TITLE: Effects of Computer-based Stress Management Training on Psychological
Well-being and Work Performance in Japanese Employees: A Cluster Randomized Controlled
Trial

  ABSTRACT:
This study evaluated the effectiveness of a computer-based stress management training
(SMT) program in improving employees' psychological well-being and work performance. A
total of 12 work units (N=263) were randomly assigned to
either an intervention group (8 work units, n=142) or to a
wait-list control group (4 work units, n=121). All
participants were requested to answer online questionnaires assessing psychological
well-being as a primary outcome, and coping style, social support, and knowledge about
stress management as secondary outcomes at baseline (T0), immediately after the
intervention (T1), and 2 months after the intervention (T2). The group × time interaction
was tested using a mixed-model repeated measures ANOVA. Results showed a group × time
interaction for "knowledge about stress management" in the entire sample. Among
participants who had more than 3 d of training, a significant group × time interaction was
observed for "problem-solving" and "avoidance and suppression" as well as "knowledge about
stress management." Our computer-based stress management program was effective for
improving knowledge about stress management. It was also effective for improving coping
skills in instances where participants had enough time (at least 3 d) to complete all
sessions.

BODY.INTRODUCTION:
Stress management training (SMT) is provided as a psychoeducational program to enable
individual workers to learn how to become aware of and develop effective skills to cope with
stress1). Several SMT techniques are used
in work settings, such as cognitive-behavioral training, personalized feedback based on
systematic assessment, relaxation training, physical fitness training, and various
combinations of these approaches2,3,4). A
recent meta-analysis of SMT has shown that cognitive-behavioral techniques are more
effective than other techniques for enhancing psychological resources and reducing the
psychological distress of employees3, 5).  Cognitive-behavioral techniques, such as cognitive restructuring skills, social skills, and
problem-solving skills, are explicitly aimed at enhancing individual coping skills6). Coping refers to cognitive and behavioral
efforts to manage specific demands that are appraised as taxing or exceeding the resources
of the person7). Previous studies suggest
that SMT programs with cognitive-behavioral techniques were effective for improving coping
skills8,9,10).  In addition to coping skills, interpersonal relationships (i.e., social support, or lack
thereof, and interpersonal problems) have been found to be critical in determining
employees' psychological distress. For instance, social support helps an employee exert
situational control through the provision of instrumental aid or advice about how to modify
a situation to make it less stressful7).
Furthermore, the workplace community is one of the factors that contributes to reducing
employee burnout rates11). Lack of social
support may lead to increased psychological distress. In Japan, 45.8% of employees indicated
that interpersonal problems are their primary stressor12). This suggests that it is important that SMT programs should focus
not only on improving behavioral and cognitive coping skills, but also interpersonal
relationships (e.g., increasing social support).  Notably, in the current research, we examined the effects of our intervention on both the
negative (i.e., psychological distress) and positive aspects of psychological well-being
(i.e., work engagement, job satisfaction, and work performance). Psychology has recently
been criticized as primarily dedicated to addressing mental illness rather than mental
"well-being". Since the turn of the century, however, a new trend toward "positive
psychology" has emerged. Positive psychology focuses on human strengths and optimal
functioning rather than on weakness and malfunctioning13). This shift found in mainstream psychology is also relevant for
occupational health psychology. In recent years, results of SMT programs included not only
negative outcomes, such as depression, psychological distress, and anxiety5, 14),
but also positive outcomes such as job satisfaction15, 16), work performance17, 18), vitality19), and
propensity to innovate16).  Although empirical evidence that supports the effectiveness of individual-focused SMT is
accumulating, the workplace still has a number of barriers that impede access to mental
health activities, such as "lack of experts" and "lack of knowledge about how to address
mental health services"12). Computer-based
self-help programs may be an effective and inexpensive alternative to traditional
face-to-face SMT programs. For instance, Shimazu et al.20) investigated the effectiveness of a
computer-based psychoeducational program for workers. They found that participants in the
intervention group experienced improvements in self-efficacy and job satisfaction. Another
study by Eisen et al.21)
investigating the relative effectiveness of a live versus computer guidance group, showed
that the computer guidance group was similar to the live guidance group in terms of the
frequency with which participants practiced their skills21). Furthermore, computer-based self-help programs can be used as
tools to compensate for the lack of experts and knowledge in the workplace on how to address
mental health services among occupational health staff. However, few studies have
investigated the positive aspects of computer-based SMT program outcomes using rigorous
study designs such as a randomized controlled trial.  The purpose of this study is to develop a computer-based SMT program and evaluate its
effectiveness on employees' psychological well-being (i.e., (lower) psychological distress,
work engagement, and job satisfaction), and work performance. We hypothesized that our
computer-based SMT program would improve employees' psychological resources (i.e., coping
skills, social support, and knowledge about stress management as secondary outcomes) and
consequently their psychological well-being (i.e., (lower) psychological distress, work
engagement, and job satisfaction) and work performance.

BODY.METHODS.PARTICIPANTS:
This study was conducted as a mental health promotion program in a manufacturing company.
In total, 12 work units from the research and development divisions and support staff
(N=266) were invited to participate in the study. All participants were
full-time employees. Participants were informed about the program by an informational
poster as well as their supervisor during meetings. Participants were randomly assigned by
work unit22) to either an intervention
or wait-list control group to participate in a computer-based SMT program. No inclusion or
exclusion criteria were adopted because the intervention was planned for all employees in
the research and development divisions. All employees participated, with the exception of
one individual who was responsible for coordinating study-related details between the
company and the author of this paper and another who changed workplaces prior to
completing the baseline survey.

BODY.METHODS.DESIGN:
The study was a cluster randomized controlled trial. In May 2009, a baseline survey (T0)
was conducted, and then participants were randomly assigned by work unit to a
computer-based intervention group (8 work units, n=142) or a wait-list
control group (4 work units, n=121). Additionally, participants were
required to answer online questionnaires at 9 weeks (T1) and 19 weeks (T2) after the
baseline survey. The timing of these questionnaires were selected based on recommendations
in a meta-analysis conducted by van der Klink5). Specifically, van der Klink recommends a minimum of 12 weeks
between baseline surveys and follow-up questionnaires since health outcomes are more
stable than coping skills8). The
intervention group started the 7-week program immediately after the baseline survey, while
the wait-list control group started after the T2 follow-up survey.

BODY.METHODS.INTERVENTION PROGRAM:
A computer-based SMT program was developed using the following 3 steps: 1) literature
review, 2) trial survey, and 3) modification. First, a trial program was developed based
on results from past stress management training research18). Next, a pilot trial, consisting of 19 employees who worked in
laboratory or administration department, was conducted at a research institute in
September 2008. Lastly, after implementing revisions based on participants' feedback
(n=11), the final version of the program was completed.  The computer-based SMT program was self-paced and consisted of the following: 1)
behavioral techniques, 2) communication techniques, and 3) cognitive techniques.
Additionally, each part was divided into 2 topics on the basis of cognitive behavioral
skills: (a) problem-solving and time management skills for the behavioral techniques
section, (b) assertion and delegation skills for the communication techniques section, and
(c) cognitive restructuring and causal attribution skills for the cognitive techniques
section.  Participants learned these skills in a 2-phased approach, which consisted of a skill
acquisition phase and a practice phase. The skill acquisition phase focused on improving
participants' understanding of each skill. Through self-monitoring, participants learned
which skills they lacked. The practice phase focused on encouraging participants to put
the skills they acquired to practice in their everyday life. Participants could enter any
problems or experiences they encountered on their own private web page to help resolve
them. According to social learning theory, self-efficacy beliefs (judgments regarding
one's capabilities) and outcome expectancies (judgments regarding the consequences of
behaviors) significantly influence coping behaviors23). The goal of the skill acquisition phase was to increase
participants' 'outcome expectancies' about intervention related outcomes, and the goal of
the practice phase was to increase 'efficacy expectancy'.

BODY.METHODS.LEARNING PROCEDURE:
One of the office staff served as the coordinator between the participants and author of
the present work. Participants in both groups were given individual IDs and passwords
before starting the program. Participants underwent the program during working hours.
Communication between participants and the author took place entirely through e-mail
without any face-to-face interaction. Considering that the average length of the stress
management intervention program was 7.4 weeks14) and that our program consisted of six lessons, an optimal pace of
one lesson per week was chosen. Hence, participants received an email every week during
the time course of the intervention. To increase participants' motivation and decrease
dropout rates, the following 3 types of e-mails served as reminders or prompts: 1) an
"encouragement e-mail" for participants who had not finished all 6 topics, 2) a
"congratulations e-mail" for participants who finished all topics for the first time, and
3) an "application enhancement e-mail" for participants who finished all topics and were
ready for skills phase. These e-mails were sent to participants through the coordinator
every week throughout the intervention.

BODY.METHODS.MEASUREMENTS:
All data were assessed using self-report questionnaires, and all questionnaires were
administered on the internet. Questionnaires, as well as the learning program, were only
accessible with an ID and password. Details of the scales and questions used in the study
are described below.

BODY.METHODS.MEASUREMENTS.PRIMARY OUTCOMES:
Psychological distress was assessed using the 18-item Brief Job Stress Questionnaire
(BJSQ)24) measuring the extent to
which participants experienced irritability-anger, fatigue (e.g., "I am completely
tired"), anxiety (e.g., "I feel ill at ease"), depression (e.g., "I feel depressed"),
and lack of vigor in the four weeks prior. Items were scored on a 4-point scale ranging
from 1 (strongly disagree) to 4 (strongly agree). Higher scores indicated greater
psychological distress.  Job satisfaction was assessed using a single item of the BJSQ24) assessing the extent to which participants were
satisfied with their job. This item was scored on a 4-point scale ranging from 1
(dissatisfied) to 4 (satisfied). Higher scores indicated greater job satisfaction.  Work engagement was assessed using the short form of the Japanese version of the
Utrecht Work Engagement Scale (UWES-J)25). The UWES-J consists of 3 subscales with 9 items (i.e., vigor,
dedication, absorption). Items were scored on a 7-point scale ranging from 0 (never) to
6 (always). Item examples were "At my job, I feel strong and vigorous" (vigor), "I am
enthusiastic about my job" (dedication), and "I am immersed in my work" (absorption). A
total score was calculated using all 9 items. Higher scores indicated greater work
engagement.  Work performance was assessed using the World Health Organization (WHO) Health and Work
Performance Questionnaire (HPQ)26, 27). The HPQ includes items assessing the
following: quantitative and qualitative work efficiency over the previous 30 d (10
items), self-evaluated job outcomes relative to other workers (1 item), and special work
success or failure over the past 30 d (2 items). Due to the space limitation, one item
was removed from the HPQ (i.e., self-evaluated job outcomes relative to those of other
workers). Participants were also asked to rate their overall work performance over the
past 4 weeks. This item was scored using an 11-point scale ranging from 0 (worst
possible performance) to 10 (best possible performance). Higher scores indicated greater
perceived work performance.

BODY.METHODS.MEASUREMENTS.SECONDARY OUTCOMES:
Coping skills were assessed using a subscale taken from the Brief Scales for Coping
Profile (BSCP)28). The BSCP consists
of 6 subscales containing 18 items (i.e., active solution, seeking help for solution,
changing mood, emotional expression involving others, avoidance and suppression, and
changing point of view). Participants were asked to indicate the extent to which they
used a particular strategy for coping with stressful workplace situations using a scale
that ranged from 1 (almost never) to 4 (very often). The current study used an "active
solution" scale for problem solving and a "seeking help for solution" scale for seeking
social support. Examples were "I try to analyze the cause and solve the problem"
(problem solving), "I try to solve the problem by talking to those involved in the
matter" (seeking social support), "I try to do something that calms me down" (changing
mood), "I complain to people who have nothing to do with the problem" (emotional
expression involving others), "I do nothing but endure the situation because I don't
know what to do" (avoidance and suppression), and "I try to look at only the positive
aspects of the situation" (changing a point of view). Higher scores reflected more
frequent use of the indicated coping strategy.  Social support was assessed using 6 items of the BJSQ24). Items were scored on a 4-point scale ranging from 1 (disagree)
to 4 (agree). Three items were used to assess social support from participants'
supervisors and another three items assessed social support from coworkers (e.g., "How
much is each of the following people willing to listen to your personal problems?").
Higher scores indicated greater support.  Knowledge about how to cope with stress was assessed using 6 questions on the following
topics: (a) problem-solving skills, (b) time management skills, (c) assertion skills,
(d) delegation skills, (e) cognitive restructuring skills, and (f) causal attribution
skills. Participants were asked to choose the most suitable option among 4 skills
presented. A score of 1 was given for a correct answer. To assess the reliability and
validity of this measurement, 2 analyses were conducted. First, using T0 and T1 scores
from the wait-list control group, a weighted kappa statistic was calculated
(K=0.49). Next, the correlation between "the minimum number of days
participants log onto a website to study the contents" and "knowledge about stress
management" was assessed for the intervention group (T0 to T1 r=0.13,
p>0.05; T0 to T2 r=0.16,
p=0.06).

BODY.METHODS.MEASUREMENTS.COVARIATES:
Job demands were assessed by using 3-item subscales of the BJSQ24). Items were scored on a 4-point self-anchoring scale
ranging from 1 (strongly disagree) to 4 (strongly agree). An item example was "My job
requires working hard." High scale scores indicated a high extent of Job demands.

BODY.METHODS.MEASUREMENTS.DEMOGRAPHIC DATA:
Demographic data such as sex, age, and job position were also collected using the
questionnaire.

BODY.METHODS.SAMPLE SIZE CALCULATION:
The statistical power analysis was conducted using the G*Power 3 program29). We calculated sample size with a method
that takes into account the intracluster correlation coefficient (ICC)30). We assumed an intracluster correlation
of ρ=0.2, 15 participants for each unit. To prove an intervention effect
with an effect size of Cohen's d=0.4 (we decided effect size from our
previous study18)) and with an error
probability α=0.05 and 80% power, n=128 people in each
study arm were required for analysis.

BODY.METHODS.STATISTICAL ANALYSES:
All data were analyzed using Statistical Package for the Social Sciences (SPSS) version
18.0 J. Baseline characteristics of the intervention and wait-list control groups were
compared and tested using t-tests for continuous data comparisons and
χ2 tests for ordinal or categorical data comparisons. Furthermore, using the
T0 data from the intervention group, we also compared baseline characteristics between
"completers", or participants who completed all six contents and answered all T0, T1 and
T2 questionnaires, and "non-completers", or participants who answered the T0 questionnaire
but (1) did not complete all the contents and (2) did not answer the T1 and/or T2
questionnaires.  To assess the effects of the intervention on the primary and secondary outcomes, a group
× time interaction was tested using a mixed-model approach employing a repeated-measures
ANOVA and the restricted maximum likelihood (REML) estimation method. We included time and
group as fixed factors and subject as a nested within unit random factor. The
within-subjects factor was "time" and the between-subjects factor was "group". Job demands
were included in the model as a covariate. When the group × time interaction was
interpreted as significant, time simple main effect was computed for each group. In
addition, paired t-test for T0 to T1 and T0 to T2 were used to test the
differences. The effect size (Cohen's d) was also calculated as a
standardized measure of change31). Cohen
suggested the values of d equal to 0.20, 0.50, and 0.80 as small, medium,
and large effect sizes, respectively. Since multiple comparisons were made, the Bonferroni
correction was applied to control for increased probability of Type 1 errors or spurious
results. Using the Bonferroni procedure, statistical significance was reduced from 0.05 to
0.0038 (0.05/13).  We conducted additional analyses. First, we assessed intervention effects excluding
participants in the "dashed study group," which referred to participants that (1) did not
finished all 6 topics, (2) had finished the program in one day, or (3) had joined the
program 2 d before the study deadline. Even though our program allows for a short learning
time (1 topic per approximately 30 min), one or two days was not enough time to finish our
computer-based SMT program during working hours. It is important to note that participants
in the intervention group were divided into two groups by the median number of days they
spent studying.  Secondly, we conducted the sub-group analysis according to the level of psychological
distress at T0. In this sub-group analysis, participants were divided into one of two
groups using a median split. Using this approach we examined whether psychological
distress moderated the effects of the intervention. We performed this analysis because
past work32) has suggested that the
effects of an SMT program are more prominent among employees experiencing high
psychological distress.

BODY.METHODS.ETHICS:
The study procedure was approved by the Research Ethics Review Board of the University of
Tokyo, Graduate School of Medicine.

BODY.RESULTS.PARTICIPANT FLOW:
A summary of participant flow and retention is shown in Fig. 1Fig. 1.Enrollment, random assignment, and follow-up of the participants.. A total of 266 participants were invited to participate in the study and 263
participants were met eligibility requirements and included in the analysis. Of the 142
employees in the intervention group, 127 participants (89%) completed all 6 topics, and 16
employees (11%) did not finish it. Of the 16 employees, 1 employee discontinued the
program because he/she retired during the course of the study. The remaining 15 employees
did not specify the reason they did not complete the program. One hundred and sixteen
participants who completed all six contents and answered all measures at T0, T1 and T2.
One hundred and thirteen (80%) participants in the intervention group first learned
problem solving skills and then time management skills.

BODY.RESULTS.BASELINE CHARACTERISTICS:
Demographic characteristics and outcome variables at baseline for the intervention and
wait-list control groups are presented in Tables
1 and 2Table 1.Demographic characteristics by conditionInterventionWait-list controlGroup factors at baselineN84List sizeLow (<20)62High (≥20)22Individual factors at baselinen142121Age (mean)39.738.0n.s.†n of male (%)135 (95.1)109 (90.1)n.s.n of manager (%)37 (26.1)24 (19.8)n.s.† n.s. indicates no significant (p>0.05)Table 2.Baseline characteristics by conditfion and intracluster correlation
coefficients (ICC) of primary outcomeValuablesIntervention (n=142)Wait-list control (n=121)p valueICCMean(SD)Mean(SD)Primary outcomePsychological distress2.0(0.56)2.0(0.48)0.1570.032Work performance5.5(2.02)5.8(2.01)0.3010.054Job satisfaction2.9(0.65)3.0(0.66)0.1000.008Work engagement2.7(0.92)3.0(0.91)0.0280.033Secondary outcomeProblem-solving2.8(0.78)2.9(0.76)0.191Seeking social support2.5(0.85)2.7(0.90)0.132Changing mood2.8(0.99)2.8(0.98)0.978Emotional expression involving others1.5(0.49)1.5(0.52)0.860Avoidance and suppression2.0(0.69)1.8(0.67)0.054Changing point of view2.4(0.66)2.5(0.74)0.125Knowledge about stress management3.0(0.92)2.8(0.80)0.071Supervisor support2.5(0.62)2.6(0.59)0.161Coworker support2.6(0.58)2.7(0.56)0.250CovariateJob demands3.2(0.63)3.0(0.49)0.084. Although the intervention group had significantly higher scores on work
engagement compared to the wait-list control group (t=−2.2,
p=0.00), no other significant differences were found between the groups
(p>0.05).

BODY.RESULTS.DROPOUT ANALYSIS:
Baseline characteristics between completers (n=116) and non-completers (n=26) in the
intervention group were compared. Non-completers had significantly higher psychological
distress scores (t=2.04, p=0.043) and lower scores for
seeking social support (t=−2.63, p=0.009) and changing a
point of view compared to completers (t=−2.70, p=0.008). However,
we detected no differences between the groups in any of the other variables
(p>0.05).

BODY.RESULTS.EFFECTS OF THE INTERVENTION:
The effects of the intervention on the primary and secondary outcome measures are
presented in Table 3Table 3.Comparison of the scores between study conditions by mixed-effects models
ANOVAT0T1T2p valueCohen's d †Mean(SD)Mean(SD)Mean(SD)T1T2Primary outcomePsychological distressIntervention §2.0(0.48)1.9(0.45)2.0(0.45)0.9910.160.14Wait-list control ‡2.1(0.56)2.0(0.55)2.0(0.55)Work performanceIntervention5.8(2.01)5.8(1.93)5.9(1.75)0.4680.240.20Wait-list control5.5(2.02)5.4(1.82)5.5(1.91)Job satisfactionIntervention3.0(0.66)3.1(0.60)3.0(0.57)0.3560.350.29Wait-list control2.9(0.65)2.8(0.64)2.8(0.65)Work engagementIntervention3.0(0.91)2.9(0.91)3.0(0.99)0.1820.120.19Wait-list control2.7(0.92)2.8(0.94)2.8(0.94)Secondary outcomeProblem-solvingIntervention3.0(0.76)3.1(0.75)3.1(0.71)0.2550.310.37Wait-list control2.8(0.78)2.9(0.71)2.8(0.82)Seeking social supportIntervention2.7(0.90)2.9(0.84)2.9(0.80)0.4130.330.37Wait-list control2.5(0.85)2.6(0.81)2.6(0.86)Changing moodIntervention2.8(0.98)2.6(0.98)2.7(0.91)0.5210.130.02Wait-list control2.8(0.99)2.7(0.98)2.7(0.99)Emotional expression involving othersIntervention1.5(0.52)1.6(0.59)1.6(0.58)0.6960.050.09Wait-list control1.5(0.49)1.6(0.51)1.6(0.58)Avoidance and suppressionIntervention1.8(0.67)1.8(0.69)1.8(0.69)0.1040.180.46Wait-list control2.0(0.69)2.0(0.72)2.1(0.79)Changing a point of viewIntervention2.5(0.74)2.5(0.62)2.6(0.72)0.8910.190.26Wait-list control2.4(0.66)2.4(0.65)2.4(0.65)Knowledge about stress managementIntervention2.8(0.80)3.2(0.88)3.0(0.88)0.0030.190.19Wait-list control3.0(0.92)3.0(0.84)2.8(0.81)Supervisor supportIntervention2.6(0.59)2.7(0.55)2.7(0.61)0.5460.230.26Wait-list control2.5(0.62)2.5(0.60)2.5(0.61)Coworker supportIntervention2.7(0.56)2.7(0.52)2.7(0.58)0.5620.170.29Wait-list control2.6(0.58)2.6(0.54)2.6(0.54)Means and standard deviation (SD) are reported for each primary and secondary
outcome at baseline (T0), 9 (T1) and 19 (T2) weeks of follow-up.
p-values are based on mixed-model repeated measures ANOVA. Job
demands were adjusted for in the model. †Cohen's d: Small effect
0.20–0.49, medium effect 0.50–0.79, large effect >0.8010). ‡
Intervention group (n=85) § Wait-list control group
(n=121). A repeated-measures mixed-model ANOVA revealed a statistically significant
group × time interaction on knowledge about stress management (F=6.028,
p=0.003). The simple main effect of time on knowledge was significant
for both the intervention and wait-list control groups (F=7.785,
p=0.001; F=4.003, p=0.020,
respectively). Knowledge scores significantly increased from T0 to T1 in intervention
group (p<0.001) and significantly decreased from T0 to T2 in the
wait-list control group (p=0.023). However, there was no significant
group × time interaction on any of the other variables assessed
(p>0.05). It is important to note that we found small effects of the
intervention on measures of work performance (T1, T2), job satisfaction (T1, T2),
problem-solving (T1, T2), seeking social support (T1, T2), avoidance and suppression (T2),
changing a point of view (T2), supervisor support (T1, T2), and coworker support (T2).
However, these effects were not statistically significant.

BODY.RESULTS.EFFECTS OF THE INTERVENTION.ADDITIONAL ANALYSES:
In the intervention group, 40% of participants were met requirements for the "dashed
study group". We assessed intervention effects excluding participants in the "dashed
study group". In this analysis, there was no significant group × time interaction on the
primary outcome measures (p>0.05). However, a repeated-measures
mixed-model ANOVA revealed a group × time interaction on secondary outcome measures.
Specifically, there was a significant group × time interaction for "problem-solving",
"avoidance and suppression", and "knowledge about stress management"
(F=5.029, p=0.007; F=3.171,
p=0.043; F=7.819, p<0.001,
respectively). Furthermore, there was a marginally significant group × time interaction
for "seeking social support" (F=2.784, p=0.063).
However, there was no significant group × time interaction for any other secondary
outcomes (p>0.05).  The simple main effects of time on "problem-solving" and "seeking social support" were
statistically significant (F=9.668, p<0.001;
F=6.273, p=0.002, respectively) for the intervention
group only. For the intervention group, "problem-solving" and "seeking social support"
scores significantly increased from T0 to T1 (p=0.002;
p<0.001, respectively) and from T0 to T2
(p=0.004; p=0.007, respectively). The simple main
effect of time on "avoidance and suppression" was marginally significant
(F=2.520, p=0.083, respectively) for the wait-list
control group. The simple main effect of time on "knowledge about stress management" was
significant for both the intervention and wait-list control groups
(F=8.087, p<0.001; F=4.003,
p=0.020, respectively). Knowledge scores significantly increased from
T0 to T1 (p<0.001) and from T0 to T2 in the intervention group
(p=0.035). Conversely, knowledge scores significantly decreased from
T0 to T2 for the wait-list control group (p=0.023) (Table 4Table 4.Comparison of the scores between study conditions excluding participants who
used less than 3 d to complete the program by mixed-effects ANOVA modelsT0T1T2p valueBetween-ES†Mean(SD)Mean(SD)Mean(SD)T1T2Primary outcomePsychological distressIntervention ‡2.0(0.47)1.9(0.42)2.0(0.41)0.8200.220.12Wait-list control §2.0(0.56)2.0(0.55)2.0(0.55)Work performanceIntervention5.8(1.90)5.8(1.82)5.8(1.64)0.6460.230.16Wait-list control5.5(2.02)5.4(1.82)5.5(1.91)Job satisfactionIntervention3.0(0.70)3.0(0.58)3.0(0.53)0.3020.340.24Wait-list control2.9(0.65)2.8(0.64)2.8(0.65)Work engagementIntervention2.9(0.87)2.8(0.84)2.9(0.85)0.4670.080.16Wait-list control2.7(0.92)2.8(0.94)2.8(0.94)Secondary outcomeProblem-solvingIntervention2.9(0.76)3.1(0.76)3.2(0.67)0.0070.340.48Wait-list control2.8(0.78)2.9(0.71)2.8(0.81)Seeking social supportIntervention2.7(0.89)2.9(0.76)2.9(0.80)0.0630.460.42Wait-list control2.5(0.85)2.6(0.81)2.6(0.86)Changing moodIntervention2.8(0.98)2.5(1.00)2.7(0.89)0.4810.160.00Wait-list control2.8(0.99)2.7(0.98)2.7(0.99)Emotional expression involving
othersIntervention1.4(0.39)1.6(0.51)1.5(0.45)0.2450.000.04Wait-list control1.5(0.49)1.6(0.51)1.6(0.58)Avoidance and suppressionIntervention1.9(0.62)1.8(0.67)1.7(0.62)0.0430.220.54Wait-list control2.0(0.69)2.0(0.72)2.1(0.79)Changing a point of viewIntervention2.5(0.75)2.5(0.62)2.6(0.68)0.9570.250.27Wait-list control2.4(0.66)2.4(0.65)2.4(0.65)Knowledge about stress managementIntervention2.8(0.83)3.3(0.82)3.1(0.85)0.0000.330.34Wait-list control3.0(0.92)3.0(0.84)2.8(0.81)Supervisor supportIntervention2.6(0.60)2.6(0.58)2.6(0.62)0.4170.170.24Wait-list control2.5(0.62)2.5(0.60)2.5(0.61)Coworker supportIntervention2.7(0.59)2.7(0.51)2.7(0.54)0.2990.130.31Wait-list control2.6(0.58)2.6(0.54)2.6(0.54)Means and standard deviation (SD) are reported for each primary and secondary
outcome at baseline (T0), 9 (T1) and 19 (T2) weeks of follow-up.
p-values are based on mixed-model repeated measures ANOVA. Job
demands were adjusted for in the model. †Cohen's d: Small effect
0.20–0.49, medium effect 0.50–0.79, large effect >0.8010). ‡ Intervention group (n=85). §
Wait-list control group (n=121)).  Next, we conducted a sub-group analysis according to level of psychological distress at
T0. Among participants with low initial psychological distress levels, a
repeated-measures mixed-model ANOVA revealed a significant group × time interaction on
"knowledge about stress management" (F=5.186,
p=0.006). However, results did not show a significant group × time
interaction on any other variables (p>0.05). The simple main effect
of time on "knowledge about stress management" was statistically significant for both
the intervention and wait-list control groups (F=4.698,
p=0.011; F=8.789, p<0.001,
respectively). Knowledge scores significantly increased from T0 to T1 among participants
in the intervention group (p=0.008) and significantly decreased from T0
to T2 among participants in the wait-list control group (p<0.001).
In contrast, among participants with high initial psychological distress levels, a
repeated-measures mixed-model ANOVA revealed a marginally significant group × time
interaction on "seeking social support" (F=2.863,
p=0.059). However, there was no group × time interaction on any other
variables (p>0.05). The simple main effect of time on "seeking
social support" was significant for the intervention group (F=5.459,
p=0.005). For participants in the intervention group, "seeking social
support" scores significantly increased from T0 to T1 (p=0.019) and T0
to T2 (p=0.006).

BODY.DISCUSSION:
The purpose of this study was to develop a computer-based SMT program and to evaluate its
effectiveness on employees' psychological resources and well-being. We used a cluster
randomization design that assigned employees to intervention and control groups by work
unit. One advantage of this design was that it prevented participants from finding out about
the contents of the program33). If
individual allocation had been used for this study, participants in the control group might
have been affected by interactions with their colleagues in the intervention group.
Furthermore, in contrast to previous interventions, which have typically focused on a single
topic20, 34,35,36), the current work employed a computer-based SMT program that
assessed a wider variety of topics on stress management skills.  The completion rate, or the ratio of participants who completed the whole program, was
higher in the current research (89 and 92% for the intervention and wait-list control
groups, respectively) compared to previous studies (76–86%)20, 34, 37). In addition, a manager in the intervention group requested
permission to use the materials for future management training of his subordinates. These
results suggest that the contents and procedures used in the current intervention were
accepted by the participants.  Dropout analyses revealed that employees with high initial levels of "psychological
distress" tended to drop out throughout the study. This result is in line with previous
research showing that stressed employees are more likely to drop out than their non-stressed
counterparts32).  Contrary to our expectations, we found a favorable effect of the intervention only on
"knowledge about stress management" at T1 but not on any other primary or secondary outcomes
at T1 and T2. In our study, 40% of participants (i.e., dashed study group) finished the
program in 1 or 2 d, and almost all of them accessed the program 2 d before the deadline for
the first time. This suggests that they did not have enough time to incorporate their newly
acquired knowledge and skills into their everyday life. Previous research has shown that
more frequent use of stress-reduction skills are significantly correlated with greater
improvements in stress related outcomes21). Hence, more time would have been necessary for participants to show
improvements on all other outcomes variables except for knowledge. This explanation is
bolstered by the finding that the intervention produced favorable effects not only on
participants' knowledge but also on coping skills (i.e., problem-solving, and seeking social
support) at T1 and T2 (when excluding data from the dashed-study group). More frequent use
of problem-solving and support-seeking skills in participants' daily lives may have led to
these improvements. Nevertheless, it should be noted that, while not statistically
significant, our program had small effects on outcome variables (i.e., work performance, job
satisfaction, problem-solving, seeking social support, and supervisor support). It was
hypothesized that the intervention would improve participants' self-efficacy; however, our
findings suggest that in spite of the intervention, participants were not able to
incorporate their newly learned skills into the work setting. This failure may, in turn,
have caused a reduction of self-efficacy. As such, the practical phase of this intervention
may benefit from more intensive follow-up sessions aimed at teaching participants how to
apply their newly learned skills to work setting scenarios.  Despite the methodological rigor of the present study, there are five limitations that
should be addressed in future research. The first limitation has to do with the sample
characteristics. Specifically, all participants in the study were employees at a
manufacturing company, most of whom were men. Therefore, this population is not
representative of the general working population. The second limitation is that our
computer-based SMT program consisted of 6 topics, but we did not examine the effect of order
on any outcome measures. Future research is needed to clarify whether there is an effect of
order on program learning. The third limitation is that outcome measures were only assessed
via self-report. Self-reported data could increase the problem of common method variance.
Objective indicators on physical health (e.g., urinary cortisol, salivary cortisol, blood
pressure, heart rate) and work performance (e.g., personnel evaluation) should also be
assessed in future work. The fourth limitation is that no specific indications of how long
it took for the intervention effect to appear or disappear were found. Although there is
some evidence showing that without booster sessions, the effectiveness of similar
interventions diminishes after 6 months38), more research is still needed. The fifth limitation pertains to the
clinical/practical significance of the current research findings. Specifically, the observed
changes between baseline and the follow-up sessions for the control and intervention groups
are unclear due to lack of previous evidence and quantitative information. Additional
studies on the effects of web-based psychoeducation are needed to assess the
clinical/practical significance of the effect of this kind of intervention on changes in the
outcomes of interest.  In conclusion, the computer-based stress management program was effective in improving
knowledge about stress management. Among participants that had enough time (at least 3 d) to
complete all training sessions, the intervention was also effective at improving coping
skills.

Question: Compared to Control what was the result of Stress managin training on Problem-solving?
Evidence: In this analysis, there was no significant group × time interaction on the
primary outcome measures (p>0.05). 
Answer: significantly increased