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Clarifying Work-Family Intervention Processes: The Roles of Work-Family Conflict and Family-Supportive Supervisor Behaviors


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Drawing on a conceptual model integrating research on training, work–family interventions, and social support, we conducted a quasi-experimental field study to assess the impact of a supervisor training and self-monitoring intervention designed to increase supervisors' use of family-supportive supervisor behaviors. Pre- and postintervention surveys were completed, 9 months apart, by 239 employees at 6 intervention (N = 117) and 6 control (N = 122) grocery store sites. Thirty-nine supervisors in the 6 intervention sites received the training consisting of 1 hr of self-paced computer-based training, 1 hr of face-to-face group training, followed by instructions for behavioral self-monitoring (recording the frequency of supportive behaviors) to facilitate on-the-job transfer. Results demonstrated a disordinal interaction for the effect of training and family-to-work conflict on employee job satisfaction, turnover intentions, and physical health. In particular, for these outcomes, positive training effects were observed for employees with high family-to-work conflict, whereas negative training effects were observed for employees with low family-to-work conflict. These moderation effects were mediated by the interactive effect of training and family-to-work conflict on employee perceptions of family-supportive supervisor behaviors. Implications of our findings for future work–family intervention development and evaluation are discussed.
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Clarifying Work–Family Intervention Processes:
The Roles of Work–Family Conflict and Family-Supportive
Supervisor Behaviors
Leslie B. Hammer
Portland State University
Ellen Ernst Kossek
Michigan State University
W. Kent Anger
Oregon Health & Science University
Todd Bodner and Kristi L. Zimmerman
Portland State University
Drawing on a conceptual model integrating research on training, work–family interventions, and social
support, we conducted a quasi-experimental field study to assess the impact of a supervisor training and
self-monitoring intervention designed to increase supervisors’ use of family-supportive supervisor behaviors.
Pre- and postintervention surveys were completed, 9 months apart, by 239 employees at 6 intervention (N
117) and 6 control (N122) grocery store sites. Thirty-nine supervisors in the 6 intervention sites received
the training consisting of 1 hr of self-paced computer-based training, 1 hr of face-to-face group training,
followed by instructions for behavioral self-monitoring (recording the frequency of supportive behaviors) to
facilitate on-the-job transfer. Results demonstrated a disordinal interaction for the effect of training and
family-to-work conflict on employee job satisfaction, turnover intentions, and physical health. In particular, for
these outcomes, positive training effects were observed for employees with high family-to-work conflict,
whereas negative training effects were observed for employees with low family-to-work conflict. These
moderation effects were mediated by the interactive effect of training and family-to-work conflict on
employee perceptions of family-supportive supervisor behaviors. Implications of our findings for future
work–family intervention development and evaluation are discussed.
Keywords: work–family intervention, family-friendly practices, supervisor training, supervisor support
Although the importance of increasing employers’ work–family
support has been widely advocated, there are two primary gaps in
the literature indicating a need for more rigorous longitudinal and
quasi-experimental research that is based on theory and designed
to examine the processes and mechanisms by which this support
operates. First, the work–family field is in need of studies that
integrate research on family-specific supervisor support and work–
family conflict with actual workplace human resource initiatives
such as training designed to increase this support. Although there
is a growing literature on the importance of perceived organiza-
This article was published Online First September 20, 2010.
Leslie B. Hammer, Todd Bodner, and Kristi L. Zimmerman, Department
of Psychology, Portland State University; Ellen Ernst Kossek, Organiza-
tional Behavior and Human Resource Management, School of Human
Resources and Labor Relations, Michigan State University; W. Kent An-
ger, Center for Research on Occupational and Environmental Toxicology,
Oregon Health and Science University.
Kristi L. Zimmerman is now located at Pacific Research and Evaluation,
Portland, Oregon.
The contents of this article are solely the responsibility of the authors
and do not necessarily represent the official views of the institutes and
offices identified below. Oregon Health & Science University (OHSU) and
W. Kent Anger have a significant financial interest in Northwest Education
Training and Assessment, LLC, a company that has a commercial interest
in research results associated with the use of the cTRAIN program. This
potential individual and institutional conflict of interest has been reviewed
and managed by OHSU. This research was partially supported by the
Work, Family and Health Network, which is funded by a cooperative
agreement through the National Institutes of Health and the Centers for
Disease Control and Prevention: National Institute of Child Health and
Human Development (Grants U01HD051217, U01HD051218,
U01HD051256, U01HD051276), National Institute on Aging (Grant
U01AG027669), Office of Behavioral and Social Sciences Research, and
National Institute for Occupational Safety and Health (Grant
U010H008788). Special acknowledgment goes to extramural staff science
collaborator Rosalind Berkowitz King (National Institute of Child Health
and Human Development) and Lynne Casper (now of the University of
Southern California) for design of the original Workplace, Family, Health
and Well-Being Network Initiative. Persons interested in learning more
about the Network should go to
We also want to thank Nannette Yragui, Jill Arnold, Pauline Acosta, Mindy
Holdsworth, Shaun Pichler, Ryan Petty, Rachel Daniels, Lauren Murphy,
Tina Riley, and Kara Burt for help with data collection. We would like to
thank the employer and employees who gave their time and support to
participate in this study. And finally, we would like to thank the Portland
State University Department of Psychology and the Michigan State Uni-
versity School of Human Resources and Labor Relations for administrative
and scholarly support of this study.
Correspondence concerning this article should be addressed to Leslie B.
Hammer, Department of Psychology, Portland State University, PO Box
751, Portland, OR 97207-0751. E-mail:
Journal of Applied Psychology © 2010 American Psychological Association
2011, Vol. 96, No. 1, 134–150 0021-9010/10/$12.00 DOI: 10.1037/a0020927
tional and supervisor support for family in relation to key work–
family outcomes (cf. Allen, 2001), more research is needed to
examine the processes by which employee perceptions of family-
specific supervisor support link to human resource change initia-
tives. Specifically, supervisor training to increase support for fam-
ily is currently among the most frequently advocated interventions
by work–life experts (cf. Hopkins, 2005). Further, although hun-
dreds of studies have examined perceived organizational support
for the family, the antecedents of work–family conflict, and how
work–family conflict relates to key outcomes such as job satisfac-
tion (cf. Eby, Casper, Lockwood, Bordeaux, & Brinley, 2005;
Kossek & Ozeki, 1998, 1999), this literature is not well connected
to the research on work–family interventions.
A second gap that has been identified in recent reviews pertains
to the need for improvement not only in the quality of intervention
research but also in workplace intervention research in general
(Macik-Frey, Quick, & Nelson, 2007; Scharf et al., 2008), and
specifically within the work–family field (Casper, Eby, Bordeaux,
Lockwood, & Lambert, 2007; Kelly et al., 2008). Critics of prior
intervention research have argued that much of this work has
limited effectiveness due to the use of tertiary prevention models
rather than primary or secondary prevention models (Quick &
Tetrick, 2003), and because this research frequently takes an
individual rather than a workplace change perspective (Lamon-
tagne, Keegle, Louie, Ostry, & Landsbergis, 2007; Scharf et al.,
2008). In addition, relatively little research on the design of human
resource interventions and work–family policies has been trans-
lated into actual organizational practice (Rynes, Colbert, & Brown,
2002). Very little work–family research has been implemented
using quasi-experimental designs to assess interventions (e.g.,
Kelly et al., 2008; Lamontagne et al., 2007; Scharf et al., 2008).
Finally, workplace interventions to reduce job stress and work–
family stress have been criticized as poorly designed and imple-
mented, suggesting that more research is needed to clarify the
conditions under which these interventions are likely to be most
successful (Lamontagne et al., 2007). For example, certain inter-
ventions may be particularly effective for specific subgroups
within the organization and must in turn be designed to target those
“in need” of the intervention, rather than the entire organization.
Study Goals, Model Overview, and Theoretical
To address these gaps in work–family intervention research, the
current study evaluated the conditions and processes under which
a work–family intervention, designed to increase employee per-
ceptions of family-specific support, led to increased job satisfac-
tion, decreased intentions to turnover, and improved physical
health. Integrating theory from research on training, work–family
interventions, social support, and perceived organizational support,
we developed and tested the model shown in Figure 1. This model
highlights the moderating effects of work–family conflict and the
processes by which a family-supportive supervisor intervention
impacts job and health outcomes. Using a longitudinal quasi-
experimental design, we tested the model by assessing the impact
of a training and self-monitoring intervention designed to increase
supervisors’ use of family-supportive supervisor behaviors (FSSB;
Hammer, Kossek, Zimmerman, & Daniels, 2007) on health and
job outcomes.
Overall, the model has three tenets. First is the premise that the
effectiveness of a family-supportive training intervention will vary
depending on the degree of employee need for support. Specifi-
cally, employee need for support is operationalized as those with
high levels of work-to-family conflict and family-to-work conflict,
compared with those with low levels of such conflict. Thus,
relationships between the intervention and positive health and
work outcomes are expected to be moderated by work–family
conflict. Here we argue that those employees with higher levels of
both work-to-family conflict and family-to-work conflict have a
greater psychological need for support.
Second, we assume that increasing perceptions of work–family-
specific supervisor support is necessary to improve work, family,
and health outcomes and that this support is more strongly related
to work–family conflict than is more general supervisor support
(Kossek, Pichler, Bodner, & Hammer, in press). Although general
supervisor support has been shown to enhance employee job
attitudes such as job satisfaction (Thomas & Ganster, 1995;
Thompson & Prottas, 2005) and to be negatively related to turn-
over intentions (Thompson, Beauvais, & Lyness, 1999; Thompson
Job Satisfaction
Physical Health
Figure 1. Conceptual model of linkages between a work–family intervention designed to increase family-
supportive supervisor behaviors (FSSB) and job and health outcomes.
& Prottas, 2005), recent research has also demonstrated that em-
ployee perceptions of FSSB are positively related to these out-
comes over and above the effects of general supervisor support
(Hammer, Kossek, Yragui, Bodner, & Hanson, 2009). Thus, we
focused our intervention to support work–family needs in order to
produce stronger effects than would result from more general
supervisor support. As with the findings of Karasek (1979) on the
moderating effects of supervisor support on high-strain jobs, we
expected that employee reports of physical health will improve
when supervisors are trained to be more supportive of family
Third, we suggest that an employee’s perception of work–family
supervisor support is the mechanism, or mediating process,
through which our work–family intervention relates to job and
health outcomes. We expect that employees who perceive greater
FSSB from supervisors will have additional resources and be
likely to have more control over management of work and family
demands that should lead to positive job and health outcomes.
Below we provide background drawn from the training and self-
monitoring literatures on the rationale for the design of the specific
intervention we developed to test our model. This is followed by
the theoretical rationale for the model hypotheses and constructs.
FSSB Training and Self-Monitoring: An Effective
Work–Family Intervention
Although some research exists on the availability and use of
work–family supportive policies and practices, there is a lack of
evaluation of the effects of those policies and practices on indi-
vidual and organizational outcomes (e.g., Kelly et al., 2008). The
family-supportive supervisor has been defined as one who empa-
thizes with an employee’s desire to seek balance between work
and family responsibilities (Thomas & Ganster, 1995). New re-
search has been conducted to clarify the FSSB construct, and this
research forms the basis for the development of our training and
self-monitoring intervention (Hammer et al., 2009).
FSSB is conceptualized as behaviors exhibited by supervisors
that are supportive of families and consists of the dimensions of
emotional support (supervisors providing support by listening and
showing care for employees’ work–family demands), instrumental
support (supervisors responding to an employee’s work and family
needs in the form of day-to-day management transactions), role-
modeling behaviors (supervisors demonstrating how to synthesize
work and family through modeling behaviors on the job), and
creative work–family management (supervisor-initiated actions to
restructure work to facilitate employee effectiveness on and off the
job; Hammer et al., 2009; Hammer et al., 2007). Thus, our super-
visor training focused on teaching behaviors to supervisors who
would implement this FSSB construct in their workplace.
Supervisors and companies often face barriers and challenges in
fully implementing family-supportive workplace policies and
practices (Ryan & Kossek, 2008). One reason for this is that
supervisor support for family has only recently become a popular
issue in the workplace, and it is a relatively new expectation that
managers demonstrate family support on the job (Lirio, Lee,
Williams, Haugen, & Kossek, 2008). Consequently, we anticipate
that supervisors may not necessarily exhibit high levels of FSSB
without being trained. Trained supervisors would better understand
the rationale for FSSB and be socialized to see FSSB as important
to exhibit. Trained supervisors would also have a greater under-
standing of how actually to engage in these behaviors and would
view the training as a signal that the organization values support of
employees’ work–family needs. Taken together, we believe that
supervisors who are trained to exhibit FSSB will be more likely to
have employees who perceive them as being more supportive of
work–family needs.
Although training supervisors is a good first step toward in-
creasing supervisor support for work–family demands, when im-
plemented, many organizations conduct training as an isolated
change strategy. In line with the training research, we argue that it
is critical for training to include a design that fosters motivation to
transfer the training content to the job (e.g., M. J. Burke & Day,
1986; Ford, Kozlowski, Kraiger, Salas, & Teachout, 1997). M. J.
Burke et al. (2006) conducted a meta-analysis of 95 quasi-
experimental workplace safety and health intervention studies and
found limited evidence of effective training when there was little
engagement of participants. They calculated effect sizes for those
methods they categorized as highly engaging (interactive face-to-
face training), moderately engaging (interactive training such as
computer based with feedback), and least engaging (printed ma-
terials) and found that only highly engaging training designed to
motivate training transfer was associated with large effect sizes
(d0.8) per Cohen (1988). Thus, it is important to strengthen the
effects of training programs by increasing the engagement of
Training effectiveness may be more engaging if the training
includes a component that motivates individuals to transfer newly
learned skills to the actual work environment. One approach for
supporting transfer of training is to ask individuals to set goals,
monitor their behavior over time, and discuss results. Such behav-
ioral self-monitoring processes are widely applied in clinical set-
tings to motivate behavior change (Elliott, Miltenberger, Kaster-
Bundgaard, & Lumley, 1996; Korotitsch & Nelson-Gray, 1999)
and are increasingly used in workplace settings to support the
transfer of training (Olson & Winchester, 2008). Behavioral self-
monitoring is a technique in which individuals repeatedly observe,
evaluate, and record aspects of their own behavior (e.g., Hickman
& Geller, 2003a, 2003b; Krause, 1997; McCann & Sulzer-Azaroff,
1996; Olson & Austin, 2001). Olson and Winchester (2008) con-
ducted a meta-analysis on 24 studies of behavioral self-monitoring
in different workplaces. They calculated a mean effect size of 2.2
for studies of self-monitoring, demonstrating the importance of
designing attitudinal and behavioral change training that motivates
transfer of training to the workplace. In the present study, we
implemented a work–family training intervention that informed
supervisors about the importance of increasing work–family-
specific supportive behaviors and asked supervisors to set goals to
self-monitor the frequency of FSSB for several weeks after the
Work–Family Conflict: A Moderator of the
Effectiveness of a Work–Family Intervention
Many studies of work–family policies and initiatives are based
on correlational designs. Few evaluations of work–family inter-
ventions have been based on quasi-experimental designs. In one of
the few published quasi-experimental work–family interventions,
Kossek and Nichol (1992) demonstrated that the positive results of
using an on-site child care center were more beneficial for those in
need of the intervention, such as employees with young children
who needed organizational support for family responsibilities.
Similarly, we believe that the FSSB training and self-monitoring
intervention will vary in effectiveness depending on individual-
level work–family conflict (work to family and family to work).
Given the well-documented finding that individuals with high
work–family conflict are more likely to have higher intentions to
turnover, lower reports of health (Allen, Herst, Bruck, & Sutton,
2000; Greenhaus, Parasuraman, & Collins, 2001), and lower job
satisfaction (Allen et al., 2000; Eby et al., 2005; Kossek & Ozeki,
1998), we expected that training supervisors to be more supportive
of family needs would be more effective for employees who
experience high work–family conflict (both work-to-family con-
flict and family-to-work conflict) compared with those with low
work–family conflict.
In addition, some theorists would argue that a supervisor support
intervention would generally have a stronger effect on reducing
work-to-family conflict compared with family-to-work conflict
because the source of the support is the supervisor (i.e., work
related; Frone, Russell, & Cooper, 1992). However, given that our
intervention is specific to family-supportive supervision, we be-
lieve that there is just as much of an argument that it would be
effective in reducing family-to-work conflict, because having a
supportive supervisor could make it easier for employees to re-
structure work to handle family demands. This is also consistent
with findings of the reciprocal, bidirectional effects and moderate
to high correlations found between work-to-family conflict and
family-to-work conflict (e.g., Frone et al., 1992). Thus, we are not
hypothesizing differential effects for work-to-family conflict as a
moderator versus family-to-work conflict as a moderator. Rather,
we expected that both directions of work–family conflict would
moderate the effects of the training on work and health outcomes.
This led to our first hypothesis:
Hypothesis 1: Employee work–family conflict will moderate
the effects of the family-supportive supervisor training inter-
vention on employee job satisfaction, turnover intentions, and
physical health. In particular, employees with higher levels of
work–family conflict (i.e., work-to-family conflict and
family-to-work conflict) in stores where managers receive
training will report higher levels of physical health and job
satisfaction and lower levels of turnover intentions compared
with employees with higher levels of work–family conflict in
stores where managers did not receive the training. These
differences between the treatment and control conditions will
be smaller for employees with lower levels of work–family
Employee Perceptions of FSSB: A Mediator of the
Moderating Effects of Work–Family Conflict and
Work–Family Intervention Effectiveness
Poor psychosocial work environments, including a combination
of high demands, low control, and low support, are related to poor
health (e.g., Belkic, Landsbergis, Schnall, & Baker, 2004; de
Lange, Taris, Kompier, Houtman, & Bongers, 2003; Landsbergis,
1988). Drawing on the demand– control–support and the conser-
vation of resources (Hobfoll, 1989) models, we theorized that
increasing supervisor support for family gives employees greater
perceptions of social support in the workplace as well as greater
control over how to perform work and family responsibilities as a
result of the increased supportive resources provided by the su-
pervisor. Extending our rationale to the general social support
literature (Cohen & Wills, 1985), we expected employee percep-
tion of FSSB to reduce the negative effects of stress, more gener-
ally by providing a resource to employees through family-specific
supervisor support (e.g., Demerouti, Bakker, Nachreiner, &
Schaufeli, 2001; Hobfoll, 1989). Thus, we predicted that employ-
ees’ perceptions of FSSB may act as a mediating mechanism to the
effects of the intervention on work and health outcomes and that
these effects are moderated by work–family conflict (i.e., work-
to-family conflict and family-to-work conflict). Overall, we pre-
dicted that training supervisors on how to increase family-
supportive behaviors would create increased perceptions of FSSB
for those employees who are high on work–family conflict com-
pared with those who are low on work–family conflict, which
would in turn positively impact the employee outcomes of job
satisfaction, turnover intentions, and physical health. Thus, we
hypothesized the following:
Hypothesis 2: The interactive effect of supervisor training and
employee work–family conflict (i.e., work-to-family conflict
and family-to-work conflict) on FSSB will mediate the mod-
erating effects of work–family conflict on training outcomes.
The study was conducted in 12 grocery stores in a midwestern
U.S. grocery chain. Six stores were randomly chosen as the inter-
vention sites, with six other stores serving as control sites. Each of
the 12 stores had at least one store manager and anywhere from
one to nine supervisors or department heads. The number of
employees per store ranged from 30 to 90. Our intervention study
used a pretest–posttest control group design.
Supervisors included store directors, assistant directors, cus-
tomer service managers, assistant customer service managers, and,
the predominant group, department managers in bakery, dairy–
frozen, delicatessen, meat, produce, and general merchandise.
Thirty-nine supervisors received the training in the six intervention
stores. The training intervention was implemented as part of
company-mandated supervisor training, but the self-monitoring
was optional for supervisors.
One hundred seventeen employees who participated in the study
were in the intervention stores, and 122 employees were in the
control stores. A majority of the employees worked as cashiers.
Many of the employees worked part time, which is common in the
grocery industry; 48% reported part-time and 52% reported full-
time work schedules. All participation occurred during paid com-
pany time, and each employee and supervisor received a $25 gift
card for each survey (pre- or postintervention) in which they
Sample characteristics are listed in Table 1. However, our study
and analyses are focused only on those employees who partici-
pated at both preintervention and postintervention (viz., 239).
Three hundred sixty (61% response rate) employees participated in
the preintervention data collection, and 239 (67% response rate)
employees participated in the evaluation data collection postinter-
vention. Of the total 360 employees who participated in the pre-
intervention survey, 27% were men and 73% were women, 92%
reported that they were White, and the entire group had a mean age
of 38 years. Fifty-five percent reported living as married or mar-
ried, 41% had children living at home, 16% were providing care
for another adult, and 9% were providing care for both a child and
an adult. There were no significant differences on key demo-
graphic variables between the control and experimental groups at
preintervention except for age. The experimental group was 2
years older than the control group.
Of the 239 who participated in the posttraining survey, 22%
were men and 77% were women. Approximately 92% were White
with a mean age of 40 years, 57% reported living as married or
married, 48% had children living at home, 14% were providing
care for another adult, and 9% were providing care for a child and
an adult.
Development of a Supervisor Work–Family
The intervention consisted of three components: computer-
based training, face-to-face training, and behavioral self-
monitoring, all focused on improving FSSB. The training was
designed to enhance supervisors’ skills and motivation to increase
their interpersonal contact with employees and support of employ-
ees’ needs in managing the work–family interface. As part of the
intervention, supervisors were also asked to participate in a be-
havioral self-monitoring activity for 2 weeks following the training
to increase the transfer of the training to on-the-job behaviors.
Computer-based supervisor training. The computer-based
training was implemented in cTRAIN software (Northwest Edu-
cation Training and Assessment, Lake Oswego, OR; http://, developed for a broad range of noneducated
trainees and educated learners (e.g., Anger et al., 2001, 2006;
Eckerman et al., 2004). The software employs (a) established
behavioral training principles of self-pacing and interactivity (fre-
quent quizzes, immediate feedback, high accuracy criterion); (b)
clear system training instructions, so students do not require coach-
ing on how to use the program; (c) icon-based navigation cues
always on-screen, so there are no commands to remember; and (d)
ready implementation of pictures and/or a movie on all screens.
The computer-based training content was developed based on a
review of the work–family literature, as well as site visits, inter-
views, and focus groups in several grocery chains, in order to
enhance generalizability of content. The supervisor training pro-
vided (a) background information on the benefits of reducing
work–family conflict for employees’ and their families’ health and
well-being; (b) the organization’s motivation for reducing work–
family conflict, including concerns about retention, absenteeism,
and health costs; (c) information on the company’s current work–
family policies and programs; (d) definitions and examples of the
four FSSB dimensions (viz., emotional support, instrumental sup-
port, role-modeling behaviors, and creative work–family manage-
ment strategies) described above; (e) data on the existence of a
consistent perceptual gap between employees and supervisors re-
garding work–family support (i.e., employees evaluated their
FSSB lower, whereas supervisors rated their own FSSB higher)
based on pretest and needs analysis survey data; and (f) a descrip-
tion of the self-monitoring program in which they would be invited
to participate during the subsequent face-to-face training. Super-
visors were given a computer-based pretest and posttest containing
an identical set of 15 questions in order to assess learning and
retention of the material. In addition, these 15 questions were
embedded throughout the training in the form of quizzes requiring
a correct answer to progress. An example of a multiple-choice item
on the knowledge test that revealed a large amount of learning
between the pre- and posttest is
Which of the following is true about work schedules and work hours
among U.S. employees? 1. 30% of working women work evenings
and weekends [correct answer]; 2. Most employees work nontradi-
tional shifts; 3. Working nontraditional shifts is related to better
health; 4. Most working fathers work part time.
Face-to-face training. The 1-hr face-to-face training was
conducted by one or more of the first three authors following an
outline that addressed the following points: (a) expression of
appreciation to the company for supporting the surveys and inter-
vention; (b) voluntary nature of the request to change behavior
over the next month and the self-monitoring procedures, with
distribution of consent forms; (c) description of self-monitoring
procedures and opening an opportunity for questions about the
procedures; (d) request for written reaction feedback on the face-
to-face training; (e) clarification that the goal of the training is to
change practices and behaviors of supervisors that include empha-
sizing emotional support, modeling healthy work–family behav-
iors, schedule conflict resolution, knowledge of company policies,
and cross-training on work skills (i.e., FSSB); (f) role play by
presenters of an employee overheard on the phone dealing with a
need to come home to help a child and a supervisor stepping in to
help resolve the conflict; (g) role play by presenters of filling out
Table 1
Participant Demographics at Each Stage of the Study
Participant Preintervention Training Postintervention
Supervisors (N)39
Gender (male/female) 14/17
Age (years, M) 42.5
Married or living as
married NA
White (%) 100
Employees (N) 360 239
Gender (male/female) 97/262 54/186
Age (years, M)38 40
Married or living as
married (%) 55 57
White (%) 92 92
Children at home (%) 41 48
Adults in need of care
at home (%) 16 14
Children and adults at
home (%) 9 9
Note. NA Not available.
self-monitoring cards and request for volunteers to fill in their
estimate of how often they currently perform these behaviors and
their goal for the following weeks; and (h) distribution of certifi-
cates for completing the training and a small gift with the univer-
sities’ logos (pen, calculator). Prior to receiving their certificate,
participants completed training reaction questionnaires on the
computer-based training (five items) and face-to-face training
(four items) that addressed the frequency of other supervisor
training, ratings of the training they received, and the usefulness of
the training. An example item was “How do you rate the infor-
mation you learned in the computer-based training that you took
yesterday or the day before?” (1 poor,2not very good,3
Behavioral self-monitoring. Participants were requested, in
both the computer-based and face-to-face training, to change their
behavior over the following 3–5 weeks by collecting self-
monitoring data on themselves for six behaviors and to set a goal
of increasing the frequency of those six behaviors. The behaviors
were (a) speak with store employees; (b) ask something about an
employee’s family; (c) say something about their (the supervi-
sor’s) family; (d) give positive feedback about an employee’s work
performance; (e) suggest a constructive improvement in an em-
ployee’s performance; and (f) initiate a question about, or offer a
way to improve, an employee’s schedule.
The computer-based and face-to-face training requested that the
supervisors carry a 3 5-in. supervisor daily data card and mark
each time they carried out one of the six behaviors noted above,
each of which was preprinted on the card. One card was provided
for each day. To obtain a baseline and a goal, we asked the
supervisors, in the face-to-face training, to provide an estimate of
how frequently they currently performed each behavior each day
and to set a goal of how much they would increase it (supervisors
at two small stores did not provide baseline estimates and goals).
They were also asked to perform those behaviors at their usual rate
for the first few days of training and then increase them to their
goal over the next 2–3 weeks.
Preintervention and postintervention surveys were administered
to employees individually in face-to-face interviews. Each inter-
view consisted of 196 survey questions and lasted 35–50 min. This
process led to virtually no missing data. Surveys were typically
administered in managers’ offices or in break rooms of the stores
for quiet and privacy.
The intervention took place approximately 9 months after the
preintervention survey was administered. The postintervention
data were collected approximately 1 month following the end of
the intervention. The computer-based training was set up for
managers in a private area of the grocery store such as a break
room or in the managers’ office area. The self-paced computer-
based training lasted approximately 1 hr. Usually, 1–2 days after
the computer-based training was delivered to all managers, a 60- to
90-min face-to-face training session was provided at the grocery
store during a slow time of the workday. At the end of the
face-to-face session, the optional behavioral self-monitoring de-
scribed in the computer-based training was reintroduced. Given
that this portion of the training intervention required managers to
provide informed consent, not all managers chose to participate.
Preintervention and Postintervention Survey Measures
FSSB. The 14-item scale of the FSSB developed by Hammer
et al. (2009) includes four dimensions: emotional support (four
items; ␣⫽.90), role-modeling behaviors (three items; ␣⫽.86),
instrumental support (three items; ␣⫽.73), and creative work–
family management (four items; ␣⫽.86). A sample emotional
support item is “My supervisor is willing to listen to my problems
in juggling work and nonwork life.” A sample role-modeling item
is “My supervisor is a good role model for work and nonwork
balance.” A sample instrumental support item is “I can depend on
my supervisor to help me with scheduling conflicts if I need it.” A
sample creative work–family management item is “My supervisor
thinks about how the work in my department can be organized to
jointly benefit employees and the company.” The reliability esti-
mate for the total FSSB scores was .94; the total score was used in
the analyses, with higher scores representing higher levels of the
Work–family conflict. The construct of work–family con-
flict was measured in two directions with a total of 10 items
(Netemeyer, Boles, & McMurrian, 1996). A sample item is “The
demands of my work interfere with my home and family life.”
Coefficient alpha reliability for work-to-family conflict was esti-
mated at .87, and at .85 for family-to-work conflict. Higher scores
represented higher levels of the constructs.
Job satisfaction and turnover intentions. Job satisfaction
was measured with a five-item scale (Hackman & Oldham, 1975).
A sample item is “Generally speaking, I am very satisfied with this
job.” Reliability for this scale was estimated to be .80. Higher
scores represented higher levels of job satisfaction. Employee
intentions to quit their job was measured with a two-item scale
(Boroff & Lewin, 1997). A sample item is “I am seriously con-
sidering quitting this company for an alternate employer.” Reli-
ability for this scale was 87. Higher scores represented higher
levels of intentions to quit. All of the above scales were based on
a Likert-type response scale ranging from 1 strongly disagree to
5strongly agree.
Physical health. Physical health was measured with the
Short-Form Health Survey (Version 2) seven-item physical com-
posite score (Ware, Kosinski, & Keller, 1996). The Short-Form
Health Survey is an internationally used self-report assessment of
subjective health, with physical health and mental health compos-
ite scores with means of 50 (SD 10); Kudielka et al., 2005). A
sample item is “During the past 4 weeks, how much of the time
have you had any of the following problems with your work or
other regular activities as a result of your physical health?” Scores
were reverse-coded such that higher levels of the construct indi-
cated more positive health. The reliability for the physical health
composite score of the survey in our study was .82.
Summary of Training Outcome Measures: Reaction,
Learning, Behavior, and Results
Using Kirkpatrick’s (1959) classification of training criteria, we
moved beyond training reactions, the most frequently used crite-
rion measure to evaluate training (e.g., Alliger, Tannenbaum,
Bennett, Traver, & Shotland, 1997; Arthur, Bennett, Edens, &
Bell, 2003; Sitzmann, Brown, Casper, Ely, & Zimmerman, 2008),
and extended our evaluation to include learning, behavior, and
results criteria. Furthermore, these methods were based on data
from supervisors and their employees. More specifically, we used
(a) supervisor reaction questionnaires immediately following the
computer-based and face-to-face training (i.e., reaction criteria);
(b) supervisor multiple-choice knowledge tests (pretest and post-
test) embedded in the computer-based training (i.e., learning cri-
teria); (c) supervisor self-reports of family-supportive behaviors
based on completion of the supervisor daily data cards in the
weeks following the training (behavior criteria); and (d) employee
surveys about work and family, safety, and health outcomes before
and after the intervention (results criteria).
Training Outcomes for Supervisors: Reaction,
Learning, and Behavior Criteria
Thirty-nine supervisors from the intervention stores received the
work–family intervention training (computer-based and face-to-
face); 32 of these supervisors participated in the self-monitoring.
The self-monitoring was voluntary as opposed to the company-
mandated training.
Reactions of supervisors (N39) indicated that they found the
computer-based training to be useful. Supervisors rated the infor-
mation they received in the computer-based training as “good”
(M4.10, SD 0.50), and they indicated that both the computer-
based training and the face-to-face training formats had a moderate
to high degree of perceived usefulness (M3.65, SD 0.67, and
M3.32, SD 0.58, respectively).
Learning was assessed with the pretest and posttest scores from
the computer-based training. The supervisors scored a mean per-
cent correct of 74.1 (SD 11.4) on the pretest, and they improved
to 91.8 (SD 10.4) on the posttest. This difference is significant,
t(39) 7.77, p.001, d_gain 1.23, an effect size considered
large per Cohen (1988). Thus, the computer-based training taught
the material effectively based on the results of the multiple-choice
Behavior criteria were assessed with self-monitoring data. Of
the 39 managers who completed the computer-based training, 32
(82%) volunteered to self-monitor, and all but four completed
supervisor daily data cards on a mean of 7.5 days (SD 3.7) over
a 25-day period; the range of the number of days on which
managers completed cards was 1–15.
Of the supervisors who completed cards during the intervention,
24 listed estimates of the frequency of the six behaviors we asked
them to increase, and 23 set goals for how much they would
increase the frequency of those behaviors. The mean goal ranged
from an increase of 63% for the number of times they would speak
to employees to 107% for the number of times they would initiate
a conversation about scheduling with an employee (typically in-
creasing from one time per day to a goal of two times per day).
Self-report data on the individual behaviors that we requested
supervisors to increase also suggest that they did in fact increase.
Given the total potential opportunities for supervisors to exceed
their estimated baseline number of behaviors (24 supervisors 6
behaviors) and meet or exceed their goals (23 6), 62.5% ex-
ceeded their estimated baseline number of behaviors at least once,
and 48.6% met or exceeded their goals at least once during the
intervention. Although we emphasized in the training that the
purpose of the cards was to allow supervisors to be more objective
and thus accurate about their actual behavior (and that the data
would not be shown to management), we were not able to conduct
independent observations of supervisor behaviors to verify these
Impact of Supervisor Training on Employee
Outcomes: Results Criteria
Of the 360 employee participants at baseline, 239 were also
available at follow-up. Two techniques were used to assess and
minimize the potential biases that this level of attrition may pro-
duce. First, we assessed the bivariate relationships between the
variables under study and a variable indicating whether the em-
ployee was available at follow-up. We found no significant dif-
ference in the percentage of dropouts in stores with (35%) and
without (36%) the supervisor training,
(1, N368) 0.06, p
.82. However, we did find that dropouts had significantly lower
mean job satisfaction (M3.31, SD 0.71) than completers
(M3.47, SD 0.65), t(358) 1.99, p.05, and dropouts had
significantly higher mean turnover intentions (M2.64, SD
1.22) than completers (M2.34, SD 1.02), t(358) 2.49, p
.01. In fact, we found that 71 of the 121 people who dropped out
of the study between baseline and follow-up no longer worked at
the company. No other significant differences were found for the
variables under study. Given the differences found in two impor-
tant study variables, we used a modeling technique that can ac-
count for such differences to minimize bias. Thus, second, we used
the full information maximum likelihood routine in Mplus 4.2
(Muthe´n & Muthe´n, 2005) to conduct all the regression analyses
that follow. This routine provides unbiased estimation of model
parameters when the data are missing at random (i.e., variable
missingness does not depend on the variable’s value but can
depend on other observed variable values). Given that, in the
regression analyses that follow, the outcome variables at follow-up
are predicted by the same variables at baseline, along with several
other control variables that are almost completely observed, we
found missing at random to be a reasonable assumption.
The means, standard deviations, and correlations among study
variables are in Table 2. Multiple regression analyses were used to
evaluate the study hypotheses. In these regression analyses, we
focused primarily on the effect of training, the interactive effect of
training and work-to-family conflict, and the interactive effect of
training and family-to-work conflict on postintervention work and
health outcomes while controlling for preintervention levels of
those outcomes. Ideally, we would have employed multilevel
modeling given the nesting of stores within training conditions and
employees within stores; however, the number of stores (i.e., six
stores per treatment condition) precluded precise estimation of
random effects across stores. Therefore, as is typical in such cases,
store differences and the training indicator were modeled as fixed
effects at the same level as the employees, yielding a one-level
model. This modeling decision necessarily limits the generaliz-
ability of these results. However, we feel that generalizability in
research is best served through replication rather than through
assumptions about the random sampling of stores.
In these analyses, we controlled for the store-level variables
through a series of 10 orthogonal contrasts (i.e., five contrasts
within each treatment condition). These contrasts are not of sub-
stantive interest, and therefore they are not labeled; they are meant
only to account for store differences that are independent of the
training effect. In these analyses, we also controlled for several
employee variables. Specifically, we controlled for the outcome
variable assessed at baseline, whether the employee was living as
married with a partner, whether the employee had elderly parents
living at home, how many children the employee had living at
home, and the typical number of hours worked in a week. To
facilitate interpretation, all predictor variables were mean centered.
Table 3 presents the results of these regression analyses to test
Hypothesis 1 where the key predictors and parameters are itali-
As presented in the treatment row of Table 3, supervisor training
led to a significant increase in physical health but no significant
change in job satisfaction or turnover intentions when evaluated at
the mean for family-to-work and work-to-family conflict and con-
trolling for the other store- and employee-level predictors. How-
ever, as presented in the Treatment Family-to-Work Conflict at
Baseline row in Table 3, all these training effects were qualified by
significant interactions between training and family-to-work con-
flict at preintervention on these outcomes. Furthermore, the train-
ing effect on physical health at follow-up was also qualified by a
Treatment Work-to-Family Conflict interaction. No other sig-
nificant interactions of treatment with work-to-family conflict on
the outcomes were observed.
Figures 2 and 3 present graphs of these interactions where the
effect of training is evaluated at one standard deviation above and
below the preintervention family-to-work (or work-to-family) con-
flict mean. Figure 2A displays the interactive effect of training and
family-to-work conflict on physical health at follow-up. Figure 3
displays the interactive effects of training and family-to-work
conflict at baseline on job satisfaction and turnover intentions at
follow-up. Inspection of these figures demonstrates that the inter-
active effect of training and family-to-work conflict on these
outcomes is disordinal in nature (i.e., the direction of the treatment
effect changes for those low vs. high in family-to-work conflict).
At high levels of family-to-work conflict at baseline, employees in
stores with training exhibited higher levels of job satisfaction and
physical health and lower levels of turnover intentions than similar
employees in stores without training. However, at low levels of
family-to-work conflict at baseline, employees in stores with train-
ing exhibited lower levels of job satisfaction and physical health
and higher levels of turnover intentions than similar employees in
stores without training.
Figure 2B displays the interactive effect of training and work-to-
family conflict on physical health at follow-up. Here an ordinal
interaction was observed. That is, the direction of the effect of treat-
ment on the outcome was consistent for the values of work-to-family
conflict. At lower levels of work-to-family conflict, employees in
stores with training exhibited higher levels of physical wealth than
similar employees in stores without training. At higher levels of
work-to-family conflict, the magnitude of this difference due to train-
ing was smaller. This finding is contrary to our hypothesis and is
discussed later. In all, these findings demonstrate that family-
supportive supervisor training was especially successful at improving
work and health outcomes for those workers with higher levels of
family-to-work conflict but was not successful and even had negative
effects for those with lower levels of family-to-work conflict. Fur-
thermore, the hypothesized effects were not observed for those with
higher levels of work-to-family conflict.
Evaluation of Process: Mediated Moderation Analyses
Next we turn to an evaluation of the theoretical process under-
lying these interaction effects. Recall that the supervisor training
was designed to improve FSSB and that the positive effects of this
training on employee work and health outcomes should theoreti-
cally be attributable to increases in employee perceptions of FSSB.
This would be particularly true for employees with higher levels of
work–family conflict, as suggested in Hypothesis 2. Therefore, we
Table 2
Means, Standard Deviations, and Zero-Order Correlations of Employee Study Variables
Variable MSD 123456789101112131415
1. Treatment
0.48 0.50
2. Baseline FWC 1.92 0.56 .03 —
3. Baseline WFC 2.61 0.88 .00 .40
4. Baseline FSSB 3.44 0.71 .01 .01 .26
5. Follow-up FSSB 3.61 0.76 .08 .08 .08 .56
6. Baseline PH 51.62 8.23 .02 .06 .09 .07 .01 —
7. Follow-up PH 51.03 8.44 .15
.06 .04 .00 .52
8. Baseline JSAT 3.41 0.68 .01 .09 .38
.04 .06 —
9. Follow-up JSAT 3.34 0.74 .06 .08 .20
.02 .00 .60
10. Baseline TOI 2.44 1.12 .05 .12
.29 .23
.08 .09 .62
11. Follow-up TOI 2.52 1.05 .01 .11 .17
.12 .04 .47
12. Living as married
0.54 0.50 .04 .07 .02 .04 .07 .03 .10 .01 .12 .11 .12
13. Number of
children at home 1.74 1.86 .14
.03 .08 .13 .15
.10 .06 .14
14. Hours worked 31.36 8.55 .03 .01 .09 .08 .08 .11
.09 .01 .06 .07 .12 .11
.03 —
15. Caring for parents
0.16 0.37 .03 .14
.01 .07 .04 .08 .03 .05 .04 .02 .08 .04 .05 —
Note. N 236 –368. FWC family-to-work conflict; WFC work-to-family conflict; FSSB family-supportive supervisor behaviors; PH physical
health; JSAT job satisfaction; TOI turnover intentions.
Treatment: 1 intervention, 0 control.
Living as married and caring for parents: 1 yes, 0 no.
conducted mediated moderation analyses (Muller, Judd, & Yzer-
byt, 2005).
In classic mediation analysis (Kenny & Judd, 1984), the medi-
ated effect is a direct or main effect; in mediated moderation
analysis, the mediated effect is an interaction. Despite this impor-
tant difference, the modeling process is similar in that it requires
four criteria to be met across three separate regression analyses.
The first regression analysis must establish the effect of interest
(here the interactive effect of training and family-to-work conflict
or work-to-family conflict) on the outcome of interest (here phys-
ical health, job satisfaction, or turnover intentions). The second
regression analysis must establish the effect of interest on the
mediating variable (here FSSB). The third regression must estab-
lish the effect of the mediating variable on the outcome of interest
(controlling for the effect of interest) and must make the effect of
interest on the outcome variable disappear (controlling for the
mediating variable). All four criteria are required to justify a claim
of complete mediation; a claim of partial mediation is justified if
all but the final criterion are met but the magnitude of the effect of
interest on the outcome of interest is weakened.
Tables 4, 5, and 6 display the results of the mediated moderation
analyses conducted for the outcomes of physical health, job satis-
faction, and turnover intentions, respectively. These results support
the claims that FSSB partially mediates the interactive effects of
training and family-to-work conflict on job satisfaction and turn-
over intentions. However, no claim can be made that FSSB me-
diates the interactive effect of training and family-to-work conflict
on physical health, nor the interactive effect of work-to-family
conflict on physical health, job satisfaction, or turnover intentions;
these interactive effects must be due to other processes. In light of
these results, Hypothesis 2 was only partially supported.
Summary of Findings
The goal of this study was to develop, implement, and
evaluate a family-supportive supervisor training intervention,
integrating research from training and workplace interventions
(e.g., M. J. Burke et al., 2006; Lamontagne et al., 2007) and
social support theory (e.g., Cohen & Wills, 1985). Using pre-
and postintervention data, we conducted one of the few existing
quasi-experimental work–family intervention studies reported
to date. The results of this study demonstrate that although the
family-supportive supervisor training intervention was success-
ful at improving work and health outcomes for those workers
with higher levels of family-to-work conflict, ironically, at the
same time, the training resulted in detrimental outcomes for
employees who exhibited lower levels of family-to-work con-
flict. Furthermore, the expected moderating effects of work-to-
family conflict were not found for the outcomes of job satis-
faction and turnover intentions and were actually in the
direction opposite to what was expected for the outcome of
physical health. This demonstrates that those employees with
Table 3
Regression Analysis Results for the Effects of Training and Other Predictors on Family Supportive-Supervisor Behaviors, Physical
Health, Job Satisfaction, and Turnover Intentions at Follow-Up Using Full Information Maximum Likelihood Estimation
Physical health Job satisfaction Turnover
Slope SE Slope SE Slope SE
Treatment (T) 2.17
0.88 0.06 0.07 0.03 0.11
Family-to-work conflict at baseline (BFWC) 1.55
0.93 0.13 0.07 0.16 0.11
TBFWC 4.78
1.88 0.47
0.15 0.70
Work-to-family conflict at baseline (BWFC) 0.16 0.61 0.06 0.05 0.06 0.08
TBWFC 2.00
0.97 0.06 0.10 0.02 0.15
Physical health at baseline 0.51
Job satisfaction at baseline 0.62
Turnover at baseline 0.57
Living as married 2.00
0.97 0.10 0.08 0.08 0.11
Children at home 0.43 0.46 0.05 0.04 0.02 0.06
Caring for parents 0.56 1.25 0.15 0.10 0.12 0.15
Hours worked 0.01 .06 0.01 0.01 0.01 0.01
Store Contrast 1 0.20 1.27 0.07 0.10 0.14 0.15
Store Contrast 2 2.26 1.80 0.03 0.14 0.15 0.21
Store Contrast 3 2.53 2.44 0.34 0.20 0.95
Store Contrast 4 0.98 2.04 0.09 0.17 0.02 0.25
Store Contrast 5 1.34 2.25 0.31 0.18 0.63
Store Contrast 6 1.49 1.24 0.10 0.10 0.12 0.15
Store Contrast 7 4.57
1.84 0.05 0.15 0.10 0.22
Store Contrast 8 2.61 2.20 0.50
0.18 0.49 0.28
Store Contrast 9 0.35 1.82 0.11 0.15 0.09 0.22
Store Contrast 10 4.86 2.51 0.06 0.20 0.50 0.30
Model R
.38 .48 .45
Test of R
(20) 111.55
(20) 146.60
(20) 125.62
Note. N 360. Key parameters are highlighted in italics. All variables are mean centered. Store contrast variables account for between-store differences
that are independent of the training effect and not of substantive interest.
the highest levels of work-to-family conflict reported the high-
est, as opposed to the lowest, levels of physical health.
Furthermore, the results of this study help to clarify the pro-
cesses by which a supervisor training intervention affected em-
ployee outcomes. Namely, employee perceptions of FSSB medi-
ated the interactive effects of the intervention and work–family
conflict (both work-to-family conflict and family-to-work conflict)
on job satisfaction and turnover intentions. However, FSSB did not
mediate the interactive effect of training and work–family conflict
(both family-to-work conflict and work-to-family conflict) on
physical health.
On the basis of analysis of the data from the supervisors who
received the training, we conclude that the supervisors generally
reported that the training and self-monitoring intervention was
useful. In addition, the tests embedded in the computer-based
training indicated that the supervisors learned the material. Evi-
dence of the supervisor training transferring to on-the-job behav-
iors was also demonstrated. Thus, in sum, our data show that the
supervisors responded favorably to the training and that the train-
ing led to behavior changes on the job that, in turn, impacted
employee work and health outcomes. Below is a more detailed
discussion of the study findings.
Employee Outcomes Associated With Supervisor
Two surprising findings emerged from the data that necessitate
further discussion. First, we discuss the results associated with the
moderating effect of work–family conflict. Second, we discuss the
unique unexpected findings associated with the physical health
Moderating effect of work–family conflict. Although there
was support that the training had a positive impact on outcomes for
some employees, our findings were surprising in that the interven-
tion had detrimental effects on those individuals who were initially
lower in family-to-work conflict. There are two related possible
explanations for these findings: “family-friendly backlash” and
workgroup blending. First, it may be that the intervention had a
negative backlash effect for individuals low in family-to-work
conflict who may have resented that company resources or atten-
tion were being allocated to work–family support that they were
not likely to need or use. Those individuals with low levels of
family-to-work conflict could have viewed the intervention as
offering support that specifically favored those with families.
Work–family backlash may occur due to an in- and out-group bias
effect, as Grover (1991) found in a study of hypothetical work–
family benefits. Employees who have lower need for work–family
support may have negative reactions because they do not benefit
directly from the support and thus do not perceive it is fair
(Thompson, Beauvais, & Allen, 2006). Furthermore, research by
Parker and Allen (2001) found that fairness perceptions of family-
friendly benefits were more positive among those who appeared to
“gain the most” from the benefit but that identifying this group was
somewhat complicated (p. 456). In other words, they suggested
that we cannot simply examine the relationship between individual
variables, such as parental status, and fairness perceptions because
other factors, such as age of children, will most likely influence
this relationship. Our findings suggest that those who may gain the
Tra ined Not Tra ined
Physical Health
Low FW C
Mean FWC
High F WC
Tra ined Not Tra ined
Physical Health
Low W FC
Mean WFC
High W FC
Figure 2. Interactive effects of training and family-to-work conflict
(FWC; A) and training and work-to-family conflict (WFC; B) on physical
health at follow-up from regression analysis reported in Table 3.
Trained Not Trained
Job Sa sfacon
Low FW C
Mean FWC
High F WC
2.50 2.53
Trained Not Trained
Turn over Int en ons
Low FW C
Mean FWC
High FWC
Figure 3. Interactive effects of training and family-to-work conflict
(FWC) on job satisfaction (A) and turnover intentions (B) at follow-up
from regression analyses reported in Table 3.
most from our intervention are those with higher levels of family–
work conflict than those with lower levels of family-to-work
conflict. Thus, we conducted post hoc analyses that are consistent
with this suggestion of a backlash effect. Those analyses demon-
strated that employees with lower family-to-work conflict in the
training intervention stores actually rated their supervisors lower in
FSSB than similar employees in control stores, after controlling for
the preintervention FSSB scores. Specifically, training leads to
higher FSSB scores only for those employees with high family-
to-work conflict, and the training actually led to decreased FSSB
among those with low and mean levels of family-to-work conflict.
Additional post hoc analyses found that there were no significant
differences between those with and without family responsibilities
on FSSB or any of the outcomes. This may suggest that the
subjective perception of having high family-to-work conflict is a
more important moderator to consider than the objective measure
of having dependent care responsibilities (vs. no responsibilities).
A second but related possible explanation is the need to plan for
tactics to address the unintended consequences of intervention
implementation with an eye toward “blended work groups.” By
this we mean that every work group has a mix of employees in
high need and low need of a particular intervening work practice.
Perhaps supervisors increased their FSSB in ways that had some
detrimental effects on employees with low work–family conflict. It
is also possible that supervisors focused their supportive behaviors
on those with high family-to-work conflict. That is, supervisors’
actual behaviors may have been different toward those with high
versus those with low family-to-work conflict.
Physical health findings compared with other outcomes.
Tests of our hypothesis revealed that family-supportive supervisor
training led to a significant increase in reports of physical health,
compared with the control group, but no significant change in job
satisfaction and turnover intentions when evaluated at the mean for
family-to-work and work-to-family conflict. In other words, the
intervention appeared to have a beneficial impact on physical
health reports, whereas the effects on job satisfaction and turnover
intentions were beneficial only at high levels of family-to-work
conflict, compared with low levels of family-to-work conflict.
Thus, when making the case for this work–family intervention, one
must be careful to clarify that this intervention is effective for
some employees and not for others depending on the outcome of
interest, leading to limitations in its utility.
In addition, the training effect on physical health was qualified
by a Treatment Work-to-Family Conflict interaction, such that
the training was more effective for this outcome for those with
lower levels of work-to-family conflict, contrary to our predic-
tions. Whereas employees in the treatment stores reported higher
levels of physical health compared with those in the control sites
(as expected), these effects were more pronounced for those with
the lowest level of work–family conflict but not for those with
higher levels of work-to-family conflict (which was contrary to our
Table 4
Results of Mediated Moderation Analysis for the Effect of Training on Physical Health at Follow-Up Using Full Information
Maximum Likelihood Estimation
Model 1 (physical
health at follow-up)
Model 2 (FSSB at
Model 3 (physical
health at follow-up)
Slope SE Slope SE Slope SE
Treatment (T) 2.17
0.89 0.08 0.07 2.18
Family-to-work conflict at baseline (BFWC) 1.56 0.93 0.15 0.08 1.54 0.94
TBFWC 4.78
1.88 0.39
0.16 4.83
Work-to-family conflict at baseline (BWFC) 0.17 0.65 0.04 0.06 0.18 0.65
TBWFC 2.46
1.22 0.05 0.10 2.47
Physical health at baseline 0.51
0.06 0.00 0.01 0.51
FSSB at baseline 0.05 0.71 0.64
0.06 0.15 0.86
FSSB at follow-up 0.01 0.78
Living as married 2.01
0.97 0.06 0.08 2.02
Children at home 0.43 0.46 0.03 0.04 0.44 0.46
Caring for parents 0.57 1.25 0.16 0.11 0.53 1.26
Hours worked 0.01 0.06 0.01 0.01 0.01 0.06
Store Contrast 1 0.19 1.28 0.12 0.11 0.16 1.28
Store Contrast 2 2.25 1.80 0.46
0.15 2.24 1.84
Store Contrast 3 2.52 2.44 0.40 0.21 2.50 2.46
Store Contrast 4 0.99 2.05 0.26 0.17 1.01 2.06
Store Contrast 5 1.34 2.25 0.40
0.19 1.34 2.27
Store Contrast 6 1.46 1.27 0.09 0.11 1.42 1.27
Store Contrast 7 4.58
1.85 0.04 0.16 4.59
Store Contrast 8 2.64 2.23 0.18 0.19 2.68 2.23
Store Contrast 9 0.36 1.84 0.42
0.16 0.39 1.86
Store Contrast 10 4.82 2.53 0.23 0.21 4.79 2.54
Model R
.38 .46 .38
Test of R
(21) 111.48
(21) 135.95
(22) 111.55
Note. N 360. Key parameters are highlighted in italics. All variables are mean centered. Store contrast variables account for between-store differences
that are independent of the training effect and not of substantive interest. FSSB family-supportive supervisor behaviors.
There are several speculative explanations for our differential
findings on health and higher work–family conflict, which may be
related to the unique nature of our sample. First, our sample
included many low-wage and working poor employees, who typ-
ically are left out of the mainstream work–family research. Com-
pared with their other low-income colleagues, perhaps those with
higher work–family conflict have higher work role identity and are
a high-functioning subgroup of the working poor. Perhaps they are
working two jobs to make ends meet, working longer hours, or
combining work with education or other workforce development
activities or are a different family structure such as less likely to be
a single parent. Unfortunately, we do not have data available to test
these possible alternative explanations.
Second, literature on the interaction between formal or structural
work–family supports compared with informal or relational sup-
ports provides a plausible explanation for some of these results
related to the physical health outcome (Kossek, Lewis, & Hammer,
2010). The FSSB intervention is more focused on informal or
relational change, which may be useful in improving the physical
health of those with lower levels of family-to-work conflict, but
that such relational interventions may not be strong enough to
budge certain outcomes for high family-to-work conflict groups.
Organizations may need to integrate structural and relational sup-
ports for work–family interventions to impact outcomes for those
high in work-to-family conflict. These findings point to the critical
importance of the differential effects of work–family interventions
for those with family-to-work versus work-to-family conflict. In
addition, they suggest the need to examine these moderators sep-
Supervisor Behavior Change Findings
In addition to the effects on employees, our intervention in-
creased supervisor knowledge about family-supportive supervision
(pre- to posttest d_gain 1.23), produced increases in self-set
goals for delivering FSSB (by 63%–107%), and resulted in modest
improvements in self-reported FSSB after training (by 48.6% on at
least one occasion). Furthermore, supervisor reactions to the train-
ing were positive. Future research and practice should incorporate
the intervention design principles we identified. To change FSSB,
(a) interventions must be designed to target and measure the
specific behavioral change construct of interest, (b) include a
component to increase motivation for transfer of training (behav-
ioral self-monitoring in this case), and (c) use multiple stakeholder
evaluations of changed supervisor behaviors that capture self-
report and employee measures.
Methodological Contributions
This study makes several methodological contributions. We
designed, implemented, and evaluated a work–family intervention
Table 5
Results of Mediated Moderation Analysis for the Effect of Training on Job Satisfaction at Follow-Up Using Full Information
Maximum Likelihood Estimation
Model 1
(job satisfaction at
Model 2
(FSSB at follow-up)
Model 3
(job satisfaction at
Slope SE Slope SE Slope SE
Treatment (T) 0.06 0.07 0.08 0.07 0.03 0.07
Family-to-work conflict at baseline (BFWC) 0.12 0.07 0.15 0.08 0.07 0.07
TBFWC 0.47
0.15 0.40
0.16 0.34
Work-to-family conflict at baseline (BWFC) 0.04 0.05 0.06 0.06 0.05 0.05
TBWFC 0.05 0.10 0.06 0.10 0.07 0.09
Job satisfaction at baseline 0.58
0.07 0.07 0.07 0.54
FSSB at baseline 0.08 0.06 0.61
0.07 0.10 0.07
FSSB at follow-up 0.32
Living as married 0.12 0.08 0.07 0.08 0.14
Children at home 0.05 0.04 0.02 0.04 0.05 0.03
Caring for parents 0.15 0.10 0.17 0.10 0.10 0.09
Hours worked 0.01 0.01 0.01 0.01 0.01 0.01
Store Contrast 1 0.06 0.10 0.13 0.11 0.09 0.10
Store Contrast 2 0.01 0.14 0.45
0.15 0.15 0.14
Store Contrast 3 0.35 0.20 0.38 0.21 0.23 0.19
Store Contrast 4 0.07 0.17 0.24 0.17 0.14 0.16
Store Contrast 5 0.30 0.18 0.38
0.19 0.42
Store Contrast 6 0.08 0.10 0.09 0.11 0.04 0.10
Store Contrast 7 0.04 0.15 0.02 0.15 0.04 0.14
Store Contrast 8 0.49
0.18 0.14 0.19 0.44
Store Contrast 9 0.15 0.15 0.40
0.16 0.03 0.14
Store Contrast 10 0.01 0.20 0.26 0.21 0.08 0.19
Model R
.48 .46 .54
Test of R
(21) 148.35
(21) 137.10
(22) 181.68
Note. N 360. Key parameters are highlighted in italics. All variables are mean centered. Store contrast variables account for between-store differences
that are independent of the training effect and not of substantive interest. FSSB family-supportive supervisor behaviors.
that addressed criticisms of prior job stress and work–family
intervention research. Design limitations noted in existing inter-
vention research have prevented the translation of such findings.
These limitations include rarely implementing control groups and
rarely collecting pre- and postintervention evaluation data (Glas-
gow & Emmons, 2007). Although much of the work–family re-
search states the importance of analyzing non-same-source longi-
tudinal data with a control group and a within-subject design, few
researchers actually use such rigorous approaches. Our study not
only reflects improved intervention research but also shows how to
design studies that use better methodology to address work–family
issues. Furthermore, we assessed Kirkpatrick’s (1959) four levels
of training effectiveness (i.e., reaction, learning, behavior, results)
in hopes that this research will be more readily translated into
practice (Glasgow & Emmons, 2007), a feat rarely reported in the
training literature (Arthur et al., 2003). Reviews show reactions are
influenced by factors beyond the training itself. These include
trainee characteristics and organizational support for the training
(Sitzmann et al., 2008). Thus, expanding training criteria to learn-
ing, behavior, and results, as suggested by Kirkpatrick (1959),
provides a more thorough assessment of training effectiveness.
Another methodological contribution of the study is the use of
multisource data. We trained supervisors and evaluated the effects
of the training on their employees. The fact that we demonstrated
beneficial effects beyond the supervisor level of analysis to the
employee level strengthens the contribution of this study. Finally,
we employed an improved analytical technique of mediated mod-
eration analysis, allowing us to model more closely the processes
by which our work–family intervention impacts work and health
Study Limitations
Although the computer-based training and face-to-face training
sessions were required by the company, the self-monitoring aspect
of the intervention was voluntary by design. This is consistent with
a training philosophy that voluntary on-the-job transfer is more
likely to be effective than coercive transfer, as supervisors have to
learn how to incorporate training concepts in their daily routines.
Because of this approach, we did not achieve 100% compliance of
the supervisors in the self-monitoring portion of the intervention.
We believe that this led to weaker results than we would have
achieved had we had 100% supervisor participation in all inter-
vention activities. However, we remain confident in our conclu-
sions, as the effects were robust despite this reduced participation.
More importantly, we were unable to implement the feedback
aspects of self-monitoring (i.e., graphing data so the supervisors
can see their behavior trends clearly) that are believed to be critical
to effective self-monitoring, which suggests why our self-reported
behavior changes were much smaller and thus weaker than those
reported in this literature (Olson & Winchester, 2008).
Table 6
Results of Mediated Moderation Analysis for the Effect of Training on Turnover Intentions at Follow-Up Using Full Information
Maximum Likelihood Estimation
Model 1
(turnover at follow-up)
Model 2
(FSSB at follow-up)
Model 3
(turnover at follow-up)
Slope SE Slope SE Slope SE
Treatment (T) 0.03 0.11 0.08 0.07 0.06 0.10
Family-to-work conflict at baseline (BFWC) 0.14 0.11 0.15 0.08 0.08 0.11
TBFWC 0.70
0.22 0.41
0.16 0.55
Work-to-family conflict at baseline (BWFC) 0.04 0.08 0.05 0.06 0.06 0.08
TBWFC 0.01 0.15 0.06 0.10 0.02 0.14
Turnover at baseline 0.56
0.06 0.04 0.04 0.53
FSSB at baseline 0.09 0.09 0.62
0.06 0.13 0.10
FSSB at follow-up 0.39
Living as married 0.10 0.12 0.07 0.08 0.13 0.11
Children at home 0.02 0.06 0.03 0.04 0.01 0.05
Caring for parents 0.11 0.15 0.16 0.10 0.04 0.14
Hours worked 0.01 0.01 0.01 0.01 0.01 0.01
Store Contrast 1 0.16 0.15 0.12 0.11 0.13 0.15
Store Contrast 2 0.13 0.22 0.43
0.15 0.29 0.21
Store Contrast 3 0.94
0.29 0.40 0.21 0.79
Store Contrast 4 0.04 0.25 0.26 0.17 0.04 0.24
Store Contrast 5 0.62
0.28 0.37 0.19 0.73
Store Contrast 6 0.09 0.15 0.09 0.11 0.05 0.15
Store Contrast 7 0.09 0.22 0.03 0.15 0.10 0.21
Store Contrast 8 0.46 0.28 0.14 0.19 0.41 0.27
Store Contrast 9 0.13 0.22 0.41
0.15 0.03 0.22
Store Contrast 10 0.45 0.31 0.26 0.22 0.34 0.30
Model R
.45 .46 .49
Test of R
(21) 126.67
(21) 136.83
(22) 146.99
Note. N 360. Key parameters are highlighted in italics. All variables are mean centered. Store contrast variables account for between-store differences
that are independent of the training effect and not of substantive interest. FSSB family-supportive supervisor behaviors.
An additional limitation is that we are not aware how long the
training effects will continue, given that the postintervention sur-
vey was conducted 1 month after training. Although the self-
monitoring was designed to help increase transfer of training, we
know that not all supervisors participated in this activity. Given
previous research demonstrating that transfer climate plays a sig-
nificant role in the ability of training to transfer (L. A. Burke &
Baldwin, 1999), future work–family training intervention studies
should assess the extent and length of transfer and take steps to
increase the transfer of training climate and “stickiness” or lasting
effects of the training.
Implications of Results for Research and Theory
We suggest that the moderating effects of work–family conflict
on intervention effectiveness need further research, as some work–
family interventions may be more effective than others for people
varying on work–family conflict, and these effects may be depen-
dent on the outcome of interest. Work–family researchers should
endeavor to include samples of employees with variance in work–
family conflict in future studies of work–family intervention ef-
fectiveness, because our results suggest that such interventions
may be most effective for those most in need.
Future studies should also include intervention efforts that are
designed to change the workplace to increase both cultural (e.g.,
more positive supervisor attitudes) and structural (e.g., more
work–family flexibility in job design) support in order to main-
stream work–family initiatives with more general organizational
change initiatives (Kossek et al., 2010). It may be that our training
intervention increased cultural support by changing attitudes and
increasing knowledge of family-supportive behaviors, and then the
supervisors informally implemented structural change in job de-
sign by being more flexible on schedules.
Because we designed the intervention to have training and then
behavioral self-monitoring in the workplace to support transfer of
training, we were unable to isolate the effects of the different
components. Future research should be conducted to differentiate
the effects of multiple-component interventions. We believe that
self-monitoring behaviors are akin to general goal setting after a
training effort to support transfer. Well-designed interventions
should consider the transfer mechanisms that could be achieved
via a number of ways, from voluntary self-monitoring with feed-
back on behavior change to goal setting to having a mentor or
“training buddy” to support transfer. The key intervention imple-
mentation lesson from this study is to conduct work–family train-
ing or other interventions with consideration of ways to motivate
transfer as part of the intervention design.
We suggest that the findings of this study also have significant
implications not only for intervention and job stress theory but also
for the theoretical development of the FSSB construct, given that
we have shown how to impact this construct through behavioral
training based on the four dimensions of FSSB (i.e., emotional
support, instrumental support, role-modeling behaviors, and cre-
ative work–family management; Hammer et al., 2009). Further,
research should examine whether the FSSB and family-to-work
interaction mediating effects found in this study are replicated for
other family outcomes or other work outcomes such as job per-
formance and extrarole behaviors.
In addition, scholars should continue to examine other psycho-
logical and mediating processes through which work–family in-
tervention effects operate. For example, work–family interventions
aimed at increasing worker control though flexible work schedules
would be expected to operate via the process of increasing per-
ceived control. Although it is a truism to say that supervisors
matter for work–family policy effectiveness, ironically, very little
work–family research actually collects data from supervisors and
then links those data to the health and productivity reports of
employees. More work–family research needs to include actual
data from supervisors and then match those data to the employees’
work–life experiences and health and productivity, as in the cur-
rent study.
Implications for Practice
Overall, this study has identified the conditions under which
work–family interventions are likely to be most effective. We
developed an intervention that focuses on changing organizational
systems (i.e., the supervisor behaviors), as opposed to changing the
individual employee. We elaborated on the meaning of this study
for the design of effective workplace stress interventions, specif-
ically those that are work–family specific.
First, our findings suggest that work–family interventions may
be most effective if they target individuals in organizations that
have higher need (higher family-to-work conflict). To date, orga-
nizations have adopted many work–family policies, but often the
individuals that may be most in need of help may not actually be
targeted for these policies, or the interventions may not have fit
their needs. Such interventions and policies tend to be more
common among higher level professional positions. We studied a
group of lower wage, hourly grocery workers who typically are not
provided opportunities for work–family supports due to the struc-
tural rigidity of their jobs. Perhaps providing our less formal
work–family intervention of training supervisors to employ
family-supportive behaviors is more beneficial for workers in
these types of positions who are not able to take advantage of more
formal policies such as flexible work schedules. For example,
Lambert and Waxman (2005) discussed the issue of work–family
policy organizational stratification, which refers to situations in
which workers in different parts of the organization are not able to
access available work–family policies such as flextime or part-
time work. Thus, it is important to ensure that the interventions are
tailored to address the workforce needs of employees with higher
work–family conflict and that such interventions reach the em-
ployee population that is likely to benefit from the intervention. At
the same time, we do not want to marginalize disadvantaged,
“nonideal” workers who are considered high on work–family
conflict by targeting them for work–family interventions (Kossek
et al., 2010, p. 3). Rather, we encourage the development of
work–family interventions that are integrated into existing core
organizational structures that enable such programs and policies to
operate more as the norm rather than the exception.
Second, our findings also appear to indicate that although the
training was particularly beneficial for those higher in family-to-
work conflict, one can see an opposite effect for those who are low
in family-to-work conflict for the outcomes of job satisfaction and
turnover intentions. We believe that this suggests that there may be
some family-friendly backlash occurring and that those with low
family-to-work conflict may actually perceive the intervention as
negative or as affecting them adversely. Although the nature of
such backlash is not clear, we suggest that there is a need for
organizations to pay attention to strategies for reducing or avoiding
such potential backlash with any work–family intervention.
Third, many workplace interventions are more individually fo-
cused than organizationally focused (Hurrell, 2005). This is a
fundamental problem because targeting individual change will not
ameliorate stressful organizational contexts in which individuals
are embedded. Our intervention improved the psychosocial envi-
ronment (cf. Hurrell, 2005) by changing the level of managerial
support for work and family demands. This is likely to be more
effective than training individual employees to solve their own
problems but who then return to a stressful, unchanged system.
The current intervention was designed with a focus on improving
supervisor skills, which we illustrated as an effective psychosocial
intervention. Although our findings did not provide strong support
for the benefits of the intervention on outcomes across all em-
ployee strata, we argue that there is value in any development and
testing of a work–family intervention that provides some benefit
and that the concepts can be developed and refined in future
research and practice.
Although the work–family literature has long lauded the impor-
tance of increasing supervisor support for family, and implement-
ing training for supervisors to address work–family issues, no
work–family studies in the peer-reviewed literature demonstrate
how to increase this support and ensure transfer of training. We
have added to knowledge of evidence-based management practice
regarding work–family support (cf. Rousseau, 2006). Overall, this
study has the potential to advance the work–family field by ad-
dressing many of the limitations of existing work–family interven-
tion research, as well as helping to improve the quality of work life
in organizations that implement work–family interventions de-
signed to increase FSSB. This study demonstrated the central
importance of supervisors to supporting the work–family interface
and in workplace intervention design and implementation. We
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Received November 19, 2008
Revision received May 14, 2010
Accepted May 24, 2010
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... An extension of the discussion of the employee-employer interface and their social exchange lies in the role of the supervisor. A supportive supervisor who facilitates employees having a positive work-life balance [43] has been shown to be often associated with work-related outcomes [16,44] including their work attitude [45] and job performance [46]. For instance, supervisors who express concern and offer encouragement to employees who are experiencing high WLC tend to care about employees' family obligations and offer flexibility to help them strike a work-life balance. ...
... A sample item was: "My organization makes an active effort to help employees when there is a conflict between work and family life." Supervisory family support: Supervisory family support was assessed with a 4-item scale which was developed in a recent study [45]. Participants were asked to rate their agreement with items on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). ...
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The need for family-friendly policies to balance work and life demands is growing. Many studies have addressed how family-friendly policies relate to a variety of employees’ work attitudes and behavioral outcomes, but not how they (positively or negatively) affect them, especially the affective components of family-friendly policies that provide “felt” support to an employee. To fill this gap, this study adopts a moderated mediating mechanism to analyze how affective components of family-friendly policies impact employees’ attitudes and behaviors through signaling and social exchange theory. We examined how this impact is mediated by factors such as work–life conflict, perceived organizational support, and control over working hours, as well as whether having a supportive supervisor moderates the mediated effect through further limiting the degree of work–life conflict or strengthening control over working hours. Data were collected through a survey with 401 employee–supervisor dyads from organizations in Hong Kong. We found that family-friendly policies do not necessarily affect work attitude and behavior, but they work through the sequential mediators of having more control over working hours and perceived organizational support. The role of supportive supervisors is also significant, in that they are likely to be key in molding the organizational environment for the gradual provision and uptake of family-friendly policies. The results of this study contribute to the development of signaling and social exchange theory and have theoretical implications for supervisors regarding them utilizing their position to improve employee work attitudes and behavioral outcomes.
... Especially in large enterprises, it is difficult to achieve the optimal effect of artificial allocation in the case of more employees and positions. It was found that this problem can be converted into a problem of maximum and optimal matching of dichotomous graphs, and then the Hungarian algorithm can be used to solve the best result, and the solution process can be easily implemented on the computer [12]. In this way, companies can use information management systems to solve the problem of optimal human resource allocation well within a very short period of time [13]. ...
... Establish the corresponding probability selection in the PP sequence. In this paper, we construct the probability of each current locally optimal solution for selecting the points in the PP sequence as (12). ...
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People are the most dynamic factor of productivity, and human resource allocation is both the starting point and the end point of human resource management. In modern enterprises, human resource optimization is the scientific and rational allocation of human resources within the enterprise through certain means and methods. The basic concept of particle swarm optimization (PSO) originates from the study of bird predation. It is an evolutionary computation technique based on the swarm intelligence method, which is similar to genetic algorithms and is a population-based optimization tool. This paper is inspired by the ant colony algorithm and introduces the ant colony pheromone and variation algorithm model into the PSO algorithm for further optimization. The application of this improved particle swarm optimization algorithm to the optimal allocation of human resources recommendations is demonstrated by a real case study.
... STAR trained supervisors on the value of demonstrating support for employees' personal lives and to prompt employees to reconsider when and where they work (Hammer et al., 2009(Hammer et al., , 2011Kelly et al., 2011Kelly et al., , 2014. Work-family conflict (the interrole conflict between the domains of work and family, measured separately using scale measures of the constructs of work-to-family conflict and family-to-work conflict) was a critical primary outcome of interest. ...
... Research designs in the occupational health intervention literature are becoming increasingly sophisticated-including repeated-measures, interventions, and field experiments, which is particularly reflected in work-family interventions like the STAR intervention we assess here (e.g., Hammer et al., 2011). We demonstrate how improved integration of organizational change and measurement equivalence literatures is important to advance the occupational health science of work-family intervention research. ...
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Given the rapid growth of intervention research in the occupational health sciences and related fields (e.g. work-family), we propose that occupational health scientists adopt an "alpha, beta, gamma" change approach when evaluating intervention efficacy. Interventions can affect absolute change in constructs directly (alpha change), changes in the scales used to assess change (beta change) or redefinitions of the construct itself (gamma change). Researchers should consider the extent to which they expect their intervention to affect each type of change and select evaluation approaches accordingly. We illustrate this approach using change data from groups of IT professionals and health care workers participating in the STAR intervention, designed by the Work Family Health Network. STAR was created to effect change in employee work-family conflict via supervisor family-supportive behaviors and schedule control. We hypothesize that it will affect change via all three change approaches-gamma, beta, and alpha. Using assessment techniques from measurement equivalence approaches, we find results consistent with some gamma and beta change in the IT company due to the intervention; our results suggest that not accounting for such change could affect the evaluation of alpha change. We demonstrate that using a tripartite model of change can help researchers more clearly specify intervention change targets and processes. This will enable the assessment of change in a way that has stronger fidelity between the theories used and the outcomes of interest. Our research has implications for how to assess change using a broader change framework, which employs measurement equivalence approaches in order to advance the design and deployment of more effective interventions in occupational settings. Supplementary information: The online version contains supplementary material available at 10.1007/s41542-022-00122-y.
... Major and Lauzun (2010) suggested that employers should empower their supervisors by providing family-specific support to employees. Supervisors should be trained on family support and encourage open conversations around realistic expectations of work-life support (Hammer et al. 2011). Yragui et al. (2017) found that FSSB moderates the relationship between workplace aggression, employee wellbeing, and work outcomes. ...
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A dearth of employees' social courage impedes positive work outcomes. Understanding the antecedents, mechanisms, and conditions that influence workplace social courage could promote better results at the individual, team, and organizational levels. Using the stressor-strain-outcome model, conservation of resource theory, and the social exchange theory, we investigated a conditional mechanism to explain how and when people with eldercare responsibilities are likely to practice lower social courage at work. The mediating mechanism of employees’ fear of negative evaluation by their supervisors explains this relationship under the moderating effect of family supportive supervisory behavior. The empirical analysis is based on data collected from 205 public, private, and corporate sector employees having eldercare demand, in a three-wave field survey across Pakistan. The results showed that eldercare demand is positively linked to fear of negative evaluation, which reduces workplace social courage. Family supportive supervisory behavior buffered the effect of eldercare demand on fear of negative evaluation, weakening its negative effect on workplace social courage. Compared with another sample of 214 employees without eldercare, the employees with eldercare demand reported significantly higher fear of negative evaluation and lower workplace social courage. Findings show that employers need to minimize the fear of negative evaluation among employees to realize positive work outcomes related to workplace social courage. Family supportive supervisory behavior may be an excellent strategy for employees with eldercare obligations to dilute the negative implications of fear of negative evaluation and improve workplace social courage.
... Furthermore, it has been discovered that workplace supervisor help is a crucial situational resource for assisting employees in reaching greater WLB (Ferguson et al., 2012). According to the JD-R (job-demands resources) model, a supportive superior may make it simpler for workers to reorganize work to accommodate family needs and have sufficient resources (Hammer et al., 2011). Reciprocity offers the theoretical foundation for anticipating work-life advantages to be positively returned by workers in the form of favourable behavior"s and actions, despite and in favor of the JD-R models (Lambert, 2000). ...
The COVID-19 epidemic changed people's working dynamics all over the world, and every sector migrated to remote working as a result. Work from Home had grown extremely common and accepted around the world. The purpose of this study is to do a comprehensive assessment of the existing past studies in order to obtain a better and clear understanding of Work from Home (WFH) as well as its influence on personal and professional life after the outbreak of COVID-19 epidemic in terms of gender roles and its impact on their career progression. It also seeks to provide an overview of major studies in the field of WFH, which can assist in identifying the key factors that have had the greatest impact on the WFH condition. WFH has been deemed as "new normal" and several studies have raised concerns regarding employees" productivity and efficiency, while many experts discuss the emotional and physical stress of working women in lockdown time. Most of the working women are involved in dual responsibility to manage the home and work both at the same time. Discriminatory practices are evident in household chores, child care, homemaking, lower wages, glass ceilings, less superior assistance, and all other unpaid work stresses that have significantly hampered women's productivity. While the downsides of WFH comprise interruption in the working place, work-home conflict, social exclusion, employee productivity, dual jobs for women, teleworking, and work-life balance, connectivity, level of support, growth opportunity, the positive aspects include flexible schedules, childcare costs, parenting, cost and time savings on travel, and workplace infrastructural facilities. Research directions domains under the WFH concept are quite broad, and gender disparities can be used to conduct industry-based studies. This paper is a study of influencing factors affecting the efficiency of working men and women and the problems faced by them during Work from Home.
... Through the literature review, we found that FSSB proved effective in other industries to help employees alleviate work-family conflict, improve job satisfaction, increase work engagement, and thus, enhance employee performance [36]. A study on Chinese construction workers indicated that FSSB buffered the negative relationship between work-family conflict and safety participation via work engagement [7]. ...
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Most current studies on the mental health of construction project management professionals (CPMPs) are conducted from a negative psychological perspective, lacking a comprehensive understanding of the positive–negative interwoven mechanism. This study developed a positive–negative dual-process psychological model of CPMPs to explore the interwoven mechanisms among five variables: family-supportive supervisor behavior (FSSB), work–family conflict, work–family enrichment, job burnout, and work engagement. We conducted a large-scale questionnaire survey among Chinese CPMPs. A total of 656 questionnaires were returned; 446 were considered valid. The groups of CPMPs prone to occupational psychological problems were identified, which enhanced the targeted organizational management in the construction industry. The hypothetical model was verified with SEM. The results revealed that the effect of work–family enrichment was more significant than work–family conflict, which implies that the positive psychology process may play a more prominent role than the negative process. There was a significant correlation between FSSB and work–family conflict/ enrichment; but no direct correlation between FSSB and job burnout/work engagement. This implies that the improvement of the work–family relationship plays a full mediating role in improving CPMPs’ occupational psychological health. This research provides a thorough understanding of CPMPs’ interwoven occupational psychological problems and gives suggestions to enhance their occupational psychological health.
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The COVID-19 pandemic brought with it the generalisation of working methods that existed beforehand, such as teleworking. Remote work has shown significant advantages, both for companies and for employees. However, teleworking has shown itself prone to certain psychosocial risks, even being viewed as an “accelerator” of the burnout process. Although research supports that teleworking promotes autonomy and flexibility, there is also evidence that teleworking performed at high-intensity may create conflict in the personal life. Intense workload, reduced and scant social support perceived in remote working were predictors, not solely of emotional weariness, but moreover of other dimensions of burnout: cynicism and lack of personal realisation. The experiences described by those who have worked remotely during the pandemic were: the ease with which schedules or rest days disappear, meeting too many demands through different channels (phone, WhatsApp, email) and with limited time. Also, taking into account that the employees lacked training and that on many occasions they were overwhelmed by techno-stress. Thorough studies are needed on the health consequences of teleworking, which clearly define their aims and take into account the complexity of mediating and modulating variables. Future research should seek to identify what behaviours and resources of teleworking can be beneficial in meeting demands and what aspects contribute to exhaustion.
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Brak zrozumienia zjawisk i procesów zachodzących na współczesnym rynku pracy, ze szczególnym uwzględnieniem okresu pandemii Covid-19, ogranicza możliwości sprostania wyzwaniom oraz przeciwdziałania negatywnym konsekwencjom tych zjawisk. Monografia, będąca efektem badań prowadzonych w Katedrze Analiz i Prognozowania Rynku Pracy UE Katowice, a także własnych przemyśleń i analiz Autorki, stanowi próbę przedstawieniu istoty aktywności zawodowej, a szczególnie pracy zarobkowej jako kluczowego elementu jakości życia, wraz z uwzględnieniem różnic ich postrzegania przez kobiety i mężczyzn. O jej naukowych i aplikacyjnych walorach świadczy także przedstawiona ocena skutków pandemii Covid-19 w obszarze rynku pracy oraz rekomendacji kierowanych do pracowników, pracodawców oraz instytucji i organizacji mających bezpośredni i pośredni wpływ na kształtowanie stosunków pracy w Polsce.
Purpose Despite a burgeoning literature on family-supportive supervisor behaviors (FSSB), it is unclear whether supervisors view these behaviors as in-role or discretionary. We proposed a new cognitive motivational construct, FSSB role perceptions (FSSB-RP; that is the extent to which supervisors perceive FSSB as an expected part of their job) and evaluated it as a mediator of the relationship between supervisors' own work–family experiences and FSSB. Design/methodology/approach We used an online survey of 245 US based supervisors. Findings We find that FSSB role perceptions is a unique but related construct to FSSB, and that approximately half of our sample of 245 supervisors either do not believe that FSSB is a part of their job or are unsure as to whether it is. Path analyses revealed that supervisors' own experiences of work–family conflict and enrichment are related to engaging in FSSB through role perceptions, especially when a reward system is in place that values FSSB. Practical implications These results may influence the design, implementation and dissemination of leader family-supportive training programs. Originality/value The factors that drive supervisors to engage in FSSB are relatively unknown, yet this study suggests the novel construct of FSSB role perceptions and supervisors' own work–family experiences are important factors.
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Family supportive supervisor behaviors (FSSB) have emerged as a powerful resource of informal support for the well‐being and development of employees. However, research to date offers limited insight into the antecedents and underlying processes that may trigger FSSBs. We investigate the association between family motivation of supervisors and FSSBs, and how the latter mediates the association between supervisors’ family motivation and subordinates’ work performance. Furthermore, we examine the role of supervisors’ satisfaction with their work–family balance as a contextual variable influencing our proposed associations. We draw on FSSB and perspective taking theory as over‐arching frameworks for our hypotheses. Using matched and multisource supervisor‐subordinate data collected from an organization in Chile (196 subordinates and 75 supervisors), our findings revealed that FSSBs are mechanisms linking supervisors’ family motivation to subordinates’ work performance. Interestingly, this positive association is moderated by supervisors’ satisfaction with their work–family balance, such that the mediation of FSSBs is stronger for supervisors who are not satisfied with their work–family balance.
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Although many employers have adopted policies to support the integration of work with personal and family life, expected positive gains due to enhanced workplace inclusion are not always realized. One reason for this gap is that practitioners and researchers often overlook how variation in how policies are implemented and used by different employee stakeholder groups fosters a culture of inclusiveness. We discuss four ways in which work-life policies are implemented differently across and within organizations that can affect the degree to which policies are seen as promoting inclusion or exclusion. They are: the level of supervisor support for use, universality of availability, negotiability, and quality of communication. These implementation attributes affect whether an adopted policy is seen as leading to fulfilling work- life needs and signaling the organization's support for individual differences in work identities and life circumstances, thus affecting levels of inclusiveness. Implications for HR practitioners are discussed.
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The authors briefly review the literature on occupational health, including occupational medicine, occupational health psychology, and occupational safety, framing the current convergence of these from their scientific origins in preventive medicine and its most basic science of epidemiology, in psychology, and in engineering. They give attention to the burden of suffering, which concerns issues of morbidity and mortality within a population group, and consider both the economic and humanitarian perspectives of the burden of suffering, which may occur within a working population as a result of poor occupational health. The authors see reason for optimism for the future and identify two sets of emerging trends: one set that includes four positive advances—positive health, leadership, mood and emotions, and interventions—and one that falls under the authors' rubric of new horizons—technology, virtual work, globalization, and aging. The authors conclude with attention to zest at work, along with cardiovascular health and well-being.
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This paper uses both qualitative and quantitative methods to examine the relationship between work-family conflict and six work outcomes: performance, turnover, absenteeism, organizational commitment, job involvement, and burnout. Also reviewed are studies on the effects of employer (work-family) policies aimed at reducing such conflict. Policies to aid employees in managing work and family roles can be expensive, and studies show that they are often marginally effective. The review shows that relationships between work-family policies and organizational effectiveness is mixed and their connection to work-family conflict often under-examined. Work-family conflict is a critical link that may shed light on policy impacts. Suggestions on how future studies can build bridges between practitioners and academics and more clearly examine organizational effectiveness links are provided.
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Workplace applications of behavioral self-monitoring (BSM) methods have been studied periodically for over 35 years, yet the literature has never been systematically reviewed. Recent occupational safety interventions including BSM resulted in relatively large behavior changes. Moreover, BSM methods are functional for addressing a broad range of occupational health psychology topics. Studies (n = 24) where workers self-monitored productivity or safety behaviors were reviewed and scored along dimensions relevant to research and practice. For intervention conditions (n = 38), standardized effect sizes ranged from 0.2 to 14.5 (weighted average d = 2.8). The results encourage the use of BSM in workplace interventions, but the literature has insufficiently addressed the isolated and additive effects of BSM, worker involvement and individual differences, assessment applications, and theory testing and development.
Experimental evaluations of Behavior-Based Safety (BBS) processes applied with lone workers are scarce. Clinical and organizational researchers alike have studied the effectiveness of self-monitoring as a performance improvement strategy, but further work is needed to determine the power of such interventions for improving safe behavior and to explore the best practices for using such processes with lone workers. In the current study, four male bus operators (20.5 years average experience) self-monitored their safe performance and received feedback based on self-monitoring data. Dispatch supervisors used radio communication to prompt participants to complete self-monitoring forms and also conducted special observations of participants to measure target performances. Both operators and supervisors were unaware of experimental observers who measured the performance of each participant by riding on busses as passengers. A multiple baseline design across performances was used to assess the effects of the intervention on four performance targets. The intervention resulted in a 12.3% increase in safe performance for the group, with individual increases in performance ranging from 2% to 41% for specific target performances. The results are discussed in terms of the value of BBS processes for employees who work alone and the research needed to determine the components of self-monitoring processes that are most critical for generating improvements in safe performance.
Survey data indicated that being of childbearing age, having children, and holding positive attitudes toward women were positively related to perceptions of parental-leave policy fairness. These findings supported the proposition from social justice theories that relation (similarity) to the object of resource distribution influences perceptions of fairness. The study also replicated the egocentric bias effect such that planning to bear children and expressing intent to take leave were positively related to perceptions of policy fairness. Policy-fairness perceptions were related to attitudes toward parental leave recipients (leave takers), and the data supported a mediation model in which fairness perceptions mediated the relation between similarity to, and attitudes toward, leave takers. The theoretical implications for theories of social justice and the practical implications for parental leave are discussed.
The purpose of this study was to decrease the risk of carpal tunnel syndrome (CTS) during keyboard entry tasks through a combination of training, self-monitoring, feedback, goal-setting, and reinforcement. Technologies from biomechanics, ergonomics, and behavioral psychology were combined effectively to construct a powerful training package. As the subjects entered text on a keyboard, their postures and hand-wrist positions were recorded. After baseline data were gathered, subjects received training and self-monitored either posture or hand-wrist position. Feedback, goal-setting, and reinforcement were given later on both behaviors in a staggered fashion. The results indicate dramatic increases in the percentages of correctly performed postures and neutral hand-wrist positions, for all subjects. The training components used are reviewed in detail and the impact of these results is discussed.