Background
A nurse’s clinical decision-making is a goal-oriented judgment process and the core ability of the nursing practice to identify a patient’s problem based on theoretical knowledge and clinical experience, create a list of problems in order of priority, and select appropriate intervention and treatment alternatives [1]. Unlike nurses in foreign hospitals, nurses in Korean hospitals have limited autonomy and authority to perform all activities for clinical practice within the scope set by the Medical Service Act [2]. The vertical decision-making culture and one-way passive communication style of Korean hospitals hinder hospital nurses’ complex clinical decision-making [3, 4]. For hospital nurses to make effective decisions, they need the ability to solve problems through judgment based on clinical knowledge and experience and make clinical decisions by utilizing available human and physical resources [1, 2, 5].
While the importance of decision-making ability is increasing in clinical practice, previous studies on the clinical decision-making ability of hospital nurses only focus on and evaluate the passive aspect of nurses recognizing problems, collecting data, and clarifying them [6]. It fails to properly reflect the changed judgment process of nurses in changed clinical settings [5]. Hospital nurses performing clinical practice have many factors to consider to solve problems and are exposed to emergencies that suddenly occur [7]. Thus, they must flexibly apply their personal intuition and analytical thinking depending on the situation. In addition, they need to have clinical decision-making skills to solve problems through communication and cooperation with colleagues and related departments performing the same work [8]. The clinical decision-making ability measurement tools currently in use were constructed for the purpose of development to compare and evaluate changes in decision-making ability of nursing students before and after clinical practice, or were developed for nurses, but due to cultural differences, some of the items in the tool were eliminated during the translation process and were used in an incomplete state [7, 9, 10]. In addition, in the case of simply translating and using a clinical decision-making ability measurement tool developed abroad, there was a problem in that the question was extracted or measured with low validity and reliability unlike the original tool during the translation process due to changes in the meaning of words or cultural differences [6, 7]. Therefore, it is important to develop questions by reflecting the demands and reality of the field for clinical decision-making ability perceived by domestic hospital nurses and to develop tools with high validity and reliability that can be measured objectively through expert verification [10].
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To measure the clinical decision-making ability of hospital nurses, the suggested alternative is to use an instrument to evaluate the strengths and complements that appear in the clinical judgment process and then apply the results to practice [9]. On the other hand, the measurement instruments currently in use do not reflect the ability of hospital nurses to use human and physical resources in the actual clinical decision-making, evaluation of results, and methods of acquiring changed knowledge [9, 10]. If an instrument to measure clinical decision-making ability developed overseas is simply translated and used, the meanings of words may change during translation, items may be extracted differently from the original instrument due to cultural differences, or problems may arise where validity and reliability are measured low [10, 11]. It is essential to develop items that reflect the practical needs and reality of clinical decision-making ability as perceived by domestic hospital nurses and create an instrument with high validity and reliability that can be objectively measured through expert verification [9].
The Korean clinical decision-making ability scale for hospital nurses was developed into items by analyzing the attributes based on meaningful statements derived through in-depth interviews about the difficulties and expectations that Korean hospital nurses feel while making decisions in actual clinical settings. Through this, the factors necessary for Korean hospital nurses to make decisions with autonomy and independence in a limited decision-making culture different from that of other countries were identified and developed into items.
Therefore, in this study, with the model on the clinical decision-making ability of nurses [12] as the theoretical basis, we developed a Korean clinical decision-making ability scale for hospital nurses to measure thoughts and attitudes of Korean hospital nurses based on factors affecting the various decision-making abilities of nurses in Korean hospitals. Actively using the measurement instrument proposed in this study in research related to the clinical decision-making ability of hospital nurses would utilize the results as fundamental data for strategizing to improve nursing practice and job satisfaction of hospital nurses and foster professional talent with autonomous authority and responsibility. Furthermore, by helping to develop nursing education materials and programs to improve the clinical decision-making ability of hospital nurses, we intend to reduce role conflict through job satisfaction and contribute to nurturing competent, skilled nurses with clinical decision-making ability.
The purpose of this study was to identify the factors that make up the clinical decision-making ability of hospital nurses and to develop a measurement tool that represents each component. The specific goals were to (1) Develop a scale to measure the clinical decision-making ability of hospital nurses; (2) Verify the reliability and validity of the developed clinical decision-making ability scale for hospital nurses.
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Methods
Study design
This study was a methodological study that develops a scale to measure the clinical decision-making ability of hospital nurses and then tests the reliability and validity of the developed scale.
Instrument development process
This study was conducted in the scale development and validation testing stages based on the scale development procedure of DeVellis [13]. Among the scale development methods, DeVellis (2016) consists of a total of 8 stages, a conceptual analysis of the clinical decision-making ability of hospital nurses in the first stage was conducted, and preliminary questions were created based on the attributes derived through the conceptual analysis in the second stage. The scale of the 3-step tool was corrected, and the 4-step expert content validity was verified. A preliminary survey was conducted on 20 hospital nurses in the 5th stage. A questionnaire survey was conducted on 371 hospital nurses with modified tools in the 6th and 7th stages. The tool was completed by selecting the final question of step 8.
Conceptual framework
Before developing a preliminary instrument, this study confirmed the attributes and components of the concept through a review of previous literature on the clinical decision-making ability of hospital nurses. Based on a review of concept analysis research on nurses’ clinical decision-making ability [2], instrument development research [10, 11, 14], and previous research on nurses’ clinical decision-making ability [1, 5, 15], hospital nurses’ clinical decision-making ability was defined as circular decision-making that reflects the nurse’s philosophy and values to interpret the meaning of the patient’s health problem discovered based on the nurse’s clinical judgment, provide nursing intervention, and then evaluate the outcomes.
The factors were composed of the four attributes of nurses’ clinical decision-making process suggested by Tanner [12] in the ‘clinical judgment model’: ‘noticing,’ ‘interpreting,’ ‘responding,’ and ‘reflecting.’ ‘Noticing’ includes expectations about the situation acquired from the nurse’s theoretical knowledge and clinical experience, which involves paying attention to abnormal situations that occur in patients. ‘Interpreting’ is a systematic approach based on evidence in which nurses collect data to determine the priority of problems occurring in patients and determine appropriate nursing plans and interventions. ‘Responding’ means applying the nursing actions planned by the nurse to actual patients and performing necessary treatment through a skilled and standardized approach. ‘Reflecting’ refers to evaluating the outcomes of nursing interventions performed on patients according to procedures and reflecting on what has been learned through nursing activities. In this study, each attribute of clinical decision-making ability obtained through a literature review and interviews with hospital nurses was modified into easy-to-understand terms. ‘Noticing’ was named ‘understanding the context’ and ‘recognizing problems’; ‘Interpreting’ was named ‘integration’; ‘Responding’ was named ‘selecting and applying alternatives,’ and ‘Reflecting’ was named ‘outcome evaluation.’ Additionally, this study completed the factors of the clinical decision-making ability of hospital nurses by adding the attribute of ‘resource utilization,’ which was not considered important in previous studies.
Development of a preliminary instrument
Based on a conceptual framework completed through a literature review and in-depth interviews with hospital nurses, 71 preliminary items were extracted. The questions used in the in-depth interviews with nurses to construct preliminary items started with a casual conversation, such as ‘Are there any patients you have cared for recently that left an impression on you?’ followed by ‘What problems did you think the patient had,’ ‘What did you do to identify the patient’s health problem,’ ‘Were there any expected outcomes or expectations related to the health problem,’ ‘How do you decide on priorities for the nursing plan for the patient,’ ‘What influences your decision on how to behave when making inferences from the data collected,’ ‘What role does your clinical knowledge or experience play in the nursing performance process,’ ‘Did the treatment outcomes match what was initially expected,’ and ‘What aspects of the outcomes of your nursing practice do you focus on when thinking back,’ The collected interview contents were classified into five factors of the clinical decision-making ability of hospital nurses through direct transcription, grouping of similar contents, and deleting duplicate contents from the literature reviewed. As a result, 71 preliminary items were prepared, consisting of 17 items on ‘recognizing,’ 13 items on ‘integration,’ 20 items on ‘selecting and applying alternatives,’ 14 items on ‘resource utilization,’ and seven items on ‘outcome evaluation.’
In the next step, content validity for preliminary items was verified by a total of 10 people, including two experts with experience in instrument development and eight nurses with more than seven years of clinical experience. The content validity of the preliminary items was measured using a four-point Likert scale. The contents of the preliminary items were scored and the content validity index (CVI) was calculated. After calculating the content validity index of experts, 18 items, including those with a CVI of lower than 0.80, items with overlapping meaning or not reflecting attributes, and ambiguous sentences, were deleted, and 28 items were revised and supplemented by gathering expert opinions. As a result, 51 items were prepared.
The finalized preliminary instrument consisted of 51 items, including 10 items on ‘recognizing,’ 10 items on ‘integration,’ 16 items on ‘selecting and applying alternatives,’ nine items on ‘resource utilization,’ and 6 items on ‘outcome evaluation,’ A five-point Likert scale (one point: strongly disagree ~ five points: strongly agree) was employed, considering the convenience and sensitivity of the response, with higher scores indicating higher clinical decision-making ability.
Evaluation of the final instrument
Subjects and data collection
To verify the reliability and validity of the preliminary instrument, a survey was conducted from January to April 2022. The subjects were nurses who completed a three-month basic clinical practical training course after joining a tertiary general hospital in Seoul and engaged in nursing work. They were those who made clinical judgments for patients and provided direct nursing care. Due to the nature of the hospital’s work, nurses with less than three months of clinical experience were excluded from the study along with operating room nurses who did not make decisions, since they had difficulty making independent clinical decisions during the probationary period to learn hospital work. In addition, in this study, nurses who had no experience in similar research related to clinical decision-making ability during the survey period and who were able to communicate to answer the questionnaire were finally selected.
At the time of this study, the work fatigue of hospital nurses was increased due to the influence of the COVID-19 pandemic. According to hospital policy, the researcher could not arbitrarily extract the subjects of exploratory and confirmatory factor analysis. After sufficient consultation with the statistical scholar of this study in consideration of the preceding literature, the survey subjects were randomly extracted from all hospital nurses.
Data were collected from 380 nurses, considering a dropout rate of 20% according to the evidence [16] that the absolute sample size is at least 300 people for stable instrument analysis, such as factor analysis or correlation between items. Excluding nine copies with missing data for some items, a total of 371 copies without missing values were finally retrieved and analyzed.
Verification of validity and reliability
The collected data were analyzed for validity and reliability using IBM SPSS/WIN 23.0 and AMOS/WIN 24.0 (IBM Inc. Armonk, NY, USA) programs. The sociodemographic and occupational characteristics of the study participants were presented as frequencies, percentages, means, and standard deviations. Items were analyzed using descriptive statistics and Pearson’s correlation, and construct validity was verified using exploratory and confirmatory factor analysis. Exploratory factor analysis used the principal axis factor method to extract a meaningful structure that many items have in common and Varimax rotation among the orthogonal rotation methods to improve the ease of interpreting the factor structure. To determine whether the collected data were suitable for factor analysis, KMO (Kaiser-Meyer-Olkin) and Bartlett test (Bartlett’s test of sphericity) were performed. To select items that could well express the meaning of each factor, items with a communality of 0.30 or higher and a factor loading of 0.50 or higher were selected [17], and the eigen values of the factors of 1.0 or higher were extracted. In confirmatory factor analysis, for the goodness-of-fit index, x² statistic (p value), standardized x² (Chisquare minimum/degree of freedom [CMIN/DF]), basic fit index (Goodness of Fit Index [GF]), standardized root mean square residual (SRMR), root mean square error of approximation (RMSEA), Tucker-Lewis index (TLI), and comparative fit index (CFI) were evaluated [18]. The construct validity of this instrument was verified by the convergent validity and discriminant validity of the items. Convergent validity was evaluated using standardized factor loadings, criticak ratio (C.R.), average variance extracted (AVE), and construct reliability (CR). Discriminant validity was evaluated by the difference between the square value of the correlation coefficient and the AVE value.
To verify criterion validity, the correlation with the scores of the clinical decision-making ability scale developed by Jenkins [10] and translated by Baek [19] was analyzed using Pearson’s correlation. A nurse’s clinical decision-making ability can be seen as a series of decision-making processes that recognize a patient’s problem, select an alternative, and evaluate the outcomes of the applied intervention, and is in the same context as clinical judgment [17].
The clinical decision-making ability scale for nurse measures nurses’ clinical judgment ability and comprises 51 items asking about understanding the context, integration, selecting and applying alternatives, resource utilization, and outcome evaluation. This instrument uses a five-point Likert scale (one point: strongly disagree ~ five points: strongly agree), with higher scores indicating higher clinical decision-making ability. The reliability was Cronbach’s α = 0.83 in Jenkins’ study and 0.71 in this study.
The reliability of the clinical decision-making ability scale for hospital nurses was evaluated by the correlation coefficient between the total scores of the items (corrected Item Total Correlation [ITC]) and Cronbach’s α value, which is the internal consistency coefficient.
Ethical considerations
This study was conducted after receiving approval from the Institutional Review Board of a Hospital in Seoul (IRB No. 3-2021-0025, Approved date: December 12, 2021). The researcher explained the background, purpose, participation method of the study, in-depth interviews, and preliminary/main surveys to develop preliminary questions, and interviewed and collected data only from those who gave written consent. All collected data were coded and quoted anonymously to prevent personal information from being revealed.
Results
Characteristics of study participants
A total of 371 nurses participated in the survey to verify the reliability and validity of the preliminary instrument for measuring the clinical decision-making ability of hospital nurses, of which 89.8% were women and 10.2% were men. The average age was 33.52 ± 8.56 years, with the largest age group being 25 to 30 years old. As for the highest level of education, most respondents were four-year college graduates at 77.1%, and the most common position was general nurse (86.5%). As for the working department, the intensive care unit accounted for 20.8%, followed by the internal medicine ward at 18.9%, the emergency room at 15.6%, and the outpatient clinic at 14.8%. Clinical experience was found to be an average of 9.34 ± 8.51 years (Table 1), and the average working years at the current department was 4.84 ± 5.04 years, with seven months to five years being the most common at 53.9%. The average number of patients to care for during work was 18.77 ± 38.81, with 10 or lower being the most common at 62.3%, and the time spent directly caring for patients was 5.90 ± 2.59 h on average, with five to seven hours being the most common at 46.1%. The average number of decisions made during work was 17 times, with 6 to 10 times being the most common at 34.2%, and the most common level of difficulty in decision-making was medium at 69.5% (Table 2).
Table 1
General characteristics of study participants
Characteristics | Frequency | Percentage | Mean (SD) |
|---|---|---|---|
Gender | |||
Female | 333 | 89.8 | |
Male | 38 | 10.2 | |
Ages (year) | 33.52 (8.56) | ||
≤ 24 | 47 | 12.7 | |
25–30 | 128 | 34.5 | |
31–35 | 60 | 16.2 | |
36–40 | 52 | 14 | |
41–45 | 40 | 10.8 | |
≥ 46 | 44 | 11.9 | |
Marital status | |||
Single | 229 | 61.7 | |
Married | 142 | 38.3 | |
Educational level | |||
College | 32 | 8.6 | |
University | 286 | 77.1 | |
Graduate school | 53 | 14.3 | |
Working department | |||
Internal medicine | 70 | 18.9 | |
Surgical medicine | 46 | 12.4 | |
Pediatrics | 15 | 4 | |
Outpatient | 55 | 14.8 | |
Intensive care unit | 77 | 20.8 | |
Emergency room | 58 | 15.6 | |
Other | 50 | 13.5 | |
Position | |||
Staff nurse | 321 | 86.5 | |
Charge nurse | 43 | 11.6 | |
Head nurse | 7 | 1.9 | |
Religion | |||
Protestant | 99 | 26.7 | |
Catholic | 56 | 15.1 | |
Buddhism | 20 | 5.4 | |
None | 193 | 52 | |
Other | 3 | 0.8 | |
Total career (year) | |||
≤ 6 months | 16 | 4.3 | 9.34 (8.51) |
7 months-2 | 64 | 17.3 | |
3-5 | 69 | 18.6 | |
6-10 | 75 | 20.2 | |
11-15 | 55 | 14.8 | |
16–20 | 42 | 11.3 | |
≥ 21 | 50 | 13.5 |
Table 2
Characteristics related to clinical decision-making of study participants
Characteristics | Frequency | Percentage | Mean (SD) |
|---|---|---|---|
Current department experience (year) | 4.84 (5.04) | ||
≤ 6 months | 43 | 11.6 | |
7 months-2 | 110 | 29.6 | |
3-5 | 90 | 24.3 | |
6-8 | 48 | 12.9 | |
9-11 | 39 | 10.5 | |
12-14 | 17 | 4.6 | |
≥ 15 | 24 | 6.5 | |
Work type | |||
3 shifts | 257 | 69.3 | |
2 shifts | 18 | 4.9 | |
Nine to five | 90 | 24.3 | |
Others | 6 | 1.6 | |
Number of patients per nurse (person) | 18.77 (38.81) | ||
≤ 10 | 231 | 62.3 | |
11-20 | 82 | 22.1 | |
21–30 | 13 | 3.5 | |
31–40 | 12 | 3.2 | |
41–50 | 7 | 1.9 | |
≥ 51 | 26 | 7 | |
Direct care time (hour) | 5.90 (2.59) | ||
≤ 1 | 30 | 8.1 | |
2-4 | 67 | 18.1 | |
5-7 | 171 | 46.1 | |
≥ 8 | 103 | 27.8 | |
Number of decisions per day (time) | 17.62 (24.16) | ||
≤ 5 | 83 | 22.4 | |
6-10 | 127 | 34.2 | |
11-15 | 18 | 4.9 | |
16–20 | 77 | 20.8 | |
21–25 | 9 | 2.4 | |
≥ 26 | 57 | 15.4 | |
Decision difficulty | |||
High | 60 | 16.2 | |
Moderate | 258 | 69.5 | |
Low | 52 | 14 | |
Other | 1 | 0.3 |
Item analysis
Among the 51 items of the selected preliminary instrument, the mean, standard deviation, skewness and kurtosis of each item, and the correlation between an item and total items were analyzed to remove items that impeded discrimination and reliability. After the analysis, items with extreme average scores (< 2 points or ≥ 4 points) were excluded. In the case of skewness and kurtosis, normality was satisfied with ± 3 or lower in all items. Additionally, the correlation coefficient between an item and total items ranged from 0.70 to 0.41, and there were no items with a correlation coefficient of 0.30 or lower.
Validity of the instrument
Construct validity
Exploratory factor analysis
An exploratory factor analysis was conducted on 51 items whose discrimination and reliability were confirmed through item analysis. Before performing factor analysis, KMO and Bartlett’s test of sphericity was performed to confirm whether the collected data were suitable for analysis. As a result of data analysis, the KMO value was 0.88, showing that the sample size was suitable for factor analysis, and Bartlett’s sphericity test result was Χ² = 6824.09 (p < 0.001), satisfying the conditions for exploratory factor analysis [17]. The principal axis method was used for factor extraction, and the factor rotation was analyzed using the Varimax method among orthogonal rotations. As a result, the number of factors with eigenvalues ≥ 1.0 was 10, and the number of factors in the drastically smooth part of the scree plot was also confirmed to be 10 (Fig. 1).
Fig. 1
Scree plot
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In order to select items that could well represent the meaning of each factor, items with a commonality of 0.30 or more and a factor loading of 0.50 or more were selected. By repeatedly checking the commonality and factor loading, items that were inappropriate for the above conditions were deleted several times, and a total of 12 items were deleted, 6, 10, 13, 14, 15, 16, 21, 24, 35, 36, 44, and 45 before the final item was confirmed, and as a result of double-checking the commonality and factor loading in 6 factors and 41 items, there were no more items to be deleted (Table 3).
Table 3
Exploratory factor analysis
Item | Factor | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | |
4 | 0.642 | 0.006 | 0.073 | 0.203 | 0.334 | 0.153 | 0.136 | -0.028 | -0.041 | 0.126 |
5 | 0.788 | 0.070 | -0.018 | 0.124 | 0.138 | 0.151 | 0.071 | 0.028 | -0.041 | 0.126 |
7 | 0.666 | 0.033 | 0.048 | 0.248 | 0.211 | 0.147 | 0.041 | 0.036 | -0.052 | 0.085 |
8 | 0.756 | 0.176 | 0.142 | 0.085 | 0.012 | -0.079 | -0.096 | 0.065 | 0.037 | 0.120 |
9 | 0.627 | 0.290 | 0.199 | 0.126 | 0.063 | 0.037 | 0.035 | 0.201 | 0.173 | -0.016 |
11 | 0.650 | 0.097 | 0.087 | 0.164 | 0.175 | 0.118 | 0.228 | 0.021 | 0.080 | -0.084 |
12 | 0.648 | 0.139 | 0.127 | 0.130 | 0.242 | 0.227 | 0.264 | 0.040 | 0.034 | -0.050 |
46 | -0.034 | 0.653 | 0.200 | 0.210 | 0.254 | 0.026 | -0.170 | -0.150 | 0.020 | 0.185 |
47 | 0.038 | 0.701 | 0.206 | 0.179 | 0.179 | 0.155 | 0.044 | 0.126 | 0.020 | 0.047 |
48 | 0.172 | 0.774 | 0.155 | 0.118 | 0.061 | 0.078 | 0.172 | -0.075 | -0.037 | -0.019 |
49 | 0.218 | 0.695 | 0.189 | 0.121 | -0.010 | 0.079 | 0.122 | -0.011 | -0.028 | -0.022 |
50 | 0.172 | 0.774 | 0.291 | 0.106 | 0.138 | 0.035 | -0.033 | 0.136 | 0.040 | 0.066 |
51 | 0.240 | 0.657 | 0.256 | 0.046 | 0.119 | 0.017 | 0.158 | -0.036 | 0.011 | 0.066 |
37 | -0.022 | 0.090 | 0.591 | 0.396 | 0.182 | 0.075 | 0.198 | -0.061 | 0.095 | -0.046 |
38 | 0.005 | 0.172 | 0.658 | 0.234 | 0.145 | 0.040 | 0.197 | 0.023 | 0.020 | 0.030 |
39 | 0.148 | 0.238 | 0.669 | -0.049 | 0.106 | 0.017 | 0.024 | 0.151 | -0.013 | -0.110 |
40 | 0.134 | 0.186 | 0.665 | -0.006 | 0.058 | 0.012 | -0.083 | 0.066 | 0.130 | 0.008 |
41 | 0.145 | 0.171 | 0.717 | -0.161 | 0.044 | -0.013 | 0.052 | 0.028 | 0.031 | 0.007 |
42 | -0.022 | 0.144 | 0.653 | 0.206 | 0.010 | 0.146 | -0.024 | -0.174 | -0.031 | 0.224 |
43 | 0.075 | 0.282 | 0.540 | 0.073 | -0.009 | 0.107 | -0.190 | -0.219 | -0.044 | 0.132 |
17 | 0.301 | 0.218 | 0.060 | 0.740 | 0.185 | 0.049 | 0.176 | 0.057 | -0.034 | 0.123 |
18 | 0.310 | 0.170 | 0.018 | 0.771 | 0.136 | 0.035 | 0.117 | -0.011 | -0.003 | 0.156 |
19 | 0.366 | 0.196 | 0.236 | 0.502 | -0.016 | -0.077 | 0.009 | 0.291 | 0.054 | -0.061 |
20 | 0.333 | 0.308 | 0.116 | 0.655 | 0.010 | 0.028 | 0.054 | 0.086 | 0.097 | -0.028 |
1 | 0.318 | 0.220 | 0.172 | 0.226 | 0.661 | 0.052 | -0.025 | 0.074 | -0.011 | 0.065 |
2 | 0.323 | 0.208 | 0.181 | 0.106 | 0.791 | 0.038 | 0.006 | 0.095 | 0.024 | -0.043 |
3 | 0.389 | 0.239 | 0.121 | 0.004 | 0.773 | 0.112 | 0.064 | 0.092 | 0.076 | -0.017 |
32 | 0.139 | 0.106 | 0.116 | -0.098 | -0.096 | 0.690 | 0.193 | 0.168 | -0.118 | -0.212 |
33 | 0.189 | 0.113 | 0.001 | 0.022 | 0.089 | 0.806 | -0.058 | 0.160 | 0.144 | 0.018 |
34 | 0.166 | 0.144 | 0.185 | 0.168 | 0.217 | 0.678 | 0.193 | 0.168 | -0.118 | -0.212 |
27 | 0.131 | 0.104 | 0.114 | 0.184 | 0.030 | 0.040 | 0.711 | 0.092 | 0.079 | 0.304 |
28 | 0.118 | 0.121 | 0.048 | 0.105 | 0.047 | 0.041 | 0.790 | 0.104 | 0.117 | 0.166 |
22 | 0.082 | -0.015 | -0.042 | 0.070 | 0.061 | 0.119 | 0.146 | 0.838 | -0.061 | 0.057 |
23 | 0.135 | 0.077 | -0.033 | 0.079 | 0.143 | 0.163 | 0.036 | 0.715 | -0.073 | 0.345 |
29 | 0.071 | 0.026 | -0.028 | -0.063 | 0.035 | 0.004 | 0.298 | 0.130 | 0.720 | 0.011 |
30 | 0.037 | -0.109 | 0.106 | -0.044 | -0.070 | 0.057 | 0.112 | -0.131 | 0.710 | 0.116 |
31 | -0.029 | 0.096 | 0.044 | 0.187 | 0.100 | -0.076 | -0.192 | -0.092 | 0.691 | 0.094 |
25 | 0.154 | 0.035 | 0.050 | 0.011 | -0.010 | 0.057 | 0.237 | 0.114 | 0.183 | 0.734 |
26 | 0.112 | 0.188 | 0.101 | 0.150 | -0.005 | 0.087 | 0.265 | 0.281 | 0.110 | 0.662 |
Facial validity was conducted on 20 hospital nurses with preliminary questions of the measurement tool developed prior to this survey. On a Likert 4-point scale, the scores were scored with 4 points for ‘appropriate’, 3 points for ‘appropriate but slightly modified’, 3 points for ‘not being able to evaluate appropriateness’, and 1 point for ‘not appropriate at all’. After filling out the questionnaire to the subjects who responded to the preliminary question, the questions were revised and supplemented by listening to their opinions.
As a result of exploratory factor analysis, the factor loadings of total items were 0.50 or higher, nine factors accounted for 65.5% of the total variance, and a 51-item instrument for measuring the clinical decision-making ability of hospital nurses was finalized. Based on the factors derived through exploratory factor analysis, they were named as a concept that can imply the contents of items of each factor. Factors 1 and 2 were items related to noticing in the conceptual framework and were named ‘understanding the context’ and ‘recognizing problems,’ and factor 3 was a set of items related to interpreting and was named ‘prioritization of problems.’ Factors 4 to 8 were related to responding and were named ‘confidence,’ ‘intuition,’ ‘coping,’ ‘compromise,’ and ‘resource utilization,’ and factor 9 was related to reflecting and was named ‘outcome evaluation’ (Table 4).
Table 4
Convergent and discriminant validity of measurement tools
Factors | Items | Standardized estimate | SE | CR | AVE | Discriminant validity |
|---|---|---|---|---|---|---|
Understanding the context | 1 2 3 | 0.745 0.898 0.867 | 0.169 0.101 0.152 | 0.937 | 0.834 | 0.913 |
Recognizing problems | 4 5 7 8 9 11 12 | 0.731 0.745 0.722 0.651 0.663 0.758 0.676 | 0.277 0.273 0.236 0.220 0.276 0.214 0.240 | 0.934 | 0.669 | 0.818 |
Prioritization of problems | 17 18 19 20 | 0.913 0.885 0.541 0.658 | 0.067 0.095 0.330 0.202 | 0.928 | 0.771 | 0.878 |
Confidence | 22 23 | 0.656 0.903 | 0.583 0.148 | 0.769 | 0.630 | 0.794 |
Intuition | 25 26 | 0.629 0.832 | 0.260 0.153 | 0.838 | 0.725 | 0.815 |
Coping | 27 28 | 0.848 0.723 | 0.136 0.238 | 0.868 | 0.769 | 0.877 |
Compromise | 32 33 34 | 0.523 0.769 0.676 | 0.862 0.348 0.347 | 0.713 | 0.459 | 0.678 |
Resource utilization | 37 38 39 40 41 42 43 | 0.571 0.658 0.674 0.640 0.640 0.577 0.536 | 0.376 0.267 0.327 0.376 0.366 0.344 0.344 | 0.885 | 0.525 | 0.725 |
Outcome evaluation | 46 47 48 49 50 51 | 0.744 0.797 0.829 0.591 0.624 0.612 | 0.240 0.187 0.179 0.357 0.238 0.282 | 0.922 | 0.668 | 0.818 |
Confirmatory factor analysis
Confirmatory factor analysis was conducted on nine factors and 51 items. By examining the C.R. of non-standardized lambda, items with a reference value of 1.96 (p < 0.05) or lower were deleted, and items with a standardized lambda of 0.5 or lower were deleted to check the model fit [20]. After confirmatory factor analysis, the revised model consisted of nine factors and 51 items, and the model fit indices were χ² = 1071.677 (p > 0.05), χ²/df = 1.949, GFI = 0.863, RMR = 0.032, CFI = 0.916, and TLI = 0.903, so all model fit indices met the recommended levels (Table 5).
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Table 5
Model fit of confirmatory factor analysis
χ² | DF | χ²/df | RMR | GFI | AGFI | CFI | TLI |
|---|---|---|---|---|---|---|---|
p > 0.05 | < 3 | ≤ 0.05 | ≥ 0.800 | ≥ 0.800 | ≥ 0.800 | ≥ 0.800 | |
1071.677 | 116 | 1.949 | 0.032 | 0.863 | 0.834 | 0.916 | 0.903 |
To verify the construct validity of this instrument, the convergent validity and discriminant validity of the items were examined. Convergent validity, which checks whether the observed variables consistently measure the construct, was confirmed by the average variance extracted (AVE) and construct reliability (CR). The critical ratio (C.R.) was set at 1.96 or higher, AVE at 0.50 or higher, and CR at 0.70 or higher.
As a result of evaluating the convergent validity using the average variance extracted (AVE) and construct reliability (CR), the AVE value was 0.459 to 0.834, which was above 0.50, and the CR value was 0.713 to 0.937, which was above 0.70, indicating the model’s convergent validity. As a result of the analysis, the CR value of autonomy was 0.625 and the AVE value was 0.366, which were lower than the reference values and were deleted. The standardized factor coefficient values of the remaining nine factors and 36 items were 0.523 to 0.913, all above 0.50. The CR and AVE values were 0.713, which met the reference values, so the items were not removed. Discriminant validity to verify the independence between factors, and correlation coefficients and AVE were used. The squared value of the correlation coefficient between all latent variables in this study was r = 0.224 to r = 0.913, which was smaller than the AVE value, securing discriminant validity (Table 4).
Criterion validity
As a result of analyzing the correlation between this research instrument and Jenkins’ clinical decision-making ability scale to verify concurrent validity among criterion validity, the correlation coefficient was r = 0.70 (p < 0.001), showing a positive correlation. The Pearson correlation coefficient of the two scales was between 0.4 and 0.8, which is the reference, securing criterion validity [20].
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Reliability test
Through factor analysis, the reliability of the nine factors and 36 questions of the hospital nurse’s clinical decision-making ability measurement tool was verified. The correlation between the questions and total scores was 0.70 ~ 0.42, and all items were above the standard value of 0.30 [18]. The reliability of the entire tool was 0.84, and Cronbach’s α value for each factor was 0.84, and Cronbach’s α value for each factor was 0.87 for understanding the situation, 0.90 for problem identification, 4 questions for problem prioritization, 0.87 for problem prioritization, 0.62 for problem, 0.60 for intuition, 2 for coping, 0.72 for coping, 0.67 for compromise, 7 questions for resource utilization, and 6 questions for result evaluation (Table 6).
Table 6
Reliability of hospital nurses’ clinical decision-making ability measurement tools (N = 371)
factor | Number of questions | Cronbach’s α |
|---|---|---|
Understanding the situation | 3 | 0.87 |
Check the problem | 7 | 0.90 |
Problem Prioritization | 4 | 0.87 |
Confidence | 2 | 0.62 |
Intuitive power | 2 | 0.60 |
Thatcher | 2 | 0.72 |
Compromise | 3 | 0.67 |
resource utilization | 7 | 0.82 |
Evaluation of results | 6 | 0.87 |
Total score | 36 | 0.84 |
Discussion
To develop an instrument to measure the clinical decision-making ability of Korean hospital nurses, this study constructed preliminary items through a literature review and in-depth interviews and then examined content validity. The developed instrument consisted of nine factors and 36 items, including recognizing problems, integration, selecting alternatives and coping, resource utilization, and outcome evaluation.
Factor 1, ‘understanding the context,’ refers to hospital nurses providing clinical judgment and high-quality nursing care by recognizing the abnormal state of problems occurring to patients in complex clinical situations [9, 21]. It involves the effort of hospital nurses to find the cause of problems occurring to patients. Moon and Kim [22] mentioned that less clinical practice experience can worsen problems due to a lack of observation and understanding of abnormal situations.
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Factor 2, ‘recognizing problems,’ is to predict the severity and progress of the disease by considering the situation in which the problem occurred. It includes items regarding ‘observation of changes in the patient’s condition,’ ‘guessing the cause through various possible situations,’ and ‘anticipating the progress of the disease’ based on the information obtained by the hospital nurse from the patient. This implies that hospital nurses recognize the urgency of the problem and evaluate the severity of the patient’s illness through their clinical experience [23].
Factor 3, ‘prioritization of problems,’ involves conducting a physical assessment and observation focusing on the patient’s symptoms, as inferred by the hospital nurse, and then determining the priority of the problem. The items include ‘Determine the priority of nursing problems according to the severity of the patient’s symptoms,’ ‘Reflect the patient’s needs when determining the priority of nursing problems,’ and ‘Solve this first as this problem is urgent for the patient.’ The preliminary items developed in this study reflected these characteristics, but the items were eliminated from the main survey. This means that hospital nurses identify the urgency of the problem through physical examination or observation in actual clinical settings and report it to the doctor in charge or superior. However, treatment plans and problem-priority decisions are made under the leadership of the doctor, so the importance of the items seems to have been evaluated somewhat low [23].
Factor 4, ‘confidence,’ includes ‘Even if a complex problem arises, I will solve it on my own without relying on colleagues’ and ‘I will confidently apply what I decided.’ Confidence gives hospital nurses a sense of competence and helps them make accurate clinical decisions [5, 24]. In this study, items regarding confidence developed as preliminary items were discarded. The cause of hospital nurses’ hesitation in making decisions is believed to be the psychological burden caused by responsibility for decision-making and results made by themselves.
Factor 5, ‘intuition,’ shows that the intuition of hospital nurses is formed through clinical practice experience based on theoretical knowledge and that methods used previously when caring for patients are first considered in selecting an alternative. On the other hand, when facing a problem for the first time, a cautious attitude was shown regardless of experience, and the more clinical experience one had, the more efforts were made to minimize negative outcomes [15, 25].
Factor 6, ‘coping,’ is to identify the cause of the patient’s problem and select a solution appropriate for the situation based on the results analysis [26]. Hospital nurses applied alternatives through active coping centered on problem-solving, considering the patient’s treatment goal and plan, and making efforts to minimize the occurrence of potential risks or negative outcomes.
Factor 7, ‘compromise,’ includes horizontal decision-making, compromise points in decision-making, and therapeutic communication with members. Hospital nurses are members of the treatment team in clinical settings and want to communicate on an equal footing with doctors and other colleagues. However, due to the nature of Korean hospital culture, one-sided communication between doctors or between doctors and nurses, arbitrary decision-making by doctors, and vertical interpersonal relationships interfered with nurses’ clinical decision-making [27]. Therefore, there is a need for a horizontal organizational culture and a change in the way of nursing unit communication where hospital nurses actively participate in decision-making related to patient treatment as clinical experts and can compromise and make decisions with members through the free exchange of opinions [22]. These changes are expected to affect the clinical decision-making ability of hospital nurses, increasing satisfaction with therapeutic decision-making and improving job ability.
Factor 8, ‘resource utilization,’ has something in common, compared with Jenkins’ instrument [10], which is currently in use, in that the nurse’s clinical decision-making ability through accurate clinical judgment is vital in problem-solving. However, this instrument added information or resource utilization part that was not covered in the Jenkins’ instrument [10]. Unlike the time when the existing instrument was developed, the ability of nurses currently performing clinical practice to solve problems by utilizing available information or physical resources was emphasized [4, 25]. In reality, hospital nurses often need help from doctors or related departments due to difficulties in solving problems independently. Therefore, the effective use of human and physical resources is an ability that nurses must have to efficiently solve discovered problems. This plays an important role in actual clinical settings as it is related to confidence and autonomy in problem-solving among clinical decision-making abilities of hospital nurses [4, 25]. Therefore, if they know and utilize the scope and method of available resources in clinical practice, it is believed that hospital nurses can improve their clinical decision-making ability as a main agent in problem-solving.
Factor 9, ‘outcome evaluation,’ is one of the most important parts that determine the job satisfaction of hospital nurses. After completing nursing, when the patient’s condition improves or a positive outcome is achieved, they have faith in their abilities and feel psychologically satisfied [5]. On the other hand, regardless of clinical experience, they feel psychologically discouraged when the treatment outcomes that occurred to patients do not match what they had initially expected, and they first look back on their critical thinking and nursing performance process [2].
Recently, nursing research on the clinical decision-making ability of hospital nurses has identified factors that improve decision-making capabilities in various environments and is considering aspects applicable to the actual field. In this regard, hospital nurses need tools in terms of measuring their interactions with the clinical environment. The results of this study can be used to measure and evaluate the decision-making ability of nurses who make and perform decisions on patients in hospitals, the use of surrounding resources, and interactions with fellow medical staff. In addition, it is significant in that it considered the hospital environment in measuring decision-making ability and reflected a unique decision-making culture that was more dependent on doctors’ decision-making than foreign countries in the decision-making process.
Based on the findings of this study, the Korean clinical decision-making ability scale for hospital nurses is an instrument that can measure various aspects as it well reflects the characteristics of the hospital nurse’s decision-making that were not reflected in the existing clinical decision-making ability scale. The results from this study can be utilized to develop decision-making ability improvement program for hospital nurses. Further research is needed experimental study on developing intervention or program for improving clinical decision-making ability of hospital nurses. Also, a comparative study before and after using it in situation-specific simulation training is needed.
Limitations
Because this study was conducted to develop a clinical decision-making scale targeting nurses at a tertiary general hospital in Seoul, there may be limitations in extending the interpretation to all hospital nurses. Additionally, the failure to take in-depth consideration of various characteristics and situations within the hospital may also be a limitation of the study.
Conclusions
This study developed an instrument based on the clinical judgment model presented by Tanner [12], considering the uniqueness of the clinical decision-making ability of Korean hospital nurses, and verified reliability and validity based on the factors identified through literature review and in-depth interviews with nurses. The developed Korean clinical decision-making ability scale for hospital nurses comprises nine factors and 36 items (Appendix). A five-point Likert scale is employed, with a total score ranging from a minimum of 36 to a maximum of 180. The higher the score, the better the clinical decision-making ability of Korean hospital nurses. It is expected to improve hospital nurses’ clinical decision-making ability and high-quality nursing practice ability.
Acknowledgements
Authors thank all the participants for their contributions to this study.
Declarations
Ethics approval and consent to participate
All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the Yonsei University Hospital Institutional Review Board (IRB No. 3-2021-0025, Approved date: December 12, 2021), and consent to participate was obtained using written informed consent from study participants all.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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