Original Research ARTICLE
Validation of the Japanese Version of the Multidimensional Measure of Family Supportive Supervisor Behaviors (FSSB-J)
- 1Department of Public Health, Kitasato University School of Medicine, Sagamihara, Japan
- 2Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States
- 3Division of Health Sciences and Nursing, Department of Gerontological Home-Care and Long-Term Care Nursing, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- 4Keio Research Institute at SFC, Keio University, Fujisawa, Japan
- 5Faculty of Policy Management, Keio University, Fujisawa, Japan
- 6Asia Pacific Centre for Work Health and Safety, University of South Australia, Adelaide, SA, Australia
Objective: The aim of the current study was to validate the Japanese version of the family supportive supervisor behaviors (FSSB-J) measure. FSSB is conceptualized as a multidimensional, superordinate construct constituted of four dimensions: emotional support, instrumental support, role modeling behaviors, and creative work–family management.
Methods: The Japanese translated and back-translated FSSB-J questionnaire was administered to 1,670 men and women aged 20–59 years who were registered with a Japanese online survey company in November 2017. Confirmatory factor analyses were performed to evaluate the factorial validity of the FSSB-J. Cross-time measurement invariance was tested using multi-group confirmatory factor analyses. Construct validity was assessed with the potential consequences of FSSB (e.g., work–family spillover, work engagement, intention to leave, job satisfaction, and psychological distress) and convergent validity was assessed using similar concepts (e.g., organizational justice and social support). Internal consistency and test–retest reliability were examined to evaluate the reliability of the four dimensions of the FSSB.
Results: A series of confirmatory factor analyses using the multiple-group method revealed that the four-factor model fitted the data best. The latent factor structure demonstrated configural, metric, and scalar invariance across time. Construct and convergent validity were generally in line with expectations. Cronbach’s α coefficient and test–retest reliability were sufficient for each of the four dimensions of the FSSB.
Conclusion: This study suggests that FSSB-J is an adequate measure of FSSB in the Japanese context.
In most contemporary developed countries, many households are financially supported by dual-earner couples, with approximately 60% of couples supporting families together (Organisation for Economic Co-operation and Development, 2011). With an increase in the proportion of dual-earner families, work and non-work demands are now more likely to conflict (Shimazu et al., 2010; Cabinet Office, 2018; French et al., 2018). For dual-earner families, it has become important to maintain an appropriate balance between work and family roles. Japan is unique in terms of its strong corporate culture, in which employees are judged by their willingness to spend extended hours face-to-face with co-workers, being required to attend endless successions of meetings, and expected to prioritize work over private life. These societal features make the implementation of work–family balance policies particularly challenging in Japan (Cabinet Office, 2018).
Work–family balance is particularly critical in Japan, where fertility rates have plummeted over the last several years to the lowest level of any country, contributing to rapid population decline (Japan Ministry of Health Labour and Welfare, 2017). Since previous studies have found that the promotion of work and family–life balance is associated with improved fertility rates, this may be an important point of intervention (Yamaguchi and Youm, 2012). As an attempt to combat this decline in birthrate, and, subsequently, the population, the Japanese government has recently promoted a reform of working styles known as “Work-style Reform.” This reform includes the introduction of legal caps on overtime hours, rules to establish the “equal work, equal pay” principle by improving working conditions for people with irregular employment status, and a new system that allows corporate employees to be paid based on their performance rather than on the number of hours spent in the workplace. The promotion of work and family–life balance is an important part of this proposed work-style reform (Japan Ministry of Health Labour and Welfare, 2017).
Work–family research has identified social support from supervisors as an important resource that can reduce the negative effects of work and family stressors (O’Driscoll et al., 2003). Moreover, the Japanese government has started the “iku boss” (i.e., educating the boss) system to re-educate managers about the need to support the work–family balance of their subordinates (Japan Ministry of Health Labour and Welfare, 2017). To help promote this change, specific measures for assessing supervisors’ behaviors in encouraging work–family balance among their subordinates are needed in Japan.
Family supportive supervisor behaviors (FSSB) are defined as behaviors exhibited by supervisors that are supportive of the family roles of employees (Hammer et al., 2009). FSSB was originally conceptualized as a multidimensional superordinate construct which is assessed with 14 items that construct the four dimensions; emotional support, instrumental support, role modeling behaviors, and creative work–family management. This measure has been shown to have sufficient construct, criterion-related, and incremental validity. It has been significantly associated with work–family conflict, work–family positive spillover, job satisfaction, and turnover intentions over and above measures of general supervisor support (Hammer et al., 2009). Furthermore, FSSB has been linked to a number of employee outcomes, including lower levels of turnover intentions and higher levels of job satisfaction (Hammer et al., 2011; Crain et al., 2014; Odle-Dusseau et al., 2016; Yragui et al., 2017). To investigate whether the application of FSSB in Japan is appropriate, the validation of a Japanese version of FSSB is a necessary first step.
Higher levels of supervisor support can benefit employees, and is related to higher levels of work–family positive spillover (Thompson et al., 1999). In addition, studies have found that supervisor support enhances employee job satisfaction (Steinhardt et al., 2003; Odle-Dusseau et al., 2016), and lessens turnover intentions (Nichols et al., 2016; Fukui et al., 2019) and psychological distress (Winnubst et al., 1982; Kawakami et al., 2005). Therefore, it was hypothesized that FSSB is positively associated with work–family positive spillover and job satisfaction, and negatively associated with turnover intentions, which would confirm the construct validity of the scale.
The Current Study
This study aimed to validate the Japanese version of the FSSB (FSSB-J) in a sample of Japanese employees. Specifically, the factorial and construct validity of this measure were examined, as well as its reliability (i.e., internal consistency and test–retest reliability). The development of the Japanese version of the FSSB scale was based on the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) (Mokkink et al., 2018).
Materials and Methods
Translation of the FSSB
Professor Leslie Hammer, the author of the original version of FSSB, approved the development of the FSSB-J. First, the English version of the FSSB was translated into Japanese by two of the authors of this study (HE and YK), then back-translated to English by one author of this study (HK) who was blinded to the original items and is proficient in both English and Japanese. The back-translated version was confirmed by Professor Leslie Hammer. The original English version was compared with the back-translated version of the FSSB and created a preliminary Japanese version after terminology corrections.
Study Design and Population
A series of online surveys was administered to men and women who were registered with a Japanese online survey company in December 2017. Of all workers who were registered with this online survey company, 1,670 married workers who were 20–59 years of age were selected and invited by e-mail to complete a web-based questionnaire in the order of arrival. The online survey company had access to more than 2,000,000 potential participants who showed interest in participating in surveys that provided fiscal incentives. The fiscal incentive for this survey was low, valued at several U.S. dollars. For financial reasons, recruitment stopped when the number of participants reached 1,670. The survey was repeated with the same respondents 1 month later because an interval between surveys of approximately 1 month is typically considered appropriate for the evaluation of instruments (Streiner et al., 2015). Respondents in the second survey were recruited from participants who completed the first survey on a first-come first-served basis. The recruitment procedure in the second survey was the same as the first survey. Recruitment ceased when the number of participants reached 1,000. There were no statistically significant differences in FSSB scores across the participant demographic characteristics between the first and second surveys (Table 1).
A total of 249 participants were excluded from the first survey and 135 were excluded from the second survey because they reported being self-employed or freelance workers. A further 43 participants who had at least one missing response on the questionnaire in the first survey were excluded, resulting in a final sample of 1,378 respondents for the first survey and 842 respondents for the second survey. COSMIN requires the researcher to evaluate the percentage of missing items because a high number of missing items can introduce bias in the study results. In the online survey, it was possible to restrict the participants from answering all questions. To evaluate bias, the restriction was removed only for FSSB items in the first survey. Since the online survey required participants to answer all questions except for the FSSB items in the first survey, no participants had missing data on the FSSB items in the second survey, or for the non-FSSB items in both surveys.
Family Supportive Supervisor Behavior
Family Supportive Supervisor Behavior was assessed with a preliminary Japanese version of the FSSB measure. The items of the FSSB measure are grouped into four subscales that reflect the underlying dimensions of FSSB: emotional support (five items), role modeling behaviors (three items), instrumental support (four items), and creative work–family management (six items). All items are scored on a five-point Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”). The total score of the subscales was used in the analyses with higher scores representing higher levels of the construct.
Procedural and Interactional Justice
Two aspects of organizational justice (i.e., procedural and interactional) were assessed using the Japanese version of the Organizational Justice Questionnaire (OJQ). This scale was developed by Moorman (1991) and modified by Elovainio et al. (2002). The scale comprises of a seven-item scale that measures procedural justice, and a six-item scale that measures interactional justice, both of which are rated on a five-point Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”). The total score for each OJQ subscale was calculated by averaging item scores (score range 1–5). The subscale scores are summed to calculate the total score, where higher scores indicate higher levels of organizational justice. This Japanese version has been shown to have sufficient reliability and validity (Inoue et al., 2009). In the present study sample, Cronbach’s α coefficients for the procedural and interactional justice scales were 0.88 and 0.94, respectively.
Source-Specific Workplace Social Support
To assess source-specific workplace social support, the New Brief Job Stress Questionnaire (New BJSQ) (Shimomitsu, 2000) was used. The New BJSQ includes a three-item supervisor and coworker support scale (response range: 3–12), with items such as “How freely can you talk with the supervisor/coworker?,” “How reliable is the supervisor/coworker when you are troubled?,” and “How well will the supervisor/coworker listen to you when you ask for advice on personal matters?” Participants responded to these statements on a four-point Likert scale ranging from 1 (“Extremely”) to 4 (“not at all”). The item scores are summed to calculate the total score. The higher scores indicate the greater levels of supervisor and co-worker support. The Cronbach’s α coefficient was 0.91 for supervisor support and 0.80 for co-worker support.
Work–Family Positive Spillover
Work–family positive spillover effects [work-to-family positive spillover (WFPS) and family-to-work positive spillover (FWPS)] were measured with 22 items using the Survey Work–Home Interaction–NijmeGen (SWING), which was developed in the Netherlands (Geurts et al., 2005). WFPS was measured with four items (e.g., “You manage your time at home more efficiently as a result of the way you do your job”) (response range: 0–12). FWPS was measured with four items (e.g., “After spending a pleasant weekend with your spouse/family/friends, you have more fun in your job”) (response range: 0–12). Items are scored on a four-point Likert scale, ranging from 0 (“never”) to 3 (“always”). The item scores are summed to calculate the total score, with higher scores indicating greater levels of WFPS and FWPS. The reliability and validity of the Japanese version of the scale has previously been shown to be sufficient (Shimada et al., 2019). The Cronbach’s α coefficients in the sample were 0.72 for WFPS and 0.81 for FWPS.
Work engagement was assessed using the short form of the Utrecht Work Engagement Scale (UWES) (Schaufeli et al., 2006). The UWES includes three subscales that reflect the underlying dimensions of engagement: vigor, dedication, and absorption (three items for each dimension). All items were scored on a 7-point Likert scale ranging from 0 (“never”) to 6 (“always”) (response range: 0–54). The item scores are summed to calculate the total score. Higher scores indicate greater levels of work engagement. A previous validation study of the Japanese version of the UWES recommended that work engagement should be treated as a unitary construct due to the high correlations among the three components (Shimazu et al., 2008). In the sample, Cronbach’s α coefficient was 0.93 for the UWES.
Intention to Leave
Intention to leave was measured with a three-item scale used by Geurts et al. (1998). Respondents used a five-point Likert scale ranging from 1 (“I agree completely”) to 5 (“I disagree completely”) to rate the extent to which they have the intention to leave their current employment in the following month (response range: 3–15). The item scores are summed to calculate the total score. Higher scores indicate greater levels of intention to leave. The internal consistency reliability of this measure was found to be good in the sample (α = 0.85).
Job satisfaction was measured using the subscales of the New BJSQ (Inoue et al., 2014). Job satisfaction, which was a single item measure, was classified into four categories; 1 = dissatisfied, 2 = somewhat dissatisfied, 3 = relatively satisfied, or 4 = satisfied.
The K6 scale was developed by Kessler et al. (2002). The scale consists of six items that measure the extent of psychological distress using a five-point response option 0 (“none of the time”) to 4 (“all of the time”). The Japanese version of the K6 scale has been shown to have sufficient reliability and validity (Furukawa et al., 2008). The item scores are summed to calculate the total score. Higher scores indicate greater levels of psychological distress. In the current study, the Cronbach’s α coefficient for the K6 scale was 0.88.
Sociodemographic factors included sex, age range (i.e., 20–29, 30–39, 40–49, and 50–59 years), educational attainment (junior high school, high school, junior college/technical school, university, graduate school, and others), having children (yes, no), occupation (professional and technical job, managerial job, clerical job, sales job, service job, manufacturing job, security job, agriculture, forestry or fishery job, transportation and communication job, others), employment contract (regular or part-time), and weekly working hours (≤19, 20–39, 40–59, 60–79, ≥80).
COnsensus-based Standards for the selection of health Measurement INstruments suggests that hypothesis testing should be used when a gold standard of a construct is not available (Mokkink et al., 2018) and FSSB is theoretically related to other psychosocial factors in the workplace (Hammer et al., 2009). Based on previous studies (Hammer et al., 2009), it was hypothesized that FSSB is negatively correlated with intention to leave and psychological distress, and positively correlated with procedural justice, interactional justice, supervisor support, coworker support, work–family positive spillover, family–work positive spillover, work engagement, and job satisfaction.
Classical test theory was used to measure FSSB. Mean values and standard deviations were calculated for each item of the FSSB scale. Item-total Spearman’s correlations were examined. CFA using maximum-likelihood estimation was conducted with AMOS (Chicago, IL, United States). The hypothesized four-factor model (Model 2) was used with a one-factor model (Model 1), whereby all items were loaded on one general FSSB factor. Moreover, to consider gender differences in the model, model testing was carried out in male and female samples simultaneously using the multiple-group method (Model 3 for the one-factor model and Model 4 for the four-factor model). Model fit was assessed using a combination of fit indices including the goodness of fit index (GFI), parsimony goodness of fit index (PGFI), non-normed fit index (NNFI), the comparative fit index (CFI), parsimony normed fit index (PNFI), and the root mean square error of approximation (RMSEA). The acceptability of model fit was judged by the following criteria; GFI, PGFI, NNFI, CFI, and PNFI of >0.90 and RMSEA of <0.08 (Hooper et al., 2008).
The survey was repeated after 1 month using the same FSSB scale on 1,000 of the 1,670 respondents who completed the first survey to assess the replicability of the FSSB with the test–retest method. To evaluate the cross-time measurement invariance, configural, metric, and scalar invariance were evaluated in three steps. First, configural invariance was tested using a two-level (i.e., first and second survey) CFA in which all parameters were estimated freely, except for the highest loading items for each factor, which were set to 1.0, while the factor means were set to 0. Second, metric invariance was tested by constraining all factor loadings to be equal for the two levels. Factor variances were set to 1.0 to identify the model. Third, scalar invariance was tested by constraining all subscale and item intercepts to be equal for the two levels. Model fit was assessed using a combination of fit indices including the Tucker–Lewis index (TLI), the CFI, and the RMSEA. The overall scale reliability was quantified by both an intraclass correlation coefficient (ICC) (2,1) based on a single measurement two-way random effects model of absolute agreement and the standard error of measurement (SEM). ICC (2,1) was red in compliance with published recommendations; an ICC (2,1) of 0.90 or higher was considered excellent, 0.75 or higher was considered good, 0.50 or higher was considered moderate, and lower than 0.50 was considered poor (Shrout and Fleiss, 1979). At least 301 participants were deemed to be necessary to detect an ICC (2,1) ≥ 0.50 (error α = 0.05 and β = 0.20) between the first and second survey (Walter et al., 1998). Previous studies indicate that this is a modest sample size (Terwee et al., 2012). Larger SEM represents lower test reliability and less precision in the measures and scores obtained (de Vet et al., 2006). Cronbach’s α coefficient was calculated to evaluate internal consistency and Pearson’s correlation coefficients were calculated to evaluate construct validity and convergent validity. All analyses were conducted in Stata 15 (College Station, TX, United States) and AMOS Version 25 for Windows (Chicago, IL, United States).
This study was approved by the Ethics Committee of the Graduate School of Medicine and Faculty of Medicine at The University of Tokyo [11666-(1)].
The majority of the sample at baseline was male (70.0%), had more than high school education (69.7%), had children (78.4%), had regular employment status (78.5%), and worked >40 h per week (66.9%) (Table 1).
A confirmatory factor analysis was conducted. As shown in Table 2, the hypothesized four-factor model (Model 2: each item loads on a hypothesized factor) showed a significantly better fit to the data than the one-factor model (Model 1: all items measuring the four constructs load on one general FSSB factor). The fit indices of the four-factor model (Model 2) were GFI = 0.923, PGFI = 0.624, NNFI = 0.961, CFI = 0.964, PNFI = 0.750, and RMSEA = 0.083. The fit indices of the four-factor model using a multiple-group model (Model 4) were GFI = 0.918, PGFI = 0.621, NNFI = 0.957, CFI = 0.964, PNFI = 0.747, and RMSEA = 0.059. A formal χ2 difference test revealed that the difference between the two models was not significant [Δχ2(71) = 73.265, p > 0.05]. These results suggest that factor loadings were indeed invariant between males and females.
Table 2. Results of confirmatory factor analyses: comparison of goodness-of-fit indices among one-factor models and four-factor models.
Construct validity was tested by exploring the associations between the FSSB score and theoretically related constructs, including procedural justice, interactional justice, supervisor support, coworker support, WFPS, FWPS, work engagement, intention to leave, and psychological distress. Table 3 shows that FSSB scores were significantly positively correlated with procedural justice, interactional justice, supervisor support, coworker support, WFPS, FWPS, and work engagement, and negatively correlated with intention to leave and psychological distress (all p < 0.01).
Table 3. Association between family supportive supervisor behavior score and other constructs at baseline.
Table 4 shows the means, standard deviations, item-total correlations, and Cronbach’s α coefficients of the scale when each item was removed. The mean score for each item was between 2.5 and 3.1. Correlations between items varied from 0.52 to 0.85 (p < 0.01). The item-total correlations ranged from 0.75 to 0.87 (p < 0.01). The correlations between the FSSB scores of the first and second surveys indicated high test–retest reliability (r = 0.72, p < 0.01). Table 5 shows the results of configural, metric, scalar invariance across time. In line with criteria defined by Bentler and colleagues (CFI > 0.900, RMSEA < 0.080) (Bentler, 1990; Hu and Bentler, 1999), the latent factor structure appeared to demonstrate configural, metric, and scalar invariance across time. The ICC (2,1) and SEM for FSSB were 0.70 [95% confidence interval (CI): 0.66–0.73] and 2.58 (95% CI: 2.52–2.64). The mean time variation for the FSSB was 0.03 ± 0.005. The internal consistency of the whole scale with 14 items was excellent, with a Cronbach’s α coefficient of 0.93. Omission of any of the items did not substantially alter the internal reliability of the scale. Cronbach’s alpha values were 0.94 for emotional factors, 0.90 for instrument support, 0.92 for role model, and 0.91 for creative work–family management.
Table 5. Evaluation of measurem ent invariance: comparison of goodness-of-fit indices among configural invariance, metric invariance, and scalar invariance.
The current results revealed that the Japanese version of the FSSB has good reliability, construct validity, and convergent validity, as well as adequate structural validity. In accordance with the COSMIN model, acceptable levels of internal consistency reliability, convergent validity, and construct validity were found among Japanese men and women. However, the current study did not investigate cross-cultural validity, interpretability, or responsiveness.
A series of confirmatory factor analyses using the multi-group method revealed that the four-factor model (Model 4) fitted the data better than the one-factor model (Model 3). In addition, as some intervention studies have been implemented using the FSSB with four factors (Hammer et al., 2011, 2016; McHale et al., 2016), FSSB was treated as a four-factor model, in line with the original study of FSSB (Hammer et al., 2009). This feature of the present study facilitates comparability between the current results and previous research findings.
Family demands and work–life conflict differ according to social and cultural context (Annor and Burchell, 2018). In Asian cultures, females and males typically play substantially different family roles, and exhibit differences in family- and work-related values. In the Global Gender Gap Index in 2018, Asian countries typically ranked lower than western countries (World Economic Forum, 2018). Japanese women tend to bear the majority of the responsibility for child care and housekeeping, even when employed outside the home. Female workers spend an average of 208 min per day on child care and housekeeping, compared with 44 min per day for men (Statistics Bureau Japan Ministry of Internal affairs and Communications, 2017). Contrary to expectations, the four-factor structure was invariant between men and women in the current study; that is, the factor loading of the items on the underlying factors did not differ systematically between men and women. Future research should examine gender differences in the impact of FSSB in an international context.
To provide evidence of construct validity, FSSB-J scores were used as predictors of six important aspects of work–family constructs (i.e., work–family positive spillover, family–work positive spillover, work engagement, intention to leave, job satisfaction, and psychological distress). FSSB was significantly and negatively correlated with intention to leave and psychological distress, and positively correlated with procedural justice, interactional justice, supervisor support, coworker support, WFPS, FWPS, work engagement, and job satisfaction. These results are consistent with previous studies (Hammer et al., 2009, 2011; Crain et al., 2014). Thus, FSSB-J scores have significant construct and convergent validity with respect to all important variables.
The internal consistency values of each of the four dimensions were excellent (0.90 < α < 0.94). These values are comparable to or higher than those reported in the original study of the FSSB (0.74 < α < 0.90) (Hammer et al., 2009). Moreover, test–retest reliability was high and the latent factor structure of FSSB was relatively stable over time. Thus, the Japanese version of FSSB appears to have a level of reliability that is comparable to the original version.
Limitations and Future Directions
The present study involved several limitations. First, all measures used in this study were self-reported, which could be a source of bias. Common method variance may have affected the results, suggesting that the true associations between variables may be weaker than those observed in this study. Future studies could use objective measures (e.g., objective company records and other records that capture work–life balance) to further investigate this construct. Second, this study used a convenience sample of people registered with an online survey company, and so may not be a representative sample of the Japanese working population. This could be a concern, as the reliability and validity of scales have been reported to depend on the characteristics of the sample (Mokkink et al., 2018). Third, this study included only married workers and did not take into account the possibility that unmarried individuals may also have family needs and work–family conflicts. The generalizability of the results is unclear, because FSSB is highly dependent on the context of the organization. Finally, the sample was predominantly male (∼70% of the sample in both surveys), potentially limiting the generalizability of the current findings across genders.
The current study suggests that the FSSB-J adequately measures FSSB, and can be used effectively in the Japanese context. The introduction of this questionnaire in Japan should stimulate further research on work–life balance in Japan and also international research collaborations on work–life balance.
Data Availability Statement
The datasets generated for this study are available on request to the corresponding author.
The studies involving human participants were reviewed and approved by the Ethics Committee of the Graduate School of Medicine and Faculty of Medicine at The University of Tokyo [11666-(1)]. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.
HE contributed to the conception and design of the study, performed the statistical analysis, and wrote the first draft of the manuscript with support from YK, HK, MS, MT, and AS. MS and MT organized the database. YK contributed to translate into Japanese. HK contributed to the back translation. AS was involved in planning and supervised the work. All authors contributed to manuscript revision, and read and approved the submitted version of the manuscript.
This study was supported by the Grant-in-aid scientific research, Grant-in-Aid for Scientific Research (A), “Work–life balance and health among dual-earner couples with children: Program development and evaluation” (Research ID: 15H01832), Japan Society for the Promotion of Science.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We thank Benjamin Knight, MSc., from Edanz Group (www.edanzediting.com/ac) for editing a draft of this manuscript.
Annor, F., and Burchell, B. (2018). A cross-national comparative study of work demands/support, work-to-family conflict and job outcomes: Ghana versus the United Kingdom. Int. J. Cross Cult. Manag. 18, 53–72. doi: 10.1177/1470595817746195
Cabinet Office, (2018). White Paper on Children and Young People. Cabinet Office; 2018. Available from: https://www8.cao.go.jp/youth/english/policy_ 2018.html (accessed July 22, 2019).
Crain, T. L., Hammer, L. B., Bodner, T., Kossek, E. E., Moen, P., Lilienthal, R., et al. (2014). Work-family conflict, family-supportive supervisor behaviors (FSSB), and sleep outcomes. J. Occup. Health. Psychol. 19, 155–167. doi: 10.1037/a0036010
Fukui, S., Wu, W., and Salyers, M. P. (2019). Mediational paths from supervisor support to turnover intention and actual turnover among community mental health providers. Psychiatr. Rehabil. J. doi: 10.1037/prj0000362 [Epub ahead of print].
Furukawa, T. A., Kawakami, N., Saitoh, M., Ono, Y., Nakane, Y., Nakamura, Y., et al. (2008). The performance of the Japanese version of the K6 and K10 in the world mental health survey Japan. Int. J. Methods Psychiatr. Res. 17, 152–158. doi: 10.1002/mpr.257
Geurts, S., Schaufeli, W., and De Jonge, J. (1998). Burnout and intention to leave among mental health-care professionals: a social psychological approach. J. Soc. Clin. Psychol. 17, 341–362. doi: 10.1521/jscp.19184.108.40.2061
Geurts, S. A. E., Taris, T. W., Kompier, M. A. J., Dikkers, J. S. E., Van Hooff, M. L. M., and Kinnunen, U. M. (2005). Work-home interaction from a work psychological perspective: development and validation of a new questionnaire, the SWING. Work Stress 19, 319–339. doi: 10.1080/02678370500410208
Hammer, L. B., Johnson, R. C., Crain, T. L., Bodner, T., Kossek, E. E., Davis, K. D., et al. (2016). Intervention effects on safety compliance and citizenship behaviors: evidence from the work, family, and health study. J. Appl. Psychol. 101, 190–208. doi: 10.1037/apl0000047
Hammer, L. B., Kossek, E. E., Anger, W. K., Bodner, T., and Zimmerman, K. L. (2011). Clarifying work-family intervention processes: the roles of work-family conflict and family-supportive supervisor behaviors. J. Appl. Psycho. 96, 134–150. doi: 10.1037/a0020927
Hammer, L. B., Kossek, E. E., Yragui, N. L., Bodner, T. E., and Hanson, G. C. (2009). Development and validation of a multidimensional measure of family supportive supervisor behaviors (FSSB). J. Manag. 35, 837–856. doi: 10.1177/0149206308328510
Hu, L. T., and Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Modeling 6, 1–55. doi: 10.1080/10705519909540118
Inoue, A., Kawakami, N., Shimomitsu, T., Tsutsumi, A., Haratani, T., Yoshikawa, T., et al. (2014). Development of a short version of the new brief job stress questionnaire. Ind. Health 52, 535–540. doi: 10.2486/indhealth.2014-0114
Inoue, A., Kawakami, N., Tsutsumi, A., Shimazu, A., Tsuchiya, M., Ishizaki, M., et al. (2009). Reliability and validity of the Japanese version of the organizational justice questionnaire. J. Occup. Health. 51, 74–83. doi: 10.1539/joh.l8042
Kawakami, N., Kobayashi, Y., Takao, S., and Tsutsumi, A. (2005). Effects of web-based supervisor training on supervisor support and psychological distress among workers: a randomized controlled trial. Prev. Med. 41, 471–478. doi: 10.1016/j.ypmed.2005.01.001
Kessler, R. C., Andrews, G., Colpe, L. J., Hiripi, E., Mroczek, D. K., Normand, S. L., et al. (2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol. Med. 32, 959–976. doi: 10.1017/s0033291702006074
McHale, S. M., Davis, K. D., Green, K., Casper, L., Kan, M. L., Kelly, E. L., et al. (2016). Effects of a workplace intervention on parent-child relationships. J. Child Fam. Stud. 25, 553–561. doi: 10.1007/s10826-015-0254-z
Mokkink, L. B., de Vet, H. C. W., Prinsen, C. A. C., Patrick, D. L., Alonso, J., Bouter, L. M., et al. (2018). COSMIN risk of bias checklist for systematic reviews of patient-reported outcome measures. Qual. Life Res. 27, 1171–1179. doi: 10.1007/s11136-017-1765-4
Moorman, R. H. (1991). Relationship between organizational justice and organizational citizenship behaviors: do fairness perceptions influence employee citizenship? J. Appl. Psychol. 76, 845–855. doi: 10.1037/0021-9010.76.6.845
Nichols, H. M., Swanberg, J. E., and Bright, C. L. (2016). How does supervisor support influence turnover intent among frontline hospital workers? The mediating role of affective commitment. Health Care Manag. 35, 266–279. doi: 10.1097/hcm.0000000000000119
Odle-Dusseau, H. N., Hammer, L. B., Crain, T. L., and Bodner, T. E. (2016). The influence of family-supportive supervisor training on employee job performance and attitudes: an organizational work-family intervention. J. Occup. Health Psychol. 21, 296–308. doi: 10.1037/a0039961
O’Driscoll, M. P., Poelmans, S., Spector, P. E., Kalliath, T., Allen, T. D., Cooper, C. L., et al. (2003). Family-responsive interventions, perceived organizational and supervisor support, work-family conflict, and psychological strain. Int. J. Stress Manag. 10, 326–344. doi: 10.1037/1072-5245.10.4.326
Organisation for Economic Co-operation and Development, (2011). Doing Better for Families: OECD Publishing; 2011. Available from: http://www.oecd.org/social/soc/doingbetterforfamilies.htm (accessed July 22, 2019).
Schaufeli, W. B., Bakker, A. B., and Salanova, M. (2006). The measurement of work engagement with a short questionnaire: a cross-national study. Educ. Psychol. Meas. 66, 701–716. doi: 10.1177/0013164405282471
Shimada, K., Shimazu, A., Geurts, S. A. E., and Kawakami, N. (2019). Reliability and validity of the Japanese version of the survey work–home interaction – Nijmegen, the SWING (SWING-J). Community Work Fam. 22, 267–283. doi: 10.1080/13668803.2018.1471588
Shimazu, A., Bakker, A. B., Demerouti, E., and Peeters, M. C. (2010). Work-family conflict in Japan: how job and home demands affect psychological distress. Ind. Health. 48, 766–774. doi: 10.2486/indhealth.ms1131
Shimazu, A., Schaufeli, W. B., Kosugi, S., Suzuki, A., Nashiwa, H., Kato, A., et al. (2008). Work engagement in Japan: validation of the Japanese version of the utrecht work engagement scale. Appl. Psychol. 57, 510–523. doi: 10.1111/j.1464-0597.2008.00333.x
Shimomitsu, T. (2000). “The final development of the brief job stress questionnaire mainly used for assessment of the individuals,” in Ministry of Labour Sponsored Grant for the Prevention of Work-Related Illness: The 1999 Report, ed. M. Kato, (Tokyo: Tokyo Medical College).
Statistics Bureau Japan Ministry of Internal affairs and Communications, (2017). Survey on Time Use and Leisure Activities 2016. Available from: http://www.stat.go.jp/english/data/shakai/2016/gaiyo.html (accessed July 22, 2019).
Steinhardt, M. A., Dolbier, C. L., Gottlieb, N. H., and McCalister, K. T. (2003). The relationship between hardiness, supervisor support, group cohesion, and job stress as predictors of job satisfaction. Am. J. Health Promot. 17, 382–389. doi: 10.4278/0890-1171-17.6.382
Terwee, C. B., Mokkink, L. B., Knol, D. L., Ostelo, R. W. J. G., Bouter, L. M., and de Vet, H. C. W. (2012). Rating the methodological quality in systematic reviews of studies on measurement properties: a scoring system for the COSMIN checklist. Qual. Life Res. 21, 651–657. doi: 10.1007/s11136-011-9960-1
Thompson, C. A., Beauvais, L. L., and Lyness, K. S. (1999). When work-family benefits are not enough: the influence of work-family culture on benefit utilization, organizational attachment, and work-family conflict. J. Vocat. Behav. 54, 392–415. doi: 10.1006/jvbe.1998.1681
Walter, S. D., Eliasziw, M., and Donner, A. (1998). Sample size and optimal designs for reliability studies. Stat. Med. 17, 101–110. doi: 10.1002/(sici)1097-0258(19980115)17:1<101::aid-sim727>3.0.co;2-e
Winnubst, J. A. M., Marcelissen, F. H. G., and Kleber, R. J. (1982). Effects of social support in the stressor-strain relationship: a dutch sample. Soc. Sci. Med. 16, 475–482. doi: 10.1016/0277-9536(82)90056-9
World Economic Forum, (2018). The Global Gender Gap Report 2018. Available from: http://www3.weforum.org/docs/WEF_GGGR_2018.pdf (accessed July 22, 2019).
Yamaguchi, K., and Youm, Y. (2012). The Determinants of Low Marital Fertility in Korea: A Comparison With Japan. The Research Institute of Economy, Trade and Industry, Discussion Paper Series. 2012:1-21. Available from: https://www.rieti.go.jp/en/publications/summary/12030001.html (accessed July 22, 2019).
Yragui, N. L., Demsky, C. A., Hammer, L. B., Van Dyck, S., and Neradilek, M. B. (2017). Linking workplace aggression to employee well-being and work: the moderating role of family-supportive supervisor behaviors (FSSB). J. Bus. Psychol. 32, 179–196. doi: 10.1007/s10869-016-9443-z
Keywords: workplace, psychosocial factor, Japan, supervisor behavior, work–life balance, scale validation
Citation: Eguchi H, Kachi Y, Koga HK, Sakka M, Tokita M and Shimazu A (2019) Validation of the Japanese Version of the Multidimensional Measure of Family Supportive Supervisor Behaviors (FSSB-J). Front. Psychol. 10:2628. doi: 10.3389/fpsyg.2019.02628
Received: 22 July 2019; Accepted: 07 November 2019;
Published: 22 November 2019.
Edited by:Mengcheng Wang, Guangzhou University, China
Reviewed by:Ying Ling, Guangdong Industry Technical College, China
Lingyan Li, Nanchang University, China
Copyright © 2019 Eguchi, Kachi, Koga, Sakka, Tokita and Shimazu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Hisashi Eguchi, email@example.com