ORIGINAL ARTICLE
Effects of an Internet-Based Cognitive Behavioral Therapy Intervention on Improving Work Engagement and Other Work-Related Outcomes An Analysis of Secondary Outcomes of a Randomized Controlled Trial Kotaro Imamura, PhD, Norito Kawakami, MD, Toshi A. Furukawa, MD, Yutaka Matsuyama, PhD, Akihito Shimazu, PhD, Rino Umanodan, PhD, Sonoko Kawakami, MS, and Kiyoto Kasai, MD
Objective: This study reported a randomized controlled trial of the effectiveness of an Internet-based cognitive behavioral therapy (iCBT) program on work engagement and secondary work-related outcomes. Methods: ParFrom the Department of Mental Health (Dr Imamura, Dr Kawakami, and Dr Shimazu), Department of Biostatistics (Dr Matsuyama), and Department of Neuropsychiatry (Dr Kasai), Graduate School of Medicine, The University of Tokyo; Departments of Health Promotion and Human Behavior and of Clinical Epidemiology (Dr Furukawa), Graduate School of Medicine/School of Public Health, Kyoto University; Kyoto Office (Dr Umanodan), Health Wave Co, Ltd; and Nippon University College of the Arts (Ms Kawakami), Tokyo, Japan. This study was supported by the Grant-in-Aid for Scientific Research (A) 2009 and 2010 (No. 20240062) and the Grant-in-Aid for Young Scientists (B) 2014 (No. 26860433) from the Japan Society for the Promotion of Science. The sponsor of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The authors had access to the data in the study and the final responsibility to submit the paper. Dr Imamura is employed part-time by Chugai Pharmaceutical Company and Medical Care Toranomon as a clinical psychologist. Dr Kawakami has received honoraria for speaking at CME meetings sponsored by GlaxoSmithKline, Eizai, and Pfizer. He is on the advisory board for Sekisui Chemicals and Junpukai Health Care Center. He has received royalties from Chuo-Hoki-Shuppan, Igaku-Shoin, Kyobun-do, Life Science, Maruzen, Nanko-do, Nanzan-do, and Fujitsu Software Technologies, Ltd, and research grants from Fujitsu Software Technologies, Ltd, Softbank, Co, Ltd, and Japan Management Association. Dr Furukawa has received lecture fees from Eli Lilly, Meiji, Mochida, MSD, Pfizer, and Tanabe-Mitsubishi, and consultancy fees from Sekisui and Takeda Science Foundation. He is diplomate of the Academy of Cognitive Therapy. He has received royalties from Igaku-Shoin, Seiwa-Shoten, and Nihon Bunka Kagaku-sha. The Japanese Ministry of Education, Science, and Technology, the Japanese Ministry of Health, Labor and Welfare, and the Japan Foundation for Neuroscience and Mental Health have funded his research projects. Dr Matsuyama has received lecture fees from the Union of Japanese Scientists and Engineers, EPS Co, Ltd, and Statcom Co, Ltd, and consultancy fees from Zeria Pharmaceutical Co, Ltd, Ono Pharmaceutical Co, Ltd, and Mebix Co, Ltd. He has received royalties from Igaku-Shoin and Ewanami-Shoten. Dr Shimazu works for Hitachi Systems, Ltd, as a part-time consultant. He is on the advisory board for Junpukai Health Care Center and Ds’s Mental Health Labo. He has received royalties from Baifukan, Kawashima-shoten, Seishin-shobou, and Seiwa-Shoten. Dr Umanodan is employed by Health Wave Co, Ltd, as a clinical psychologist. Ms Kawakami is employed by Square-Enix Co, Ltd, as a contract employee. She also worked part-time for Dice Creative, Co, Ltd. Dr Kasai has received lecture fees from Astellas, Novartis, Eli Lilly, Otsuka, Dainippon-Sumitomo, and Yoshitomi Pharmaceutical Companies. He has received collaborative research grants from Astellas, Hitachi Co, and Hitachi Medical, and research grants from Yoshitomi, Dainippon-Sumitomo, Astellas, and GSK. Drs Imamura and Kawakami conceived of the study, developed study design, conducted literature search, collected, analyzed, and interpreted data, and prepared the first draft. Drs Furukawa, Matsuyama, Shimazu, and Kasai developed study design and interpreted data. Dr Umanodan and Ms Kawakami provided technical support. All authors reviewed the manuscript. The authors declare no conflicts of interest. Address correspondence to: Norito Kawakami, PhD, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-0033, Japan ([email protected]). C 2015 by American College of Occupational and Environmental Copyright Medicine DOI: 10.1097/JOM.0000000000000411
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ticipants who fulfilled the inclusion criteria were randomly allocated to an intervention or a control group (N = 381 for each). A 6-week, 6-lesson iCBT program using a Manga (Japanese comic) story was provided only to the intervention group. Work engagement was assessed at baseline and at 3- and 6-month follow-ups for both groups. Results: The iCBT program showed a significant intervention effect on work engagement (P = 0.04) with small effect sizes (Cohen’s d = 0.16 at 6-month follow-up). Conclusions: The study showed computerized cognitive behavior therapy delivered via the Internet to be effective (with a small effect size) in increasing work engagement in the general working population. Trial Registration: UMIN Clinical Trials Registry (UMIN-CTR) UMIN000006210.
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ecently, occupational health research has focused on positive health outcomes, while mortality, mobility, and other illhealth indicators are still important.1 One outcome is work engagement, which is a positive, fulfilling, work-related state of mind and measured with three dimensions: vigor, dedication, and absorption.2,3 The other outcome, closely related to work engagement, is work performance, which includes both sick leave and onthe-job performance.4,5 There is increasing research to develop interventions to improve work engagement. We searched the literature using databases including PubMed, PsycINFO, and PsycARTICLES, and found six previous randomized controlled trials (RCTs) on this topic,6–11 which were all published since 2012. Nevertheless, four of the six RCTs, which included lifestyle change programs such as a physical fitness, failed to show a significant improvement in work engagement6,8 ; one focused on mindfulness-based intervention7 and another on career management skill workshops.9 Another RCT reported a significant, but small effect only for changing the physical environment (eg, creating a coffee corner) on the absorption subscale of work engagement.10 The last RCT found a significant effect of an online mindfulness-based intervention on Shirom’s vigor scale score among workers immediately after the intervention,11 but the effect at a longer follow-up was not assessed with an RCT design, and thus is unclear. A more effective intervention to improve work engagement needs to be developed and tested. Cognitive behavioral therapy (CBT)12,13 has been applied extensively to stress management interventions in workplace settings, and previous findings have revealed its effectiveness of improving work-related stress and negative emotions such as depression and anxiety among workers.14,15 In addition, a limited number of studies have reported that CBT-based intervention programs are effective in improving positive mental health at work, by such measures as job satisfaction16,17 and vitality,18 which— while similar—are not exactly the same as work engagement. Work engagement is considered a persistent and pervasive affective cognitive state.2,3 Thus, a CBT-based intervention may also be effective in improving work engagement. Nevertheless, no study has investigated the effects of a CBT-based intervention on improving work engagement. JOEM r Volume 57, Number 5, May 2015
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A previous controlled trial reported a significant effect of CBT-based stress management interventions in improving work performance among workers.19 One study included in a metaanalysis15,20 reported a nonsignificant and small (−0.18 in Cohen’s d) effect of CBT on improving absenteeism (ie, sick leave days) among workers. Nevertheless, two other RCTs failed to show a significant effect of improving work performance or absenteeism by applying telephone CBT-based interventions among depressed workers.21,22 A larger-scale RCT is needed to examine whether a CBT intervention could improve work performance, specifically regarding on-the-job work performance and absenteeism. Computerized CBT delivered via the Internet (iCBT) holds promise as a cost-effective method to make CBT accessible to more workers.23–25 The iCBT program provides basic information and skills on the basis of the same CBT principles as face-to-face CBT programs, with a highly structured format that comprises educational lessons, homework assignments, and supplementary resources.26 Although most studies of iCBT programs have focused on the treatment of patients with depression and anxiety disorders in clinical settings, showing favorable effects,27 the effects of iCBT programs on improving subthreshold depression have also been documented among healthy workers.25 Nevertheless, no previous study has investigated the beneficial effects of an iCBT program on improving work engagement and work performance among workers. The effects of iCBT have been shown to vary depending on the extent of therapist involvement. A previous meta-analysis of treatment studies reported that the effect size of iCBT programs with therapist support was greater than that of self-guided programs without therapist support, about 0.6 and 0.25, respectively, in Cohen’s d.24,28 Even so, self-guided programs may still have merit because of their greater accessibility and much lower cost.26 The purpose of this study was to examine the effects of an iCBT program on improving work engagement and work performance in the general working population. We analyzed data of these work-related outcomes, which were collected as secondary outcomes at 3- and 6-month follow-ups in an RCT that primarily targeted improving subthreshold depressive symptoms among the nonclinical general working population in Japan.25 We also tested whether the effect of the intervention on work-related outcomes was partly mediated by improvement of depression, the primary outcome of the study.
METHOD Trial Design Data for this study were collected as secondary outcomes of an RCT primarily examining the effects of an Internet-based CBT intervention on improving subthreshold depressive symptoms among healthy workers.25 The original trial was registered at the UMIN Clinical Trials Registry (UMIN-CTR; ID = UMIN000006210).
Participants Participants were recruited from employees of two information technology companies. All workers in one company (N = 290) and workers in three departments of another company (N = 1500) were invited by e-mail to participate in the study in September and October 2011. The inclusion criteria at the baseline survey were (1) aged 20 to 60 years at the study entry, (2) males and females, (3) currently employed full-time by the business company, and (4) having access to the Internet via a PC at home or at the workplace. The exclusion criteria were (1) having a major depressive disorder in the past month (using diagnostic criteria on the web version of the WHO-CIDI 3.029 ), (2) having lifetime bipolar disorder (WHO-CIDI 3.0), (3) having sick leave days of 15 days or more in total because of own health problems during the past 3 months, and (4) receiving medical treatment for mental health problems during the past month.
Internet-Based CBT in Work Engagement
Randomization Participants who fulfilled the inclusion criteria were randomly allocated to an intervention (N = 381) or a control group (N = 381) (see Imamura et al., 2014, for more detail.25 ). An independent biostatistician created a permuted-block random table. A clinical research coordinator conducted enrollment, and an independent research assistant conducted assignment. The permuted-block random table was password-protected and blinded to the researcher. Only the research assistant had access to the table during the work of random allocation.
Intervention Participants in the intervention group were provided access to the iCBT program.25 Briefly, the program provided a 6-week webbased training course consisting of weekly 30-minute training sessions in CBT-based stress management skills. The CBT components of the program included self-monitoring (in lesson 2), cognitive restructuring (in lesson 3), cognitive restructuring and relaxation (in lesson 4), assertiveness (in lesson 5), and problem solving (in lesson 6). At the end of each lesson, participants were asked to submit homework to facilitate their learning, although it was voluntary. Participants who submitted their homework received feedback from trained clinical psychologists. Five trained clinical psychologists provided feedback on the submitted homework just one time per lesson, on a first-come first-served basis. A particular clinical psychologist was not always assigned to a particular participant.
Intervention and Control Group Conditions Participants in the intervention group were encouraged to complete six weekly lessons and submit homework from the iCBT program within 10 weeks after the baseline survey. Participants were reminded by email to complete a lesson and/or to submit a homework assignment if they had not done so. Participants in the control group received a short email message of non-CBT stress management tips.25 Participants in the intervention and control groups were also able to use an internal employee assistance program service. All employees (both intervention and control groups) of Company B were provided another one-session e-learning program for stress management during the study. A possible contamination of information learnt by the intervention group participants to the control group participants was not assessed.
Outcome Measures All outcomes including work-related outcomes and depression as a mediator were measured using a web-based selfreport questionnaire at baseline, 3-month follow-up, and 6-month follow-up.
Work Engagement Work engagement was assessed using the short form of the Japanese version of the Utrecht Work Engagement Scale (UWES).30 The UWES consists of three subscales comprising nine items (ie, vigor, dedication, and absorption). Items are scored on a seven-point scale ranging from zero (never) to six (always). Item examples are “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 from all nine items.
Work Performance Work performance was assessed using one item from the WHO Health and Work Performance Questionnaire (HPQ).31 Respondents were asked to rate their overall work performance during the past 4 weeks. The item was scored on an 11-point scale ranging from 0 (worst possible performance) to 10 (best possible performance). High scores indicated a high degree of perceived work performance.
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Sick Leave Days During the Past 3 Months Respondents were asked to report the number of sick leave days during the past 3 months.
Depression as a Mediator As a mediator for the intervention effect on work-related outcomes, depression was measured by using the Beck Depression Inventory II (BDI-II), a 21-item self-report inventory.32,33 A higher total score indicates serious depressive symptoms.
Demographic Characteristics Demographic data such as age, sex, marital status, occupation, education, and chronic disease were also collected at baseline.
Statistical Power Calculation A minimum sample size of 336 in each group was determined to detect an effect size of 0.30 or greater for depressive symptoms, at an alpha error rate of 0.05 (two-tailed) and a beta error rate of 0.10, with an expected dropout rate of 30%. No previous study reported an effect size for any type of intervention for work engagement. An estimated post hoc power (1-beta) was 1.00 if the effect size was medium (0.5) and 0.75 if the effect size was small (0.2), assuming that alpha was less than 0.05 (two-tailed), and 70% of the initial 381 respondents in each group completed the follow-up using the G*Power 3 program.34,35
Statistical Analyses As a primary analysis, a mixed model for repeated measures conditional growth model analysis was conducted using a group (intervention and control) × time (baseline, 3-month, and 6-month follow-up) interaction as an indicator of intervention effect. Intention-to-treat analysis was conducted. The linear mixed model in PASW Statistics 18.0 (SPSS Inc, Chicago, IL) was used. As a sensitivity analysis, a mixed model for repeated measures analysis of variance model analysis was conducted. Also, the effect sizes and the 95% confidence intervals (95% CIs) were calculated using Cohen’s d only among those who completed the questionnaire at baseline and at follow-up, although the effect sizes may be more biased because of dropping out. The values of 0.2, 0.5, and 0.8 are generally interpreted as being suggestive of small, medium, and large effects, respectively.36 A mediation analysis was conducted on the effect of the intervention (X, coded as 1 = intervention and 0 = control) on a change of each outcome variable (Y, for work engagement score, sick leave days, or HPQ score), with using a change of the BDI-II score as a mediator (M). The analysis was done separately for 3- and 6-month follow-ups, among respondents who completed each follow-up. A direct effect was estimated as a unique effect of X on Y adjusting for M; an indirect effect was estimated as a product of correlation coefficients of X on M and of M on Y. The direct and indirect effects were directly tested by using a mediation analysis method with an SPSS macro.37
FIGURE 1. Participant flowchart.
RESULTS Participant Flowchart The participant flowchart is shown in Fig. 1. A total of 850 (47.5%) workers in the target workplaces completed a baseline survey. Of those, 88 were excluded because they did not fulfill the criteria. The remaining 762 participants were randomly allocated to an intervention or a control group (N = 381 for each). At 3-month follow-up, 270 (70.9%) participants in the intervention group and 336 (88.2%) in the control group completed the follow-up survey. At 6-month follow-up, 272 (71.4%) participants in the intervention group and 320 (84.0%) in the control group completed the follow-up survey. Reasons for dropping out were not assessed in this study. For the process evaluation, 247 (64.8%) participants of the intervention group completed all six lessons, whereas 93 (24.4%) of them submitted all six homework assignments. The participants’ transferral between the groups did not occur.
Ethics
Baseline Characteristics
The Research Ethics Review Board of the University of Tokyo, Graduate School of Medicine (No. 3083), approved the study procedures. Before the baseline survey, participants were invited to read the explanation on the Web site, and asked to click an “agree” button to show their consent to participate in the study; then they proceeded to the baseline questionnaire page. Written consent was not required by the National Ethical Guidelines for Epidemiologic Research, Japan; the Research Ethics Review Board of Graduate School of Medicine, the University of Tokyo, approved this procedure to obtain participants’ consent.
Demographic characteristics are presented in Table 1. No significant differences existed in the demographic characteristics between the intervention and control groups. In both groups, most participants were males, professionals, and received university or higher education, and did not have any chronic disease. Among the total sample at baseline (n = 762), the BDI-II depression score moderately and negatively correlated with work engagement (Spearman’s r = −0.42, P < 0.01) and work performance (r = −0.37, P < 0.01), and weakly and positively with sick leave days (r = 0.18; P < 0.01). Although work engagement and work performance positively
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Internet-Based CBT in Work Engagement
TABLE 1. Baseline Characteristics of Participants in the Intervention and Control Groups Intervention Group (N = 381) n (%) Age, yrs 18–34 35–44 45–60 Sex (male) Marital status (currently married) Occupation Manager Professional Clerical/sales Production Others Education High school Some collage University or higher Chronic disease (yes) Depressive symptoms (scored by BDI-II)
Mean (SD)
Control Group (N = 381) n (%)
Mean (SD)
P* 0.54
157 (41.2) 123 (32.3) 101 (26.5) 325 (85.3) 212 (55.6)
167 (43.8) 126 (33.1) 88 (23.1) 314 (82.4) 226 (59.3)
93 (24.4) 256 (67.2) 21 (5.5) 3 (0.8) 8 (2.1)
79 (20.7) 278 (73.0) 19 (5.0) 3 (0.8) 2 (0.5)
43 (11.3) 60 (15.7) 278 (73.0) 38 (10.0)
34 (8.9) 70 (18.4) 277 (53.7) 44 (11.5)
0.33 0.47 0.25
0.59
11.9 (8.0)
11.8 (8.0)
0.56 0.83
*t test or chi-square test. BDI-II, Beck Depression Inventory II; SD, standard deviation.
correlated (r = 0.34, P < 0.01), these two outcomes only weakly correlated with sick leave days (r = −0.07, P < 0.05; and r = −0.10, P = 0.01, respectively).
P = 0.95) and 0.06 (SE = 0.04, P = 0.09, 87% of the total effect), respectively. The direct and indirect effects at 6-month follow-up were −0.096 (SE = 0.14, P = 0.55) and 0.09 (SE = 0.48, P = 0.07, 1,009% of the total effect), respectively.
Effects of the iCBT Program on Work-Related Outcomes Table 2 shows the means and standard deviations of the outcome variables at baseline, 3-month, and 6-month follow-ups in the intervention and control groups. Table 3 shows the estimated effects of the iCBT program on the outcome variables on the basis of the mixed-model analyses. The iCBT program showed a significant effect on the UWES (t = 2.03, P = 0.04). Nevertheless, the effect sizes were small: 0.11 (95% CI, −0.05 to 0.27) at 3-month follow-up and 0.16 (95% CI, 0.0007 to 0.32) at 6-month follow-up. The program showed a marginally statistically significant effect on sick leave days during past 3 months (t = −1.84, P = 0.07). Again, the effect sizes were small: −0.16 (95% CI, −0.32 to 0.0003) at 3-month follow-up and −0.14 (95% CI, −0.30 to 0.02) at 6-month follow-up.
Mediation Analysis Among respondents who completed 3-month follow-up (n = 606), direct and indirect effects through the change in the BDI of the intervention on UWES scores at 3-month follow-up were 0.06 (standard error [SE] = 0.06, P = 0.34) and 0.03 (SE = 0.02, P < 0.10, explaining 31% of the total effect), respectively. Among respondents who completed 6-month follow-up (n = 592), the direct and indirect effects through the change in the BDI were 0.099 (SE = 0.07, P = 0.13) and 0.035 (SE = 0.02, P = 0.07, 26% of the total effect), respectively. For sick leave days, the direct and indirect effects at 3-month follow-up were −0.677 (SE = 0.35, P = 0.05) and −0.00 (SE = 0.03, P = 0.94, 0.3% of the total effect), respectively. The direct and indirect effects at 6-month follow-up were −0.643 (SE = 0.39, P = 0.10) and −0.04 (SE = 0.04, P = 0.35, 5% of the total effect), respectively. For the work performance score, the direct and indirect effects at 3-month follow-up were 0.01 (SE = 0.14,
DISCUSSION The present RCT examined the effects of a newly developed iCBT program to improve work engagement and work performance as the secondary outcomes at 3- and 6-month follow-ups among workers employed in private companies in Japan. The iCBT program showed a significant small intervention effect on work engagement at 6-month follow-up. The iCBT program also showed a marginally statistically significant intervention effect on sick leave days during the past 3 months. On the other hand, the iCBT program did not show a significant intervention effect on the HPQ. This study also found that a change of depression partly mediated the effect of the iCBT on work engagement but not for sick leave days. The iCBT program significantly increased work engagement, as measured by the UWES, among the intervention group, compared with the control group (P = 0.04), whereas the effect was small (0.07 per 6 months). The effect sizes were also small (0.11 to 0.16) and nonsignificant at 3-month follow-up, possibly because the estimates were only based on the responders to these surveys. To our knowledge, this is the first study that demonstrated a positive effect of an iCBT program on improving work engagement. Work engagement is theoretically considered to be affected by psychological resources such as self-efficacy, optimism, and positive perception regarding one’s job.38,39 A possibility is that improved depression by the iCBT program, as already shown in our previous report,25 might contribute to improvement of work engagement to some extent. In fact, in this study, a change in depression marginally significantly mediated the effect on work engagement, which explained 26% to 31% of the total effect. Nevertheless, the direct effect still remained explaining the majority of the total intervention effect, whereas it was not statistically significant, partly because of a lack of statistical
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TABLE 2. Means (SDs) of Outcome Variables at Baseline, 3-, and 6-Month Follow-Up in the Intervention and Control Groups for the Whole Sample Intervention
UWES HPQ Sick leave days during the past 3 mos
Control
Baseline (N = 381) Mean (SD)
3 mos (N = 270) Mean (SD)
6 mos (N = 272) Mean (SD)
Baseline (N = 381) Mean (SD)
3 mos (N = 336) Mean (SD)
6 mos (N = 320) Mean (SD)
2.4 (1.0) 5.4 (1.9) 0.9 (1.7)
2.4 (1.0) 5.4 (2.0) 1.3 (3.3)
2.5 (1.1) 5.6 (1.9) 1.4 (3.5)
2.6 (1.0) 5.4 (1.9) 0.7 (1.5)
2.4 (1.0) 5.2 (2.0) 1.9 (4.9)
2.5 (1.1) 5.5 (2.0) 1.9 (5.8)
HPQ, Health and Work Performance Questionnaire; SD, standard deviation; UWES, Utrecht Work Engagement Scale.
TABLE 3. Effect of the Internet-Based Computerized Cognitive Behavioral Therapy Program on Work-Related Outcome Variables for the Whole Sample Estimated Means (Standard Errors) Intervention UWES 3 mos* 2.4 (0.1) 6 mos* 2.5 (0.1) Pooled† HPQ 3 mos* 5.3 (0.1) 6 mos* 5.5 (0.1) Pooled† Sick leave days during the past 3 mos 3 mos* 1.3 (0.2) 6 mos* 1.4 (0.2) Pooled†
Control
Estimates of Fixed Effects (95% CI)
t
P
2.4 (0.1) 2.4 (0.1)
0.08 (−0.04 to 0.19) 0.14 (−0.02 to 0.29) 0.07 (0.002 to 0.13)
1.29 1.73 2.03
0.20 0.08 0.04
5.2 (0.1) 5.5 (0.1)
0.07 (−0.22 to 0.35) 0.01 (−0.34 to 0.36) 0.00 (−0.15 to 0.16)
0.47 0.04 0.04
0.64 0.97 0.97
1.9 (0.2) 1.9 (0.2)
− 0.71 (−1.42 to 0.003) − 0.63 (−1.41 to 0.15) − 0.32 (−0.66 to 0.02)
−1.95 −1.58 −1.84
0.05 0.11 0.07
*A mixed-model for repeated measures analysis of variance model analyses was conducted. †A mixed-model for repeated measures conditional growth model analyses was conducted. CI, confidence interval; HPQ, Health and Work Performance Questionnaire; UWES, Utrecht Work Engagement Scale.
power. The current iCBT program may enhance work engagement by other mechanisms, such as improving psychological resources, such as self-efficacy and positive perception. The iCBT program may be effective in improving work engagement among workers with the universal approach (ie, targeting the whole working population). Even though the effect size is small, the public health impact may be still meaningful, if the great accessibility and minimal cost of this kind of program are considered. A mechanism with which a CBT program could improve work engagement should be investigated further in a future study. Only a few previous studies investigated the effect of a CBT program on sick leave days among workers, and the results remain controversial.14,15 Although the result was only marginally statistically significant, this study added additional evidence for an effect of CBT programs on reducing sick leave days. A change of depression did not mediate the intervention effect; rather the iCBT showed a marginally significant direct effect on sick leave days. Non–moodimproving components of this iCBT program, such as assertiveness, problem-solving, and relaxation skills, may have been effective for improving sick leave. The iCBT program failed to improve on-thejob work performance as measured by the HPQ at 3- or 6-month follow-up. Previous telephone-based CBT interventions, which consisted of cognitive restructuring and behavioral activation, did not show such an effect on on-the-job work performance as measured by the HPQ.21,22 Nevertheless, a program combining cognitive restruc582
turing and problem-solving techniques showed a positive effect.19 Although the current program included a component for problemsolving techniques, enhancing this component may improve work performance. On the other hand, the intervention effect on work performance was almost mediated by a change of depression. The current program showed a significant but only small effect for improving depression (Cohen’s d: −0.15, at 6-month follow-up).25 A nonsignificant intervention effect on work performance may be attributable to the small effect size of this low-intensity program for improving depression.
Limitations This study has several limitations. First, participants were recruited from two IT companies in Japan. Computer software engineers and technicians are known as stressful occupations, and they have been reported to have schizotypal and avoidant personality traits.40 Most participants were males, professionals, and university graduates, and they had their own PCs in their offices or homes. Participants were also supposed to have experience using a PC and studying using online programs. Higher education levels may also help participants learn from the iCBT program. Therefore, generalization of the present findings to the working population is limited. Second, the rate of completing homework was low, although the completion rate of lessons was moderate and similar to the previous guided iCBT program.41 Only 93 participants submitted all
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JOEM r Volume 57, Number 5, May 2015
homework assignments, and the average number of homework assignments submitted was 2.7 per respondent, which may particularly weaken the findings. For the future implementation of this iCBT program, it is essential to keep or even increase the participants’ program completion rate by, for instance, an improvement of reminder messages or the use of mobile devises. Third, the dropout rates from the follow-up surveys in this study were 29.1% and 28.6% at 3- and 6-month follow-ups, respectively. In their systematic review, Kaltenthaler et al42 reported that the average computerized CBT dropout rates were 18% to 35%. Wantland et al43 reported that an average dropout rate was 21%. The dropout rates in this study were within these ranges. Nevertheless, dropouts may have caused an attrition bias, particularly if participants in the intervention group had higher levels of motivation and were more likely to complete the program. Fourth, there was the possibility that participants in the control group could have information about the iCBT program from participants in the intervention group at same workplace. Such a contamination is one of the major limitations. In addition, this study provided the participants in the control group with stress management tips by several e-mails. These may weaken the intervention effect. Fifth, all outcomes in this study were measured by self-report, which may be affected by participants’ perceptions or situational factors at work. A self-reported measure could be vulnerable to a cognitive bias. A future study should consider the use of objectively measured outcomes such as supervisor ratings or company records of sick leave and work performance of participants. A further RCT should be conducted to examine whether the iCBT program is effective in a larger sample of workers with diverse characteristics, particularly in terms of occupation and education.
CONCLUSIONS This study first demonstrated that a computerized cognitive behavior therapy delivered via the Internet was effective in increasing work engagement in the general working population. The effect was partly, but not fully, explained by a change of depression.
ACKNOWLEDGMENTS We appreciate the help of the following persons in completing this project: Takayuki Narumi, Jun Naoi, Keisuke Kito, Chinatsu Narumi, Fukiko Ueda, and Mizuho Yamagishi.
REFERENCES 1. Schaufeli WB. The future of occupational health psychology. Appl Psychol. 2004;53:502–517. 2. Schaufeli WB, Salanova M, Gonz´alez-Rom´a V, Bakker AB. The measurement of engagement and burnout: a two sample confirmatory factor analytic approach. J Happiness Stud. 2002;3:71–92. 3. Schaufeli WB, Bakker AB. UWES–Utrecht Work Engagement Scale: Test Manual. Department of Psychology, Utrecht University; 2003. 4. Kessler RC, Akiskal HS, Ames M, et al. Prevalence and effects of mood disorders on work performance in a nationally representative sample of U.S. workers. Am J Psychiatry. 2006;163:1561–1568. 5. Wang PS, Simon GE, Avorn J, et al. Telephone screening, outreach, and care management for depressed workers and impact on clinical and work productivity outcomes: a randomized controlled trial. J Am Med Assoc. 2007;298:1401– 1411. 6. Strijk JE, Proper KI, van Mechelen W, van der Beek AJ. Effectiveness of a worksite lifestyle intervention on vitality, work engagement, productivity, and sick leave: results of a randomized controlled trial. Scand J Work Environ Health. 2013;39:66–75. 7. van Berkel J, Boot CR, Proper KI, Bongers PM, van der Beek AJ. Effectiveness of a worksite mindfulness-related multi-component health promotion intervention on work engagement and mental health: results of a randomized controlled trial. PLoS One. 2014;9:e84118. 8. Hengel KMO, Blatter BM, Joling CI, van der Beek AJ, Bongers PM. Effectiveness of an intervention at construction worksites on work engagement, social support, physical workload, and need for recovery: results from a cluster randomized controlled trial. BMC Public Health. 2012;12:1008.
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9. Vuori J, Toppinen-Tanner S, Mutanen P. Effects of resource-building group intervention on career management and mental health in work organizations: randomized controlled field trial. J Appl Psychol. 2012;97:273– 286. 10. Coffeng JK, Hendriksen IJ, Duijts SF, Twisk JW, van Mechelen W, Boot CR. Effectiveness of a combined social and physical environmental intervention on presenteeism, absenteeism, work performance, and work engagement in office employees. J Occup Environ Med. 2014;56:258–265. 11. Aikens KA, Astin J, Pelletier KR, et al. Mindfulness goes to work: impact of an online workplace intervention. J Occup Environ Med. 2014;56:721– 731. 12. Beck AT. Depression: Clinical, Experimental, and Theoretical Aspects. New York: Hoeber Medical Division; 1967. 13. Beck AT. Cognitive Therapy of Depression. New York: Guilford Press; 1979. 14. Richardson KM, Rothstein HR. Effects of occupational stress management intervention programs: a meta-analysis. J Occup Health Psychol. 2008;13: 69–93. 15. van der Klink JJ, Blonk RW, Schene AH, van Dijk FJ. The benefits of interventions for work-related stress. Am J Public Health. 2001;91:270–276. 16. Bond FW, Bunce D. Mediators of change in emotion-focused and problemfocused worksite stress management interventions. J Occup Health Psychol. 2000;5:156–163. 17. Mackenzie CS, Poulin PA, Seidman-Carlson R. A brief mindfulness-based stress reduction intervention for nurses and nurse aides. Appl Nurs Res. 2006;19:105–109. 18. Atlantis E, Chow CM, Kirby A, Singh MF. An effective exercise-based intervention for improving mental health and quality of life measures: a randomized controlled trial. Prev Med. 2004;39:424–434. 19. Umanodan R, Kobayashi Y, Nakamura M, Kitaoka-Higashiguchi K, Kawakami N, Shimazu A. Effects of a worksite stress management training program with six short-hour sessions: a controlled trial among Japanese employees. J Occup Health. 2009;51:294–302. 20. Higgins NC. Occupational stress and working women: the effectiveness of two stress reduction programs. J Vocat Behav. 1986;29:66–78. 21. Bee PE, Bower P, Gilbody S, Lovell K. Improving health and productivity of depressed workers: a pilot randomized controlled trial of telephone cognitive behavioral therapy delivery in workplace settings. Gen Hosp Psychiatry. 2010;32:337–340. 22. Furukawa TA, Horikoshi M, Kawakami N, et al. Telephone cognitivebehavioral therapy for subthreshold depression and presenteeism in workplace: a randomized controlled trial. PLoS One. 2012;7:e35330. 23. Gega L, Marks I, Mataix-Cols D. Computer-aided CBT self-help for anxiety and depressive disorders: experience of a London clinic and future directions. J Clin Psychol. 2004;60:147–157. 24. Spek V, Cuijpers P, Nyklicek I, Riper H, Keyzer J, Pop V. Internet-based cognitive behaviour therapy for symptoms of depression and anxiety: a metaanalysis. Psychol Med. 2007;37:319–328. 25. Imamura K, Kawakami N, Furukawa TA, et al. Effects of an Internet-Based Cognitive Behavioral Therapy (iCBT) Program in Manga Format on Improving Subthreshold Depressive Symptoms among Healthy Workers: A Randomized Controlled Trial. PLoS One. 2014;9:e97167. 26. Titov N, Andrews G, Sachdev P. Computer-delivered cognitive behavioural therapy: effective and getting ready for dissemination. F1000 Med Rep. 2010;2:49. 27. Andrews G, Cuijpers P, Craske MG, McEvoy P, Titov N. Computer therapy for the anxiety and depressive disorders is effective, acceptable and practical health care: a meta-analysis. PLoS One. 2010;5:e13196. 28. Andersson G, Cuijpers P. Internet-based and other computerized psychological treatments for adult depression: a meta-analysis. Cogn Behav Ther. 2009;38:196–205. 29. Peters L, Clark D, Carroll F. Are computerized interviews equivalent to human interviewers? CIDI-Auto versus CIDI in anxiety and depressive disorders. Psychol Med. 1998;28:893–901. 30. Shimazu A, Schaufeli WB, Kosugi S, et al. Work engagement in Japan: validation of the Japanese version of the Utrecht Work Engagement Scale. Appl Psychol. 2008;57:510–523. 31. Kessler RC, Barber C, Beck A, et al. The world health organization health and work performance questionnaire (HPQ). J Occup Environ Med. 2003;45:156– 174. 32. Beck AT, Steer RA, Brown GK. BDI-II, Beck Depression Inventory: Manual. San Antonio, Texas, Boston: Psychological Corp; Harcourt Brace; 1996. 33. Hiroe T, Kojima M, Yamamoto I, et al. Gradations of clinical severity and sensitivity to change assessed with the Beck Depression Inventory-II
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39. Schaufeli WB, Shimazu A, Taris TW. Being driven to work excessively hard the evaluation of a two-factor measure of workaholism in the Netherlands and Japan. Cross Cult Res. 2009;43:320–348. 40. Kawakami N, Haratani T. Epidemiology of job stress and health in Japan: review of current evidence and future direction. Ind Health. 1999;37: 174–186. 41. van Ballegooijen W, Cuijpers P, van Straten A, et al. Adherence to Internetbased and face-to-face cognitive behavioural therapy for depression: a metaanalysis. PLoS One. 2014;9:e100674. 42. Kaltenthaler E, Sutcliffe P, Parry G, Beverley C, Rees A, Ferriter M. The acceptability to patients of computerized cognitive behaviour therapy for depression: a systematic review. Psychol Med. 2008;38:1521–1530. 43. Wantland DJ, Portillo CJ, Holzemer WL, Slaughter R, McGhee EM. The effectiveness of web-based vs. non-web-based interventions: a meta-analysis of behavioral change outcomes. J Med Internet Res. 2004;6:e40.
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Effects of an Internet-Based Cognitive Behavioral Therapy Intervention on Improving Work Engagement and Other Work-Related Outcomes An Analysis of Secondary Outcomes of a Randomized Controlled Trial Kotaro Imamura, PhD, Norito Kawakami, MD, Toshi A. Furukawa, MD, Yutaka Matsuyama, PhD, Akihito Shimazu, PhD, Rino Umanodan, PhD, Sonoko Kawakami, MS, and Kiyoto Kasai, MD
Objective: This study reported a randomized controlled trial of the effectiveness of an Internet-based cognitive behavioral therapy (iCBT) program on work engagement and secondary work-related outcomes. Methods: ParFrom the Department of Mental Health (Dr Imamura, Dr Kawakami, and Dr Shimazu), Department of Biostatistics (Dr Matsuyama), and Department of Neuropsychiatry (Dr Kasai), Graduate School of Medicine, The University of Tokyo; Departments of Health Promotion and Human Behavior and of Clinical Epidemiology (Dr Furukawa), Graduate School of Medicine/School of Public Health, Kyoto University; Kyoto Office (Dr Umanodan), Health Wave Co, Ltd; and Nippon University College of the Arts (Ms Kawakami), Tokyo, Japan. This study was supported by the Grant-in-Aid for Scientific Research (A) 2009 and 2010 (No. 20240062) and the Grant-in-Aid for Young Scientists (B) 2014 (No. 26860433) from the Japan Society for the Promotion of Science. The sponsor of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The authors had access to the data in the study and the final responsibility to submit the paper. Dr Imamura is employed part-time by Chugai Pharmaceutical Company and Medical Care Toranomon as a clinical psychologist. Dr Kawakami has received honoraria for speaking at CME meetings sponsored by GlaxoSmithKline, Eizai, and Pfizer. He is on the advisory board for Sekisui Chemicals and Junpukai Health Care Center. He has received royalties from Chuo-Hoki-Shuppan, Igaku-Shoin, Kyobun-do, Life Science, Maruzen, Nanko-do, Nanzan-do, and Fujitsu Software Technologies, Ltd, and research grants from Fujitsu Software Technologies, Ltd, Softbank, Co, Ltd, and Japan Management Association. Dr Furukawa has received lecture fees from Eli Lilly, Meiji, Mochida, MSD, Pfizer, and Tanabe-Mitsubishi, and consultancy fees from Sekisui and Takeda Science Foundation. He is diplomate of the Academy of Cognitive Therapy. He has received royalties from Igaku-Shoin, Seiwa-Shoten, and Nihon Bunka Kagaku-sha. The Japanese Ministry of Education, Science, and Technology, the Japanese Ministry of Health, Labor and Welfare, and the Japan Foundation for Neuroscience and Mental Health have funded his research projects. Dr Matsuyama has received lecture fees from the Union of Japanese Scientists and Engineers, EPS Co, Ltd, and Statcom Co, Ltd, and consultancy fees from Zeria Pharmaceutical Co, Ltd, Ono Pharmaceutical Co, Ltd, and Mebix Co, Ltd. He has received royalties from Igaku-Shoin and Ewanami-Shoten. Dr Shimazu works for Hitachi Systems, Ltd, as a part-time consultant. He is on the advisory board for Junpukai Health Care Center and Ds’s Mental Health Labo. He has received royalties from Baifukan, Kawashima-shoten, Seishin-shobou, and Seiwa-Shoten. Dr Umanodan is employed by Health Wave Co, Ltd, as a clinical psychologist. Ms Kawakami is employed by Square-Enix Co, Ltd, as a contract employee. She also worked part-time for Dice Creative, Co, Ltd. Dr Kasai has received lecture fees from Astellas, Novartis, Eli Lilly, Otsuka, Dainippon-Sumitomo, and Yoshitomi Pharmaceutical Companies. He has received collaborative research grants from Astellas, Hitachi Co, and Hitachi Medical, and research grants from Yoshitomi, Dainippon-Sumitomo, Astellas, and GSK. Drs Imamura and Kawakami conceived of the study, developed study design, conducted literature search, collected, analyzed, and interpreted data, and prepared the first draft. Drs Furukawa, Matsuyama, Shimazu, and Kasai developed study design and interpreted data. Dr Umanodan and Ms Kawakami provided technical support. All authors reviewed the manuscript. The authors declare no conflicts of interest. Address correspondence to: Norito Kawakami, PhD, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-0033, Japan ([email protected]). C 2015 by American College of Occupational and Environmental Copyright Medicine DOI: 10.1097/JOM.0000000000000411
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ticipants who fulfilled the inclusion criteria were randomly allocated to an intervention or a control group (N = 381 for each). A 6-week, 6-lesson iCBT program using a Manga (Japanese comic) story was provided only to the intervention group. Work engagement was assessed at baseline and at 3- and 6-month follow-ups for both groups. Results: The iCBT program showed a significant intervention effect on work engagement (P = 0.04) with small effect sizes (Cohen’s d = 0.16 at 6-month follow-up). Conclusions: The study showed computerized cognitive behavior therapy delivered via the Internet to be effective (with a small effect size) in increasing work engagement in the general working population. Trial Registration: UMIN Clinical Trials Registry (UMIN-CTR) UMIN000006210.
R
ecently, occupational health research has focused on positive health outcomes, while mortality, mobility, and other illhealth indicators are still important.1 One outcome is work engagement, which is a positive, fulfilling, work-related state of mind and measured with three dimensions: vigor, dedication, and absorption.2,3 The other outcome, closely related to work engagement, is work performance, which includes both sick leave and onthe-job performance.4,5 There is increasing research to develop interventions to improve work engagement. We searched the literature using databases including PubMed, PsycINFO, and PsycARTICLES, and found six previous randomized controlled trials (RCTs) on this topic,6–11 which were all published since 2012. Nevertheless, four of the six RCTs, which included lifestyle change programs such as a physical fitness, failed to show a significant improvement in work engagement6,8 ; one focused on mindfulness-based intervention7 and another on career management skill workshops.9 Another RCT reported a significant, but small effect only for changing the physical environment (eg, creating a coffee corner) on the absorption subscale of work engagement.10 The last RCT found a significant effect of an online mindfulness-based intervention on Shirom’s vigor scale score among workers immediately after the intervention,11 but the effect at a longer follow-up was not assessed with an RCT design, and thus is unclear. A more effective intervention to improve work engagement needs to be developed and tested. Cognitive behavioral therapy (CBT)12,13 has been applied extensively to stress management interventions in workplace settings, and previous findings have revealed its effectiveness of improving work-related stress and negative emotions such as depression and anxiety among workers.14,15 In addition, a limited number of studies have reported that CBT-based intervention programs are effective in improving positive mental health at work, by such measures as job satisfaction16,17 and vitality,18 which— while similar—are not exactly the same as work engagement. Work engagement is considered a persistent and pervasive affective cognitive state.2,3 Thus, a CBT-based intervention may also be effective in improving work engagement. Nevertheless, no study has investigated the effects of a CBT-based intervention on improving work engagement. JOEM r Volume 57, Number 5, May 2015
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A previous controlled trial reported a significant effect of CBT-based stress management interventions in improving work performance among workers.19 One study included in a metaanalysis15,20 reported a nonsignificant and small (−0.18 in Cohen’s d) effect of CBT on improving absenteeism (ie, sick leave days) among workers. Nevertheless, two other RCTs failed to show a significant effect of improving work performance or absenteeism by applying telephone CBT-based interventions among depressed workers.21,22 A larger-scale RCT is needed to examine whether a CBT intervention could improve work performance, specifically regarding on-the-job work performance and absenteeism. Computerized CBT delivered via the Internet (iCBT) holds promise as a cost-effective method to make CBT accessible to more workers.23–25 The iCBT program provides basic information and skills on the basis of the same CBT principles as face-to-face CBT programs, with a highly structured format that comprises educational lessons, homework assignments, and supplementary resources.26 Although most studies of iCBT programs have focused on the treatment of patients with depression and anxiety disorders in clinical settings, showing favorable effects,27 the effects of iCBT programs on improving subthreshold depression have also been documented among healthy workers.25 Nevertheless, no previous study has investigated the beneficial effects of an iCBT program on improving work engagement and work performance among workers. The effects of iCBT have been shown to vary depending on the extent of therapist involvement. A previous meta-analysis of treatment studies reported that the effect size of iCBT programs with therapist support was greater than that of self-guided programs without therapist support, about 0.6 and 0.25, respectively, in Cohen’s d.24,28 Even so, self-guided programs may still have merit because of their greater accessibility and much lower cost.26 The purpose of this study was to examine the effects of an iCBT program on improving work engagement and work performance in the general working population. We analyzed data of these work-related outcomes, which were collected as secondary outcomes at 3- and 6-month follow-ups in an RCT that primarily targeted improving subthreshold depressive symptoms among the nonclinical general working population in Japan.25 We also tested whether the effect of the intervention on work-related outcomes was partly mediated by improvement of depression, the primary outcome of the study.
METHOD Trial Design Data for this study were collected as secondary outcomes of an RCT primarily examining the effects of an Internet-based CBT intervention on improving subthreshold depressive symptoms among healthy workers.25 The original trial was registered at the UMIN Clinical Trials Registry (UMIN-CTR; ID = UMIN000006210).
Participants Participants were recruited from employees of two information technology companies. All workers in one company (N = 290) and workers in three departments of another company (N = 1500) were invited by e-mail to participate in the study in September and October 2011. The inclusion criteria at the baseline survey were (1) aged 20 to 60 years at the study entry, (2) males and females, (3) currently employed full-time by the business company, and (4) having access to the Internet via a PC at home or at the workplace. The exclusion criteria were (1) having a major depressive disorder in the past month (using diagnostic criteria on the web version of the WHO-CIDI 3.029 ), (2) having lifetime bipolar disorder (WHO-CIDI 3.0), (3) having sick leave days of 15 days or more in total because of own health problems during the past 3 months, and (4) receiving medical treatment for mental health problems during the past month.
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Randomization Participants who fulfilled the inclusion criteria were randomly allocated to an intervention (N = 381) or a control group (N = 381) (see Imamura et al., 2014, for more detail.25 ). An independent biostatistician created a permuted-block random table. A clinical research coordinator conducted enrollment, and an independent research assistant conducted assignment. The permuted-block random table was password-protected and blinded to the researcher. Only the research assistant had access to the table during the work of random allocation.
Intervention Participants in the intervention group were provided access to the iCBT program.25 Briefly, the program provided a 6-week webbased training course consisting of weekly 30-minute training sessions in CBT-based stress management skills. The CBT components of the program included self-monitoring (in lesson 2), cognitive restructuring (in lesson 3), cognitive restructuring and relaxation (in lesson 4), assertiveness (in lesson 5), and problem solving (in lesson 6). At the end of each lesson, participants were asked to submit homework to facilitate their learning, although it was voluntary. Participants who submitted their homework received feedback from trained clinical psychologists. Five trained clinical psychologists provided feedback on the submitted homework just one time per lesson, on a first-come first-served basis. A particular clinical psychologist was not always assigned to a particular participant.
Intervention and Control Group Conditions Participants in the intervention group were encouraged to complete six weekly lessons and submit homework from the iCBT program within 10 weeks after the baseline survey. Participants were reminded by email to complete a lesson and/or to submit a homework assignment if they had not done so. Participants in the control group received a short email message of non-CBT stress management tips.25 Participants in the intervention and control groups were also able to use an internal employee assistance program service. All employees (both intervention and control groups) of Company B were provided another one-session e-learning program for stress management during the study. A possible contamination of information learnt by the intervention group participants to the control group participants was not assessed.
Outcome Measures All outcomes including work-related outcomes and depression as a mediator were measured using a web-based selfreport questionnaire at baseline, 3-month follow-up, and 6-month follow-up.
Work Engagement Work engagement was assessed using the short form of the Japanese version of the Utrecht Work Engagement Scale (UWES).30 The UWES consists of three subscales comprising nine items (ie, vigor, dedication, and absorption). Items are scored on a seven-point scale ranging from zero (never) to six (always). Item examples are “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 from all nine items.
Work Performance Work performance was assessed using one item from the WHO Health and Work Performance Questionnaire (HPQ).31 Respondents were asked to rate their overall work performance during the past 4 weeks. The item was scored on an 11-point scale ranging from 0 (worst possible performance) to 10 (best possible performance). High scores indicated a high degree of perceived work performance.
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Sick Leave Days During the Past 3 Months Respondents were asked to report the number of sick leave days during the past 3 months.
Depression as a Mediator As a mediator for the intervention effect on work-related outcomes, depression was measured by using the Beck Depression Inventory II (BDI-II), a 21-item self-report inventory.32,33 A higher total score indicates serious depressive symptoms.
Demographic Characteristics Demographic data such as age, sex, marital status, occupation, education, and chronic disease were also collected at baseline.
Statistical Power Calculation A minimum sample size of 336 in each group was determined to detect an effect size of 0.30 or greater for depressive symptoms, at an alpha error rate of 0.05 (two-tailed) and a beta error rate of 0.10, with an expected dropout rate of 30%. No previous study reported an effect size for any type of intervention for work engagement. An estimated post hoc power (1-beta) was 1.00 if the effect size was medium (0.5) and 0.75 if the effect size was small (0.2), assuming that alpha was less than 0.05 (two-tailed), and 70% of the initial 381 respondents in each group completed the follow-up using the G*Power 3 program.34,35
Statistical Analyses As a primary analysis, a mixed model for repeated measures conditional growth model analysis was conducted using a group (intervention and control) × time (baseline, 3-month, and 6-month follow-up) interaction as an indicator of intervention effect. Intention-to-treat analysis was conducted. The linear mixed model in PASW Statistics 18.0 (SPSS Inc, Chicago, IL) was used. As a sensitivity analysis, a mixed model for repeated measures analysis of variance model analysis was conducted. Also, the effect sizes and the 95% confidence intervals (95% CIs) were calculated using Cohen’s d only among those who completed the questionnaire at baseline and at follow-up, although the effect sizes may be more biased because of dropping out. The values of 0.2, 0.5, and 0.8 are generally interpreted as being suggestive of small, medium, and large effects, respectively.36 A mediation analysis was conducted on the effect of the intervention (X, coded as 1 = intervention and 0 = control) on a change of each outcome variable (Y, for work engagement score, sick leave days, or HPQ score), with using a change of the BDI-II score as a mediator (M). The analysis was done separately for 3- and 6-month follow-ups, among respondents who completed each follow-up. A direct effect was estimated as a unique effect of X on Y adjusting for M; an indirect effect was estimated as a product of correlation coefficients of X on M and of M on Y. The direct and indirect effects were directly tested by using a mediation analysis method with an SPSS macro.37
FIGURE 1. Participant flowchart.
RESULTS Participant Flowchart The participant flowchart is shown in Fig. 1. A total of 850 (47.5%) workers in the target workplaces completed a baseline survey. Of those, 88 were excluded because they did not fulfill the criteria. The remaining 762 participants were randomly allocated to an intervention or a control group (N = 381 for each). At 3-month follow-up, 270 (70.9%) participants in the intervention group and 336 (88.2%) in the control group completed the follow-up survey. At 6-month follow-up, 272 (71.4%) participants in the intervention group and 320 (84.0%) in the control group completed the follow-up survey. Reasons for dropping out were not assessed in this study. For the process evaluation, 247 (64.8%) participants of the intervention group completed all six lessons, whereas 93 (24.4%) of them submitted all six homework assignments. The participants’ transferral between the groups did not occur.
Ethics
Baseline Characteristics
The Research Ethics Review Board of the University of Tokyo, Graduate School of Medicine (No. 3083), approved the study procedures. Before the baseline survey, participants were invited to read the explanation on the Web site, and asked to click an “agree” button to show their consent to participate in the study; then they proceeded to the baseline questionnaire page. Written consent was not required by the National Ethical Guidelines for Epidemiologic Research, Japan; the Research Ethics Review Board of Graduate School of Medicine, the University of Tokyo, approved this procedure to obtain participants’ consent.
Demographic characteristics are presented in Table 1. No significant differences existed in the demographic characteristics between the intervention and control groups. In both groups, most participants were males, professionals, and received university or higher education, and did not have any chronic disease. Among the total sample at baseline (n = 762), the BDI-II depression score moderately and negatively correlated with work engagement (Spearman’s r = −0.42, P < 0.01) and work performance (r = −0.37, P < 0.01), and weakly and positively with sick leave days (r = 0.18; P < 0.01). Although work engagement and work performance positively
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TABLE 1. Baseline Characteristics of Participants in the Intervention and Control Groups Intervention Group (N = 381) n (%) Age, yrs 18–34 35–44 45–60 Sex (male) Marital status (currently married) Occupation Manager Professional Clerical/sales Production Others Education High school Some collage University or higher Chronic disease (yes) Depressive symptoms (scored by BDI-II)
Mean (SD)
Control Group (N = 381) n (%)
Mean (SD)
P* 0.54
157 (41.2) 123 (32.3) 101 (26.5) 325 (85.3) 212 (55.6)
167 (43.8) 126 (33.1) 88 (23.1) 314 (82.4) 226 (59.3)
93 (24.4) 256 (67.2) 21 (5.5) 3 (0.8) 8 (2.1)
79 (20.7) 278 (73.0) 19 (5.0) 3 (0.8) 2 (0.5)
43 (11.3) 60 (15.7) 278 (73.0) 38 (10.0)
34 (8.9) 70 (18.4) 277 (53.7) 44 (11.5)
0.33 0.47 0.25
0.59
11.9 (8.0)
11.8 (8.0)
0.56 0.83
*t test or chi-square test. BDI-II, Beck Depression Inventory II; SD, standard deviation.
correlated (r = 0.34, P < 0.01), these two outcomes only weakly correlated with sick leave days (r = −0.07, P < 0.05; and r = −0.10, P = 0.01, respectively).
P = 0.95) and 0.06 (SE = 0.04, P = 0.09, 87% of the total effect), respectively. The direct and indirect effects at 6-month follow-up were −0.096 (SE = 0.14, P = 0.55) and 0.09 (SE = 0.48, P = 0.07, 1,009% of the total effect), respectively.
Effects of the iCBT Program on Work-Related Outcomes Table 2 shows the means and standard deviations of the outcome variables at baseline, 3-month, and 6-month follow-ups in the intervention and control groups. Table 3 shows the estimated effects of the iCBT program on the outcome variables on the basis of the mixed-model analyses. The iCBT program showed a significant effect on the UWES (t = 2.03, P = 0.04). Nevertheless, the effect sizes were small: 0.11 (95% CI, −0.05 to 0.27) at 3-month follow-up and 0.16 (95% CI, 0.0007 to 0.32) at 6-month follow-up. The program showed a marginally statistically significant effect on sick leave days during past 3 months (t = −1.84, P = 0.07). Again, the effect sizes were small: −0.16 (95% CI, −0.32 to 0.0003) at 3-month follow-up and −0.14 (95% CI, −0.30 to 0.02) at 6-month follow-up.
Mediation Analysis Among respondents who completed 3-month follow-up (n = 606), direct and indirect effects through the change in the BDI of the intervention on UWES scores at 3-month follow-up were 0.06 (standard error [SE] = 0.06, P = 0.34) and 0.03 (SE = 0.02, P < 0.10, explaining 31% of the total effect), respectively. Among respondents who completed 6-month follow-up (n = 592), the direct and indirect effects through the change in the BDI were 0.099 (SE = 0.07, P = 0.13) and 0.035 (SE = 0.02, P = 0.07, 26% of the total effect), respectively. For sick leave days, the direct and indirect effects at 3-month follow-up were −0.677 (SE = 0.35, P = 0.05) and −0.00 (SE = 0.03, P = 0.94, 0.3% of the total effect), respectively. The direct and indirect effects at 6-month follow-up were −0.643 (SE = 0.39, P = 0.10) and −0.04 (SE = 0.04, P = 0.35, 5% of the total effect), respectively. For the work performance score, the direct and indirect effects at 3-month follow-up were 0.01 (SE = 0.14,
DISCUSSION The present RCT examined the effects of a newly developed iCBT program to improve work engagement and work performance as the secondary outcomes at 3- and 6-month follow-ups among workers employed in private companies in Japan. The iCBT program showed a significant small intervention effect on work engagement at 6-month follow-up. The iCBT program also showed a marginally statistically significant intervention effect on sick leave days during the past 3 months. On the other hand, the iCBT program did not show a significant intervention effect on the HPQ. This study also found that a change of depression partly mediated the effect of the iCBT on work engagement but not for sick leave days. The iCBT program significantly increased work engagement, as measured by the UWES, among the intervention group, compared with the control group (P = 0.04), whereas the effect was small (0.07 per 6 months). The effect sizes were also small (0.11 to 0.16) and nonsignificant at 3-month follow-up, possibly because the estimates were only based on the responders to these surveys. To our knowledge, this is the first study that demonstrated a positive effect of an iCBT program on improving work engagement. Work engagement is theoretically considered to be affected by psychological resources such as self-efficacy, optimism, and positive perception regarding one’s job.38,39 A possibility is that improved depression by the iCBT program, as already shown in our previous report,25 might contribute to improvement of work engagement to some extent. In fact, in this study, a change in depression marginally significantly mediated the effect on work engagement, which explained 26% to 31% of the total effect. Nevertheless, the direct effect still remained explaining the majority of the total intervention effect, whereas it was not statistically significant, partly because of a lack of statistical
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TABLE 2. Means (SDs) of Outcome Variables at Baseline, 3-, and 6-Month Follow-Up in the Intervention and Control Groups for the Whole Sample Intervention
UWES HPQ Sick leave days during the past 3 mos
Control
Baseline (N = 381) Mean (SD)
3 mos (N = 270) Mean (SD)
6 mos (N = 272) Mean (SD)
Baseline (N = 381) Mean (SD)
3 mos (N = 336) Mean (SD)
6 mos (N = 320) Mean (SD)
2.4 (1.0) 5.4 (1.9) 0.9 (1.7)
2.4 (1.0) 5.4 (2.0) 1.3 (3.3)
2.5 (1.1) 5.6 (1.9) 1.4 (3.5)
2.6 (1.0) 5.4 (1.9) 0.7 (1.5)
2.4 (1.0) 5.2 (2.0) 1.9 (4.9)
2.5 (1.1) 5.5 (2.0) 1.9 (5.8)
HPQ, Health and Work Performance Questionnaire; SD, standard deviation; UWES, Utrecht Work Engagement Scale.
TABLE 3. Effect of the Internet-Based Computerized Cognitive Behavioral Therapy Program on Work-Related Outcome Variables for the Whole Sample Estimated Means (Standard Errors) Intervention UWES 3 mos* 2.4 (0.1) 6 mos* 2.5 (0.1) Pooled† HPQ 3 mos* 5.3 (0.1) 6 mos* 5.5 (0.1) Pooled† Sick leave days during the past 3 mos 3 mos* 1.3 (0.2) 6 mos* 1.4 (0.2) Pooled†
Control
Estimates of Fixed Effects (95% CI)
t
P
2.4 (0.1) 2.4 (0.1)
0.08 (−0.04 to 0.19) 0.14 (−0.02 to 0.29) 0.07 (0.002 to 0.13)
1.29 1.73 2.03
0.20 0.08 0.04
5.2 (0.1) 5.5 (0.1)
0.07 (−0.22 to 0.35) 0.01 (−0.34 to 0.36) 0.00 (−0.15 to 0.16)
0.47 0.04 0.04
0.64 0.97 0.97
1.9 (0.2) 1.9 (0.2)
− 0.71 (−1.42 to 0.003) − 0.63 (−1.41 to 0.15) − 0.32 (−0.66 to 0.02)
−1.95 −1.58 −1.84
0.05 0.11 0.07
*A mixed-model for repeated measures analysis of variance model analyses was conducted. †A mixed-model for repeated measures conditional growth model analyses was conducted. CI, confidence interval; HPQ, Health and Work Performance Questionnaire; UWES, Utrecht Work Engagement Scale.
power. The current iCBT program may enhance work engagement by other mechanisms, such as improving psychological resources, such as self-efficacy and positive perception. The iCBT program may be effective in improving work engagement among workers with the universal approach (ie, targeting the whole working population). Even though the effect size is small, the public health impact may be still meaningful, if the great accessibility and minimal cost of this kind of program are considered. A mechanism with which a CBT program could improve work engagement should be investigated further in a future study. Only a few previous studies investigated the effect of a CBT program on sick leave days among workers, and the results remain controversial.14,15 Although the result was only marginally statistically significant, this study added additional evidence for an effect of CBT programs on reducing sick leave days. A change of depression did not mediate the intervention effect; rather the iCBT showed a marginally significant direct effect on sick leave days. Non–moodimproving components of this iCBT program, such as assertiveness, problem-solving, and relaxation skills, may have been effective for improving sick leave. The iCBT program failed to improve on-thejob work performance as measured by the HPQ at 3- or 6-month follow-up. Previous telephone-based CBT interventions, which consisted of cognitive restructuring and behavioral activation, did not show such an effect on on-the-job work performance as measured by the HPQ.21,22 Nevertheless, a program combining cognitive restruc582
turing and problem-solving techniques showed a positive effect.19 Although the current program included a component for problemsolving techniques, enhancing this component may improve work performance. On the other hand, the intervention effect on work performance was almost mediated by a change of depression. The current program showed a significant but only small effect for improving depression (Cohen’s d: −0.15, at 6-month follow-up).25 A nonsignificant intervention effect on work performance may be attributable to the small effect size of this low-intensity program for improving depression.
Limitations This study has several limitations. First, participants were recruited from two IT companies in Japan. Computer software engineers and technicians are known as stressful occupations, and they have been reported to have schizotypal and avoidant personality traits.40 Most participants were males, professionals, and university graduates, and they had their own PCs in their offices or homes. Participants were also supposed to have experience using a PC and studying using online programs. Higher education levels may also help participants learn from the iCBT program. Therefore, generalization of the present findings to the working population is limited. Second, the rate of completing homework was low, although the completion rate of lessons was moderate and similar to the previous guided iCBT program.41 Only 93 participants submitted all
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JOEM r Volume 57, Number 5, May 2015
homework assignments, and the average number of homework assignments submitted was 2.7 per respondent, which may particularly weaken the findings. For the future implementation of this iCBT program, it is essential to keep or even increase the participants’ program completion rate by, for instance, an improvement of reminder messages or the use of mobile devises. Third, the dropout rates from the follow-up surveys in this study were 29.1% and 28.6% at 3- and 6-month follow-ups, respectively. In their systematic review, Kaltenthaler et al42 reported that the average computerized CBT dropout rates were 18% to 35%. Wantland et al43 reported that an average dropout rate was 21%. The dropout rates in this study were within these ranges. Nevertheless, dropouts may have caused an attrition bias, particularly if participants in the intervention group had higher levels of motivation and were more likely to complete the program. Fourth, there was the possibility that participants in the control group could have information about the iCBT program from participants in the intervention group at same workplace. Such a contamination is one of the major limitations. In addition, this study provided the participants in the control group with stress management tips by several e-mails. These may weaken the intervention effect. Fifth, all outcomes in this study were measured by self-report, which may be affected by participants’ perceptions or situational factors at work. A self-reported measure could be vulnerable to a cognitive bias. A future study should consider the use of objectively measured outcomes such as supervisor ratings or company records of sick leave and work performance of participants. A further RCT should be conducted to examine whether the iCBT program is effective in a larger sample of workers with diverse characteristics, particularly in terms of occupation and education.
CONCLUSIONS This study first demonstrated that a computerized cognitive behavior therapy delivered via the Internet was effective in increasing work engagement in the general working population. The effect was partly, but not fully, explained by a change of depression.
ACKNOWLEDGMENTS We appreciate the help of the following persons in completing this project: Takayuki Narumi, Jun Naoi, Keisuke Kito, Chinatsu Narumi, Fukiko Ueda, and Mizuho Yamagishi.
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