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Japanese version of the Brief Sense of Community Scale: construct validity and reliability

Abstract

Background

The Brief Sense of Community Scale is a widely accepted eight-item scale that measures the four dimensions of sense of community; however, the factor structure of the Japanese version of this scale has never been confirmed. In this study, we demonstrated the reliability and validity of the Japanese version of the Brief Sense of Community Scale.

Methods

After completing the back translation of the scale, a sample of 993 Japanese individuals completed the Japanese version of the Brief Sense of Community Scale.

Results

The results indicate that the Japanese version of the Brief Sense of Community Scale is comparable to the original scale and demonstrated adequate goodness-of-fit for both the four-factor and second-order models, which demonstrates its validity. Nonetheless, it remains necessary to consider possible cross-national cultural concerns when utilizing the scale.

Conclusions

The Japanese version of the Brief Sense of Community Scale will contribute toward the creation of a community in which all members feel comfortable.

Peer Review reports

Background

Sense of Community (SOC)—sometimes also called “psychological sense of community”— refers to “a feeling that members have of belonging, a feeling that members matter to one another and to the group, and a shared faith that members’ needs will be met through their commitment to be together” [1]. The concept of SOC has mainly evolved from the theoretical framework of McMillan and Chavis [1], which emphasizes the following four core dimensions of SOC: need fulfilment (a sense that members’ needs will be met by the resources received by their group membership); membership (a shared sense of personal relatedness or belonging to the community); influence (a sense of mattering to group members or community, such as by making a difference in the group); and emotional connection (a belief among members related to a shared history, place, time, and experiences).

Nonetheless, some researchers have argued that the four dimensions of SOC are not relevant for the measurement of SOC in a statistical sense [2, 3]; it has frequently been reported that measurements including reversal items or response methods cannot provide statistical clarity of the SOC for any samples [2, 4]. Additionally, the necessity of a measure including fewer items, which can be utilized in various community contexts, has been raised [2, 5].

To address these problems, Peterson et al. [5] created the Brief Sense of Community Scale (BSCS) and confirmed its reliability and validity. Comprising only eight items, the BSCS can not only measure the four SOC dimensions proposed by McMillan and Chavis [1] but can also represent a robust factor structure [5]. Recently, BSCS has gained attention for its applicability in various community studies, such as those among youth [6, 7], LGBT individuals [8], and residents [5]; moreover, it has been translated to several non-English languages [9]. BSCS is widely used in Asia, including China 10,11,12,13], Korea [14], Vietnam [15], and Japan [16], as well as in the Western community. However, problems exist in the BSCS used in Asia, such as the translation process being unclear 10,11,12,13,14,15,16,17,18,19] and back translate being performed but not examined for validity [20]. In addition, the factor structure of the BSCS has not been examined, and many studies use the BSCS as a one-factor 10,11,12,13,14,15,16,17,18,19,20]. We believe that it is necessary to clarify the factor structure of the BSCS in Asia and to verify its validity to make cross-national comparisons with the Western community. We conducted the present study in Japan as the first step, and the findings can be compared with those in other regions of Asia in the future.

It is noteworthy that the most SOC studies in Japan developed their own measures instead of adopting Western ones 21,22,23]. This is because the strong influence of Japan’s unique socio-cultural contexts, such as “ie” (household) and “mura” (village community), can hinder the accurate translation of a measure to Japanese [21]. Nonetheless, the independent measures developed in Japan cannot be considered suitable for application in future cross-national studies on SOC. The Japanese version of the BSCS will resolve this issue of the generalization of SOC measurements.

Considering this situation, we developed a Japanese version of the BSCS and examined its reliability and validity within a sample of Japanese community residents. To verify the “criterion-related validity,” we also used the Sense of Community Scale 2 (SCI-2), Community Consciousness Scale (CCS [21, 22]), and Center for Epidemiologic Studies Depression Scale (CES-D [24]). Below, we briefly explain why each of the three scales were used for the criterion-related validity test.

  1. (i)

    SCI-2: As a McMillan-Chavis four-factor structure was confirmed in SCI-2 by increasing the number of items, eliminating inverted items, and making changes to the required responses, it is expected that all factors of SCI-2 would be positively correlated with those of the Japanese version of the BSCS.

  2. (ii)

    CCS: CCS is a widely accepted measure of SOC that was developed in Japan and includes the roles of the government and initiatives by citizens of the community. [21, 22]

  3. (iii)

    CES-D: SOC has been shown to improve an individual’s mental health [1, 25, 26], and CES-D, a measure of depression, is negatively correlated with BSCS. [5, 11, 12, 18]

Methods

Participants

The survey was outsourced to an online survey agency (Cross Marketing Co., Ltd.). Participants were Japanese residents from various age groups and regions who provided their consent to participate. The survey was conducted such that the number of men and women and those in each age group were approximately equal. In total, 1000 Japanese people were recruited to participate in the survey in November 2021. Excluding a few suspicious responses (such as those with the same answers throughout the questionnaires), the responses of 993 participants (498 men and 495 women) were used for further statistical analysis. The mean and standard deviation of the ages were 49.55 years and 16.74 years, respectively. Among the participants. 33.53% were aged 18–39, 31.13% were aged 40–59, and 33.33% were aged 60 or older. In terms of educational level, 2.11% were less than high school educated, 29.41% had completed high school, 19.64% had graduated from junior college or vocational school, 43.20% had earned a bachelor’s degree, and 5.64% had a master’s degree or higher. A total of 53.07% of the participants lived in the eastern region of Japan (Hokkaido, Tohoku, Kanto region) and 49.63% in the western region (Chubu, Kinki, Chugoku, Shikoku, Kyushu, Okinawa region). In addition, the eastern and western regions have different cultures (e.g., food flavoring) [27]. Thus, both regions are geographically and culturally different. As the Chubu region can be considered either to the east or the west [28], it was classified as the western region in this study.

Measures

Japanese version of the BSCS

The BSCS, created by Peterson et al. [5], comprises eight items scored on a 5-point Likert-type scale (ranging from 1 = strongly disagree to 5 = strongly agree) to assess the four dimensions of SOC (needs fulfilment, membership, influence, and emotional connection). The scale’s reliability was confirmed by an internal consistency of Cronbach’s α = 0.85 ~ 0.92 [5, 7]. We translated the BSCS into Japanese after obtaining permission and performed the standard procedure of back-translation with advice from Dr. Peterson.

Sense of Community Index 2 (SCI-2)

SCI-2 is a 24-item self-report scale that adopts the theoretical framework of McMillan and Chavis [1]; its four subscales are “reinforcement of needs,” “membership,” “influence,” and “shared emotional connection.” [29] The scale’s reliability was confirmed by an internal consistency of Cronbach’s α = 0.91 for the entire scale and 0.79 ~ 0.86 for the subscales [30].The SCI-2 items are scored on a 4-point Likert scale ranging from 0 (not at all) to 3 (completely), with six items under each subscale.

Short version of Community Conscious Scale

The short version of community conscious scale is a 12-item self-report questionnaire [22]. This scale is a short version of the CCS [21, 31] considers SOC to be a multifaceted concept that included the roles of government and citizen agency in the community. The items are scored on a 5-point Likert-type scale ranging from 1 (disagree) to 5 (agree). This scale comprises the following four subscales, each including three items: solidarity (e.g., “I want to participate in voluntary activities in my community”), self-determination (e.g., “In the problem solving in the community, it is important to build up an equal partnership between the residents and administration”), attachment (e.g., “Because I live temporarily in this community, I have neither the concern of nor the attachment to my community”), and dependency on others (e.g., “It is acceptable that the residents leave the activities in improving their living environment in the community to more dedicated people”).

Japanese version of the Center for Epidemiologic Studies Depression (CES-D)

The Japanese version of the CES-D is a 20-item self-report scale that measures depression under the following four subscales: “somatic complaints,” “depressed affect,” “positive affect,” and “interpersonal problems” [32]. Participants respond to the 20 items based on their experiences within the past week on a 4-point Likert scale ranging from 0 (rarely or none of the time, less than 1 day) to 3 (most or all the time, 5–7 days).

Procedures

This study was approved by the Ethics Committee of the authors’ university. Participation was entirely voluntary. Before administering the questionnaire, the participants were informed of the survey overview and terms of confidentiality, and their consent was obtained. Cross Marketing awarded the participants with reward points for completing the questionnaire.

Statistical analyses

Confirmatory factor analysis (CFA) was performed using the Mplus 8.1 statistical software package [33]. Additionally, the maximum likelihood estimator (ML) was applied for CFA estimation in this study. To test the goodness-of-fit, we conducted comparative fit index (CFI), Tucker–Lewis index (TLI), root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), Akaike’s information criterion (AIC), Bayesian information criterion (BIC), and Akaike’s Bayesian information criterion (ABIC). The cut-off values for acceptable model fit used in this study are: RMSEA 0.10 for poor fit and < 0.06 for good fit; CFI > 0.90 for acceptable fit and > 0.95 for good fit; and SRMR < 0.10 for acceptable fit and < 0.08 for good fit [34, 35]. For additional analyses, multiple-group CFA was conducted to examine gender and region of residence (eastern or western region) invariance. Furthermore, measurement invariance was tested by creating three models: a configural model (no constraints), metric invariance model (with item loading constraints to be equal across groups), and scalar invariance model (with item loadings and item intercepts with simultaneous constraints to be equal across groups). Following the hierarchy of these nested models, they were compared with each other. We focused on the ratio of χ2 to its degree of freedom, ΔCFI, ΔRMSEA and ΔSRMR as indicators in the model comparisons. Model invariance is indicated by Δχ2df of less than or equal to 5 and ΔCFI smaller than 0.01, accompanied by ΔRMSEA smaller than 0.015 and ΔSRMR smaller than 0.03 36,37,38]. For the comparison of factor means, we followed guidelines [39] and demonstrated ΔM and p-value.

Other analyses were conducted using the program R version 3.6.3 [40]. Cronbach’s alpha coefficients, McDonald’s omega coefficients, and correlations between the Japanese BSCS and other measures were established by calculating the Pearson’s correlation coefficients. All statistical analyses used two-tailed tests. For all statistical evaluations, p values less than 0.05 were considered indicative of significant differences.

Results

Factor structure

The mean scores for each item of the Japanese BSCS are shown in Table 1. The mean values for each item ranged 2.33–3.10, with standard deviations ranging 0.91–1.04. Skewness and kurtosis were smaller than 1. Confirmatory factor analyses were used to examine the goodness-of-fit. Based on the original scale validation study [5], three models were tested for use among Japanese participants (Fig. 1). As shown in Table 2, the four-factor and second-order models demonstrated acceptable fits, whereas the one-factor case did not. Therefore, although the second-order model had higher AIC, BIC, and ABIC than the four-factor model, we will examine the gender and region of residence invariances for both.

Table 1 Descriptive Statistics of the Japanese BSCS Items
Fig. 1
figure 1

Three models in Brief sense of community scale (BSCS)

Table 2 Factor Loadings for the Japanese BSCS

Multiple-group CFA was performed to examine the gender and region of residence invariances in both models. In the four-factor model, the metric invariance and configural models showed acceptable cutoff criteria (gender: Δχ2df = 1.46, ΔCFI = − 0.001, ΔRMSEA = − 0.006 and ΔSRMR = 0.016; region: Δχ2df = 0.98, ΔCFI = 0.000, ΔRMSEA = − 0.006 and ΔSRMR = 0.011). The metric invariance and scalar invariance models also showed acceptable cutoff criteria (gender: Δχ2df = 0.75, ΔCFI = 0.000, ΔRMSEA = − 0.004 and ΔSRMR = 0.001; region: Δχ2df = 1.31, ΔCFI = -0.001, ΔRMSEA = − 0.002 and ΔSRMR = 0.003). Consequently, the scalar invariance model was supported in the four-factor model (Table 3). Meanwhile, in the second-order model, the metric invariance and configural models were acceptable (gender: Δχ2df = 4.47, ΔCFI = − 0.004, ΔRMSEA = − 0.002 and ΔSRMR = − 0.019; region: Δχ2df = 4.11, ΔCFI = − 0.004, ΔRMSEA = − 0.003 and ΔSRMR = 0.010). The metric invariance and scalar invariance models also showed acceptable cutoff criteria (gender: Δχ2df = 0.78, ΔCFI = 0.000, ΔRMSEA = − 0.009 and ΔSRMR = 0.000; region: Δχ2df = 1.32, ΔCFI = − 0.001, ΔRMSEA = − 0.007 and ΔSRMR = − 0.001). Therefore, the scalar invariance model was supported in the second-order model as well (Table 3).

Table 3 Measurement Invariance of Four factor model and Second-order model Among Gender Groups and Region Groups for the Japanese BSCS

Finally, the factor means were compared between genders. In the four-factor model, women had lower factor means than men for both IN and EC, which were all non-significant (NF: ΔM = 0.02, p = 0.73; MB: ΔM = 0.01, p = 0.09; IN: ΔM = − 0.03, p = 0.60; EC: ΔM = − 0.02, p = 0.72). Meanwhile, in the second-order model, women had lower factor means than men, which were not significant (ΔM = − 0.02, p = 0.83). Similarly, factor means were also compared between the regions. In the four-factor model, the western region had higher factor means than the eastern region with the exception of NF, which were not significant (NF: ΔM = − 0.01, p = 0.81; MB: ΔM = 0.07, p = 0.30; IN: ΔM = 0.03, p = 0.55; EC: ΔM = 0.10, p = 0.11). Meanwhile, in the second-order model, the western region had higher factor means than eastern region, which were not significant (ΔM = 0.08, p = 0.23).Thus, we did not find differences between the factor means of men and women, in the eastern and western regions either in the four-factor or the second-order models.

Reliability and validity of the BSCS

The descriptive statistics of the Japanese version of the BSCS are presented in Table 1, which indicates that the intercorrelations between all domains were significant, ranging from r = 0.41 to 0.76. The values for the internal consistency reliability were acceptable for need fulfillment (α = 0.89/ ω = 0.89), membership (α = 0.92/ ω = 0.92), influence (α = 0.75/ ω = 0.75), and emotional connection (α = 0.91/ ω = 0.91), as well as for the total BSCS scores (α = 0.91/ ω = 0.91).

Table 4 shows the correlations between demographic variables and the four domains of the BSCS, and between BSCS and the other scales. Age was significantly associated with membership (r = 0.16, p < 0.01; 95% CI 0.06 ~ 0.27) and emotional connection (r = 0.14, p < 0.01; 95% CI 0.03 ~ 0.24). Additionally, educational level was significantly associated with needs fulfilment (r = . 15, p < 0.01; 95% CI 0.05 ~ 0.25). The correlations between all domains in the Japanese BSCS and SCI-2 were significant, ranging from r = 0.29 ~ 0.56, p < 0.01. All domains of the Japanese BSCS were significantly positively correlated with solidarity (r = 0.39 ~ 0.54, p < 0.01), self-determination (r = 0.32 ~ 0.40, p < 0.01), and attachment (r = 0.33 ~ 0.58, p < 0.01) in the CCS. Dependency on others in the CCS demonstrated a significantly negative correlation with only membership (r = − 0.11, p < 0.01). All factors of the Japanese version of the BSCS, except influence, were negatively correlated with CES-D (r = − 0.15 ~ − 0.21, p < 0.01).

Table 4 Correlations between the Japanese BSCS and other scales

Discussion

We developed the Japanese version of the BSCS and confirmed its four subscales—“needs fulfilment,” “membership,” “influence,” and “emotional connection”—through analyses of its factor. For the factor structure, acceptable goodness-of-fit was confirmed in both the four-factor and second-order models. The multiple-group CFA by gender and region of residence found identical factor structures and non-differentiable factor loadings and intercept. Additionally, the factor means were not differentiable in the four-factor and second-order models. The BSCS has represented the same factor structures across various samples, such as in midwestern United states neighborhood residents [5], youth [6, 7], and LGB individuals [8]. Therefore, the factor structure of BSCS may show demonstrate robustness even in communities within different cultures and demographics. We also note that the four-factor and second-order models in this study, in addition to the previous study cases 5,6,7,8], showed adequate goodness-of-fit.

Let us discuss the correlations between the Japanese version of the BSCS and other measures, which can indicate acceptable reliability and validity of the Japanese BSCS. First, the significantly positive correlations between each factor of the BSCS and all factors of the SCI-2 indicate that the Japanese version of the BSCS corresponds to the four dimensions of McMillan and Chavis [1]. Second, in the correlations between the BSCS and CCS, we found that “solidarity,” “self-determination,” and “attachment” in the CCS were positively correlated with all factors of the BSCS; additionally, “dependence on others” in the CCS demonstrated a negative correlation with only “group membership” in the BSCS. As “dependency on others” is a factor that indicates an indifference toward local issues and reliance on unknown others to solve them [21, 22, 31], it is possible that the feeling of being a part of the community results in a decrease in the indifference toward the community. Third, CES-D was negatively correlated with the BSCS. This indicates that a sense of community is related to individual mental health in Japan, as in previous studies [5, 25, 26].

It is also remarkable that the correlations between the Japanese version of the BSCS and the demographic variables were generally consistent with those in previous studies [5, 8], and that the Japanese version of the BSCS had a factor structure in common with cases in previous studies 5,6,7,8]. Taken together, these results suggest that the BSCS has a robust factor structure, even across different cultures.

Limitations

This study has some limitations. We note that the relationships between the SOC and “community participation” could not be evaluated. As local activities remain restricted due to COVID-19 in Japan [41], we did not continue to measure community participation as it may mislead further analysis. We hope that future studies will analyze the community participation from the perspective of the SOC.

The second limitation is that comparisons by place of residence could only be made for the broad categories of the eastern and western regions. In this study, respondents were asked about their place of residence, but only up to prefecture. It is possible that SOC may differ between those who live in urban areas and those who live in rural areas, even in the same prefecture. In the future, it will be necessary to examine differences by size of cities of residence and type of community, such as rural or urban.

The third limitation is related to the survey methodology; we used an online survey agency to collect data from participants of various ages and living across different areas of Japan. However, nonprobability online surveys, as in this study, have been noted to be less accurate than probability telephone and online surveys [42]. Therefore, it may be necessary to conduct a probability survey, or a survey of all members of a particular local community, to examine whether a similar factor structure can be obtained.

Finally, as this study was conducted on Japanese participants, it remains unclear whether the factor structure identified in the present study is also observed in other countries, particularly in Asia. In the future, it will be necessary to clarify the factor structure of the BSCS through cross-national comparisons.

Conclusions

Despite the abovementioned limitations, this study is the first in Asia to utilize the BSCS. The Japanese version of the BSCS was found to have good internal consistency. The positive correlations with other SOC scales and negative correlations with depression indicate that the validity of the Japanese BSCS is relatively comparable to the original BSCS. The Japanese BSCS is an 8-item scale for the assessment of SOC in Japanese communities, which will contribute to the creation of communities in which members feel a sense of “belonging.” Moreover, the Japanese version of the BSCS will enable cross-national comparative studies of SOC in the future.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

SOC:

Sense of community

BSCS:

Brief Sense of Community Scale

SCI-2:

Sense of Community Scale 2

CCS:

Community Consciousness Scale

CES-D:

Center for Epidemiologic Studies Depression Scale

CFA:

Confirmatory factor analysis

ML:

Maximum likelihood estimator

CFI:

Comparative fit index

TLI:

Tucker–Lewis index

RMSEA:

Root mean square error of approximation

SRMR:

Standardized root mean square residual

AIC:

Akaike’s information criterion

BIC:

Bayesian information criterion

ABIC:

Akaike’s Bayesian information criterion

References

  1. McMillan DW, Chavis DM. Sense of community: a definition and theory. J Community Psychol. 1986;14(1):6–23. https://doi.org/10.1002/1520-6629(198601)14:1%3c6::AID-JCOP2290140103%3e3.0.CO;2-I.

    Article  Google Scholar 

  2. Long DA, Perkins DD. Confirmatory factor analysis of the sense of community index and development of a brief SCI. J Community Psychol. 2003;31(3):279–96. https://doi.org/10.1002/jcop.10046.

    Article  Google Scholar 

  3. Vieno A, Perkins DD, Smith TM, Santinello M. Democratic school climate and sense of community in school: a multilevel analysis. Am J Community Psychol. 2005;36(3–4):327–41. https://doi.org/10.1007/s10464-005-8629-8.

    Article  Google Scholar 

  4. Peterson NA, Speer PW, Hughey J. Measuring sense of community: a methodological interpretation of the factor structure debate. J Community Psychol. 2006;34(4):453–69. https://doi.org/10.1002/jcop.20109.

    Article  Google Scholar 

  5. Peterson NA, Speer PW, McMillan DW. Validation of a brief sense of community scale: confirmation of the principal theory of sense of community. J Community Psychol. 2008;36(1):61–73. https://doi.org/10.1002/jcop.20217.

    Article  Google Scholar 

  6. Lardier DT Jr, Opara I, Cantu I, Garcia-Reid P, Reid RJ. The brief sense of community scale: testing dimensionality and measurement invariance by gender among Hispanic/Latinx youth. J Community Psychol. 2022;50(1):409–25. https://doi.org/10.1002/jcop.22585.

    Article  Google Scholar 

  7. Lardier DT Jr, Reid RJ, Garcia-Reid P. Validation of the Brief Sense of Community Scale among youth of color from an underserved urban community. J Community Psychol. 2018;46(8):1062–74. https://doi.org/10.1002/jcop.22091.

    Article  Google Scholar 

  8. Griffin JA, Eldridge-Smith ED, Kridel MM, Draheim AA, Stepleman LM. Validation of the Brief Sense of Community Scale in a lesbian, gay, and bisexual sample. J Community Psychol. 2022;50(1):576–91. https://doi.org/10.1002/jcop.22638.

    Article  Google Scholar 

  9. Wombacher J, Tagg SK, Bürgi T, MacBryde J. Measuring sense of community in the military: cross-cultural evidence for the validity of the brief sense of community scale and its underlying theory. J Community Psychol. 2010;38(6):671–87. https://doi.org/10.1002/jcop.20388.

    Article  Google Scholar 

  10. Au A, Lai DWL, Yip H, Chan S, Lai S, Chaudhury H, Scharlach A, Leeson G. Sense of community mediating between age-friendly characteristics and life satisfaction of community-dwelling older adults. Front Psychol. 2020;11:86. https://doi.org/10.3389/fpsyg.2020.00086.

    Article  Google Scholar 

  11. Huang Y, Wong H. Impacts of sense of community and satisfaction with governmental recovery on psychological status of the Wenchuan earthquake survivors. Soc Indic Res. 2014;117(2):421–36. https://doi.org/10.1007/s11205-013-0354-3.

    Article  Google Scholar 

  12. Huang Y, Tan NT, Liu J. Support, sense of community, and psychological status in the survivors of the Yaan earthquake. J Community Psychol. 2016;44(7):919–36. https://doi.org/10.1002/jcop.21818.

    Article  Google Scholar 

  13. Zheng W, Huang Y, Fu Y. Mediating effects of psychological resilience on life satisfaction among older adults: a cross-sectional study in China. Health Soc Care Community. 2020;28(4):1323–32. https://doi.org/10.1111/hsc.12965.

    Article  Google Scholar 

  14. Kim JI, Kono A, Yoshiyuki N, Kang J. Korean translation and validation of the community commitment scale for preventing social isolation in older adults. Geriatr Geronto Int. 2018;18(5):806–12. https://doi.org/10.1111/ggi.13249.

    Article  Google Scholar 

  15. Le TH, Nakagawa Y, Kobayashi Y. Conditions under which rural-to-urban migration enhances social and economic sustainability of home communities: a case study in Vietnam. Sustainability. 2021;13(15):8326. https://doi.org/10.3390/su13158326.

    Article  Google Scholar 

  16. Tadaka E, Kono A, Ito E, Kanaya Y, Dai Y, Imamatsu Y, Itoi W. Development of a community’s self-efficacy scale for preventing social isolation among community-dwelling older people (Mimamori Scale). BMC Public Health. 2016;16:1198. https://doi.org/10.1186/s12889-016-3857-4.

    Article  Google Scholar 

  17. Guo Y, Liu Y, Lu S, Chan OF, Chui CHK, Lum TYS. Objective and perceived built environment, sense of community, and mental wellbeing in older adults in Hong Kong: a multilevel structural equation study. Landsc Urban Plan. 2021;209: 104058. https://doi.org/10.1016/j.landurbplan.2021.104058.

    Article  Google Scholar 

  18. Wu Q, Chow JCC. Social service utilization, sense of community, family functioning and the mental health of new immigrant women in Hong Kong. Int J Environ Res Public Health. 2013;10(5):1735–46. https://doi.org/10.3390/ijerph10051735.

    Article  Google Scholar 

  19. Zhang J, Yu NX, Zhang J, Zhou M. Sense of community and life satisfaction in Chinese older adults: moderating roles of personal and partner resilience. J Community Psych. 2017;45(5):577–86. https://doi.org/10.1002/jcop.21878.

    Article  Google Scholar 

  20. Kuwayama A, Sasao T. The role of social-ecological correlates of psychological well-being and parenting self-efficacy among Filipino migrant mothers in urban Japan. Educ Stud. 2020;62:21–37. https://doi.org/10.34577/00004652.

    Article  Google Scholar 

  21. Ishimori M. Community consciousness and citizen’s participation in community building: through a development of a community consciousness scale. Jpn J Community Psychol. 2004;7(2):87–98. https://doi.org/10.32236/jscpjournal.7.2_87.

    Article  Google Scholar 

  22. Ishimori M, Okamoto T, Kato J. Development of the short version of the community consciousness scale. Jpn J Exp Soc Psychol. 2013;53(1):22–9. https://doi.org/10.2130/jjesp.1113.

    Article  Google Scholar 

  23. Sasao T, Koyama A, Ikeda M. Toward a new generation of faculty development programs: a community psychological perspective. Int Christ Univ Publ. 2003;45:55–71.

    Google Scholar 

  24. Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1(3):385–401. https://doi.org/10.1177/014662167700100306.

    Article  Google Scholar 

  25. Bailey M, McLaren S. Physical activity alone and with others as predictors of sense of belonging and mental health in retirees. Aging Ment Health. 2005;9(1):82–90. https://doi.org/10.1080/13607860512331334031.

    Article  Google Scholar 

  26. Parker EA, Lichtenstein RL, Schulz AJ, Israel BA, Schork MA, Steinman KJ, James SA. Disentangling measures of individual perceptions of community social dynamics: results of a community survey. Health Educ Behav. 2001;28(4):462–86. https://doi.org/10.1177/109019810102800407.

    Article  Google Scholar 

  27. Wang J, Kawada T, Sasazawa Y, Shimada O. Geographical difference in sodium and potassium concentrations of noodle soups in Japan. Jpn J Health Human Ecolo. 1999;65(2):92–103. https://doi.org/10.3861/jshhe.65.92.

    Article  Google Scholar 

  28. Shinmura I. Kojien. 7th ed. Tokyo: Iwanami-Shoten; 2017.

    Google Scholar 

  29. Chavis DM, Lee KS, Acosta JD. The sense of community (SCI) revised: the reliability and validity of the SCI-2. In: 2nd International Community Psychology Conference. Lisboa: Portugal; 2008.

  30. Community Science. Sense of community index 2 (sci-2): background, instrument, and scoring instructions. http://www.communityscience.com/pdfs/Sense of Community Index-2(SCI-2).pdf. Accessed 20 May 2022.

  31. Ishimori M. Relationship between sense of community and motivation to participate in NPO activities. Nonprofit Rev. 2007;7(2):67–73. https://doi.org/10.11433/janpora.7.67.

    Article  Google Scholar 

  32. Shima SS, Kitamura T, Asai M. New self-rating scale for depression. Seisin-Igaku. 1985;27:717–23.

    Google Scholar 

  33. Muthén LK, Muthén BO. Mplus user’s guide. 8th ed. Los Angeles: Muthén & Muthén; 2017.

    Google Scholar 

  34. Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6(1):1–55. https://doi.org/10.1080/10705519909540118.

    Article  Google Scholar 

  35. Kline R. Principles and practice of structural equation modeling (methodology in the social sciences). 3rd ed. New York: Guilford Press; 2011.

    Google Scholar 

  36. Chen FF. Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct Equ Model. 2007;14(3):464–504. https://doi.org/10.1080/10705510701301834.

    Article  Google Scholar 

  37. Rosay AB, Gottfredson DC, Armstrong TA, Harmon MA. Invariance of measures of prevention program effectiveness: a replication. J Quant Criminol. 2000;16(3):341–67. https://doi.org/10.1023/A:1007527022941.

    Article  Google Scholar 

  38. Wang J, Wang X. Structural equation modeling: applications using Mplus. Hoboken: John Wiley & Sons; 2019.

    Book  Google Scholar 

  39. Van de Schoot R, Lugtig P, Hox J. A checklist for testing measurement invariance. Eur J Dev Psychol. 2012;9(4):486–92. https://doi.org/10.1080/17405629.2012.686740.

    Article  Google Scholar 

  40. R Core Team. R: a language and environment for statistical computing. 2021.

  41. Kuwahara K, Kuroda A, Fukuda Y. COVID-19: Active measures to support community-dwelling older adults. Travel Med Infect Dis. 2020;36: 101638. https://doi.org/10.1016/j.tmaid.2020.101638.

    Article  Google Scholar 

  42. Yeager DS, Krosnick JA, Chang L, Javitz HS, Levendusky MS, Simpser A, Wang R. Comparing the accuracy of RDD telephone surveys and internet surveys conducted with probability and non-probability samples. Public Opin Q. 2011;75(4):709–47. https://doi.org/10.1093/poq/nfr020.

    Article  Google Scholar 

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Acknowledgements

The authors would like to express their gratitude to Dr. Peterson, N. Andrew at the Rutgers University for permission to translate the BSCS.

Funding

This work was supported by JSPS KAKENHI Grant Number 20K03325.

Author information

Authors and Affiliations

Authors

Contributions

K.Y. and K.A. conceptualized the project. K.Y. collected the data. K.A. analyzed the data. K.Y. and K.A. wrote the manuscript. T.H. and K.W. contributed to the analysis and interpretation of the findings. T.H. and K.W. revised and edited the final manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Keigo Asai.

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Ethics approval and consent to participate

This study has been approved by the research ethics committee of Hokkaido University of Education (No: 2021114002). Participants were informed about the survey overview and terms of confidentiality, and their informed consent was obtained. All methods were performed in accordance with the relevant guidelines and regulations.

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Not applicable.

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The authors declare that they have no competing interests.

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Yu, KR., Asai, K., Hiraizumi, T. et al. Japanese version of the Brief Sense of Community Scale: construct validity and reliability. BMC Psychol 10, 301 (2022). https://doi.org/10.1186/s40359-022-01017-x

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Keywords

  • Brief Sense of Community Scale (BSCS)
  • Confirmatory factor analysis
  • Gender
  • Japanese
  • Psychological sense of community
  • Reliability
  • Validity