Reliability and validity testing the Chinese version of the nursing surveillance scale: a cross-sectional study

Abstract

Background

Nursing surveillance is an essential process that allows nurses to ensure patient safety and prevent further deterioration in their condition. At present, there is no specialized tool in China to evaluate nurses’ surveillance within the framework of multiple dimensions. The aim of this study was to translate the Nursing Surveillance Scale into Chinese and to evaluate its psychometric properties, including reliability and validity, among nurses in China.

Method

A total of 629 clinical nurses from Grade III Level A hospitals in Liaoning, Zhejiang, and Jiangxi Provinces were recruited through convenience sampling in April 2025. With the consent of the original author, the scale was translated according to Brislin’s guidelines, and item analysis, reliability, and validity testing were performed using general data and the Chinese version of the Nursing Surveillance Scale. Data were analyzed using SPSS 29.0 and AMOS 27.0.

Results

Item analysis retained 16 items in the final Chinese version of the Nursing Surveillance Scale. The scale showed good reliability, with Cronbach’s α = 0.891, split-half reliability = 0.928, and test–retest reliability = 0.908. The content validity index was 0.938. Exploratory factor analysis identified four factors—Problem Prediction and Decision-Making, Systematic Assessment, Pattern Recognition, and Identifying Patient Self-Care and Coping Strategies—which explained 68.41% of the total variance. Confirmatory factor analysis supported the structural validity (CMIN/DF = 1.559, GFI = 0.942, NFI = 0.942, IFI = 0.978, TLI = 0.973, CFI = 0.978, RMSEA = 0.042, RMR = 0.029). Convergent validity was confirmed, with AVE values ranging from 0.500 to 0.730 and CR values from 0.823 to 0.897. Discriminant validity was also supported, as the square roots of AVE (0.707–0.854) exceeded the inter-factor correlations.

Conclusion

The Chinese version of the Nursing Surveillance Scale shows acceptable reliability and validity and provides an appropriate tool for evaluating nurses’ monitoring capabilities.

Background

Preventable in-hospital deaths remain a major concern for patient safety worldwide. A systematic review and meta-analysis estimated that about 3.1% of hospital deaths are preventable, corresponding to roughly 22,165 cases each year in the United States [1]. Among patients with an expected survival of more than three months, preventable deaths account for as many as 7,150 annually. Most of these deaths are linked to delays in recognizing changes in patient conditions and in initiating appropriate interventions. A retrospective study at a secondary teaching hospital in Finland also found that only 4.7% of in-hospital unexpected deaths were assessed as potentially or highly preventable [2]. These patients were typically younger and had fewer comorbidities, and the associated years of life lost were minimal. Although the proportion of preventable in-hospital deaths varies across different healthcare systems, clinical consensus holds that early identification of patient conditions and timely intervention are critical steps in reducing such deaths [3].

Nurses are a fundamental part of the healthcare system. The World Health Organization’s (WHO) 2020 State of the World’s Nursing Report [4] highlighted that nurses deliver more than 80% of primary healthcare services worldwide, and their professional competence has a direct influence on patient safety, healthcare quality, and the resilience of health systems. The 2025 Global State of the Nursing Report [5] indicates that nurses represent the largest group within the global healthcare workforce and continue to face challenges such as staff shortages. Nurses fulfill multiple roles within the healthcare system, which are essential for maintaining patient safety and safeguarding high-risk populations [6]. At the clinical level, nurses serve not only as implementers of treatment plans but also as a vital line of defense for patient safety [7, 8]. Evidence shows that nurse-led real-time surveillance can reduce adverse events in hospitalized patients [9], while early warning systems can help prevent severe complications and deaths among emergency patients [10]. Therefore, nurses play an essential role in clinical surveillance, acting as the primary professionals responsible for observing patient conditions, collecting clinical data, and initiating early interventions. Surveillance is a fundamental approach to ensuring patient safety and supporting clinical decision-making [11]. It entails the continuous and systematic collection of clinical information to monitor disease progression, evaluate treatment effectiveness, and identify potential risks [12]. Surveillance is reflected in early warning and timely intervention [13], particularly in the complex clinical practice of nurses, who rely on their professional knowledge and early recognition skills to monitor changes in patients’ conditions in real time and provide prompt feedback and interventions [14]. Therefore, the effectiveness of nursing surveillance is closely associated with patient treatment outcomes. The Nursing Intervention Classification (NIC) [15] is a standardized system of nursing activities designed to promote patient recovery, grounded in clinical judgement and comprehensive medical knowledge. Within this framework, NIC defines nursing surveillance as “the purposeful and continuous acquisition, interpretation, and synthesis of patient data to support clinical decision-making” [15]. Halverson and Tilley [11] suggest that nursing surveillance is a multidimensional concept encompassing not only five key attributes—systematic process, pattern recognition, coordinated communication, anticipation of instability, and decision-making—but also factors such as nurse education, clinical expertise, staffing levels, and the organizational culture of surveillance over time. Nursing surveillance plays a critical role in ensuring patient safety, particularly in complex cases. Kim and Cho [16]_, drawing on the hybrid model proposed by Schwartz-Barcott and Kim [17], further analyzed the concept of nursing surveillance. The study identified the characteristics of nursing surveillance as “system assessment,” “pattern recognition,” “the anticipation of problems,” “effective communication,” “decision-making,” and “performing nursing practice.” It concluded that nursing surveillance is a comprehensive intervention that integrates both behavioral and cognitive components. Previous research emphasizes that the early identification of patient deterioration is critical for preventing severe but avoidable adverse hospital outcomes [10]. Sarah Collins Rossetti et al. [18] applied real-time nursing surveillance documentation patterns in their machine learning algorithm through the Communicating Narrative Concerns Entered by RNs Early Warning System (CONCERN EWS) to identify patients at risk of deterioration. Compared with most early warning systems (EWS), CONCERN EWS can predict all-cause deterioration up to 42 hours in advance. By utilizing nursing surveillance patterns instead of relying solely on physiological indicators, this approach addresses the inherent limitations of physiological measures. The study results showed [18] a 35.6% reduction in in-hospital mortality risk, an 11.2% reduction in length of stay, a 7.5% decline in the risk of in-hospital sepsis, and a 24.9% increase in the likelihood of unexpected ICU transfer. These findings highlight the importance and necessity of nursing surveillance in early warning systems. Nurses are often the first to detect changes in patients’ conditions and can take timely actions to prevent deterioration [19]. In a prospective cohort study [20], stroke patients who received vital signs monitoring every six hours, compared with the conventional twelve-hour interval, were found to have a significantly lower 30-day mortality rate.

Nursing surveillance is no longer limited to data collection but now involves continuous, real-time, and multidimensional surveillance [21]. Kelly [22] emphasized that nursing surveillance is a complex concept that cannot be assessed merely by acknowledging its presence. The authors adopted activities from the NIC system as a tool to measure surveillance practices and developed a scale that incorporated related concepts. However, the length of the questionnaire resulted in a low completion rate, and the validity of the tool was not reported. The authors highlighted the need to develop a nursing surveillance instrument that addresses multiple dimensions in the future. Building on this, Kim and his research team [23], drawing from the NIC surveillance activities, successfully developed a nursing surveillance scale with four attributes to evaluate nurses’ surveillance competence.At present, there is no tool in China to assess nurses’ clinical surveillance within a multidimensional conceptual framework. In addition, no translated versions of this scale exist in other languages, and no studies have reported the psychometric evaluation of such translations. Accordingly, this study is the first to translate the Nursing Surveillance Scale into Chinese, carry out cross-cultural adaptation, and evaluate its psychometric properties, including reliability and validity, among clinical nursing professionals in China. Our objective is to obtain a more precise understanding of Chinese nurses’ practices in implementing nursing surveillance for patients. The findings will facilitate a deeper understanding of nursing surveillance within a multidimensional conceptual framework and provide a reference for improving training strategies in healthcare institutions. The findings will also provide a theoretical basis for reducing the likelihood of patient harm, protecting patient safety [24], and improving the quality of nursing care services.

Method

Study design and participants

This cross-sectional study evaluated the Chinese version of the Nursing Surveillance Scale. Data were collected in April 2025 from 629 clinical nurses recruited through convenience sampling from Grade III Level A hospitals in Liaoning, Zhejiang, and Jiangxi provinces.

Inclusion criteria were as follows: (1) possession of a valid nursing licence; (2) at least six months of clinical work experience; and (3) voluntary participation with signed informed consent. Exclusion criteria were (1) nurses currently engaged in further training, rotation, or internship in the surveyed departments and (2) nurses on leave from employment, including marriage leave, sick leave, or maternity leave. According to the rough estimation method for determining sample size, the reliability and validity of a questionnaire should be tested with a sample size of 5–10 times the number of items in the questionnaire [25]. Larger samples are recommended for exploratory and confirmatory analyses to ensure the stability of the factor structure [26]. The original Nursing Surveillance Scale consists of 16 items. Using the upper limit of 10 times the number of items and allowing for a 20% attrition rate, at least 300 participants were required. Therefore, a total of 629 participants were included in this study.

Measurement and instruments

General demographic characteristics

Based on the study objectives, the researchers developed a questionnaire to collect general demographic information. The questionnaire included questions on age, gender, educational level, marital status, vocational position, positional titles, department, and working years.

Nursing surveillance scale

The Nursing Surveillance Scale, developed by Kim and Cho [23], comprises 16 items across four dimensions: anticipation of problems and decision-making (6 items), systematic assessment (5 items), recognition of patterns (3 items), and identification of patients’ self-care and coping strategies (2 items). The scale employs a five-point Likert scale ranging from 0 (never) to 4 (always). The overall score is calculated as the mean of all item scores, with higher scores reflecting stronger nursing surveillance performance. The original version demonstrated a Cronbach’s α of 0.90, while the coefficients for the four dimensions ranged from 0.71 to 0.87. Four common factors were identified in the original scale, explaining 70.1% of the cumulative variance, with CFI = 0.964, RMSEA = 0.055, CMIN = 1.65, SRMR = 0.048, GFI = 0.921, NFI = 0.916, TLI = 0.955, and χ² = 155.62 (df = 94, p < 0.001).

Procedure

Translation procedure

With the permission of the original scale author, Mi-Kyoung Cho [23], we translated, back-translated, and cross-culturally adapted the scale using Brislin’s back-translation model [27]. The procedure was as follows: (1) Translation: A graduate student in nursing and another in English independently translated the original English version of the Nursing Surveillance Scale, producing two Chinese versions (A1 and A2). Differences were reconciled through discussion, and the two versions were integrated into a single direct-translation Chinese version (Version A). (2) Back-translation: A nursing master’s degree holder with overseas exchange experience and a graduate-level English instructor independently translated Version A into two English versions (B1 and B2). A graduate student in nursing with strong English proficiency compared and revised these two versions to produce the final back-translated English version (Version B). (3) Expert review: The back-translated English version was sent to the original author for review. The author confirmed that the translation was consistent with the subdomains of the original English version, considered it appropriate for use, and did not suggest modifications, thereby ensuring equivalence with the original scale.

Cultural adaptation

Following the cross-cultural adaptation guidelines for self-report scales [28], the Chinese version of the Nursing Surveillance Scale underwent cultural adaptation. During the cultural adaptation process, we consulted eight nursing experts from different fields, including critical care nursing (2), emergency nursing (2), surgical nursing (1), nephrology nursing (1), pediatric nursing (1), and neurology nursing (1). All experts had more than 10 years of professional experience and extensive research experience. These experts participated in two rounds of expert consultation to assess the conceptual consistency between the Chinese version of the Nursing Surveillance Scale (Scale A) and the back-translated English version (Scale B), ensuring alignment with the original English version. The assessment used a four-point Likert scale, with scores defined as follows: 1 = ‘completely unrelated to the study content,’ 2 = ‘weakly related to the study content,’ 3 = ‘moderately related to the study content,’ and 4 = ‘highly related to the study content.’ Experts were asked to evaluate the relevance of each item to the research content, based on their expertise and experience. The scale was then revised according to their evaluations and suggestions. Subsequently, 30 clinical nurses were invited to participate in a pre-test to evaluate the comprehension of the Chinese version. They were asked to complete the scale and provide feedback on the clarity, wording, and cultural relevance of each item, and their responses were analyzed to ensure the items were well understood and conceptually consistent.

Data collection procedure

Prior to conducting the survey, we explained the objective and content of this study to the head nurses of each hospital, who then facilitated the distribution of the questionnaires. With their consent, the questionnaires were provided both online and in paper form. The purpose of the survey was explained to the clinical nurses, and their informed consent was obtained. Eligible nurses completed the questionnaire. Questionnaires with missing or invalid data were excluded. A total of 650 questionnaires were collected, of which 629 were valid, resulting in an effective response rate of 96.7%. Two weeks later, 30 nurses were selected to complete the scale again to assess its test–retest reliability.

Data analysis procedures

The statistical analysis of the data was conducted utilizing IBM SPSS Statistics 29.0 and IBM SPSS AMOS 27.0 software. Continuous variables in the demographic characteristics were described using mean ± standard deviation, while the categorical variables were reported as percentages and frequencies. Subsequently, the kurtosis and skewness of the scale items were analyzed. When the sample size exceeded 300, absolute skewness values above 2 or absolute kurtosis values exceeding 7 were considered reference values for non-normal distribution [29].

Item analysis

Item analysis assesses whether each item can effectively distinguish respondents and whether it is consistent with the overall measurement objective [30]. The item analysis of the scale was conducted using critical ratio analysis and item–total correlation coefficients.

Critical ratio analysis: The data from the Chinese version of the Nursing Surveillance Scale were ranked by total score in ascending order. The top 27% were designated as the high-score group, and the bottom 27% as the low-score group. Independent-sample t-tests were used to compare item scores between these two groups [31]. A critical ratio (CR = |t|) ≥ 3.000 with p < 0.050 indicated that the item had discriminative validity [32]. (2) Item–total correlation analysis: Pearson’s correlation coefficients were calculated between each item and the total scale score. A correlation coefficient ≥ 0.40 [33] suggested that the item was suitable for retention.

Reliability analysis

Reliability analysis is conducted to evaluate the consistency and stability of a measurement instrument [34]. This study assessed the reliability of the Chinese version of the Nursing Surveillance Scale using internal consistency analysis, split-half reliability, and test-retest reliability. Cronbach’s α coefficients were calculated for each dimension of the scale, with values > 0.7 [35] considered indicative of acceptable reliability. Test-retest reliability was examined by re-administering the scale to 30 clinical nurses after a two-week interval and analyzing the intraclass correlation coefficients (ICC) to evaluate consistency. For split-half reliability, the items were divided into two groups based on odd and even item numbers, and the correlation between the total scores of the two groups was calculated to assess internal consistency.

Validity analysis

Validity is used to evaluate the extent to which a measurement instrument can accurately reflect the target attributes, characteristics, or concepts [36]. This study invited eight experts to evaluate the importance and relevance of each item in the Chinese version of the Nursing Surveillance Scale. The evaluation employed the item-level content validity index (I-CVI) and the scale-level content validity index (S-CVI). Experts rated each item on a four-point Likert scale, ranging from “completely unrelated” (1 point) to “highly related” (4 points).

The sample of 629 nurses was randomly divided into two subgroups for factor analysis: one for exploratory factor analysis (EFA, n = 314) and the other for confirmatory factor analysis (CFA, n = 315). For the EFA group, the suitability of the data for factor analysis was confirmed by a Kaiser-Meyer-Olkin (KMO) value greater than 0.6 and a significant Bartlett’s test of sphericity (p < 0.05) [37]. Principal component analysis with varimax rotation was applied to extract common factors with eigenvalues greater than 1, while items with factor loadings below 0.5 were excluded [38, 39]. For the CFA group, model fit was examined using AMOS 27.0. Model evaluation included the chi-square/degree of freedom ratio (CMIN/DF), root mean square error of approximation (RMSEA), root mean square residual (RMR), comparative fit index (CFI), goodness-of-fit index (GFI), incremental fit index (IFI), normed fit index (NFI), Tucker-Lewis index (TLI), and adjusted goodness-of-fit index (AGFI).

Convergent validity assesses whether different measurement indicators of the same construct are strongly correlated. An average variance extracted (AVE) greater than 0.500 and a composite reliability (CR) above 0.700 indicate good convergent validity [40]. Discriminant validity evaluates whether different constructs can be clearly distinguished from one another. This is examined by comparing correlation coefficients with the square root of the AVE. When the correlation coefficient is smaller than the square root of the AVE [41], it suggests that the constructs are independent and can be effectively differentiated.

Ethical approval

This study protocol was approved by the Ethics Committee for Scientific Research of the First Affiliated Hospital of Jinzhou Medical University (Approval Number: KYLL202530). All participants were apprised of the study’s goal before completing the questionnaire and consented to participate voluntarily. Each participant provided informed consent. This research adheres to the guidelines established in the Declaration of Helsinki. Furthermore, all participant information is completely confidential, and the obtained data is exclusively utilized for research reasons.

Results

Participant descriptive statistical analysis

A total of 629 participants were included in this study, with 314 assigned to the EFA group and 315 to the CFA group. The detailed information is presented in Table 1.

Table 1.

Distribution of general demographic characteristics (n = 629)

Factors	Group	EFA (n = 314, %)	CFA (n = 315, %)
Age	20~	115(36.6)	105(33.3)
	31~	128(40.8)	125(39.7)
	41~	71(22.6)	85(27.0)
Gender
	Male	34(10.8)	24(7.6)
	Female	280(89.2)	291(92.4)
Educational level
	Associate degree	29(9.2)	30(9.5)
	Undergraduate	266(84.7)	258(81.9)
	Master’s degree and above	19(6.1)	27(8.6)
Marital status
	Married	220(70.1)	228(72.4)
	Single	94(29.9)	87(27.6)
Vocational positon
	Clinical nurse	289(92.0)	284(90.2)
	Head Nurse	25(8.0)	31(9.8)
Positional titles
	Registered Nurse	66(21.0)	60(19.1)
	Senior Nurse	139(44.3)	115(36.5)
	Nurse-in charge	90(28.7)	109(34.6)
	Associate-Chief-Nurse	17(5.4)	24(7.6)
	Chie-Nurse	2(0.6)	7(2.2)
Department
	Internal Medicine	121(38.5)	126(40.0)
	Surgery	85(27.1)	70(22.2)
	Gynecology	13(4.1)	17(5.4)
	Pediatrics	11(3.5)	13(4.1)
	Intensive Care Unit	15(4.8)	16(5.1)
	Emergency Department	8(2.5)	8(2.5)
	Operating Room	14(4.5)	17(5.4)
	Oters	47(15.0)	48(15.3)
Working years
	<1 year	23(7.3)	19(6.1)
	1–5 years	66(21.0)	57(18.1)
	6–10 years	70(22.3)	54(17.1)
	>10 years	155(49.4)	185(58.7)

Note: EFA, exploratory factor analysis; CFA, confirmatory factor analysis

Project analysis

Forthe Chinese version of the Nursing Surveillance Scale, the critical ratio values ranged from 11.198 to 24.700. All items showed statistically significant differences between the high- and low-score groups (p < 0.001). The item–total correlation coefficients ranged from 0.512 to 0.775. The scale demonstrated good internal consistency, with a Cronbach’s alpha of 0.891. When any item was deleted, Cronbach’s alpha varied between 0.877 and 0.891. Since removing items did not increase the internal consistency, all items were retained. The mean, skewness, and kurtosis values for the Chinese version of the Nursing Surveillance Scale are presented in Table 2.

Table 2.

Item analysis, skewness, kurtosis, and mean analysis of the Chinese version of the nursing surveillance scale

Item	Item score(SD)	Critical ratio	Item-total correlation	Cronbach’s Alpha if the item is deleted	Skewness	Kurtosis
1	3.06	21.427	0.666	0.882	0.633	0.155
2	2.67	15.983	0.551	0.891	0.459	0.594
3	3.13	21.250	0.709	0.880	0.754	0.293
4	3.05	21.349	0.712	0.879	0.564	0.029
5	3.08	24.700	0.708	0.880	0.776	0.132
6	3.30	23.173	0.727	0.880	0.947	0.581
7	3.31	11.425	0.523	0.888	0.927	0.669
8	2.97	16.581	0.585	0.887	0.658	0.344
9	3.45	21.678	0.775	0.877	1.345	1.516
10	2.99	15.549	0.562	0.887	0.564	0.270
11	3.03	17.517	0.626	0.884	0.596	0.074
12	3.32	11.198	0.512	0.888	0.750	0.076
13	3.59	13.025	0.583	0.885	1.402	1.197
14	3.44	14.836	0.624	0.884	1.146	1.090
15	3.22	11.412	0.523	0.887	0.821	1.088
16	3.26	11.708	0.516	0.887	0.961	1.389

Reliability analysis

The Chinese version of the Nursing Surveillance Scale showed adequate internal consistency, with a Cronbach’s α of 0.891 for the total scale and values ranging from 0.814 to 0.876 across the four subscales, indicating good reliability. To further assess stability, 30 clinical nurses were randomly selected, and the scale was re-administered two weeks later. The test–retest reliability was 0.908, and the split-half reliability was 0.928. Detailed results are presented in Table 3.

Table 3.

Chinese version of the nursing surveillance scale reliability analysis

The scale and its dimensions	Cronbach’s Alpha	Split-half reliability	Test-retest reliability
Nursing Surveillance Scale	0.891	0.928	0.908
Problem Prediction and Decision-Making	0.876
Systematic Assessment	0.823
Pattern Recognition	0.814
Identifying Patient Self-Care and Coping Strategies	0.856

Validity analysis

Content validity

This study invited eight experts to evaluate each item of the nursing surveillance scale. The results showed that the item-level content validity index (I-CVI) ranged from 0.871 to 1.000, and the scale-level content validity index (S-CVI) was 0.938, indicating that the scale had acceptable content validity.

Exploratory factor analysis (EFA)

This study employed Bartlett’s sphericity test, with a Kaiser-Meyer-Olkin (KMO) value of 0.873, x² = 2605.087, df = 120, p < 0.001. Principal component analysis with varimax rotation was conducted, extracting four common factors with eigenvalues greater than 1. The explained variances were 22.0%, 19.53%, 15.20%, and 11.68%, respectively, accounting for 68.41% of the total variance. Factor 4 contained only two items (Items 15 and 16), and all items had factor loadings above 0.50. The factor loadings of each item are presented in Table 4. Exploratory analysis identified four principal component factors(Factor 1: Problem Prediction and Decision-Making; Factor 2: Systematic Assessment; Factor 3: Pattern Recognition; Factor 4: Identifying Patient Self-Care and Coping Strategies). Figure 1 illustrates the scree plot of the four-factor structure identified by exploratory factor analysis.

Table 4.

Factor loadings from the exploratory factor analysis of the Chinese version of the nursing surveillance scale (n = 314)

Item	Factor1	Factor2	Factor3	Factor4
1. Predict potential problems based on an evaluation of treatment or intervention outcomes.	0.750	-	-	-
2. Participate in decisions regarding patient treatment plans.	0.766	-	-	-
3. Select appropriate patient indicators for ongoing monitoring based on the patient’s condition.	0.673	-	-	-
4. Predict potential problems based on the comprehensive assessment of patient data.	0.731	-	-	-
5. Determine the frequency of data collection and interpretation based on the patient’s status.	0.827	-	-	-
6. Identify issues based on changes in patient condition and communicate effectively with physicians to address them.	0.672	-	-	-
7. Monitor infection status as appropriate.	-	0.718	-	-
8. Monitor excretion status as appropriate.	-	0.737	-	-
9. Routinely monitor the skin of high-risk patients.	-	0.829	-	-
10. Troubleshoot devices and systems to enhance the acquisition of reliable patient data.	-	0.700	-	-
11. Monitor the bleeding tendencies of high-risk patients.	-	0.734	-	-
12. Monitor patients who are unstable or critically stable (e.g., patients requiring frequent neurological assessments, those experiencing arrhythmias, or those receiving continuous intravenous infusions of medications such as nitroglycerin or insulin).	-	-	0.700	-
13. Monitor vital signs as appropriate.	-	-	0.830	-
14. Directly verify the accuracy of handover content during rounds.	-	-	0.829	-
15. Monitor the patient’s ability to perform self-care activities.	-	-	-	0.863
16. Monitor the coping strategies used by the patient and their family.	-	-	-	0.872

Fig. 1.

Scree plot of the four-factor structure from the exploratory factor analysis of the Chinese version of the Nursing Surveillance Scale (n = 314)

Confirmatory factor analysis

Confirmatory factor analysis was performed (Fig. 2), and the model fit indices were as follows: CMIN/DF = 1.559, RMSEA = 0.042, RMR = 0.029, CFI = 0.978, GFI = 0.942, IFI = 0.978, NFI = 0.942, TLI = 0.973, and AGFI = 0.919. All indices met the recommended thresholds, indicating that the model constructed using AMOS 27.0 demonstrated a good fit. The results are summarized in Table 5.

Fig. 2.

Structural model of the confirmatory factor analysis for the Chinese version of the Nursing Surveillance Scale (n = 315). Legend: Factor 1: Problem Prediction and Decision-Making; Factor 2: Systematic Assessment; Factor 3: Pattern Recognition; Factor 4: Identifying Patient Self-Care and Coping Strategies

Table 5.

Model fit indices of the Chinese version of the nursing surveillance scale

Index	Four-factor	Evaluation standard
CMIN/DF	1.559	≤ 3.000
RMSEA	0.042	<0.080
RMR	0.029	<0.050
CFI	0.978	>0.900
GFI	0.942	>0.900
IFI	0.978	>0.900
NFI	0.942	>0.900
TLI	0.973	>0.900
AGFI	0.919	>0.900

Convergent validity

The average variance extracted (AVE) values for the four subscales ranged from 0.500 to 0.730, while the composite reliability (CR) values ranged from 0.823 to 0.897. Since all AVE values exceeded 0.50 and all CR values were greater than 0.70. The results suggest that the Chinese version of the Nursing Surveillance Scale demonstrates good convergent validity. Further details are presented in Table 6.

Table 6.

Convergent validity of the Chinese version of the nursing surveillance scale

Factors	Item	Standardized estimate	p-value	AVE	CR
Factor1	1	0.778	P<0.001	0.594	0.897
	2	0.639	P<0.001
	3	0.769	P<0.001
	4	0.871	P<0.001
	5	0.829	P<0.001
	6	0.719	P<0.001
Factor2	7	0.553	P<0.001	0.500	0.826
	8	0.632	P<0.001
	9	0.963	P<0.001
	10	0.577	P<0.001
	11	0.739	P<0.001
Factor3	12	0.622	P<0.001	0.613	0.823
	13	0.814	P<0.001
	14	0.889	P<0.001
Factor4	15	0.922	P<0.001	0.730	0.843
	16	0.782	P<0.001

AVE: Average variance extracted; CR: Composite reliability

Discriminant validity

The correlations between each subscale and the total scale were examined. The results showed that the square roots of the AVE values for the subscales ranged from 0.707 to 0.854, all of which were higher than the corresponding subscale–total correlations [41]. These findings indicate clear distinctions among the subscales of the Chinese version of the Nursing Surveillance Scale, suggesting that the questionnaire has sound discriminant validity. Refer to Table 7 for specifics.

Table 7.

Discriminant validity of the Chinese version of the nursing surveillance scale

	Factor4	Factor3	Factor2	Factor1
Factor4	0.771
Factor3	0.508***	0.707
Factor2	0.303***	0.491***	0.783
Factor1	0.346***	0.454***	0.595***	0.854
	0.771	0.707	0.783	0.854

*** represents p < 0.001. The diagonal elements are the square roots of the average variance extracted (AVE)

Discussion

This study aimed to translate the Nursing Surveillance Scale into Chinese, adapt it culturally, and evaluate its psychometric properties to determine its applicability among clinical nurses in China, thereby addressing a gap in nursing research within the Chinese context. The original Nursing Surveillance Scale was developed in 2024 by Kim and Cho [23]. The multidimensional features of the scale reflect nurses’ perceptions and experiences in performing surveillance activities, making it important to validate across different cultural contexts. The findings of this study demonstrate that the Chinese version of the Nursing Surveillance Scale exhibits good reliability and validity.

Translation and cross-cultural adaptation

The cross-cultural validation of the Chinese version of the Nursing Surveillance Scale was conducted in strict accordance with established guidelines [27], ensuring equivalence between the original and translated versions. Experts evaluated the items using a structured assessment form, examining semantic, conceptual, and cultural equivalence, along with clarity and relevance [42]. Based on expert feedback, the items were revised until consensus was achieved. Without altering the original meaning, only minor modifications were made to certain items, with no additions or deletions, to ensure consistency with the local linguistic context and to accurately reflect the characteristics of Chinese nursing culture, while preserving the conceptual integrity of the scale [29]. For example, in item 4, “overall judgements” was translated as “comprehensive assessment,” which refers to a systematic and holistic evaluation of patient data [43]. This modification ensured conceptual equivalence and aligned with terminology commonly used in Chinese nursing assessment. In item 7, “monitor for infections” was translated as “monitor infection status.” The addition of “status” emphasizes the dynamic nature of continuous infection monitoring [44], maintaining structural and content similarity to the original scale, while clarifying meaning and improving understanding in line with Chinese nursing practice. In item 8, “elimination patterns” was translated as “excretion status.” The latter is more intuitive and commonly used in routine nursing practice in China [45], accurately conveying the medical meaning and aligning with the clinical context and expression habits of Chinese nurses. These cultural adaptations facilitate integration into the Chinese context and enhance the applicability of the scale among Chinese nurses.

Item analysis

The item analysis showed that all 16 items met the critical ratio standard and were significantly correlated with the total score, indicating good discrimination and internal consistency of the scale [32], Since deleting any item did not improve Cronbach’s α, all items were retained, suggesting that the Chinese version of the Nursing Surveillance Scale preserved the structural integrity of the original tool and is suitable for evaluating the nursing surveillance ability of Chinese nurses.

Reliability analysis

This study examined the internal consistency, split-half reliability, and test–retest reliability of the Chinese version of the Nursing Surveillance Scale. The results showed that the overall scale, its four subdomains, and the split-half reliability all reached satisfactory levels [35]. The two-week test–retest reliability also remained stable, confirming that the tool produces consistent results across different time points [46]. Compared with the original version, minor differences were observed, which may be related to cultural and contextual variations in nurses’ understanding of surveillance behaviors, as well as subtle semantic changes introduced during translation [47]. At the subdomain level, problem prediction and decision-making demonstrated the highest reliability, suggesting that Chinese nurses perform well in risk anticipation and clinical decision-making support [48]. Systematic assessment also performed well, indicating that nurses are competent in monitoring and evaluating patient conditions, although holistic assessment still needs to be strengthened [49]. Pattern recognition was relatively weaker, implying shortcomings in the early identification of abnormalities, which may be associated with nurse–patient ratios, heavy workloads, and limited training in critical thinking [50]. Identifying patient self-care and coping strategies remained stable, reflecting the growing emphasis in Chinese nursing practice on patient-centered care and psychosocial support [51]. Overall, the Chinese version of the Nursing Surveillance Scale demonstrated good reliability at both the overall and subdomain levels, with test–retest results further confirming its temporal stability and reproducibility. In addition, the subdomain analysis highlighted both strengths and weaknesses in Chinese nurses’ surveillance practice, providing directions for future improvements.

Validity analysis

The content validity analysis of this study showed that all indices were within the acceptable reference range [52], indicating that the scale maintained strong relevance and accuracy in its content and was able to better reflect the constructs being measured. The structural validity analysis revealed that EFA extracted four factors from the translated scale, with the composition and allocation of items consistent with the original version, suggesting that the core conceptual dimensions of the scale were effectively preserved. The cumulative variance explained by the translated version was 68.41%, which exceeded the standard threshold [25] but was lower than the 70.1% reported in the original study. This difference suggests that the concept of “nursing surveillance” may be interpreted differently in the clinical practice and cultural context of Chinese nurses. For example, Chinese nurses may interpret the “problem prediction and decision-making” dimension differently from those in the original cultural setting, leading to slightly lower explanatory power, whereas the “identifying patient self-care and coping strategies” dimension was relatively higher, suggesting that this construct was expressed more clearly in the Chinese context. Despite these minor differences, all factor loadings were greater than the minimum standard of 0.50 [38], and no items were deleted. Factor 4 contained only two items, both of which had loadings greater than 0.50 and showed acceptable internal consistency, supporting their applicability in the Chinese version. To maintain consistency with the original structure and preserve the conceptual integrity of the construct, they were retained. The CFA results of the translated scale showed that the model fit indices (CMIN/DF, CFI, GFI, IFI, NFI, TLI, AGFI, RMR, and RMSEA) all met the standards for structural validity [53, 54], indicating that the theoretical structure proposed in the original scale is also applicable in the Chinese nursing context. Convergent validity was examined using standardized factor loadings, average variance extracted (AVE), and composite reliability (CR), and all indices reached the recommended thresholds [40]. Some dimensions had AVE values higher than those of the original scale, suggesting that adjustments made during translation and cultural adaptation improved the conceptual clarity and internal consistency of the dimensions, making them more aligned with Chinese nursing culture and language practices. Other dimensions had AVE values similar to the original, indicating that the theoretical framework was preserved and that the scale can measure the same constructs across cultures. The discriminant validity results showed that the square root of the AVE for each factor was greater than the correlations among the factors [41], indicating that the four subdomains remained clearly separated and effectively reflected different aspects of nursing surveillance. Compared with the results of the original version, the Chinese version maintained a consistent pattern of discrimination among dimensions, demonstrating that the translated scale successfully preserved the conceptual boundaries of each domain. Taken together, these analyses indicate that the Chinese version of the Nursing Surveillance Scale demonstrates good measurement validity.

Limitations

This study has several limitations that should be acknowledged. First, the use of convenience sampling may limit the representativeness of the findings. The participants were recruited from only three provinces in China, and the sample size was relatively small, making it difficult to capture the diversity of the national healthcare context. Therefore, the results may not fully reflect the broader nursing population. Future studies should expand the sample size and include participants from hospitals of different levels to enhance generalizability. Second, although this study provided a comprehensive evaluation of the Chinese version of the Nursing Surveillance Scale, it did not adequately explore the factors that may influence nursing surveillance. Further research is needed to examine these factors from multiple perspectives in order to reduce insufficient surveillance and strengthen strategies for ensuring patient safety. Third, all data were collected through self-report, which may be subject to bias. To address this limitation, future studies could incorporate objective measures or be conducted in multicultural settings. Finally, while the reliability and validity of the instrument were assessed, criterion validity was not examined. Future research should investigate the consistency and differences between this scale and other established tools to further support its external validity.

Conclusion

In conclusion, the Chinese version of the Nursing Surveillance Scale, developed through Brislin’s back-translation model and rigorous cross-cultural adaptation, has demonstrated satisfactory reliability and validity. It appears to be a psychometrically sound instrument for evaluating nurses’ surveillance competencies in the Chinese context. Furthermore, it may provide a useful basis for designing interventions and surveillance strategies aimed at supporting patient risk management and enhancing patient safety.

Abbreviations

CMIN/DF

chi-square/degree of freedom

GFI

Goodness-of-fit Index

NFI

Normed Fit Index

IFI

Incremental Fit Index

TLI

Tucker Lewis Index

CFI

Comparative Fit Index

AGFI

Adjusted goodness-of-fit index

RMSEA

Root-mean-square error of approximation

RMR

Root Mean Square Residual

AVE

Average variance extracted

CR

Composite Reliability

EWS

Early warning systems

EFA

Exploratory factor analysis

CFA

Confirmatory factor analysis

KMO

Kaiser-Meyer-Olkin

Author contributions

D. X. Data collection and article writing. S.b.L. Data collection and statistical analysis. W.H. Data collection. X. L. Quality control and project management.

Funding

This study received no funding from any source.

Data availability

The data and materials used in this study are available from the corresponding author upon reasonable request.

Declarations

Ethical approval and Participant Consent

This study was approved by the Ethics Committee of the First Affiliated Hospital of Jinzhou Medical University (Approval Number: KYLL202530) and conducted in accordance with the ethical principles of the Declaration of Helsinki. Data were collected through online questionnaires and paper-based surveys. All participants received an informed consent form prior to the study, and participation in the survey was voluntary, with no incentives provided. Participants could withdraw at any time. All data were anonymously and securely stored, and only authorized researchers could access them. Authorized individuals were permitted to share anonymized data for academic research purposes, and participants were assured of the confidentiality of their data.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.