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This article was downloaded by: [Erasmus University]On: 27 May 2013, At: 05:10Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
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Supervisor and coworker support:a source congruence approach tobuffering role conflict and physicalstressorsMargarita Mayo a , Juan I. Sanchez b , Juan C. Pastor a & AlfredoRodriguez ca IE Business School, Madrid, Spainb Florida International University, Miami, FL, USAc Facultad de Psicología, Universidad Complutense de Madrid,Madrid, SpainPublished online: 18 Apr 2012.
To cite this article: Margarita Mayo , Juan I. Sanchez , Juan C. Pastor & Alfredo Rodriguez (2012):Supervisor and coworker support: a source congruence approach to buffering role conflict andphysical stressors, The International Journal of Human Resource Management, 23:18, 3872-3889
To link to this article: http://dx.doi.org/10.1080/09585192.2012.676930
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Supervisor and coworker support: a source congruence approachto buffering role conflict and physical stressors†
Margarita Mayoa*, Juan I. Sanchezb, Juan C. Pastora and Alfredo Rodriguezc
aIE Business School, Madrid, Spain; bFlorida International University, Miami, FL, USA;cFacultad de Psicologıa, Universidad Complutense de Madrid, Madrid, Spain
The buffering effects of supervisor support on the stressor–strain relationship haveproven elusive in prior research (Beehr, Farmer, Glazer, Gudanowski and Nair (2003),‘The Enigma of Social Support and Occupational Stress: Source Congruence andGender Role Effects,’ Journal of Occupational and Health Psychology, 8, 220–231).We built on emerging work on source congruence and conservation of resource theoryto test a series of hypotheses intended to clarify these mixed findings. Using a sample of768 employees from 45 organizations in North America, results from moderatedregression analyses, showed that the effects of supervisor support on the stressor–strainrelationship depended on source congruence. In accordance with our predictions,although we found buffering effects for the physical stressors–strain relationship, wefound a reverse buffering effect for the role conflict–strain relationship. Thesedifferential buffering effects did not emerge when considering coworker support. Wediscuss the implications of our results for shedding light on the mixed evidenceregarding buffering work stressors reported in prior research.
Keywords: coworker support; physical stressors; role conflict; source congruence;stress; supervisor support
Introduction
Social support has been heralded as a resource that helps employees cope with work
stressors, which are the stimuli that induce the stress process and ultimately provoke
employee strains (Sosik and Godshalk 2000; Searle, Bright and Bochner 2001; van
Dierendonck, Haynes, Borrill and Stride 2004). Theoretical models involving both main
and interaction effects have been advanced to explain the role that supervisor support plays
in the work stressor–strain relationship (Carlson and Perrewe 1999; Cooper, Dewe and
O’Driscoll 2001). According to the main effects model, supervisor support directly
reduces the level of tension, dissatisfaction and other forms of strain, regardless of the
level of stressors. On the other hand, the moderating or buffering hypothesis postulates
an interaction effect whereby supervisor support attenuates the impact of stressors on
strains. In other words, there should be a strong stressor–strain relationship when
supervisor support is low and a weak relationship when supervisor support is high.
Unlike the main effects model, which has held up in individual studies (e.g. Blau 1981;
Beehr 1985; Ganster, Fusilier and Mayer 1986; Fried and Tiegs 1993) as well as in a
meta-analysis of the work stress literature (Viswesvaran, Sanchez and Fisher 1999),
ISSN 0958-5192 print/ISSN 1466-4399 online
q 2012 Taylor & Francis
http://dx.doi.org/10.1080/09585192.2012.676930
http://www.tandfonline.com
†An earlier version of this paper was published in the Best Paper Proceedings of the Academy ofManagement Conference in 2007.
*Corresponding author. Email: [email protected]
The International Journal of Human Resource Management,
Vol. 23, No. 18, October 2012, 3872–3889
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evidence of the moderating effects of supervisor support has been, in the words of Beehr
et al. (2003, p. 220), ‘rather tenuous, inconsistent and unclear’. That is, although several
studies have supported this ‘buffering effect’ suggesting that supervisor support reduces
the impact of stressors on strain (e.g. Beehr, King and King 1990; Dorman and Zapf 1999;
Sargent and Terry 2000; Beehr et al. 2003), others have either failed to detect it (e.g. Blau
1981; Ganster et al. 1986; Fried and Tiegs 1993; Beehr, Jex, Stacy and Murray 2000) or
found rather weak support (Dorman and Zapf 1999). Furthermore, still other studies have
reported an intriguing ‘reverse buffering’ effect, which suggested that support may at
times exacerbate, rather than weaken, the impact of stressors on strains (e.g. Kobasa and
Puccetti 1983; Kaufmann and Beehr 1986; Glaser, Tatum, Nebeker, Sorenson and Aiello
1999; Kickul and Posig 2001; Deelstra et al. 2003). Our study attempts to reconcile these
apparent contradictory results by investigating how the congruence between the sources of
stressors and of social support makes a difference in determining the ameliorating effect of
social support on the relationship between stressors and strain. The notion of source
congruence, first advanced by Blau (1981) and later Kaufmann and Beehr (1986), refers to
the congruence between sources of the stressor and of social support. In particular, we
examine two sources of stressors – role conflict and physical stressors – and two sources
of support – supervisor and coworker. From a both theoretical and practical standpoint, it
seems important to understand why support from the supervisor, a frequently offered
prescription in the practitioners press, does not alleviate employee strain in every situation.
Researchers have called for theoretically guided efforts to disentangle the seemingly
inconsistent findings concerning the buffering effects of supervisor support (Beehr et al.
2003). Although Cohen and Wills (1985) contended that, to be effective, the kind of
support should have a good fit with the focal stressor, the extant research does not seem to
provide a convincing, unambiguous set of criteria capable of explaining when and how
stressors and support fit each other. Indeed, Viswesvaran, Sanchez and Fisher’s meta-
analysis (1999) concluded that the type of support thought to fit the specific type of stressor
did not yield larger moderator effects than types of support that did not seemingly fit the
stressor. Beehr et al. (2003) also noted that researchers have had a great deal of difficulty
predicting whether or not a specific type of support will buffer a given stressor. Along
these same lines, de Jonge and Dormann (2006) concluded that ‘inconsistencies in
demonstrating interaction effects between stressors and resources represent one of the
major threats to prominent models on organizational stress’ (p. 1369).
The study described herein relies on emerging work on source congruence and
conservation of resource (COR) theory to predict the extent to which the buffering effect of
supervisor support depends on the congruence between the resource (e.g. supervisor
support) and the source of the specific stressor. In particular, we examined a work stressor
that is likely to be congruent with or emanate from primarily the supervisor (e.g. role
conflict), together with a stressor (e.g. physical stressors), which tends to be incongruent
with the supervisor because it typically falls beyond the supervisor’s control. Then, we
compared the results of supervisor support with those of coworker support to provide a more
robust test of the source congruence hypothesis. An additional strength of our study is that, in
contrast to prior studies of buffering effects, it employed a relatively large sample size that
afforded us sufficient statistical power to detect even small stressor by support interactions.
Theoretical background
Social support generally refers to the individual belief that help would be available from
other people in difficult situations (Cobb 1976). Support may come from different sources.
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There are work-related and non-work related sources of support, such as supervisors,
coworkers and family (Halbesleben 2006). Here, we focus on work-related sources of
support because they are more closely related to the stressors of interest – work conflict
and poor physical conditions. Family and non-work related sources might be most relevant
when considering buffering stressors such as work–family conflict. Traditionally, it was
thought that social support, independently of the source, was a strong remedy against job
stressors. However, Blau (1981) was the first to suggest that sources of support may need
to be independent of sources of stressors because support coming from the same source
that is provoking the stressor might be awkward and unproductive. Similarly, Kaufmann
and Beehr (1986) also called for further examination of the congruence between the source
of the stressor and the source of support as an explanation for the contradictory buffering
effects of social support. Beehr et al. (2003) further explicated the theoretical rationale
behind this source congruence hypothesis by arguing that, when both support and stressors
originate in the same source (e.g. the supervisor), two conflicting or dissonant cognitions
may arise about this source, hence augmenting rather than buffering the impact of stressors
on strains. However, Beehr et al. (2003) did not find consistent support for the source
congruence hypothesis, which had anticipated that such congruence would be more
harmful than helpful, which led them to call for additional research on alternative forms of
support–stressor congruence. In line with this call for further research, recent revisions of
the COR theory (Hobfoll 2001; Hobfoll and Kay 2007) focusing on employee appraisals of
resources may help us sort out the boundary conditions under which supervisor support has
a buffering effect from those under which it has a reverse buffering effect.
The basic tenet of COR theory (Hobfoll 1989, 1998; Hobfoll and Shirom 2000) is that
strain is most likely to occur when (a) there is a perceived threat to one’s resources, (b) there
is an actual resource loss or (c) the anticipated return on investment of one’s resources does
not materialize. This theory proposes that people seek to acquire and maintain resources and
stress arises because there is a threat of a loss of resources, an actual loss in resources or lack
of an expected gain in resources. The term ‘resources’ refers to objects, conditions, personal
characteristics and energies that are valued by the individual (Hobfoll 1989). Thus, stressors
threaten valuable employee resources such as status, position, self-esteem and energy.
Hobfoll (1998) designated social support as one of the most important resources for dealing
with stressors, since it can both widen one’s pool of available resources and can replace or
reinforce other resources that have been lacking. That is, supervisor support may promote a
positive sense of self and a sense of security that in turn facilitates the preservation of these
and other valued resources, thereby preventing strain despite the threat represented by work
stressors (Hobfoll 1989). COR theory also incorporates the notion of resource appraisal
(Hobfoll 2001; Hobfoll and Kay 2007), suggesting that employees assess the extent to
which the resource (e.g. source of support) matches the stressor. Thus, for supervisor
support to have a buffering effect on the stressor–strain relationship, it needs to be
perceived by the subordinate as fitting the specific type of stressor. In particular, job-related
strain involves both mental and physical health over a relative long period of time (6 or 12
months). Following previous studies on strain (e.g. Spreitzer, Kizilos and Nason 1997;
Sprigg, Jackson and Parker 2000), we consider two aspects of job-related strain, namely
job-related tension or anxiety and medical physical symptoms.
To test this argument regarding fit, we focused on two stressors that have been
traditionally associated with employee strain, namely role conflict and physical working
conditions. On the one hand, role conflict, which has received a great deal of attention for
over four decades (e.g. Katz and Kahn 1966; Rizzo, House and Lirtzman 1970; Perrewe
et al. 2004), occurs when individuals experience two or more sets of incompatible role
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demands so that fulfilling one impedes the fulfilment of the other(s). Research has shown
that role conflict is closely related to the supervisor (O’Driscoll and Beehr 1994) and it is
associated with a number of dysfunctional outcomes, such as job dissatisfaction and
psychological strains (e.g. Jackson and Schuler 1985). On the other hand, poor working
conditions (Sutton and Rafaeli 1987; McCoy and Evans 2005), such as extreme
temperatures, inappropriate lighting, noise, crowding, and lack of space and privacy,
according to ergonomics research, are the result of occupational and organizational design,
which are typically beyond the control of the supervisor (Humphrey, Nahrgang and
Morgeson 2007; Dierdorff and Ellington 2008; Fritz and Sonnentag 2009). We have
focused on these two specific resources because they are viewed to have their origin at
differing sources, hence allowing us to test the source congruence hypothesis. In particular,
we expect role conflict to be originated from the supervisor, whereas physical stressor
would be originated from the organization. Thus, role conflict is source-congruent with
supervisor support, but physical stressors are not.
Hypotheses
Because one of the supervisor’s main responsibilities is to shape the employee’s role
expectations, employees are therefore likely to perceive their supervisor as the main source
of conflicting role demands (O’Driscoll and Beehr 1994). This line of thinking is consistent
with the fact that ‘the boss’ dominates anecdotal reports of complaints about conflicting
work assignments (e.g. Kellerman 2004). Thus, because role conflict and supervisor
support are likely to emanate from the same source (i.e. the supervisor), supervisor support
seems particularly prone to magnify the negative impact of this stressor (e.g. Rizzo, House
and Lirtman 1970; Perrewe et al. 2004). According to Kaufmann and Beehr (1986), when a
supervisor who is also the source of stress approaches employees to offer his/her support,
‘even this “friendly” approach may be experienced as stressful’ (p. 524). Under such
circumstances, supervisor support may be perceived as inconsistent and insincere (Kickul
and Posig 2001), and it may even provoke self-perceptions of incompetence in the
subordinate (Blaine, Crocker and Major 1995). Thus, we propose the following source
congruence hypothesis between supervisor support and role conflict.
Hypothesis 1: Supervisor support will have a reverse buffering effect on the relationship
between role conflict and strain so that role conflict will be more strongly
associated with strains (i.e. job tension and medical symptoms) when
supervisor support is high than when it is low.
In contrast, when stressors are typically attributed to the nature of the job, as it is the
case for poor physical working conditions (Sutton and Rafaeli 1987; McCoy and Evans
2005; Dierdorff and Ellington 2008), employees attribute less responsibility to supervisors
for the hardships of the physical environment. That is, even though managers may
influence employees’ individual working conditions through differential task assignments,
they are unlikely to control the fundamental physical conditions that define the job. Also,
supervisors know about these conditions and, therefore, may provide tips and support to
cope with this type of physical stressor (Beehr et al. 2003). Thus, we propose a source
incongruence hypothesis between supervisor support and physical stressors.
Hypothesis 2: Supervisor support will have a buffering effect on the relationship
between physical stressors and strain so that physical stressors will be
less strongly associated with strains (job tension and medical symptoms)
when supervisor support is high than when it is low.
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To provide a more comprehensive test of our theory, we compared the impact of
supervisor support with that of coworker support. Our reasoning for including coworker
support was twofold. First, support from coworkers is an important source of social
support for employees and therefore it is often included in this literature (Viswesvaran
et al. 1999). Second, although coworkers are certainly important role senders and can
influence the speed and coordination of work tasks, they do not typically have the authority
to shape employee work assignments in the manner that supervisors do. Therefore,
because employees are unlikely to attribute stressors such as role conflict or working
conditions to coworkers, one should not expect a reverse buffering effect for coworkers’
support. Instead, supportive coworkers may indeed buffer the effects of role conflict on
strain because they help employees vent their frustrations, provide fresh ideas that help
employees cope with conflicting role demands and coach employees to develop new
coping mechanisms. In line with these arguments, Beehr et al. (2003) found that coworker
support moderated the relationship between workload and psychological strain. Thus, we
expect a buffering effect.
Hypothesis 3: Coworker support will have a buffering effect on the relationship
between role conflict and strain so that role conflict will be less strongly
associated with strain (i.e. job tension and medical symptoms) when
coworker support is high than when it is low.
In addition, support from coworkers should also help neutralize the negative
consequences of physical stressors. Even though coworkers might influence working
conditions, they are hardly responsible for the general physical conditions at work, such as
the size of work stations, amount of storage space, visual privacy, air quality and
temperature. Coworkers can certainly be a source of noise and distraction (Oldham
and Rotchford 1983), but even if that is the case, work settings in which people encounter
frequent contact with others facilitate communication and interpersonal bonds (Oldham
and Brass 1979), which help reduce strain. For instance, there is ample evidence that
frequent communication with peers is related to higher levels of job satisfaction (Brass,
Galaskiewicz, Greve and Tsai 2004; Balkundi and Harrison 2006). Furthermore, a
supportive group of coworkers should help alleviate physical stressors because coworkers
share a common understanding of the same physical environment. Thus, we expect the
following buffering effect.
Hypothesis 4: Coworker support will have a buffering effect on the relationship
between physical stressors and strain so that physical stressors will be less
strongly associated with strain (i.e. job tension and medical symptoms)
when coworker support is high than when it is low.
Method
Participants
The data for this study were collected from 45 service and manufacturing organizations of
various sizes in the northeastern USA and Canada. In total, 768 completed surveys were
returned out of the 1291 distributed to employees at all job levels, yielding a response rate
of 59%. About half of participants were male (55.6%). Thirty percent were between 20 and
30 years of age, and 27% were between 30 and 40. Twenty-seven percent had an average
tenure with their organization of between 2 and 5 years, and 41% had their current
supervisors for the last 2–5 years.
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Data collection procedure
After initial contacts (via students enrolled in an MBA program at a large university in the
northeastern USA), requests to participate in a large-scale study were sent to supervisors
at 45 companies. These supervisors were asked to request their subordinates to participate
in the study and distribute the questionnaires. Completed surveys were returned in a
sealed envelope to the researchers. Employees received an explanation of the objectives
of the study and instructions for filling out the survey at a meeting of their work group
held during working hours. The work groups were defined as those employees reporting to
the same supervisor. Following this introduction, participants were asked to participate in
the study voluntarily by completing the survey, and they were also assured of the
anonymity of their responses. The purpose and procedure of the study were stated as
follows:
We are interested in learning more about the job situations of people working in variousindustries located within the Western New York and Southern Ontario Region. This surveyfocuses on three areas: (1) the potentially stressful aspects of your job, (2) your own senseof health and well-being, and (3) your supervisor’s style of interacting with you. To makethings easier and less time consuming, you will be asked to respond to a series of standardquestions and statements concerning each of these three areas. In all cases, you need onlywrite in the number which comes closest to providing the most accurate picture of you,your job and its context. Rest assured that your responses will remain completelyconfidential and anonymous. Your completed survey will be turned over to researchersat the University for analyses. No one will ever be able to connect your name with yourresponses.
We used a survey design because we were interested in targeting attitudinal outcomes
across a large sample of organizations in order to increase the generalizability of our
results. In addition, a survey design allowed us to collect data via well-tested scales in the
literature that provide reliable and valid measures of the theoretical constructs.
Measures
Social support. We assessed social support via the social support scale developed by
Caplan, Cobb, French, Van Harrison and Pinneau (1975). Items asked participants to
evaluate the extent to which their supervisor and coworkers provided social support.
The four items are: (1) How much does each of these people go out of their way to do
things to make your life easier for you? (2) How easy is it to talk with each of the following
people? (3) How much can each of these people be relied on when things get tough at
work? And (4) How much is each of the following people willing to listen to your personal
problems? For each question, participants evaluated the extent to which their supervisor
and their coworkers provided support, using a 5-point Likert scale ranging from ‘not at all’
(1) to ‘almost always’ (5). Each set of four items was summed into a global index of
support for each of the two sources. Cronbach’s a reliabilities were 0.87 and 0.82 for
supervisor and coworker support, respectively.
Role conflict. We assessed role conflict through the stress diagnostic survey developed
by Ivancevich and Matteson (1980). The five items included in this scale are as follows:
(1) I work on unnecessary tasks or projects, (2) I get caught in the middle between my
supervisor and my subordinates, (3) The formal chain of command is not adhered to,
(4) I do things on the job that are accepted by one person and not by others and (5) I receive
conflicting requests from two or more people. Respondents indicated the frequency of this
stressor using a 5-point scale ranging from ‘never’ (1) to ‘frequently if not always’ (5).
The scale’s Cronbach’s a was 0.73.
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Physical stressors. We measured physical stressors using Sutton and Rafaeli’s (1987)
18-item scale, which assesses the degree to which employees perceive their working
conditions (such as temperature, quality of light and space) as adequate. Answers ranged
from ‘very inadequate’ (1) to ‘very adequate’ (5). Cronbach’s a was 0.87.
Strain. Two forms of strain were assessed, namely job tension and medical symptoms.
Job tension was measured using the seven-item scale included in House and Rizzo’s
(1972) anxiety–stress questionnaire. This scale measures individuals’ feelings of irritation
and tension (e.g. ‘My job tends to directly affect my health’, ‘I work under a great deal of
tension’). The Cronbach’s a for the scale in this study was 0.85. To assess the degree to
which employees experienced medical symptoms, we provided participants with the list of
physical ailments in the Quick and Quick’s (1984) stress survey, which includes
headaches, nervousness, poor appetite, constipation, restlessness, cold sweats, heart
beating hard and hands trembling. Participants reported the frequency with which they had
experienced these medical symptoms in the past 12 months using a 5-point scale ranging
from ‘never’ (1) to ‘frequently if not always’ (5). The Cronbach’s a for the scale in this
study was 0.80.
Control variables. We controlled for employees’ age, gender, years of experience at
the company, years worked with the supervisor and dispositional optimism. Age and years
of experience at the company might provide employees with solid and stable social
support networks, including the relationship with their supervisors. For example, age has
been positively related to job and mental well-being (Siu, Spector, Cooper and Donald
2001). Gender is another variable that has been related to stress and social support. Men
and women often choose different career paths (Stroth and O’Reilly 1999) that lead to
different kinds of work stressors (Alvesson and Billing 1997) and develop different social
support networks (Ibarra 1992, 1993; McPherson, Smith-Lovin and Cook 2001).
Similarly, we expect the number of years working with the supervisor to have a positive
effect on the quality of the relationship, as interpersonal problems between leaders and
followers will result in attrition. Finally, we included dispositional optimism to control for
the potential effect of negative affectivity (Watson, Pennebaker and Folger 1987).
Dispositional optimism has been found to buffer the relationship between stressors and
strain (Scheier and Carver 1985, 1992), and it has also shown a positive relationship with
social support (Brissette, Scheier and Carver 2002). We measured dispositional optimism
using the nine-item life orientation test (Scheier and Carver 1985). Each item is scored on
a 5-point scale ranging from ‘not at all true’ (1) to ‘frequently if not always true’ (5), and
the scale yielded a Cronbach’s a of 0.68.
Measurement model
To evaluate the extent to which our findings were influenced by common method
variance, we followed the procedure recommended by Podsakoff, MacKenzie, Lee, and
Podsakoff (2003) and employed by Ahuja, Chudoba, Kacmar, McKnight and George
(2007) and by Carlson and Kacmar (2000). Following this approach, we estimated three
models: (1) a null measurement model, (2) a multifactor trait measurement model with
the proposed latent constructs and (3) a trait measurement model with an additional
method factor. If a common method effect existed, model 3 would fit the data
significantly better than model 2. Then we would need to determine the amount of
variance in the model contributed by the single method factor. To do that, we computed
the average variance extracted (AVE) for the latent constructs against the method factor.
It has been argued that, to rule out the presence of pervasive method variance, the
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variance explained by the method factor should be less than 25% of the total variance
(Williams, Cote and Buckley 1989).
Three models were estimated through confirmatory factor analysis (CFA) using AMOS
7.0 (Arbuckle 2006). The results of the CFA were as follows: null model, x 2 ¼ 9125,
df ¼ 1540, p , 0.001; Tucker–Lewis index, TLI ¼ 0.38, comparative fit index,
CFI ¼ 0.40, root mean square error of approximation, RMSEA ¼ 0.10; multifactor trait
model with eight factors, x 2 ¼ 3342, df ¼ 1488, p , 0.001; TLI ¼ 0.90, CFI ¼ 0.91,
RMSEA ¼ 0.05; and multifactor trait model with a single method factor, x 2 ¼ 3123,
df ¼ 1480, p , 0.001; TLI ¼ 0.92, CFI ¼ 0.93, RMSEA ¼ 0.04. The eight-factor model
provided a good fit to the data, with RMSEA scores below 0.06, whereas TLI and CFI were
above 0.90 (Bentler and Bonnet 1980). The loadings from model 3 were then used to
compute the AVE for each latent construct, including the method factor. The results
indicated that, although model 3 fitted the data better than model 2 (Dx 2 ¼ 219, df ¼ 8),
the method factor accounted for only 16% of the total variance – less than the 25% cut-off
recommended by Williams et al. (1989). Thus, we concluded that common method
variance did not significantly contaminate the results.
Data analyses
To test the hypotheses, we used moderated hierarchical regression analyses computed in
accordance with the procedure delineated by Aiken and West (1991). To test the ‘reverse
buffering effect’, we first computed the interaction term or cross-product between
supervisor support and role conflict. We expected that the sign of this interaction would be
positive when predicting strain, such that the relationship between role conflict and strain
would be stronger under high supervisor support. In contrast, to test the ‘buffering effect’,
we computed three interaction or cross-product terms: supervisor support and physical
stressors, coworker support and role conflict, and coworkers support and physical stressors.
According to our hypotheses, we expected a negative sign of these interactions when
predicting strain. The statistical significance of the interaction or moderation effect was
assessed after controlling for all main effects. Control variables (demographic variables,
optimism) were entered first in the models, followed by the main effects of physical
stressors and role conflict. The two sources of social support were entered in the next step,
and the interaction terms in the final step.
Results
Descriptive statistics
Descriptive statistics, reliabilities and correlations for all variables are reported in Table 1.
The bivariate correlations indicated that the relationships between sources of social support
and strain were negative. Supervisor support had negative and statistically significant
correlations with job tension (r ¼ 20.27, p , 0.01) and medical symptoms (r ¼ 20.27,
p , 0.01). The same correlation pattern emerged for coworker support, although
correlations with job tension (r ¼ 20.21, p , 0.01) and medical symptoms (r ¼ 20.21,
p , 0.01) were smaller. Role conflict had positive and statistically significant correlations
with job tension (r ¼ 0.46, p , 0.01) and medical symptoms (r ¼ 0.36, p , 0.01).
Physical stressors had positive and statistically significant correlations with job tension
(r ¼ 0.26, p , 0.01) and medical symptoms (r ¼ 0.24, p , 0.01). In addition, optimism
had a negative correlation with job tension (r ¼ 20.25, p , 0.01) and medical symptoms
(r ¼ 20.36, p , 0.01).
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Tab
le1
.D
escr
ipti
ve
stat
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rrel
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ater
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nt
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e,1¼
20
or
less
,2¼
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s,3¼
40
s,4¼
50
s,5¼
60
so
rm
ore
;g
end
er,
1¼
mal
e,2¼
fem
ale;
yea
rsat
the
com
pan
yan
dy
ears
wo
rked
wit
hsu
per
vis
or,
1¼
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than
2,
2¼
2–
5,
3¼
6–
10
,4¼
11
–1
5,
5¼
more
than
15
.
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Tests of hypotheses
Table 2 shows that the interaction terms predicted incremental variance beyond main
effects for the two dependent variables (job tension and medical symptoms). To minimize
the threat of multicollinearity, we centered all independent variables before entering them
into the regression equations (Aiken and West 1991). No evidence of multicollinearity was
detected, according to Kleinbaum, Kupper and Mueller’s (1988) criteria for variance
inflation factor (VIF) and tolerance criteria. Also, the Durbin–Watson statistics for all
analyses indicated that errors were not correlated (Ryan 1997).
Buffering effects of supervisor support. Hypothesis 1 predicted a reverse buffering
effect of supervisor support on the relationship between role conflict and strain.
The supervisor support £ role conflict interaction emerged as a positive and statistically
significant predictor of job tension (b ¼ 0.12, p , 0.01) and medical symptoms
(b ¼ 0.07, p , 0.05). To further examine whether the nature of this interaction conformed
to the reverse buffering effects of supervisor support predicted by our hypotheses, we
plotted the interactions using Aiken and West’s (1991) procedures. Figure 1(a), (b) shows
that, as Hypothesis 1 predicted, the association of role conflict with both job tension and
medical symptoms was stronger when supervisory support was high than when it was low.
In contrast, Hypothesis 2 predicted a positive buffering effect for supervisor support
when the stressor is the physical environment. As we expected, the unfavorable or reverse
buffering effect of supervisor support was limited to the experience of role conflict and did
not apply to the effects of physical stressors on strain. Indeed, there was a significant
buffering effect of supervisor support on the relationship between physical stressors and
medical symptoms (b ¼ 20.08, p , 0.05, Figure 1(c)). That is, the negative consequences
of physical stressors on medical symptoms were weaker when supervisory support was high
than when it was low. Although statistically non-significant, a similar trend was detected for
job tension.
Buffering effects of coworker support. Hypotheses 3 and 4 predicted that support from
coworkers would buffer the negative effects of both role conflict and physical stressors.
Table 2 shows that the coworker support £ role conflict interaction term had a negative
and statistically significant relationship with job tension (b ¼ 20.10, p , 0.05) and
medical symptoms (b ¼ 20.09, p , 0.05). Again, we further examined the direction of
the moderating effects by plotting the interactions using Aiken and West’s (1991)
procedures. As we expected, role conflict had significantly weaker associations with job
tension (Figure 2(a)) and medical symptoms (Figure 2(b)) when employees reported high
rather than low coworker support, thereby supporting Hypothesis 3. However, the
coworker support £ physical stressors interaction did not reach statistical significance
predicting either job tension or medical symptoms. These results failed to support
Hypothesis 4.
We repeated the regression analyses and examined the moderating effect of optimism
on the relationship between role conflict and strain after controlling for social support.
The results failed to yield statistically significant interactions between role conflict and
optimism or between physical stressors and optimism, hence strengthening the argument
that social support, and not optimism, accounted for the buffering effects between work
stressors and strain.
A post hoc test of stressor–support source congruence
COR theory underscores the importance of source congruence between stressors and
support (Hobfoll 2001). We have argued that role conflict is more likely to be attributed to
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Tab
le2
.R
esu
lts
of
hie
rarc
hic
alre
gre
ssio
nan
aly
ses
on
stra
in.
Jobtension
Medicalsymptoms
Stepsandvariables
12
31
23
1.
Co
ntr
ols
Ag
e0
.03
0.0
30
.03
20
.11*
*2
0.1
0*
*2
0.1
0*
*G
end
er0
.02
0.0
20
.02
0.2
0*
*0
.20
**
0.2
0*
*Y
ears
atth
eco
mp
any
0.1
6*
*0
.15
**
0.1
6*
*0
.06
0.0
60
.07*
Yea
rsw
ith
sup
erv
iso
r0
.05
0.0
50
.05
20
.04
20
.03
20
.02
Op
tim
ism
20
.16
**
20
.15
**
20
.15
**
20
.28*
*2
0.2
7*
*2
0.2
7*
*R
ole
con
flic
t0
.39
**
0.3
7*
*0
.37
**
0.2
6*
*0
.24
**
0.2
4*
*P
hy
sica
lst
ress
ors
0.1
1*
*0
.10
**
0.0
9*
*0
.07*
0.0
6*
0.0
6*
2.
Su
pp
ort
Su
per
vis
or
sup
po
rt2
0.0
6*
20
.07
*2
0.0
52
0.0
7*
Co
wo
rker
ssu
pp
ort
20
.06
*2
0.0
42
0.0
6*
20
.04
3.
Inte
ract
ion
sS
up
erv
iso
rsu
pp
ort£
role
con
flic
t0
.12
**
0.0
7*
Su
per
vis
or
sup
po
rt£
ph
ysi
cal
stre
sso
rs2
0.0
22
0.0
8*
Co
wo
rker
ssu
pp
ort£
role
con
flic
t2
0.1
0*
*2
0.0
9*
*C
ow
ork
ers
sup
po
rt£
ph
ysi
cal
stre
sso
rs2
0.0
52
0.0
2R
20
.28
**
0.2
9*
*0
.31
**
0.2
8*
*0
.29
**
0.3
0*
*DR
20
.01
*0
.02
**
0.0
1*
*0
.01*
No
te.A
ge,
1¼
20
or
less
,2¼
30
s,3¼
40
s,4¼
50
s,5¼
60
so
rm
ore
;g
end
er,1
¼m
ale,
2¼
fem
ale;
yea
rsat
the
com
pan
yan
dy
ears
wo
rked
wit
hsu
per
vis
or,
1¼
less
than
2,2
¼2
–5
,3¼
6–
10
,4¼
11
–1
5,
5¼
mo
reth
an1
5.
*p,
0.0
5;
**p,
0.0
1.
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supervisors than to peers, customers and other organizational stakeholders. To test the
assumption that employees are more likely to perceive supervisors as the source of their
role conflict, but not as the source of physical stressors, we conducted a separate
supplementary study using a different sample. Participants used a 5-point scale ranging
from 1 (not at all) to 5 (almost always) to answer the following six questions: ‘To what
extent do you find inadequate physical conditions at work emanating from your (1)
supervisors, (2) coworkers and (3) organization?’ and ‘To what extent do you find role
–0.8
–0.6
–0.4
–0.2
0
0.2
0.4
0.6
0.8(a)
(b)
(c)
Role Conflict
Job
Ten
sion
Low Supervisor Support
High Supervisor Support
–0.8
–0.6
–0.4
–0.2
0
0.2
0.4
0.6
0.8
Role Conflict
Med
ical
Sym
ptom
s
–0.8
–0.6
–0.4
–0.2
0
0.2
0.4
0.6
0.8
Physical Stressors
Med
ical
Sym
ptom
s
Low Supervisor Support
High Supervisor Support
Low Supervisor Support
High Supervisor Support
Figure 1. Reverse buffering effects of supervisory support for (a) role conflict predicting jobtension, (b) role conflict predicting medical symptoms and (c) physical stressors predicting medicalsymptoms.
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conflict at work emanating from your (1) supervisors, (2) coworkers and (3) organization?’
A sample of 131 employed individuals enrolled in an executive MBA program in Spain
completed the questionnaire. The average age of sample members was 32, the average
work experience was 9 years and 74% of this sample was male.
As we expected, role conflict was primarily attributed to the supervisor, and not to the
coworkers (Msupervisor ¼ 3.37 vs. Mcoworker ¼ 1.57, d ¼ 1.80; t(130) ¼ 24.14, p , 0.001) or
to the organization (Msupervisor ¼ 3.37 vs. Morganization ¼ 2.24, d ¼ 1.13; t(130) ¼ 12.79,
p , 0.001). Also as we expected, physical stressors were attributed primarily to the
organization, and not to the supervisors (Morganization ¼ 2.55 vs. Msupervisor ¼ 1.36,
d ¼ 1.19; t(130) ¼ 12.59, p , 0.001) or to the coworkers (Morganization ¼ 2.55 vs.
Mcoworker ¼ 1.19, d ¼ 1.36; t(130) ¼ 12.17, p , 0.001). These results are consistent with
our assumption that role conflict is source congruent primarily with supervisor rather than
coworker support.
Discussion
Contributions to theory
This study contributes to clarify the mixed evidence concerning the buffering and reverse
buffering effects of supervisor support in regard to the impact of work stressors on
employee strain. The results are largely consistent with our source congruence hypotheses,
suggesting that supervisor support may be beneficial when it counteracts stressors that are
–0.8
–0.6
–0.4
–0.2
0
0.2
0.4
0.6
0.8(a)
(b)
Role Conflict
Job
Ten
sion
Low Coworker Support
High Coworker Support
–0.8
–0.6
–0.4
–0.2
0
0.2
0.4
0.6
0.8
Role Conflict
Med
ical
Sym
ptom
s
Low Coworker Support
High Coworker Support
Figure 2. Buffering effects of coworker support for role conflict predicting (a) job tension and (b)medical symptoms.
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originated outside of the supervisor’s realm, such as physical stressors. In contrast,
supervisor support may increase subordinates’ strains when stressors deemed to be
originated in the supervisor, such as role conflict.
Our finding concerning the simultaneous occurrence of opposite buffering effects of
supervisor support is noteworthy, because such a finding has proven elusive in prior
studies. In what was possibly the first study explicitly designed to identify the conditions
under which reverse buffering occurs. Beehr et al. (2003) found no support for the
hypothesis that a reverse buffering effect occurs when the source of supervisor support
coincides with the source of the stressor. Beehr et al. (2003) speculated that the lack of
empirical support might have been due, in part, to a small sample size. They also noted that
there are multiple interpretations of the concept of source congruence, and called for
additional research on alternative forms of fit between work stressors and social support.
Based on the COR framework, we found support for the notion that role conflict and
physical conditions are two stressors likely to have differential effects when interacting
with supervisor support. Our results hint that although supervisor support alleviates
medical symptoms originated by physical stressors, it magnifies the unfavorable effects of
role conflict on both job tension and medical symptoms.
An alternative causal explanation for the reverse buffering effect of social support has
been that stressors lead to strain, which in turn leads employees (as proactive agents) to
seek social support (Kaufmann and Beehr 1986). We addressed this issue by examining
the effects of support from coworkers. If employees actively seek support when stressors
are related to strain, then we should find reverse buffering effects for both supervisor and
coworker support. However, we found that only supervisor support exacerbated the
association between role conflict and strain. This finding supports the source congruence
explanation.
Lastly, our results indicated that supervisor support had stronger direct associations
with strains than did coworker support: correlations between supervisor support and
strains (job tension and medical symptoms were 20.27 and 20.27 vs. correlations of
20.21, 20.21, between coworker support and the same strains). The magnitude of these
differences is similar to that reported in Viswesvaran et al.’s (1999) meta-analysis. When
compared to the relatively modest effect sizes associated with both positive and negative
buffering uncovered here and elsewhere (Viswesvaran et al. (1999) reported similar DR 2
ranging from 0.01 to 0.03), these correlations suggest that supervisor support is still a more
powerful reducer of employee strain than coworker support is, despite the former’s
potential for reverse buffering.
Limitations and future research
In spite of the large sample size and the high response rate, our design had some
limitations. First, associations among self-reported variables might have been inflated by
common method variance, but our CFAs suggested that such inflation was minimal in our
case. In addition, nonlinear effects such as the interactions that captured the buffering
effects are hardly attributable to method bias (Aiken and West 1991). Second, our cross-
sectional design precluded cause-and-effect determinations, and future longitudinal and
experimental research may help clarify the causal direction of these findings. More
nuanced relationships between stressors and support should be examined in future
research. For instance, Harris and Kacmar (2006) found a U-shape curvilinear relationship
between the quality of the relationship between leaders and followers so that employees in
high-quality leader member exchange (LMX) relationships with their supervisors
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paradoxically experienced more stress than did their colleagues in moderate-quality LMX
relationships. Finally, we examined solely self-reported measures of strain. Our reliance
on self-reports undoubtedly facilitated gathering data from a large sample, thus increasing
the statistical power needed to detect the kind of interaction or buffering effects that we
sought. Even though there is a well-documented empirical association between
psychological and physiological measures of strains (Fox, Dwyer and Ganster 1993;
Sprigg, Stride, Wall, Holman and Smith 2007), a broader set of strain measures that also
encompasses directly measurable physiological outcomes such as cortisol levels, muscular
disorders and blood pressure should be included in future studies.
Implications and conclusions
The most straightforward implication of our study is that managers should be aware of the
sources of stressors impinging on their subordinates before they possibly overwhelm them
with their support. For this reason, it is important that they develop observation and
diagnostic skills to assess the origin of stressors affecting their subordinates, and then offer
the kind of support that is most likely to match the stressor. When the source of employees’
stressors is largely unrelated to their supervisors (e.g. physical conditions), supervisors
may be in the best position of truly alleviating the negative consequences of stressors.
However, if the source of stressors is perceived to be linked to the supervisor, as it appears
to be the case of role conflict, supervisor support may make matters worse. Employees
should also remain aware of instances when ‘talking to the boss’ may not be the best
approach to reduce tension (Harris and Kacmar 2006). Our results suggest that this
scenario is likely when the source of stressors is also the supervisor, who may end up
aggravating the stressor–strain relationship.
In short, while supervisor support has undeniable beneficial effects to alleviate
employee strain, it also has the potential for making matters worse when support comes
from the same source as stressor at hand. We hope that our findings stimulate further
research on the boundary conditions influencing the extent to which social support and
other resources adequately match work stressors (Beehr et al. 2003; de Jonge and
Dormann 2006).
Acknowledgement
This research was partially funded by a research grant from the Ministry of Science and Innovationof Spain # ECO2009-12952 to Margarita Mayo.
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