Background
In nursing practice, with the mutual influence of behavior and emotions between nurses and patients, a nurse-patient relationship characterized by caring interaction has been formed [1]. As nurses deliver front-line care, communication between nurses and patients is essential in developing the nurse-patient relationship and gaining trust from patients and their families [2]. As a fundamental component of nursing practice, nurse-patient communication occurs not only during the nursing process but also in daily interactions, constituting the bedrock of nursing activities that ensuring optimal health outcomes.
The communication between nurses and patients plays a crucial role in nursing care. Firstly, patient-nurse communication is imperative for fulfilling patient-centered care requirement, through which nurses can acknowledge patients’ health conditions and emotional experiences, and thus delivering healthcare services according to patients’ needs and preferences [3, 4].Secondly, patient-nurse communication is essential for the implementation of routine nursing tasks, as data collection during nursing assessments, dissemination of health education, and explanation prior to nursing procedures all rely on communication process. Furthermore, patient-nurse communication is the core element for safeguarding patients’ autonomy, informed consent, and shared decision-making rights [4, 5]. Thirdly, effective nurse-patient communication significantly improves patient health outcomes. Research has demonstrated that such communication can alleviate patients’ negative emotions, enhance treatment adherence, and thereby promote better disease prognosis [6, 7]. Moreover, effective communication between nurses and patients is conducive to improving patient satisfaction with nursing staff, enhancing patient cooperation with nursing work, improving patients’ healthcare experience, and thereby improving patient health outcomes [6, 8]. Lastly, given the paramount importance of patient safety in global healthcare services, effective communication founded on mutual trust between nurses and patients is crucial. Such communication not only mitigates errors in information transmission but also empowers nurses to proactively prevent or promptly identify adverse events, thereby fostering a culture of patient safety [9, 10].
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Studies have shown that effective nurse-patient communication plays a pivotal role in enhancing patient outcomes and satisfaction by mitigating patients’ negative emotions and bolstering their adherence to treatment regimens and medication protocols [11‐13]. Nevertheless, studies have highlighted a significant prevalence of medical disputes attributable to nurse-patient communication breakdowns. For example, 78.1% of patients have reported encountering obstacles during interactions with nursing personnel [14]. IFurthermore, a systematic review underscored that a substantial majority (78%) of nurses in mainland China have encountered incidents of workplace violence, with communication barriers identified as one of the contributing factors [15].
Attitude is defined as the predisposition to assess phenomena with leaning towards agreement or disagreement, typically manifested through cognitive, affective, and behavioral dimensions [12]. According to the Theory of Planned Behavior, all factors influencing behavior indirectly affect behavioral performance through behavioral intentions, which are primarily influenced by individuals’ attitudes [16]. In the context of nurse-patient communication, attitudes denote the viewpoints embraced by both nurses and patients during their interactions. The attitudes nurses espouse in their communication with patients are indicative of their commitment to caring values and service philosophy [17].
However, the measures assessing attitudes in nurse-patient communication, including the Observational Checklist of Health Dialogue Elements (OCHDE) [18], the Amsterdam Attitude and Communication Scale (AACS) [19], and the Caring Nurse-Patient Interaction Scale (CNPI Scale) [20], often exhibit a narrow focus. These instruments offer limited items and may thus inadequately capture the entirety of nurses’ attitudes. Research has shown that attitudes measured across multiple dimensions possess superior predictive validity concerning overall behavioral patterns. If the behavior to be predicted is highly specific, then the attitudes used for prediction should also be highly specific and targeted [21]. Therefore, utilizing scales that specifically assess nurses’ attitudes towards communication with patients can yield enhanced measurement efficacy and enhance predictive accuracy of behaviors.
The nurses’ attitudes towards communication with the patients (ACO) scale was developed by professor Giménez-Espert using literature analysis and expert consultation methods [22]. The scale comprises three dimensions, including cognition, affection and behavior, with a total of 25 items. The Cronbach’s α coefficient for each dimension of the scale ranges from 0.85 to 0.95. The scale has been applied in clinical nurse and nursing student populations [22]. It has a moderate number of items, a comprehensive item pool, and good reliability and validity. However, evidence on the psychometric properties of the ACO scale in the context of Chinese cultural remains unknown.
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Currently, there is a lack of specific scales for measuring nurses’ attitudes towards nurse-patient communication in China, making it difficult to provide measurement tools for subsequent research. Therefore, this study aims to translate the ACO scale into Chinese and conduct research on a sample of nurses in China to evaluate its psychometric properties. It would be beneficial to provide a reliable and valid tool for cross-sectional surveys and intervention studies, specifically for nurses’ attitudes towards communication with patients, considering the unique nature of nursing practice environments.
Methods
Study design and participants
This cross-sectional study was conducted in line with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist [23].A convenience sample of nurses from 4 hospitals in Beijing and Tianjin City, mainland China.
The inclusion criteria were participants who: (a) were registered nurses with at least six months of working experience; (b) worked in inpatient ward; (c) were able to give informed consent. The exclusion criteria were participants who: (a) were nursing students or interns; (b) were not involved in bedside care, for example, full-time teaching or research nurses.
According to the standard advocated Kendall [24], a sample size of 5–10 participants per item was recommended when testing the psychometric properties of a scale, and 20% of participants should be added to account for attrition. With 25 items for ACO scale, the total sample size needed was at least 300 individuals. In this study, we planed to conduct exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The sample size for CFA should be at least ten times the number of items and greater than the sample size for EFA [25]. Therefore, we ultimately included 610 nurses, with 300 participants for EFA and 310 participants for CFA.
Instruments
ACO scale
The ACO scale is a self-rating instrument developed to measure nurses’ attitudes towards communication with patients [22]. It consists of 25 items answered on a 5-point Likert scale (ranging from strongly disagree to strongly agree) and is categorized into three dimensions: recognition, affection, and behavioral tendencies. Each item is scored from 1 to 5 points, with the affection dimension being scored negatively. Higher scores indicate more positive attitude.
Jefferson Scale of Empathy-Health Professionals (JSE-HP)
The JSE-HP, which was developed by professor Mohammadreza Hojat and his research team, is a valid and reliable instrument for assessing health providers and medical students empathy ability [26].This study employed the Chinese version of JSE-HP scale to assess nurses’ empathy [27].Each item of the JSE-HP is rated on a 7-point Likert scale from 0 (strongly disagree) to 6 (strongly agree). Higher scores reflect greater empathy ability. The Chinese version of JSE-HP has acceptable validity and reliability for assessing empathy ability among nurses in China, and it has been used to test the convergent validity of other scales [28, 29].
Translation and cross-cultural adaptation process
We contacted the original author and obtained permission to translate the scale into Chinese. Then we translate the ACO scale using a forward-backward translation procedure in line with the guidelines proposed by Brislin [30].The procedure was as followed:
Step I:
Two translators who hold PhD in nursing translated the original ACO scale into Chinese independently. They were both unfamiliar with the scale.Two psychology professors discussed and resolved any discrepancies to reached an agreement on a original version named Chinese version 1 of the ACO scale (ACO-C1).
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Step II:
Two English professors with overseas learning experiences translate ACO-C1 back into English and created two back-translations. These two professors were completely blind to ACO scale and had no medical background. Two nursing professors discussed and revised the differences of back-translations and formed a back-translation version.
Step III:
According to the principle of achieved semantic, idiomatic, and conceptual equivalence, a nursing professor and a psychology professor reviewed the original version, ACO-C1 and back-translation version, after comparing and proofreading, formed a Chinese version called ACO-C2.
Step IV:
Based on nursing-related professional knowledge, actual work situations and Chinese language habits, an expert panel consisting of 2 nursing management specialists, 2 nursing professors, 2 psychology professors and 2 clinical nursing specialists was invited to revise the ACO-C2. The expert panel then reached consensus, and produced a pre-final version ACO-C3.
Stage V:
A pilot study was conducted in 20 clinical nurses. The participants were encouraged to provide suggestions and comments on the revision to make expressions clearer. The response time was also recorded.
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Data collection
Before the survey conducted, we introduced the purpose and content of this research to the directors of the nursing departments in each hospital. The questionnaire was distributed through a web platform (Questionnaire Star). The objectives and scope of the survey were introduced to the clinical nurses. Nurses meeting the predefined criteria were subsequently invited to utilize their mobile phones to scan a QR code for accessing the questionnaire. In order to ensure the reliability of data collected via the electronic questionnaire, a minimum completion time was enforced based on the pilot study. Furthermore, measures were implemented to restrict submission to a single instance per IP address associated with each mobile device. Incentives, such as red envelopes distributed through the Questionnaire Star platform, were provided to encourage participants to complete the survey.
Statistical analysis
All data analyses were performed using SPSS Version 26.0 (SPSS Inc.) and AMOS Version 26.0 (IBM Corp.). The online questionnaire required a response to every question, otherwise, it could not be submitted, thus eliminating the possibility of missing data.
Item analysis
The item analysis of the ACO was estimated in terms of item-to-total correlations and discriminative validity. The item-to-total correlations were evaluated using Pearson correlation between the item scores and total scale scores. If the correlation between an item score and the total score is < 0.30, it would be deleted. Discriminative validity was evaluated by comparing the average ACO scores between the high and low groups for each item using independent sample t test tests. If p < 0.05, it indicated that the item had good discrimination and could be retained; otherwise, it will be deleted. In addition, if the difference value was 95%, and its confidence interval does not include 0, which can also indicate that the difference is statistically significant.
Content validity
The content validity of the ACO was estimated using the content validity index (CVI) derived from the evaluations executed by eight experts (two nursing professors, two psychology professors, two nursing directors and two head nurses). All items of the scale were assessed by a 4-point Likert scale (1 = not relevant, 2 = weekly relevant, 3 = strongly relevant, 4 = highly relevant). If the item-level CVI (I-CVI) was ≥ 0.75, scale-level CVI/average (S-CVI/Ave) ≥ 0.90 and scale-level CVI/universal agreement (S-CVI/UA) ≥ 0.80, the content validity of the scale was considered acceptable [31].
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EFA
The total samples were randomly divided into Group A (300 participants), which was used for EFA, and Group B (310 participants), which was used for CFA. Before EFA, the correlation matrix between items was calculated. The EFA was performed using main component analysis and varimax rotation, and the adequacy of using the EFA was estimated using the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett’s sphericity test. If the value of KMO >0.80, it suggested suitability for EFA. Factor loadings for each item should be bigger than 0.40 on one of the common factors [32]. If item commonality < 0.50 or the item had high loading values (> 0.40) on more than two common factors, it will be considered for deletion.
CFA
The goodness-of-fit of the CFA model was determined by assessing ratio between chi-square and the degrees of freedom (χ 2/df), comparative fit index (CFI), root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), goodness-of-fit index (GFI) and adjust goodness-of-fit index (AGFI).The criteria for a good fit were χ 2/df < 3,CFI ≥ 0.90, RMSEA < 0.08, SRMR < 0.10,GFI>0.9,AGFI>0.9. Parsimony Fit Indexes include the Parsimony Goodness-of-Fit Index (PGFI), Parsimony-Adjusted Normed Fit Index (PNFI), and Parsimony-Adjusted Comparative Fit Index (PCFI). Values greater than 0.5 for these three indices indicate that the model is parsimonious. The higher the value, the simpler the model.
Convergent validity
In our study, JSE-HP was used to test the convergent validity of the ACO. The correlation between the ACOR-C and the JSE-HP was assessed using Spearman’s correlation coefficient. A Cronbach’s alpha value of > 0.70 was considered satisfactory reliability.
Reliability analysis
Internal consistency was calculated by Cronbach Alpha value of the scale and three dimensions. Sufficient homogeneity of the items is based on a score above 0.70. To describe the test-retest reliability of the ACO, 30 clinical nurses were selected to complete the scale after a 14-day interval. The test-retest reliability was estimated in terms of the intraclass correlation coefficient (ICC), with a value > 0.70, suggesting acceptable reliability [33].
Ethical considerations
This research was approved by the Ethics Committee on Scientific Research of Chinese PLA General Hospital(NO.2024KY010-KS001). All participants signed an electronic informed consent form before answering the online questionnaires. Furthermore, all the information obtained from the participants remained strictly confidential and anonymous, and the data collected was for research purposes only.
Result
Characteristics of participants
A total of 610 nurses completed the questionnaires, out of which 561 (91.9%) were women and 49 (8.1%) were men. Their ages ranged from 22 to 56 years, with a mean age of 33 years and a standard deviation (SD) of 6.3. Nurses who had completed an undergraduate course count the most (82.1%), and 38 had received a master’s degree (6.2%). Among them, most were married (70.4%), and 1.5% were divorced / widowed. 244 (40%) participates had been working for 6 to 10 years,118(19.3%) had been working for 11 to 15 years. The frequency distribution of responses to each item by all participants was shown in Table 1.
Table 1
Frequency distribution of ACO responses (n = 610)
Translation and cross-cultural adaptation
We finished forward-backward translation. In process of cross-cultural adaptation, experts expressed that most of the items are consistent with Chinese culture. Four experts suggested that item 3 (“I’m nervous when I explain the procedure to the patient and/or family”) and item 12 (“It makes me nervous to explain the procedure to the patient or family”) have similar meanings in Chinese, indicating a lack of clear semantic differentiation. Following correspondence with the original author of the ACO scale via email, it was clarified that these two items refer to different temporal aspects: item 3 pertains to emotions experienced before undertaking a nursing operation, whereas item 12 pertains to emotions experienced after completing such an operation. However, in the Chinese context, nursing procedure spans the entire nursing process, the time points referred to by these two items were found to be ambiguous.The semantic redundancy between the two items makes it impossible to ensure content equivalence. The subsequent analysis phase will further evaluate whether to delete the items to ensure methodological rigor. For item 5, “I feel nervous about providing information to patients and/or families to help prepare for discharge,” experts recommended removing the word “help” as it was considered redundant based on linguistic conventions.Regarding item 22, “It is important to inform the patient and/or family members how to adjust to the ward (visiting hours, daily schedule),” experts suggested that the phrase “adjust to the ward (visiting hours, daily schedule)” was neither accurate nor comprehensive enough. They recommended changing it to “adapt to the ward environment.“After careful discussion with the experts, we have decided to implement both of these suggestions.
In the pilot study, all participants affirmed the scale’s coherent thematic structure and expressed satisfaction with its semantics and scoring methodology. The average response time was approximately 4 min, with a 100% response rate.
Item analysis
The item-to-total correlations ranged from 0.489 to 0.811 (p < 0.001) (Table 2). Ranked nurses’ ACO total scores, taking the highest 27% of the scores (>109)as the high group and the lowest 27% (< 79) as the low group. The results showed that there were significant differences between the high and low groups for each item (p < 0.001), and none of the 95% confidence intervals included 0, so we retained these 24 items of the ACO scale.
Table 2
Item-to-total correlation, CVI for the ACO (n = 610)
Content validity
The ACO was assessed by the eight experts, with the I-CVI ranging from 0.875 to 1.00, an S-CVI/Ave of 0.96 and S-CVI/UA of 0.83, thus indicating acceptable content validity (Table 2).
EFA
The correlation matrix between the items was calculated. Except for the correlation coefficient between item 3 and item 12, which was 0.881, the remaining correlation coefficients fell within the ideal range of 0.3 to 0.7. Since the correlation coefficient between these two items was excessively high (greater than 0.8), it indicated severe multicollinearity, preventing the calculation of the KMO value [32]. Based on expert opinions regarding cross-cultural adaptation, item 12 was removed, while item 3–having a higher factor loading–was retained. This adjustment resulted in the resequencing of the remaining items.
An EFA of the 24 items showed that the KMO value was 0.932, and Bartlett’s test of sphericity reached a level of significance (χ 2 = 4578.95, df = 276, p < 0.001), indicating that it was suitable for factor analysis. The main component analysis with varimax rotation led to the extraction of three factors, where the eigenvalues were > 1, accounting for 70.138%of cumulative variance contribution. All variables had a loading value above the criterion 0.4. However, item 14 and item 22 exhibited cross-loading, indicating that both had high loading values on two different factors. Although we attempted to apply oblique rotation to eliminate the cross-loading, the resulting loading values for these two items were even higher than those obtained with orthogonal rotation. Additionally, the commonality values for both items were found to be below 0.5, which falls below the acceptable threshold for meaningful interpretation. After a thorough review of the content, the researchers concluded that these two items were not crucial in explaining NACO. Consequently, we decided to remove item 14 and item 22, the remaining items were reordered accordingly. Then the EFA still yielded a three-factor structure (Fig. 1), explaining a variance of 69.277% in the model. The factor loading values of the remaining items were shown in Table 3.
Table 3
Factor loading values of the ACO (n = 300)
Fig. 1
The gravel figure of the ACO
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CFA
It could be seen from the model fitting results that, except for the CFI which was slightly lower than the criterion (CFI = 0.832), the other indicators were up to standard (X²/df = 2.027, RMSEA = 0.039, GFI = 0.964, AGFI = 0.995, RMR = 0.073, PGFI = 0.743, PNFI = 0.882, PCFI = 0.861), indicating that the factor model matched well. Nevertheless, the three dimensions had a moderate-to-high correlation with each other (r = 0.54,0.58,0.84 respectively, p < 0.001) (Fig. 2). A second-order CFA was conducted to examine the hierarchical relationships among constructs by specifying a second-order latent factor with the three first-order factors. The results showed that the model fit indices were (X²/df = 2.412, RMSEA = 0.059, GFI = 0.959, AGFI = 0.904, RMR = 0.064, CFI = 0.892, PGFI = 0.594, PNFI = 0.637, PCFI = 0.0.604), indicating an acceptable fit to the data. Hence, 22 items were retained in the final ACO (Fig. 3).
Fig. 2
A first-order confirmatory factor model of the ACO
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Fig. 3
A second-order confirmatory factor model of the ACO
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Convergent validity
Significant and positive correlations were found between the overall score of ACO and scores on JSE-HP (r = 0.375, P<0.01).The affection dimension of ACO had a moderate and positive correlation of r = 0.368 with empathy measured by JSE-HP (p < 0.01); The behavior dimension also had a moderate and positive correlation of r = 0.321 with empathy. But the cognition dimension had low correlation with empathy (r = 0.021, P<0.01).
Reliability analysis
The ACO presented excellent internal consistency with Cronbach’s alpha coefficient for the total scale being 0.946, and for the three dimensions were 0.826,0.937and 0.909, respectively. As for test-retest analysis, 30 clinical nurses were selected to complete the scale after a 14-day interval.The ICCs for the ACO were 0.879, and the ICCs for three dimensions were ranged from 0.754 to 0.934, which may be considered adequate.
Discussion
To our knowledge, this research first translated the ACO scale into Chinese. The psychometric testing results demonstrate that the Chinese version ACO scale is a reliable and valid tool for evaluating nurses’ attitudes toward communication with patients.
Introducing a translated scale entails evaluating its equivalence to the original scale. Content equivalence necessitates ensuring that each item resonates appropriately within the cultural context of its users [34]. Specificity considerations encompass group-specific nuances, acknowledging that identical terms may carry divergent connotations across distinct cultural milieus. Skillful management during translation and back-translation processes is crucial. Expert panel deliberations are also necessary, which culminating in decisions regarding the inclusion, modification, or omission of scale items [35]. During the cultural adaptation process, it was found that the translated item 12 did not achieve content equivalence. This issue arose because in the Chinese context, the nursing procedure encompasses the entirety of nursing practice, thereby blurring distinct boundaries between the stages of ‘before’ and ‘after’ implementation. Following consultations with experts, item 12 was deleted.
Item analysis is an important step to test the quality of each item of the scale, aiming to evaluate whether the items are applicable and independent in the dimension or scale [36]. By comparing the results between the high and low groups for each item, significant discriminative ability of the ACO in assessing the participants’ attitude levels was revealed. In addition, the item-to-total correlations and the corrected item-to-total correlations for each item were well above the limit, suggesting that the items were representative.
Content validity analysis checked the adaptation degree of the actual measurement content and expected measurement content of the scale for evaluation indicators [37]. The I-CVI, S-CVI/Ave and S-CVI/UA of ACO met the statistical criteria, indicating that the content validity of this Chinese version scale was excellent.
Based on the research findings, the results of KMO and Bartlett’s sphericity test showed that there was a strong correlation between the items, which is suitable for subsequent factor analysis. This research extracted three common factors through principal component analysis and varimax rotation. Compared to the original scale, two items (item 14 and item 22) respectively exhibited higher loading values across two factors. Although EFA accommodates some degree of item cross-loading, such occurrences can diminish factor discriminability and compromise model fit [38]. When the oblique rotation method was applied for testing, the factor loadings of these two items increased, further verifying the correlation between the three factors of the scale, a relationship that was fully validated in the CFA. The increase in factor loading values occurred because oblique rotation of correlated factors tends to overestimate the loading values, resulting in larger values compared to orthogonal rotation [39]. Ultimately, we decided to delete items 14 and 22 due to their low commonalities and minimal contribution to the conceptual interpretation.
The original scale did not conduct CFA, whereas this research addresses this limitation by thoroughly exploring the applicability of the three-factor model. The result of CFA showed moderate to high correlations between the factors, which reflected that the items of these three factors were not completely independent, thus constructing and fitting a second-order three-factor CFA model was needed. In CFA, when the model has only three first-order factors, the second-order factor model is mathematically equivalent to the first-order factor model [40, 41]. The overall fit indices of the second-order CFA model indicated that both models were similar, with minimal differences in the final fit indices. However, the parsimony fit indices showed that the first-order CFA model was more parsimonious. Considering the practicality of the model, the first-order CFA model requires fewer parameters to express the relationships between variables. Therefore, by combining the parsimony indices with the model’s practicality, selecting the first-order confirmatory factor model is a more reasonable choice.
The ACO had excellent internal consistency, consistent with previous findings. This suggests that the scale’s reliability is well-supported among the Chinese population. Furthermore, the test-retest reliability of both the total score and the three dimensions indicated good stability and consistency over time. Consistent with prior research, we observed a significant correlation between the ACO and the JSE-HP, implying an association between communication attitude and empathy among clinical nurses. This suggests that improving empathy when communicating with patients may positively influence nurses’ attitudes [42‐44].
In the convergent validity test, the cognitive dimension of the NACO scale exhibited a low correlation with the JSE-HP. This low correlation is likely due to the conceptual differences between the scales. The JSE-HP Scale comprises three dimensions: perspective taking, compassionate care, and walking in the patient’s shoes, focusing on emotional reactions and behavioral abilities [27]. Consequently, this focus results in a low correlation with the cognitive dimension of the NACO scale. For future research, it is recommended to select alternative measurement indicators to further evaluate the convergent validity of the NACO scale.
The Attitude ABC Theory, proposed by Hovland [45], serves as the theoretical foundation of the ACO scale, offering a comprehensive understanding of attitude. This theory outlines three components: the affective component, which pertains to emotional responses or evaluations towards the attitude object; the cognitive component, which involves awareness and thoughts about the attitude object; and the behavioral component, which reflects behavioral intentions or actions towards the attitude object.
The cognition dimension of the ACO scale assesses nurses’ awareness of factors like adaptation to the ward environment, discharge rehabilitation, and multidisciplinary cooperation. Patients’ adaptation to the ward environment is crucial for fostering positive nurse-patient relationships and improving treatment outcomes [46, 47].Similarly, multidisciplinary cooperation in rehabilitation plays a vital role in enhancing patients’ quality of life [48, 49]. The affection dimension of the scale gauges nurses’ subjective initiative in exchanging opinions, emotions, and information with patients. Assessing nurses’ feelings of nervousness or irritability during daily work reflects their caregiving role and emotional transmission in nurse-patient communication. Positive emotional communication can alleviate patients’ distress, enhance treatment compliance, and improve disease prognosis [50‐52]. The behavior dimension of the scale is rooted in the predictive influence of attitude on behavior. This influence manifests in three aspects: attitude’s impact on behavior choice, intensity, and persistence [53‐55]. People tend to choose behaviors aligned with their attitudes, and stronger attitudes often lead to more robust behaviors. Moreover, stable attitudes are more likely to sustain consistent behavior over time.
The findings of the cross-sectional study affirmed the suitability of the Chinese version ACO scale as a self-assessment tool for evaluating nurses’ attitudes towards nurse-patient communication. This scale serves as a tool for the objective assessment of NACO and the exploration of its determinants. By employing this practical scale, nurses can gain deeper insights into their own communication attitudes and their potential impact on nurse-patient interactions. Furthermore, the scale facilitates the identification of nurses harboring negative communication attitudes, enabling targeted support initiatives for this subgroup. Drawing on insights derived from the assessment and influencing factors outlined by the ACO scale, nursing administrators are encouraged to implement strategic interventions. These may encompass the establishment of communication frameworks, introduction of incentives to promote positive communication attitudes, and the provision of customized communication education and training programs. Such initiatives aim to enhance nurses’ communication attitudes and behaviors, thereby elevating patient satisfaction levels and ensuring optimal patient safety.
Limitation
This research presents several limitations. Firstly, nurses’ attitudes toward nurse-patient communication is an topic that requires further research, as there are few studies on its concepts, influencing factors, and interventions. More theoretical and practical research will help optimize the theoretical framework and application evaluation of this scale. Secondly, during the CFA stage, two items were deleted. However, factor loadings and factor models may vary due to differences in regions, sample sizes, and respondent conditions. Therefore, future research endeavors are warranted to validate the appropriateness of these item deletions. Thirdly, the convenience sampling method used in this research may have introduced sampling bias, limiting the generalizability of findings to the broader population of nurses. To enhance the robustness of the scale, future studies should consider conducting multi-center research involving diverse regional and cultural contexts, thereby providing a more comprehensive assessment of the scale’s reliability and validity.
Conclusion
The Chinese version of the ACO scale has good psychometric properties and can be used to measure nurses’ attitudes toward communication with patients, identify weakness in nurse-patient communication, and propose targeted intervention measures. Further evidence supporting its application is expected from a diverse population among Chinese clinical nurses. Large-sample studies are also needed to demarcate the thresholds for positive and negative attitudes. Due to differences in cultural background and medical environment, this tool needs to be validated in more countries and regions.
Acknowledgements
None.
Declarations
Ethics approval and consent to participate
The Ethics Committee on Scientific Research of Chinese PLA General Hospital approved the research. All participants signed an informed consent form.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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