Identifying the causes and consequences of work interruptions in nursing is crucial, as they play a vital role in improving workflow, nurse well-being, and enhancing patient safety. Therefore, by considering these factors, healthcare institutions can implement effective interventions and strategies to improve the nursing work environment while simultaneously enhancing the quality of patient care.
Aim
This study aims to culturally adapt and psychometrically evaluate the Persian version of the Nursing Work Interruption Scale.
Methods
This methodological cross-sectional study involved a sample of 506 nurses selected through convenience sampling. The translation and cultural adaptation of the Nursing Work Interruption Scale were conducted using the Polit and Yang model. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and assessments of internal consistency were conducted to evaluate the validity and reliability of the instrument. SPSS version 27 and LISREL version 8 software were used in this study.
Results
The results of the EFA and CFA confirmed the tool with two factors and 12 items. The CFA results indicated a well-fitting model (CFI = 0.91, NNFI = 0.92, GFI = 0.91, RMSEA = 0.057, SRMR = 0.045). Pearson’s correlation coefficient confirmed a significant relationship between items, subscales, and the main scale. Additionally, Cronbach’s alpha coefficient (0.896) and McDonald’s Omega (0.892) confirmed the scale’s reliability.
Conclusion
The Persian version of the Nursing Work Interruption Scale is a valid and reliable tool, consisting of 12 items and two factors. This scale provides a valuable tool for measuring the extent of work interruptions experienced by nurses. Additionally, it can be utilized to develop and evaluate the efficacy of strategies designed to reduce these interruptions.
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Introduction
Nursing, a cornerstone of healthcare systems, plays a critical role in the delivery of patient care [1‐3]. However, nurses frequently encounter numerous challenges in their work environments that can negatively impact both the quality of care and their own well-being. One such challenge is the occurrence of work interruptions. Due to the dynamic and complex nature of healthcare settings, where patient needs and service demands fluctuate constantly, work interruptions have become a pervasive issue [4].
Nursing work interruptions, common occurrences that frequently disrupt the workflow of nurses, can lead to errors, delays, and omissions in patient care [5‐7]. These interruptions, defined as external events that interfere with or delay nurse-patient interactions, can divert attention during the provision of healthcare services [8]. Nursing work interruptions can stem from various sources, including human and technical factors. Human sources encompass healthcare personnel, patients, and families, while technical sources involve equipment malfunctions [9], operational failures, and resource shortages [10]. Interruptions can occur through different communication channels, such as face-to-face interactions or technological means like telephones, pagers, and monitoring devices [11]. To effectively address work interruptions, it is crucial to identify their underlying causes. Categorizing interruptions based on factors such as duration [7], physical location, and primary and secondary task types [7, 10] can provide valuable insights.
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Numerous studies have demonstrated a high prevalence of work interruptions across various hospital settings, including intensive care units (ICUs) [12, 13], emergency departments (EDs) [14], post-anesthesia care units (PACUs) [15], and pediatric wards [16]. Work interruptions are prevalent in various nursing tasks, particularly during medication administration [17]. A study by Wang et al. investigated work interruptions during medication administration in a Chinese hospital. Over 270 h of observation, nurses experienced 3424 interruptions, resulting in a rate of 12.68 interruptions per hour, which accounted for 9.87% of the total observation time [18].
Work interruptions in nursing have been associated with a range of negative consequences. These disruptions can prolong task completion times, reduce efficiency, and increase the risk of errors and omissions in patient care. By diverting nurses’ attention, interruptions can compromise patient safety and quality of care [19]. Furthermore, interruptions can negatively impact the work environment [20], leading to increased stress, burnout, and psychological distress among nurses. These factors can ultimately contribute to increased healthcare costs. In conclusion, work interruptions pose significant challenges to both nurses and patients [21]. Therefore, the development and utilization of standardized tools for measuring and assessing work interruptions can aid in identifying patterns, implementing targeted interventions, and evaluating their effectiveness. Ultimately, this process will improve nurse well-being and enhance patient safety.
A comprehensive literature review revealed a limited number of self-report measures designed to assess workplace interruptions. While tools like the four-item scale for assessing intrusions [22] and the Workplace Interruptions Measure (WIM) [23] have been developed, their generalizability to the unique demands of nursing practice may be limited. Based on Jett and George’s [24] four-factor conceptual typology of interruptions—intrusions, distractions, discrepancy detections, and breaks—the WIM offers a generalizable tool for evaluating work interruptions across various work settings [23]. However, due to the unique characteristics of healthcare settings and nursing work, some items of this instrument may not be entirely suitable for such environments. Therefore, there is a critical need for a tool specifically designed to assess work interruptions in nursing contexts, tailored to the unique demands and challenges of the nursing profession. To address this gap, Yu and Lee developed the Nursing Work Interruption Scale (NWIS) in 2022 [25]. This 12-item self-report measure is specifically designed to assess work interruptions in nursing settings, focusing on both human and environmental factors. By accurately capturing the specific challenges faced by nurses, the NWIS can provide valuable insights for improving patient safety, enhancing nurse well-being, and optimizing organizational efficiency.
Iranian nurses frequently encounter a multitude of challenges within their profession. These challenges include, but are not limited to, nursing shortages [26], equipment deficiencies [27], and excessive workload [28]. Such factors can significantly disrupt the delivery of quality and safe patient care, leading to numerous interruptions in nursing processes. To date, there has been a dearth of research investigating nursing work interruptions in Iran, and no validated tools exist to measure this phenomenon. The absence of such a tool hinders the accurate assessment of work interruptions and limits the potential for evidence-based interventions to improve nursing practice. Given the increasing recognition of the impact of work interruptions on nurse well-being and patient safety, the development and validation of a culturally appropriate tool is crucial. However, the existing tools are not efficient enough to accurately measure this phenomenon. To address this gap, the present study aimed to adapt and validate the Nursing Work Interruption Scale (NWIS) into Persian for use in the Iranian nursing context.
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Method
Design
This cross-sectional methodological study, conducted between May and September 2024, utilized a psychometric evaluation framework to assess the Persian version of the Nursing Work Interruption Scale. The research design was characterized by two sequential phases: a translation and cultural adaptation process, followed by a comprehensive evaluation of the scale’s psychometric properties.
Participants and study setting
Currently, more than 3,000 nurses work in the clinical departments of public and private hospitals in Kermanshah. The study involved 506 nurses employed in the clinical wards of public and private hospitals located in Kermanshah City. Participants were selected through a convenience sampling process, adhering to predetermined inclusion criteria. The inclusion criteria required a minimum of six months of independent nursing experience and a willingness to participate in the study. Individuals who exhibited more than 10% incompleteness in their questionnaire responses were excluded from the analysis [29]. Participants were assigned to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) according to established guidelines to fulfill the sample size requirements for these analyses. For EFA, a participant-to-item ratio of 2 to 20 is recommended [30]. To accommodate the 12-item Nursing Work Interruption Scale, a sample size of 200 nurses was deemed suitable for EFA. The remaining 306 nurses were allocated to CFA, adhering to the recommended sample size range of 150 to 500 for this analysis [31].
Translation and cultural adaptation
The research employed the Nursing Work Interruption Scale, initially developed by Eun-Jeong Yu and Eun-Nam Lee in Korea [25]. This 12-item instrument assesses two distinct factors related to nursing work interruptions: human factors and environmental factors. Each item on the scale is rated using a 6-point Likert scale, ranging from “At Least 5 Times per Day” to “Almost None.” Higher scores indicate a greater frequency of perceived interruptions. The scale does not contain any reverse-scored items. The scale has demonstrated robust construct validity and satisfactory internal consistency, as indicated by a Cronbach’s alpha coefficient of 0.88.
Forward-backward translation
With the original developers’ approval, the translation and cultural adaptation of the Nursing Work Interruption Scale were conducted using the Polit and Yang model [32]. This process involved several stages:
Forward Translation: Two bilingual Iranian translators, proficient in both Persian and English, independently translated the original English scale into Persian.
Synthesis: A panel of experts reviewed the translations and created a consolidated Persian version.
Back-Translation: Two additional bilingual translators, who had no prior exposure to the original scale or the initial translations, independently back-translated the synthesized Persian version into English.
Reconciliation: A panel of experts compared the back-translations to the original English scale, making necessary adjustments to the Persian version to ensure semantic and conceptual equivalence.
Pre-Testing and Cognitive Interviewing: A qualitative assessment of face validity was carried out with the participation of 15 nurses. Participants were interviewed to evaluate the clarity, relevance, and potential ambiguity of each item in the Persian version of the scale.
Psychometric evaluation
This phase of the study aimed to evaluate the psychometric properties of the Persian version of the Nursing Work Interruption Scale, including its face, content, and construct validity, as well as its internal consistency reliability.
Face validity assessment
To quantitatively assess face validity, 15 nurses were asked to rate the importance of each item on a 5-point Likert scale, ranging from “not important” to “completely important.” Each item’s impact score was calculated by multiplying its frequency of selection by its average importance rating. Items with an impact score above 1.5 were selected for further analysis [33].
Content validity assessment
Content validity was established through a mixed-methods approach. Qualitative content validity was ensured by expert review. A panel of fifteen experts, comprising five nursing faculty members, five nursing managers with master’s degrees, and five clinical nurses with master’s degrees, assessed the scale’s items for grammatical accuracy, appropriate word choice, item placement, clarity, scoring method, and cultural relevance to the Iranian context.
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Two indices were calculated based on expert ratings to quantitatively assess the content validity: the Content Validity Ratio (CVR) and the Content Validity Index (CVI). Experts rated each item’s necessity on a 3-point Likert scale, ranging from “not necessary” to “necessary” for the CVR [34, 35]. The resulting CVR was compared to Lawshe’s table, with a minimum acceptable value of 0.49 for a panel of 15 experts [36]. The CVI was calculated by assessing each item’s relevance on a 4-point Likert scale, ranging from “not relevant” to “very relevant.” Polit and Beck state that a CVI of 0.79 or above is deemed excellent, irrespective of the number of experts involved [34].
Construct validity assessment
In this phase, both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were utilized to validate that the instrument accurately measured the intended variable [35]. EFA was conducted with Varimax rotation. Specific criteria were employed to determine an optimal structure, including eigenvalues greater than 1.0 and factor loadings exceeding 0.5 [37, 38]. The Kaiser-Meyer-Olkin (KMO) and Bartlett’s tests were employed to evaluate the suitability of the sample size for factor analysis. A KMO value above 0.7 and a significant Bartlett’s test (p < 0.05) indicate a suitable sample size [39].
Confirmatory Factor Analysis (CFA) was utilized to evaluate the effectiveness of each item in measuring the factors of the scale. Model fit was assessed using the following indices: χ2/df < 3, RMSEA < 0.08 [40], GFI > 0.90, CFI > 0.90, TLI > 0.90, IFI > 0.90, and AGFI > 0.80 [41, 42].
Reliability
Cronbach’s alpha and McDonald’s omega coefficients were used to assess the internal consistency. Both coefficients exceeded the 0.70 threshold, indicating acceptable internal consistency [43, 44]. Test-retest reliability was evaluated using the Intraclass Correlation Coefficient (ICC) on a 10% subsample (n = 50) over two separate occasions, 14 days apart [45]. An ICC of 0.75 or higher, as observed in this study, suggests satisfactory test-retest reliability [46].
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Data collection
After obtaining the necessary permissions from relevant authorities at each hospital, the researcher utilized a random sampling method to select participants who met the study’s inclusion criteria. After clarification of the study’s objectives and obtaining informed consent, questionnaires were distributed in sealed envelopes to nurses at the nursing stations during various shifts. Nurses independently completed the questionnaires either at home or in designated rest areas to ensure accurate self-reporting. Participants were given flexibility in completing and submitting the questionnaires, eliminating any influence from the head nurse or research team to minimize potential bias. Of the 549 questionnaires distributed, 506 were analyzed, while 43 were excluded due to incomplete information.
Statistical analysis
Data analysis was conducted using SPSS (version 26.0) and LISREL (version 8.0). Statistical techniques included Cronbach’s alpha, Intraclass Correlation Coefficient (ICC), and both exploratory and confirmatory factor analyses. The significance level was set at P < 0.05.
Results
Demographic characterizes
A total of 200 nurses participated in the exploratory factor analysis (EFA) phase. The sample had a mean age of 30.28 years (SD = 5.11), with ages ranging from 23 to 51 years. In terms of demographic characteristics, the sample was composed of 50% male and 50% female participants. Additionally, 60.5% of the participants were unmarried, and a significant majority, 87.5%, held a bachelor’s degree (Table 1).
Table 1
Demographic characteristics of the study participants
Variables
N (%)
EFA (200)
CFA (306)
Age (year)
30.28 ± 5.11
30.59 ± 5.09
Job history (year)
6.43 ± 5.07
6.07 ± 4.93
Gender
Male
100(50)
151(49.3)
Female
100(50)
155(50.7)
Marital Status
Unmarried
121(60.5)
173(56.5)
Married
79(39.5)
133(43.5)
Educational Level
BSc
175(87.5)
259(84.6)
MSc
25(12.5)
47(15.4)
Ward
Internal
72(35.5)
103(33.7)
Surgical
34(17)
50(16.3)
Critical Care
53(26.5)
82(26.8)
Emergency
42(21)
71(23.2)
Work Shift
Circular
177(88.5)
241(78.8)
Daily
23(11.5)
65(21.2)
Hospital
State hospital
177(88.5)
252(82.4)
Non-government hospital
23(11.5)
54(17.6)
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For the confirmatory factor analysis (CFA), the sample included 306 nurses. The sample had a mean age of 30.59 years (SD = 5.09), with ages ranging from 23 to 56 years. In terms of demographic characteristics, the sample was composed of 49.3% male and 50.7% female participants. Additionally, 56.5% of the participants were unmarried, and a significant majority, 84.6%, held a bachelor’s degree (Table 1).
Face validity
After translating the instrument from the original version to the Persian version, a qualitative face validity assessment showed that the Persian translation of items 4 and 9 lacked clarity and could be interpreted ambiguously. After necessary revisions, all items were deemed suitable for inclusion in the quantitative face validity evaluation, as each item demonstrated a significant impact score exceeding 1.5.
Content validity
Qualitative content analysis of the Persian version of the instrument revealed the need to revise three items (2, 3, and 8) to improve clarity and comprehensibility. Therefore, after review by the research team and assistance from a Persian language and literature expert, the three items were changed in such a way that the basic concepts of the items in the original version did not differ. After expert review and modifications, these items were deemed suitable. The Content Validity Ratio (CVR) and the Content Validity Index (CVI) were employed to assess the quantitative content validity of the instrument. The CVR yielded a value of 0.90, indicating strong content validity and exceeding the recommended threshold of 0.86. The CVI, calculated using the Waltz and Bausell index, was found to be 0.95, suggesting excellent content validity. Individual item scores ranged from 0.93 to 1.00, further supporting the instrument’s strong content validity. Additionally, the S-CVI of the tool was 0.95, and the I-CVI ranged from 0.93 to 1.00, both indicating high levels of content validity.
Exploratory factor analysis
Exploratory factor analysis (EFA) was performed on a sample of 200 participants to assess the construct validity of the scale. The Kaiser-Meyer-Olkin (KMO) measure, a widely used indicator of sampling adequacy, was found to be 0.838, surpassing the recommended threshold of 0.7 Bartlett’s test of sphericity also confirmed the suitability of the data for factor analysis (χ² = 1411.52, p < 0.001).
A two-factor solution emerged from the EFA, using the Maximum Likelihood (ML) method and Varimax orthogonal rotation. These factors, accounting for 63.58% of the total variance, were identified based on eigenvalues exceeding 1.0. As illustrated in Table 2, all 12 items exhibited factor loadings greater than 0.50 and were categorized into two distinct constructs: Human factors (6 items) and Environmental factors (6 items). The scree plot, depicted in Fig. 1, visually reinforces the two-factor structure of the instrument.
Table 2
Item factor loadings from exploratory factor analysis of the nursing work interruption Scale
Factor
Items
Mean
SD
Factor
Communality
1
2
Human factors
Q1
4.46
1.60
0.903
0.145
0.805
Q2
3.96
1.48
0.719
0.309
0.765
Q3
4.01
1.40
0.530
0.325
0.496
Q4
3.30
1.71
0.845
0.208
0.764
Q5
2.75
1.54
0.665
0.391
0.804
Q6
3.82
1.64
0.575
0.365
0.617
Environmental factors
Q7
2.51
1.53
0.172
0.759
0.684
Q8
3.26
1.58
0.319
0.728
0.686
Q9
3.95
1.53
0.576
0.532
0.655
Q10
3.78
1.70
0.448
0.582
0.586
Q11
3.26
1.58
0.353
0.766
0.742
Q12
2.98
1.61
0.241
0.905
0.829
Eigenvalue
6.975
1.491
Percentage of the variance %
32.88
30.7
Fig. 1
Scree Plot of the Extracted Components of the Nursing Work Interruption Scale
×
Confirmatory factor analysis
A sample of 306 nurses was used to perform a confirmatory factor analysis (CFA) aimed at validating the scale’s two-factor structure. The model exhibited satisfactory fit indices, including χ²=150.83, P-value = 0.0001, RMSEA = 0.057, NNFI/TLI = 0.92, CFI = 0.91, GFI = 0.91, SRMR = 0.045, df = 75, and χ²/df = 2.01.
Instrument reliability
Cronbach’s alpha coefficient for the Persian version of the Nursing Work Interruption Scale in this study was 0.896, and this coefficient was between 0.82 and 0.858 for the subscales. Also, the McDonald Omega-Near value was 0.892. (Table 4).
Correlation between factors
As can be seen in Table 3, the Pearson correlation test showed a direct and significant relationship between the items and the model of the Persian version of the Nursing Work Interruption Scale in the study population (P < 0.001). - Also, a direct and significant relationship was seen between the factors and the original model of the Persian version of the Nursing Work Interruption Scale (Table 3).
Table 3
Correlation of the nursing work interruption Scale and Sub-scales
Factor
1
2
NWIS
F. 1
Human factors
1
F. 2
Environmental factors
0.686**
1
NWIS
0.912**
0.924**
1
**P < 0.01
Note. Correlations are latent factor correlation estimates from the CFA model. All correlations were statistically significant at p < 0.01
Figure 2 displays the path diagram and factor loadings derived from the CFA. Furthermore, Pearson’s correlation analysis demonstrated significant and positive relationships between the subscales and the overall scale, as presented in Table 2. All first and second-order factor loadings were statistically significant at the 95% confidence level (|λ| > 1.96). Table 4 presents the Lambda coefficient, which summarizes the factor loadings for each factor.
Fig. 2
Final Measurement Model of the Nursing Work Interruption Scale from Confirmatory Factor Analysis (N = 306)
×
Table 4
T-value, Pearson Correlation Coefficient, factor loadings, Macdonald’s omega (ῶ), and Cronbach’s alpha of the nursing work interruption Scale and Sub-scales
Factor
No
t valuea
b(λ)
Rc
Macdonald’s Omega (ῶ)
ICC
Cronbach Alpha
Human factors
Q1
13.24
0.70***
0.67***
0.812
0.908
(CI: 0.845 − 0.951)
0.82
Q2
13.06
0.70***
0.69***
Q3
9.94
0.56***
0.59***
Q4
12.97
0.69***
0.66***
Q5
13.15
0.70***
0.68***
Q6
10.59
0.59***
0.66***
Environmental factors
Q7
11.50
0.62***
0.63***
0.858
0.873
(CI: 0.786- 0.932)
0.858
Q8
14.48
0.74***
0.73***
Q9
11.36
0.61***
0.701***
Q10
11.81
0.63***
0.68***
Q11
16.65
0.81***
0.75***
Q12
17.84
0.85***
0.75***
The Nursing Work Interruption Scale
0.892
0.925
(CI: 0.875- 0.959)
0.896
***P < 0.001
(a) The calculated values for all first and second-order factor loadings are greater than 1.96, making them significant at the 95% confidence level. (b) The specific value, denoted by the Lambda coefficient (λ), is calculated from the sum of the factor loadings related to all the variables of that factor. (c) Pearson Correlation Coefficient
Discussion
In this study, the instrument developed by Yu and Lee in 2022 was culturally translated and adapted into Persian for use in Iran [25]. The final version of the instrument consisted of two factors and 12 items, with satisfactory cultural adaptation. These factors included Human Factors (6 items) and Environmental Factors (6 items). Content validity was assessed through a combination of expert feedback and quantitative indices. The Content Validity Ratio (CVR) and the Scale-level Content Validity Index (S-CVI) were 0.90 and 0.95, respectively, both of which exceed the accepted thresholds, indicating strong content validity. In this study, the high CVR and S-CVI values reflect the expert panel’s consensus on the relevance and clarity of the items. These findings support the conclusion that the NWIS effectively identifies and measures key dimensions of interruptions in nursing workflows, demonstrating both robust content validity and cultural adaptability.
In this study, the two factors accounted for 63.58% of the variance, and the model fit indices were satisfactory. Yu and Lee [25] reported an explained variance of 55.73%. The comparison of explained variances between the two studies suggests that the Nursing Work Interruption Scale (NWIS) items were able to measure the target construct in both Iranian and South Korean cultures.
In this study, the “Human factors” component accounted for 32.88% of the total variance explained by the instrument. Similarly, Yu and Lee [25] reported that “Human factors” contributed 27.1% of the total variance. This component, comprising six items, refers to individuals who unexpectedly interrupt nurses’ work. “Intrusions” are defined as disruptions that reduce the time available for primary tasks, leading to longer task completion times. Previous studies [22‐24, 47] have identified “intrusions” as a crucial feature of workflow disruptions, with examples including sudden requests for new tasks or requests from colleagues. Individuals interrupting nurses include patients, physicians, fellow nurses, other staff, and security personnel, reflecting the unique characteristics of hospital environments. It is important to note that in healthcare settings, nurses frequently need to pause their activities to respond to phone calls or sudden requests from patients, the treatment team, and other staff. These interruptions, especially in care-oriented work environments, are not always perceived as workflow disruptions [25]. Therefore, it is essential to inform patients and hospital visitors about the negative impact of interruptions on nursing workflow and the quality of care. Additionally, while raising awareness, hospital management should implement strategies to create interruption-free zones or allocate dedicated staff to handle such requests.
The second component of the instrument, “Environmental Factors,” accounted for 30.7% of the total variance in this study. This component included items that assess environmental factors such as patient and staff noise, equipment alarms, equipment malfunctions, sudden changes in patient condition, sudden increases in patient volume, and safety emergencies. Essentially, “Environmental Factors” denote changes and stimuli that can distract nurses and disrupt their focus [23, 48]. Distractions are defined as cognitive shifts resulting from environmental stimuli or secondary tasks and can lead to workflow disruptions [49, 50]. Noise, particularly arising from constant communication among doctors, nurses, patients, and families, as well as medical equipment operation, has emerged as a significant distraction in healthcare settings. These noises can be frequent and loud, disrupting staff concentration [51, 52]. Previous studies, including Wilkes et al. [23], have primarily focused on noise as a distractor. However, the Nursing Work Interruption Scale (NWIS) encompasses a broader range of environmental distractions, including sudden changes in patient condition, equipment malfunctions, and increased patient volume. Identifying environmental factors that disrupt nurses’ workflow can enhance our understanding of these factors and facilitate the development of effective strategies to mitigate disruptions.
In addition to exploratory factor analysis, confirmatory factor analysis was conducted in this study. The findings confirmed a two-factor structure in the sample, aligning with the original instrument. Each item is loaded onto a single factor as hypothesized. Furthermore, model fit indices were calculated, indicating a good fit for the model. In the study by Yu and Lee [25], the confirmatory factor analysis results showed satisfactory model fit indices (GFI = 0.88, TLI = 0.89, CFI = 0.91, NFI = 0.86, RMSEA = 0.09). These findings suggest that the relationship between items and dimensions is consistent [53].
In this study, internal consistency was assessed using Cronbach’s alpha and McDonald’s omega, yielding coefficients of 0.896 and 0.892, respectively, indicating acceptable reliability. Furthermore, all subscales exhibited Cronbach’s alpha values above 0.82. Consistent with these findings, Yu and Lee [25] reported Cronbach’s alpha coefficients of 0.88 for the 12 items, 0.84 for Factor 1 (human factors), and 0.83 for Factor 2 (environmental factors), suggesting high reliability. Overall, Cronbach’s alpha and McDonald’s omega coefficients in the present study indicate that the Persian version of the Nursing Work Interruption Scale (NWIS) is a reliable instrument for measuring interruptions in nursing work.
The Nursing Work Interruption Scale (NWIS) is recognized as the first self-report measure specifically designed to assess interruptions in nursing workflows, capturing the unique characteristics of the nursing work environment. This instrument not only addresses the distinct challenges faced by nursing professionals but also accounts for the broader nature of work interruptions in general organizational settings. By offering valuable insights into the causes and dynamics of interruptions, the NWIS facilitates a deeper understanding of the problems and challenges inherent in nursing workflows.
Among the scale’s items, “I had to stop what I was doing due to a patient suddenly asking for something” and “I had to stop what I was doing due to a malfunction of equipment” exhibited the highest factor loadings. These findings highlight the critical role of unplanned patient demands and equipment malfunctions in disrupting nursing workflows, emphasizing their significance in understanding and addressing work interruptions.
The NWIS serves as a tool for identifying the causes of nursing work interruptions across various hospital departments. By providing a comprehensive assessment of workflow disruptions, the scale enables researchers and healthcare administrators to collect baseline data on the frequency, causes, and patterns of these interruptions. This data is pivotal in designing targeted interventions to address specific challenges in nursing workflows.
To evaluate the effectiveness of these interventions, the NWIS can be utilized in pre- and post-intervention assessments. For example, comparing NWIS scores before and after implementing strategies such as workflow redesigns or enhanced equipment maintenance protocols allows for an objective measure of intervention success. Moreover, reductions in NWIS scores can correlate with tangible improvements in related outcomes, including reduced medical errors, lower stress levels, and decreased burnout among nurses. This makes the NWIS an invaluable tool for offering a comprehensive evaluation of intervention effectiveness and its broader implications for healthcare delivery.
Despite its significant utility, there remains a paucity of research investigating the psychometric properties of the NWIS across diverse contexts and healthcare systems. While the findings of this study align with the scale’s original conceptual framework, they underscore the need for further cross-cultural validations and comparative studies. Such efforts are essential to enhance the scale’s generalizability and applicability in diverse healthcare settings, ensuring its effectiveness in addressing the complexities of nursing work interruptions on a global scale.
Limitations
This cross-sectional study utilized a convenience sample of nurses from a university hospital in a western Iranian city to examine the psychometric properties of the Persian version of the Nursing Work Interruption Scale (NWIS). The study used a data-driven measurement model, so caution is necessary when generalizing the findings. Although content and structural validity were assessed, the study did not examine criterion validity, which includes concurrent and predictive validity. Future research should evaluate the applicability of the NWIS in diverse cultural contexts and countries to enhance its validity and generalizability for measuring nursing work interruptions across a broader range of nursing work environments.
Conclusion
This study psychometrically evaluated the Persian version of the Nursing Work Interruption Scale (NWIS), a valid and reliable tool designed for assessing interruptions in nursing work within the Iranian cultural context. By identifying both human and environmental factors that disrupt nursing workflows, the NWIS provides valuable insights into the causes of work interruptions. While primarily designed to assess these disruptions, the scale’s findings can also guide efforts to improve nurses’ working conditions. These insights may contribute to optimizing efficiency and supporting targeted interventions aimed at reducing interruptions, which can have a positive impact on both staff well-being and patient care.
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 4020258 Kermanshah University of Medical Sciences, Iran.
Declarations
Ethics approval and consent to participate
This study was approved by the Ethics Committee of Kermanshah University of Medical Sciences (Ethics code: IR.KUMS.REC.1401.437). Written permission to use the scale was obtained from the tool’s developer. All participants provided written informed consent before participation. The study was conducted according to the Declaration of Helsinki and relevant ethical guidelines and regulations.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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