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Journal of Applied Gerontology
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DOI: 10.1177/0733464814542465
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Article
Stress, Social Support,
and Burnout Among
Long-Term Care
Nursing Staff
Erin L. Woodhead1, Lynn Northrop2,
and Barry Edelstein3
Abstract
Long-term care nursing staff are subject to considerable occupational stress
and report high levels of burnout, yet little is known about how stress and
social support are associated with burnout in this population. The present
study utilized the job demands–resources model of burnout to examine
relations between job demands (occupational and personal stress), job
resources (sources and functions of social support), and burnout in a sample
of nursing staff at a long-term care facility (N = 250). Hierarchical linear
regression analyses revealed that job demands (greater occupational stress)
were associated with more emotional exhaustion, more depersonalization,
and less personal accomplishment. Job resources (support from supervisors
and friends or family members, reassurance of worth, opportunity for
nurturing) were associated with less emotional exhaustion and higher levels
of personal accomplishment. Interventions to reduce burnout that include
a focus on stress and social support outside of work may be particularly
beneficial for long-term care staff.
Manuscript received: December 11, 2013; final revision received: May 25, 2014;
accepted: June 14, 2014.
1San Jose State University, San Jose, CA, USA
2Sharp Mesa Visa Hospital, San Diego, CA, USA
3West Virginia University, Morgantown, WV, USA
Corresponding Author:
Erin L. Woodhead, San Jose State University, 1 Washington Square, San Jose, CA 95192-0120,
USA.
Email: erin.woodhead@sjsu.edu
542465JAGXXX10.1177/0733464814542465Journal of Applied GerontologyWoodhead et al.
research-article2014
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2 Journal of Applied Gerontology
Keywords
family-to-work spillover effects, long-term care, social provisions, occupational
stress
Staff burnout represents a danger to the mental and physical health of human-
service workers (Borritz et al., 2010; Kim, Ji, & Kao, 2011). In addition,
burnout often diminishes the quality and efficiency of care provided by
human-service workers and thus represents a danger to service recipients as
well as a cost to employers (Ben Natan, Lowenstein, & Eisikovits, 2010;
Poghosyan, Clarke, Finlayson, & Aiken, 2010). Prior studies with human-
service workers suggest that burnout is associated with higher levels of sub-
jective occupational stress and lower levels of social support (Barnard, Street,
& Love, 2006; Jenkins & Elliott, 2004; Nissly, Mor Barak, & Levin, 2005).
There is limited research, however, on how stress and social support are asso-
ciated with burnout among direct care and supervisory nursing staff at long-
term care facilities, despite the high levels of burnout in this population (Rai,
2010). The current study examined the relation between occupational and
personal stress, social support sources and functions both on- and off-the-job,
and burnout in a sample of long-term care nursing staff.
Burnout
Burnout is characterized by a prolonged response to chronic emotional and
interpersonal stressors on the job (Maslach, Schaufeli, & Leiter, 2001), and is
typically defined and measured according to three dimensions: emotional
exhaustion, feelings of cynicism and detachment from the job (depersonali-
zation), and a sense of ineffectiveness and lack of accomplishment (low per-
sonal accomplishment; Maslach, 2003; Weber & Jaekel-Reinhard, 2000).
Burnout, as it applies to human-service workers, is experienced by individu-
als whose occupations require intense interactions with persons for whom
they are responsible in some way (e.g., their patients, clients, or students;
Morse, Salyers, Rollins, Monroe-DeVita, & Pfahler, 2012; Schaufeli & Van
Dierendonck, 1993).
Factors that contribute to burnout among human-service workers have
been conceptualized according to several theoretical models, including the
job demands-resources model of burnout (Demerouti, Bakker, Nachreiner, &
Schaufeli, 2001; Schaufeli & Bakker, 2004), the effort-reward imbalance
model (Bakker, Killmer, Siegrist, & Schaufeli, 2000; van Vegchel, de Jonge,
Bosma, & Schaufeli, 2005), and a model specific to long-term care workers
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Woodhead et al. 3
(Cohen-Mansfield, 1995). In the current study, burnout is conceptualized
according to the job demands-resources model. This model has been applied
to nurses, although not specifically to nursing staff in long-term care facilities
(Hansen, Sverke, & Näswell, 2009; Jourdain & Chênevert, 2010). These
studies (Hansen et al., 2009; Jourdain & Chênevert, 2010) found that job
demands were associated with lower levels of emotional exhaustion and
depersonalization, and higher levels of personal accomplishment. Job
resources were not significantly associated with burnout, suggesting that, for
direct care staff in some health care settings, burnout levels may be more
directly affected by workplace demands.
Occupation and Personal Stress and Burnout
In the current study, we conceptualized occupational and personal stressors as
job demands, according to the job demands–resources model of burnout
(Demerouti et al., 2001). Nursing staff at long-term care facilities face several
specific occupational stressors not experienced by acute care nursing staff that
influence their job satisfaction and may lead to increased rates of burnout
(Stone & Harahan, 2010). One such stressor is the high number of residents
with dementia who may direct physical and verbal abuse toward staff or other
residents. These residents also often require frequent transfers between beds,
chairs, and wheelchairs, further adding to the strain on direct care staff
(Pitfield, Shahriyarmolki, & Livingston, 2011). Additional stressors include
exposure to the declining health and death of many of their service recipients,
care of individuals who are incontinent of urine or feces, care to individuals
needing different levels of assistance, and integrating residents with dementia
with other nursing home residents (Hasson & Arnetz, 2008; Morgan, Semchuk,
Stewart, & D’Arcy, 2002; Pekkarinen, Sinervo, Perälä, & Elovainio, 2004).
The current literature on spillover effects between personal and occupa-
tional stress (family-to-work spillover effects) suggests that personal stress
may lead to higher levels of emotional exhaustion, although this research has
not focused on nursing staff at long-term care facilities (Pfaff, Kowalski, &
Ansmann, 2013). The research that has been conducted on long-term care
staff suggests that personal stress may contribute to higher depressive symp-
toms, although burnout has not been examined as an outcome (O’Donnell,
Ertel, & Berkman, 2011).
The task of decreasing burnout among long-term care nursing staff
requires identification of employee variables that have the potential to
decrease or prevent burnout-related stressors. In light of research that is dis-
cussed below, social support is a strong candidate for this task.
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4 Journal of Applied Gerontology
Social Support and Burnout
The social climate of a workplace is linked to occupational stress and burnout
(Kinman, Wray, & Strange, 2011; Kowalski et al., 2010). Social support can
decrease burnout and occupational stress (Jenkins & Elliott, 2004), although
little is known about the types of social support that are available to long-term
care nursing staff, and whether different types of support are related to burn-
out. In the current study, social support sources and functions were conceptu-
alized as job resources, according to the job demands-resources model of
burnout (Demerouti et al., 2001). We included both source of support and
function of support in the current study in light of prior research suggesting
that types of support (i.e., function of support) and type of supporters (i.e.,
source of support) are two conceptually distinct constructs (Thoits, 2011).
There is some evidence that work-related support, particularly support
from supervisors, may be particularly important in decreasing stress among
long-term care nursing staff (Liang, Hsieh, Lin, & Chen, 2013; McGilton,
Hall, Wodchis, & Petroz, 2007), although previous research has not exam-
ined burnout directly. To our knowledge, there is no published work about
non-work sources of support (friends, family members) among long-term
care nursing staff and about their associations with burnout.
A variety of distinctions have been made between various types of social
support and the functions they serve (Uchino, 2004). For example, social
support may provide informational, emotional, or instrumental functions
(Thoits, 2011). To our knowledge, existing studies of burnout among nursing
staff in long-term care settings have not considered functions of support
when examining the impact of job resources on burnout. Provision of certain
types of social support within work and non-work relationships, such as
instrumental support and reassurance of worth, may have a positive outcome
on health and well-being, such as helping individuals cope with occupational
stress and burnout (Akroyd, Caison, & Adams, 2002; Scheurer, Choudhry,
Swanton, Matlin, & Shrank, 2012; Stevens et al., 2013; Varvel et al., 2007).
Overview of the Present Study
The goals of the present study were to utilize the job demands-resources
model of burnout to (a) determine the amount of job demands (occupational
stress, personal stress) and job resources (sources of social support, functions
of social support) in a sample of nursing staff in a long-term care setting;
(b) examine zero-order correlations of demographic variables (age, sex, edu-
cation), job demands, and job resources with the three dimensions of burnout
(emotional exhaustion, depersonalization, and personal accomplishment);
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Woodhead et al. 5
and (c) examine the amount of variance accounted for by each of the job
demands and job resources in predicting burnout, controlling for demo-
graphic variables significantly associated with burnout. Based on prior
research on the job demands-resources model (Demerouti et al., 2001;
Schaufeli & Bakker, 2004), we hypothesized that high levels of job demands
and low levels of job resources would predict high levels of emotional
exhaustion, high levels of depersonalization, and low levels of personal
accomplishment. We also hypothesized that higher levels of supervisor sup-
port would predict high levels of emotional exhaustion, high levels of deper-
sonalization, and low levels of personal accomplishment (Liang et al., 2014;
McGilton et al., 2007).
Method
Participants
Participants were 216 female and 34 male nursing staff who ranged in age
from 17 to 63 years. The majority of participants were direct care staff (certi-
fied nursing assistants or licensed practical nurses), although registered
nurses (supervisory nursing staff) were also included in the sample. Each
participant worked in 1 of 10 nursing homes in West Virginia. All of the
facilities had residents with different types of dementia diagnoses, although
the facilities did not exclusively serve residents with dementia. Participants
were mostly White and had earned a high school degree or completed some
college. Most of the sample worked the first shift from 7am to 3pm and were
relatively experienced in nursing home work. Additional background infor-
mation about the participants is presented in Table 1. The study was approved
by the Institutional Review Boards at San Jose State University and West
Virginia University.
Measures
Demographic questionnaire. Participants completed background information
on their age, gender, marital status, position in the nursing home, primary
work shift, highest degree earned, years of nursing home experience, and
duration of employment at the present nursing home.
Nursing Home Stress Inventory (NHSI). The NHSI was developed by the sec-
ond author to assess occupational stress experienced by nursing staff in the
long-term care environment. It contains 46 items (e.g., argued with a resident,
worked overtime) that were generated in consultation with 11 personnel from
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6 Journal of Applied Gerontology
three nursing homes representing five disciplines (nursing, administration,
psychology, social work, and activity therapy). The NHSI is completed at the
end of a shift. Participants are asked to indicate which events occurred during
the prior shift and the stressfulness of those events on a 7-point rating scale
(1 = occurred but was not stressful to 7 = caused me to panic). The total score
for the NHSI is a ratio obtained by dividing the total impact score by the total
number of events during the shift (α = .98; Table 2). Preliminary support for
the convergent validity of the NHSI measure was established via examination
of correlations with the Daily Stress Inventory (DSI; r = .59, p < .001), a
1-item measure of self-reported stress in the past month (1 = no stress to 10 =
extreme stress; r = .41, p < .001), and a 1-item measure of self-reported job
satisfaction (1 = very satisfied to 10 = very unsatisfied; r = .36, p < .001).
Table 1. Participant Characteristics.
Variable M (SD; range) or %
Age 37.0 (10.6; 17-63)
Female 86.4%
Marital status 19.6% single
56.4% married
22.8% divorced
1.2% widowed
Race 83.5% White
8.4% African America
5.6% Asian American
2.5% Native American
Education 3.2% grade school
15.2% some high school
33.6% high school/technical school degree
34.0% some college
7.6% college degree
3.2% graduate degree
Position 78.8% staff
21.2% supervisor
Shift 66.3% first (7:00 a.m.-3:00 p.m.)
22.1% second (3:00 p.m.-11:00 p.m.)
7.2% third (11:00 p.m.-7:00 a.m.)
4.4% float (8-hr shift)
Hours worked per week 40.2 (7.3; 16-80)
Years worked in nursing homes 7.5 (6.1; 0.5-45.0)
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Woodhead et al. 7
Daily Stress Inventory (DSI). The DSI (Brantley & Jones, 1989) was used to
measure personal stress. Participants indicate which of 58 potentially stress-
ful events they experienced in the past 24 hours (e.g., difficulty in traffic, car
trouble), and the stressfulness of those events on a 7-point rating scale (1 =
occurred but was not stressful to 7 = caused me to panic). Items assess five
areas of stress: interpersonal problems, personal competency, cognitive
stressors, environmental hassles, and varied stressors. The total DSI score is
a ratio obtained by dividing the total impact score by the number of stressful
events endorsed in the past 24 hours (α = .87; Table 2). Validity studies of the
DSI indicate that it is correlated with global stress measures (Brantley &
Jones, 1989), endocrine measures of stress (Brantley, Deitz, McKnight,
Jones, & Tulley, 1988), and measures of daily hassles (Kanner, Coyne, Schae-
fer, & Lazarus, 1981).
Sources of Support (SOS). The SOS is a 48-item measure designed by the
second author to assess perceived social support from four different sources
(supervisors, coworkers, spouse/significant other, friends/family members).
The SOS contains 12 items from the Social Support Scale (House, 1981).
Additional items were added for the current study to assess social support
targeted at decreasing occupational stress, improving job performance, and
Table 2. Baseline Values of Stress and Social Support.
Variable M (SD) Range
Occupational stress (NHSI) 2.80 (1.61) 0-6
Personal stress (DSI) 3.30 (1.38) 0-6.11
Sources of support
Supervisor 38.49 (12.40) 12-60
Coworker 37.80 (9.04) 12-60
Spouse/significant other 39.27 (14.10) 12-60
Friend/family member 37.65 (11.74) 12-60
Functions of support (SPS)
Guidance 13.11 (2.83)a4-16
Reassurance of worth 12.11 (2.29)a,b 6-16
Social integration 12.96 (2.14)b,c 7-16
Attachment 12.53 (2.88)a,d 4-16
Reliable alliance 13.50 (2.22)b,c,d 6-16
Opportunity for nurturing 13.77 (2.06)a,b,c,d 7-16
Note. For functions of support, same superscripts indicate significant differences. Ranges
presented are actual rather than possible ranges. NHSI = Nursing Home Stress Inventory;
DSI = Daily Stress Inventory; SPS = Social Provisions Scale.
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8 Journal of Applied Gerontology
increasing coping with occupational stress or burnout. Participants were
asked whether they received certain types of support (e.g., willingness to
listen to work-related problems, concern about the participant’s welfare)
from each of the four target sources of support. Responses were on a 5-point
rating scale (1 = not at all true to 5 = always true; supervisor α = .97; coworker
α = .94; spouse/significant α = .97; family/friend α = .96; Table 2). The SOS
scores for each subscale are derived by adding responses to each of the items
(12 items per subscale; Table 2). Total score on the SOS was significantly
correlated in the expected directions with total score on the Social Provisions
Scale (SPS; r = .70; p < .001), total NHSI score (r = −.45, p < .001), and total
DSI score (r = −.39, p < .001).
Social Provisions Scale (SPS; Functions of Support). The 24-item SPS (Cutrona &
Russell, 1987) was designed to assess the extent to which a person’s current
social relationships serve specific social functions. Participants are asked to
think of current relationships with friends, spouses, family members, and
other individuals in their lives and rate 24 statements on a 4-point rating scale
(1 = strongly disagree to 4 = strongly agree). The total SPS scores for each
subscale are derived by adding responses to each of the items (4 items per
subscale; Table 2). The six relationship functions assessed by the SPS include
(a) guidance, involving trustworthy and authoritative individuals who can
provide advice (“There is someone I could talk to about important decisions
in my life”); (b) reassurance of worth, involving acknowledgment of skills
and abilities (“I have relationships where my competence and skill are recog-
nized”); (c) social integration, which involves a network of social relation-
ships in which individuals share interests and concerns (“There are people
who enjoy the same social activities I do”); (d) attachment, which involves
receiving a sense of security and safety from the relationship (“I feel a strong
emotional bond with at least one other person”); (e) reliable alliance, derived
from relationships in which the person can count on others for assistance
under any circumstances (“There are people I can depend on to help me if I
really need it”); and (f) opportunity for nurturing, derived from relationships
in which the person is responsible for the well-being of another (“There are
people who depend on me for help”).
Maslach Burnout Inventory (MBI). The MBI (Maslach & Jackson, 1986) is a
22-item self-report instrument designed to assess several dimensions of burn-
out. Participants are asked to report how often the statements apply to them
(1 = never to 7 = every day). Subscales of the MBI include emotional exhaus-
tion (extent to which one feels overextended and exhausted by one’s work; 9
items; M = 37.4, SD = 13.9, range = 9-63, α = .90), depersonalization
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Woodhead et al. 9
(negative attitudes and behaviors toward care recipients; 5 items; M = 12.0,
SD = 6.1, range = 5-29, α = .79), and personal accomplishment (feelings of
competence and achievement at work; 8 items; M = 44.5, SD = 8.2, range =
19-56, α = .71). The MBI is correlated with other measures of burnout (Pines
& Aronson, 1988) and with measures of somatic complaints and psychologi-
cal strain (anxiety, depression, and irritation; Schaufeli & Van Dierendonck,
1993).
Procedure
Administrators of nursing homes were contacted by phone to obtain permis-
sion for recruiting nursing staff. All nursing homes that were approached
agreed to participate. All eligible staff members at each facility were invited
to participate. Participation was voluntary; informed consent was obtained
from all participants. Questionnaires were administrated at the nursing home
during shift changes and break periods. Participants completed the demo-
graphic questionnaire, NHSI (occupational stress), DSI (personal stress),
SOS (sources of support), SPS (functions of support), and MBI (burnout
inventory). Questionnaires were administered by research assistants who had
prior experience working in geriatric settings. Participants were compensated
for participation with small merchandise and gift certificates donated by local
merchants.
Analysis Plan
Independent-samples t tests were used to examine differences in occupational
versus personal stress, the sources of social support, and the functions of
social support. We then examined zero-order correlations between age, sex,
education, position (supervisor or staff), occupational stress, personal stress,
the four subscales of the SOS, and the six subscales from the SPS with the
three burnout dimensions from the MBI (emotional exhaustion, depersonali-
zation, and personal accomplishment). Hierarchical linear regression analy-
ses were used to examine the direct effects of job demands and resources on
outcomes. Intercorrelations of the independent variables were examined
prior to running the regression analyses to check for multicollinearity. One
regression analysis was run for each outcome variable (emotional exhaustion,
depersonalization, and personal accomplishment). Block 1 controlled for par-
ticipant characteristics significantly associated with burnout. Block 2
included the job demand variables of total scores (impact–event ratios) from
the NHSI (occupational stress) and the DSI (personal stress), respectively.
Block 3 included the job resource variables of support from supervisors,
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10 Journal of Applied Gerontology
coworkers, spouse/significant others, and friends/family members, as mea-
sured by the SOS. Block 4 included the six functions of support as measured
by the SPS (guidance, reassurance of worth, social integration, attachment,
reliable alliance, and opportunity for nurturing).
Results
Amount of Job Demands and Job Resources
Participants reported significantly higher levels of personal stress than
occupational stress, t(490) = 3.69, p = .0002 (Table 2). No significant dif-
ferences were observed between sources of support (supervisor, coworker,
spouse/significant other, friend/family member). Participants reported
obtaining more guidance from social relationships than reassurance of
worth, t(492) = 4.32, p < .001; attachment, t(492) = 2.26, p = .024; and
opportunity for nurturing, t(492) = 2.96, p = .003. Reassurance of worth
was obtained less frequently than social integration, t(492) = 4.26, p < .001;
reliable alliance, t(492) = 6.85, p < 0.001; and opportunity for nurturing,
t(492) = 8.47, p < .001. Social integration was obtained less frequently than
reliable alliance, t(492) = 2.75, p = .006; and opportunity for nurturing,
t(492) = 4.29, p < .001. Finally, attachment was also obtained less fre-
quently than reliable alliance, t(492) = 4.19, p < .001; and opportunity for
nurturing, t(492) = 5.50, p < .001.
Zero-Order Correlations Between Demographic Variables, Job
Demands, Job Resources, and Burnout
Table 3 presents zero-order correlations of sex, age, education, position,
occupational stress, personal stress, and sources and functions of support
with the three components of burnout. Older age was associated with less
emotional exhaustion and depersonalization. Higher occupational and per-
sonal stress ratings were associated with more emotional exhaustion and
depersonalization, and less endorsement of personal accomplishment.
Individuals who reported more support from all four sources endorsed less
emotional exhaustion, less depersonalization, and more personal accomplish-
ment. All of the six functions of support were significantly associated with
less emotional exhaustion, less depersonalization, and more personal accom-
plishment. Based on these correlations, age was included in Block 1 of the
regression analyses because it was correlated with two of the burnout out-
come variables (emotional exhaustion and depersonalization). Sex and edu-
cation were not included in the regression analyses.
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Woodhead et al. 11
Regression Analyses Predicting Burnout
The average correlation between predictors of burnout was .38 (Table 4).
Sources of support, as assessed by the SOS, and functions of support, as
assessed by the SPS, were moderately correlated. Despite the moderate cor-
relation, these variables were retained for the regression analyses (Table 5)
due to the conceptual distinction between type and source of support (Thoits,
2011). Block 2 (occupational and personal stress) accounted for 26% of the
variance in emotional exhaustion, F(5, 221) = 16.90, p < .001; 17% of the
variance in depersonalization, F(5, 221) = 10.08, p < .001; and 7% of the
variance in personal accomplishment, F(5, 221) = 4.16, p = .001. When
examining significance of the individual predictors, occupational stress (but
not personal stress) was a significant predictor of all dimensions of burnout.
Block 3 (sources of support) accounted for significant amounts of variance
Table 3. Correlations Between Participant Characteristics, Job Demands, Job
Resources, and Burnout Outcomes.
Variable
Emotional
exhaustion Depersonalization
Personal
accomplishment
Participant characteristics
Sex .01 −.12 −.06
Age −.15* −.16* .05
Education −.11 −.08 .05
Position (Staff or supervisor) −.09 −.05 −.15
Job demands
Nursing Home Stress Inventory .48*** .39*** −.27***
Daily Stress Inventory .37*** .31*** −.25***
Job resources
Sources of support
Supervisor −.58*** −.40*** .33***
Coworker −.42*** −.38*** .25***
Spouse/significant other −.46*** −.32*** .28***
Friend/family member −.43*** −.35*** .29***
Functions of support
Guidance −.46*** −.34*** .42**
Reassurance of worth −.51*** −.40*** .38***
Social integration −.36*** −.27*** .34***
Attachment −.46*** −.31*** .40***
Reliable alliance −.19** −.26*** .17**
Opportunity for nurturing −.43*** −.23*** .37***
*p < .05. **p < .01. ***p < .001.
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Table 4. Intercorrelation of Predictors.
Variable 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.
1. Age — −.08 −.12 .06 .06 −.01 −.02 −.01 .05 −.01 .01 .01 −.07
2. Occupational stress (NHSI) — .59*** −.47*** −.36*** −.33*** −.29*** −.39*** −.42*** −.30*** −.42*** −.31*** −.12
3. Personal stress (DSI) — −.38*** −.33** −.32*** −.27*** −.42*** −.36*** −.33*** −.41*** −.25*** −.05
Sources of support
4. Supervisor — .58*** .58*** .50*** .51*** .51*** .39*** .49*** .45*** .22***
5. Coworker — .48*** .58*** .51*** .47*** .36*** .44*** .40*** .20***
6. Spouse/partner — .66*** .58*** .46*** .45*** .62*** .48*** .22***
7. Friend/family member — .61*** .48*** .44*** .56*** .50*** .25***
Functions of support
8. Guidance — .63*** .63*** .81*** .72*** .29***
9. Reassurance of worth — .61*** .64*** .56*** .37***
10. Social integration — .62*** .58*** .31***
11. Attachment — .66*** .25***
12. Reliable alliance — .33***
13. Opportunity for nurturing —
Note. NHSI = Nursing Home Stress Inventory; DSI = Daily Stress Inventory.
*p < .05. **p < .01. ***p < .001.
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Table 5. Hierarchical Multiple Regression Analyses for Demographics, Job Demands, and Job Resources Predicting Burnout.
Emotional exhaustion Depersonalization Personal accomplishment
Variable β95% CI β95% CI β95% CI
Block 1
Age −.21** [−0.37, −0.05] −.01* [−0.01, 0.00] .01 [−0.01, 0.02]
Adjusted R2.03 .02 −.01
Block 2
Occupational stress (NHSI) 3.45*** [2.28, 4.61] .04*** [0.02, 0.06] −.13* [−0.24, −0.02]
Personal stress (DSI) 1.15 [−0.22, 2.52] .02 [0.00, 0.05] −.10 [−0.23, 0.03]
Adjusted R2.26 .17 .07
Block 3
Supervisor −.32*** [−0.48, −0.16] −.01 [−0.01, 0.00] .01 [−0.01, 0.03]
Coworker .03 [−0.18, 0.25] −.01 [−0.01, 0.00] −.01 [−0.02, 0.02]
Spouse/significant other −.09 [−0.24, 0.06] −.01 [0.00, 0.00] .01 [−0.01, 0.02]
Friend/family member −.19* [−0.36, −0.02] .01 [−0.01, 0.00] .01 [−0.01, 0.03]
Adjusted R2.41 .22 .09
Block 4
Guidance −.52 [−1.53, 0.48] −.01 [−0.03, 0.01] .09 [−0.01, 0.19]
Reassurance of worth −1.17* [−2.12, −0.21] −.01 [−0.03, 0.01] .12* [0.03, 0.21]
Social integration .32 [−0.66, 1.29] −.02 [−0.02, 0.01] −.01 [−0.11, 0.08]
Attachment −.35 [−1.33, 0.62] .00 [−0.02, 0.01] −.01 [−0.10, 0.08]
Reliable alliance −.49 [−1.53, 0.54] −.01 [−0.02, 0.01] −.10 [−0.20, 0.01]
Opportunity for nurturing −.08 [−0.88, 0.71] −.01 [−0.02, 0.01] .10* [0.02, 0.17]
Adjusted R2.34 .22 .15
Note. β = unstandardized regression coefficient; CI = confidence interval; NHSI = Nursing Home Stress Inventory; DSI = Daily Stress Inventory.
*p < .05. **p < .01. ***p < .001.
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14 Journal of Applied Gerontology
across the three dimensions of burnout (9%-41%; Table 5). When examining
individual predictors, more emotional exhaustion was predicted by less sup-
port from supervisors and friends/family members, F(9, 217) = 18.26, p <
.001. Block 4 (functions of support) accounted for 15% to 34% of the vari-
ance in the dimensions of burnout. More emotional exhaustion was predicted
by obtaining less reassurance of worth from relationships, F(11, 215) = 11.44,
p < .001; more personal accomplishment was predicted by obtaining more
reassurance of worth from social interactions and more opportunity for nur-
turing, F(11, 215) = 4.62, p < .001.
Discussion
The goals of the current study were to examine levels of personal and occu-
pational stress among long-term care nursing staff and determine the extent
to which job demands and job resources were associated with scores on the
MBI. Unique features of the present study include consideration of the con-
tributions of personal stress, examination of four different sources of social
support, and examination of the functions of social support and their relation
to scores on the MBI. Personal stress, sources and functions of social support,
and their relation to burnout have not been examined together in prior studies
of long-term care nursing staff. Source of support (supervisor, family, and
friends) and function of support (reassurance of worth, opportunity for nur-
turing) were significant contributors to MBI scores and therefore, potential
targets for preventive and intervention efforts. We also found a relatively high
level of personal stress, which was significantly higher than reported occupa-
tional stress. This finding may suggest the need for more holistic approaches
to stress reduction that potentially incorporate the entire waking day and
7-day week.
Job Demands and Burnout
We assessed personal stress in the current study, which has not previously
been examined in the literature on burnout among long-term care staff.
Although not predictive of burnout scores on the MBI, levels of personal
stress in our sample were significantly higher than occupational stress.
Personal sources of stress, such as difficulties within one’s family, may make
it difficult to focus on work and find meaning in working with patients, poten-
tially leading to greater risk of occupational burnout (Cohen-Mansfield, 1995).
To this end, nursing home administrators may find it advantageous to incorpo-
rate in-service training that teaches strategies for stress reduction that incorpo-
rate potential sources of stress encountered by staff throughout their waking
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Woodhead et al. 15
hours. This may help to minimize the spillover of stress from multiple sources
and thereby, prevent or manage its impact on occupational burnout.
Our finding that occupational stress predicted all three dimensions of
burnout on the MBI is consistent with the findings of prior studies on the job
demands-resources model with nurses working in acute care hospitals
(Hansen et al., 2009; Jourdain & Chênevert, 2010); specifically, job demands
may have a greater impact on increasing burnout than job resources do on
lowering burnout. Our study extends these findings to nursing staff in long-
term care settings, a sample to which the job demands-resources model has
not yet been applied. Although there have been successful programs aimed at
reducing turnover and increasing job satisfaction among nursing home staff
(Castle & Bost, 2009; Dill, Craft Morgan, & Konrad, 2010), there are limited
data on tailored stress management programs for nursing staff in long-term
care settings. The specific occupational demands required of long-term care
staff, such as caring for residents with dementia, may need to be addressed in
a stress management program tailored to the nursing home setting (e.g.,
VonDras, Flittner, Malcore, & Pouliot, 2009). This may include strategies for
managing the physical and often repetitive verbal abuse that is frequently
directed toward staff who are providing direct care to individuals with demen-
tia, which can take a significant emotional toll.
Job Resources and Burnout
Existing research on job resources has either not examined separate sources
of social support in the same study, or has focused exclusively on supervisor
support (McGilton et al., 2007; Schaufeli & Buunk, 2003). The current study
assessed four sources of social support. Based on existing research focused
on job satisfaction (e.g., McGilton et al., 2007), we hypothesized that super-
visor support would predict MBI scores in our sample. We found that partici-
pants obtained equal amounts of support from the four sources assessed in the
study (supervisor, coworker, spouse/significant other, friend/family mem-
ber). More support from supervisors and friends or family members predicted
lower levels of emotional exhaustion as measured by the MBI. Prior research
on the effects of supervisor support in non-nursing home settings suggests
that increasing supervisor support may lead to higher employee retention and
less absenteeism (Eisenberger, Stinglhamber, Vandenberghe, Sucharski, &
Rhoades, 2002; Van Dierendonck, Schaufeli, & Buunk, 1998). The finding
regarding the importance of support from friends/family members is unique
in the literature on burnout among long-term care nursing staff and again,
underscores the need to look beyond the walls of the long-term care facility
for contributions to stress, burnout, and their reduction or prevention.
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16 Journal of Applied Gerontology
To our knowledge, our study is the first to examine the role of social sup-
port functions in burnout among long-term care nursing staff. Of the six func-
tions of social support assessed in the study, participants most frequently
endorsed the functions of guidance, reliable alliance, and opportunity for nur-
turing. Greater reassurance of worth predicted less emotional exhaustion and
a greater sense of personal accomplishment, whereas social relationships that
provided greater opportunity for nurturing predicted a greater sense of per-
sonal accomplishment. This result supports our hypothesis regarding the
importance of reassurance of worth and replicates existing research on other
professions suggesting that reassurance of worth is associated with less burn-
out (Akroyd et al., 2002; Varvel et al., 2007).
Clinical Implications
Interventions to reduce burnout are typically categorized as person-directed,
organization-directed, or a combination of both (Awa, Plaumann, & Walter,
2010; Westermann, Kozak, Harling, & Nienhaus, 2014). Person-directed inter-
ventions focus on bolstering individual coping strategies in the face of stress,
whereas organization-directed interventions tend to focus on decreasing job
demands. Recent reviews suggest that person-directed interventions to reduce
burnout are effective in the short term (6 months or less), whereas interventions
that include both person-directed and organization-directed techniques are
more effective in the long term (Awa et al., 2010; Westermann et al., 2014). Our
results provide information that would inform the selection of skills and tech-
niques that could be included in person- and organization-directed interven-
tions to reduce burnout. For example, person-directed interventions might
include strategies for eliciting social support in and outside of work, whereas
organization-directed interventions might focus on supervisor training to
increase support provided to employees. Person-directed interventions could
be geared toward teaching employees to provide support to each other, as low
social support at work has been associated with nurses’ intentions to leave the
profession (Zeytinoglu, Denton, & Plenderleith, 2010). In addition, staff mem-
bers may benefit from learning how to bring new social contacts into their
network and/or accept social support from those that are offering, as well as
techniques for seeking support outside of work from family and friends. To the
extent that friends and family members offer emotional support and active cop-
ing assistance (Thoits, 2011), our findings suggest that learning to elicit support
from non-work sources is important in reducing job burnout.
For organization-directed interventions to reduce burnout, supervisors
may need additional training and coaching around the creation and mainte-
nance of supportive environments for their staff. Given that reassurance of
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Woodhead et al. 17
worth involves acknowledgment of skills and abilities, the training of super-
visors to support this function may be particularly helpful in reducing burn-
out (van der Heijden et al., 2010). Relatively brief supervisor training that
instructs and models this skill could contribute to reductions in staff burnout.
These additions to burnout programs may improve their ability to reduce
burnout in the long term.
Our study results also suggest the importance of regularly assessing levels
of burnout and social support in long-term care staff. Long-term care facili-
ties may benefit from policies that incorporate regular assessment of burnout
symptoms and social support structures that are in place for staff to cope with
burnout.
Limitations
The sample for the present study was largely female, White, and rural, which
may limit generalization to more diverse nursing staff at other long-term care
facilities and may limit generalization to urban settings. The NHSI (occupa-
tional stress) was created for the purposes of the present study based on input
from an expert panel. Specific constructs within the measure were not exam-
ined, which is an area for future research. The SOS (sources of support) was
created based on an existing measure of social support, with additional items
added to answer questions specific to the current study. Preliminary psycho-
metric support for the reliability and validity of these new instruments was
examined and was acceptable.
Conclusions and Future Directions
Unique contributions of the current study are the findings that support from
friends and family, and social relationships that provided reassurance of
worth and opportunity for nurturing, both in and outside of the work environ-
ment, reduced scores on the emotional exhaustion subscale of the MBI and
increased scores on the personal accomplishment subscale. These findings
point the way to burnout reduction interventions that focus more strongly, or
even exclusively, on eliciting and maintaining social support across settings.
Future directions include replication of the study in nursing homes with more
diverse staff and in urban settings, examination of moderators of the stress–
burnout relation, further validation of the measures created for the purposes
of the study, comparison of facility factors that may influence burnout, and
development of brief interventions that would bolster social resources avail-
able to long-term care staff and supervisors (e.g., Leiter, Laschinger, Day, &
Oore, 2011; Van Dierendonck et al., 1998).
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18 Journal of Applied Gerontology
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
Funding
The authors disclosed receipt of the following financial support for the research, author-
ship, and/or publication of this article: Lynn Northrop received funding for the project
from the Alumni Fund of the West Virginia University Department of Psychology.
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Author Biographies
Erin L. Woodhead, PhD, is an assistant professor in the Department of Psychology
at San Jose State University. She received her PhD in clinical psychology from West
Virginia University. Her research interests are in facilitating treatment for late life
depression, and training in aging and geropsychology at the undergraduate and gradu-
ate levels. She has worked in long-term care settings and has provided stress manage-
ment training to direct care staff.
Lynn Northrop, PhD, is director of predoctoral and postdoctoral psychology training
at Sharp Mesa Vista Hospital and the Sharp McDonald Center. She received her PhD
in clinical psychology from West Virginia University and has worked in several long-
term care settings throughout her career. The research reported in this article was part
of her doctoral dissertation. In her clinical work, she continues to emphasize the
importance of social support in all its forms.
Barry Edelstein, PhD, is professor of psychology at West Virginia University. His
research interests include older adult anxiety, older adult decision-making, and the
assessment of decision-making capacity. For 26 years, he has been a consultant to
Hopemont Hospital, a state long-term care facility in Terra Alta, West Virginia, where
clinical psychology students receive practicum training with older adults. He and his
students provide mandatory stress management training to all direct care staff at the
hospital with the goal of reducing burnout.
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