Background
Clinical reasoning is an important and integral part of professional qualification in medical sciences, as the mission of various medical professions is to provide healthcare, nursing, treatment, and rehabilitation services at the highest standard level in order to ensure, maintain, and improve the health of individuals in society [1]. Clinical reasoning is a logical process of gathering information, understanding problems, assessing the patient’s condition, and planning, implementing, and evaluating The most efficient interventions are aimed at improving the health of patients [2]. Therefore, healthcare providers must have the precise and fast clinical reasoning to assess the clinical condition of patients and provide the most effective therapeutic and care interventions [3]. Although clinical reasoning is a well-known term in the field of medicine, and there is a strong emphasis on the importance of clinical competence and training for medical students, this concept is also highly significant in other fields of medical sciences, especially nursing [1, 2].
Clinical reasoning in nursing is a way of thinking about clinical skills and focuses on identifying and diagnosing patient problems and providing timely interventions and care [4, 5]. Because nurses are constantly at the bedside of patients and are the main ones responsible for taking care of patients and evaluating care interventions [6]. Also, nurses who have weak clinical reasoning will be unsuccessful in identifying the care needs of patients and providing timely care to patients and this can severely affect the performance of the treatment team and subsequently seriously threaten the health of the patients [7]. Therefore, it is necessary to pay a lot of attention to their clinical reasoning competence in nursing education and evaluating the clinical competence of nurse [8]. Meanwhile, the nurses of the special care units are one of the most important groups of clinical nurses, whose ability and competence in clinical reasoning to improve the performance of the treatment team and improve the health status of patients is undeniable [9]. Because the nurses of the special care units are facing many challenges and problems due to the critical condition of the patients, and their decision-making and clinical reasoning ability is important in identifying the patients’ problems and presenting them during therapeutic-care interventions to save the lives of the patients [10]. Therefore, the nurses of these departments should have the competence of clinical reasoning, knowledge, skills, and appropriate experience to evaluate and respond appropriately to the complex needs of patients [11].
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Meanwhile, the evaluation of clinical reasoning in nurses is complex and there is a need for valid and reliable tools to measure and evaluate the clinical competence of nurses. Based on this, in recent years, emphasis has been placed on the design and psychometrics of effective and efficient tools for measuring and evaluating nurses’ clinical reasoning. [12, 13]. In this regard, nurses’ clinical reasoning competence scale is one of the most useful scales to evaluate nurses’ decision-making and clinical reasoning ability, which was designed by Bae et al. in 2023 in America. The scale consists of 22 items that assess plan setting, intervention strategy planning, and self-instruction. It has been proven to be a valid and reliable tool for evaluating nurses’ decision-making ability and clinical reasoning in America [13].
Due to the specificity of this scale to measure the clinical reasoning of nurses, we decided to check psychometric characteristics of this scale in Iranian society so that we can evaluate the decision-making ability and competence of clinical reasoning of nurses. So, this study aims to translate and conduct a psychometric evaluation of the Persian version of the clinical reasoning competency scale for nurses in critical care units in Iran.
Methods
Study design
The current methodological study was conducted in the west region of Iran in 2023–2024. The study aimed to assess the psychometric properties of the CRCSN. This included evaluating content validity, reliability (internal consistency and stability), and construct validity (exploratory factor analysis and confirmatory factor analysis). The psychometric properties of CRCSN were evaluated utilizing the COSMIN (Consensus-based Standards for the selection of health Measurement Instruments) criteria [14].
Participants
To ensure the accuracy of evaluating the psychometric properties of CRCN, the sample size was determined based on the number of inventory sections. Initially, a calculation recommended having ten subjects per item [14]. However, for this study, we increased the recruitment to approximately 15 respondents per item to guarantee the precision of both the exploratory factor analysis and confirmatory factor analysis. The participants were conveniently selected from eleven hospitals in Iran. A total of 630 nurses were involved in both exploratory and confirmatory factor analyses. The participants in the exploratory factor analysis differed from those in the confirmatory factor analysis. To be eligible for the study, nurses had to be nursing school graduates, willing to participate, and have a minimum of one year of work experience in an critical care units.
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Clinical reasoning competency scale for nurses
The Clinical Reasoning Competency Self-Report Questionnaire (CRCSN) is designed based on the literature review and in-depth interviews, with 41 items to evaluate nurses’ decision-making power and clinical reasoning competence. In the construct validity phase, 22 items were confirmed in 3 dimensions (plan setting 11 items, intervention strategy planning 8 items, and self-instruction 3 items). The items of this questionnaire were scored based on a 5-point Likert scale (1 = strongly disagree; 5 = strongly agree). The total score on the questionnaire ranged from 22 to 110, with higher scores indicating greater clinical reasoning competency. It is important to note that no specific cut-off points are established to categorize respondents’ clinical reasoning competency [13].
Translation of the scale
Before translating the questionnaire, the developers were contacted, and permission was obtained. The translation followed the standard protocol for the forward-backward translation set by the WHO [15]. Consequently, CRCSN was initially translated into Persian. Two independent translators worked independently and translated the English text into Persian during the forward translation phase. Subsequently, for accurate and specialized translation, the research team and the translators agreed on a single Persian script. During the backward translation stage, two additional translators, who were not involved in the initial translation and had no knowledge of the English version of the questionnaire, independently translated the Persian script back into English. Afterward, to ensure the accuracy of the translation, the research team compared the retranslated English scripts with the original English version. Throughout the entire process of forward-backward translation, the team evaluated the discrepancies between the English and Persian scripts. Lastly, the psychometric properties of CRCN, such as its content validity, reliability (internal consistency and stability), and construct validity, were assessed.
Psychometric properties
Face validity
Thirty-five practicing nurses were chosen with convenience sampling to evaluate the face validity of the items. Each nurse rated each item’s clarity and use of correct and appropriate words and grammar on a 5-point Likert scale. The ratings ranged from 1 (unimportant) to 5 (very important). The completed questionnaires were then collected and analyzed. Items with impact scores above 1.5 were considered acceptable [16, 17].
Content validity
Thirty experts, consisting of 20 nursing PhDs, 5 nurses with master degree of NICU, and 5 neonatal specialist, familiar with the tool making principles, were selected in the convenience method to assess content validity. The experts in qualitative content validity assessed each item for comprehensibility and relevance to Iranian culture, providing comments for each. The experts then reviewed the questionnaires to calculate the content validity ratio (CVR), determining the necessity of each item. In order to evaluate the content validity index (CVI) for each item and the overall instrument, the revised version of CRCN was resubmitted to experts for evaluation of each items relevance to the main concept using a four-point Likert scale ranging from 1 to 4. This study considered a CVI greater than 0.8 and a CVR greater than 0.33 appropriate [17, 18].
Exploratory factor analysis
The construct validity was evaluated with exploratory factor analysis and confirmatory factor analysis to ensure the instrument accurately measured the intended variable [18]. An exploratory factor analysis with Principal axis factoring (PAF) method was performed using promax rotation. The researchers utilized specific criteria to attain an optimal structure, including eigenvalues greater than 1.0 and factor loadings higher than 0.5 [19]. To achieve the most appropriate structure, the researchers conducted the Kaiser-Meyer-Olkin (KMO) test and Bartlett’s test before conducting exploratory factor analysis. In order to conduct exploratory factor analysis, the KMO values closer to 1 and factor loadings higher than 0.5 were considered [14]. In this study, about 14 nurses were included for each item, resulting in 315 nurses participating in the evaluation of exploratory factor analysis.
Confirmatory factor analysis
A confirmatory factor analysis was performed on a sample of 315 practicing nurses who were not included in the exploratory factor analysis. The analysis was conducted using AMOS (v. 21.0), and various indices were utilized to assess the model’s effectiveness. The requirements that needed to be met are as follows: a goodness of fit index (GFI) greater than 0.90, a root mean square error of approximation (RMSEA) lower than 0.08, a Tucker Lewis Index (TLI) higher than 0.90, and a comparative fit index (CFI) higher than 0.90 [20].
Reliability (internal consistency and stability)
This instrument’s reliability was assessed using the Cronbach’s alpha coefficient and test-retest reliability. The Cronbach’s alpha coefficient was calculated for a sample of 315 individuals to evaluate internal consistency. An alpha coefficient greater than 0.7 was deemed acceptable [15]. For test–retest reliability, the intra-class correlation (ICC) was calculated by collecting data from 60 participants at a two-week interval [21].
Data analysis
The collected data were analyzed in SPSS 21.0 and AMOS (v. 21.0) using descriptive statistics(frequency, percentage, mean, and standard deviation), Cronbach’s alpha, test-retest reliability, and factor analysis. The significance level was considered P < 0.05.
Ethical considerations
The institutional review board of the Hamadan university medical science. Research Center provided ethics approval (1402.515). Also at the beginning of this study, the researcher introduced herself explained the goals of the study and provided assurance that all information would remain confidential and that they could withdraw from the study at any time. The researchers provided the opportunity for participants to inform the researcher about their withdrawal from the study at any stage and assured them that their lack of participation or withdrawal would not have any consequence for them. Finally, the participants provided written informed consent to participate in this study. After completing the consent form, the study was planned and implemented.
Results
The socio-demographic characteristics of the nurses
The average age of the participants was 39.84 ± 2.76, ranging from 24 to 53 years. The majority of participants in this phase were women (79.367%), married (75.07%), and possessed a bachelor’s degree (71.58%). Additionally, the average monthly income was reported to be 600 US dollars. They had 6–10 years of work experience and mostly in ICU departments. A statistically significant difference was observed between the clinical reasoning score and work experience (P < 0.05)( Table 1).
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Table 1
Frequency distribution of demographic characteristics (n = 630)
Variable | N | % | |
|---|---|---|---|
Gender | Male | 130 | 20.63 |
Female | 500 | 79.36 | |
Marital status | Unmarried | 472 | 74.92 |
Married | 110 | 17.46 | |
Divorced/Widowed | 48 | 7.61 | |
Education level | Bachelor’s degree in nursing | 451 | 71.58 |
Master degree in nursing | 157 | 24.92 | |
PhD degree in Nursing | 11 | 1.74 | |
Work experience(year) | 1–5 | 64 | 10.15 |
6–10 | 297 | 47.14 | |
11–15 | 108 | 17.14 | |
> 15 | 161 | 25.55 | |
Ward | Intensive Care Units | 365 | 57.93 |
A coronary care unit | 102 | 16.19 | |
Open heart surgery | 13 | 2.06 | |
Neonatal intensive care unit | 78 | 12.38 | |
Pediatric intensive care unit | 72 | 11.42 | |
Face validit y
During this research phase, the participating nurses indicated that all the items assessed were simple, clear, and relevant to the study’s topic. Additionally, the impact score for each item surpassed 1.5.
Content validity
In qualitative content analysis, a panel of experts, recommended revising three items (8, 15, and 21) in the Persian script to enhance clarity and comprehension of meaning and concept. Following the revision, these three items were re-evaluated and approved by experts. The necessity of the items was assessed based on the experts’ opinions, and the CVR was calculated. According to the Lawshe table, a CVR value of 0.33 is considered acceptable. The CVR for all items in CRCN ranged from 0.69 to 1, indicating that no items were removed due to unsatisfactory CVR. Each item’s CVI was also calculated, ranging from 0.82 to 1. None of the items scored below the cut-off point, so all items were kept. Finally, the SCVI/Average of MSCS was determined to be 0.95.
Construct validity (exploratory factor analysis)
Exploratory factor analysis using the varimax rotation identified three main factors, as shown in Table 2, which explained 74.32% of the observed variance together. The items’ factor loadings ranged from 0.621 to 0.912. The three included factors were ' “plan setting” (11 items),” intervention strategy regulation” (8 items), and “self-instruction” (3 items), which showed in Table 2.
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Table 2
Varimax factor loadings of the items of the clinical reasoning competency scale for nurses (n = 315)
Factors’ names | Item | Communality | Factor loading |
|---|---|---|---|
Factor 1: Plan setting | 1- Identify the other method other to solve the patient’s problem. | 0.83 | 0.912 |
2- Reflect the anything wrong with the plan before intervention. | 0.081 | 0.910 | |
3- Repeatedly reflect the process of solving the patient’s problem. | 0.80 | 0.894 | |
4- A different perspective on patient’s health problems. | 0.77 | 0.884 | |
5- Identify a better way to solve the problem even after solving the patient’s problem | 0.75 | 0.868 | |
6- Compare the results of the patient’s problem solving with the target level. | 0.73 | 0.834 | |
7-. Provide integrative interventions considering the patient and situation (e.g., family and environment). | 0.70 | 0.818 | |
8- Evaluate the nursing intervention. | 0.687 | 0.801 | |
9-. A process of sufficient deliberation for interventions. | 0.654 | 0.788 | |
10- Collect additional data to close the gap between the information. | 0.643 | 0.764 | |
11- Continuously check the missing parts in solving the patient’s problem. | 0.621 | 0.737 | |
Factor 2: Intervention strategy regulation | 12- Relate the knowledge to the information. | 0.80 | 0.896 |
13- Prioritize problem solving strategies. | 0.78 | 0.887 | |
14- Discover important problems based on the data. | 0.76 | 0.879 | |
15- Distinguish the importance of the data. | 0.75 | 0.863 | |
16- Comprehensively grasp the relationship between the patient data. | 0.73 | 0.821 | |
17- Understand the overall patient situation. | 0.70 | 0.820 | |
18- Analyze the cause of an error during nursing care. . | 0.67 | 0.787 | |
19- Find any problems in the care and correct them immediately. | 0.65 | 0.739 | |
Factor 3: Self-instruction | 20-. Look for answers to questions don’t know on my own. | 0. 78 | 0.890 |
21- Invest extra time to encounter problems to acquire don’t know about the field of work. | 0.73 | 0.831 | |
22- Interested in acquiring new information related to the field of work. | 0.67 | 0.794 |
Confirmatory factor analysis
The CFA analysis revealed that the model consisted of three factors: “plan setting” (11 items), “intervention strategy regulation” (8 items), and “self-instruction” (3 items). The factor “plan setting” displayed a correlation of 0.90 with the total score of moral competence, while “intervention strategy regulation” and “self-instruction” exhibited correlations of 0.92 and 0.91, respectively. A strong correlation was observed between plan setting and intervention strategy regulation (r = 0.89) and between plan setting and self-instruction (r = 0.90). Additionally, a correlation of 0.88 was found between intervention strategy regulation and self-instruction. The chi-square test yielded a value of 7652.76 (df = 79, P = 0.036), indicating a good fit. Furthermore, the current study found that the GFI was 0.92, indicating a strong alignment with the uni-dimensional model of the PTES construct. Additional indices were examined in this model, including RMSEA = 0.037, CFI = 0.94, NFI = 0.91, and TLI = 0.93. All of these indices confirmed that the moral competence scale was well-fitted by the extracted model (Fig. 1: Model fit of the clinical reasoning competency).
Fig. 1
Model fit of the clinical reasoning competency
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Reliability
The reliability of the questionnaire was evaluated using Cronbach’s alpha coefficient and test-retest reliability. The Cronbach’s alpha coefficient of internal consistency across the 22 items instrument was 0.91; the three subscales of “plan setting,” “intervention strategy regulation,” and “self-instruction” also demonstrated good internal consistency, with Cronbach’s alpha coefficients of 0.93, 0.90, and 0.91, respectively. To assess test-retest reliability, 60 nurses were asked to complete the questionnaire again after two weeks. The results showed no statistically significant difference between the pre-and post-test scores (p = 0.79), indicating good test-retest reliability. Additionally, the intra-class correlation coefficient for the 22-item instrument was 0.91, further supporting the questionnaire’s internal consistency (Table 3).
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Table 3
Mean (standard deviation) and intraclass correlation coefficient (ICC) values for the domains of the clinical reasoning competency scale for nurses (n = 315)
Factor | Dimensions | Mean ± SD | ICC | Confidence interval | P -value |
|---|---|---|---|---|---|
1 | Plan setting | 45.61(2.54) | 0.90 | 0.79–0.90 | p < 0.05 |
2 | Intervention strategy regulation | 31.21(2.76) | 0.91 | 0.86–0.94 | p < 0.05 |
3 | Self-instruction | 13.15(2.18) | 0.90 | 0.81–0.92 | p < 0.05 |
Clinical reasoning competency scale (total) | 90.07(2.48) | 0.91 | 0.80–0.92 | p < 0.05 | |
Discussion
The present study was conducted to translate and evaluate the Persian version of the CRCSN in critical care units in Iran. The research results demonstrated that the Persian version of the scale maintains the same level of validity and reliability as the original version, with all 22 questionnaire items retained. The face validity assessment of the scale showed that all 22 items had a score of over 1.5, indicating a high impact. Additionally, the content validity assessment revealed that the CVR for each item ranged from 0.69 to 1, the I-CVI for the scale ranged from 0.82 to 1, and the S-CVI was 0.95, which is considered suitable. In the exploratory validity phase, the questionnaire structure was found to consist of three dimensions: “plan setting” (11 items), “intervention strategy regulation” (8 items), and “self-instruction” (3 items). The confirmatory validity phase confirmed the tool structure without item deletion or rearrangement. The scale’s reliability was deemed acceptable based on Cronbach’s alpha and test-retest methods. These findings indicate this tool’s appropriateness for measuring nurses’ clinical reasoning competence in critical care units of Iranian society. Therefore, with the Persian version of the Nurses’ Clinical Reasoning Scale, it is possible to evaluate the ability of Iranian nurses to make decisions and correct clinical reasoning. It is also possible to be aware of their challenges and problems to achieve clinical reasoning competence and plan the necessary educational and skill interventions to improve clinical reasoning competence in these nurses.
It is important to note that there are limited professional tools available for researchers to assess the clinical reasoning competence of nurses. However, three specific tools have been utilized in studies to evaluate nurses’ competency in clinical reasoning, and they will be discussed in detail.
In this regard, one of the most suitable scales for evaluating the clinical reasoning of nurses is the CRCSN scale, which the Persian version of this scale has been psychometrically evaluated in the present study. The CRCSN was developed by Bae et al. in 2023 in the United States. This tool consists of 22 items in three dimensions: plan setting, intervention strategy regulation, and self-instruction. The tool has appropriate face and content validity, and the CVR and CVI values have been reported as appropriate. Additionally, in terms of exploratory validity, item factor loadings of this tool have been reported between 0.52 and 0.74, explaining 52.62% of the variance in nurses’ clinical reasoning competence across the three dimensions. Furthermore, the tool has acceptable confirmatory validity, and its reliability has been estimated as 0.92 using Cronbach’s alpha and 0.76 using test-retest reliability. Therefore, it is consistent with the present study (14). However, the evaluation of I-CVI and S-CVI has not been conducted in Bae et al.‘s study, which could further enhance the credibility of this scale for measuring nurses’ clinical reasoning competence. On the other hand, this tool was designed to measure nurses’ clinical reasoning competence in a different cultural context from the Iranian society. Nurses must have strong clinical reasoning skills to effectively evaluate the deteriorating health of patients in critical care units and deliver optimal care to them.
Another scale for evaluating the clinical reasoning of nurse is the Italian Nurses Clinical Reasoning Scale that is among the most commonly utilized tools for assessing the clinical reasoning competence of nurses. In a study conducted by Notarnicola et al. in Italy in 2023, this tool was employed to evaluate three dimensions: nursing problems of health, nursing information of health, and nursing assessment of health. The tool demonstrates strong face validity, structure, and reliability [21]. Although This tool is widely acknowledged as valuable for evaluating the clinical reasoning abilities of nurses in the domains of education and research, it is crucial to highlight that it is specifically founded on the Levett-Jones theoretical clinical reasoning model. In contrast to alternative scales, this tool is renowned for being more demanding and challenging.
The Clinical Reasoning Evaluation Simulation Tool (CREST) is a significant scale utilized in assessing the clinical reasoning competence of nursing students. This tool is based on a clinical reasoning model comprising ten content items. It has been found to possess content, construct, and convergent validity. Additionally, the reliability of CREST has been estimated to be 0.92, making it a suitable tool according to Cronbach’s alpha method. Hence, this scale is considered valid and reliable for measuring the effectiveness of simulation in enhancing reasoning skills for clinical diagnosis and response [22]. This tool is appropriate for educational purposes and for evaluating nursing students’ learning and clinical reasoning. However, it is important to note that working in clinical settings, particularly in critical care units and with sick patients, enhances nurses’ clinical knowledge and skills. Therefore, it is necessary to enhance and assess the clinical reasoning competence of critical care unit nurses through psychometric evaluation.
Another popular tool to evaluate the clinical reasoning of nursing students is the Clinical Reasoning Scale among Nursing Students by Huang et al. (2023) designed and evaluated in Taiwan. This tool consisted of 16 items rated on a 4-point Likert scale. CVI was 0.85-1.0, and confirmatory factor analysis demonstrated a good fit. Additionally, the tool showed satisfactory reliability with a Cronbach’s alpha of 0.78–0.89 [23]. This is a convenient and easy-to-use tool for measuring clinical students’ clinical performance and reasoning. However, there is a need for development and psychometrics to measure and evaluate the clinical reasoning competence of nurses, especially nurses in critical care units.
Limitation
One of the limitations of this study was the selection of samples from public hospitals and the non-participation of private hospital nurses was due to limited access and insufficient resources. Considering the different organizational atmosphere public hospitals compared to private hospitals, also the relative differences in the work and educational records of these nurses with government nurses, so it is advisable for future research to include nurses who work in private hospitals. Furthermore, this scale is recommended to be translated and evaluated in other countries due to cultural differences and variations in nurse education, discipline, and scope of practice among different countries.
Conclusion
The Iranian version of CRCSN in critical care units has been determined to be reliable and valid. As a result, nursing managers are encouraged to utilize this tool to assess the clinical reasoning skills of nurses. It is also recommended that managers and policymakers consistently evaluate the clinical reasoning abilities of nurses, identifying areas for improvement and addressing their needs and challenges. Additionally, nursing education programs should incorporate the evaluation of clinical reasoning skills to enhance patient care quality. Because more correct clinical reasoning can lead to more accurate nursing diagnoses and subsequently to perform the best care measures in the shortest time, which itself improves the quality of care.
Acknowledgements
The present article is the outcome of a research project registered at Hamadan University of Medical Sciences. The researchers are grateful to the authorities at the school of nursing and midwifery of the Hamadan University. The participants, and other individuals who helped them for their cooperation.
Declarations
Ethics approval and consent to participate
The institutional review board of the Hamadan university medical science. Research Center provided ethics approval (1402.515). Also at the beginning of this study, the researcher introduced herself explained the goals of the study and provided assurance that all information would remain confidential and that they could withdraw from the study at any time. The researchers provided the opportunity for participants to inform the researcher about their withdrawal from the study at any stage and assured them that their lack of participation or withdrawal would not have any consequence for them. Finally, the participants provided written informed consent to participate in this study. After completing the consent form, the study was planned and implemented.
Consent for publications
Not applicable.
Competing interests
The authors declare no competing interests.
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