Quantifying the professional ethical challenges that nurses encounter is crucial for both theoretical insights and practical outcomes. The objective of this research is to assess the psychometric properties of the Chinese adaptation of the Moral Distress Scale for Healthcare Professionals (MD-APPS).
Methods
In 2024, a survey approach was utilized to engage with several tertiary-level healthcare institutions throughout China. A cohort of 448 nursing professionals who satisfied the specified selection benchmarks was consequently incorporated into the study. To evaluate the scale's reliability and validity, methods including the Content Validity Index (CVI), Factor Analysis—both Exploratory (EFA) and Confirmatory (CFA)—alongside assessments of internal consistency and test-retest reliability were employed.
Results
Expert evaluations yielded an I-CVI of 0.90, suggesting good content validity for the MD-APPS's Chinese adaptation. Exploratory Factor Analysis (EFA) revealed a bi-dimensional framework with 7 components, explaining 56.34% of the cumulative variance. Confirmatory Factor Analysis (CFA) outcomes displayed a χ-square/df ratio of 1.542. The estimate for Robust RMSEA was 0.054, and the SRMR was ascertained to be 0.041. Indices for both Robust TLI and Robust CFI surpassed the 0.9 threshold, indicating an acceptable fit; this aspect was supported by a P-value (Chi-square) of 0.094. The internal consistency, measured by Cronbach's α, was found to be 0.74, while the test-retest reliability over a two-week period reached 0.964. These findings provide initial evidence for the psychometric properties of the Chinese MD-APPS.
Conclusion
The Chinese adaptation of the MD-APPS demonstrates promising initial psychometric properties, suggesting its potential suitability for exploring nurses' professional ethical challenges within the Chinese cultural context. This scale may facilitate the identification of diverse elements influencing nurses' professional ethics and the assessment of the ethical climate in nursing practices. However, further validation studies are needed to fully establish its psychometric robustness across various healthcare settings in China.
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Introduction
The healthcare sector has always been fraught with ethical challenges; however, nurses, as frontline providers of patient care, face particularly complex and frequent ethical issues [1]. This study focuses on the ethical dilemmas and moral distress experienced by nurses, with a particular emphasis on nurses in China. We aim to assess and understand these experiences within the context of China's unique healthcare environment, using a newly developed scale that takes into account cultural and institutional differences. A key question driving this research is: What are the primary sources of ethical dilemmas and moral distress among clinical nurses in China? By addressing this question, we seek to identify and understand the specific challenges faced by Chinese nurses in their daily practice. This understanding is crucial as it can inform targeted interventions and support strategies. Furthermore, by examining these experiences in depth, we aim to contribute to the broader understanding of nursing ethics and provide insights that can inform strategies to support nurses in navigating ethical challenges globally. Our focus on the Chinese healthcare context offers a unique perspective that can enrich the international discourse on nursing ethics and moral distress [2].
Through this study, we hope to shed light on the complex ethical landscape navigated by Chinese nurses and provide a foundation for developing culturally sensitive approaches to mitigate moral distress and support ethical decision-making in nursing practice.
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Background
It is important to distinguish between ethical dilemmas and moral distress. Ethical dilemmas occur when nurses encounter situations with conflicting moral demands, requiring a choice between two or more ethically justifiable but mutually exclusive actions [3]. Moral distress, on the other hand, is the emotional response when nurses know the right action but are constrained from taking it. Such situations typically arise when nurses are aware of the correct course of action but are unable to carry it out due to institutional or environmental constraints [4, 5].
Prolonged moral distress can lead to negative emotions, professional burnout, and even prompt some exceptional nurses to resign [6, 7]. Research indicates that under extreme work demands, such as during the 2019 COVID-19 pandemic, the consequences of this distress are even more severe [8]. Therefore, assessing and addressing the ethical dilemmas faced by nurses is of fundamental importance for maintaining healthcare quality, promoting nurses' mental health, and fostering professional retention [9].
Nurses face a wide and profound range of ethical conflicts, stemming from both external and internal factors. External factors include high-pressure environments such as mental health, surgery, emergency departments, and Intensive Care Units (ICUs) [10‐12]. Internal factors contributing to ethical challenges may include personal values conflicts, lack of ethical knowledge or decision-making skills, fear of repercussions for speaking up, and emotional exhaustion from repeated exposure to morally distressing situations [13]. Additionally, individual differences in moral sensitivity and coping strategies can influence how nurses perceive and respond to ethical dilemmas [14].
Psychiatric nurses are required to deal with sensitive situations related to patient behavior management, such as the use of restraints and, when necessary, compulsory medication, which can conflict with their personal ethical beliefs, triggering professional moral conflicts [15]. This situation is particularly evident among the nursing community in China due to several unique factors. Firstly, China's healthcare system has undergone rapid and extensive reforms in recent years, creating a dynamic and sometimes challenging work environment for nurses [16]. Secondly, traditional Chinese cultural values, which emphasize harmony and respect for authority, may sometimes conflict with modern nursing ethics, creating additional moral tension [17]. Thirdly, the high patient-to-nurse ratio in many Chinese hospitals increases workload and time pressure, potentially exacerbating ethical dilemmas [18]. Lastly, the hierarchical structure in Chinese healthcare institutions may sometimes limit nurses' autonomy in ethical decision-making [19]. These factors collectively contribute to the heightened prevalence and intensity of ethical dilemmas faced by Chinese nurses, making it especially important to conduct precise assessments and gain a deep understanding of their experiences.
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While several scales have been developed and widely used internationally, they may not apply to Chinese nurses due to differences in cultural and institutional backgrounds. In 2021, Belgian scholar Céline A. Baele and colleagues [20] developed the Nurse Professional Ethical Dilemma Scale (MD-APPS), a new, brief, and context-independent tool for assessing moral distress. MD-APPS employed an evaluative theory-based assessment approach, rather than solely relying on descriptions of specific situations. It focused on individuals' subjective evaluation of moral distress scenarios, emphasizing the central role of psychological processes in an individual's experience. The scale's content validity index was established through expert opinions, its structural validity through exploratory and confirmatory factor analyses, and its reliability was ensured by Cronbach's α coefficient and test-retest reliability coefficients.
Purpose
The purpose of this study is to assess and gain a deep understanding of the ethical dilemmas faced by nurses in China, with a particular focus on psychiatric nurses. By using the MD-APPS scale, we aim to provide a more accurate understanding of the level of ethical challenge cognition faced by Chinese nurses in their professional practice. This research not only facilitates a deeper understanding of the concept of moral distress but also supports healthcare and educational institutions in making improvements in training and environmental design through quantitative measures. By doing so, it aims to enhance the quality of nursing care, reduce professional burnout, boost the professional morale of nursing teams, and ultimately achieve better patient care. These measures allow for a more comprehensive examination of the ethical challenges in nursing practice within the Chinese context, while also contributing to the international discourse on nursing ethics.
Data and methods
Scale introduction
The MD-APPS is a self-administered scale designed to assess the psychological characteristics of nurses' professional ethical dilemmas. It comprises two dimensions with a total of eight items and utilizes a six-point Likert scale, ranging from 1 (strongly disagree) to 6 (strongly agree). This six-point scale allows for a more nuanced assessment of participants' responses, capturing subtle differences in their perceptions of ethical dilemmas. For each item, respondents are asked to indicate their level of agreement or disagreement, providing a comprehensive evaluation of their experiences with professional ethical challenges.
For each item, the factor loading values of the scale are as follows: the first item has a factor loading of 0.79, indicating high item commonality; the second item is 0.76; the third item is 0.67; the fourth item is 0.63; the factor loading of the fifth item is somewhat lower, at 0.48, which may indicate a weaker association with the constructed dimensions; the sixth item is 0.58; the seventh item is 0.68; and the final item is 0.74. The items are divided into two dimensions: 'Obstacles' and 'Coercion/Compulsion', and 'Autonomy/Agency' and 'Support', with the latter dimension's items being scored in reverse. The scale's overall score is the sum of the individual item scores, with a higher total score indicating a more severe level of ethical dilemmas encountered by nurses. The scale demonstrates good internal consistency, with a Cronbach's α coefficient of 0.87, indicating it provides a reliable assessment of the relevant psychological traits.
The translation of the scale
To ensure the linguistic validity and accuracy of the MD-APPS, a detailed translation-back translation process was undertaken. During the translation phase, two bilingual experts — one with a Master's degree in Nursing and the other holding a Master's in English — independently translated the original scale into Chinese, resulting in versions T1 and T2. Subsequently, a Master's graduate in Neurosurgical Nursing and a postgraduate student in Intensive Care Nursing jointly reviewed and synthesized these two versions, ultimately consolidating them into a unified Chinese version of the scale, referred to as version T.
In the back-translation step, two bilingual translators who had not been exposed to the original scale — one holding a Master's degree in Nursing and the other a Master's degree in English — independently translated the Chinese version of the scale, version T, back into English, resulting in versions BT1 and BT2. Subsequently, a Nursing Psychology Master's student with a strong foundation in English compared and organized these two versions, arriving at the final English version of the scale, version B.
Finally, through the collective efforts of the entire translation team, by comparing the original scale, the forward translation versions, and the back-translation versions, we ensured the accuracy of the translation and cultural adaptation of the Chinese version of the MD-APPS, thus completing the development of the initial Chinese version of the MD-APPS.
Cultural adaptation
In the process of applying the MD-APPS scale to the Chinese nursing context, we conducted a series of cultural adaptations to ensure that the scale accurately reflects the characteristics of Chinese nursing culture while maintaining the integrity of the original concepts. These adaptations primarily included the following aspects:
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Linguistic expression adjustments
Each scale item underwent meticulous linguistic adjustments to ensure accurate reflection of Chinese nursing cultural characteristics. For example:
Item 4: "I received help to work in a way that I believe is morally correct".
In this item, we emphasized the concept of "receiving help," reflecting the collectivism and mutual support spirit in Chinese culture. The nursing environment in China typically emphasizes teamwork and mutual support, making this expression more relatable to Chinese nurses.
Maintaining conceptual equivalence
We paid special attention to ensuring that the concept of "moral distress" remained consistent within the Chinese nursing context. Considering China's collectivist culture, we placed more emphasis on team and organizational influences in our wording. For instance:
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Item 6: "I am forced to do things that I believe are morally wrong".
In this item, we used the term "forced," reflecting potential organizational pressures or team expectations in the Chinese nursing environment. This phrasing better captures the moral dilemmas Chinese nurses might face, such as conflicts between personal moral judgments and organizational requirements.
Contextual adaptation
Considering the characteristics of the Chinese healthcare system, we ensured that the scale items were applicable to Chinese nursing practices. During the translation process, we maintained the original concepts while using expressions that Chinese nurses could more easily understand and accept. For example:
Item 7: "I receive support to engage in ethical nursing behaviors".
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Here, we emphasized "receiving support," reflecting the importance of team support and leadership guidance in Chinese nursing culture. This expression better aligns with Chinese nurses' work experiences and expectations.
Through these cultural adaptations, we strived to ensure that the MD-APPS scale accurately reflects moral distress situations in the Chinese nursing environment while maintaining conceptual consistency with the original scale. These adjustments not only considered linguistic equivalence but also fully accounted for the characteristics of Chinese nursing culture, including collectivism, hierarchical structure, and team collaboration, to ensure the scale's applicability and effectiveness in the Chinese nursing context.
Expert opinions
To enhance the clarity and comprehensibility of the MD-APPS scale, we solicited opinions from eight experienced nursing experts from different fields, including psychiatric nursing (1), surgical nursing (2), pediatric nursing (1), emergency nursing (1), intensive care (2), and internal medicine nursing (1). These experts reviewed the original version of the MD-APPS and its drafts, evaluating the relevance of the initial Chinese version of the MD-APPS scale. This evaluation utilized a Likert four-point rating scale, with scores ranging from "not relevant" (1) to "highly relevant" (4), providing a quantitative assessment of the links and appropriateness of each item on the scale. After integrating the valuable opinions of these experts from various nursing fields, necessary cultural adjustments were made to the MD-APPS scale to ensure its content is suitable and accurate within the local medical cultural context. This process strengthened the scale’s effectiveness and practicality as a tool for assessing ethical dilemmas in the nursing profession.
Pilot survey
Through convenience sampling, we selected 42 clinical nurses from a tier-three top-grade hospital in Jiangxi Province in March 2024 as research subjects to fill out the initial Chinese version of the MD-APPS scale. After completion, the research team conducted interviews with the participants, thoroughly inquiring about the clarity and comprehensibility of each item on the initial Chinese version of the MD-APPS scale, while also recording their feedback and suggestions.
Based on the feedback and suggestions received, the research team proceeded to make detailed cultural adjustments and revisions to the initial Chinese version of the MD-APPS scale, to ensure that the items on the scale could be accurately understood and adapted to the local medical and nursing cultural context. The result of this process was the creation of a refined, formal Chinese version of the MD-APPS, providing a solid foundation for further research and practice.
Survey population
In this study, we employed convenience sampling to conduct a questionnaire survey among clinical nurses from several top-tier (tier-three, class A) hospitals in China in March 2024. To ensure the reliability of the sinicization of the scale, when determining the sample size, we followed the convention in measurement studies by multiplying the number of items on the scale by 5 to 10 times, while also taking into consideration the possibility of approximately 20% potential invalid questionnaires. Therefore, we estimated that the effective sample size would be between 40 to 80. Considering the statistical requirements for conducting factor analysis [21], we set a target sample size of 500 [22]. Based on this standard, the research team distributed 500 questionnaires and received 448 valid questionnaires, resulting in an effective response rate of 89.6%. To ensure that the two groups designated for random allocation had appropriate sample sizes and that each group had at least 200 participants, we used the random sampling function 'sample' in R language. A random seed was set to ensure the reproducibility of the results, meaning that using the same seed value and sampling code would yield the same random number results, ensuring the reproducibility of the findings. The study included a total of 448 participants, with 223 involved in the Exploratory Factor Analysis (EFA) and 225 in the Confirmatory Factor Analysis (CFA). Data analysis revealed that the median score for the MD-APPS among participants was 33, with scores ranging from 18 to 48.
Statistical methods
Study design and participants
This cross-sectional study encompassed two substudies with distinct cohorts, derived from a total sample of 448 participants. Utilizing R (version 4.3.2), participants were randomized into two groups: 223 for Exploratory Factor Analysis (EFA) and 225 for Confirmatory Factor Analysis (CFA), ensuring sample independence.
Non-response bias assessment
To evaluate potential non-response bias, we conducted an early-late respondent analysis. The initial quartile of respondents (n = 112) was classified as early respondents, while the final quartile (n = 112) was designated as late respondents.
Statistical analysis
Demographic and clinical characteristics were compared between early and late respondents. Categorical variables (gender and satisfaction) were analyzed using chi-square tests. For continuous variables, Mann-Whitney U tests were employed for non-normally distributed data (age and years of professional experience), while independent samples t-tests were used for normally distributed data (total scores). All tests were two-tailed with a significance threshold of p < 0.0500.
Common method bias evaluation
To assess potential common method bias, Harman's single-factor test was performed. This involved conducting an exploratory factor analysis on all eight items (Item1-Item8), examining the unrotated factor solution to determine the proportion of variance accounted for by a single factor.
All statistical analyses were performed using R (version 4.3.2).
Results
The sample consisted of 448 registered nurses, with the majority (73.4%) being female. The age distribution showed that 50.4% were between 20-30 years old, 38.4% were 31-40 years old, with the remaining 11.2% aged 41 years or above. Regarding education, 67.9% held an undergraduate degree, 28.8% had a community college diploma, and 3.3% possessed a master's degree. In terms of work experience, 40.0% had 6-10 years of nursing experience, 28.8% had 1-5 years, 25.9% had over 10 years, and 5.3% had less than 1 year of experience. The median score for participants' MD-APPS is 33 points, with a minimum score of 18 points and a maximum score of 48 points. Detailed descriptive information is provided in Table 1.
Table 1
Demographic and clinical characteristics of the study population (N = 448)
Characteristic
N
Percentage (%)
Gender
Male
56
12.5
Female
329
87.5
Age
20-30 years
226
50.4
31-40 years
172
38.4
41-50 years
31
6.9
Aged 50 and above
19
4.2
Educational level
Community college
129
28.8
Undergraduate
304
67.9
Master
15
3.3
Marital status
Married
288
64.3
Single
160
35.7
Vocational position
Clinic nurse
405
90.4
Head nurse
43
9.6
Children
With a child
244
54.5
Childless
204
45.5
Years of Work Experience
1-5 years
129
28.8
6-10 years
179
40.0
Over 10 years
116
25.9
Less than 1 year
24
5.4
Department
Emergency Department
57
12.7
Internal Medicine
147
32.8
Surgery
137
30.6
Intensive Care Unit (ICU)
94
21.0
Administrative Department
13
2.9
Work Schedule
Day
129
28.8
Day + Night
314
70.1
Night
5
1.1
Commute Time
Within 30 min
344
76.8
Within 1 h
63
14.1
More than 1 h
50
9
Health Issues
Yes
59
13.2
No
389
86.8
Job Satisfaction
Satisfied
347
77.5
Dissatisfied
101
22.5
Construct validity
Exploratory factor analysis
In this study, to assess the structural validity of the scale, Exploratory Factor Analysis (EFA) was utilized. Before conducting the EFA, a normality test for the questionnaire items was performed using the Shapiro-Wilk test, which is widely recognized for its power in detecting departures from normality. We utilized R's built-in function for the Shapiro-Wilk test to assess normality. Additionally, we examined the skewness and kurtosis values for each item using the 'psych' package in R.
The results indicated that the scores for all items did not conform to a normal distribution (P < 0.0500 for all items in the Shapiro-Wilk test). This non-normality is likely due to the characteristic distribution of data often seen in social science research, particularly with Likert-scale items. We conducted skewness and kurtosis analyses on all eight items to assess the normality of data distribution. For large samples (n > 300), an absolute skewness value greater than 2 or an absolute kurtosis value greater than 7 indicates significant non-normality [23]. Our analysis showed that the skewness and kurtosis values for all items did not exceed these thresholds. Specific skewness and kurtosis values can be found in Supplementary Table 1, Although the skewness and kurtosis values of all items did not exceed the threshold for significant non-normality, the data still exhibited slight characteristics of non-normal distribution. All items displayed negative skewness, indicating that the data distribution is slightly tilted to the right. This mild non-normality should be taken into account when interpreting subsequent analyses and results.
Given this observation, a polychoric correlation matrix was chosen for conducting EFA corrections, a method suitable for analyzing the relationships between non-normally distributed variables with inherent ordinal levels. To determine whether the sample was suitable for factor analysis, the Bartlett's Test of Sphericity and Kaiser–Meyer-Olkin (KMO) test were conducted. The KMO test result showed a KMO coefficient of 0.7600 for this study, indicating that the sample has moderate to high commonality, meaning that there is a significant shared variance among variables, making them suitable for factor analysis. The Bartlett's Test of Sphericity produced a highly significant statistical result (χ2 (28) = 1080.56, p < 0.0500), suggesting that the variable correlations in the data are non-random and statistically significant.
Typically, the closer the KMO (Kaiser-Meyer-Olkin) coefficient is to 1, the more suitable the sample is for factor analysis. For the Bartlett test, an ideal outcome would be a p-value less than 0.0500, which was achieved in this study. Based on these criteria, we can conclude that the data from this Chinese version of the scale is highly suitable for factor analysis.
In the factor analysis step, the two-factor model identified for the Chinese version of the scale accounted for a total variance of 56.34% (see Fig. 1), indicating appropriate structural validity. Moreover, the factor loadings of individual items ranged from 0.63 to 0.845 (see Table 2), suggesting that, with a few exceptions, all items were highly related to their corresponding factors. However, in our analysis, item 1 had a relatively low factor loading of 0.21, which may be due to cultural differences [24]. Based on this result, we decided to remove item 1 from the scale to improve the overall quality of the instrument.
Fig. 1
Screen plot of exploratory factor analysis for the Chinese version of MD-APPS
Table 2
Factor analysis and total correlation of MD-APPS Chinese version (N = 448)
Item
N = 223
Factor loading
h2
U2
Corrected items-total correlation
Cronbach's alpha
McDonald’s
Omega
% Of the variance explained
PA2
0.78
0.71
57.30
Item3
0.68
0.447
0.52
0.409
Item6
0.81
0.672
0.33
0.42
Item8
0.74
0.605
0.40
0.470
PA1
0.82
0.74
55.62
Item2
0.63
0.448
0.55
0.496
Item4
0.87
0.735
0.27
0.465
Item5
0.85
0.735
0.30
0.494
Item7
0.71
0.561
0.44
0.493
Total
0.74
0.73
56.34
PA1 as Dimension 1, PA2 as Dimension 2, h2 (Squared Multiple Correlation for Endogenous Variables) represents the proportion of explainable variance, and u2(Unique Variance) indicates unique variance or residual variance
×
Non-response bias analysis or early-late respondent analysis
The analysis of potential non-response bias revealed several significant findings. With regard to gender distribution, no significant difference was observed between early and late respondents (χ2 = 0.4536, p = 0.5006). Similarly, the distribution of satisfaction levels showed no statistically significant variation between the two groups (χ2 = 1.7233, p = 0.1893).
However, significant differences were noted in other key variables. The age distribution exhibited a marked difference between early and late respondents (W = 4850.5, p = 0.0011). Additionally, the distribution of years of professional experience differed significantly between the two groups (W = 5251.5, p = 0.0270).
The most pronounced disparity was observed in the total scores. Early and late respondents demonstrated a highly significant difference in this measure (t = -4.9396, p < 0.0010). Early respondents had a mean total score of 32.4 (SD = 5.08), whereas late respondents showed a higher mean score of 36.3 (SD = 6.52).
These findings suggest that while gender and satisfaction levels remained consistent across response timing, other crucial factors such as age, professional experience, and overall scores varied significantly between early and late respondents.
Common method bias analysis
To address potential common method bias, Harman's single-factor test was conducted. The analysis revealed that one factor accounted for 27.94% of the variance, which is well below the 50% threshold. This result suggests that common method bias is not a major concern in our data, lending additional credibility to the survey methodology employed in this study.
Confirmatory factor analysis
A Confirmatory Factor Analysis (CFA) was conducted on an independent sample of 225 participants utilizing the maximum likelihood robust (MLR) estimation method within the lavaan package. The MLR method not only corrects for bias in non-normal data but is also suitable for smaller sample sizes, allowing for more accurate model estimation and inference. This is attributed to the MLR estimation method's adjustment for standard errors and fit statistics to accommodate the non-normality and kurtosis of the data distribution. The selection of this method ensured the robustness and reliability of our model evaluation results. The analysis demonstrated that factor loadings ranged from 0.5900 to 0.8400 [25], with all factor loadings exceeding the critical value of 0.7, except for the second factor (Fig. 2). The revised Chinese version of the MD-APPS model presented a good model fit, as evidenced by: a Chi-square (χ2) value of 20.05, degrees of freedom (df) of 13, a Robust Root Mean Square Error of Approximation (Robust RMSEA) of 0.050, and a Standardized Root Mean Square Residual (SRMR) of 0.0410 [26].
Fig. 2
Factor analysis path diagram the Chinese version of MD-APPS
×
A chi-square to degrees of freedom ratio (χ2/df) below 2 is generally considered indicative of good model compatibility. In this analysis, the Mandarin version of MD-APPS demonstrated a χ2/df of 1.5420, suggesting a potentially good fit. Additionally, values for the adjusted Tucker-Lewis Index (Robust TLI), reaching 0.9740, and for the adjusted Comparative Fit Index (Robust CFI), achieving 0.9840, both surpass traditional acceptance benchmarks, indicating a promising fit of the model. The significance level associated with the adjusted chi-square statistic was recorded at 0.0940, suggesting that the differences between the hypothesized model and the observed data were not statistically significant at the conventional p < 0.0500 level. While these results are encouraging, it's important to note that model fit indices should be interpreted cautiously and in conjunction with other validity evidence. Further validation studies with diverse samples would be beneficial to fully establish the robustness of these preliminary findings.
Reliability analysis
The reliability of the Chinese version of the MD-APPS was assessed using both Cronbach's alpha and McDonald's omega coefficients, providing a comprehensive evaluation of the scale's internal consistency. The standardized Cronbach's alpha coefficient for the overall Chinese version of the MD-APPS was 0.74, suggesting acceptable internal consistency. Specifically, the standardized α coefficients for the first and second dimensions of the scale were 0.82 and 0.78, respectively, indicating good reliability for these subscales. We also calculated McDonald's omega coefficients. The overall McDonald's omega for the Chinese MD-APPS was 0.73, closely aligning with the Cronbach's alpha result. For the individual dimensions, the omega coefficients were 0.74 for the first dimension and 0.71 for the second dimension. These results provide additional support for the scale's reliability, as omega is considered to be a more robust estimate of reliability, especially when the assumptions of tau-equivalence may not be fully met. The total correlation coefficient among all items ranged from 0.409 to 0.496, revealing moderate correlations among the items. These statistical performances suggest that the Chinese version of the MD-APPS demonstrates promising reliability, potentially suitable for related research and practice fields, though further validation would be beneficial. The consistency between Cronbach's alpha and McDonald's omega results provides preliminary evidence for the stability and internal consistency of the scale as a measurement tool. This dual approach to reliability assessment offers encouraging support for the psychometric quality of the Chinese MD-APPS. However, it's important to note that while these initial results are positive, additional studies with diverse samples would be valuable to further establish the scale's reliability and validity in various Chinese nursing contexts.
Content validity
In the process of culturally adapting the tool, based on assessments from eight specialists, the individual item validity scores (I-CVI) for the Mandarin adaptation of MD-APPS ranged between 0.8 and 1.0. Simultaneously, the overall measure of content agreement (S-CVI/UA) achieved a score of 0.9. These results suggest that, following detailed assessments by experienced experts, each aspect of the instrument was positively evaluated, and collectively, the instrument demonstrated good content validity.
Test–retest reliability
To evaluate the scale's stability, thirty nursing professionals were chosen for a follow-up assessment after a two-week interval. This specific timeframe was selected based on recommendations in psychometric literature [27] suggesting that a period of 2-4 weeks is optimal for test-retest reliability in psychological measures. This interval is considered long enough to minimize memory effects while being short enough to avoid significant changes in the construct being measured. To address potential memory effects, participants were asked about their recall of previous responses at the time of the retest. The majority reported little to no recollection of their exact answers, suggesting minimal impact of memory on the retest results. Additionally, the order of items was randomized in the retest to further mitigate any potential memory effects.
Observing that the dataset diverged from normal distribution assumptions, Spearman's rank-order correlation was applied to accommodate the dataset's non-parametric characteristics. This statistical approach is designed to determine the magnitude and orientation of monotonic relationships among paired data, especially apt for datasets deviating from a Gaussian distribution.
The findings revealed that the Spearman coefficients for individual item consistency over the two sessions varied between 0.9000 and 0.9920 (P < 0.0500), indicating exceptionally high reliability across various items. By calculating the average of these individual coefficients, the aggregate mean consistency coefficient was discerned to be 0.9640. Such a notable mean coefficient underscores the instrument's temporal stability, affirming its capability to yield dependable and steady outcomes even when applied to datasets that are not normally distributed.
Discussion
The validation of the Chinese version of the MD-APPS scale provides crucial insights into the unique cultural and ethical landscape faced by nurses in China. Chinese culture, characterized by collectivism, respect for authority, and emphasis on harmony, significantly influences how nurses perceive and respond to moral distress. This cultural backdrop is essential for understanding the results of our study and their implications for nursing practice in China [28].
The COVID-19 pandemic has further intensified the ethical challenges faced by Chinese nurses. The pandemic has exposed nurses to unprecedented moral dilemmas, such as balancing patient care with personal safety, allocating limited resources, and navigating rapidly changing healthcare policies. These experiences have likely shaped their responses to the MD-APPS scale items, particularly in relation to autonomy and agency.
Our findings, especially the need to remove Item 1 ("I am unable to execute my job duties in the manner I deem morally correct"), highlight the complex interplay between professional ethics and cultural norms in China. This item's low factor loading (0.21) suggests that the concept of individual moral correctness in job duties might be perceived differently in Chinese nursing culture. This could be attributed to the unique professional environment, cultural values, educational system, institutional policies, and differences in linguistic and cultural expression specific to China [29]. Chinese nurses may have distinctive experiences and expectations concerning the management system, workflow, team dynamics, values of collectivism and humility, respect for authority, and reliance on support networks, all of which can profoundly influence their understanding of and responses to scale items [30, 31].
The psychometric evaluation of the Chinese MD-APPS demonstrated good structural validity and reliability, with some culturally specific nuances. The two-factor model, explaining 56.34% of the total variance, reflects the dual nature of moral distress as experienced by Chinese nurses: external constraints (Obstacles and Coercion/Compulsion) and internal capacities (Autonomy/Agency and Support).
The structural validity of the scale was supported by both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). The Kaiser-Meyer-Olkin (KMO) value of 0.76 and the significant Bartlett's test of sphericity indicated the suitability of the data for factor analysis [32]. The CFA demonstrated good model fit, with indices such as CFI and TLI exceeding 0.95, which are generally considered to indicate excellent model fit [33].
The high internal consistency (Cronbach's alpha 0.74) and excellent test-retest reliability (0.964) indicate that the scale reliably captures a stable construct of moral distress within the Chinese nursing context [34]. This stability is particularly noteworthy given the dynamic and often stressful nature of nursing work in China, especially in the wake of the COVID-19 pandemic.
The content validity assessment, with I-CVI ranging from 0.8 to 1.0 and S-CVI/UA of 0.9, confirms that the scale items resonate with the Chinese nursing experience and effectively capture the nuances of moral distress in this cultural context [35]. This high content validity is crucial for ensuring that the scale accurately reflects the ethical challenges faced by Chinese nurses, which may differ from those in Western contexts due to cultural, institutional, and systemic factors.
Comparing our findings with the Turkish validation study of MD-APPS reveals both similarities and differences that illuminate the role of culture in shaping moral distress experiences. Both studies found a two-factor structure with good model fit, suggesting some universality in the core components of moral distress. However, the need to remove Item 1 in our study, which was not necessary in the Turkish context, underscores the importance of cultural adaptation in scale validation.
These differences may reflect varying cultural attitudes towards individual moral agency in professional settings. In China, where collective harmony and respect for authority are highly valued, nurses might experience moral distress differently compared to cultures that place greater emphasis on individual decision-making [36].
In the assessment of the test-retest reliability for the scale, the use of Spearman's rank correlation analysis addressed the issue of data not adhering to a normal distribution, allowing us to measure the consistency of scores through non-parametric means. The high correlation coefficients (0.900 to 0.992) indicate that scores maintained high stability over a 2-week interval, confirming that the scale can provide consistent and credible results when measuring nurses' moral feelings and action intentions at different time points. The mean test-retest reliability obtained through this method was 0.9640, further attesting to the stability of scale scores and ensuring the reliability of repeated measurements, especially in challenging non-normal data environments.
Our findings show notable similarities with the validation of the Turkish version [37] of the MD-APPS scale, while also revealing some unique aspects in the Chinese context. Both our study and the Turkish validation study found a two-factor structure with good model fit. The Turkish version reported factor loadings ranging from 0.48 to 0.84, which is comparable to our range of 0.590 to 0.840 (after removing item 1). This consistency across different cultural contexts supports the robustness of the MD-APPS scale structure and its cross-cultural applicability.
However, unlike the Turkish study, we found it necessary to remove item 1 due to its low factor loading in the Chinese context. This difference highlights the importance of cultural adaptation in scale validation processes. It also suggests that while the overall structure of moral distress might be similar across cultures, specific aspects may be perceived differently in various cultural settings.
The validation of the Chinese version of the Moral Distress Scale-Revised (MD-APPS) offers significant implications for nursing practice in China. At its core, this tool provides hospital administrators and nursing managers with a powerful means to regularly assess and monitor moral distress levels among nurses. This regular assessment is crucial as it enables the identification of specific areas of ethical concern, allowing for the implementation of targeted interventions.
The scale's potential extends beyond mere assessment, reaching into the realm of education and policy development. By incorporating the MD-APPS into nursing education programs, we can raise awareness about moral distress among future nurses, equipping them with the skills to recognize and address ethical challenges in their practice. Furthermore, the two-factor structure of the scale—encompassing 'Obstacles and Coercion/Compulsion' and 'Autonomy/Agency and Support'—provides a comprehensive framework for policy development. This structure allows for the creation of policies that not only address external constraints faced by nurses but also enhance their internal capacities to deal with moral distress.
The test-retest reliability of the scale opens up opportunities for longitudinal studies, enabling researchers and administrators to track changes in moral distress over time. This is particularly valuable for evaluating the effectiveness of interventions or policy changes, providing empirical evidence to guide future strategies.
Collectively, these applications of the MD-APPS have the potential to significantly improve nurses' work environments, potentially reducing burnout rates and ultimately enhancing the quality of patient care in Chinese healthcare settings. As we move forward, it will be crucial to explore the scale's applicability in different regions and specialized nursing fields within China, as well as investigate its predictive validity. Additionally, complementing these quantitative assessments with qualitative research could provide deeper insights into the meanings implied by the scale items and structure in the Chinese context.
By integrating regular assessments, targeted education, informed policy development, and ongoing research, we can create a comprehensive approach to addressing moral distress in nursing. This holistic strategy not only benefits individual nurses but also has far-reaching implications for the overall quality of healthcare delivery in China. As we continue to refine and apply this tool, we move closer to creating more ethically robust and supportive environments for nurses, ultimately leading to better patient outcomes and a stronger healthcare system.
Limitations
The use of convenience sampling may limit the representativeness of our sample, despite selecting 448 clinical nurses from several top-tier hospitals across China. Future studies should consider random or stratified sampling to enhance generalizability.
While we adapted the scale for Chinese culture, unidentified cultural differences might still affect its content validity. Further qualitative research could help uncover subtle cultural impacts.
The dual-factor structure explained 56.34% of the total variance, suggesting potential unexplored factors or dimensions that warrant future investigation.
Non-response bias
The early-late respondent analysis revealed significant differences in age, work experience, and total scores, indicating potential non-response bias. Late respondents scored notably higher (M = 36.3, SD = 6.52) than early respondents (M = 32.4, SD = 5.08) on the main outcome measure (t = -4.9396, p < 0.0010). While this suggests our sample may not fully represent the target population, it provides valuable context for result interpretation. The higher scores among late respondents highlight the importance of maximizing response rates to capture a comprehensive view of the population. These findings underscore the need to consider response timing in online surveys and to incorporate it as a control variable in analyses. This bias may affect result interpretation and generalizability. Despite these limitations, our study retains considerable value and generalizability potential. By transparently reporting these biases, we enhance the depth of our insights and provide a foundation for more robust future research. This approach allows for nuanced interpretation of results and strengthens the overall validity of our findings, albeit with careful consideration of the identified response patterns. Future studies should consider mixed-mode data collection and more aggressive follow-up strategies to mitigate these biases and improve representativeness.
These limitations highlight areas for improvement in future research on moral distress among Chinese nurses. Despite these constraints, our study provides valuable initial insights into the psychometric properties of the Chinese MD-APPS, serving as a foundation for further validation in diverse healthcare settings across China.
Conclusion
In summary, the Chinese version of the MD-APPS scale, through rigorous psychometric evaluation and culturally sensitive editing, has been confirmed as a reliable and effective tool for assessing moral distress in the Chinese nursing professional environment. The validation process not only demonstrated the scale's robust psychometric properties but also highlighted the importance of cultural adaptation in cross-cultural research. The successful validation of this scale provides valuable insights into the nature of moral distress among Chinese nurses and offers a practical tool for its assessment. The two-factor structure of the scale aligns with previous validations in other cultures, supporting its cross-cultural applicability while also revealing unique aspects specific to the Chinese context. The validated Mandarin MD-APPS has significant potential for various practical applications, including regular assessment of moral distress levels, incorporation into nursing education programs, informing policy development, facilitating cross-cultural comparisons, and enabling longitudinal studies. These applications could contribute to improving nurses' work environments, reducing burnout rates, and ultimately enhancing the quality of patient care in Chinese healthcare settings.
Future research could further explore the scale's applicability in different regions and specialized nursing fields within China, as well as investigate its predictive validity. Additionally, qualitative research could be employed to gain a deeper understanding and interpretation of the meanings implied by the scale items and structure in the Chinese context. Such efforts would aim to extend the scale's application and its impact on nursing practice in China, potentially leading to more targeted interventions and strategies for addressing moral distress among Chinese nurses.
Overall, this study provides a solid foundation for future research on moral distress in Chinese nursing practice and contributes to the growing body of cross-cultural research on this important issue in healthcare.
Acknowledgements
We acknowledge the Ethics Committee of Huai'an Hospital, Huai'an City (Ethics Approval No: 2023030) for approving this study; we are also grateful to all human participants for their consent to participate in this research.
Instrument usage
The scale used in this study has been translated into Chinese and is cited in the paper. The original scale was developed by Professor Céline A. Baele and we have obtained her authorization for its use. The original article was published in the Journal of Advanced Nursing (JAN), with Céline A. Baele as the corresponding author. Professor Baele is affiliated with the Faculty of Psychology and Educational Sciences at Ghent University, Belgium.
Declarations
Ethics approval and consent to participate
This study, approved by the Ethics Committee of Huai'an Hospital, Huai'an City (No: 2023030), adhered to the Declaration of Helsinki. Data were collected via online questionnaires and offline surveys. All participants provided informed consent (digital for online, written for offline) after receiving detailed study information.
Participation was voluntary, with no incentives offered. Participants could withdraw at any time without consequences. All data were anonymized and securely stored, with access restricted to authorized researchers. Paper surveys were digitized and securely archived.
The consent process included permission for anonymized data sharing for academic research purposes, including potential future studies subject to ethical approval. Participants were assured of data confidentiality and that only aggregated, de-identified data would be used in publications or presentations.
Consent for publication
Written informed consent was obtained from the nurse volunteers for publication of this manuscript, including any potentially identifiable images or data included.
Competing interests
The authors declare no competing interests.
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