whether respondents in the past week felt
happy, depressed, sad, lonely, like everything was an effort,
that sleep was restless, that people were unfriendly, that people
disliked them, that they could not get going, that they had
a poor appetite, and that they enjoyed life. All 11 items had the
same response categories: 1 ¼ hardly ever, 2 ¼ some of the
time, and 3 ¼ most of the time. The answers for the positive
items were reverse coded. The ACL staff developed an index
by standardizing the arithmetic means of the 11 items at each
wave. I used the standardized index in the analysis. The internal
consistency of the standardized index as measured by coefficient alpha equaled .83 at W1, .82 at W2, and .83 at W3.
Self-efficacy. —In the ACL study, self-efficacy included six
questions: (a) ‘‘I take a positive attitude toward myself,’’ (b)
‘‘At times, I think I am no good at all,’’ (c) ‘‘All in all, I am
inclined to feel that I am a failure,’’ (d) ‘‘I can do just about
anything I really set my mind to do,’’ (e) ‘‘Sometimes, I feel
that I am being pushed around in life,’’ and (f) ‘‘There is really
no way I can solve the problem I have.’’ Responses were coded
1 ¼ strongly agree to 4 ¼ strongly disagree. After reversecoding the positively worded items, the ACL staff developed an
index by standardizing the arithmetic means of all the items at
each wave. High values on this standardized index indicated
a high level of self-efficacy. The coefficient alpha equaled .67 at
W1, .67 at W2, and .65 at W3.
Volunteer role. —The interviewer asked respondents whether
they had done any of five types of volunteer work during the
past 12 months: volunteering in (a) church, synagogue, or other
religious organization; (b) school or educational organization;
(c) political group or labor union; (d) senior citizen group; and
(e) other national or local organization. I created a dummy
variable for the volunteer role, scoring people 0 if they had not
volunteered and 1 if they had volunteered for any type of
organization.
Volunteer hours. —This measured the number of hours
the respondents spent doing formal volunteer work during the

LI

past year. It contained six survey response categories, where
0 was assigned to people who had not participated. The
other responses included volunteering for less than 20 hr (1),
20 to 39 hr (2), 40 to 79 hr (3), 80 to 159 hr (4), and 160 hr or
more (5).
Widowhood variables. —These reflected the amount of
time elapsed since one had become widowed. I used a number
of variables indicating the timing of widowhood to construct
four dichotomous widowhood indicators: widowed more than
3 years before W1, within 3 years before W1, between W1
and W2, and between W2 and W3. The reference category
was ‘‘continually married.’’ After reformatting the data into
two survey times, I combined the four variables into three,
indicating widowed (a) more than 3 years before T1, (b) within
3 years before T1, and (c) sometime between T1 and T2. In
terms of years, they represented widowed more than 7 years,
about 4 to 7 years, and about 1 to 4 years before T2
measurement, respectively. I used these three variables in the
final analysis.

Control Variables
The analyses controlled for a series of T1 variables that
were likely to be associated with volunteering and personal
well-being outcomes at T2. Because formal meeting attendance and physical activities did not significantly predict
volunteering in preliminary analyses, for parsimony I deleted
them from the models in which volunteer participation was the
outcome variable. I controlled for two additional variables—
hazard instrument and recent survey year—in all regression
models. I obtained the hazard instrument from the Heckman
selection model as described in the ‘‘Missing Data’’ section.
Recent survey year was a binary variable that identified the
actual survey year of the ACL study after the three-wave data
had been reformatted for the cross-sectional time-series design
containing two time points. The variable was coded 1 if T2
data were from 1994 and 0 if T2 data were from 1989. A significant survey year variable captured the period effect indicating that people would be more likely to volunteer (or be
depressed) in a given year.
Formal social integration. —I included two measures.
Formal meeting attendance was measured by asking the
question ‘‘How often do you attend meeting of groups, clubs,
or organizations you belong to?’’. Responses were coded 1 ¼
never, 2 ¼ less than once a month, 3 ¼ about once a month, 4 ¼
2 or 3 times a month, 5 ¼ once a week, and 6 ¼ more than once
a week. Religious service attendance was measured by the
question ‘‘How often do you usually attend religious services?’’. This variable had the same coding as formal meeting
attendance.
Informal social integration. —This was a standardized index
constructed by taking the arithmetic means of the following
two items: (a) how often in a typical week the respondent talked
on the telephone with friends, neighbors, or relatives; and (b)
how often the respondent got together with friends, relatives,
or neighbors. Responses for the first item ranged from 1 ¼ never
to 6 ¼ more than once a day, and for the second item from 1 ¼
never to 6 ¼ more than once a week.

VOLUNTEERING AND WIDOWHOOD IN LATER LIFE

Physical activities. —Respondents indicated how often they
(a) worked in their garden or yard, (b) engaged in active sports
or exercise, and (c) took walks. Responses were coded from 1 ¼
never to 4 ¼ often. The ACL staff constructed the index by
standardizing the arithmetic mean of the three items. Higher
values indicated higher levels of physical activities.
Functional impairment. —This measured the degree to which
the respondent had difficulty performing a variety of daily tasks
such as bathing by himself or herself, climbing a few flights of
stairs, walking several blocks, and doing heavy work around
the house. This was an index measure coded from 1 ¼ no
functional impairment to 4 ¼ most severe impairment.
Demographic variables. —Education represented the highest
number of years of schooling completed and ranged from
0 to 17. Total annual family income was measured with 10
categories ranging from 1 ¼ less than $5,000 to 10 ¼ more than
$80,000. Employed was coded 1 for persons employed full or
part time and 0 for those not employed. Age was measured in
years (50–96). Gender and race were two binary variables, with
female and Black each coded 1.

RESULTS

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Table 1. Range of Indicators, Weighted Means, and Standard
Deviations: Americans’ Changing Lives, 1986–1994
Variable
Depressive symptoms, T1
Depressive symptoms, T2
Self-efficacy, T1
Self-efficacy, T2
Volunteer role, T1
Volunteer role, T2
Volunteer hours, T1
Volunteer hours, T2
Widowed more than 3 years before T1
Widowed within 3 years before T1
Widowed between T1 and T2
Age, T1
Female
Black
Education, T1
Income, T1
Employed, T1
Functional impairment, T1
Formal meeting attendance, T1
Church attendance, T1
Informal social interaction, T1
Physical activities, T1
Recent survey year
Hazard instrument

Range
À1.49–4.25
À1.55–4.38
À4.39–1.61
À4.74–1.91
0–1
0–1
0–5
0–5
0–1
0–1
0–1
50–99
0–1
0–1
0–17
1–10
0–1
1–4
1–6
1–6
À3.07–1.54
À2.69–1.84
0–1
.01–1.02

M

SD

À0.13
À0.13
0.03
À0.05
0.41
0.42
1.16
1.15
0.20
0.06
0.07
65.53
0.59
0.09
11.31
4.98
0.39
1.49
2.91
3.69
0.05
À0.18
0.45
0.23

0.90
0.92
0.98
1.03
0.49
0.49
1.68
1.61
0.40
0.23
0.25
9.16
0.49
0.28
3.39
2.62
0.49
0.86
1.83
1.81
0.96
1.04
0.50
0.16

Notes: N ¼ 2,695. T1 ¼ Time 1; T2 ¼ Time 2; SD ¼ standard deviation.

Widowhood and Volunteer Participation
Table 1 presents the ranges, weighted means, and standard
deviations for all variables in the analysis. They showed that
relatively small proportions of people had become widowed
within 3 years before T1 (6%) or between T1 and T2 (7%). To
test the effect of widowhood on volunteer role, I regressed
volunteer role at T2 on widowhood variables, volunteer role at
T1, other T1 covariates, recent survey year, and hazard
instrument (results in Table 2). The highly significant volunteer
role at T1 increased the likelihood of volunteer participation
over time. Among the three widowhood indicators, widowed
between T1 and T2 moderately increased volunteering at T2.
Given that only 7% of the sample had experienced widowhood
between measurements, the modest effect identified here is
truly noteworthy. The odds of becoming a volunteer increased
by 48.4% for people widowed between 1 to 4 years than for
people continually married during the same period of time.
This model also supported the hypothesis regarding the
timing of widowhood. People who had been widowed for more
than 4 years did not show an increase in volunteer participation
at T2. Also in this model, age had a negative effect on volunteer
participation at T2. Three social and personal characteristics
were related to an increase in volunteer participation over time.
They were better education, higher income, and frequent
religious service attendance. The positively significant recent
survey year variable indicated a higher likelihood of becoming
a volunteer in 1994 than in 1989. The nonsignificant hazard
instrument suggested that nonrandom attrition was not a serious
problem in this model.
Secondly, I used a residualized regression model to test the
effect of widowhood on the increase in volunteer hours over
time. Volunteer hours at T2 were modeled as a function of T1
volunteer hours and the independent variables. It predicted
change in volunteer hours between T1 and T2 (Allison, 1990).

The last column of Table 2 displays these results. Widowhood
indicators did not appear to influence volunteer hours over time.
Besides volunteer hours at T1, better education and frequent
church attendance at T1 led to a significant increase in
volunteer participation at T2. The significant negative effect
of recent survey year suggested that volunteer hours were more
likely to decrease in 1994 than in 1989.

Widowhood, Volunteer Participation, and Well-Being
I used residualized regression models to test (a) whether the
timing of widowhood affected depressive symptoms and selfefficacy, and (b) whether volunteer role and volunteer hours
moderated the effect of widowhood on depressive symptoms
and self-efficacy. Because volunteer hours may have exerted
nonlinear effects (Van Willigen, 2000), I used second-order
polynomial regression analysis to account for the possible
nonlinear effects of volunteer hours. Volunteer hours variables
were centered around the means in order to avoid a lack of scale
invariance in regression equations containing interactions and
problems of multicollinearity when testing curvilinear relationships (Aiken & West, 1991). I first regressed depressive
symptoms and self-efficacy at T2 on their T1 measures,
widowhood variables, volunteer variables at T1, and other
control variables. Next, I added interaction terms between
widowhood indicators and volunteer variables to assess the
moderating effect of volunteering in the relationships between
widowhood and depressive symptoms and between widowhood
and self-efficacy. Table 3 presents the results as Models 1 to 4
for depressive symptoms and Models 5 to 8 for self-efficacy.
In Model 1, volunteer role at T1 moderately reduced the
increase in depressive symptoms at T2. People who had been
widowed for a long period of time (more than 7 years) were

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Table 2. Effects of Widowhood on Change in Volunteer Role and Volunteer Hours From T1 to T2 Among Americans
Aged 50 and Older: Americans’ Changing Lives, 1986–1994
T2 Volunteer Rolea
Coefficient (Robust SE)

Variable
c

Widowed more than 3 years before T1
Widowed within 3 years before T1
Widowed between T1 and T2

0.158 (.199)
À0.058 (.263)
0.395* (.226)

d

Odds Ratio
1.171
0.944
1.484

T2 Volunteer Hoursb
0.040d (.096)
0.109 (.145)
0.141 (.101)

T1 control variables
Volunteer role, T1
Volunteer hours, T1
Age
Female
Black
Education
Income
Employed
Depressive symptoms
Functional impairment
Church attendance
Informal social interaction
Recent survey year
Hazard instrument
Constant
Adjusted R2
N

2.176*** (.135)

8.811

À0.024*
À0.051
À0.090
0.078***
0.054*
0.029
À0.071
0.018
0.239***
0.101
0.304*
0.082

(.012)
(.193)
(.153)
(.022)
(.029)
(.175)
(.090)
(.118)
(.043)
(.075)
(.132)
(.708)

0.976
0.950
0.914
1.081
1.055
1.029
0.931
1.018
1.270
1.106
1.355
1.085

À2.009** (.741)

0.134

2,695

0.529***
À0.003
À0.028
À0.073
0.044***
0.012
À0.074
À0.047
À0.021
0.077***
0.028
À0.206**
À0.145

(.028)
(.006)
(.082)
(.062)
(.011)
(.015)
(.095)
(.033)
(.045)
(.019)
(.032)
(.067)
(.309)

0.086 (.408)
.395
2,695

Notes: T1 ¼ Time 1; T1 ¼ Time 2; SE ¼ standard error.
a
Binary logistic regression.
b
Residualized regression.
c
Reference category is continually married from Time 1 to Time 2.
d
Unstandardized regression coefficient (robust SE).
*p , .05; **p , .01; ***p , .001 (one-tailed).

somewhat depressed. People who had become widowed within
the 1 to 4 years prior to T2 measurement showed elevated
depressive symptoms compared to people who had been
continually married during the same period of time.
The results in Model 2 revealed a stress-buffering effect of
volunteer role on depressive symptoms at T2. In the presence of
a significant interaction between widowed within 3 years before
T1 and volunteer role at T1 (b ¼ À.330; p , .05), the main
effect of widowed within 3 years before T1 became highly
significant. These significant effects indicated that although
widowed within 3 years before T1 was associated with an
increase in depressive symptoms at T2, because of the
interaction effect, the magnitude declined substantially for
people who became volunteers at T1 (.219 for nonvolunteers;
.219 À .330 ¼ À.111 for volunteers). The interaction between
volunteer role and widowed between measurements was not
significant. People who had volunteered before becoming
widowed experienced a similar negative impact of spousal loss
as those who had not been volunteers.
In Model 3, volunteer hours at T1 were associated with fewer
depressive symptoms at T2. Although people who had been
widowed for more than 7 years and those who had become
widowed within the past 4 years were more depressed at T2
compared with their continually married counterparts, people
widowed more recently manifested more depressive symptoms
(b ¼ .275). With the addition of the interaction terms, volunteer
hours no longer significantly predicted depressive symptoms
(Model 4). The interaction between volunteer hours and
widowed between measurement was modest (b ¼ À.081,

p , .05), suggesting that people who had volunteered at
higher levels before spousal loss coped better with depressive
symptoms at T2.
A number of T1 covariates predicted depressive symptoms at
T2 in all four models. Women and people with greater functional impairment were more depressed at T2. Better education
helped to reduce depressive symptoms at T2. Increased age was
also associated with fewer depressive symptoms at T2.
Consistent with the age effect, recent survey year negatively
predicted depressive symptoms, indicating that the respondents
tended to be less depressed in 1994 than in 1989. The significant hazard instrument suggested that more depressed people
had a higher likelihood of dropping out of the sample.
Models 5 to 8 in Table 3 are parallel to Models 1 to 4, but
with a different outcome variable—self-efficacy. In Model 5,
people who had become widowed within the past 4 years
showed a much lower sense of self-efficacy than people who
had been continually married. Volunteer role at T1 did not lead
to an increase in self-efficacy at T2. Despite the addition of
interaction terms between volunteer role and widowhood
indicators, Models 5 and 6 were similar in terms of all
regression coefficients. None of the interaction terms were
significant, indicating that the moderating effect of volunteer
role on self-efficacy was minimal. Volunteer role did not
improve self-efficacy after spousal loss.
In both Models 7 and 8, I deleted the nonsignificant secondorder volunteer hours term. In Model 7, volunteer hours at T1
had a modest positive effect on self-efficacy at T2. People who
had become widowed within 1 to 4 years prior to measurement

Model 1

(.004)
(.055)
(.067)
(.006)
(.008)
(.058)
(.030)
(.014)
(.011)
(.026)
(.023)
(.049)
(.239)

.336 (.252)
.350
2,695

À.008*
.113*
.099
À.018**
À.012
.001
.061*
À.020
.017
.007
À.008
À.093*
1.021***

.435*** (.032)

.142* (.075)
.102 (.085)
.274** (.092)
—
—
—

À.094* (.045)a

Model 2

(.087)
(.106)
(.133)
(.074)
(.145)
(.161)

(.004)
(.055)
(.066)
(.006)
(.008)
(.058)
(.030)
(.014)
(.011)
(.026)
(.023)
(.049)
(.240)

.311 (.251)
.353
2,695

À.009*
.118*
.099
À.018**
À.012
.004
.061*
À.020
.017
.007
À.006
À.086*
1.045***

.434*** (.032)

.160*
.219*
.370**
À.031
À.330*
À.238

À.056 (.051)
(.025)
(.008)
(.076)
(.085)
(.093)

(.004)
(.055)
(.067)
(.006)
(.008)
(.059)
(.030)
(.015)
(.010)
(.026)
(.023)
(.049)
(.238)
.283 (.246)
.350
2,695

À.008*
.112*
.097
À.018**
À.012
.002
.062*
À.021
.016
.006
À.009
À.091*
1.029***

.435*** (.032)

—
—
—

À.043*
.011
.144*
.103
.275**

Model 3
(.026)
(.008)
(.075)
(.083)
(.092)

(.004)
(.055)
(.066)
(.006)
(.009)
(.061)
(.030)
(.015)
(.010)
(.026)
(.023)
(.049)
(.240)
.283 (.245)
.352
2,695

À.009*
.118*
.095
À.018**
À.011
.007
.060*
À.021
.016
.006
À.006
À.088*
1.054***

.434*** (.032)

À.024 (.019)
À.070 (.043)
À.081* (.044)

À.031
.011
.149*
.096
.271**

Model 4

a

(.026)
(.004)
(.057)
(.074)
(.007)
(.009)
(.056)
(.034)
(.012)
(.012)
(.028)
(.029)
(.049)
(.260)
À.111 (.238)
.310
2,695

.489***
.002
À.194***
À.064
.018**
.014
À.008
À.058*
.018
À.001
.022
À.028
À.097*
À0.677**

À.097 (.061)
.093 (.107)
À.173** (.072)
—
—
—

.044 (.048)

Model 5

Notes: The correlations between depression and self-efficacy were À.46 at T1 (p , .001) and À.49 at T2 (p , .001). T1 ¼ Time 1; T1 ¼ Time 2.
Unstandardized regression coefficient (robust SE).
b
Reference category is continually married from Time 1 to Time 2.
*p , .05; **p , .01; ***p , .001 (one-tailed).

Constant
Adjusted R2
N

Depressive symptoms, T1
Self-efficacy, T1
Age
Female
Black
Education
Income
Employed
Functional impairment
Formal meeting attendance
Church attendance
Informal social interaction
Physical activities
Recent survey year
Hazard instrument

T1 control variables

Volunteer role, T1
Volunteer hours, T1
Volunteer hours squared, T1
Widowed more than 3 years before T1b
Widowed within 3 years before T1
Widowed between T1 and T2
T1 volunteer role 3 widowed more than 3 years before T1
T1 volunteer role 3 widowed within 3 years before T1
T1 volunteer role 3 widowed between T1 and T2
T1 volunteer hours 3 widowed more than 3 years before T1
T1 volunteer hours 3 widowed within 3 years before T1
T1 volunteer hours 3 widowed between T1 and T2

Variable

T2 Depressive Symptoms

(.026)
(.004)
(.056)
(.073)
(.007)
(.008)
(.055)
(.035)
(.012)
(.012)
(.028)
(.029)
(.049)
(.259)

(.072)
(.136)
(.110)
(.083)
(.177)
(.172)

À.076 (.252)
.312
2,695

.488***
.002
À.198***
À.064
.019**
.014
À.011
À.058*
.018
À.001
.023
À.030
À.102*
À0.693**

À.086
.012
À.261**
À.051
.234
.224

.026 (.056)

Model 6

(.026)
(.003)
(.056)
(.074)
(.007)
(.009)
(.057)
(.034)
(.012)
(.012)
(.028)
(.029)
(.049)
(.259)

(.061)
(.107)
(.072)

(.013)

À.056 (.237)
.312
2,695

.487***
.002
À.194***
À.064
.017**
.014
À.006
À.058*
.013
À.003
.021
À.029
À.101*
À0.674**

—
—
—

.028*
—
À.095
.099
À.167**

Model 7

T2 Self-Efficacy

Table 3. Residualized Regression Estimating the Effect of Widowhood, Volunteer Role, and Volunteer Hours on Changes in Well-Being
From T1 to T2 Among Americans Aged 50 and Older: Americans’ Changing Lives, 1986–1994

(.061)
(.104)
(.068)

(.014)

(.026)
(.004)
(.056)
(.074)
(.007)
(.008)
(.056)
(.035)
(.012)
(.012)
(.028)
(.029)
(.049)
(.257)
À.050 (.238)
.314
2,695

.488***
.002
À.200***
À.062
.017**
.013
À.010
À.057
.013
À.003
.021
À.032
À.105*
À0.701**

.002 (.027)
.092* (.046)
.240 (.382)

.020
—
À.102*
.112
À.162**

Model 8

VOLUNTEERING AND WIDOWHOOD IN LATER LIFE
S263

S264

showed a significantly lower sense of self-efficacy at T2. After
I took into account the interactions between widowhood and
volunteer hours, the significant main effect of volunteer hours
at T1 on self-efficacy disappeared at T2 (Model 8). People who
had been widowed for more than 7 years and people who had
become widowed within the past 4 years had a lower sense of
self-efficacy at T2. The interaction effect between volunteer
hours and widowed within 3 years before T1 was modest (b ¼
.092; p , .05). The spouses widowed within 3 years before T1
managed to sustain much greater self-efficacy at T2 (.112 þ
.092 ¼ .204) by increasing their volunteer hours after spousal
loss.
The effects of T1 covariates on self-efficacy were comparable in Models 5 to 8. People with better education were more
self-efficacious at T2. Women and functionally impaired
persons showed lower self-efficacy at T2. The recent survey
year variable suggested that people became less self-efficacious
in 1994 than in 1989. Nonrandom attrition was evident in this
model—people with a lower sense of self-efficacy were more
likely to drop out of the study.

DISCUSSION
With data from the ACL survey, the analyses show that the
temporal aspects of widowhood influence subsequent volunteer
participation and personal well-being. I uncovered an augmented
level of volunteer participation after spousal loss after considering the temporal dynamics of adjusting to widowhood. The
analyses also reveal that volunteer activities have stressbuffering effects on personal well-being in the face of loss.
Although the volunteer role offset the negative impact of
widowhood on subsequent depressive symptoms but not on
self-efficacy, volunteer hours had salubrious effects on both
depressive symptoms and self-efficacy. The evidence that
volunteer role acquired after spousal loss helps to alleviate
depressive symptoms is consistent with that from a recent study
on helping behaviors (Brown et al., 2004). Brown and
colleagues found that bereaved older adults who provided
help to others 6 months after spousal loss exhibited fewer
depressive symptoms in following years than their peers who
did not help others. Whereas volunteering at higher levels
before spousal loss helps one cope with depressive symptoms, increasing volunteer hours after spousal loss contributes
to better self-efficacy. These results suggest that increased
involvement in an existing volunteer role is more beneficial than
the acquisition of a new volunteer role during the psychosocial
adjustment to widowhood.
It should be noted that the effect of widowhood on volunteer
roles and the stress-buffering effect were only modest because
the ratio between a regression coefficient and its robust standard
error is small. Whereas a standard error is partly determined by
sample size, the modest effects obtained may be partially due to
the relatively small number of respondents who were widowed
between measurements. Nonetheless, it is substantively very
meaningful to interpret these modest effects from the current
analyses.
The benefits of volunteer participation in the adjustment
to widowhood in late life lend empirical support to the theory
of selective compensation. It is reasonable to conclude that
the selectivity theory aids researchers’ understanding of the

LI

function of volunteer involvement in later life. Research has
suggested that older people often utilize proactive selective
strategies to ensure a positive emotional climate when their
social network size is shrinking (Lang & Carstensen, 1994).
The fact that spousal loss triggers the adoption of volunteer
roles suggests that volunteer activities are a compensatory
resource invoked in the time of loss to help stabilize the size of
social networks and social interactions. In an effort to restore
personal equilibrium after spousal loss, bereaved persons
choose volunteer participation to help maximize positive
emotional affect and minimize negative affect (Carstensen,
1995). The benefits of volunteer participation on depressive
symptoms and self-efficacy uncovered in this study provide
empirical evidence that volunteer participation contributes to
selective optimization of emotional well-being in later life.
The present study has a number of limitations. First, each of
the widowhood indicators represented a relatively long period
of time. The average number of years for those participants
who had been widowed more than 3 years before baseline was
16 (M ¼ 16.1, SD ¼ 10.9). Retrospective widowhood information based upon personal recall may have been biased. Also,
because the time between interviews could be up to 5 years
(1989–1994), the large time intervals may have masked the
rapid changes in psychosocial well-being that usually occur
within the first few years after spousal loss. The long passage of
time between T1 and T2 may also have obscured the interplay
of changes in volunteer roles (or hours). There is no way to rule
out that the widowed persons first declined in depressive
symptoms and then increased volunteer activities. In order to
accurately assess the consequence of widowhood timing and
duration, the field needs other prospective studies that contain
the precise timing of widowhood occurrence so that shorter
intervals in the units of year (or month) may be specified.
Second, also due to data constraints, I could not control the
preloss personal characteristics for people widowed before
baseline. Rather, I used their initial postloss characteristics
collected in 1986 as surrogates. In supplementary analysis, I
investigated the surrogate approach and found that this
approach complicated the interpretation of the results but was
not problematic. I compared the mean levels of volunteer
activities and depressive symptoms between survey waves for
people in each of the widowhood categories. The levels of
volunteer activities fluctuated across the three waves regardless
of the timing of the widowhood event. The mean depressive
symptoms reached peak level in the wave immediately
following the widowhood event and declined in subsequent
waves. For people widowed between 1983 and 1986, their
depressive symptoms measured in 1986 were highest. Because
their postloss depressive symptoms in 1986 were controlled as
the T1 variable, people who had become widowed within 3
years before T1 did not report higher depressive symptoms at
T2 compared with people who had been continually married
(Table 3, Model 1).
One solution to avoiding the surrogate approach is to restrict
the analytic sample to people who were continually married at
baseline and examine widowhood between T1 and T2. I
analyzed this restricted sample (results not shown) and obtained
substantive results similar to the models in Tables 2 and 3. But
I believe an analysis including all participants widowed prior
to baseline would greatly enhance the contribution of this study.

VOLUNTEERING AND WIDOWHOOD IN LATER LIFE

The restricted model would only show the influence of existing
volunteer activities on subsequent personal well-being. By
including all participants widowed before baseline, the analyses
could reveal the mediating effects of the adoption of volunteer
roles and increased volunteer hours after widowhood on personal well-being. With regard to these study limitations, improvement is contingent upon the quality of the repeatedly
measured prospective data.
Older bereaved persons face many physical and psychological challenges. They tend to have higher rates of mortality
and morbidity, more depressive symptoms, and higher rates
of hospitalization than their married peers (Laditka & Laditka,
2003). Bereavement counseling and services should be
designed to meet these challenges. Coping resources may
include augmented social relations that help the newly bereaved
manage their emotions as well as restore their activity levels
(Richardson, 2006). Social relations after spousal loss may
provide frequent health reminders and health regulations that
are associated with positive health outcomes (Williams, 2004).
The evidence that volunteering compensates for losses in the
bereavement process suggests that social integration by means
of establishing new roles, identities, and relationships may
provide effective social interventions. Therefore, I suggest that
policy practitioners promote community programs that provide
bereaved older adults with an easy access to meaningful social
participation.
Assuming that future research uses truly prospective data,
I recommend a contextual analysis of the relationship among
widowhood, social integration, and well-being. Previous
research has suggested that the effect of widowhood is partly
determined by the context in which the widowhood is
experienced (Umberson et al., 1992). This context encompasses
both preloss personal circumstances and postloss coping
resources. Existing contextual analysis has examined how
preloss personal circumstances and the cause, timing, and
context of the death may influence psychosocial adjustment to
widowhood (Wheaton, 1990). Such research has shown that
the late spouse’s illness and the amount of forewarning predict
postloss psychological adjustment (Carr, House, Wortman,
Nesse, & Kessler, 2001). To date, scant research has examined
interpersonal factors as coping resources in the adjustment to
widowhood. In a contextual analysis, interpersonal factors that
did not seem important prior to widowhood may become very
meaningful after widowhood. The present study highlights
volunteering as one factor that may partially offset the negative
impact of widowhood on psychosocial well-being. I hope that
this study helps to kindle interest among other researchers in
examining various dimensions of social integration and their
potential contribution to improving the well-being of widows
and widowers in later life.
ACKNOWLEDGMENTS
An earlier version of this article was presented at the annual meeting of
the American Sociological Association, August 2005, Philadelphia, PA.
The research was supported by the Purdue Research Foundation, Purdue
University, when I was completing my doctoral dissertation. The views
expressed in this article are my own and do not reflect those of the New
Jersey Department of Health and Senior Services. My thanks go to Deborah
Carr, Kenneth Ferraro, Jessica Kelley-Moore, Geraldine Mackenzie, and
three anonymous reviewers for their helpful comments on the manuscript.
Data were made available by the Inter-University Consortium for Political

S265

and Social Research, Ann Arbor, Michigan. Neither the collector of the
original data nor the Consortium bears any responsibility for the analyses or
interpretations presented herein.
CORRESPONDENCE
Address correspondence to Yunqing Li, PhD, Center for Health
Statistics, New Jersey Department of Health and Senior Services, 3635
Quakerbridge Road, P.O. Box 360, Trenton, NJ 08625. E-mail:
yunqing.li@doh.state.nj.us
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Received July 19, 2006
Accepted March 2, 2007
Decision Editor: Neal M. Krause, PhD