Sage Journals: Discover world-class research

Abstract

Introduction:

The development of cultural sensitivity is essential for health care professionals but there are few tools to measure this quality in Japan. The purpose of this study was to develop a scale of cultural sensitivity for Japanese health care professionals and examine its reliability and validity.

Method:

A draft scale was created through conceptual analysis and a questionnaire was completed by 515 health care professionals and 1,322 college students. Exploratory and confirmatory factor analyses were used to determine suitable scale items and examine model fitness.

Results:

The four-factor 18-item scale showed acceptable model fitness. Cronbach’s α coefficient exceeded .90 and correlation coefficients for criterion-related validity were over .29. Construct validity was confirmed by the significantly higher score of the cross-culturally experienced groups. The intraclass correlation coefficient was .642 (professionals) and .722 (students).

Discussion:

This reliable and valid scale for Japanese health professionals and college students may be used to evaluate training programs to increase their cultural sensitivity.

Keywords

cultural sensitivity health care professionals health care students scale development

Introduction

Globalization has led to rapid growth in the transnational movement of people and has ushered in an era in which we live with people of diverse ethnic, religious, and cultural backgrounds. Under such circumstances, cultural and linguistic differences between patients and health care professionals (HPs) are expected to increase. Indeed, the cultural and linguistic barriers between patients and HPs are known to affect the quality of health care delivery. In previous studies, the populations studied that were susceptible to these barriers were predominantly immigrant populations from non-English-speaking countries living in English-speaking countries (Al-Jumaili et al., 2020).

In Japan, immigrant women are at higher risk for mental health problems (Luo & Sato, 2021a, 2021b). Unsatisfactory health care, language barriers and poor access to health care services are also factors in health disparities (Nagamine et al., 2022; Okamoto et al., 2022; Yasukawa et al., 2019). The American Association of Colleges of Nursing (2021) states that as health care providers, nurses can contribute to reducing health disparities by providing equal and equitable health care services to people of diverse backgrounds. The association further advocates for 21st-century nursing education based on the foundational values of diversity, equity, and inclusion.

In Japan, we are gradually moving toward a society that accepts people of diverse cultural backgrounds. To cope with labor shortages caused by a declining birthrate and an aging population, the Japanese government has implemented policies to promote the acceptance of foreign workers (Immigration Service Agency, 2018). Japan further implemented the 300,000 Foreign Student Plan to secure human resources for the future (Ministry of Education, Culture, Sports, Science and Technology, 2021). These policies have been effective; the number of foreign residents has increased continuously since 2012, reaching a record high of approximately 2.83 million in 2019, before the coronavirus disease 2019 (COVID-19) pandemic (Statistics Bureau of Japan, 2021). As increasing numbers of foreigners visit Japanese medical facilities, Japanese HPs face challenges including differences in language, culture, and lifestyle; misunderstandings caused by divergent views about illness; and the control of negative emotions (Saigusa & Igawa, 2022; Saito et al., 2018). In particular, foreign workers from developing countries are more prone to health issues because they often refrain from accessing health care facilities because of financial problems, language barriers, differences in cultural customs, and the impact of illness on work (Morita et al., 2021; Sawada, 2019). To ensure that foreign patients receive satisfactory treatment, health care providers must consider the life background and social characteristics of these patients and provide culturally sensitive care.

Since the 1990s, the importance of intervention by health care provider with high Cultural Sensitivity (CS) has been continuously emphasized (Leung & Ku, 2023). Several studies have revealed that interventions by culturally sensitive health care providers have been shown to have an impact on patient outcomes (Kuhlmann & Tallman, 2022; Wadi et al., 2021). The development of CS is an important component of nursing education, and all nurses are expected to provide culturally sensitive care (Blankinship, 2018). Furthermore in previous studies, CS has been recognized as a component and foundation of CC (Henderson et al., 2018; Sharifi et al., 2019). This indicates that CS is an important concept in health care provision and health professional education. The CS scale is necessary for developing CS training program and its evaluation.

Background

Among the international tools for CS measurement in health care professionals and college students, the Intercultural Sensitivity Scale (ISS) by Chen and Starosta (2000) is one of the most prominent; the ISS has been translated into several languages and has been used in many studies (Aktaş et al., 2021; Dur et al., 2022; Toda & Maru, 2018). Chen (1997) concluded that intercultural communicative competence consists of three aspects: (a) an affective aspect of facing cultural differences with positive feelings without rejection or negativity, (b) a cognitive aspect of cultural awareness, and (c) a behavioral aspect of conversation and attitude. Chen referred to the affective aspect as “intercultural sensitivity.” Therefore, the ISS measures the emotional aspect of intercultural communication in daily life but does not measure CS as it applies to HPs’ roles and characteristics.

Reviewing the CS scale for health care field, only the Tucker-Culturally Sensitive Health Care Provider Inventory (T-CSHCPI) developed in the United States was found (Tucker et al., 2017). Based on results from focus group in which low-income African, Hispanic, Latino, and non-Hispanic whites American, it is difficult to use this measure in Japan because the racial and ethnic diversity in the United States is very different from those in Japan.

Compared with people in countries such as the United States and some European countries that have multi-ethnic and culturally diverse populations, Japanese people have less experience interacting at school, work, or in other facets of daily life with people from other cultures. Therefore, Japanese people have less direct experience of respecting cultural differences and less opportunity to consciously attempt to understand people from other cultures. Japan is considered a mono-ethnic and monolingual country; its foreign population was as low as 2.2% in 2021 (Nishikawa et al., 2022). Correspondingly, Japanese nurses have limited experience caring for foreign patients (Asakawa et al., 2023; Kondo et al., 2021). Few Japanese nurses have received lecture-style or simulation exercise training in caring for patients with diverse cultural backgrounds (Kambayashi et al., 2020). In previous studies, Japanese nurses were found to have lower CC scores than Thai nurses (Kawabata et al., 2020). It is suggested that this less frequent exposure to other cultures and fewer opportunities to participate in CS training may have affected the CC of Japanese nurses. To transition to a culturally diverse future society, Japanese HPs and STs must improve their CS, the foundational element of CC for a HP.

A considerable need exists for a “CS of HPs” measurement scale to guide the development and evaluation of educational and training programs in CS. After an extensive literature review, no instrument was found that measured the concept of CS of Japanese HPs and STs. To ensure the readiness of Japanese HPs and STs in providing CS care to patients, a measurement tool that measures CS is needed. The purpose of this study was to develop a “CS of HPs” scale that can be used by both HPs and STs who are training as HPs. If translated and used in countries with cultural immersion stages similar to those in Japan, this scale could contribute to improving CS among HPs in these countries.

Method

Development and testing of the CS of health care professionals proceeded through a four-phase process is shown in Figure 1. A quantitative cross-sectional study was conducted following a conceptual analysis of CS of health care professionals.

Figure 1.

Overview of Study Procedure

Phase 1: Conceptualization

In previous conceptual analyses of CC, CS has been identified as a sub-concept or antecedent of CC (Garrido et al., 2019; Henderson et al., 2018; Sharifi et al., 2019; Yang, 2021). This scale is based on the conceptual analysis of CS to differentiate it from CC to which it is a subconcept. The creation of the content and domains areas for the construct of measurement must be clear. We used the attributes of CS derived from our conceptual analysis for the study (Tanaka & Arakida, 2019).

Phase 2: Item Generation

Generation of Initial Item

Scale items were generated based on the concept of “CS of HPs” by referring to the literature on cross-cultural nursing competence, cultural sensitivity, and related measurement scales. A pool of 58 items in Japanese was created.

Content and Face Validity of Initial Item

Japanese experts with extensive knowledge of and experience in cross-cultural care were individually interviewed to collect expert opinions on whether the initial item appropriately queried the “attributes of CS among HPs” and whether any expressions were difficult to understand. The experts were four researchers with research interests similar to ours teaching at universities and three experienced members of the Japan Overseas Cooperation Volunteers with more than 2 years of experience providing care to patients with different cultural backgrounds in foreign countries. All experts were selected for convenience sampling.

The duration of the interview ranged from 90 to 120 min and interviews were recorded. Items were modified and integrated into the wording as a result of expert opinion. Finally, 50 initial items were generated in Japanese.

Pre-Test

A pre-test was conducted to examine the face validity of the initial items. The participants were 30 doctoral students in nursing and included many nursing faculty. They were all Japanese. They were asked to participate in the pre-test after class. After filling out the questionnaire, participants developed and integrated comments on the modification of the initial items in the five-person group discussion. Finally, a draft 7-point CS scale (1 = not at all applicable to 7 = very applicable) with five subscales and 37 items was developed. Five subscales are (a) a positive desire to understand people with diverse cultures (10 items), (b) respect for culture (6 items), (c) an understanding of culture (6 items), (d) knowledge of culture (8 items), and (e) an awareness of differences with own culture (7 items).

Phase 3: Psychometric Testing of Measurement Properties

A cross-sectional quantitative survey was conducted to evaluate the internal consistency and the construct and criterion validity of the CS scale for HPs and STs.

Sample and Data Collection

The study samples consisted of Japanese HPs and STs. The HP target samples consisted of physicians, nurses, pharmacists, physical therapists, or occupational therapists. Requests for participation in the research were sent to 315 hospitals with at least 50 beds (excluding psychiatric and long-term care beds for older adults) located in Japanese cities that had a foreign population ratio of over 3.0%. After obtaining research approval from 11 hospitals, 853 questionnaires were distributed to HPs by the chiefs of participants’ departments. The data collection period was from November 2019 to November 2020 and included an intermission period to account for the COVID-19 pandemic.

The ST target samples consisted of sophomores and juniors enrolled in a college of medicine, nursing, pharmacy, physical therapy, or occupational therapy. Sophomores and juniors were selected to examine whether differences in the stage of study affected CS scores. Forty schools were randomly selected from a list of medical, nursing, pharmacy, physical therapy and occupational therapy schools nationwide, and requests for participation in the research were sent by mail to college deans. A description of the research and a complete set of questionnaires were distributed to a total of 3,712 students from 27 schools (nine nursing, five pharmacy, seven physical therapy, and six occupational therapy) that were approved to conduct the study. Approval was not granted by the College of Medicine. The data collection period was from November 2019 to March 2020.

Instruments

The questionnaire in Japanese consisted of the elements listed below. A series of survey forms were self-administered, anonymous, and paper-and-pencil-based.

Demographic Profile

HPs were asked about their gender, age, profession, education, years of experience in the current profession, and total years of experience as an HP. STs were asked about their gender, age, and the school and year in which they were enrolled.

Draft CS Scale (37 Items)

The following instructions were included at the beginning of the form that included the scale: “Please select one of the following seven that best describes your approach and attitude as a health care professional when providing care to culturally diverse patients.”

Scales for Criterion Validity

Permission for the use of scales was obtained from developers.

The Japanese Version of the Intercultural Sensitivity Scale (J-ISS)

The ISS (a 24-item 5-point scale) developed by Chen and Starosta (2000) is the original version of the scale. As mentioned, the scale has been used in a relatively large number of studies in the health care field and is recognized as a gold standard. Suzuki (2017) confirmed the validity and reliability of the J-ISS (a 16-item 5-point scale) based on a Cronbach’s α of .61 to .77 and test–retest correlation coefficients of .67 to .80.

Multidimensional Empathy Scale-Short Form

Empathy is an important factor that deepens the understanding of others and motivates helping and other prosocial behaviors (Suzuki & Kino, 2008). The Multidimensional Empathy Scale (MES) measures individual characteristics related to the emotional aspects of empathy and the generation of cognitive processes (Suzuki & Kino, 2008). They developed the original 24-item (5-point scale) version in Japanese, and then 10-item short versions were created (Kino & Suzuki, 2016). The scale consists of five subscales: “other-oriented reactions,” “self-oriented reactions,” “affectedness,” “perspective-taking,” and “imagination.” Of these subscales, “other-oriented reactions (empathic concern)”—which entails putting oneself in the position of others—and “perspective-taking” as its cognitive tendency are related to our “CS of HPs” attributes “positive desire to understand people with diverse cultures,” “awareness of differences with own culture,” and “respect for culture,” all of which include supportive and empathic attitudes toward people. For these reasons, we adopted the MES-Short Form (MES-SF) for examination of criterion validity.

Questions for Known Groups and Convergent Validity

Three questions were prepared to examine known-groups validity using the t-test: (a) “experience living abroad more than one year,” (b) “proficiency in a foreign language at the level of daily life,” and (c) “experience of attending in-country training in cultural diversity.” Another four questions regarding the perception of health disparities among minority groups with different cultures and willingness to work in a foreign country were created to test convergent validity by Pearson’s correlation. A 7-point scale (1 = not at all applicable to 7 = very applicable) was used to answer these questions.

Statistical Analysis

The collected data were analyzed using SPSS for Windows Ver. 26 (IBM Japan, Ltd., Tokyo, Japan) and AMOS for Windows Ver. 26 (IBM Japan, Ltd., Tokyo, Japan). Missing data were removed from the analysis. Descriptive statistics for all variables were performed and confirmed to have the normality of scale items using QQ plots and histograms. The level for statistical significance was set at 5%.

For construct validation, the total returned samples for HPs and STs were divided into two subsamples using a random number generated by Microsoft Excel. For HPs, Subsample 1 (n= 256) was used for exploratory factor analysis (EFA) and Subsample 2 (n=259) was used for confirmatory factor analysis (CFA). Similarly, ST Subsample 1 (n=700) was used for EFA and ST Subsample 2 (n =622) for CFA. The size of subsamples satisfied the criteria of seven times the number of items and more than 100 for EFA and at least 200 for CFA (Mokkink et al., 2018).

Item Analysis

To determine whether EFA could be used for the draft scale, ceiling and floor effects, item-total correlations (≥.30), item-to-item correlations (≤80), a Kaiser–Mayer–Olkin measure of sampling adequacy (≥.90, and the Bartlett’s test of sphericity (≥.90) of Subsample 1 for HPs and STs were conducted. Statistical criteria were set as above (Stainer et al., 2016).

Exploratory Factor Analysis

EFA was performed with Promax rotation and the generalized least-squares method to determine their underlying factor structures for HPs and STs. Items with factor loadings of .40 or more but not more than .40 across multiple factors were adapted repeatedly until convergence was achieved. The criterion for determining the number of factors was an eigenvalue of 1.0 or more, which was used in combination with the decreasing trend of eigenvalues in the scree plot (De Vet et al., 2011).

Confirmatory Factor Analysis

To confirm the factor structure and create a higher goodness-of-fit model after EFA, CFA was performed on Subsample 2 for HPs and STs using maximum-likelihood estimation. The CFA model fit criteria were set using multiple indices: a comparative fit index (CFI) > .95, a root mean square error of approximation (RMSEA) ≤ .06, or a standardized root mean square residual (SRMR) < .08 (Mokkink et al., 2018).

Identification of a Common Model for HPs and STs

The factor structures of the respective models for HPs and STs were very similar; therefore, a common model creation was attempted by analyzing the samples that were fed into each model. The criterion of RMSEA value was set at ≤.05 (Toyoda, 2007).

Internal Consistency

Cronbach’s α values between .70 and .95 are considered acceptable to confirm the internal consistency of the CS scale. We deemed a value of .80 or higher sufficient.

Convergent Validity

Known-groups validity was assessed using a t test. The magnitude of the known-groups validity was decided using Cohen’s effect sizes d for yes/no groups. Pearson’s correlation between the score of the “CS of HPs” and the perception of health disparities in minority populations in Japan was calculated. The criterion correlation coefficient value for the item-total correlation in this study was set at ≥.30 (Stainer et al., 2016).

Criterion-Related Validity

Pearson’s correlation coefficients were calculated for the final CS scale and the J-ISS, the criterion value of r was set at .40 to .80 (Stainer et al., 2016).

Multi-Group Confirmatory Analysis

After identifying a common model, a multi-group confirmatory analysis (MGCFA) was performed to investigate whether HPs had higher CS scores than STs. Because we hypothesized that HPs might have more experience than STs in providing care to foreign patients in clinical sites, it was predicted that HPs would have higher scores compared with STs.

The goodness-of-fit index, the CFI, the RMSEA, and Akaike’s information criterion were used to examine measurement invariance (Toyoda, 2007). Then, the effect size Cohen’s d was calculated to examine the degree of difference in the mean score. Small, moderate, and large effect sizes were defined as those having d values of 0.20, 0.50, and 0.80, respectively (Kim & Mallory, 2016).

Phase 4: Reliability Using the Test–Retest Method

A cross-sectional web-based survey was conducted to evaluate the reproducibility of the final CS scale.

Sample and Data Collection

Inclusion criteria for HPs were physicians, nurses, pharmacists, physical therapists, or occupational therapists who worked in Japanese general hospitals with 50 or more beds. Inclusion criteria for STs were students enrolled in the courses of medicine, nursing, pharmacy, physical therapy, or occupational therapy and in the second year or above. Sample size was calculated using the following formula; n = 2 + k/2(k − 1)(zr − zr^-)² (confidence coefficient: r=.85, standard error [SE]=.05, k [number of observations] = 2) (Stainer et al., 2016). Then, we determined sample sizes of 50 HPs and 50 STs.

Participant recruitment and data collection were outsourced to an internet research firm (NTT Com Online Marketing Solutions Corporation: NTT Com, Tokyo, Japan), which has a large number of monitors and covers a wide range of demographics in Japan. The COVID-19 pandemic was the primary reason for using an internet survey method. At the time, it was impossible to conduct the survey using conventional face-to-face and paper-and-pencil methods.

To test the reproducibility of the final CS scale, participants were asked to respond twice, with 10 to 14 days elapsing between the first and second responses.

HPs were asked to provide information on gender, age, and job title, whereas STs were asked about gender, age, area of study, and grade.

Statistical Analysis

The intraclass correlation coefficient (ICC 2.1) for reproducibility was analyzed. ICC ≥ .70 was considered the criterion for reliability (Mokkink et al., 2018).

Ethical Considerations

All study procedures were approved by the Soka University Institutional Review Board for Human Research (approval numbers: 2019040, 2020061).

Results

Demographic Characteristics

Health Care Professionals

Among the total 853 HPs, 541 (63.4%) responded, and 515 completed items were included in the analysis. The demographic characteristics of Subsample 1 (n=259 for EFA) and Subsample 2 (n=256 for CFA) are shown in Table 1. Nurses were the largest group of HPs. No significant differences were observed between the occupational ratios of the two subsamples (χ² = 5.097, df = 4, p= .206).

Table 1.

Demographic Characteristics of Participants.

Phase 3: Psychometric testing												Phase 4: Test-retest testing
HPs n = 515						STs n = 1,322						HPs n = 132				STs n = 107
		Subsample 1 (EFA) n = 259		Subsample 2 (CFA) n = 256				Subsample 1 (EFA) n = 700		Subsample 2 (CFA) n = 622		HPs n = 132				STs n = 107
		n	%	n	%			n	%	n	%			n	%			n	%
Gender	Male	32	12.4	26	10.2	Gender	Male	237	33.9	208	33.4	Gender	Male	90	68.2	Gender	Male	20	18.7
	Female	227	87.6	230	89.8		Female	463	66.1	414	66.6		Female	42	31.8		Female	87	81.3
Occupation^a	MD	3	1.2	1	0.4	College^b	Medicine	0		0		Occupation	MD	59	44.7	College	Medicine	29	27.1
	Ns	213	82.2	225	87.9		Nursing	231	33.0	193	31.0		Ns	48	36.4		Nursing	35	32.7
	Ph	12	4.6	6	2.3		Pharmacy	197	28.1	199	32.0		Ph	11	9.3		Pharmacy	36	33.6
	PT	21	8.1	20	7.8		Physical therapy	202	28.9	156	25.1		PT	8	6.1		Physical therapy	2	1.9
	OT	10	3.9	4	1.6		Occupational therapy	70	10.0	74	11.9		OT	6	4.5		Occupational therapy	5	4.7
Age	20s	67	25.9	62	24.2	Grade in school	2nd	337	48.1	306	49.2	Age	20s	8	6.1	Grade in school	2nd	34	31.8
	30s	66	25.5	69	27.0		4th	363	51.9	316	50.8		30s	21	15.9		3rd	32	29.9
	40s	61	23.6	70	27.3	Age	20s	680	97.1	606	97.4		40s	40	30.0		4th	26	24.3
	50s	48	18.5	46	18.0		30s	16	2.3	15	2.4		50s	37	28.0		5th	5	4.7
	60s	15	5.8	9	3.5		40s	4	0.6	1	0.2		60s	22	16.7		6th	10	9.3
	Over 70	2	0.8										Over 70	4	3.0	Age	20s	105	98.1
																	30s	2	1.9
Frequency of providing care to foreigners (HPs n = 515)							n						%
2–3 person/6 month							255						33.6
1–2 person/month							54						10.5
1–2 person/2 weeks							19						3.7
1–2 person/week							13						2.5
1–2 person/everyday							16						3.1
Nonresponse							125						24.3

Note. HP = health care professional; ST = College Student; EFA = exploratory factor analysis; CFA = confirmatory factor analysis; MD = Medical doctor; Ns = Nurse; Ph = Pharmacist; PT = Physical therapist; OT = Occupational therapist.

χ² test among occupations between Subsamples 1 and 2, no significant difference (χ² = 5.097, df = 4, p=.206). ^bχ² test among college between Subsamples 1 and 2, no significant difference (χ² = 4.582, df = 3, p =.183).

College Students

In total, 1,355 of 3,712 (36.5%) STs responded, and the 1,322 respondents who completed items were examined in the analysis. The demographic characteristics of Subsample 1 (n = 700 for EFA) and Subsample 2 (n = 622 for CFA) are shown in Table 1. Medical students were not included because the faculty of medicine did not provide consent for participation. No significant differences were observed in the college ratio between the two subsamples (χ² = 4.852, df = 3, p = .183).

Item Analysis

No items showed a ceiling or floor effect in either group. Both subsamples satisfied item-total and item-to-item correlation criteria. The Kaiser–Mayer–Olkin measure (HP Subsample 1 = .949; ST Subsample 1 =.972) and Bartlett’s test of sphericity (HP Subsample 1: χ² = 8,380.308, p<.001; ST Subsample 1: χ² = 19,578.510, p <.001) were also acceptable. Results indicated that EFA could be performed on both samples.

Exploratory Factor Analysis

Health Care Professionals

After conducting an EFA on 37 items, 26 items with four factors were finally extracted. Eleven items that did not meet factor loading criteria were examined separately for possible deletion; it was confirmed that these items were appropriate for deletion following a discussion of the similarity and importance of the items. Cronbach’s α coefficients were .928, .921, .920, and .884 for factors 1, 2, 3, and 4, respectively, and .961 for the total of 26 items. Given that all coefficients were above .80, we confirmed internal consistency reliability (Table 2).

Table 2.

Exploratory Factor Analysis of Health Care Professionals.

No.	Total 26 items, α = .961	M	SD	Factor loadings
No.	Total 26 items, α = .961	M	SD	F1	F2	F3	F4
Factor 1. 9 items, α = .928
36	I want to accept and listen them first, even if there are differences in my way of thinking and values.	5.3	1.1	.952	−.134	−.057	.105
32	I try to understand the feelings of them.	5.4	1.0	.885	.015	−.033	−.094
37	I am flexible and open to their values and beliefs.	5.1	1.0	.807	−.020	.069	−.051
24	I want to use nonverbal communication to communicate with them, even if I cannot communicate well.	5.3	1.1	.771	−.149	−.049	.294
26	I think from the standpoint of them living in Japan.	5.1	1.0	.740	.053	.059	−.022
25	I understand their important values through the knowledge and interactions with them.	5.0	1.0	.648	.124	.098	.088
33	I understand their health care needs from the knowledge and interactions with them.	4.9	1.0	.640	.299	.124	−.173
16	I want to communicate with them by using translation tools, etc., even if I don’t speak the foreign language.	5.4	1.1	.623	−.086	−.093	.305
1	I respect their lifestyle.	5.3	1.1	.405	.149	−.041	.084
Factor 2. 7 items, α = .921
6	I seek to gather information about the old traditional treatment and recuperation methods in their culture.	4.0	1.4	.012	.980	−.202	−.030
8	I seek to gather information about how to care for the illness in their culture.	4.3	1.4	.076	.882	−.047	−.103
10	I seek to gather information about the general social characteristic (educational, political, economic, etc.) in their country.	4.3	1.4	−.158	.850	.004	.151
31	I try to understand how to care for sick family members in their country using the information obtained from them.	4.2	1.2	.121	.692	.127	−.151
17	I seek to get information about high prevalence disease and its factors in their country.	4.0	1.3	−.138	.681	−.003	.271
15	I try to gather information to gain knowledge of their values and ideas in their culture.	4.3	1.2	−.030	.648	.056	.285
29	I understand the perception of the disease in their culture through the knowledge and interactions with them.	4.7	1.1	.235	.483	.224	−.058
Factor 3. 7 items, α = .920
18	I often find that Japanese cultural characteristics, ideas, and values through interactions with cultural diverse people.	4.5	1.1	−.152	.010	.903	.065
28	I often find that their sense of time differs from my own.	4.6	1.1	−.061	−.029	.900	−.071
22	I often find that their behaviors and lifestyles differ from my own.	4.6	1.2	−.028	−.015	.840	.079
34	I often find that others’ values differ from my own.	4.8	1.1	.210	−.128	.802	−.086
13	I often find that the way they express their feelings and thoughts differs in some ways from my own.	4.7	1.2	.030	−.066	.713	.118
19	I often find my own assumptions and prejudices to their culture through interactions with them	4.6	1.0	.160	−.002	.599	.053
35	I understand how families take care of the sick person through the knowledge and interactions with them.	4.7	1.1	.179	.251	.488	−.025
Factor 4. 3 items, α = .884
11	I enjoy learning about their cultural values and their lifestyle.	5.0	1.4	.114	.029	−.056	.854
21	I am interested in learning about their cultural values and lifestyle.	4.8	1.2	.194	.020	.104	.658
14	I am interested in the culture-specific meaning behind their behavior patterns and habits.	4.5	1.3	−.051	.233	.143	.613
				Factor correlations	F1	F2	F3
				F2	.559
				F3	.711	.664
				F4	.568	.581	.588

Note. n = 256. Generalized least-squares method and promax rotation was adopted. Eigenvalues of 1.0 or higher and factor loadings of .40 or higher were used. Bold values indicate factor loadings of 0.40 or greater. F1: Factor 1—“Respect of culture and positive desire to understand people with diverse culture”; F2: Factor 2—“Knowledge and understanding regarding culture and illness/health care”; F3: Factor 3—“Awareness of differences with own culture”; F4: Factor 4—“Interest and concern in learning about the cultural values and lifestyle of culturally diverse people.” α = Cronbach’s α coefficient.

Next, four factors were named as follows: (a) “respect of culture and positive desire to understand people with diverse culture,” (b) “knowledge and understanding regarding culture and illness/health care,” (c) “awareness of differences with own culture,” and (d) “interest and concern in learning about the cultural values and lifestyle of culturally diverse people.”

College Students

As with the HPs, an EFA for Subsample 1 of STs was conducted starting with the 37-item draft scale. 31 items with four factors were finally extracted. Because six items did not meet factor loading criteria, it was confirmed through discussion that the items were appropriate for deletion. Cronbach’s α coefficients were .938, .914, .886, and .866 for Factors 1, 2, 3, and 4, respectively, and .966 for the total of 31 items. Given that all coefficients were above .80, internal consistency reliability was confirmed (Table 3).

Table 3.

Exploratory Factor Analysis of College Students.

No.	Total 31 items α = .966	M	SD	Factor loadings
No.	Total 31 items α = .966	M	SD	F1	F2	F3	F4
Factor 1. 13 items α=.938
36	I want to accept and listen them first, even if there are differences in my way of thinking and values.	5.8	1.1	.891	−.162	.080	−.002
32	I try to understand the feelings of them.	6.0	1.0	.835	−.060	.080	−.053
9	I try to understand the confusion and difficulties of others living in Japan.	5.9	1.0	.706	.042	−.087	.184
3	I value their thinking and ideas.	5.9	0.9	.670	−.018	−.059	.175
37	I am flexible and open to their values and beliefs.	5.6	1.1	.645	.083	.104	−.045
26	I think from the standpoint of them living in Japan.	5.6	1.1	.603	.077	.187	−.025
5	I want to be persistent until I understand what they are trying to say.	5.5	1.2	.567	.262	−.298	.217
25	I understand their important values through the knowledge and interactions with them.	5.6	1.1	.528	.029	.164	.225
33	I understand their health care needs from the knowledge and interactions with them.	5.5	1.1	.523	.329	.145	−.158
16	I want to communicate with them by using translation tools, etc., even if I don’t speak the foreign language.	5.8	1.1	.511	−.084	−.058	.383
1	I respect their lifestyle.	5.8	1.0	.495	.000	.036	.170
24	I want to use nonverbal communication to communicate with them, even if I cannot communicate well.	5.7	1.2	.494	−.094	.114	.305
7	Even if there is a difference in the way they express their will and the way they express themselves, I want to treat them according to their way.	5.3	1.1	.436	.371	−.081	.008
Factor 2. 8 items: α=.914
8	I seek to gather information about how to care for the illness in their culture.	5.2	1.3	.071	.869	−.111	−.013
6	I seek to gather information about the old traditional treatment and recuperation methods in their culture.	5.0	1.2	−.035	.867	−.171	.114
31	I try to understand how to care for sick family members in their country using the information obtained from them.	5.0	1.2	−.066	.706	.158	.025
10	I seek to gather information about the general social characteristic (educational, political, economic, etc.) in their country.	5.0	1.3	−.168	.643	.028	.280
29	I understand the perception of the disease in their culture through the knowledge and interactions with them.	5.3	1.1	.232	.596	.206	−.156
17	I seek to get information about high prevalence disease and its factors in their country.	5.1	1.2	−.073	.481	.139	.236
23	I try to obtain general knowledge of the culture of the subject’s country (food, clothing, shelter, family structure, etc.).	5.3	1.2	.016	.440	.221	.225
35	I understand how families take care of the sick person through the knowledge and interactions with them.	5.3	1.1	.267	.422	.276	−.119
Factor 3. 6 items: α=.886
34	I often find that others’ values differ from my own.	5.3	1.1	.156	−.033	.794	−.135
22	I often find that their behaviors and lifestyles differ from my own.	5.2	1.1	−.045	−.047	.781	.141
28	I often find that their sense of time differs from my own.	5.0	1.2	.004	.110	.763	−.141
19	I often find my own assumptions and prejudices to their culture through interactions with them	5.2	1.2	.045	−.123	.661	.246
18	I often find that Japanese cultural characteristics, ideas, and values through interactions with cultural diverse people.	5.0	1.2	−.094	.045	.657	.211
13	I often find that the way they express their feelings and thoughts differs in some ways from my own.	5.2	1.2	−.014	−.059	.651	.128
Factor 4. 4 items: α = .866
11	I enjoy learning about their cultural values and their lifestyle.	5.5	1.3	.152	.015	.030	.632
14	I am interested in the culture-specific meaning behind their behavior patterns and habits.	5.2	1.2	−.060	.256	.061	.630
21	I am interested in learning about their cultural values and lifestyle.	5.5	1.2	.203	.056	.051	.616
12	When my values and behavioral standards differ from subjects, I consider the reasons and background behind the difference.	5.4	1.2	.015	.298	.095	.454
				Factor correlations	F1	F2	F3
				F2	.697
				F3	.696	.671
				F4	.606	.606	.566

Note. n = 700. Generalized least-squares method and promax rotation were adopted. Eigenvalues of 1.0 or higher and factor loadings of .40 or higher were used. Bold values indicate factor loadings of 0.40 or greater. F1: Factor 1—“Respect of culture and positive desire to understand people with diverse culture”; F2: Factor 2—“Knowledge and understanding regarding culture and illness/health care”; F3: Factor 3—“Awareness of differences with own culture”; F4: Factor 4—“Interest and concern in learning about the cultural values and lifestyle of culturally diverse people.” α = Cronbach’s α coefficient.

Confirmatory Factor Analysis

CFA was conducted to validate the hypothesized model of latent factors and items determined by EFA and improve the model’s goodness of fit. We set up correlations of error and deleted some items based on correction and goodness-of-fit indices.

Confirmatory Factor Analysis for Health Care Professionals

Examining HP Subsample 2 (n=256), 18 items with four-factor model were ultimately confirmed. Fit indices were χ²/df = 2.067, CFI = .954 > .95, RMSEA =.065, and SRMR = .049 < .08, satisfying the criteria (Figure 2).

Figure 2.

Path Diagrams for Confirmatory Factor Analyses

Confirmatory Factor Analysis for College Students

The results for ST Subsample 2 (n = 622) showed the same factor structure and items as for HPs and differed only in the location of the error correlations. Fit indices were χ²/df = 3.822, CFI =.964 > .95, RMSEA = .038 ≤ .06, and SRMR = .0398 < .08, satisfying the criteria (Figure 2).

Multi-Group Confirmatory Analysis

As the model structures for HPs and STs were the same except for the location of error correlations, we sought to determine which model could be adopted as a common model. When ST data (n= 622) were fed into the HP model, the goodness-of-fit indices declined slightly (χ²/df = 3.328, CFI = .953, RMSEA = .061, and SRMR = .0397). In contrast, when HP data (n = 256) were fed into the ST model, the goodness-of-fit index improved further (χ²/df = 3.453, CFI = .963, RMSEA = .039, and SRMR = .0467), signifying that the ST model could be designated as a common model for HPs and STs. Next, the MGCFA was performed to examine the difference in factor means between HPs and STs. The prerequisite for factor means analysis is that the common model has placement and measurement invariance. Measurement invariance assumes that factor patterns are equal across populations (Brown, 2015). The goodness-of-fit of placement invariance was RMSEA = .040 and measurement invariance was RMSEA = .038. Therefore, the applicability of the measurement invariance model was confirmed. In addition, it was confirmed that the ST model could be used as the common model. Factor mean estimates for STs were calculated by fixing the factor mean and the factor variance for HPs to 0 and 1, respectively. Results indicated that STs had higher factor means than HPs; the degree of difference using Cohen’s d effect size was moderate (Table 4).

Table 4.

Multi-Group Confirmatory Factor Analysis and Effect Sizes.

	Mean		Variance		Cohen’s d
	HP	ST	HP	ST	Cohen’s d
F1	0	0.47	1	0.65	−0.543
F2	0	0.89	1	0.91	−0.919
F3	0	0.45	1	0.81	−0.484
F4	0	0.53	1	0.99	−0.532

Note. HP = Health Professional; ST = College Student.

Reliability and Validity of the Final Cultural Sensitivity Scale

Internal Consistency

Cronbach’s α coefficient for the final CS scale was .937 for HPs (n = 515) and .934 for STs (n = 1,322). All factors for both HPs and STs were above .80, indicating sufficient internal consistency.

Convergent Validity

Contact With People From Diverse Cultures

HPs (n = 515): No significant difference was observed between the “yes” and “no” groups in the total score of the final CS scale for “experience living abroad for more than one year,” t(513) = 1.933, p= .054, d = 0.59. However, the “yes” group scored significantly higher than the “no” group in “proficiency in a foreign language at the level of daily life,” t(513) = 4.824, p < .001, d = 0.69.

STs (n = 1,322): The “yes” group scored significantly higher than the “no” group in “experience living abroad for more than one year,” t(1,320) = 2.186, p = .029, d = 0.20 and “proficiency in a foreign language at the level of daily life,” t(1,320) = 4.822, p < .001, d = 0.35 (Table 5).

Table 5

Known-Group Analysis of the Total Score of the Final Cultural Sensitivity Scale.

	Group	n	Mean	SD	t value	p value	Cohen’s d
Experience living abroad more than 1 year
HP	Yes	13	94.5	11.7	1.933	.054	0.59
HP	No	502	86.7	14.4
ST	Yes	28	102.3	15.6	2.186	.029	0.20
ST	No	1,294	96.2	14.6
Proficiency in a foreign language at the level of daily life
HP	Yes	57	95.4	13.9	4.824	.000	0.69
HP	No	458	85.8	14.1
ST	Yes	224	100.6	14.1	4.822	.000	0.35
ST	No	1,098	95.5	14.6
Experience attending in-country training in cultural diversity
HP	Yes	103	91.8	15.1	3.965	.000	0.42
HP	No	412	85.6	13.9
ST	Yes	730	99.0	13.5	7.480	.000	0.41
ST	No	592	93.1	15.3
Overseas training participation experience
HP	Yes	31	95.4	14.8	3.542	.001	0.63
HP	No	484	86.3	14.2
ST	Yes	217	101.9	13.4	6.139	.000	0.47
ST	No	1,105	95.3	14.6

Note. t-test. HP = Health Care Professional: n = 515; ST = College Student: n = 1,322.

Experience in Education/Training on Cultural Diversity

HPs (n = 515): The “yes” group scored significantly higher than the “no” group in “experience attending in-country training in cultural diversity,” t(513) = 3.965, p < .001, d = 0.42, and “overseas training participation experience,” t(513) = 3.542, p < .001, d = 0.63.

STs (n = 1,322): The “yes” group scored significantly higher than the “no” group in “experience attending in-country training in cultural diversity,” t(1,320) = 7.480, p < .001, d = 0.41, and “overseas training participation experience,” t(1,320) = 6.139, p < .001, d = 0.47.

Therefore, groups with higher language ability, experience of living abroad, and experience of CS training scored moderately higher than groups with less language ability, no experience of living abroad, and no CS training (Table 5).

Awareness of Health Disparities Among Minorities With Diverse Cultures

A weak positive correlation was observed between both HPs and STs in “I am concerned for health issues of people from developing countries living in Japan” in the total score of the final scale (HPs: r = .303, n = 515, p < .01; STs: r = .294, n = 1,322, p < .01). The correlation was close to the criterion of .30 or higher (Table 6).

Table 6.

Correlation of Scores With the Perception of Health Disparities Among Minorities With Diverse Cultures.

	Factor 1	Factor 2	Factor 3	Factor 4	Total score
Q3-01: People from developing countries living in Japan have limited access to medical services
HP	.104*	.050	.125**	.158**	.128**
SDT	.082**	.045	.003	.051	.049
Q3-02: People from developing countries living in Japan are vulnerable to health problems
HP	.075	.092*	.102*	.133**	.119**
SDT	.002	.045	-.025	.061*	.018
Q3-03: I am concerned for health issues of people from developing countries living in Japan
HP	.226**	.262**	.231**	.304**	.303**
SDT	.221**	.275**	.197**	.338**	.294**
Q4: I want to work as a healthcare professional abroad in the near future.
HP	.265**	.265**	.259**	.353**	.337**
SDT	.149**	.213**	.186**	.276**	.237**

Note. From Q3-1 to Q3-3, and Q4: 7-point Likert-type scale (1 = Not at all agree; -7 = Very much agree). HP = Health Care Professionals, n = 515; SDT = College Students, n = 1,322.

Pearson’s correlation coefficient *p < .05. **p < .01.

Willingness to Work in a Foreign Country

Weak positive correlations were observed between HPs and STs in “Willingness to work in a foreign country” and the total score of the final scale (HPs: r = .337, n = 515, p < .01; STs: r = .237, n = 1,322, p < .01). The correlation among HPs met the criteria of .30 or higher (Table 6).

Criterion Validity

Japanese Version of the Intercultural Sensitivity Scale

HPs: The correlation coefficient between the subscale of the J-ISS and the final CS scale was .291 ≤ r ≤ .607 (p < .01), showing a weak-to-moderate positive correlation. However, F2 “Knowledge and understanding of culture and illness/health care” had a lower correlation coefficient than F1, F3, and F4.

STs: The correlation coefficient between the subscale of J-ISS and the final CS scale was .117 ≤ r ≤ .606 (p < .01), showing a weak-to-moderate positive correlation. As with HPs, F2 had lower correlation coefficients than the other three factors (Table 7).

Table 7.

Examination of Criterion-Related Validity.

Scale	Subscale	Group	The final CS scale
Scale	Subscale	Group	F1	F2	F3	F4	Total score
J-ISS	1. Cross-cultural involvement and interest	HP	.607	.291	.459	.527	.556
	1. Cross-cultural involvement and interest	ST	.606	.456	.520	.547	.626
	2. Confidence to engage with different cultures	HP	.163	.255	.244	.251	.276
	2. Confidence to engage with different cultures	ST	.046	.117	.179	.176	.155
	3. Tolerance for different cultures	HP	.366	.056	.163	.300	.253
	3. Tolerance for different cultures	ST	.365	.161	.169	.283	.280
	4. Low prejudice against different cultures	HP	.358	.254	.291	.363	.374
	4. Low prejudice against different cultures	ST	.286	.215	.250	.274	.301
	5. Respect for cultural differences	HP	.573	.273	.420	.500	.520
	5. Respect for cultural differences	ST	.543	.364	.400	.464	.519
MES-SF	1. Other-oriented emotional reactivity	HP	.356	.142	.184	.254	.273
	1. Other-oriented emotional reactivity	ST	.437	.286	.292	.323	.393
	2. Perspective taking	HP	.307	.158	.248	.192	.273
	2. Perspective taking	ST	.377	.291	.359	.312	.400

Note. Pearson’s correlation coefficient. All p values are less than .01. CS = Cultural Sensitivity; J-ISS = Japanese version of the Intercultural Sensitivity Scale; HP = Health Care Professional: n = 515; ST = College Student: n = 1,322; MES-SF = Multidimentional Empathy Scale–Short Form.

Multidimensional Empathy Scale–Short Form

The relationship between “perspective-taking”—which refers to the “other-oriented cognitive tendency to put oneself in the position of others”—and “other-oriented reactions (empathic concern)”—which refers to “other-oriented feelings such as sympathy and concern for others”—in the MES-SH and the subscale of the final CS scale was examined. Weak positive correlations were observed between F1 “respect of culture and positive desire to understand people with diverse culture” and “other-oriented emotional reactivity” of the MES-SH (r = .356, p < .01) and “perspective taking” of the MES-SH (r = .307, p < .01). F2 had a lower correlation with “other-oriented emotional reactivity” and “perspective-taking” than F1, F3, and F4.

STs: STs exhibited results similar to those of HPs (Table 7).

Test–Retest Reliability

Sample Characteristics

The HP group had 132 participants; physicians were the largest group with 59 (44.7%) participants. The ST group had 107 participants; pharmacy students were the predominant group with 36 (33.6%) participants (Table 1).

Intraclass Correlation Coefficient

The ICC (2.1) was r = .642, 95% confidence interval [CI]: [.530, .732] for HPs and r = .722, 95% CI [.618, .802] for STs.

Discussion

Sample

According to the COSMIN Risk of Bias checklist, the sample size required for factor analysis is seven times the number of items and at least 100 items (Mokkink, 2018). In our study, a sufficient number of participants was obtained and these criteria were met. In addition, the sample size required for ICC (2.1) was sufficient to verify the reproducibility of the common CS scale.

Construct Validity

Two scales—the J-ISS and the MES-SH—were used to examine criterion-related validity: a weak-to-moderate positive correlation was observed between the J-ISS and the final CS subscales among HPs (.163 ≤ r ≤ .607) and STs (.117 ≤ r ≤ .606). Although these values were below our criterion value of .70, we were able to demonstrate some positive association with the criterion scale.

It should be noted that F2 (“knowledge and understanding regarding culture and illness/health care”) of this scale had a lower correlation coefficient with the J-ISS subscale than F1, F3, and F4. F2 consists of elements that are needed by HPs to help patients recover from their illnesses and improve their level of health. While F2 is a unique factor characteristic of HPs, the J-ISS subscale does not include a health-related component. Therefore, the lower correlation coefficient between the F2 and J-ISS subscales is a reasonable result that indicates discriminant validity.

In the comparison between the MES-SF and this scale, two of the five subscales of the MES-SF—the “other-oriented response (empathic concern),” which means putting oneself in the position of others and “perspective taking” as its cognitive tendency—were used to examine the construct validity of the final CS scale. The correlations between the two subscales of the ME-SF and the subscale of the final CS scale were weak (HPs: .142≤ r ≤ −.356; STs: .291 ≤ r ≤ −.437) for both HPs and STs. Correlations did not meet our criterion of r = .70; however, as with the J-ISS, a certain level of relevance was identified. Focusing on F2, an HP-specific subscale of the final CS scale, the correlation coefficient was lower than that of the other factors. This result further implies that the final CS scale adequately reflected the characteristics of HPs. Based on the examination of these two scales, the final CS scale was confirmed to have criterion-relevant and discriminant validity.

In the known-groups analysis, the mean scores were significantly higher for the groups that had contact with people from different cultures and had received education/training on cultural diversity than for the group that had not received such education/training. This result confirms our hypothesis that the final CS score is higher for individuals with experience in cross-cultural contact and cultural diversity education/training. In addition, positive correlations were observed between the level of interest in the health issues of foreigners from developing countries in Japan and a willingness to work abroad and the total score of the final CS scale. This further confirms our hypothesis that experience regarding CS antecedent increases CS scores. Based on the above, we concluded that the final CS scale has construct validity.

Common Model and Factor Mean Scores

First, latent factors in an exploratory factor analysis of the HP and ST populations were extracted and then a CFA was performed to test a hypothetical model of the CS scale’s factor structure. In this study, we performed EFA and CFA on different samples by creating two subsamples, referring to a previous study (Lee et al., 2022; Şimşek et al., 2023). Although previous studies performed EFA and CFA on the same sample for scale development, we believe that the use of two samples in this study was an appropriate way to increase the accuracy in confirming the hypothesized model with CFA (Mokkink et al., 2018). The results of the CFA showed that the HP and ST models had the same four factors and 18 items as latent factors and items, with the only difference being the site of error correlation.

In the MGCFA, the ST model was confirmed to have placement invariance (RMSEA = .040) and measurement invariance (RMSEA = .039) for the two populations (HPs and STs), signifying that statistically, the ST model could be considered a common model for HPs and STs.

The MGCFA indicated higher scores for each factor among STs than among HPs. At the time the study was initiated, it had been predicted that HPs’ clinical experience would result in higher mean scores for HPs than for STs on the “CS of HPs” factor. However, that hypothesis was not confirmed. Two possible reasons for this result are the influence of clinical experience on self-evaluation and the self-evaluation nature of the scale. Previous studies have reported that although HPs wished to provide culturally sensitive care to foreigners, they were confused and were often unable to provide care as they wished (Nishikawa et al., 2021). Therefore, it can be inferred that some HPs in the study were unable to provide the care that they would have liked to patients with different cultural and linguistic backgrounds and that their experiences may have influenced their answers to study questions. Among all HPs in this study, approximately 44% provided care to one to two foreign patients monthly; therefore, these HPs had only occasional contact with foreign patients.

In contrast, STs have less experience in clinical practice; therefore, STs are unable to estimate their skills in caring for foreign patients. ST scores may have been higher because of the social desirability bias of “wanting to do it this way.” Furthermore, the high self-assessment of skills by those with immature skills is called the Dunning–Kruger effect, which refers to having insufficient metacognitive skills to accurately assess one’s own abilities (Bradley et al., 2022).

Although this study provides a final CS scale for HPs and STs, based on the above discussion, it is believed that the comparison of CS scores between HPs and STs using the scale is inappropriate given their different experiences in clinical practice. When the CS level is evaluated on an individual basis, percentile reference values must be used to determine where individual CS scores stand within each group. For each group in this study, a separate table (available separately) of percentile reference values was created. Such a table is expected to be useful in understanding the position of the individual in the overall population. It is believed that percentile reference values must be adjusted periodically based on the society’s degree of diversity and the target population for which the scale is used.

Reliability

Test–retest reliability provided an ICC (2.1) of HPs and STs. A meta-analysis of retest reliability coefficients in psychological scales by Oshio (2016) showed that the 95% CI for ICC was .69 ≤ r ≤ .86 for test–retest periods of up to 4 weeks, .59 ≤ r ≤ .81 for 10 or more items, and .64 ≤ r ≤ .89 for 100 to 199 items surveyed. The ICC for HPs in this study was slightly lower than that in the meta-analysis but was within Oshio’s ICC range. Therefore, we believe that the scale has a certain degree of reliability.

The possible reasons why the ICC for health care professionals was lower than .70 which set as a criterion for reliability in this study are discussed here. In addition to memory issues, it cannot be ruled out the possibility that additional CS-related experiences occurred between the first and second tests, such as the opportunity to interact with people from diverse cultures or to gain cross-cultural knowledge. We believe that this is partly due to the fact that we did not ask participants about their CS-related experiences in the second test; thus, we were not able to eliminate factors that might have influenced answers. There is a need for additional methods to reduce these biases and for further confirmation of test–retest reliability.

In-service training programs are known to be effective in increasing CS among HPs. To develop a training program, assessing the readiness of the target population is important. This scale could contribute to determining trainee readiness, guide training program design, and help measure the effectiveness of training programs in Japan. Many Japanese universities offer short-term overseas training programs for students to allow students to expand their horizons and learn about diverse cultures. Using our scale to evaluate these programs could provide objective information from the viewpoint of “CS to ensure preparedness as a health professional.”

Limitations

Study limitations were the subject bias and a test–retest reliability that was lower than the criterion correlation coefficient value in this study.

In this study, nurses accounted for more than 80% of HPs by job category in Phase 2. In general, nurses represent by far the largest proportion of health care personnel in hospitals; this composition of the hospital’s HP workforce affected study results. In the ST sample, medical students could not be included in Phase 2. Continued use of the survey across representative ST populations is required to reduce sample bias in further studies.

As the purpose of the study was to develop a scale, we did not examine issues in the practical use of the CS scale. Therefore, analyzing and improving the scale through repeated use is needed to increase its practicality. Despite these limitations, we believe that this study is original and novel because it is the first to develop a scale that measures “the CS of HPs” and that can be used by both HPs and STs in Japan.

Conclusion

The “Cultural Sensitivity of Health Care Providers” scale is a four-factor, 18-item structural model that was validated with an MGCFA for use with HPs and STs.

The final CS scale has a certain degree of reliability and construct validity.

Supplemental Material

sj-xlsx-3-tcn-10.1177_10436596231217688 – Supplemental material for The Development and Psychometric Testing of the Scale of Cultural Sensitivity of Health Care Professionals in Japan

Supplemental material, sj-xlsx-3-tcn-10.1177_10436596231217688 for The Development and Psychometric Testing of the Scale of Cultural Sensitivity of Health Care Professionals in Japan by Hiroko Tanaka and Mikako Arakida in Journal of Transcultural Nursing

Footnotes

Acknowledgements

We would like to express our sincere gratitude to all those who contributed to this study.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Grant-in-Aid for Scientific Research, JSPS KAKENHI, Grant Number JP17K12140.

ORCID iD

Hiroko Tanaka

Supplemental Material

Supplemental material for this article is available online.

References

Aktaş

Pasinlioğlu

Kılıç

Özaslan

(2021). Determination of intercultural sensitivity among nurses. Journal of Religion and Health, 60(1), 112–121. https://doi.org/10.1007/s10943-019-00902-x

Al-Jumaili

A. A.

Ahmed

K. K.

Koch

(2020). Barriers to healthcare access for Arabic-speaking population in an English-speaking country. Pharmacy Practice, 18(2), 1809. https://doi.org/10.18549/PharmPract.2020.2.1809

American Association of Colleges of Nursing. (2021). Essentials: Core competencies for professional nursing education. https://www.aacnnursing.org/Essentials

Asakawa

Takeda

Henker

(2023). Barriers encountered by nurses in the care of walk-in international patients in an emergency department in Japan. International Emergency Nursing, 70, 101337. https://doi.org/10.1016/j.ienj.2023.101337

Blankinship

L. A

. (2018). Providing culturally sensitive care for Islamic patients and families. Journal of Christian Nursing, 35(2), 94–99. https://doi.org/10.1097/CNJ.0000000000000418

Bradley

C. S.

Dreifuerst

K. T.

Johnson

B. K.

Loomis

(2022). More than a meme: The Dunning-Kruger effect as an opportunity for positive change in nursing education. Clinical Simulation in Nursing, 66, 58–65. https://doi.org/10.1016/j.ecns.2022.02.010

Brown

A. T

. (2015). Confirmatory factor analysis for applied research (2nd ed.). Guilford Press.

Chen

G. M

. (1997). A review of the concept of intercultural sensitivity. Paper presented at the Biennial Convention of the Pacific and Asian Communication Association, Honolulu, HI, United States.

Chen

G. M.

Starosta

W. J.

(2000, November 8–12). The development and validation of the intercultural sensitivity scale. Paper presented at the annual meeting of the National Communication Association, Seattle, WA, United States.

10.

De Vet

W. H.

Terwee

B. C.

Mokkink

B. L.

Knol

L. B.

(2011). Measurement in medicine: A practical guide. Cambridge University Press.

11.

Dur

Ş.

Göl

İ.

Erkin

Ö.

Yildiz

N. U

. (2022). The effect of moral intelligence on cultural sensitivity in nurses. Perspectives in Psychiatric Care, 58(4), 2423–2432. https://doi.org/10.1111/ppc.13077

12.

Garrido

Garcia-Ramirez

Balcazar

F. E.

(2019). Moving towards community cultural competence. International Journal of Intercultural Relations, 73, 89–101. https://doi.org/10.1016/j.ijintrel.2019.09.002

13.

Henderson

Horne

Hills

Kendall

(2018). Cultural competence in healthcare in the community: A concept analysis. Health and Social Care in the Community, 26(4), 590–603. https://doi.org/10.1111/hsc.12556

14.

Immigration Services Agency. (2018). Recent revision to the immigration control act. https://www.moj.go.jp/isa/laws/kaisei_index.html

15.

Kambayashi

Kondo

Mami

Futami

(2020). Needs and motivation of hospital nurses regarding training on how to care for foreign patients in Japan. Journal of International Health, 35(1), 27–38. https://doi.org/10.11197/jaih.35.27. (In Japanese)

16.

Kawabata

Uesugi

Juntasopeepun

Matsuo

(2020). Comparison of cultural competences between nurses in Thai Land and Japan. Bulletin of Health Sciences Kobe, 36, 1–13. https://doi.org/10.24546/81012724

17.

Kim

Mallory

(2016). Statistics for evidence-based practice in nursing (2nd ed.). Jones & Bartlett Learning.

18.

Kino

Suzuki

(2016). Development of a short form of the multidimensional empathy scale (MES-SF). Bulletin of Miyagi Gakuin Women’s University, 123, 37–52. https://doi.org/10.20641/00000283. (In Japanese)

19.

Kondo

Kambayashi

Koizumi

Futami

(2021). Factors related to difficulty in caring for foreign patients among nurses in Japanese hospitals. Journal of International Health, 36(2), 39–47. https://doi.org/10.11197/jaih.36.39

20.

Kuhlmann

Tallman

B. A.

(2022). The impact of nurses’ beliefs, attitudes, and cultural sensitivity on the management of patient pain. Journal of Transcultural Nursing, 33(5), 624–631. https://doi.org/10.1177/10436596221109829

21.

Lee

E.-H.

Lee

Y. W.

Lee

K.-W.

Kim

H. J.

Hong

Kim

S. H.

Kang

E. H.

(2022). Development and psychometric evaluation of a new brief scale to measure eHealth literacy in people with type 2 diabetes. BMC Nursing, 21(1), 1–13. https://doi.org/10.1186/s12912-022-01062-2

22.

Leung

D. S.-Y.

B. H.-B.

(2023). Health-seeking, intercultural health communication, and health outcomes: An intersectional study of ethnic minorities’ lived experiences. Journal of Advanced Nursing, 79, 1856–1867. https://doi.org/10.1111/jan.15568

23.

Luo

Sato

(2021a). Health-related quality of life and risk factors among Chinese women in Japan following the COVID-19 outbreak. International Journal of Environmental Research and Public Health, 18(16), 8745. https://doi.org/10.3390/ijerph18168745

24.

Luo

Sato

(2021b). Relationships of social support, stress, and health among immigrant Chinese women in Japan: A cross-sectional study using structural equation modeling. Health Care, 9(3), 258. https://doi.org/10.3390/healthcare9030258

25.

Ministry of Education, Culture, Sports, Science and Technology. (2021). Report on the 300,000 foreign students plan. https://www.mext.go.jp/content/20220914-mxt_gakushi02-000025000_1.pdf

26.

Mokkink

L. B

. (2018). COSMIN risk of bias check list. https://www.cosmin.nl/wp-content/uploads/COSMIN_risk-of-bias-checklist_dec-2017.pdf

27.

Mokkink

L. B.

Princen

C. A.

Patrick

D. L.

Alonso

Bouter

L. M.

de Vet

H. C.

Terwee

C. B.

(2018). COSMIN methodology for systematic review s of patient-reported outcome measures (PROMs) user manual (Version 1.0). https://cosmin.nl/wp-content/uploads/COSMIN-syst-review-for-PROMs-manual_version-1_feb-2018.pdf

28.

Morita

Kanamori

Nochi

Kondo

(2021). A mixed methods study on specifying the inhibitory factors to access medical services and effective support for foreign residents living in Japan. Journal of International Health, 36(3), 107–121. https://doi.org/10.11197/jaih.36.107. (In Japanese)

29.

Nagamine

Mori

Ohyama

(2022). Structuring communication difficulties of foreign residents when visiting a medical institution in Japan. The Kitakanto Medical Journal, 72(1), 9–22. https://doi.org/10.2974/kmj.72.9

30.

Nishikawa

Okayash

Tsuda

Niiya

(2021). Nursing care for oversea visitors in Japan: A text-mining and logistic regression analysis. The Japan Society of Human Health Care, 6, 9–23.

31.

Nishikawa

Yamanaka

Shibanuma

Kiriya

Jimba

(2022). Cross-cultural information for Japanese nurses at an international hospital: A controlled before–after intervention study. International Journal of Environmental Research and Public Health, 19(19), 12829. https://doi.org/10.3390/ijerph191912829

32.

Okamoto

Matsuda

Foronda

C. L.

(2022). Healthcare needs and experiences of foreign residents in Japan by language fluency. Public Health Nursing, 39(1), 103–115. https://doi.org/10.1111/phn.13026

33.

Oshio

. (2016). Evaluation of test-retest reliability in the development of psychological scales: A meta-analysis of correlation coefficients described in the “Japanese Journal of Psychology.” Japanese Psychological Review, 59(1), 68–83. https://doi.org/10.24602/sjpr.59.1_68

34.

Saigusa

Igawa

(2022). Cultural competence in nursing of nurses in a high-acute care hospital and difficulties in perioperative care for foreign patients. Journal of Japan Operative Nursing Academy, 18(1), 168–176. http://id.ndl.go.jp/bib/000007876483. (In Japanese)

35.

Saito

Okubo

Tezuka

Odagaki

Hiroyama

Misumi

(2018). Difficulties during pregnancy for foreign resident women in Japan. Journal of Japanese Society for International Nursing, 1(1), 1–12. https://doi.org/10.57321/jsin.1.1_1

36.

Sawada

. (2019). Challenges and future prospects surrounding medical care for foreign residents. The Journal of Public Health Practice, 83(2), 96–101. https://doi.org/10.11477/mf.1401209071. (In Japanese)

37.

Sharifi

Adib-Hajbaghery

Najafi

(2019). Cultural competence in nursing: A concept analysis. International Journal of Nursing Studies, 99, 103386. https://doi.org/10.1016/j.ijnurstu.2019.103386

38.

Şimşek

Özmen

G. Ç.

Kemer

A. S.

Aydin

R. K.

Bulut

Çilingir

(2023). Development and psychometric testing of perceived preoperative nursing care competence scale for nursing students (PPreCC-NS). Nurse Education Today, 120, 105632. https://doi.org/10.1016/j.nedt.2022.105632

39.

Stainer

L. D.

Norman

R. G.

Cainey

(2016). Health measurement scales: A practical guide to their development and use ( Kihara

, Trans., 5th ed.). Medical Science International.

40.

Statistics Bureau of Japan. (2021). Estimate of population 2021. https://www.stat.go.jp/english/data/jinsui/2021np/index.html

41.

Suzuki

. (2017). Influence of child and family services workers’ multicultural personality on intercultural sensitivity—Implications for a cultural competence educational program- [Doctoral dissertation, Meiji Gakuin University]. https://meigaku.repo.nii.ac.jp/?action=pages_view_main&active_action=repository_view_main_item_detail&item_id=2541&item_no=1&page_id=13&block_id=21. (In Japanese)

42.

Suzuki

Kino

(2008). Development of the multidimensional empathy scale (MES): Focusing on the distinction between self-and other-orientation. Japanese Journal of Educational Psychology, 56, 487–497. https://doi.org/10.5926/jjep1953.56.4_487. (In Japanese)

43.

Tanaka

Arakida

(2019). Concept analysis of cultural sensitivity in healthcare professionals. Journal of Japan Academy of Nursing Science, 39, 221–226. https://doi.org/10.5630/jans.39.221. (In Japanese)

44.

Toda

Maru

(2018). Cultural sensitivity of Japanese nurses: Exploring clinical application of the intercultural sensitivity scale. Open Journal of Nursing, 8(9), 640–655. https://doi.org/10.4236/ojn.2018.89048

45.

Toyoda

. (2007). Covariance structure analysis Amos version—Structural equation modeling. Tokyo-Tosyo. (In Japanese)

46.

Tucker

C. M.

Roncoroni

Wippold

Wall

Marsiske

(2017). Validation of an inventory for providers to self-assess their engagement in patient-centered culturally sensitive health care. Journal of Patient Experience, 4(3), 129–137. https://doi.org/10.1177/2374373517706622

47.

Wadi

Asantewa

A. S.

Rivas

Goff

L. M.

(2021). Culturally tailored lifestyle interventions for the prevention and management of type 2 diabetes in adults of Black African ancestry: A systematic review of tailoring methods and their effectiveness. Public Health Nutrition, 25(2), 422–436. https://doi.org/10.1017/S1368980021003682

48.

Yang

(2021). Nursing and cultural competence in nursing: A concept analysis. Diversity and Equality in Health and Care, 18(9), 457. https://doi.org/10.36648/2049-5471.21.18.260

49.

Yasukawa

Sawada

Hashimoto

Jimba

(2019). Health-care disparities for foreign residents in Japan. Lancet, 393(10174), 873–874. https://doi.org/10.1016/s0140-6736(19)30215-6

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB