Skip to main content

ORIGINAL RESEARCH article

Front. Psychol., 23 June 2022
Sec. Personality and Social Psychology

Validation of the Japanese Big Five Scale Short Form in a University Student Sample

Rie Toyomoto
Rie Toyomoto1*Masatsugu SakataMasatsugu Sakata1Kazufumi YoshidaKazufumi Yoshida1Yan LuoYan Luo1Yukako NakagamiYukako Nakagami2Taku IwamiTaku Iwami2Shuntaro AokiShuntaro Aoki3Tomonari IrieTomonari Irie4Yuji SakanoYuji Sakano5Hidemichi SugaHidemichi Suga6Michihisa SumiMichihisa Sumi7Hiroshi IchikawaHiroshi Ichikawa8Takafumi WatanabeTakafumi Watanabe9Aran TajikaAran Tajika1Teruhisa UwatokoTeruhisa Uwatoko10Ethan Sahker,Ethan Sahker1,11Toshi A. FurukawaToshi A. Furukawa1
  • 1Department of Health Promotion and Human Behavior, School of Public Health, Kyoto University Graduate School of Medicine, Kyoto, Japan
  • 2Agency for Health, Safety and Environment, Kyoto University Health Service, Kyoto, Japan
  • 3Center for Medical Education and Career Development, Fukushima Medical University, Fukushima, Japan
  • 4Department of Psychology and Counseling, School of Education and Culture, Hokusho University, Ebetsu, Japan
  • 5Department of Clinical Psychology, Goryokai Medical Corporation, Sapporo, Japan
  • 6Department of Social Welfare, Ryukoku University Junior College, Kyoto, Japan
  • 7Ritsumeikan Medical Service Center, Kyoto, Japan
  • 8Department of Medical Life Systems, Faculty of Life and Medical Sciences, Doshisha University, Kyoto, Japan
  • 9Department of Psychiatry and Cognitive-Behavioral Medicine, Nagoya City University Graduate School of Medical Science, Nagoya, Japan
  • 10Department of Psychiatry, Kyoto University Hospital, Kyoto, Japan
  • 11Medical Education Center, Kyoto University Graduate School of Medicine, Kyoto, Japan

The Japanese Big Five Scale Short Form (JBFS-SF), a 29-item self-report scale, has recently been used to measure the Big Five personality traits. However, the scale lacks psychometric validation. This study examined the validity and reliability of the JBFS-SF with data collected from 1,626 Japanese university students participating in a randomized controlled clinical trial. Structural validity was tested with exploratory and confirmatory factor analysis and measurement invariance tests were conducted across sex. Internal consistency was evaluated with McDonald’s omega. Additionally, construct validity was estimated across factors using the PHQ-9, GAD-7, AQ-J-10, and SSQ. EFA results showed that the JBFS-SF can be classified according to the expected five-factor structure, while three items had small loadings. Therefore, we dropped these three items and tested the reliability and validity of the 26-item version. CFA results found that a 26-item JBFS-FS has adequate structural validity (GFI = 0.907, AGFI = 0.886, CFI = 0.907, and RMSEA = 0.057). The omega of each factor was 0.74–0.85. Each JBFS-SF factor was specifically correlated with the PHQ-9, GAD-7, and SSQ. This research has shown that the JBFS-SF can be a clinically useful measure for assessing personality characteristics.

Introduction

The Big Five Model (Goldberg, 1993) and the Five-Factor Model (McCrae and Costa, 1987) are two of the foremost theories for classifying personality traits. The models consist of five basic dimensions: Openness to experience (e.g., tendency to be creative, intellectually curious, and emotionally open), Conscientiousness (e.g., self-disciplined, organized, and reliable), Extraversion (e.g., energetic, enthusiastic, and socially outgoing), Agreeableness (e.g., thoughtful, kind, and modest), and Neuroticism (e.g., emotionally unstable and experiencing negative emotions). It has been widely used and had a significant impact on the research of individual personality traits. Previous studies have shown that these personality traits are associated with various individual health-related outcomes including wellbeing, stress responses, depression, and anxiety (Soto, 2019). Personality traits are also reported to be related with a broad range of interpersonal and social variables, such as autistic traits (Lodi-Smith et al., 2019) and perceived social support (Barańczuk, 2019). Furthermore, personality traits can influence treatment adherence and outcomes (Maj et al., 2020).

Based on the Big Five Model or Five-Factor Model, various scales, such as the 240-item Revised NEO Personality Inventory (NEO-PI-R; Costa and McCrae, 1992), the 60-item NEO Five-Factor Inventory (NEO-FFI; Costa and McCrae, 1992), and the 44-item Big Five Inventory (BFI-44; John and Srivastava, 1999), have been developed. However, these scales have many items, which are time-consuming and may cause stress and exhaustion leading to incompleteness or inaccuracy (Burisch, 1984). In recent years, shorter versions have been developed, such as the 10-item Big Five Inventory (BFI-10; Rammstedt and John, 2007) and the 20-item Mini-IPIP (Donnellan et al., 2006). Short versions can reduce the burden on the respondent, making it easier to use in conjunction with other measures, and can also lead to more accurate responses (Burisch, 1984). However, such advantages may be accompanied by a trade-off with psychometric weaknesses. Additionally, the short-form instruments listed above lack the cross-cultural support that the full-scale versions previously achieved.

In Japan, there are two types of scales: those translated from other countries’ scales [e.g., the 240-item Japanese NEO-PI-R (Shimonaka et al., 1998)] and those adapted to Japanese culture [e.g., the 150-item Five-Factor Personality Questionnaire (FFPQ; FFPQ Kenkyukai, 2002)] and the 60-item Japanese Big Five Scale (Wada, 1996).

The Japanese Big Five Scale (JBFS) was developed using the Adjective Check List (300 items; Gough and Heilbrun, 1983) and consists of 12 items for each factor. The JBFS has the advantage of being in adjective form, which makes the structure more stable than in sentence form (Gough and Heilbrun, 1983). To reduce the burden on respondents, the JBFS was shortened to 29 items using Item Response Theory (IRT) and reported to be highly correlated with the original JBFS (0.93–0.95; Namikawa et al., 2012). The Big Five Scale Short Form (JBFS-SF) has recently been used for the general population (Suzuki et al., 2015; Yoshino et al., 2021) and university students (Fukase et al., 2021; Hatabu et al., 2021). However, the reliability and validity of the JBFS-SF remain questionable because a part of the original scale (60 items, 7-point scale) was substituted for the validation of the short form, and the JBFS-SF itself (29 items, 5-point scale) has not been used. In addition, correlations with the JBSF-SF and NEO-FFI were low for some subscales (Openness 0.21, Agreeableness 0.46, Conscientiousness 0.52, Neuroticism 0.70, Extraversion 0.74; Namikawa et al., 2012).

In the present study, we fill the gap in the literature by investigating the psychometric properties of the JBSF-SF. We have included this JBFS-SF in a battery of psychological tests used for a clinical trial with university students and hereby aim to examine its reliability and validity.

Materials and Methods

Participants and Procedures

This study is based on data from the Healthy Campus Trial (HCT), which was a fully factorial randomized controlled trial to optimize smartphone cognitive behavioral therapy (CBT) among healthy university students. The HCT began in September 2018 and the final participant was enrolled in June 2021. Participants were recruited via posters, flyers, websites, and social networking services. Participants were included in the HCT if they were 18- to 39-year-old junior college, undergraduate, or graduate students from five universities in Japan, understood written Japanese, had a score of 0 to 14 on the PHQ-9, and were not receiving any mental health treatment at enrolment. Those scoring 15 or above were not eligible because such high scores indicate a high likelihood of clinical depression (Kroenke et al., 2001). Participants attended a group orientation meeting and provided written informed consent. After March 2020, due to the COVID-19 pandemic, we changed from face-to-face to online orientation meetings. Details of the trial are described in the protocol (Uwatoko et al., 2018). This trial is registered with UMIN-CTR Clinical Trial, CTR-000031307. Ethical approval was obtained from the Kyoto University School of Medicine.

We divided our sample into two groups. Sample 1 included 845 university students who participated in the HCT between September 2018 and May 2020 when half of the planned sample size was reached. Sample 2 included 781 students between June 2020 and June 2021. Sample 1 was used for the primary analysis and Sample 2 for a confirmatory factor analysis of the shortened 26-item JBFS.

Measurement

All data were collected online via the trial website and smartphone application. We used a system that would not allow them to proceed unless they completed the responses, thus there were no missing values except for the Social Support Questionnaire.

The Japanese Big Five Scale Short Form

The Japanese Big Five Scale Short Form (JBFS-SF; Namikawa et al., 2012) is a brief version of the original 60-item JBFS (Wada, 1996) for assessing personality traits. The scale consists of 29 items on five personality trait factors: Openness to experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. The items are composed of single adjectives in the adjective checklist form (Gough and Heilbrun, 1983), which avoids ambiguity and multiple meanings. Though the original JBFS-SF is a 5-point Likert scale from 1 (untrue of me) and 5 (true of me), we changed it to a 4-point scale for the following reasons: (1) to avoid a central tendency of odd-numbered Likert scales, and (2) to reduce the burden on respondents. A higher average score indicates a higher level of the self-reported trait. It has been reported that there is a high correlation (rs = 0.92–0.95) between each factor in the original and short versions (Namikawa et al., 2012).

The Patient Health Questionnaire-9

The Patient Health Questionnaire-9 (PHQ-9; Kroenke et al., 2001) is a self-reported questionnaire for screening and measuring severity of depression, based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) for major depressive disorder. It is a 9-item scale, each rated from 0 (not at all) to 3 (nearly every day). The reliability and validity of the original scale and the Japanese version have been demonstrated (Kroenke et al., 2001; Muramatsu et al., 2018). Previous studies showed that high neuroticism, which refers to the persistent tendency to experience negative emotions, is strongly associated with depressive symptoms, and we expected a positive correlation between PHQ-9 and Neuroticism (Kotov et al., 2010; Hakulinen et al., 2015; Soto, 2019).

The Generalized Anxiety Disorder Screener-7

The Generalized Anxiety Disorder Screener-7 (GAD-7; Spitzer et al., 2006) is a self-reported questionnaire for measuring anxiety. The GAD-7 comprises 7 items rated on a 3-point scale, ranging from 0 (not at all) to 3 (nearly every day). The validity and reliability of the original scale (Spitzer et al., 2006) and the Japanese version (Doi et al., 2018) have been established. Neuroticism has a robust association with anxiety, hence we assumed that the GAD-7 and Neuroticism would be positively correlated (Kotov et al., 2010; Watson and Naragon-Gainey, 2014; Soto, 2019).

The Autism Spectrum Quotient Japanese Version

The Autism Spectrum Quotient Japanese Version (AQ-J-10) is a short version of the Autism Spectrum Quotient measuring autistic traits (Baron-Cohen et al., 2001). The reliability and validity of the Japanese original version and its shortened version have been verified (Kurita et al., 2005). A recent meta-analysis indicated ASD characteristics were negatively associated with all Big Five personality traits, especially Extraversion (Lodi-Smith et al., 2019). Therefore, we expected a negative relationship between Extraversion and the AQ-J-10.

The Social Support Questionnaire

The Social Support Questionnaire (SSQ) has six items measuring the quality and quantity of social support (Sarason et al., 1987). The reliability and validity of the original scale and the Japanese version have been demonstrated (Sarason et al., 1987; Furukawa et al., 1999). A previous meta-analysis shows that Extraversion was positively associated with perceived support received, and we expected that the SSQ and Extraversion would be positively correlated (Barańczuk, 2019). We failed to include the second and fourth items from the original version among the first 917 participants due to a clerical error: we corrected the questionnaire after the 917th student. Therefore, when calculating correlation coefficients with the JBFS-SF in Sample 1, we substituted the subscale scores of the original six items by the average of the four items.

Statistical Analysis

Structural Validity

In Sample 1, we assessed the structural validity of the JBFS-SF by conducting an exploratory factor analysis (EFA) using the psych package (Version 2.0.12) in R (Version 4.0.3; Revelle, 2017). EFA was performed with the principal factor method and Varimax rotation and the number of factors extracted was determined by a Scree test and the Kaiser criterion. We set the threshold for meaningful factor loadings at 0.4 for interpretative purposes (Stevens, 2012). If items were found to have small loadings of less than 0.4, we would exclude them and examine the validity of the scale composed of the remaining items.

In Sample 2, we conducted confirmatory factor analyses (CFA) to examine the model fit of the original and revised versions, first for the original version with all the items, and second for the revised version excluding the items which had loadings less than 0.4. We introduced covariant relationships where appropriate to improve the model fit. We used the lavaan package (version 0.6-8) in R to check the goodness-of-fit of the factor structure, goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA; Rosseel, 2012). It is recommended that the criteria for a good model fit are GFI ≥ 0.95, AGFI ≥0.90, CFI ≥ 0.97, and RMSEA ≤0.05, and an acceptable model fit is GFI ≥ 0.90, AGFI ≥0.85, CFI ≥ 0.95, and RMSEA ≤0.08 (Schermelleh-Engel et al., 2003). We used AMOS 27 (IBM SPSS Statistics, Chicago, Illinois, United States) for graphics. Additionally, we conducted measurement invariance tests across sex using a series of multi-group CFAs, considering different tendencies of personality traits by sex (Schmitt et al., 2017). We compared the fit between four models (configural invariance, metric invariance, scalar invariance, and error variance invariance) using the likelihood ratio test and examined the differences in the comparative fit index (ΔCFI) and the Tucker–Lewis index (ΔTLI), which is not influenced by sample size. Non-significant p-values (p ≥ 0.05) in the chi-square difference test indicated that measurement invariance was acceptable (Bontempo and Hofer, 2007). ΔCFIs ≤ −0.01 and ΔTLIs ≤ −0.01 were interpreted as evidence of non-invariance (Cheung and Rensvold, 2002).

Internal Consistency Reliability

In Sample 1, we examined the internal consistency of the JBFS-SF by calculating McDonald’s omega (McDonald, 1999). We calculated omega rather than Cronbach’s alpha because many methodological studies suggest that Cronbach’s alpha has problems arising from unrealistic assumptions, such as one-dimensionality and homogeneity of scales (McNeish, 2018).

Construct Validity

In Sample 1, we calculated Pearson’s correlation coefficients between each factor of the JBFS-SF with the PHQ-9, GAD-7, AQ-J-10, and SSQ to examine our expectations mentioned in the “Measurement” section.

Results

Sample Characteristics

Table 1 summarizes the demographic and baseline characteristics of both samples. In Sample 1 (N = 845), the mean age (SD) was 22.0 (3.04), slightly more than half were women (53.4%), and most were in bachelor’s (70.1%) or master’s programs (21.7%). In Sample 2 (N = 781), the mean age (SD) was 21.0 (2.84), with more women (61.6%) and more students in bachelor’s programs (83.5%) than in Sample 1.

TABLE 1
www.frontiersin.org

Table 1. Demographic and baseline characteristics.

Validation of the 29-Item JBFS-SF

Structural Validity

As shown in Table 2, the EFA in Sample 1 extracted five factors for the JBFS-SF and the factor loadings for items of each factor were highest among the items as per the original scale: 0.359–0.760 for Conscientiousness, 0.613–0.831 for Extraversion, 0.358–0.761 for Agreeableness, 0.390–0.675 for Openness to experience, and 0.500–0.798 for Neuroticism. Item 25 of the JBFS-SF had an effect across the two factors of Conscientiousness and Agreeableness, and three items (items 19: sharp-witted, 25: self-centered, and 28: kind) had loadings of less than 0.4. Figure 1 shows the Scree plot. The sixth component has an Eigenvalue smaller than 1.0 and the plot flattens thereafter. We therefore decided to set the number of factors to extract at five (Kaiser, 1960). The results of CFA in Sample 2 assuming a covariant relationship between some error variables showed that the GFI = 0.856, AGFI = 0.827, CFI = 0.839, and RMSEA = 0.071.

TABLE 2
www.frontiersin.org

Table 2. Factor loadings of the 29-item Big Five Scale Items with Varimax Rotation.

FIGURE 1
www.frontiersin.org

Figure 1. Scree plot of exploratory factor analysis.

Validation of the Shortened 26-Item JBFS-SF

Three items (items 19, 25, and 28) had small or ambiguous loadings and were excluded. The following examines the 26-item JBFS-SF.

Structural Validity

Figure 2 indicates the results of the CFA assuming a covariant relationship between some error variables in Sample 2 (GFI = 0.907, AGFI = 0.886, CFI = 0.907, and RMSEA = 0.057). With multiple group structural equation modeling by sex, the result of CFA shows that the GFI = 0.875, AGFI = 0.862, CFI = 0.897, and RMSEA = 0.041. Table 3 shows the fit between four levels, assuming configural invariance, metric invariance, scalar invariance, or error variance invariance. Both ΔCFI and ΔTLI were ≤ 0.01 at all levels, indicating that there was no significant difference by sex.

FIGURE 2
www.frontiersin.org

Figure 2. Confirmatory factor analysis of the five-factor structure of the shortened 26-item JBFS-SF (N = 781). O; openness, C; conscientiousness, E; extraversion, A; agreeableness, N; neuroticism.

TABLE 3
www.frontiersin.org

Table 3. Measurement invariance tests across sex.

Internal Consistency

The results of McDonald’s omega of each Big Five factor of the 26-item JBFS-SF were 0.74 for Openness to experience, 0.78 for Neuroticism, 0.82 for Agreeableness, 0.84 for Conscientiousness, and 0.85 for Extraversion.

Construct Validity

Table 4 shows the correlation coefficients for each Big Five factor of the 26-item JBFS-SF with depression, anxiety, autism spectrum, and social support. Within the Big Five factors, there was a weak positive correlation between Extraversion and Openness to experience. Neuroticism had a weak positive correlation with depressive symptoms and a moderate positive correlation with anxiety symptoms. The autistic trait subscale of the AQ-J-10 was not strongly correlated with any of the factors. As for social support, there was a weak positive correlation between the quantity of Social Support Questionnaire and Extraversion.

TABLE 4
www.frontiersin.org

Table 4. Pearson’s Correlation between the shortened 26-item JBFS-SF, the PHQ-9, the GAD-7, the AQ-J-10, and the SSQ in Sample 1 (N = 845).

Discussion

This study examined the structure and validity of the JBFS-SF in a Japanese university student sample. We examined the 26-item version, removing 3 items with small or ambiguous loadings in the EFA. The results showed that this short version can act as a reliable and valid assessment of personality traits, simultaneously reducing the time and burden required to complete an assessment.

The results of the EFA showed that 29 items can be classified according to the expected five-factor structure, but three items had small loadings or moderate secondary loadings. Therefore, we dropped these three items and tested the reliability and validity of a 26-item version. In the present study, the CFA results showed that the 26-item JBFS-FS has adequate structural validity. Nevertheless, we could not compare the goodness-of-fit of the factor structure results with existing studies because a CFA has not previously been conducted.

Omega coefficients suggested good internal consistency. These results add to the evidence supporting the validity and reliability of the JBFS-FS. Furthermore, the results of multiple group structural equation modeling by sex indicated that the 26-item JBFS-SF had strict measurement invariance across genders.

In addition, we examined construct validity using associations between each Big Five Scale factor and potential outcomes of depression, anxiety, autism spectrum, and social support. First, we identified a positive correlation between Extraversion and Openness to experience of the Big Five factors, which was consistent with the results of the original Japanese version (Wada, 1996) and the short version (Namikawa et al., 2012). Second, we found a positive correlation between Neuroticism, the PHQ-9, and the GAD-7 scores. These relationships are consistent with previous findings showing that Neuroticism is strongly linked to depression and anxiety (Kotov et al., 2010; Hakulinen et al., 2015; Lyon et al., 2021). Third, the positive correlation between Extraversion and social support is consistent with a previous meta-analysis (Barańczuk, 2019). Third, while previous studies (Kanai et al., 2011; Strunz et al., 2015; Schwartzman et al., 2016) have commonly suggested positive correlations between Neuroticism and autistic traits, or negative correlations between Extraversion/Agreeableness and autistic traits, we did not find these features in the present study. Not observing such associations reported in the literature may be due to our sample being limited to basically healthy university students having relatively narrow variability in autistic traits. Previous studies used potentially sharper contrasts by comparing clinical samples with the healthy controls. Alternatively, this may be related to differences between the scales based on the Big Five Model. As noted in previous studies (Ohnogi, 2004; Namikawa et al., 2012), a comprehensive discussion on personality traits scales is required in the future.

Recently ultra-short scales measuring the Big Five personality traits have been reported in Japan (Oshio et al., 2012). How it compares with BFS-SF has not been examined.

Limitations and Future Directions

The present study has some limitations of note. First, the participants in this study were university students below the threshold for clinical depression. Sample selection can have an impact on the results generated using some psychometric techniques, such as the EFA (Gaskin et al., 2017). Nevertheless, we were interested in the personality of university students. The sample was drawn from five different universities, both public and private in the second largest metropolitan area in Japan. We therefore argue that our sample would be fairly representative of university students in Japan. Results are not readily generalizable to younger adults in general, let alone the general population. Additionally, we did not compare the short form with the original BFS, NEO-FFI, or FFPQ. This limits the generalizability of our findings to only the short-form version.

Conclusion

The 26-item JBFS-SF demonstrated adequate reliability and validity among Japanese university students when excluding three items with ambiguous loadings. From a practical point of view, this research adds evidence supporting the short form as a useful measure for assessing personality characteristics cross-culturally. Findings also showed that the Big five personality traits, as measured with this short form, may be used as a potential predictor and effect modifier of psychological symptoms in future research among university student populations.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The Ethics Committee of Kyoto University School of Medicine have approved this study (Protocol # C1357). All participants provided written informed consent to participate in this study.

Author Contributions

TF, SA, TIr, YS, TIw, TU, YL, and MSa designed this trial. RT, MSa, KY, YL, YN, HS, MSu, HI, TW, AT, TU, ES, and TF acquired the data. RT and MSa conducted the statistical analyses. RT and TF wrote the first draft of the manuscript. All authors contributed to the article and approved the submitted version.

Funding

This research was funded by grants from Japan Agency for Medical Research and Development (AMED; grant number 20dk0307085), Japan Society for the Promotion of Science (JSPS; grant number 18K18643, 21K03049, 19F19110, and P19110), Suzuken Memorial Foundation, KDDI Foundation and Pfizer Health Research Foundation.

Conflict of Interest

YS was employed by Goryokai Medical Corporation. TF reports grants and personal fees from Mitsubishi-Tanabe, personal fees from SONY, grants, and personal fees from Shionogi, COI outside the submitted work; in addition, TF has a patent 2020-548587 concerning smartphone CBT apps pending, and intellectual properties for Kokoro-app licensed to Mitsubishi-Tanabe. MSa reports personal fees from SONY outside the submitted work. AT has received lecture fees from Sumitomo Dainippon Pharma, Eisai, Janssen Pharmaceutical, Meiji-Seika Pharma, Mitsubishi Tanabe Pharma, Otsuka, and Takeda Pharmaceutical.

The remaining 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.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

Barańczuk, U. (2019). The five factor model of personality and social support: a meta-analysis. J. Res. Pers. 81, 38–46. doi: 10.1016/j.jrp.2019.05.002

CrossRef Full Text | Google Scholar

Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., and Clubley, E. (2001). The autism-spectrum quotient (AQ): evidence from Asperger syndrome/high-functioning autism, males and females, scientists and mathematicians. J. Autism Dev. Disord. 31, 5–17. doi: 10.1023/A:1005653411471

CrossRef Full Text | Google Scholar

Bontempo, D. E., and Hofer, S. M. (2007). “Assessing factorial invariance in cross-sectional and longitudinal studies,” in Oxford Handbook of Methods in Positive Psychology. eds. A. D. Ong and M. H. M. van Dulmen (London: Oxford University Press), 153–175.

Google Scholar

Burisch, M. (1984). Approaches to personality inventory construction: A comparison of merits. Am. Psychol. 39, 214–227. doi: 10.1037/0003-066X.39.3.214

CrossRef Full Text | Google Scholar

Cheung, G. W., and Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Struct. Equ. Model A Multidiscip. J. 9, 233–255. doi: 10.1207/S15328007SEM0902_5

CrossRef Full Text | Google Scholar

Costa, P. T. J., and McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) Professional Manual. Odessa, FL: Psychological Assessment Resources.

Google Scholar

Doi, S., Ito, M., Takebayashi, Y., Muramatsu, K., and Horikoshi, M. (2018). Factorial validity and invariance of the 7-item generalized anxiety disorder scale (GAD-7) among populations with and without self-reported psychiatric diagnostic status. Front. Psychol. 9, 1–6. doi: 10.3389/fpsyg.2018.01741

CrossRef Full Text | Google Scholar

Donnellan, M. B., Oswald, F. L., Baird, B. M., and Lucas, R. E. (2006). The mini-IPIP scales: tiny-yet-effective measures of the big five factors of personality. Psychol. Assess. 18, 192–203. doi: 10.1037/1040-3590.18.2.192

PubMed Abstract | CrossRef Full Text | Google Scholar

FFPQ Kenkyukai (2002). Kaitei FFPQ (5 inshi seikaku kensa) manual [FFPQ (five-factor personality test) manual]. Kitaohji Shobo.

Google Scholar

Fukase, Y., Kamide, N., Murayama, N., Kawamura, A., Ichikura, K., Shiba, Y., et al. (2021). The influence of ageism on stereotypical attitudes among allied health students in Japan: a group comparison design. BMC Med. Educ. 21, 1–7. doi: 10.1186/s12909-020-02439-0

CrossRef Full Text | Google Scholar

Furukawa, T. A., Harai, H., Hirai, T., Kitamura, T., and Takahashi, K. (1999). Social Support Questionnaire among psychiatric patients with various diagnoses and normal controls. Soc. Psychiatry. Psychiatr. Epidemiol. 34, 216–222. doi: 10.1007/s001270050136

CrossRef Full Text | Google Scholar

Gaskin, C. J., Lambert, S. D., Bowe, S. J., and Orellana, L. (2017). Why sample selection matters in exploratory factor analysis: implications for the 12-item World Health Organization disability assessment schedule 2.0. BMC Med. Res. Methodol. 17:40. doi: 10.1186/s12874-017-0309-5

CrossRef Full Text | Google Scholar

Goldberg, L. R. (1993). The structure of phenotypic personality traits. Am. Psychol. 48, 26–34. doi: 10.1037/0003-066X.48.1.26

CrossRef Full Text | Google Scholar

Gough, H. G., and Heilbrun, A. B. (1983). The Adjective Check List Manual. Palo Alto, CA: Consulting Psychologists Press.

Google Scholar

Hakulinen, C., Elovainio, M., Pulkki-Råback, L., Virtanen, M., Kivimäki, M., and Jokela, M. (2015). PERSONALITY and DEPRESSIVE SYMPTOMS: INDIVIDUAL PARTICIPANT META-ANALYSIS of 10 COHORT STUDIES. Depress. Anxiety 32, 461–470. doi: 10.1002/da.22376

PubMed Abstract | CrossRef Full Text | Google Scholar

Hatabu, A., Mao, X., Zhou, Y., Kawashita, N., Wen, Z., Ueda, M., et al. (2021). Knowledge, attitudes, and practices toward COVID-19 among university students in Japan and associated factors: an online cross-sectional survey. PLoS One 15:e0244350. doi: 10.1371/journal.pone.0244350

PubMed Abstract | CrossRef Full Text | Google Scholar

John, O. P., and Srivastava, S. (1999). “The big five trait taxonomy: history, measurement, and theoretical perspectives,” in Handbook of Personality: Theory and Research. 2nd Edn. eds. L. A. Pervin and O. P. John (New York, NY, US: Guilford Press), 102–138.

Google Scholar

Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educ. Psychol. Meas. 20, 141–151. doi: 10.1177/001316446002000116

CrossRef Full Text | Google Scholar

Kanai, C., Iwanami, A., Hashimoto, R., Ota, H., Tani, M., Yamada, T., et al. (2011). Clinical characterization of adults with Asperger’s syndrome assessed by self-report questionnaires based on depression, anxiety, and personality. Res. Autism. Spectr. Disord. 5, 1451–1458. doi: 10.1016/j.rasd.2011.02.005

CrossRef Full Text | Google Scholar

Kotov, R., Gamez, W., Schmidt, F., and Watson, D. (2010). Linking “big” personality traits to anxiety, depressive, and substance use disorders: a meta-analysis. Psychol. Bull. 136, 768–821. doi: 10.1037/a0020327

PubMed Abstract | CrossRef Full Text | Google Scholar

Kroenke, K., Spitzer, R. L., and Williams, J. B. W. (2001). The PHQ-9: validity of a brief depression severity measure. J. Gen. Intern. Med. 16, 606–613. doi: 10.1046/j.1525-1497.2001.016009606.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Kurita, H., Koyama, T., and Osada, H. (2005). Autism-Spectrum quotient-Japanese version and its short forms for screening normally intelligent persons with pervasive developmental disorders. Psychiatry Clin. Neurosci. 59, 490–496. doi: 10.1111/j.1440-1819.2005.01403.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Lodi-Smith, J., Rodgers, J. D., Cunningham, S. A., Lopata, C., and Thomeer, M. L. (2019). Meta-analysis of big five personality traits in autism spectrum disorder. Autism 23, 556–565. doi: 10.1177/1362361318766571

PubMed Abstract | CrossRef Full Text | Google Scholar

Lyon, K., Elliott, R., Ware, K., Juhasz, G., and Brown, L. (2021). Associations between facets and aspects of big five personality and affective disorders: A systematic review and best evidence synthesis. J. Affect. Disord. 288, 175–188. doi: 10.1016/j.jad.2021.03.061

CrossRef Full Text | Google Scholar

Maj, M., Stein, D. J., Parker, G., Zimmerman, M., Fava, G. A., De Hert, M., et al. (2020). The clinical characterization of the adult patient with depression aimed at personalization of management. World Psych. 19, 269–293. doi: 10.1002/wps.20771

PubMed Abstract | CrossRef Full Text | Google Scholar

McCrae, R. R., and Costa, P. T. (1987). Validation of the five-factor model of personality across instruments and observers. J. Person. Soc. Psychol. 52, 81–90. doi: 10.1037/0022-3514.52.1.81

CrossRef Full Text | Google Scholar

McDonald, R. P. (1999). Test Theory: A Unified Approach. Mahwah, NJ: Erlbaum.

Google Scholar

McNeish, D. (2018). Thanks coefficient alpha, we’ll take it from here. Psychol. Methods 23, 412–433. doi: 10.1037/met0000144

PubMed Abstract | CrossRef Full Text | Google Scholar

Muramatsu, K., Miyaoka, H., Kamijima, K., Muramatsu, Y., Tanaka, Y., Hosaka, M., et al. (2018). Performance of the Japanese version of the patient health Questionnaire-9 (J-PHQ-9) for depression in primary care. Gen. Hosp. Psychi. 52, 64–69. doi: 10.1016/j.genhosppsych.2018.03.007

PubMed Abstract | CrossRef Full Text | Google Scholar

Namikawa, T., Tani, I., Wakita, T., Kumagai, R., Nakane, A., and Noguchi, H. (2012). Development of a short form of the Japanese big- five scale, and a test of its reliability and validity. Shinrigaku Kenkyu 83, 91–99. doi: 10.4992/jjpsy.83.91

PubMed Abstract | CrossRef Full Text | Google Scholar

Ohnogi, H. (2004). A correlational analysis of three Japanese versions of five-factor model (FFM) personality inventory. Japanese J. Personal. 12, 82–89. doi: 10.2132/personality.12.82

CrossRef Full Text | Google Scholar

Oshio, A., Abe, S., and Pino, C. (2012). Development, reliability, and validity of the Japanese version of ten item personality inventory (TIPI-J). Japanese J. Personal. 21, 40–52. doi: 10.2132/personality.21.40

CrossRef Full Text | Google Scholar

Rammstedt, B., and John, O. P. (2007). Measuring personality in one minute or less: a 10-item short version of the big five inventory in English and German. J. Res. Pers. 41, 203–212. doi: 10.1016/j.jrp.2006.02.001

CrossRef Full Text | Google Scholar

Revelle, W. R. (2017). psych: Procedures for Personality and Psychological Research. Northwestern University. Software.

Google Scholar

Rosseel, Y. (2012). An R package for structural equation modeling. J. Stat. Softw. 48:i02. doi: 10.18637/jss.v048.i02

CrossRef Full Text | Google Scholar

Sarason, I. G., Sarason, B. R., Shearin, E. N., and Pierce, G. R. (1987). A brief measure of social Support: practical and theoretical implications. J. Soc. Pers. Relat. 4, 497–510. doi: 10.1177/0265407587044007

CrossRef Full Text | Google Scholar

Schermelleh-Engel, K., Moosbrugger, H., and Müller, H. (2003). Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures. Methods Psychol. Res. 8, 23–74.

Google Scholar

Schmitt, D. P., Long, A. E., McPhearson, A., O’Brien, K., Remmert, B., and Shah, S. H. (2017). Personality and gender differences in global perspective. Int. J. Psychol. 52, 45–56. doi: 10.1002/ijop.12265

PubMed Abstract | CrossRef Full Text | Google Scholar

Schwartzman, B. C., Wood, J. J., and Kapp, S. K. (2016). Can the five factor model of personality account for the variability of autism symptom expression? Multivariate approaches to behavioral Phenotyping in adult autism Spectrum disorder. J. Autism. Dev. Disord. 46, 253–272. doi: 10.1007/s10803-015-2571-x

PubMed Abstract | CrossRef Full Text | Google Scholar

Shimonaka, Y., Nakazato, K., Gondo, Y., and Takayama, M. (1998). Construction and factorial validity of the Japanese NEO-PI-R. Japanese J. Personal. 6, 138–147. doi: 10.2132/jjpjspp.6.2_138

CrossRef Full Text | Google Scholar

Soto, C. J. (2019). How replicable are links Between personality traits and consequential life outcomes? The life outcomes of personality replication project. Psychol. Sci. 30, 711–727. doi: 10.1177/0956797619831612

PubMed Abstract | CrossRef Full Text | Google Scholar

Spitzer, R. L., Kroenke, K., Williams, J. B. W., and Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch. Intern. Med. 166, 1092–1097. doi: 10.1001/archinte.166.10.1092

PubMed Abstract | CrossRef Full Text | Google Scholar

Stevens, J. P. (2012). Applied Multivariate Statistics for the Social Sciences. United States: Routledge.

Google Scholar

Strunz, S., Westphal, L., Ritter, K., Heuser, I., Dziobek, I., and Roepke, S. (2015). Personality pathology of adults With autism Spectrum disorder Without accompanying intellectual impairment in comparison to adults With personality disorders. J. Autism. Dev. Disord. 45, 4026–4038. doi: 10.1007/s10803-014-2183-x

PubMed Abstract | CrossRef Full Text | Google Scholar

Suzuki, Y., Tamesue, D., Asahi, K., and Ishikawa, Y. (2015). Grit and work engagement: a cross-sectional study. PLoS One 10:e0137501. doi: 10.1371/journal.pone.0137501

PubMed Abstract | CrossRef Full Text | Google Scholar

Uwatoko, T., Luo, Y., Sakata, M., Kobayashi, D., Sakagami, Y., Takemoto, K., et al. (2018). Healthy campus trial: a multiphase optimization strategy (MOST) fully factorial trial to optimize the smartphone cognitive behavioral therapy (CBT) app for mental health promotion among university students: study protocol for a randomized controlled trial. Trials 19, 1–16. doi: 10.1186/s13063-018-2719-z

CrossRef Full Text | Google Scholar

Wada, S. (1996). Construction of the big five scales of personality trait terms and concurrent validity with NPI [in Japanese]. Jpn. J. Psychol. 67, 61–67. doi: 10.4992/jjpsy.67.61

CrossRef Full Text | Google Scholar

Watson, D., and Naragon-Gainey, K. (2014). Personality, emotions, and the emotional disorders. Clin. Psychol. Sci. J. Assoc. Psychol. Sci. 2, 422–442. doi: 10.1177/2167702614536162

PubMed Abstract | CrossRef Full Text | Google Scholar

Yoshino, S., Shimotsukasa, T., Hashimoto, Y., and Oshio, A. (2021). The association between personality traits and hoarding behavior during the COVID-19 pandemic in Japan. Pers. Individ. Dif. 179:110927. doi: 10.1016/j.paid.2021.110927

PubMed Abstract | CrossRef Full Text | Google Scholar

Keywords: personality, psychometric properties, five-factor model, adolescence, brief measures

Citation: Toyomoto R, Sakata M, Yoshida K, Luo Y, Nakagami Y, Iwami T, Aoki S, Irie T, Sakano Y, Suga H, Sumi M, Ichikawa H, Watanabe T, Tajika A, Uwatoko T, Sahker E and Furukawa TA (2022) Validation of the Japanese Big Five Scale Short Form in a University Student Sample. Front. Psychol. 13:862646. doi: 10.3389/fpsyg.2022.862646

Received: 26 January 2022; Accepted: 06 May 2022;
Published: 23 June 2022.

Edited by:

Sören Kliem, Ernst-Abbe-Hochschule Jena, Germany

Reviewed by:

Merten Neumann, Criminological Research Institute of Lower Saxony, Germany
Johannes Beller, Hannover Medical School, Germany

Copyright © 2022 Toyomoto, Sakata, Yoshida, Luo, Nakagami, Iwami, Aoki, Irie, Sakano, Suga, Sumi, Ichikawa, Watanabe, Tajika, Uwatoko, Sahker and Furukawa. 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: Rie Toyomoto, dG95b21vdG8ucmllLjVyQGt5b3RvLXUuYWMuanA=

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.