Introduction

In increasingly complex clinical settings, Evidence-Based Practice (EBP) is being emphasized to ensure patient safety, reduce medical costs, and improve the quality of care [1]. EBP is a problem-solving process aimed at making right clinical decisions [2], and clinical reasoning is essential to this process [3]. Clinical reasoning is a complex cognitive process involving the use of various thought strategies to collect and analyze patient information, assess the significance of that information, and prepare alternative courses of action [4]. To implement EBP, nursing students, as future nurses, must develop clinical reasoning skills, which can be cultivated through critical thinking, nursing knowledge, and learning experiences. For this reason, systematic education for undergraduate nursing students is necessary [5].

Several prior studies have highlighted the need for changes in nursing education to enhance nursing students’ clinical reasoning skills. Kavanagh and Szweda (2017) [6] reported that about 77% of newly licensed nurses either fail to recognize or inadequately respond to changes in patient condition or urgency due to insufficient clinical reasoning skills [6]. Hunter and Arthur (2016) [7] argued that the current clinical training environment prevents clinical instructors from adequately assessing students’ clinical reasoning skills [7]. Van Wyngaarden et al. (2019) [8] pointed out that nursing education for clinical reasoning skills should employ innovative, learner-centered teaching strategies rather than traditional teacher-centered approaches. Moreover, students need be provided with clinical practice environments where they can apply nursing theory to practice [8].

In the nursing process, nursing diagnoses are the outcomes of clinical reasoning based on a complete nursing assessment [9]. Case reports utilizing the nursing process are one of the main learning strategies used to enhance students’ clinical reasoning abilities [3,10]. According to previous studies, education using unfolding case studies has a positive effect on improving students’ critical thinking, self-efficacy [11], clinical reasoning, and selfdirected learning [12]. Introducing case reports early in the nursing curriculum has also been recognized as a meaningful teaching strategy for enhancing clinical reasoning skills [13].

To improve nursing students’ clinical reasoning skills, it is necessary to learn, practice, and apply various types of clinical reasoning techniques [14]. Additionally, effective teaching methods and improvements in both theoretical and practical education are required [3]. For effective clinical reasoning education, identifying the shortcomings of current educational methods should be prioritized. Therefore, this study aims to analyze case reports written by students during clinical practice, identify issues within the nursing process, and provide foundational data for the development of effective teaching strategies.

Materials and Methods

Study design

This study employed a qualitative research method using document analysis [15] to propose teaching-learning methods and improvements in clinical practice guidance aimed at enhancing the clinical reasoning abilities of nursing students. Specifically, the study analyzed case reports submitted by students during clinical practice. Document analysis has been utilized in various studies, such as analyzing nursing curricula related to EBP [16] and examining perspectives on health integrated into care plans based on NANDA-I diagnoses concerning individuals with bipolar disorder [17]. Document analysis is a systematic procedure for reviewing or evaluating documents, and in this study, the READ approach was used to systematically analyze the case reports [18]. This research was conducted after obtaining approval from the IRB of Nambu University (1041478-2022-HR-010).

Materials

The subjects who submitted case reports for this study were thirdyear students from a nursing college located in the southern region of South Korea. The participants were intentionally sampled, as they were all guided by the same full-time faculty member responsible for the clinical practice course. These students had completed courses on critical thinking, the nursing process, and basic nursing practice in the skills lab during their second year, and they began clinical practice in the first semester of their third year. At the time of the study, the students had completed one or two clinical practice courses. Each student participated in a total of 90 hours of clinical practice over two weeks. The case reports, submitted before a group discussion held during the second week of practice, primarily focused on patients who had undergone joint replacement surgery at a specialized joint center. The reports involved applying the nursing process to these surgical cases. To maintain confidentiality, personal information was removed from the case reports, and the file names were replaced with serial numbers. Reports that did not include data related to nursing diagnoses were excluded from the analysis. Of the 27 submitted reports, one was unusable due to file corruption, and four were excluded because they lacked objective and subjective data.

Consequently, 22 reports were included in the final analysis.

Extract data

The researcher developed and utilized a data extraction form using an Excel spreadsheet. The extracted data included Operation Name (OP), Post-Operative Day (POD), number of nursing diagnoses, names of nursing diagnoses, related/risk factors, and defining characteristics (subjective and objective data). For subjective data, the researcher copied and organized the exact sentences written by the students, while the objective data were organized in the order presented by the students. Data extraction was conducted by the researcher, and all information was used as described by the students without modification.

Analyze data

Quantitative and qualitative analyses were conducted using the extracted data. For the general characteristics of the collected data, a frequency analysis was performed on the types of surgery, post-operative days (POD), and the number of nursing diagnoses. The extracted nursing diagnoses were categorized into domains and classes based on the NANDA-I classifications [9], followed by a frequency analysis. Additionally, the nursing diagnoses were classified as problem-focused, risk, or health promotion, and a frequency analysis was performed to identify the types of diagnoses used by students.

To evaluate whether the nursing diagnoses made by students were based on appropriate nursing assessment data, a panel was formed, consisting of the researcher responsible for clinical practice guidance, two professors teaching nursing process courses, and one professor responsible for adult nursing theory courses related to joint replacement surgery. The panel used the data extraction form to discuss the appropriateness of the related/risk factors and defining characteristics for each nursing diagnosis. The panel first reviewed the diagnosis definitions and diagnostic indicators provided by NANDA-I for each extracted nursing diagnosis and conducted discussions in sequential order based on serial numbers. They assessed the appropriateness of the nursing diagnoses, related/risk factors, and defining characteristics by categorizing them as “Yes” or “No.” For diagnoses evaluated as “No,” the panel discussed the reasons, and the researcher documented the discussions in the data extraction form. After completing the evaluation, the researcher summarized the discussion outcomes and shared them with the panel to ensure the accuracy of the interpretation.

Distil Findings

Quantitative analysis data were presented narratively or in tables, while qualitative data were categorized based on the issues identified in the nursing diagnosis process during the panel discussions. To enhance the readers’ understanding, relevant examples were provided alongside the categorized findings from the case reports.

Results

Results of quantitative analysis

General characteristics of case reports

Among the collected case reports, 15 cases (68.2%) involved total knee arthroplasty (TKA), and 7 cases (31.8%) involved Total Hip Arthroplasty (THA). The most frequent Post-Operative Day (POD) was the 3^rd day with 5 cases (22.7%), followed by the 1^st and 2^nd days with 4 cases each (18.2%). The 5^th and 6^th days had 3 cases each (13.6%), while the 4^th, 7^th, and 10^th days each had 1 case (4.5%). In terms of the number of nursing diagnoses, 3 diagnoses were the most common, occurring in 14 cases (63.6%), while 4 and 5 diagnoses appeared in 4 cases each (18.2%).

Characteristics of extracted nursing diagnosis

A total of 16 unique nursing diagnoses were extracted from the 22 case reports (Table 1). Of these, 9 diagnoses (56.3%) were problem-focused, while 7 diagnoses (43.8%) were risk-focused. The most frequently diagnosed condition was acute pain, identified in 22 cases (95.7%). This was followed by risk for infection in 16 cases (69.6%) and risk for adult falls in 15 cases (65.2%).

Results of qualitative analysis

Issues related assessment

Most students demonstrated a lack of clear understanding of the definitions of diagnostic indicators, such as defining characteristics, related factors, or risk factors, often confusing them with associated conditions. Additionally, many students presented defining characteristics (DCs) when diagnosing riskbased conditions, indicating a misunderstanding that risk nursing diagnoses require risk factors, while problem-focused diagnoses require defining characteristics and related factors. Some students also appeared to confuse subjective and objective data when identifying DCs.

There were frequent instances where important information, such as pain assessment (#16) or surgical site assessment (#1,5), was missing during the nursing assessment. Students often presented only vital signs and lab results as objective data (#1,5), neglecting other critical assessment details. In some cases, additional assessment was necessary to arrive at a more accurate diagnosis, but these opportunities were missed (#22). Students were also uncertain whether to classify elevated body temperature as a defining characteristic or as a nursing diagnosis itself (#1,5). There were also instances of students including irrelevant information indiscriminately in their assessments (#13) (Table 2).

Issues related to diagnosing

There were cases where the nursing diagnoses did not align with the defining characteristics (#3, #16). Students also tended to choose broad diagnoses (e.g., Risk for infection) rather than more specific diagnoses (e.g., Risk for surgical site infection) (#18) (Table2).

Table 2: Examples of nursing diagnosis based on assessment data.