Italian Adaptation and Psychometric Validation of the Evidence‐Based Practice (EBP) Competency Scale

ABSTRACT

Background

Evidence‐based practice (EBP) competence is essential to high‐quality and safe nursing care, yet rigorously validated instruments to assess EBP competencies are lacking in the Italian context.

Aims

To translate, culturally adapt, and psychometrically validate the Italian version of the Evidence‐Based Practice Competency Scale for registered nurses and advanced practice nurses.

Methods

In 2024, a cross‐sectional online survey of Italian nurses was conducted. The 24‐item EBP Competency Scale was translated and culturally adapted following international guidelines. Content validity was assessed by a 16‐member expert panel, and 405 nurses completed the scale and a sociodemographic questionnaire. The sample was randomly split for exploratory and confirmatory factor analyses, and internal consistency, test–retest reliability, and measurement invariance by prior EBP training were examined.

Results

Content validity indices were high (I‐CVI = 0.75–1.00; S‐CVI = 0.92). A one‐factor model explained 72.1% of variance and showed excellent fit. Reliability was very high (α = 0.974; ICC = 0.83). Multigroup CFA supported configural and metric invariance and partial scalar invariance, with lower latent EBP competence in nurses without prior training.

Linking Evidence to Action

The Italian EBP Competency Scale is a valid and reliable instrument for assessing EBP competence among Italian nurses. Its use can support benchmarking, guide EBP‐focused education and implementation strategies, and provide a foundation for future advanced psychometric applications.

1. Introduction

Evidence‐based practice (EBP) is widely recognized as a key strategy to improve care quality, patient safety, and the sustainability of health systems (Melnyk and Hsieh 2025). It refers to clinical decision making integrating individual clinical expertise with the best available external clinical evidence from systematic research (Sackett 1997). Consistent use of EBP is associated with better clinical outcomes, higher patient satisfaction, and reduced costs (Connor et al. 2023; Fontaine et al. 2024).

Nevertheless, EBP uptake in nursing remains uneven (Adombire et al. 2024; Sampson et al. 2024). Insufficient education, limited access to resources and misconceptions about the time and effort required for evidence‐based implementation are persistent barriers (Melnyk et al. 2012; Saunders et al. 2019). Organizational culture and readiness for change are also critical, with continuous learning, peer support, mentorship and transformational leadership identified as key enablers of system‐wide EBP integration (Lehane et al. 2019; Melnyk et al. 2018). Establishing an EBP‐supportive environment requires a culture of continuous learning, peer support, the presence of skilled mentors, and transformational leadership (Lehane et al. 2019).

In response to these challenges, Melnyk et al. (2014) developed the first comprehensive set of evidence‐based practice competencies tailored to clinical nurses and advanced practice nurses (APNs), providing a structured framework to ensure safe, high‐quality care (Melnyk et al. 2014). Subsequent studies have shown that EBP competency levels among nurses remain suboptimal, posing a continuing threat to care quality and patient safety (Melnyk et al. 2012; Melnyk et al. 2018).

To reliably assess these competencies, several psychometric instruments have been created and validated. Among the most widely used in Europe is the Questionnaire to Evaluate the Competency in Evidence‐Based Practice of Registered Nurses (EBP‐COQ), originally developed in Spain to measure nurses' knowledge, skills, and attitudes toward EBP and subsequently adapted to multiple languages and settings (Ruzafa‐Martínez et al. 2020). A separate instrument, the Evidence‐Based Practice (EBP) Competency Scale, was developed by Melnyk and colleagues to directly assess the 24 core EBP competencies they defined for registered nurses and advanced practice nurses (Melnyk et al. 2018). Although both tools evaluate aspects of EBP competence, the EBP‐COQ focuses on self‐reported knowledge, skills, and attitudes. In contrast, the EBP Competency Scale specifically measures attainment of the competency framework established by Melnyk's framework (Melnyk et al. 2014). Adapted and validated versions in different linguistic and cultural contexts (e.g., Spain, Greece, and China) have demonstrated excellent psychometric properties, with high internal consistency and robust construct validity (de Pedro Gómez et al. 2009; Fu et al. 2020; Patelarou et al. 2021). In Europe, a Delphi consensus has further identified a set of Core EBP competencies and learning outcomes for European nurses, underscoring the need for validated instruments to measure these competencies (Dolezel et al. 2021).

Nevertheless, the absence of a validated Italian version limits opportunities to monitor and strengthen EBP competencies among Italian nurses. This gap is particularly critical in a national context where the implementation of EBP is still evolving. At the same time, the demand for reliable assessment tools to guide the transition toward evidence‐based care models continues to grow (Ylimäki et al. 2024).

To address this gap, the present study aims to translate, culturally adapt, and examine the psychometric properties of the Italian version of the EBP Competency Scale (Melnyk et al. 2014, 2018). Providing a valid and reliable instrument for the Italian nursing community will facilitate the systematic assessment of EBP competencies and support educational and organizational strategies to advance the quality and consistency of evidence‐based nursing care.

2. Materials and Methods

2.1. Design

A cross‐sectional observational study was carried out between December 2024 and November 2025. The study complies with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (Cevallos and Egger 2014).

2.2. Translation and Cultural Adaptation

The adaptation process followed established guidelines for cross‐cultural validation of self‐report measures (Beaton et al. 2000; Sousa and Rojjanasrirat 2011). Two independent bilingual translators produced forward translations that were synthesized by the research team. A multidisciplinary expert panel (n = 16) with a mean age of 32 years (range: 21–50), predominantly female (80%, n = 13) comprised of research nurses, nurse educators, and clinical managers; reviewed items for clarity, cultural relevance, and conceptual equivalence. Two different translators then completed back‐translations, which were compared with the original to resolve discrepancies. The pre‐final version was piloted with about 20 clinical nurses to confirm comprehensibility, and formal permission to translate and validate the scale was obtained from the original developers (Beaton et al. 2000).

2.3. Setting, Participants, and Data Collection

Registered nurses employed in hospital, community, or academic settings across Italy were eligible. Inclusion criteria were: (a) current professional registration, (b) ability to read and write Italian, and (c) giving informed consent. Recruitment used a combined convenience and snowball approach through professional networks, mailing lists, and social media. Data were collected online via a secure electronic survey platform. Demographic information included age, gender, region, years of professional experience, highest educational level, and prior formal education in EBP.

2.4. Measures

EBP Competency Scale (Melnyk et al. 2014, 2018): 24 items (13 core RN competencies + 11 APN competencies) rated on a 4‐point Likert scale (1 = “Not at all competent” to 4 = “Highly competent”). Total scores range 24 to 96 and higher scores indicate greater attainment of the EBP competencies. Previous studies report excellent internal consistency (Cronbach's α > 0.95) and strong construct validity. Sociodemographic questionnaire: age, sex, education, region, work setting, role, and prior EBP training.

2.5. Data Analysis

Content validity was evaluated following established guidelines for instrument development and in accordance with the COnsensus‐based Standards for the Selection of Health Measurement INstruments (COSMIN) framework (Mokkink et al. 2010). A multidisciplinary panel of 16 experts, including researchers, nursing faculty, nurse managers, and registered nurses, assessed each item for clarity, relevance, and comprehensibility using a 4‐point Likert scale (1 = “not relevant”, 2 = “somewhat relevant”, 3 = “quite relevant”, 4 = “highly relevant”).

Item‐level Content Validity Index (I‐CVI) was calculated as the proportion of experts rating an item as 3 or 4. The Scale‐level Content Validity Index (S‐CVI) was computed as the mean of all I‐CVI values (Polit et al. 2007). Both indices range 0–1, with a threshold of ≥ 0.70 considered acceptable for item retention (Lawshe 1975; Polit et al. 2007). Items scoring below this threshold were subjected to qualitative review to improve clarity and conceptual equivalence.

An Exploratory Factor Analysis (EFA) was conducted to investigate the underlying factor structure and guide model refinement. The full sample was randomly split into two subsamples (60%/40%) to allow separate execution of the EFA and subsequent Confirmatory Factor Analysis (CFA). The EFA was performed on the first subsample using minimum residual (minres) extraction combined with oblique (oblimin) rotation. Sampling adequacy was confirmed through the Kaiser‐Meyer‐Olkin (KMO) measure and Bartlett's test of sphericity (Bartlett 1954; Dabbagh et al. 2023; Kaiser 1974). The number of factors was determined via parallel analysis, while item retention was based on factor loadings (> 0.30), cross‐loadings, and conceptual coherence.

Model fit was evaluated using standard cut‐off indices including the Comparative Fit Index (CFI ≥ 0.95), Tucker–Lewis Index (TLI ≥ 0.95), Root Mean Square Error of Approximation (RMSEA ≤ 0.06), and Standardized Root Mean Square Residual (SRMR ≤ 0.08), in accordance with widely accepted guidelines for good model fit (Hu and Bentler 1999). Internal consistency and convergent validity were examined with Cronbach's alpha, McDonald's omega (both ≥ 0.70), Guttman's λ6, Average Variance Extracted (AVE ≥ 0.50), Composite Reliability (CR) and the signal‐to‐noise ratio (S/N > 2.0) (Taber 2018; Zinbarg et al. 2005). Temporal stability was assessed 48 h apart using a two‐way mixed‐effects intraclass correlation coefficient (ICC [3,1]) for single measures (Koo and Li 2016). Measurement invariance across known groups was tested with multigroup CFA (configural, metric and scalar models), with changes in CFI, RMSEA, SRMR and chi‐square (χ ²) used to evaluate invariance (Cronbach and Gleser 1964). Measurement invariance across known groups was tested with multigroup CFA (MGCFA)configural, metric and scalar models, with changes in CFI, RMSEA, SRMR and (χ²) used to evaluate invariance.

2.6. Ethical Considerations

Ethical approval for the study was obtained from the local Ethics Committee (Protocol number 30.23 CET 2 CBM). The research adhered to recognized ethical standards and complied with the principles outlined in the Declaration of Helsinki (World Medical Association 2025). Before participating in the survey, all individuals received detailed information about the study procedures and provided their informed consent electronically. Participant data were stored securely, with access limited to authorized members of the research team, in accordance with confidentiality protocols and the requirements of the General Data Protection Regulation (Regulation—2016/679—EN—gdpr—EUR‐Lex, s.d.).

3. Results

The sample (n = 405) was predominantly female (68.9%, n = 279), with a mean age of 41 years (SD = 10.9). Detailed description of participants are reported in Table 1.

TABLE 1.

Characteristics of the sample.

Variable	Category	n (%)
Age (mean, SD)	41.0 (10.9)
Gender	Male	126 (31.1%)
	Female	279 (68.9%)
Highest Educational Attainment	Regional course	25 (6.2%)
	Bachelor's degree	134 (33.1%)
	I‐level Master's degree	148 (36.5%)
	Master's degree	73 (18.0%)
	II‐level Master's degree	18 (4.4%)
	Doctorate (PhD)	7 (1.7%)
Job Position	Staff Nurse	320 (79.0%)
	Acting Nurse Coordinator	17 (4.2%)
	Nurse Coordinator	37 (9.1%)
	Managerial Position	31 (7.7%)
Years of Experience in Current Role	≤ 1 year	17 (4.2%)
	1–5 years	111 (27.4%)
	6–10 years	60 (14.8%)
	11–15 years	61 (15.1%)
	16–20 years	44 (10.9%)
	> 20 years	112 (27.7%)
Geographical Region	Region 1	39 (9.8%)
	Region 2	96 (24.2%)
	Region 3	257 (64.7%)
	Region 4	5 (1.3%)
Work Setting	Hospital	266 (65.7%)
	Research Institute (e.g., IRCCS)	36 (8.9%)
	Community healthcare	71 (17.5%)
	Community health center	6 (1.5%)
	Nursing home	17 (4.2%)
	Other	9 (2.2%)
Type of Healthcare Organization	Public facility	297 (73.3%)
	Private accredited facility	73 (18.0%)
	Private facility	19 (4.7%)
	Other	16 (4.0%)
Previous Training on Evidence Implementation	Yes	210 (51.9%)
	No	195 (48.1%)

3.1. Content Validity

I‐CVI ranged from 0.75–1.00, resulting in S‐CVI = 0.92. None of the items needed revision to improve clarity.

3.2. Exploratory Factor Analysis

Prior to factor analysis, data suitability was confirmed (KMO = 0.970; Bartlett's χ²(276) = 2224.729, p < 0.001). Parallel analysis initially suggested two factors (Table S1), but almost all items loaded strongly on a dominant first factor, and the second accounted for little additional, conceptually uninterpretable variance. The low item complexity and modest factor correlation indicated that common variance was essentially captured by a single dimension (Table S2), so the more parsimonious unidimensional model was retained for subsequent analyses.

3.3. Confirmatory Factor Analysis

The one‐factor model explaining 72.1% of variance showed good fit to the data, χ²(238) = 379.41, p < 0.001, CFI = 0.999, TLI = 0.998, RMSEA = 0.061, 90% CI [0.049, 0.072], SRMR = 0.049. Model structure is displayed in Figure 1.

FIGURE 1.

Confirmatory factor analysis (CFA) model for the Italian version of the Evidence‐Based Practice (EBP) Competency Scale. Single‐headed arrows from the latent factor (F1) to the 24 observed items represent standardized factor loadings, while the small circles (e1–e24) indicate item‐specific error variances. Dashed curved arrows between error terms denote correlated residuals. Residual correlations between Items 4‐14 (r = 0.44), 12‐24 (r = 0.48) and 18‐20 (r = 0.47) are not displayed for clarity. The model reflects a unidimensional structure, with all items loading strongly on a single latent factor, supporting the coherence and internal consistency of the EBP competence construct.

3.4. Reliability

Internal consistency was excellent, with Cronbach's alpha, ordinal alpha, and omega coefficients all exceeding 0.96 (see Table 2). Test–retest reliability was assessed over a one‐week interval with a sample of 20 registered nurses. ICC[3,1] was 0.83 (95% CI 0.77–0.87).

TABLE 2.

Reliability indices.

Indices	Cronbach's alpha	Ordinal alpha	Omega total	Omega (omega2)	Omega (omega3)	AVE	CR	S/N ratio
Values	0.974	0.984	0.984	0.961	0.972	0.722	0.984	62.72

Abbreviations: AVE, Average Variance Extracted; CR, Composite Reliability; S/N, Signal‐to‐Noise Ratio.

3.5. Invariances

Measurement invariance across trained and untrained nurses was examined using a sequence of increasingly constrained MGCFA models (Table 3). The configural model showed good fit, indicating an equivalent basic factor structure across groups. Constraining factor loadings (metric model) and then selected thresholds (partial scalar model) led to only negligible changes in fit indices, supporting the conclusion that the scale operates similarly in both groups and allows meaningful comparison of latent means.

TABLE 3.

Fit indices for measurement invariance models across trained and untrained groups.

Model	χ2(df)	CFI	RMSEA	ΔCFI	ΔRMSEA
Configural	1329.20 (476)	0.997	0.094	—	—
Metric (loadings)	1479.30 (449)	0.996	0.099	0.000	0.004
Scalar (partial)	1381.90 (542)	0.997	0.088	0.001	0.011
Latent means	2026.20 (543)	0.995	0.116	0.002	0.029

Note: ΔCFI and ΔRMSEA values are calculated relative to the configural model. Partial scalar invariance was achieved by freeing the second thresholds of Items 6, 17, 18, and 20.

Although some items displayed modest differences in factor loadings and threshold values, these did not compromise overall metric or partial scalar invariance. After freeing a small number of thresholds to achieve partial scalar invariance, model fit remained acceptable and the untrained group showed a significantly lower latent mean (M = −0.42, SE = 0.02, p < 0.001), indicating lower EBP competence relative to trained nurses (Table 4). Measurement invariance across trained and untrained groups was examined through a sequence of increasingly constrained models (Table 3). The configural model showed good fit, indicating that the basic factor structure was equivalent across groups. Constraining factor loadings (metric model) and subsequently selected thresholds (partial scalar model) produced only negligible changes in fit indices (ΔCFI ≤ 0.001; ΔRMSEA ≤ 0.011), supporting the assumption that the scale operates similarly in both groups and allowing for meaningful comparison of latent means.

TABLE 4.

Factor loadings and threshold 2 estimates for selected items across trained and untrained groups.

Item	Group	Factor loading (λ)	Threshold 2 (τ2)
Item 12	Trained	1.280	−0.316
	Untrained	1.023	0.348
Item 14	Trained	1.323	0.173
	Untrained	1.080	0.736
Item 18	Trained	1.353	0.241
	Untrained	1.097	0.720
Item 6	Trained	1.281	0.195
	Untrained	1.117	0.639
Item 8	Trained	1.294	−0.136
	Untrained	1.129	0.375
Item 13	Trained	1.236	−0.208
	Untrained	1.091	0.348
Item 17	Trained	1.350	0.195
	Untrained	1.131	0.687
Item 20	Trained	1.256	0.190
	Untrained	1.074	0.687

Note: Loadings are standardized factor loadings from the partial scalar model. Threshold 2 (τ₂) refers to the cut‐point separating the middle from the highest response category. Items 6, 17, 18, and 20 were freed to achieve partial scalar invariance.

3.5.1. Metric Invariance

While overall model fit supported metric invariance, some items showed noticeable variation in factor loadings between groups. For instance, Item 12 had λ = 1.280 in the trained group and λ = 1.023 in the untrained group. Similarly, Item 18 showed λ = 1.353 and λ = 1.097, respectively, and Item 14 showed λ = 1.323 and λ = 1.080. These differences, although statistically significant, did not exceed accepted thresholds for ΔCFI or ΔRMSEA, and therefore did not compromise overall metric invariance.

3.5.2. Scalar Invariance

Inspection of the thresholds revealed significant between‐group differences in the second threshold (separating the middle‐highest response). Specifically, threshold 2 was significantly higher in the trained group for Item 6. Conversely, in the untrained group, threshold 2 was significantly elevated for Items 8, 13, 14, 17, 18, and 20. To achieve an acceptable scalar solution, partial scalar invariance was imposed by freeing the second thresholds for Items 6, 17, 18, and 20. This adjustment improved overall model fit to acceptable levels (CFI = 0.997, RMSEA = 0.088), while maintaining the comparability of the measurement model across groups (Table 4).

3.5.3. Latent Means

When constraining latent means to equality across groups, model fit deteriorated substantially (CFI = 0.995, RMSEA = 0.116), indicating that full mean invariance was not supported. The trained group was fixed to zero as the reference. The untrained group showed a significantly lower latent mean (M = −0.42, SE = 0.02, p < 0.001).

4. Discussion

The present study aimed to translate, culturally adapt, and psychometrically validate the Italian version of the EBP Competency Scale originally developed by Melnyk et al. (2014, 2018). The results strongly support the validity and reliability of the adapted tool for use among Italian nurses. Factorial analyses confirmed a unidimensional structure; this supports the scale's capacity to measure a coherent and integrated EBP construct, consistent with other EBP scale validations conducted in different countries (de Pedro Gómez et al. 2009; Fu et al. 2020; Ruzafa‐Martínez et al. 2020; Shuman et al. 2018).

In previous validations of EBP‐related instruments, multiple factors capturing practice, attitudes, knowledge, skills, and use of EBP have typically emerged (de Pedro Gómez et al. 2009; Fu et al. 2020; Ruzafa‐Martínez et al. 2020; Shuman et al. 2018). Taken together, these studies conceptualize EBP competence as a constellation of correlated attitudinal, cognitive, and behavioral dimensions, whereas in our study the items behaved empirically as indicators of a single, higher‐order EBP competence factor, suggesting that respondents tend to experience EBP as a coherent and integrated capability rather than as clearly separable domains. Therefore, variability in factor structures reported internationally should not be interpreted as true conceptual inconsistency, but rather as the result of heterogeneity in item pools, cultural adaptation strategies, and clinical populations.

Reliability indices were excellent, and convergent validity estimates confirmed the scale's accuracy and precision in evaluating EBP competencies. From a measurement perspective, the demonstration of partial scalar invariance between nurses with and without formal EBP training, with only a few freed thresholds and preserved overall fit, indicates that most item parameters operate equivalently across groups. The significantly lower latent mean scores observed among untrained nurses can therefore be interpreted as reflecting true competence differences rather than measurement artifacts, consistent with previous evidence on the impact of structured education and formal training on EBP competencies (Melnyk et al. 2012; Saunders et al. 2019).

It is well established that EBP is an essential component of high‐quality healthcare, contributing to reduced clinical variability, better outcomes and more efficient use of resources (Connor et al. 2023; Dawes et al. 2005). As the largest professional group in the health sector, nurses are pivotal to the implementation of EBP in everyday practice. Because nursing competence is multidimensional and evolving (Mrayyan et al. 2023), and EBP is a core domain of this construct (Wit et al. 2023), robust assessment tools are needed to obtain a snapshot of individual competence and to inform implementation strategies over time (Landsverk et al. 2023). Integrating EBP content into undergraduate curricula and continuing professional development, supported by structured training and ongoing in‐service education, is therefore essential (Cardoso et al. 2021; Yeh et al. 2025).

The organizational context also significantly influences the development and application of EBP. Establishing a culture that supports EBP requires strong commitment and the development of systems that promote inquiry, innovation, and knowledge‐sharing. Nurse managers and clinical leaders must serve as role models and facilitate a culture of inquiry by ensuring protected time for EBP activities, integrating EBP into routine care, and fostering a continuous learning environment (Gallagher‐Ford et al. 2020; Melnyk et al. 2018; Pendoni et al. 2024; Wallen et al. 2010). Another effective strategy is the implementation of EBP mentors or clinical champions within practice settings; these figures provide real‐time guidance, encourage peer learning, and help reduce the perceived complexity of applying evidence in clinical decision‐making (Gallagher‐Ford et al. 2020; Melnyk et al. 2014).

4.1. Limitations

Despite its strengths, this study is not without limitations. The use of convenience and snowball sampling strategies may have introduced selection bias, possibly favoring individuals more engaged or motivated with respect to EBP. Moreover, although the sample was geographically diverse, the predominance of participants from hospital settings may limit the generalizability of findings to nurses in community, primary care, or long‐term care environments.

4.2. Implications for Research and Practice

The strong unidimensional saturation observed in this study, together with the large proportion of common variance explained, suggests that the Italian EBP Competence Scale possesses the foundational measurement characteristics required to support modern psychometric applications. While the present validation was conducted within a Classical Test Theory framework, the scale demonstrates features that are highly suitable for subsequent Item Response Theory (IRT) calibration (Cappelleri et al. 2014; Nguyen et al. 2014; Petrillo et al. 2015). A unidimensional and highly saturated structure is a prerequisite for the development of item banks and for the future implementation of Computer Adaptive Testing (CAT) approaches, which can considerably enhance measurement precision, reduce respondent burden, and support individual‐level score interpretation.

To further consolidate its measurement robustness, future research should investigate additional psychometric properties, such as longitudinal measurement invariance and competency development following targeted EBP interventions. These developments are essential to determine the instrument's capacity to monitor competence trajectories over time, as well as to detect meaningful change at both individual and organizational levels (Napolitano et al. 2026). Ultimately, advancing toward IRT modeling and CAT development will allow the Italian EBP Competence Scale to evolve from a highly reliable static instrument to a dynamic and scalable measurement system fully aligned with contemporary standards in health measurement science.

5. Conclusions

The present study translated, culturally adapted, and psychometrically validated the Italian version of the Evidence‐Based Practice (EBP) Competency Scale for use with registered nurses and advanced practice nurses. Findings from content validation, exploratory and confirmatory factor analyses, and reliability testing consistently supported a robust unidimensional structure, excellent internal consistency, and satisfactory measurement precision. The scale demonstrated partial scalar invariance across nurses with and without formal EBP training, allowing meaningful comparisons of latent means and confirming that lower competence scores among untrained nurses likely reflect true differences rather than measurement bias.

Taken together, these results indicate that the Italian EBP Competency Scale is a valid, reliable, and conceptually coherent instrument for assessing EBP competence in the Italian nursing context. Its use can support educational planning, inform the design and evaluation of implementation strategies, and provide healthcare organizations with a standardized metric to monitor EBP‐related capacity over time and across settings. Future studies should extend this work by examining longitudinal stability, sensitivity to change following targeted interventions, and the potential for advanced psychometric applications, such as Item Response Theory and Computer Adaptive Testing. By enabling precise and scalable assessment of EBP competence, the Italian EBP Competency Scale can contribute to strengthening evidence‐based nursing practice and, ultimately, to improving the quality and safety of patient care in Italy.

Ethics Statement

Ethical approval for the study was obtained from the local Ethics Committee (Protocol number 30.23 CET 2 CBM). The research adhered to recognized ethical standards and complied with the principles outlined in the Declaration of Helsinki (World Medical Association 2025). Before participating in the survey, all individuals received detailed information about the study procedures and provided their informed consent electronically. Participant data were stored securely, with access limited to authorized members of the research team, in accordance with confidentiality protocols and the requirements of the GDPR (Regulation—2016/679—EN—gdpr—EUR‐Lex, s.d).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Table S1: Two‐factor exploratory factor analysis (minres, oblimin rotation) based on the polychoric correlation matrix (N = 162).

Table S2: One‐factor exploratory factor analysis (minres) based on the polychoric correlation matrix (N = 162).

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.