Skip to main content

Cultural adaptation and validation of Japanese medical resident version of the workplace social capital scale: a cross-sectional study

Abstract

Background

The Workplace Social Capital (WSC) Scale is the most frequently used tool for measuring social capital at work in Western countries. However, there are no corresponding tools for assessing WSC among medical trainees in Japan. Thus, this study was conducted to develop the Japanese medical resident version of the WSC (JMR-WSC) Scale and examine its validity and reliability.

Methods

The Japanese version of the WSC Scale by Odagiri et al. was reviewed and the scale was partially modified for use in the Japanese context of postgraduate medical education. To verify the validity and reliability of the JMR-WSC Scale, a cross-sectional survey was performed in 32 hospitals across Japan. Postgraduate trainees (years 1–6) at the participating hospitals responded to the online questionnaire on a voluntary basis. We tested the structural validity through confirmatory factor analysis. We also examined criterion-related validity and internal consistency reliability of the JMR-WSC Scale.

Results

In all, 289 trainees completed the questionnaire. The results of confirmatory factor analysis supported the JMR-WSC Scale’s structural validity on the same two-factor model as that of the original WSC Scale. Logistic regression analysis showed that, after adjustment for gender and postgraduate years, trainees with good self-rated health had a significantly elevated odds ratio for good WSC. Cronbach’s alpha coefficients showed acceptable internal consistency reliability.

Conclusions

We successfully developed the JMR-WSC Scale and examined its validity and reliability. Our scale could be used to measure social capital in postgraduate medical training settings in Japan to help prevent burnout and reduce patient safety incidents.

Peer Review reports

Background

Social capital is defined as the resources that individuals and groups have access to through their social networks [1, 2]. Social capital can be conceptualized at both the individual and collective levels. It can be studied at the macro level (i.e., regional or country level), the meso-level (i.e., workplace and community), and the micro level [3]. In recent years, Workplace Social Capital (WSC) has received increased attention because the workplace is considered to be the primary social context to which working-age populations devote the majority of their waking hours [4].

WSC refers to the contextual psychosocial characteristics of the workplace, characterized by interpersonal trust and norms of reciprocity [5]. Previous studies have shown an association between social capital in the workplace and workers’ health. Lower WSC is associated with poorer self-rated health [6], poorer mental health [4, 7,8,9], and higher mortality [10]. There is mounting evidence that WSC benefits employees. Therefore, it is important to measure employees’ WSC and follow up with them based on the results to promote their health. In contrast, burnout is common and a major concern among medical residents [11,12,13]. A recent systematic review and meta-analysis revealed that the overall prevalence of burnout was as high as 40% [14]. This finding indicates the existence of a significant problem, as burnout can undermine professionalism, lead to medical errors, reduce the quality of patient care, and lead to various personal consequences (e.g., substance abuse, suicidal ideation, and relationship difficulties) [15,16,17,18,19,20]. Given its prevalence and the severity of its consequences, immediate action is required to prevent burnout among residents [11]. Although it can be caused by a range of factors, including personal, organizational, and social problems, the precise nature of the work environment may be of great importance [21]. In particular, WSC is crucial, as previous studies have reported the association between higher WSC and lower likelihood of burnout [22,23,24]. Therefore, a validated scale should be developed to assess WSC among medical residents.

In Western countries, several instruments are available for assessing WSC. Among them, Kouvonen et al.’s WSC Scale is the most frequently used; it was well validated through psychometric analysis in a Finnish Public Sector Study [25].

Odagiri et al. developed the Japanese version of the WSC Scale in 2010 [26]. The scale developed by Odagiri et al. was a translated version of the original English scale developed following a rigorous translation process, including forward-translation and back-translation, followed by a review of the back-translation by the author of the original instrument. However, the Japanese version of the WSC Scale has the following two problems that limit its potential use in a Japanese medical education setting. First, Odagiri et al. used only factory employees. The scale has recently been used in a study of medical settings, but only seven participants out of 440 were doctors, and the study also omitted data on the doctors’ years of postgraduate study [27]. In addition, some of the items in the questionnaire are inconsistent with the Japanese healthcare context. Accordingly, it is unclear whether the Japanese version of the scale can be used for Japanese residents and whether it requires cultural adaptation to the Japanese healthcare setting. Second, the Japanese version of the scale has only been presented at an academic conference in Japan. Publication in an international English-language journal would promote international research on the WSC.

Burnout has become a major problem among medical trainees in Japan [28, 29]. A scale for measuring WSC in this group would make it possible to assess training environments and thereby plan for burnout prevention. Therefore, this study aimed to validate and culturally modify the WSC Scale for use by Japanese medical residents.

Methods

Design, setting, and participants

We conducted a multicenter cross-sectional study from July to August 2022. We contacted training directors at 78 postgraduate clinical training hospitals throughout Japan, and 32 agreed to cooperate in this study. Their characteristics are presented in Table 1. We sent survey invitations to medical trainees at the 32 hospitals via email and asked them to complete an online questionnaire using SurveyMonkey. In the invitation email, we informed the trainees that participation was optional, and that nonparticipation would not result in any negative consequences for them. Non-respondents were reminded three times via email to complete the survey.

Table 1 Characteristics of the participating hospitals

Measures

The original English WSC Scale, as developed by Kouvonen et al., is an eight-item instrument [25]. According to Oksanen et al.’s study, the factor analysis revealed two-factor structure (vertical trust in the supervisor and horizontal trust in peers) [8]. Odagiri et al. developed the Japanese version of the scale and confirmed its acceptable reliability and validity [26]. The question items are rated on a five-point Likert scale (from 1 = strongly disagree to 5 = strongly agree). Factor analysis revealed the same two-factor structure as that of the original scale: horizontal (Q1–5) and vertical trust (Q6–8) [8, 25, 26]. The average score of the eight items was calculated within a range from 1 to 5 for each item, such that higher scores indicate a higher level of WSC.

In this study, the Japanese version of the WSC Scale was reviewed, and the need for cultural adaptation to the medical training setting in Japan was examined. We decided to modify two of the words in the questionnaire so that they could be used for Japanese residents. First, the term busho (“work unit”) is an unnatural Japanese expression for the medical trainee setting. Accordingly, we altered this term to busho (shinryoka “clinical department”) to make the meaning clear. Second, because only Q5 was written in an interrogative way, the text was changed to a statement. These steps produced the Japanese medical resident version of the WSC Scale (JMR-WSC Scale) (Additional file).

Statistical analysis

We validated the JMR-WSC Scale by following the three steps.

First, we tested the structural validity of the JMR-WSC Scale by confirmatory factor analysis (CFA), using maximum likelihood estimation. In the CFA, we hypothesized the same factor structure (i.e., a two-factor structure) as that of the original WSC Scale developed by Kouvonen et al. and the Japanese version of the WSC Scale developed by Odagiri et al. [8, 25, 26]. The cut-off value for factor loadings was set to 0.40. We assessed the model fitness using the following multiple criteria: chi-square to degrees of freedom ratio (χ2/df) < 5, the comparative fit index (CFI) > 0.95, the root mean square error of approximation (RMSEA) < 0.10, and the standardized root mean square residual (SRMR) < 0.08 [30, 31].

Second, as shown by Kouvonen et al. and Odagiri et al., the measure of self-rated health was used for examining criterion-related validity [25, 26]. Self-rated health was assessed by the following item: “How would you estimate your current state of health?” [32] This item was rated on a 5-point Likert scale: 1 = poor, 2 = fair, 3 = good, 4 = very good, and 5 = excellent. Those who answered 4–5 to this item were classified as the “good” self-rated health group, whereas those who answered 1–3 were classified as the “poor” self-rated health group. JMR-WSC Scale scores were divided into two groups by median value. Referring to previous validation studies, we used logistic regression analysis to calculate the gender and postgraduate years adjusted odds ratio and its 95% confidence intervals for the association between WSC and self-rated health.

Third, we checked Cronbach’s alpha coefficients to examine the internal consistency reliability. Alpha values greater than 0.70 are acceptable [33].

Fourth, we conducted descriptive statistics (e.g., mean and standard deviations). In the present study, all statistical analysis was performed using R version 4.2.1. We used the lavaan package version 0.6–12 [34], semPlot package version 1.1.6 [35], stats version 4.3.0, ltm version 1.2.0 [36], and psych version 2.2.9 [37].

Ethical considerations

All participants provided their individual informed consent through the survey form. Participants were enrolled in a drawing for one of ten ¥5,000 gift cards. The study received ethical approval from the Institutional Review Board of the University of Tokyo (2022062NI).

Results

In all, 289 (23.5%) of the 1228 individuals who were residents of the participating hospitals completed the online survey. The participant selection flowchart is displayed in Fig. 1. Due to the tiny amount of missing data, we chose a complete case analysis. Table 2 provides a summary of the respondents’ characteristics. The replies of the participants to each of the questionnaire items are shown in Table 3.

Fig. 1
figure 1

Participants’ flowchart in a study on the cultural adaptation and validation of Japanese medical resident version of the Workplace Social Capital Scale

Table 2 Characteristics of the participants (N = 289)
Table 3 Participants’ responses to the Japanese medical resident version of the Workplace Social Capital Scale (N = 289): N (%)

To verify the structural validity, we conducted CFA. The path diagrams of the CFA are shown in Fig. 2. All factor loadings exceeded the 0.40 criteria (ranging from 0.70 to 0.93). The model fitness met the recommended criteria: χ2/df = 65.707/19 = 3.46, CFI 0.970, RMSEA 0.092, and SRMR 0.028.

Fig. 2
figure 2

The final confirmatory factor analysis model of the Japanese medical resident version of the Workplace Social Capital Scale. Ellipses represent latent variables (factors). Rectangles are observed variables (items). Values on single-headed arrows are standardized factor loadings. Values on double-headed arrows represent correlation coefficients

We examined the criterion-related validity in relation to self-rated good health. In the logistic regression analysis, trainees with good self-rated health had a significantly elevated odds ratio of 1.83 (1.11–3.04) (p < 0.05) for good WSC.

Table 4 shows internal consistency reliability and score distribution and of the JMR-WSC Scale. We obtained a Cronbach’s alpha value of 0.91 for all items, 0.89 for Factor 1 (horizontal trust), and that of 0.90 for Factor 2 (vertical trust). Thus, we obtained the final version of the scale.

Table 4 Internal consistency reliability and score distribution of the Japanese medical resident version of the WSC Scale

Discussion

We developed the JMR-WSC Scale. In a multicenter survey, psychometric analysis indicated acceptable reliability and validity. To the best of our knowledge, the JMR-WSC Scale is the first validated measure that enables us to assess the WSC of medical trainees in Japanese hospital settings.

In our study, the JMR-WSC Scale exhibited a high Cronbach’s alpha value (0.91), indicating a good level of consistency. This finding is consistent with previous studies. In Kouvonen et al.’s study, the sample consisted of workers in Finland, and the alpha value of the WSC Scale was 0.88 [25]. Odagiri et al. tested the scale’s internal consistency reliability in a study of factory employees in Japan and found a Cronbach’s alpha value of 0.90 [26]. Thus, the WSC Scale would be a very useful instrument with good internal consistency across countries and occupations.

The results of the present study confirmed that the JMR-WSC Scale has the same two-factor structure as the original WSC Scale and the Japanese version of the WSC Scale: horizontal and vertical WSC [8, 25, 26]. The horizontal component refers to coworker trust and reciprocity, whereas the vertical component refers to employees’ relationships with their supervisors [8, 38, 39]. Few studies have empirically compared the impact of these different dimensions of WSC on outcomes (e.g., well-being and health). Oksanen et al. conducted a unique study in which they separately analyzed the association between the horizontal and vertical components of WSC and new-onset depression in Finnish public sector employees and identified the importance of both components of WSC as predictors of depression in workers [8]. However, the WSC was influenced by the organization’s and country’s prevailing norms and cultures [40]. Future studies examining the impact of the two components of WSC on various outcomes in various settings, while taking cultural differences into account, would deepen our knowledge of WSC.

The instrument developed in our study can be used to measure social capital in the postgraduate medical training environments in Japan and may help prevent burnout. Since medical trainees’ burnout is currently a serious problem in Japan [41], our tool would be very relevant. Considering that previous studies have suggested a relationship between physician burnout and patient safety incidents [41, 42], our tool could also improve patient care. Furthermore, future development of other versions in other languages would be very appreciated as it will aid WSC research.

Finally, we should note some limitations of the present study. First, we have not examined other psychometric properties (e.g., convergent validity, discriminant validity, and test-retest reliability) beyond structural validity, criterion-related validity, and internal consistency reliability. In future studies, these psychometric properties should be evaluated. Second, the response rate to the questionnaire was relatively small. Online surveys frequently have response rates as low as 10% since it is challenging to have a high response rate [43], and it is not uncommon for the response rate to reach as low as 10% [44]. Referring to recent research findings [45, 46], we believe that our survey’s sample size and response rate are sufficient to provide reliable data.

Conclusions

We developed the JMR-WSC Scale and then verified its structural validity, criterion-related validity, and internal consistency reliability. The instrument would be useful in evaluating the social capital of medical trainees in postgraduate medical education in Japan, which would lead to preventing burnout and patient safety incidents.

Abbreviations

CFA:

Confirmatory factor analysis

CFI:

Comparative fit index

JMR-WSC Scale:

Japanese medical resident version of the Workplace Social Capital Scale

RMSEA:

Root mean square error of approximation

SRMR:

Standardized root mean square residual

WSC:

Workplace social capital

References

  1. Bourdieu P. Forms of Capital. In: Richardson JG, editor. Handbook of theory for the sociology of education. Westport, CT: Greenwood; 1986. pp. 241–58.

    Google Scholar 

  2. Moore S, Kawachi I. Twenty years of social capital and health research: a glossary. J Epidemiol Community Health. 2017;71(5):513–7.

    Article  Google Scholar 

  3. Xu Z, Zhang W, Zhang X, Wang Y, Chen Q, Gao B, et al. Multi-level social capital and subjective wellbeing among the elderly: understanding the effect of family, workplace, community, and society social capital. Front Public Health. 2022;10(1):772601.

    Article  Google Scholar 

  4. Firouzbakht M, Tirgar A, Oksanen T, Kawachi I, Hajian-Tilaki K, Nikpour M, et al. Workplace social capital and mental health: a cross-sectional study among iranian workers. BMC Public Health. 2018;18(1):794.

    Article  Google Scholar 

  5. Oksanen T, Suzuki E, Takao S, Vahtera J, Kivimäki M. Workplace social capital and health. In: Kawachi I, Takao S, Subramanian SV, editors. Global perspectives on social capital and health. New York: Springer; 2013. pp. 23–63.

    Chapter  Google Scholar 

  6. Suzuki E, Takao S, Subramanian SV, Komatsu H, Doi H, Kawachi I. Does low workplace social capital have detrimental effect on workers’ health? Soc Sci Med. 2010;70(9):1367–72.

    Article  Google Scholar 

  7. Kouvonen A, Oksanen T, Vahtera J, Stafford M, Wilkinson R, Schneider J, et al. Low workplace social capital as a predictor of depression: the finnish public sector study. Am J Epidemiol. 2008;167(10):1143–51.

    Article  Google Scholar 

  8. Oksanen T, Kouvonen A, Vahtera J, Virtanen M, Kivimaki M. Prospective study of workplace social capital and depression: are vertical and horizontal components equally important? J Epidemiol Community Health. 2010;64(8):684–9.

    Article  Google Scholar 

  9. Sakuraya A, Imamura K, Inoue A, Tsutsumi A, Shimazu A, Takahashi M, et al. Workplace social capital and the onset of major depressive episode among workers in Japan: a 3-year prospective cohort study. J Epidemiol Community Health. 2017;71(6):606–12.

    Article  Google Scholar 

  10. Oksanen T, Kivimäki M, Kawachi I, Subramanian SV, Takao S, Suzuki E, et al. Workplace social capital and all-cause mortality: a prospective cohort study of 28 043 public-sector employees in Finland. Am J Public Health. 2011;101(9):1742–8.

    Article  Google Scholar 

  11. Dyrbye L, Shanafelt T. A narrative review on burnout experienced by medical students and residents. Med Educ. 2016;50(1):132–49.

    Article  Google Scholar 

  12. Dyrbye LN, West CP, Satele D, Boone S, Tan L, Sloan J, et al. Burnout among U.S. medical students, residents, and early career physicians relative to the general U.S. population. Acad Med. 2014;89(3):443–51.

    Article  Google Scholar 

  13. Leep Hunderfund AN, West CP, Rackley SJ, Dozois EJ, Moeschler SM, Vaa Stelling BE, et al. Social support, social isolation, and burnout: cross-sectional study of U.S. residents exploring associations with individual, interpersonal, program, and work-related factors. Acad Med. 2022;97(8):1184–94.

    Article  Google Scholar 

  14. Rodrigues H, Cobucci R, Oliveira A, Cabral JV, Medeiros L, Gurgel K, et al. Burnout syndrome among medical residents: a systematic review and meta-analysis. PLoS ONE. 2018;13(11):e0206840.

    Article  Google Scholar 

  15. Dyrbye LN, Massie FS, Eacker A, Harper W, Power D, Durning SJ, et al. Relationship between burnout and professional conduct and attitudes among US medical students. JAMA. 2010;304(11):1173–80.

    Article  Google Scholar 

  16. Dyrbye LN, Thomas MR, Massie FS, Power DV, Eacker A, Harper W, et al. Burnout and suicidal ideation among U.S. medical students. Ann Intern Med. 2008;149(5):334–41.

    Article  Google Scholar 

  17. Jackson ER, Shanafelt TD, Hasan O, Satele DV, Dyrbye LN. Burnout and alcohol abuse/dependence among U.S. medical students. Acad Med. 2016;91(9):1251–6.

    Article  Google Scholar 

  18. Prins JT, van der Heijden FMMA, Hoekstra-Weebers JEHM, Bakker AB, van de Wiel HBM, Jacobs B, et al. Burnout, engagement and resident physicians’ self-reported errors. Psychol Health Med. 2010;14(6):654–66.

    Article  Google Scholar 

  19. West CP, Huschka MM, Novotny PJ, Sloan JA, Kolars JC, Habermann TM, et al. Association of perceived medical errors with resident distress and empathy. JAMA. 2006;296(9):1071–8.

    Article  Google Scholar 

  20. West CP, Shanafelt TD, Kolars JC. Quality of life, burnout, educational debt, and medical knowledge among internal medicine residents. JAMA. 2011;306(9):952–60.

    Article  Google Scholar 

  21. Lam LT, Lam MK, Reddy P, Wong P. Factors associated with work-related burnout among corporate employees amidst COVID-19 pandemic. Int J Environ Res Public Health. 2022;19(3):1295.

    Article  Google Scholar 

  22. Driller E, Ommen O, Kowalski C, Ernstmann N, Pfaff H. The relationship between social capital in hospitals and emotional exhaustion in clinicians: a study in four german hospitals. Int J Soc Psychiatry. 2010;57(6):604–9.

    Article  Google Scholar 

  23. Farahbod F, Goudarzvand Chegini M, Kouchakinejad Eramsadati L, Mohtasham-Amiri Z. The association between social capital and burnout in nurses of a trauma referral teaching hospital. Acta Med Iran. 2015;53(4):214–9.

    Google Scholar 

  24. Kowalski C, Ommen O, Driller E, Ernstmann N, Wirtz MA, Köhler T, et al. Burnout in nurses - the relationship between social capital in hospitals and emotional exhaustion. J Clin Nurs. 2010;19(11–12):1654–63.

    Article  Google Scholar 

  25. Kouvonen A, Kivimäki M, Vahtera J, Oksanen T, Elovainio M, Cox T, et al. Psychometric evaluation of a short measure of social capital at work. BMC Public Health. 2006;6(1):251.

    Article  Google Scholar 

  26. Odagiri Y, Ohya Y, Inoue S, Hayashi T, Uchiyama A, Takamiya A, et al. Reliability and validity of the japanese version of the Workplace Social Capital Scale. Sangyo Eiseigaku Zasshi. 2010;52(1):631.

    Google Scholar 

  27. Fujita S, Kawakami N, Ando E, Inoue A, Tsuno K, Kurioka S, et al. The association of workplace social capital with work engagement of employees in health care settings. J Occup Environ Med. 2016;58(3):265–71.

    Article  Google Scholar 

  28. Fujikawa H, Son D, Eto M. Are residents learners or workers? A historical perspective in Japan. TAPS. 2021;6(1):122–4.

    Article  Google Scholar 

  29. Ishikawa M. Relationships between overwork, burnout and suicidal ideation among resident physicians in hospitals in Japan with medical residency programmes: a nationwide questionnaire-based survey. BMJ Open. 2022;12(3):e056283.

    Article  Google Scholar 

  30. Brown TA. Confirmatory factor analysis for applied research. 2nd ed. New York: The Guilford Press; 2015.

    Google Scholar 

  31. Hooper D, Coughlan J, Mullen M. Structural equation modelling: guidelines for determining model fit. Electron J Bus Res Methods. 2008;6(1):53–60.

    Google Scholar 

  32. Idler EL, Benyamini Y. Self-rated health and mortality: a review of twenty-seven community studies. J Health Soc Behav. 1997;38(1):21–37.

    Article  Google Scholar 

  33. DeVellis RF. Scale development: theory and applications. Fourth ed. Los Angeles: SAGE; 2017.

    Google Scholar 

  34. The Comprehensive R. Archive Network. Package ‘lavaan’: The Comprehensive R Archive Network; 2022 [Available from: https://cran.r-project.org/web/packages/lavaan/lavaan.pdf.

  35. The Comprehensive R. Archive Network. Package ‘semPlot’: The Comprehensive R Archive Network; 2022 [Available from: https://cran.r-project.org/web/packages/semPlot/semPlot.pdf.

  36. The Comprehensive R. Archive Network. Package ‘ltm’: The Comprehensive R Archive Network; 2022 [Available from: https://cran.r-project.org/web/packages/ltm/ltm.pdf.

  37. The Comprehensive R. Archive Network. Package ‘psych’: The Comprehensive R Archive Network; 2022 [Available from: https://cran.r-project.org/web/packages/psych/psych.pdf.

  38. Engström K, Mattsson F, Järleborg A, Hallqvist J. Contextual social capital as a risk factor for poor self-rated health: a multilevel analysis. Soc Sci Med. 2008;66(11):2268–80.

    Article  Google Scholar 

  39. Ferlander S. The importance of different forms of social capital for health. Acta Sociol. 2016;50(2):115–28.

    Article  Google Scholar 

  40. Eguchi H, Tsutsumi A, Inoue A, Hikichi H, Kawachi I. Association of workplace social capital with psychological distress: results from a longitudinal multilevel analysis of the J-HOPE study. BMJ Open. 2018;8(12):e022569.

    Article  Google Scholar 

  41. Matsuo T, Takahashi O, Kitaoka K, Arioka H, Kobayashi D. Resident burnout and work environment. Intern Med. 2021;60(9):1369–76.

    Article  Google Scholar 

  42. Hayashino Y, Utsugi-Ozaki M, Feldman MD, Fukuhara S. Hope modified the association between distress and incidence of self-perceived medical errors among practicing physicians: prospective cohort study. PLoS ONE. 2012;7(4):e35585.

    Article  Google Scholar 

  43. Fan W, Yan Z. Factors affecting response rates of the web survey: a systematic review. Comput Hum Behav. 2010;26(2):132–9.

    Article  Google Scholar 

  44. Van Mol C. Improving web survey efficiency: the impact of an extra reminder and reminder content on web survey response. Int J Soc Res Methodol. 2016;20(4):317–27.

    Google Scholar 

  45. Fosnacht K, Sarraf S, Howe E, Peck LK. How important are high response rates for college surveys? Rev High Ed. 2017;40(2):245–65.

    Article  Google Scholar 

  46. Wu M-J, Zhao K, Fils-Aime F. Response rates of online surveys in published research: a meta-analysis. Comput Hum Behav Rep. 2022;7(1):100206.

    Article  Google Scholar 

Download references

Acknowledgements

The authors wish to thank all participants.

Funding

This study was not funded by any public, private, or nonprofit organization. Availability of data and materials: Upon reasonable request, the corresponding author can provide the data sets generated and analyzed in this study.

Author information

Authors and Affiliations

Authors

Contributions

HF, DS, and ME designed the study. HF analyzed the data and drafted the manuscript. All authors critically reviewed the manuscript. The final version of the manuscript was then approved by the authors.

Corresponding author

Correspondence to Hirohisa Fujikawa.

Ethics declarations

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki. All methods were performed in accordance with relevant guidelines. All participants checked the consent box at the beginning of the questionnaire to reveal they are informed consent to participate in this study. The Institutional Review Board of the University of Tokyo granted ethical approval (2022062NI).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fujikawa, H., Son, D. & Eto, M. Cultural adaptation and validation of Japanese medical resident version of the workplace social capital scale: a cross-sectional study. BMC Med Educ 23, 487 (2023). https://doi.org/10.1186/s12909-023-04469-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12909-023-04469-w

Keywords