Development and validation of a core competency evaluation scale for otolaryngology-head and neck surgery (ENT-HNS) nurse specialists

Abstract

Objective

To develop a self-perceived core competency evaluation scale for otolaryngology-head and neck surgery (ENT-HNS) nurse specialists and test its reliability and validity.

Methods

Based on theoretical analysis, a literature review, and semi-structured interviews, the item pool was established. A preliminary draft of the scale was formed through two rounds of Delphi expert consultations and a pilot test. From August to October 2024, 450 ENT-HNS nurse specialists from 25 provinces in China were selected using convenience sampling for a formal survey to screen items and test reliability and validity.

Results

The final version of the scale contains 30 items in four dimensions: clinical nursing, teaching and management, research and innovation, and professional qualities. The authority coefficients of the two rounds of experts were 0.920 and 0.925, respectively, and the Kendall’s W coefficient was 0.219 and 0.181, respectively (all P < 0.001). After three exploratory factor analyses (EFAs), four common factors were extracted, accounting for 74.543% of the cumulative variance. The results of the revised confirmatory factor analysis (CFA) model were χ2/df = 2.416, RMSEA = 0.081, TLI = 0.934, IFI = 0.941, CFI = 0.941, and NFI = 0.904. The item-level content validity index of the scale was 0.846 to 1.00, and the scale-level content validity index was 0.919. The Cronbach’s α coefficient of the total scale was 0.981, the split-half reliability was 0.941, and the test-retest reliability was 0.995.

Conclusion

The core competency evaluation scale for ENT-HNS nurse specialists has good reliability and acceptable validity and is suitable for assessing self-perceived competencies in this population.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12912-026-05037-5.

Background

As clinical medicine continues to develop, the public’s demand for high-quality healthcare services has been steadily increasing. Nurse specialists, who can provide high-quality nursing care, have gained increasing attention and recognition [1, 2]. A nurse specialist is defined as a nurse who holds a current license as a generalist nurse, has completed an education program that meets the standards for specialized nursing practice, and is authorized to work within a defined scope of practice in a specified field of nursing [3]. According to the International Council of Nurses’ framework, competence for nurse specialists is the integration of knowledge, skills, and professional judgment in daily practice to provide safe and effective care [4]. Compared to general nurses, nurse specialists not only demonstrate deep theoretical knowledge and proficient operational skills but also have extensive clinical experience. These attributes enable them to deliver specialized high-quality nursing care [5, 6].

Effectively measuring the core competencies of nurse specialists is significant because it enhances the quality of specialized nursing care, improves nursing services, evaluates nurse specialist performance, and advances their training and certification [7]. In 1996, Hamric proposed a core competency framework for advanced practice nurses that includes direct clinical practice, guidance and coaching, consultation, evidence-based practice, leadership, collaboration, and ethical decision-making [8]. Studies have indicated that the core competencies of nurse specialists can vary across different fields [9]. International research has established evaluation tools to assess the core competencies of nurse specialists in fields such as heart failure [10], hemophilia [11], and ambulance services [12]. Chinese scholars have also developed evaluation systems for nurse specialists in sleep medicine [13], traditional Chinese medicine [14], and liver transplantation [15].

The ears, nose, and throat perform critical daily functions, including hearing, balance, smell, speech, respiration, and swallowing. Diseases affecting these organs not only impair physiological functions but also result in psychological issues, significantly reducing patients’ quality of life [16, 17]. As head and neck oncology management becomes increasingly complex, multidisciplinary collaboration has become essential and requires highly specialized healthcare professionals [18]. Research demonstrates that high-quality nursing care can enhance the effectiveness of surgery by reducing complications and improving quality of life, underscoring the urgent need for highly educated and qualified ENT-HNS nurse specialists [19]. England has established the first tracheostomy clinical nurse specialist since 2001 [20], followed by Scotland since 2009 [21]; concurrently, Northern Ireland has documented the inaugural head and neck oncology clinical nurse specialist since 2001 [22].In recent years, the Chinese Nursing Association and some provincial nursing associations have launched training programs for ENT-HNS nurse specialists. While the number of nurse specialists has increased, there are no specific scales to assess the core competencies of ENT-HNS nurse specialists. Han Yu et al. conducted preliminary research on the job functions of clinical nurse specialists in speech and swallowing rehabilitation in China, but the evaluation indicators are limited to this field. They cannot be used to assess the core competencies of ENT-HNS nurse specialists [23]. Wu et al. constructed a core competency evaluation index system for otolaryngology nurse specialists but did not conduct validation testing, making it difficult to assess validity and reliability [24]. To advance high-quality nursing care and address the research gap, this study aims to develop and verify a core competency evaluation scale for ENT-HNS nurse specialists.

Methods

Study design

The study design references the COSMIN (Consensus-based Standards for the selection of health status Measurement Instruments) checklist [25] and the standardized procedure for scale development [26] and comprises three stages (Fig. 1). The detailed mapping of each measurement property to the COSMIN domains is provided in Supplementary S1.

Fig. 1.

Three stages in the scale development

Stage 1: Establishing the item pool

Literature review

This study was based on the competency framework for Chinese registered nurses [27] and the core competency framework for advanced practice nurses [8]. Using the keywords “otolaryngology/ ear/ nose/ throat/ ENT”, “head and neck”, “specialist nurse”, “nurs* specialist”, “CNS”, and “competenc*”, we systematically searched PubMed, Web of Science, Embase, CINEHL, and some Chinese database like China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Chinese Journal Service Platform, and China Biology Medicine (CBM) for articles published from inception to December 31, 2023. The inclusion criteria included surveys, interventional studies, and practice guidelines related to the evaluation of core competency for nurse specialists or ENT-HNS nurse specialists. Case reports, conference abstracts, articles that could not be retrieved in full-text, and literature not in English or Chinese were excluded.

Our search identified 4,518 documents, of which 2,843 remained after duplicates were removed. After two rounds of screening, 12 articles were considered eligible for inclusion. The PRISMA flow diagram and items extraction summary are provided in Supplementary S2.

Qualitative interviews

From March 1, 2024, to April 30, 2024, convenience sampling was used to select 12 healthcare staff from four tertiary-level general hospitals in Guangzhou for semi-structured interviews. Eligible participants should have advanced education (bachelor’s degree or above) and at least five years of experience in clinical nursing, clinical medicine, or nursing management in ENT-HNS. After obtaining informed consent, semi-structured interviews lasting 30–45 min were conducted to explore the key capabilities. All interviews were audio-recorded and transcribed verbatim. Two researchers independently coded the transcripts and reached consensus through discussion. Saturation was achieved after 12 interviews (no new themes in two consecutive interviews). Participant characteristics and the full interview guide are provided in Supplementary S3. Data were analyzed using Colaizzi’s phenomenological method [28].

Forty-two items were derived from the literature review and qualitative interview, including clinical nursing (14 items), critical thinking (5 items), teaching and management (12 items), research and innovation (6 items), and professional qualities (5 items).

Stage 2: Delphi expert consultation

From May 15, 2024, to July 31, 2024, 26 experts from 14 provinces in China were selected using convenience sampling to participate in two rounds of consultation to collect expert opinions and reach consensus on the derived items. All included experts have advanced education and have worked in ENT-HNS nursing, clinical medicine, or nursing management for 10 years or more; (2) associate senior title or above; if the work experience in the relevant field exceeds 20 years, the requirement may be relaxed to intermediate title.

Participants were invited to complete a questionnaire either online or in person. The questionnaire consists of four sections (Supplementary S4): (1) instructions detailing the purpose, completion guidelines, and key notes; (2) an expert profile to gather basic information; (3) item evaluation and revision suggestions. In this section, participants were asked to score the importance of derived items, using a prespecified importance scoring system (5 = very important, 4 = important, 3 = moderately important, 2 = not very important, 1 = not important) and relevance scoring (1 = not relevant, 2 = weakly relevant, 3 = moderately relevant, 4 = very relevant); (4) familiarity level and judgment criteria survey.

The response rate, authority coefficient, Kendall’s W coefficient, coefficient of variation (CV), importance score, and full score rate of the questionnaire were calculated in each consultation round. Indicator screening: items with a mean ≤ 3.50 or a full score rate ≤ 0.20 were deleted; items with CV > 0.25 or with expert suggestions for revision were discussed by the research team and revised accordingly [25]. Consequently, 15 items were revised, 7 removed, and 2 added. After the Delphi process, the scale consisted of 5 dimensions and 37 items.

Pilot test

In August 2024, 25 ENT-HNS nurse specialists in Guangdong Province, affiliated with either the Chinese Nursing Association or the Provincial Nursing Association, were recruited via convenience sampling for a pilot test. The results showed that the scale’s content was clear and easy to understand, and that it took 5–8 min to complete. No adjustments were made to the scale.

Stage 3: Item analysis, validity, and reliability testing

From August to October 2024, 450 ENT-HNS nurse specialists from 25 provinces in China were recruited using a similar sampling method and inclusion criteria for the formal survey. The standards for validity and reliability testing require a sample size of 5–10 times the number of questionnaire items [29]. Considering different samples are required for EFA and CFA, a 10% invalid questionnaire rate, and 37 items in this study, the estimated sample size ranges from 405 to 611. A total of 450 questionnaires were distributed, and 443 were returned, resulting in a valid response rate of 98.4%.

Item analysis

An item analysis was conducted to assess item quality. Items were deleted using the following criteria [25, 26]: (1) if the selection frequency (the frequency of an item being selected) exceeded 80%; (2) if the critical ratio was less than 3 or not significant when comparing items between the high score group and the low score group; (3) if the Pearson correlation coefficients between the scores of each item and the total score were less than 0.4 or statistically insignificant; (4) if Cronbach’s α coefficient was improved after the item was removed.

Validity analysis

Validity was evaluated through structural, convergent, discriminant, and content validity. Structural validity was examined using EFA and CFA [30]. EFA was performed when Bartlett’s sphericity test was significant (P < 0.05) and KMO > 0.900 [31], using principal component analysis with varimax rotation. Factors were required to have at least three items; items with factor loadings < 0.40, double loadings, or similar loadings (all > 0.4 and difference < 0.05) were deleted [26]. CFA was conducted using maximum likelihood estimation to evaluate model fit; good fit was defined as Chi-square/ degree of freedom (χ²/df) < 3.000, root mean square error of approximation (RMSEA) < 0.080, standardized root mean residual (SRMR) < 0.05, comparative fit index (CFI) > 0.900, Tucker-Lewis index (TLI) > 0.900, incremental fit index (IFI) > 0.900, and the normed fit index (NFI) > 0.900 [31]. Convergent validity was considered adequate when the average variance extracted (AVE) > 0.5 [32]. Discriminant validity was supported if the absolute correlation between any two factors was less than the square root of their respective AVE [32]. Content validity was assessed using item-level (I-CVI) and scale-level (S-CVI) indices. I-CVI > 0.78 and S-CVI > 0.9 indicated good content validity [33].

Reliability analysis

Reliability was assessed using internal consistency, split-half, and test-retest reliability. Internal consistency was evaluated using Cronbach’s α, with values ≥ 0.7 considered acceptable [29]. Split-half reliability was measured by odd-even correlation, where a coefficient > 0.8 indicates good consistency [29]. Test-retest reliability was assessed using the intraclass correlation coefficient (ICC) with a two-way random effects model for absolute agreement and single measurement. Using convenience sampling, 45 respondents from the formal survey were selected for a follow-up survey two weeks after the initial study. An ICC ≥ 0.70 indicates good test-retest reliability [34].

Statistical analysis

The data was analyzed using SPSS 25.0 and AMOS 24.0. Demographic characteristics were described using frequency and proportions.

Items were screened using the item distribution method, the critical ratio method, the correlation coefficient method, and the Cronbach’s α coefficient method. EFA and CFA were used to test the structural validity. Five a priori hypotheses were formulated based on the theoretical framework before any confirmatory analysis was conducted. The I-CVI and S-CVI were used to evaluate content validity, and internal consistency, split-half, and test-retest reliability were used to evaluate reliability.

Ethical review

This study was approved by the Ethics Committee of the First Affiliated Hospital of Sun Yat-sen University (No. 2024229), and the research process strictly adhered to the ethical guidelines. All participants signed an informed consent form and have the right to withdraw from the study.

Results

Delphi expert consultation results

Table 1 shows the demographic characteristics of 26 experts who participated in the Delphi consultation. The average age of the experts was 48.08 ± 6.41 years, with an average work experience of 28.04 ± 8.08 years.

Table 1.

Demographic characteristics of the experts in the Delphi consultation stage (n = 26)

Item	Category	Number	Proportion (%)
Gender	Male	2	7.69
	Female	24	92.31
Age (years)	≤40	3	11.54
	41–50	13	50.00
	51–60	9	34.61
	≥61	1	3.85
Education	Bachelor	20	76.92
	Master	3	11.54
	Doctor and above	3	11.54
Professional title	Intermediate	4	15.38
	Associate senior	13	50.00
	Senior	9	34.62
Current field of work	Clinical nursing	3	11.54
	Clinical medicine	3	11.54
	Nursing management	20	76.92
Years of work experience	10–20	6	23.09
	21–30	9	34.61
	31–40	9	34.61
	≥41	2	7.69

Table 2 presents the initiative, authoritativeness, coordination level, and centralization level of expert opinions. The experts in both rounds of consultations had a high degree of consensus on the importance of each item.

Table 2.

Summary and statistical table of expert opinions (n = 26)

Item	Response rate	Authority coefficient	Kendall’s W coefficient	Importance scores for each dimension and item	CV	Full score rate
Round 1	90.00%	0.920	0.219**	4.23-5.00	0.066–0.135	0.38-1.00
Round 2	96.30%	0.925	0.181**	4.35-5.00	0-0.163	0.42-1.00

Note: ** indicates P < 0.01

Item analysis results

Item analysis revealed that the selection rate of each item was below 80%, indicating good discriminative ability for all items. All absolute critical ratios were greater than 3 and statistically significant. All Pearson correlation coefficients between each item’s scores and the total score were greater than 0.4 and statistically significant. The Cronbach’s α coefficient of the scale was 0.985, and after deleting a specific item, the coefficient did not increase significantly. Therefore, no items were deleted based on the item analysis results.

Validity analysis results

Structural validity results

The total sample (n = 443) was randomly split into EFA (n = 222) and CFA (n = 221). Table 3 presents the characteristics of participants. No significant differences were found in the two groups.

Table 3.

Characteristics of participants in the validation stage (n = 443)

General characteristics	EFA sample (n = 222)	CFA sample (n = 221)	t/χ²	P
Age	35.94 ± 5.27	35.48 ± 5.25	0.916	0.360
Gender			0.000	0.997
Male	1 (0.45)	1 (0.45)
Female	221 (99.55)	220 (99.55)
Highest level of education			4.175	0.124
Associate degree	8 (3.61)	16 (7.24)
Bachelor	203 (91.44)	199 (90.05)
Master	11 (4.95)	6 (2.71)
Marital status			0.024	0.988
Unmarried	31 (13.96)	32 (14.48)
Married	188 (84.68)	186 (84.16)
Divorced	3 (1.36)	3 (1.36)
Title			1.826	0.609
Registered Nurse	39 (17.57)	42(19.00)
Supervisor Nurse	158 (71.17)	162 (73.30)
Associate Professor of Clinical Nursing	21 (9.46)	15 (6.79)
Professor of Clinical Nursing	4 (1.80)	2 (0.91)
Years of specialized work experience	11.44 ± 4.77	11.45 ± 5.38	-0.023	0.982
Training institution			2.769	0.096
Chinese Nursing Association	128 (57.66)	110 (49.77)
Provincial Nursing Association	94 (42.34)	111 (50.23)

EFA results

Table 4 displays the loadings matrix of the items in the third EFA. Four common factors were extracted, accounting for 74.543% of the cumulative variance. Items 16, 18, 19, and 17 of the critical thinking dimensions were deleted due to double loading (detailed factor loadings are provided in Supplementary S5).

Table 4.

Loadings matrix of the items in the third EFA (n = 222)

Item	Factor 1	Factor 2	Factor 3	Factor 4
1. Demonstrate mastery of the anatomy and physiology in ENT-HNS.	0.588	0.169	0.302	0.464
2. Accurately interpret the results of common specialized examinations in ENT-HNS.	0.645	0.164	0.195	0.448
3. Master the administration methods, side effects, and precautions of drugs commonly used in ENT-HNS.	0.738	0.141	0.262	0.308
4. Apply the principles of treatment and nursing care for common diseases in ENT-HNS.	0.750	0.188	0.287	0.229
5. Apply the principles of treatment and nursing care for emergencies in ENT-HNS.	0.759	0.288	0.312	0.038
6. Able to assess and solve difficult and complex nursing problems in ENT-HNS.	0.531	0.584	0.273	0.101
7. Demonstrate the mastery of perioperative management according to Enhanced Recovery After Surgery (ERAS) protocols, including nutrition management, pain management, and thrombosis prevention.	0.728	0.351	0.247	0.153
8. Identify and manage emergencies effectively for postoperative complications in ENT-HNS.	0.676	0.436	0.295	0.177
9. Demonstrate proficiency in specialized nursing care and operations in ENT-HNS.	0.733	0.317	0.343	0.084
10. Able to perform specialized nursing physical examination in ENT-HNS.	0.734	0.343	0.221	0.182
11. Provide practical nursing cooperation during common rescue procedures in ENT-HNS.	0.691	0.431	0.344	0.123
12. Properly use, maintain, and manage specialized instruments.	0.633	0.410	0.238	0.232
13. Be proficient in common rehabilitation training for ENT-HNS patients.	0.573	0.362	0.339	0.282
14. Able to implement personalized health education for patients in ENT-HNS patients and their families.	0.581	0.462	0.436	0.081
15. Able to offer psychological counseling and emotional support for patients in ENT-HNS.	0.406	0.347	0.569	0.164
20. Able to take the initiative to learn and acquire cutting-edge knowledge in ENT-HNS.	0.341	0.579	0.244	0.382
21. Plan and develop personal core competencies according to the requirements of specialty development.	0.298	0.682	0.289	0.317
22. Demonstrate leadership to improve team performance.	0.280	0.735	0.333	0.219
23. Demonstrate strong communication and teamwork skills.	0.359	0.572	0.487	0.149
24. Analyze and improve the quality of nursing care in the specialty.	0.340	0.725	0.248	0.325
25. Possess effective teaching skills.	0.271	0.689	0.226	0.418
26. Possess effective clinical education skills.	0.345	0.657	0.368	0.268
27. Conduct specialty nursing consultations.	0.210	0.757	0.173	0.299
28. Conduct specialized nursing rounds and participate in difficult case discussions.	0.401	0.716	0.183	0.297
29. Promote and popularize knowledge related to ENT-HNS.	0.354	0.586	0.207	0.372
30. Conduct literature search.	0.213	0.391	0.143	0.754
31. Apply evidence-based nursing care.	0.195	0.396	0.122	0.785
32. Engage in scientific research and innovation (e.g., publications, patents, new technologies, group standards, projects).	0.159	0.440	0.123	0.742
33. Familiar with relevant laws, regulations, professional codes, and standards, and adhere strictly to them.	0.307	0.198	0.523	0.447
34. Demonstrate professionalism and dedication to ENT-HNS nursing.	0.292	0.232	0.828	0.191
35. Maintain a positive professional attitude and commitment to career.	0.313	0.254	0.813	0.125
36. Show empathy with ENT-HNS patients and demonstrate critical thinking during their care.	0.360	0.231	0.818	0.081
37. Demonstrate emotional resilience and effective self-regulation in clinical practice.	0.331	0.284	0.782	0.146

The EFA results indicated that both the KMO and Bartlett’s sphericity tests were satisfactory. Figure 2 shows the scree plot, which indicates that extracting four common factors was appropriate. The loading values for each item in the corresponding factors were all > 0.4, with no double loading, as shown in Table 4. After EFA, the core competency evaluation scale for ENT-HNS nurse specialists had 4 dimensions and 33 items.

Fig. 2.

Scree plot for the core competency evaluation scale for ENT-HNS nurse specialists(n = 222)

CFA results

Figure 3 shows the results of the CFA. Based on modification indices and expected parameter changes, items 15, 33, and 27 were deleted: item 15 overlapped conceptually with item 36 (both related to empathy and humanistic care); item 33 represented a general nursing requirement rather than a specialty-specific competency; and item 27 lacked specificity as a standalone indicator, as consultation competence reflects a composite of multiple abilities. Eight within-factor residual covariances were added (see Supplementary S5 for the theoretical justifications). The revised model fit indices were χ²/df = 2.416, RMSEA = 0.081, SRMR = 0.041, CFI = 0.941, TLI = 0.934, IFI = 0.941, and NFI = 0.904. RMSEA = 0.081 indicates acceptable fit. SRMR = 0.041 meets the COSMIN criterion for sufficient structural validity, though model modifications were not independently validated. After CFA, the core competency evaluation scale for ENT-HNS nurse specialists had 4 dimensions and 30 items.

Fig. 3.

CFA structural model of the core competency evaluation scale for ENT-HNS nurse specialists (n = 221)

Convergent validity results

The results of the convergent validity analysis showed that all AVEs exceeded 0.5 and all composite reliabilities exceeded 0.7, demonstrating good convergent validity of the scale.

Discriminant validity results

Table 5 shows the results of the discriminant validity analysis. The results indicated that, except for teaching and management, the absolute values of the correlation coefficients between any two factors are smaller than the square root of the corresponding factor’s AVE, indicating a certain degree of discriminant validity.

Table 5.

Discriminant validity analysis results

Variable	Professional qualities	Teaching and management	Research and innovation	Clinical nursing
Professional qualities	0.957
Teaching and management	0.819**	0.887
Research and innovation	0.544**	0.777**	0.892
Clinical nursing	0.833**	0.922**	0.680**	0.870

Note: diagonal elements are the square roots of the corresponding dimension AVE; ** indicates P < 0.01

Dimension mean scores were: professional quality (4.578 ± 0.608), clinical nursing (4.471 ± 0.576), teaching and management (4.337 ± 0.650), and research and innovation (3.877 ± 0.837). Professional quality was the highest-ranked dimension, while research and innovation was the lowest, thus supporting Hypothesis 4 (research and innovation lowest) but not Hypothesis 3 (clinical nursing highest). Hypothesis testing using known-group comparisons (professional title, work years) confirmed 4 out of 5 a priori hypotheses (80%), meeting the COSMIN criterion of ≥ 75% confirmation for sufficient construct validity (see Supplementary S1 for detailed hypothesis testing results).

Content validity results

The I-CVI values for this scale range from 0.846 to 1.00, with an average I-CVI of 0.953 and an S-CVI of 0.919.

Reliability analysis results

Table 6 shows the results of the reliability analysis. The Cronbach’s α coefficient for the total scale was 0.981, and each dimension’s Cronbach’s α coefficient exceeded 0.7, indicating good internal consistency. The split-half reliability was 0.941, and each dimension’s reliability exceeded 0.8, indicating good split-half reliability. Repeated survey of 45 ENT-HNS nurse specialists showed that the test-retest reliability of the total scale was 0.995 (95% CI: 0.992–0.997, P < 0.001), and the test-retest reliability of each dimension ranged from 0.973 to 0.996, suggesting good test-retest reliability. The final 30-item scale is provided in Supplementary S6.

Table 6.

Reliability analysis results

Dimension	Number of items	Cronbach’s α coefficient	Split-half reliability	Test-retest reliability
Clinical nursing	14	0.971	0.954	0.996
Teaching and management	9	0.963	0.937	0.989
Research and innovation	3	0.914	0.829	0.973
Professional quality	4	0.966	0.960	0.979
Total	30	0.981	0.941	0.995

Discussion

The significance and innovation of the scale

This study developed and psychometrically validated the first Core Competence Evaluation Scale for ENT-HNS nurse specialists in China, addressing a critical gap in specialty-specific assessment tools. The scale was developed referencing COSMIN guidelines through a rigorous four-phase process: integrating established competency frameworks [8, 27], qualitative interviews with 12 clinical experts, a two-round Delphi survey (26 experts from 14 provinces, authority coefficient = 0.925), and psychometric validation (N = 443). This approach reflects best practice in nursing instrument development [26]. The Delphi method, with its anonymity and iterative feedback, effectively minimized authority bias and enabled consensus among geographically diverse experts [35]. Overall, the scale demonstrated high internal consistency, although the very high Cronbach’s α may also suggest potential item redundancy (Cronbach’s α = 0.981; test-retest reliability = 0.995), and acceptable validity (CFI = 0.941, TLI = 0.934, RMSEA = 0.081; S-CVI = 0.919) [1–3]. The 98.4% response rate and 5-8-minute completion time support clinical feasibility, which is critical in busy clinical settings [26].

Dimensional structure and theoretical interpretation

The EFA identified four factors explaining 74.5% of the variance: clinical nursing (43.3% of items), professional quality (20.0%), teaching and management (23.4%), and research and innovation (13.3%). The initial “critical thinking” dimension was removed due to cross-loadings > 0.4 across three factors. Rather than indicating psychometric weakness, this finding aligns with contemporary theory, which positions critical thinking as a meta-competency embedded within clinical reasoning, teaching, and research rather than an isolated dimension [36, 37].

CFA required model refinement based on statistical indicators and theoretical rationale [26]. Three items were removed due to conceptual overlap or lack of specificity. After adding eight theoretically justified covariances, the revised model demonstrated acceptable fit: CFI = 0.941, TLI = 0.934, RMSEA = 0.081. All indices, except RMSEA (slightly above 0.08), met the recommended thresholds [26, 31]. AVE values exceeded 0.5 for all dimensions, supporting convergent validity; however, discriminant validity was not fully supported, particularly because the correlation between clinical nursing and teaching-management (0.922) exceeded the square root of AVE for teaching-management (0.887), suggesting that clinical, teaching, and management roles overlap in specialist nursing practice.

Hypothesis 3 was not supported. Professional quality, rather than clinical nursing, emerged as the highest-ranked dimension. This finding is consistent with the self-report literature, where attitudinal competencies (e.g., professional values, empathy, commitment) tend to be rated higher than specific technical competencies in self-assessments [38, 39]. This may reflect that nurses evaluate their professional attitudes more favorably than their specific clinical skills, which are more susceptible to critical self-judgment.

Clinical interpretation and implication

The four-dimensional structure reflects the unique demands of ENT-HNS practice. The predominance of clinical nursing appropriately prioritizes direct patient care, addressing airway safety and functional preservation. For example, item 11 addresses nursing cooperation in common ENT-HNS emergencies, including airway foreign body removal, emergency tracheotomy, and severe epistaxis. Nurse specialists require proficient rescue skills to prevent adverse events such as asphyxia. This finding is consistent with Hu et al.‘s research on emergency nursing in otorhinolaryngology [40].

The professional quality dimension addresses the distinctive psychosocial burden in this population, including sensory loss, visible disfigurement, and depression rates reaching 64.2% in head and neck cancer survivors—nearly double that of other cancer populations [41]. This dimension distinguishes ENT-HNS nursing from ICU or OR specialties, which emphasize technical algorithms over holistic care [42, 43].

The inclusion of teaching-management and research-innovation is consistent with the International Council of Nurses’ advanced practice standards [4]. Teaching-management acknowledges the nurse specialists’ role in translating rapidly technological advances into standardized nursing protocols and clinical education. Research-innovation positions the ENT-HNS nurse specialist as an evidence generator rather than a passive consumer and responds to the needs of the development of the Chinese nursing discipline. This dual emphasis aligns with Benner’s framework, in which expert nurses assume responsibility for disseminating knowledge and creating evidence within their specialty [44].

Based on current evidence, the scale is primarily intended for identifying training needs and self-assessment. For example, gap analysis can identify specific competency weaknesses, which may help address the persistent training-use gap in Chinese specialist nursing [45]. Future studies may explore its use for credentialing or promotion, but this would require substantial additional validation and remains exploratory at this stage.

Limitations

This study has several limitations. First, convenience sampling was used. Although participants came from 25 provinces, selection bias cannot be ruled out entirely. Future multi-center stratified random sampling would strengthen representativeness. Second, the scale is self-reported, measuring perceived rather than objective competence. Social desirability and self-perception bias may therefore influence responses. Third, the CFA model was modified based on the same dataset (item deletions and added covariance paths), which carries a risk of overfitting. The factor structure should ideally be confirmed in an independent sample. Fourth, discriminant validity was not fully supported, and the high Cronbach’s α (0.981) suggests possible item redundancy. Future refinements could merge or reduce items. Fifth, according to the COSMIN framework, criterion validity and responsiveness were not tested. Finally, the scale was developed and validated only in the Chinese healthcare context. Cross-cultural adaptation and testing are needed before international implementation. We hope these limitations will be addressed in future research to improve the scale further.

Conclusion

This study provides a reliable, valid, and practical instrument for assessing self-perceived competencies of ENT-HNS nurse specialists in China. The 30-item, four-dimensional scale captures essential domains of specialist practice and has strong psychometric properties supporting its use for self-assessment and identification of training needs. As the first tool of its kind, it offers a foundation for advancing professional standards and may inform training and professional development in this specialized field.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

ENT-HNS

Otolaryngology-head and neck surgery

EFA

Exploratory Factor Analysis

CFA

Confirmatory Factor Analysis

COSMIN

Consensus-based Standards for the selection of health status Measurement Instruments

CV

Coefficient of Variation

RMSEA

Root Mean Square Error of Approximation

SRMR

Standardized Root Mean Residual

CFI

Comparative Fit Index

TLI

Tucker-Lewis Index

IFI

Incremental Fit Index

NFI

Normed Fit Index

AVE

Average Variance Extracted

I-CVI

Item-level Content Validity Index

S-CVI

Scale-level Content Validity Index

ICC

Intraclass Correlation Coefficient

Author contributions

R.Y.Y., W.X., C.C.L., X.L.Y., and L.J.H contributed to the research design. R.Y.Y., W.X., F.L.W, and J.L.W. contributed to the data collection. R.Y.Y. and L.J.H. contributed to the data analysis. R.Y.Y. wrote the main manuscript text and revised it with L.J.H. All authors reviewed the manuscript.

Funding

This study was supported by the Nursing Talent Training Program of the First Affiliated Hospital of Sun Yat-sen University (Approval No. KLHL2023AF01).

Data availability

All data supporting the findings of this study are available within the paper and its supplementary information.

Declarations

Ethics approval and consent to participate

This study was approved by the Ethics Committee of the First Affiliated Hospital of Sun Yat-sen University (No. 2024229), and the research process strictly adhered to the ethical guidelines. All participants signed an informed consent form and have the right to withdraw from the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.