Clinical reasoning is a multifaceted and complex process that begins as soon as the health professionals meet the patients [1], during which they identify the signs and symptoms, process the information, gain a correct understanding of the patients' problems, plan and implement interventions, evaluate outcomes, and reflect on the workflow and learn [2, 3]. Clinical reasoning in nursing includes examining the patients, collecting and reviewing key information, relating the pieces of information to each other, interpreting the information, distinguishing between relevant and irrelevant information, matching, predicting and combining the pieces of information for making a diagnosis, identifying the difficulties or problems, setting goals, planning and selecting the methodology, implementing interventions, evaluating outcomes, and utilizing the results of the evaluation [4].

Evidence suggests that clinical reasoning is a vital competency for improving patient outcomes and increasing the effectiveness of nursing practice [5]. Nurses with poor clinical reasoning are less likely to succeed in understanding the patients, diagnosing their conditions, and saving their lives [6]. Leoni-Scheiber et al. argued that enhancing nurses’ clinical reasoning can improve their job performance [7]. There is an important relationship between clinical reasoning competency and patient outcomes. Nevertheless, nurses’ competency in clinical reasoning is rarely evaluated in nursing schools and even less in clinical settings [8].

To the best of our knowledge, there are a limited number of tools for measuring nurses’ clinical reasoning, most of which are not valid and reliable or have been developed for physicians. For example, Carrière et al. employed it for measuring the clinical reasoning of the medical staff working in pediatric emergency departments [9]. Although that tool was specialized for physicians, it was also used by Dawson et al. to evaluate the clinical reasoning competency of nursing students [10]. It seems that these scales could be suitable in the medical field. In a recent review article, it was found that most of the included articles reported on the Script Concordance Test or Lasater Clinical Judgement Rubric to measure clinical reasoning [11].

Various tools were used to evaluate clinical reasoning and related constructs in placements and simulation in health professional education, but many of these evaluation tools were described as rubrics, examinations, and objective structured clinical examinations (OSCEs), and the authors did not clearly define the construct being assessed as one of critical thinking, clinical judgment, clinical decision making, or clinical reasoning [11]. There may be semantic differences between these concepts, however, if they are developed based on the clinical reasoning model, they can be considered clinical reasoning scales.

Liou et al. developed the Nurses Clinical Reasoning Scale (NCRS) and evaluated its psychometric properties [12]. Its items were (i) based on a specific model of clinical reasoning, and (ii) noted by the original authors to be “perceived” clinical reasoning competencies. In this model, clinical reasoning was described as ‘a logical process by which nurses collect cues, process the information, come to an understanding of a patient problem or situation, plan and implement interventions, evaluate outcomes and reflect on and learn from the process’ [12]. The NCRS was psychometrically tested in Chinese and translated into English. The results of this psychometric study supported the validity and reliability of the developed scale. Construct validity of the NCRS was based on factor analysis where the emerged one factor explained 50.7% of the variance of clinical reasoning competence. The Cronbach’s alpha for the NCRS was good (α = 0.90), and the test-retest reliability was evidenced by high intraclass correlation (ICC = 0.87). It was translated and validated by Jung and Han [13] for use in a Korean context and was also used to measure nursing students' clinical reasoning ability by Hong et al. [14]. It seems that, this scale has good reliability in other cultures, for example, in Korea, Italy and Dutch [13, 15, 16]. Due to the described properties, the NCRS seemed well-suited to assess clinical reasoning in Iranian clinical nurses [12]. This study aimed to translate and determine the psychometric test of the Persian version of the nurses clinical reasoning scale.

A total of 170 nurses completed the NCRS (response rate: 94.44%). The data showed that the mean and standard deviation of age and work experience of the respondents were 34.54±6.97 and 9.91±6.41 years, respectively. The demographic information of the respondents is presented in Table 1. The mean and standard deviation of nurses clinical reasoning score was 60.91±7.079 (Range: 34 to 75, CI 95%, 59.84 to 61.98).

This study aimed to translate and determine the psychometric test of the Persian version of the nurses' clinical reasoning scale. The results showed that the CVI of this tool was acceptable, and no significant change was made in face validity.

The results of the KMO test and Bartlett's test indicated the adequacy of the sample size for this analysis. Based on EFA results, there were two factors with eigenvalues greater than 1 that predicted 52.65% of the total variance.

The first factor, nursing diagnosis, was mainly about data collection to diagnose and nursing diagnosis Nurses with poor clinical reasoning competency often cannot diagnose the worsening conditions of a patient; this may result in making wrong decisions and, thereby, inefficient patient care and increases patients’ suffering [20]. The second factor, care knowledge, was mainly focused on nursing interventions and nursing knowledge. Regarding the promotion of patient safety when performing routine nursing interventions, nurses need to acquire clinical knowledge, skills, and expertise through clinical reasoning. In fact, clinical reasoning can correctly guide nurses to achieve optimistic outcomes and prevent unpleasant injuries to patients [7].

These two factors extracted from the instrument (nursing diagnosis and care knowledge) can largely represent the nursing process. Leoni-Scheiber et al. stated that clinical reasoning is a method for achieving an advanced nursing process [7]. Bruylands et al. and Müller-Staub et al. also believe that a high level of clinical reasoning can effectively help nurses to improve nursing evaluation, diagnosis, and interventions [21, 22].

However, Guerrero et al. believed that clinical reasoning manifests itself through the nursing process [20]. The nursing process involves assessment, diagnosis, planning, implementation and evaluation, which form the basis of clinical reasoning. Clinical reasoning is practically an organizing framework that underpins all models of care and hence must be the center of attention [23]. Considering that both clinical reasoning and the nursing process may be rooted in problem-solving [24], it is possible to point out the connection of clinical reasoning with the nursing process and problem-solving. Problem-solving is one of the main uses of critical thinking, and critical thinking is the main tool for problem-solving [25]. On the other hand, Clinical reasoning is based on the principles of the nursing process, problem-solving, and the scientific method, and requires opinion and decision-making based on evidence [24].

The EFA reported on one factor in the study of Liou et al. They discussed although the clinical reasoning model used to construct the NCRS presents an eight-step circular diagram, the distinction between the stages is not clearly defined, providing a one-dimensional conceptual model of clinical reasoning [ 12 ].

In our research, Cronbach’s alpha for the overall instrument was 0.9, which was an acceptable value for internal consistency. Italian, Dutch and Korean versions have also reported good reliability [ 13-15]. Italian version has been reported as reliable, both showing a good internal consistency (Cronbach's Alpha = 0.90], and good stability (ICC = 0.90; CI = 0.87-0.92) [16], in the Dutch version, Cronbach’s alpha was 0.94 [15], and in Korean version, Cronbach's Alpha was 0.93 [13].

Given the fact that this is the first study testing these psychometric properties of a translated version of the NCRS, we are not able to compare our results to equal studies in Iran. Considering more than a one-factor model may be meaningful in future studies for this population to improve model fit. In the liou study, one factor was revealed in the factor analysis [ 12 ], but in the Dutch version, CFA, did not provide the hypothesized one-factor structure too. In the Dutch version, EFA showed a two-factor structure, and this result is similar to our study results [ 15 ].

This study aimed to determine the psychometric properties of a model-based tool for assessing nurses’ clinical reasoning from the perspective of nurses working in Iranian public hospitals. The results showed that the NCRS was a valid and reliable instrument that could be applied to future surveys on the clinical reasoning of Iranian nurses. The Iranian version is a short and easily administrable questionnaire with good overall psychometric properties. Therefore, the scale could be a useful tool for Iranian nurses.

The findings of this study provide a suitable tool for nurses, officials and researchers so that by accurately measuring the clinical reasoning of nurses, they can take appropriate measures to improve the conditions, or they can measure the effect of interventions related with clinical reasoning. Also, future researchers can use advanced methods to test psychometric of the instruments by removing the limitations of the study. We thank all nurses for their sincere cooperation despite demanding workloads.

Study design: EA

Data collection: AS

Data analysis: PS

Study supervision: FJ

Manuscript writing: EA, AS, FJ