The clinical readiness of newly graduated nurses is crucial in meeting the growing demand for health services. Consequently, it is essential to develop a scale that accurately evaluates the clinical readiness of these novice nurses.
Aim
This study aimed to translate and psychometrically evaluate the Persian version of the Nursing Practice Readiness Scale (NPRS) for new graduate nurses.
Methods
This methodological and cross-sectional study was conducted on new graduate nurses from June to November 2023 in Kermanshah City, Iran. The translation of the scale was performed using the forward–backward translation method. Construct validity was assessed using Exploratory Factor Analysis (EFA) with a sample of 180 participants and Confirmatory Factor Analysis (CFA) with a sample of 318 participants, both employing the convenience sampling method. The internal consistency of the tool was measured using Cronbach’s alpha coefficient. Additionally, the tool’s reliability was evaluated using the intraclass correlation coefficient (ICC). The analyses were conducted using SPSS version 27 and LISREL version 8 software.
Results
The results of EFA and CFA confirmed the tool’s structure, comprising five factors and 35 items. The CFA results showed a well-fitting model (CFI = 0.96, NNFI = 0.96, GFI = 0.893, RMSEA = 0.062, SRMR = 0.049). Pearson’s correlation coefficient indicated a significant relationship between the items, subscales, and the main scale. Additionally, the Cronbach's alpha coefficient of the tool was 0.932, and the intraclass correlation coefficient (ICC) was 0.891(0.724–0.957).
Conclusion
The Persian version of the Nursing Practice Readiness Scale (NPRS) is a valid and reliable tool, comprising 35 items and five factors. This scale can be effectively used to evaluate the clinical readiness of newly graduated nurses within the Iranian community.
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Abkürzungen
NPRS
Nursing Practice Readiness Scale
CVI
Content Validity Index
CVR
Content Validity Ratio
KMO
Kaiser–Meyer–Olkin
EFA
Exploratory Factor Analysis
CFA
Confirmatory Factor Analysis
TLI
Tucker-Lewis Index
NFI
Normed Fit Index
GFI
Goodness of Fit Index
RMSEA
Root Mean Square Error of Approximation
PD
Principal Components
SRMR
Standardized Root Mean Square Residual
KUMS
Kermanshah University of Medical Sciences
Introduction
The nursing community shoulders half of the global healthcare burden [1], highlighting the significant role of nurses in patient care [2]. However, the shortage of adequate nurses remains a global challenge [3, 4]. In 2020, the State of the World's Nursing (SOWN) report highlighted a global shortage of 5.9 million nurses and estimated that 17% of the nursing workforce will retire within the next decade [4]. The shortage of nurses adversely affects the quality of care and patient outcomes [5], leading to higher mortality rates [6], prolonged hospital stays [7], increased workloads for nurses, and more instances of missed care [8]. These issues ultimately result in lower job satisfaction and increased turnover [9]. Therefore, increased attention to the nursing workforce, especially newly graduated nurses, is essential in addressing these outcomes.
The practice readiness of nursing students refers to their ability to successfully transition from newly graduated nurses to professional nurses [10]. In other words, practice readiness occurs when nursing students can effectively apply their theoretical knowledge in clinical settings [11] and acquire the necessary competencies [12].
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Newly graduated nurses constitute the primary source of the nursing workforce in many countries, and their successful transition from newly graduated nursing to professional clinical nursing significantly supports job retention [13, 14]. Several factors significantly influence the effective transition of newly graduated nurses into their roles as professional nurses [15]. Factors such as the availability of equipment and training opportunities [16], support and guidance have a positive impact, while a lack of resources, burnout syndrome, work overload, and insufficient support are barriers to this transition [17, 18]. Therefore, supporting these novice nurses is crucial in meeting the increasing demand for health services [19]. However, a study conducted by Günay and Kılınç indicated that, despite having abundant theoretical knowledge, nursing students believe that they often struggle to apply their knowledge effectively in clinical settings [20].
The transition from nursing student to professional clinical nurse has been shown by many studies to be a challenging and stressful phase for newly graduated nurses [21‐23]. During the transition phase, newly graduated nurses may face challenging situations, including feelings of apprehension, insecurity, solitude, and the possibility of experiencing a phenomenon known as 'transition shock' [24, 25]. Transition shock, which is common among novice nurses [26], threatens their physical and mental health [27]. Furthermore, an unsuccessful transition can evoke negative emotions [28] and is reported by newly graduated nurses as a key factor contributing to decreased job satisfaction and increased turnover rates [29]. Hence, it has become increasingly evident that attention to the nursing education system, along with the importance of increasing clinical readiness and strengthening nursing education globally, is more crucial than ever before [30‐32].
Clinical education forms the foundation of nursing education [30]. One of the crucial objectives of nursing education is to equip nurses with the necessary cognitive, emotional, and psychomotor skills to provide nursing services to diverse individuals [33]. Nevertheless, the theory–practice gap remains one of the most critical challenges in the nursing profession [16, 34]. Consequently, enhancing the essential clinical skills of nursing students is a paramount challenge for nursing schools [16, 35].
The characteristics of clinical readiness encompass cognitive, professional, and clinical abilities, as well as self-efficacy, and the outcomes of clinical readiness include the provision of safe care, increased self-confidence, and a successful transition to the role of a professional clinical nurse [36‐38]. Therefore, it is essential to develop a scale that evaluates the clinical readiness of newly graduated nurses [39]. The Work Readiness Scale (WRS) developed by Caballero and colleagues measures the readiness of newly graduated nurses [40]. Additionally, the Casey-Fink Readiness for Practice Survey (CFRPS) assesses senior nursing students' perceptions of their readiness for practice [41]. These are among the existing scales for evaluating the clinical readiness of newly graduated nurses. However, both scales have limitations when used by nursing managers to measure the clinical readiness of newly graduated nurses entering the clinical setting. The WRS does not assess the critical thinking and clinical judgment of newly graduated nurses [40]. Additionally, the CFRPS focuses on the effectiveness of specific training methods [41]. Therefore, a scale that can be used extensively in the clinical field without such limitations is necessary. In this regard, Kim and colleagues (2020) developed the Nursing Practice Readiness Scale (NPRS) for new graduate nurses [31]. Despite the high importance of measuring the clinical readiness of newly graduated nurses, no specialized tool in this field has been designed or psychometrically evaluated in Iran. Therefore, the present study aimed to determine the psychometric properties of the Persian version of the NPRS for new graduate nurses.
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Methods
Study design
This methodological and cross-sectional study was conducted from June to November 2023 to determine the psychometric properties of the Persian version of the NPRS for new graduate nurses. The study was executed in two main phases: the translation and cultural adaptation phase, followed by the psychometric evaluation phase.
Participants and setting
The participants in this study were 498 nurses working in the clinical wards of public and private hospitals in Kermanshah City. They were selected based on the inclusion criteria and through convenience sampling. For Exploratory Factor Analysis (EFA), a sample size of approximately 100 to 250 participants, or 2 to 20 participants per item, is recommended [42]. For Confirmatory Factor Analysis (CFA), a sample size of 150 to 500 participants is suggested [43]. Given that the NPRS consists of 35 items, 14 participants were allocated per item. Consequently, a total of 498 nurses were selected and randomly divided into two sub-samples: 180 for EFA and 318 for CFA. The inclusion criteria for this study were as follows: interest and satisfaction in participating, working in clinical wards, and having less than 12 months of work experience. Questionnaires that were less than 95% complete were excluded from the study. Additionally, all participants completed the study's informed consent form.
The translation and cultural adaptation phase
Instrument
Nursing Practice Readiness Scale (NPRS)
This scale was developed and validated using a deductive approach by Kim and colleagues in 2022 to measure the readiness for nursing practice among newly graduated nurse [31]. The NPRS is a self-report tool consisting of 35 items and five factors: clinical judgment and nursing performance (16 items, Cronbach’s α = 0.83), professional attitudes (8 items, Cronbach’s α = 0.83), patient-centeredness (5 items, Cronbach’s α = 0.85), self-regulation (3 items, Cronbach’s α = 0.85), and collaborative interpersonal relationships (3 items, Cronbach’s α = 0.83). It utilizes a 4-point Likert scale: strongly disagree (1), disagree (2), agree (3), and strongly agree (4). Scores range from 35 to 140, with higher scores indicating greater readiness. If the scale is scored by summing all the items, the internal consistency estimate is Cronbach’s α = 0.90 [31]. The validity of the NPRS was supported by content and construct validity through exploratory factor analysis, confirmatory factor analysis, and criterion-related validity.
The cultural validation steps of the tool were performed using the ten-step method of Wild and colleagues [44]:
Step 1: After selecting the tool, permission to translate and analyze its psychometric properties was obtained from the tool designer.
Step 2: Two independent translators simultaneously translated the tool from English to Persian using the forward translation method.
Step 3: After evaluating the translations, the research team merged the translated versions into a single document.
Step 4: Two translators, who were not involved in the initial translation, independently translated the merged Persian version back into English.
Step 5: The research team reviewed the two English versions, merged them into one, and sent it to the tool developer for feedback.
Step 6: All discrepancies and vocabulary issues were resolved by comparing the translated version to the original. Finally, the alignment between the translated versions and the original tool was confirmed.
Step 7: Ten nurses working in clinical wards received the final Persian version and were asked to report any ambiguities or possible errors (face validity).
Step 8: The research team assessed the feedback from the ten nurses and made the necessary changes to the final version.
Step 9: An expert in Persian language and literature edited and approved the final version.
Step 10: The final version was used for psychometric evaluations after documenting all the steps.
The psychometric evaluation phase
In this phase, the evaluation focused on the face, content, and construct validity, along with the reliability of the Persian version of the NPRS (Fig. 1).
Fig. 1
Flow chart of the psychometric assessment process of the Persian Version of the NPRS
×
Face validity assessment (qualitative and quantitative)
In this phase, a group of ten newly graduated nurses, who were not part of the initial sample, evaluated the scale items in terms of understandability, absence of ambiguity, and appropriate relationships among them [45]. This group was asked to rate the significance of each item using a 5-point Likert scale (1 = Not important at all to 5 = Very important). Items with an impact score exceeding 1.5 were retained [46].
Content validity assessment
Qualitative content validity
In this stage, to confirm the qualitative content validity, the questionnaire was distributed among 14 faculty members, researchers, and experts in this field (nine nursing faculty members, two master's degree holders and nursing managers, and three clinical nurses with master's degrees and extensive work experience). They were asked to assess the scale items for syntax, phrasing, clarity, and compatibility with Iranian culture.
Quantitative content validity
The content validity ratio (CVR) and the content validity index (CVI) were employed to evaluate the content validity of the instrument. The same 14 experts were invited to rate the necessity of the instrument items on a 3-point Likert scale: 'Essential', 'Useful but not essential', and 'Unessential' to calculate the CVR. Additionally, their suggestions for revisions to the item wording were collected and incorporated into the final version [47]. The Lawshe method was used to calculate the CVR of the instrument based on their rating scores. The minimum acceptable value for the CVR, considering the panel of 14 experts, was determined to be 0.51 [48].
The CVI can be used to assess the relevance of the instrument's items at both the individual item level (I-CVI) and the overall scale level (S-CVI). Therefore, to evaluate the relevance of the NPRS items, the same 14 experts were asked to rate them using a 4-point Likert scale from 1 to 4 (1 = not relevant, 2 = somewhat relevant, 3 = quite relevant, 4 = highly relevant). Additionally, the I-CVI was calculated by taking the ratio of experts who gave a relevance rating of 3 or 4 to the overall number of experts. Items with a CVI value above 0.79 were deemed suitable, those with CVI values from 0.70 to 0.79 required modifications, and items with CVI values below 0.70 were judged unsatisfactory and thus excluded [49]. Additionally, the S-CVI was determined by averaging the CVI values of all items. An S-CVI value of 0.9 or above signifies that the scale has good content validity [50].
Construct validity assessment
A test demonstrates construct validity when the scores derived from its administration correlate with the intended concepts or theoretical constructs [48]. To assess the construct validity of the Persian version of the NPRS, exploratory and confirmatory factor analyses were employed.
Due to the importance of separating the samples in each stage of construct validation [51, 52], a subset of 180 participants was chosen for EFA out of a total of 498 participants. The remaining 318 participants were used for CFA. Previous studies have recommended that the amount of data required should be at least five times the number of items for EFA [53]. Generally, it is suggested to have a sample size exceeding 200 participants for the CFA stage [54, 55]. Hence, the number of participants in this study was considered adequate.
In this study, EFA was performed using Varimax rotation. The researchers established that eigenvalues should exceed one and factor loadings should surpass 0.3 to achieve an optimal construct [56]. The Kaiser–Meyer–Olkin (KMO) measure and Bartlett's test were utilized to evaluate sampling adequacy. KMO values should exceed 0.7, and the value for Bartlett's test should be below 0.05 (p < 0.05) [57].
CFA demonstrates the effectiveness of each item in measuring the different dimensions of the scale. The assessment of the model fit indices was based on the following criteria: The ratio of chi-square to its degree of freedom (χ2/df) < 3, and the Root Mean Square Error of Approximation (RMSEA) < 0.08 [58]. Furthermore, the Goodness of Fit Index (GFI) > 0.90, Comparative Fit Index (CFI) > 0.90, Tucker-Lewis index(TLI) > 0.90, Incremental Fit Index (IFI) > 0.90, and Adjusted Goodness of Fit Index (AGFI) > 0.80 [59].
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Reliability
To assess the reliability of the Persian version of the NPRS, methods evaluating internal consistency and stability were employed. The instrument's overall Cronbach's alpha, as well as that for each individual item, was calculated to determine internal consistency, with values above 0.7 being deemed satisfactory [60]. The NPRS was subjected to a test–retest reliability assessment. It was administered to a separate group of 20 new graduate nurses working in hospital wards who were not part of the initial sample. These nurses completed the questionnaire on two separate occasions, 14 days apart. Following this, the intraclass correlation coefficient (ICC) for the test–retest was determined, with values of 0.75 or above considered indicative of acceptable reliability [61].
Data analysis
SPSS software version 27 and LISREL software version 8 were utilized for data analysis in this study. Descriptive statistics were used to summarize the demographic characteristics. The Waltz & Bausell index was used to confirm the quantitative content validity [49]. Exploratory and confirmatory factor analyses were employed to verify the construct validity [62]. A p-value of less than 0.05 was accepted as the significance level of statistical tests. Skewness and Kurtosis were used to evaluate the normality of data distribution in this study. Cronbach's alpha coefficient and test–retest methods [63] were employed to ensure the tool's reliability. The internal correlation of the tool was determined using the Pearson correlation coefficient.
Data collection procedure
After visiting each hospital, liaising with the respective officials, and obtaining the necessary permissions, the researcher employed a convenience sampling method to identify individuals who met the inclusion criteria for the study. After the study's objectives were explained and consent obtained, the questionnaires were personally distributed to the nurses in sealed envelopes at the nursing station during morning, afternoon, and night shifts. The nurses independently completed the questionnaires at home or in the rest area to ensure self-reporting. To minimize potential bias, such as that which could arise from the presence of the head nurse or researchers, participants were permitted to complete the questionnaires at their convenience. Of the 347 distributed questionnaires, 318 were completed and included in the analysis, while 29 were excluded from the study due to missing information in the CFA stage.
Result
Descriptive results
In the Exploratory Factor Analysis (EFA) stage, 180 employed nurses were selected. Their mean age was 24.03 ± 1.34 years, ranging from 22 to 31 years. As shown in Table 1, 49.4% of the participants were male, and all had bachelor's degrees in nursing.
Table 1
General Characteristics of Participants (N.498)
Variables
N (%)
t / χ2 (p)
EFA(180)
CFA(318)
Gender
Female
91(50.6)
151(47.5)
0.61 (0.53)
Male
89(49.4)
167(52.5)
Educational level
BSc
180(100)
318(100)
-
Mean Age
24.03 ± 1.34
24.44 ± 1.61
0.315 (0.723)
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In the Confirmatory Factor Analysis (CFA) stage, the total sample reached 318 nurses, all selected by convenience sampling according to the inclusion criteria. Their mean age was 24.44 ± 1.61 years, ranging from 22 to 32 years. Of all the participants, 52.5% were male, and all had bachelor's degrees in nursing (Table 1).
Face validity
In assessing the qualitative face validity, items 17 and 32 were identified as needing revisions to remove any ambiguity. These revisions were made and included in the questionnaire. During the quantitative face validity assessment, all items achieved an impact score greater than 1.5, leading to the retention of all items.
Content validity
In the qualitative content analysis, nine experts recommended revisions for four specific items (items 4, 7, 14, and 33) to enhance clarity and comprehension. Following the review, these items were re-evaluated and subsequently validated by a panel of experts.
The quantitative content validity of the instrument was assessed using the Content Validity Ratio (CVR) for the entire questionnaire, with individual item scores ranging from 0.57 to 1. Additionally, the CVI of the instrument, calculated using the Waltz and Bausell index, was 0.89, with individual item scores ranging from 0.79 to 1.
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Construct validation results
Exploratory Factor Analysis (EFA)
EFA was performed on an initial sample of 180 participants. Initially, the correlation coefficients between the questionnaire items were evaluated to ensure their high values. The Kaiser–Meyer–Olkin (KMO) measure and Bartlett's test of sphericity were used for this purpose. The results of the KMO and Bartlett's test were 0.902 and 5394.65, respectively. Additionally, the significance level of Bartlett's test was 0.001, indicating that performing EFA on this questionnaire is justified.
Subsequently, EFA was conducted on the participants' responses to the 35 questionnaire items. The Maximum Likelihood (ML) analysis method and orthogonal varimax rotation were employed to extract the factors in this study. The eigenvalues extracted for each item using the Principal Component Analysis (PCA) method, along with the related stability test results, are presented in Supplementary Table 1.
Additionally, to determine the number of factors, those with eigenvalues greater than one were selected. The initial findings indicated that five factors could be chosen for analysis. The extracted factors and their eigenvalues, the percentage contribution of each factor in explaining the variance of the 35 items, and the cumulative variance explained by each of the five factors are presented in Table 2. In total, five factors with eigenvalues greater than one accounted for 64.13% of the variance in the 35 items. Also, the scree plot generated from the factor analysis in SPSS software demonstrated the suitability of five factors for the final analysis (Fig. 2). Table 3 presents the rotated factor matrix. In this table, items with factor loadings greater than 0.3 and the highest loading were assigned to the corresponding factor.
Table 2
Variance percentage and specific values of different factors (N = 180)
Component
Initial Eigenvalues
Extraction Sums of Squared Loadings
Rotation Sums of Squared Loadings
Total
% of Variance
Cumulative %
Total
% of Variance
Cumulative %
Total
% of Variance
Cumulative %
1
14.200
40.572
40.572
13.645
38.985
38.985
9.019
25.767
25.767
2
4.396
12.559
53.131
4.166
11.902
50.888
5.761
16.459
42.227
3
2.516
7.189
60.320
2.121
6.061
56.948
3.378
9.651
51.877
4
1.683
4.808
65.128
1.477
4.219
61.167
2.347
6.705
58.582
5
1.351
3.859
68.987
1.038
2.966
64.134
1.943
5.551
64.134
6
.990
2.830
71.817
7
.862
2.463
74.279
8
.756
2.161
76.440
9
.698
1.994
78.434
10
.677
1.936
80.370
11
.586
1.674
82.043
12
.569
1.625
83.668
13
.543
1.551
85.219
14
.468
1.336
86.555
15
.419
1.197
87.752
16
.404
1.154
88.906
17
.393
1.123
90.029
18
.370
1.056
91.085
19
.336
.961
92.046
20
.323
.922
92.968
21
.294
.841
93.809
22
.283
.809
94.617
23
.248
.709
95.327
24
.227
.648
95.975
25
.213
.608
96.583
26
.189
.539
97.121
27
.160
.456
97.577
28
.156
.446
98.023
29
.141
.402
98.425
30
.123
.352
98.777
31
.102
.290
99.067
32
.096
.275
99.342
33
.091
.261
99.603
34
.077
.220
99.824
35
.062
.176
100.000
Table 3
Matrix of factor loadings of questionnaire questions on components after rotation (N.180)
Items
Factors
1
2
3
4
5
Q1
.843
.153
.011
.020
.164
Q2
.824
.124
.137
.090
.183
Q3
.791
.121
.216
-.044
.020
Q4
.724
.200
.260
.108
.027
Q5
.849
.140
.055
.048
.197
Q6
.726
.266
.127
.036
.166
Q7
.687
.151
.190
.124
.137
Q8
.782
.251
.085
.070
.013
Q9
.637
.097
.314
.060
.019
Q10
.717
.206
.135
-.110
-.030
Q11
.690
.155
.152
-.029
.002
Q12
.624
.067
.300
-.059
.092
Q13
.677
.103
.053
-.057
.177
Q14
.679
.177
.094
-.038
.227
Q15
.581
.188
.023
.093
.091
Q16
.525
.129
.260
.152
.149
Q17
.026
.172
.123
.871
.069
Q18
.002
.237
.149
.778
.046
Q19
.005
.202
.327
.779
.064
Q20
.277
.177
.657
.227
.131
Q21
.236
.273
.358
.071
.624
Q22
.132
.165
.783
.144
-.011
Q23
.205
.186
.678
.090
.201
Q24
.231
.138
.690
.148
.072
Q25
.280
.207
.523
.111
.288
Q26
.198
.839
.130
.143
.146
Q27
.215
.829
.082
.088
.144
Q28
.277
.662
.104
.142
.150
Q29
.285
.306
.203
.067
.694
Q30
.224
.524
.364
.077
.245
Q31
.227
.796
.200
.055
.132
Q32
.220
.842
.104
.173
.138
Q33
.159
.785
.256
.217
.106
Q34
.193
.833
.119
.083
.092
Q35
.227
.334
.089
.090
.681
Extraction Method: Maximum Likelihood
Rotation Method: Varimax with Kaiser Normalization
aRotation converged in 6 iterations
Fig. 2
Scree Plot of the extracted of Nursing Practice Readiness Scale
×
Confirmatory Factor Analysis (CFA)
CFA was performed on 318 samples. At each step of the CFA, the normality of the data distribution was evaluated using the Kolmogorov–Smirnov test. Additionally, the skewness for all items ranged from -0.87 to 0.96, and the kurtosis ranged from -0.55 to 0.98, both within the range of (-1, 1). These values indicate that the distribution of the items was approximately symmetrical.
Moreover, the factor loadings of each item were evaluated at each stage of the CFA to determine the validity of the tool. According to the values greater than 3.29 for each item, the significance level was 0.001 (Table 4). Additionally, the model fit was assessed using the fit indices presented in Table 5.
Table 4
T-value Pearson correlation coefficient and factor loadings of the Nursing Practice Readiness Scale (NPRS) (N = 318)
Factor
No
valuea t
b(λ)
Rc
Cronbach Alpha
Clinical judgment and nursing performance
1
11.93
0.62***
0.64**
0.915
2
13.71
0.69***
0.71**
3
14.44
0.72***
0.73**
4
13.83
0.7***
0.71**
5
13.3
0.67***
0.69**
6
11.44
0.6***
0.63**
7
12.72
0.65***
0.68**
8
14.17
0.71***
0.73**
9
11.42
0.6***
0.64**
10
13.06
0.67***
0.69**
11
12.2
0.63***
0.68**
12
11.63
0.61***
0.64**
13
11.3
0.6***
0.45**
14
11.91
0.62***
0.66**
15
10.44
0.56***
0.61**
16
9.79
0.54***
0.58**
Professional attitudes
26
14.62
0.73***
0.77**
0.886
27
14.67
0.73***
0.77**
28
12.53
0.65***
0.71**
30
11.54
0.61***
0.66**
31
14.4
0.72***
0.77**
32
14.98
0.75***
0.79**
33
14.01
0.71***
0.75**
34
14.3
0.72***
0.69**
Patient-centeredness
20
12.59
0.69***
0.74**
0.735
22
11.52
0.64***
0.73**
23
10.37
0.59***
0.69**
24
11.86
0.65***
0.76**
25
10.86
0.61***
0.69**
Collaborative interpersonal relationship
17
12.35
0.72***
0.83**
0.896
18
11.91
0.69***
0.81**
19
11.58
0.67***
0.76**
Self-regulation
21
12.12
0.68***
0.79**
0.712
29
12.49
0.7***
0.82**
35
11.24
0.64***
0.79**
the Nursing Practice Readiness Scale (NPRS)
0.932
***P < 0.001; **P < 0.01
aThe calculated values for all factor loadings of the first and second orders are greater than 1.96 and are therefore significant at the 95% confidence level, bThe specific value, which is denoted by the Lamda coefficient and the statistical symbol λ, is calculated from the sum of the factors of the factor loads related to all the variables of that factor, C. Pearson Correlation coefficient
Table 5
fit indices of confirmatory factor analysis model of the Nursing Practice Readiness Scale (NPRS) (N.318)
Fit indicators
Criterion
Level
Interpretation
χ2/DF
≤ 3
2.23
Optimal fit
df
550
X2
1230.78
Pvalue
0.0001
NNFI
(or TLI)
> 0.9
0.96
Optimal fit
CFI
> 0.9
0.96
Optimal fit
AGFI
> 0.8
0.893
Optimal fit
SRMR
< 0.05
0.049
Optimal fit
RMSEA
0.05–0.08
0.062
Optimal fit
Overall, CFA was conducted for five factors comprising a total of 35 items. The significance and standardization of the coefficients are presented in Figs. 3 and 4 as the results of the factor analysis. All the values exceeded the critical value of 1.96, eliminating the need for item removal. Additionally, the fit indices in Table 4 suggest a well-fitting model.
Fig. 3
5-factor model of Nursing Practice Readiness Scale (Standard)
Fig. 4
5-factor model of Nursing Practice Readiness Scale (Significant)
×
×
Internal consistency of the tool
The internal consistency of the Persian version of the Nursing Practice Readiness Scale (NPRS) was assessed using Cronbach's alpha coefficient, Intraclass Correlation Coefficient (ICC), and the test–retest method. The test–retest results indicated significant internal consistency of the Persian version of the tool. The ICC of the tool in this study was 0.891(0.724–0.957). As shown in Table 4, the Cronbach's alpha coefficients of the five factors of the model were 0.915, 0.886, 0.735, 0.896, and 0.712, respectively. The Cronbach's alpha coefficient for the entire scale was 0.932.
Correlation among factors
The Pearson correlation test was used to evaluate the correlation between the factors of the Persian version of the NPRS. The data for the main scale and the factors were normally distributed according to the Kolmogorov–Smirnov test. As shown in Table 6, there was a significant correlation between all individual factors and the overall scale at the 99% confidence level (P< 0.01). Moreover, these factors themselves exhibited significant intercorrelations at the same level of confidence. Thus, it can be concluded that there is a robust relationship between the scale and its factors.
Table 6
Correlation results of the Persian version of Nursing Practice Readiness Scale and its factors (N.318)
Factor
Correlation Coefficient
Clinical judgment and nursing performance (Cjnp)
1
Professional attitudes (Pa)
0.49**
1
Patient-centeredness (Pc)
0.47**
0.47**
1
Collaborative interpersonal relationship (Cir)
0.19**
0.36**
0.395**
1
Self-regulation (Sr)
0.46**
0.58**
0.44**
0.286**
1
Nursing Practice Readiness Scale (NPRS)
0.87**
0.801**
0.69**
0.45**
0.68**
1
**P < 0.001
Discussion
In this study, the Nursing Practice Readiness Scale (NPRS) [31] was translated into Persian and validated, resulting in a scale with five factors and 35 items. These five factors accounted for 64.134% of the variance, and the model demonstrated a good fit according to the fit indices. In line with the cultural validation of this tool in the present study, Alquwez and colleagues translated and validated the tool into Arabic in Saudi Arabia, achieving a cumulative explained variance of 69.2% [64]. By comparing the variances of the two translated tools in Iranian and Saudi Arabian cultures, it can be concluded that the translated items were effective in measuring the main phenomenon of the study.
Among the factors of the scale, Factor 1 'Clinical judgment and nursing performance' accounted for the highest percentage of the variance explained by the entire scale, contributing 38.99% to the total variance. Consistent with this finding, Alquwez and colleagues' study also identified Factor 1 as having the highest percentage of variance, accounting for 42.9% [64].
The high explained variance attributed to the factor 'Clinical judgment and nursing performance' underscores the importance of these skills in preparing nurses for clinical settings. Based on this factor, newly graduated nurses need to possess strong clinical judgment and effective nursing performance to be well-prepared for clinical settings [65]. The high explained variance attributed to the factor 'Clinical judgment and nursing performance' in the present study aligns with the findings of Alquwez and colleagues, as well as the original study by Kim and colleagues [31, 64]. This emphasizes that the ability of nurses to apply theoretical knowledge to real clinical situations and solve complex problems is one of the most crucial aspects of readiness for performance in nursing settings. Furthermore, this factor was found to be associated with the subscale 'clinical problem-solving, learning techniques, professional identity, and trials and tribulations' of the 'Casey-Fink Readiness for Practice Scale' [41]. Based on this finding, it was emphasized that clinical practice requires strong problem-solving and decision-making skills [41]. Through these skills, nurses can effectively and creatively address both common and complex challenges in clinical settings [66]. Clinical judgment and nursing performance involve assessing clinical situations, identifying patient needs, prioritizing care, implementing appropriate interventions, and evaluating patient responses to treatment [67]. These abilities are crucial not only for providing safe and effective care but also for enabling nurses to respond swiftly to sudden, emergency, and unexpected situations in clinical settings [68]. In another tool designed by Avşar and colleagues, titled the 'Scale of Readiness for Clinical Practice,' the 'Clinical judgment and nursing performance' subscale aligned with the 'Clinical judgment and nursing performance' factor in the present tool. However, the tool designed by Avşar and colleagues was intended to assess the readiness of nursing students, whereas the validated tool in this study focused on the readiness of graduate nurses. On the other hand, the 'Clinical judgment and nursing performance' factor in the present tool focused on a more accurate and comprehensive assessment of nurses' abilities in performing tasks and making clinical decisions. In contrast, the 'Clinical decision making and practice skills' dimension in Avşar and colleagues' tool focused more on nursing students' perceived readiness to perform nursing diagnoses and practical skills such as injections [69].
'Professional attitudes' was the second most influential factor identified in the tool, accounting for 11.91% of the total variance. This factor, following 'Clinical judgment and nursing performance,' demonstrated the greatest impact on measuring Nursing Practice Readiness. This finding aligns with the study by Alquwez and colleagues. In their study, the 'Professional attitudes' factor ranked second in importance after the 'clinical judgment and nursing performance' factor, explaining 10.8% of the total variance [64]. This factor includes five items that address the applications used by nursing students to solve problems, cope, and perform nursing care independently [70]. In line with the 'Professional attitudes' factor in the present tool, another tool validated by Kuleyin and Basaran-Acil, known as the Turkish version of the 'Casey-Fink Readiness for Practice Scale', includes a factor called 'Professional Identity.' This factor addresses questions about nurses' readiness to assume professional roles [39]. In the 'Professional attitudes' factor of the present tool, both professional readiness and the nurse's professional behavior toward the patient were evaluated.
The third factor of the present tool was 'patient-centeredness,' which explained 6.06% of the total variance. This factor includes elements that focus on maintaining patient privacy, encouraging patients to express their needs and concerns, and striving to understand and empathize with their situation. This factor defines patient-centeredness as respecting and responding to patients' preferences, needs, and values [31]. Unfortunately, in other tools designed and validated to evaluate the nurse's readiness in clinical settings, there was no emphasis on patient-centeredness, except for the tool by Alquwez and colleagues [64]. Various studies, such as the one by Radwin and colleagues, have developed tools for evaluating the patient-centeredness of nurses. However, these tools lack a perspective on assessing nurses' readiness in clinical settings [71, 72]. Patient-centered care is one of the six main components of high-quality health care in the United States, and its significance in evaluating nurses' readiness in clinical settings cannot be overstated [73].
The fourth factor of the tool, 'Self-regulation,' accounted for 4.22% of the total variance. This factor evaluates individuals' ability to manage and control their behaviors, emotions, and reactions in various situations, particularly in the work environment. The items assigned to this area cover crucial aspects of self-regulation, including the ability to control impulsive behaviors in stressful work environments. Our search revealed that self-regulation was not emphasized in any of the tools used to assess the nurses' readiness in clinical settings. Incorporating self-regulation and its related items into the development of future tools could increase the variance explained by the entire scale, given that self-regulation accounts for 4.22% of the total variance.
The fifth factor of the tool, 'Collaborative Interpersonal Relationship,' focused on assessing and enhancing individuals' abilities in cooperation and effective communication within work environments, particularly in the health sector. This factor aligns with the 'ability to provide safety and effective communication' factor from the tool developed by Avşar and colleagues. However, the items in this factor of the present tool, in addition to patient communication, also focused on interprofessional communication and communication with colleagues. In contrast, the tool developed by Avşar and colleagues focused solely on patient communication [69].
In the present study, both EFA and CFA were performed. The results confirmed the five-factor structure of the tool, which was consistent with the content of the original tool. In this process, each item of the assumed structure was loaded onto a single factor. In addition, the fit indices for the tool were calculated, and the values demonstrated a good fit for the model. However, Alquwez and colleagues validated the cultural validity of the tool in Saudi Arabia without performing CFA [64]. Orçan suggested that the use of CFA is essential, as the absence of factor analysis in cross-cultural studies represents a flaw in the psychometric process [74].
In this study, internal consistency was estimated using Cronbach's alpha coefficient, which was 0.932 for the entire scale, indicating an acceptable level. Additionally, all factors of the tool had a Cronbach's alpha coefficient higher than 0.7. In line with this finding, the studies by Avşar and colleagues (α = 0.964) and Alquwez and colleagues (α = 0.957) also reported acceptable Cronbach's alpha coefficients for the entire scale and its subscales. However, in the study by Kuleyin and Basaran-Acil, one of the factors of the tool had a Cronbach's alpha coefficient estimated to be less than 0.7.
Limitations
The present study was limited to participants from only one western city in Iran. Therefore, it is suggested that the tool's cultural adaptation be evaluated in larger populations in future studies.
Conclusion
The Persian version of the Nursing Practice Readiness Scale (NPRS) is a valid and reliable tool, comprising 35 items and five factors. It can be used to evaluate the clinical readiness of novice nurses in the Iranian community. This tool can be utilized by educational and therapeutic managers to measure and enhance the readiness of newly graduated nurses. Additionally, researchers can use this tool to evaluate the practice readiness of Iranian nurses in their studies.
Acknowledgements
The authors thank the faculty members of the Student Research Committee of Kermanshah University of Medical Sciences. This research project has been registered with code 4020472 at Kermanshah University of Medical Sciences, Iran (IR.KUMS.REC.1402.069).
Declarations
Ethics approval and consent to participate
A written permission was secured from the developer of scale, and the ethics committee of Kermanshah University of Medical Sciences approved the study under the ethics code: IR.KUMS.REC.1402.069. Participation by the students was voluntary and anonymous, and informed consent was obtained from all study subjects. Additionally, the principles of the Helsinki Declaration were observed. All methods were performed according to the relevant guidelines and regulations.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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