Sage Journals: Discover world-class research

Abstract

Background: Professional engagement as a crucial organizational variable can enhance the organization’s productivity and efficiency. As nurses’ professional engagement within an organization increases, the organization’s effectiveness is also expected to improve. Engaged nurses are energetic, proactive, deeply focused on their work, and dedicated to continuous performance improvement. However, measuring professional engagement poses challenges due to its subjective and multidimensional nature. Since no dedicated tool exists to specifically measure professional engagement in nurses, this research aims to develop and validate an instrument for assessing professional engagement in clinical nurses. Method: This study employs a mixed-methods approach with an explorative sequential design, conducted in two phases: quantitative and qualitative. In the first phase (qualitative phase), the dimensions and concepts of professional engagement in clinical nurses will be defined and elucidated through the content analysis approach. To strengthen the data, five rigor criteria such as transferability, confirmability, authenticity, dependability, and credibility will be used. In the second phase (quantitative phase), the tool for measuring professional engagement in clinical nurses will be designed based on the Waltz et al.'s four-step approach. Subsequently, the designed tool will undergo psychometric evaluation, including assessments of face validity, content validity, structural validity, and reliability. Discussion: Given the lack of a specialized tool for assessing nurses’ professional engagement, a valid and reliable instrument will be developed. It will enable more accurate measurement of engagement among nurses, ultimately leading to improved patient care quality through better utilization of human resources and targeted interventions.

Keywords

professional engagement clinical nurse instrument development psychometric properties mixed-methods design protocol

Introduction

Human resources are pivotal to the success of any organization. Without motivated and engaged personnel, an organization risks becoming stagnant and ineffective over time. Engaged employees drive productivity, innovation, and a positive organizational culture, while a lack of motivation can lead to reduced performance and overall organizational decline. Therefore, fostering a motivated workforce is essential for maintaining a dynamic and successful organization (Sabokro et al., 2017). This is crucial in healthcare systems because they influence sustainable development in human societies due to their direct relationship with human health (World Health Organization WHO, 2018). Nurses constitute a large part of healthcare providers and play an important role in the continuity of care, promoting and maintaining health at different levels of health service provision (Sharma, 2021). Challenges at the care environment, nurse shortages, diversity of the patient population, chronic diseases, lack of resources, pressure to reduce healthcare costs, and demand for quality care have made work engagement as a vital part of nursing practice (Hisel, 2020). Schaufeli and colleagues defined work engagement as a positive, complete and work-related state of mind with three dimensions: vigor, dedication and absorption (Schaufeli & Bakker, 2003).

In an organization, work engagement is created when employees act beyond their job expectations and involve themselves physically, emotionally and mentally in their performance. Dedicated employees are usually full of energy and enthusiasm, communicate with their work in a proper way and do their best to finish their work in the best possible way. They also have a strong motivation to learn, as they are less likely to make mistakes in the work environment and rarely experience work-related accidents (Alkorashy & Alanazi, 2023; Schaufeli & Bakker, 2003).

Although empirical evidence shows that the concept of work engagement is of interest to researchers, a deeper look at the literature indicates that this phenomenon is still not fully understood (Soodani et al., 2016). The concept of work engagement has been extensively studied in the field of business and organizations, but nursing is considered a profession based on the criteria introduced by Miller et al. (1993) (Cao et al., 2023; Miller et al., 1993). Nursing is different from other jobs in various ways as nurses experience high job burnout due to the high stress caused by caring for patients and their pain and suffering, so that nearly 7% to 11.3% of nurses experience excruciating clinical burnout and 25% of them have some degree of mental burnout (Soodani et al., 2016; Woo et al., 2020). Since burnout is considered the opposite of work engagement, nurses’ work engagement can also be negatively affected by burnout. Also, long work shifts, more than one work shift per day, voluntary and involuntary overtime work, work-family conflict, and multiple nursing roles (Schaufeli, 2021) can make the concept of nurses’ work engagement different from other jobs. Nurses with higher professional engagement show a better caring role than nurses with lower engagement (Kim & Seo, 2021). Therefore, it is necessary to address the concept of professional engagement in nursing, particularly given the high levels of job burnout, especially after crises such as the COVID-19 pandemic (Giusti et al., 2024). This will help to understand and explain the concept of engagement and develop a theoretical and practical definition specific to this field. While it is crucial to modify work characteristics to reduce job burnout and stress, thereby enhancing nurses’ professional engagement, it is even more crucial to assess the effectiveness of these changes using a valid instrument (Torabinia et al., 2017). Table 1 displays a list of tools used to measure work engagement in the international literature.

Table 1.

Tools to Measure Work Engagement.

Name of the tool	Compilation year	Number of items	Number of dimensions	Scale	Target group
Lodahl & Kejnar Job (Lodahl & Kejner, 1965) Involvement Scale	1962	20 Item	2 dimensions	5-point Likert scale	Employees
Kanungo Job Involvement (Kanungo, 1982)	1982	12 Item	4 dimensions	5-point Likert scale	Employees
Edward Zvkyl Patrick Job Engagement (Ranjbar et al., 2018)	1984	20 Item	No dimension	4-point Likert scale	Employees
Utrecht Work Engagement Scale (Schaufeli & Bakker, 2003) (UWES)	2003	17 Item	3 dimensions	7-point Likert scale	Employees
Utrecht Work Engagement Scale (Schaufeli et al., 2006) (UWES-9)	2006	9 Item	3 dimensions	7-point Likert scale	Employees
Utrecht Work Engagement Scale Ultra Short (Schaufeli et al., 2017) (UWES-3)	2017	3 Item	3 dimensions	7-point Likert scale	Employees

Utrecht work Engagement Scale is the most famous one (Schaufeli et al., 2017; Torabinia et al., 2017), which has been translated and used in international studies in different countries such as Japan, Italy, Norway, Spain and Iran (Torabinia et al., 2017). However, like other tools, it is not specific to nursing and fails to capture the dynamic roles of nurses, thus overlooking some factors that influence their engagement. In the dimension of absorption, the item “I forget my surroundings while working” does not consider that in the nursing profession, roles cannot be distinguished in terms of time and place, so the nurse cannot become immersed in a task and forget other roles. The nurse must use critical thinking and clinical judgment at the same time in all care and professional levels, or for example, one of the items is “I can continue to work long hours”, which is also inconsistent with nursing standards regarding working hours.

All available tools have been designed for employees at various job levels, including managers and staff, within organizations and offices. However, nursing has unique working conditions including the importance of teamwork, a wide range of services, diverse clients (patients, families, and the society), work shift, high pressure and stress, fatigue, and a high rate of job burnout. Therefore, the concept of work engagement in nursing may differ significantly, necessitating a specialized approach. Existing tools developed for occupational contexts other than nursing encompass general aspects applicable to nursing, but they often fail to capture all dimensions of professional engagement specific to the multifaceted and interactive roles of nurses in patient and family care. Therefore, there is a recognized need to design a tool that is grounded in the unique characteristics and nuances of the nursing profession.

Aim

This research aims to develop and validate an instrument for assessing professional engagement in clinical nurses. The research objectives are:

○ Explaining nurses’ perceptions of the concept of professional engagement and determining and defining the main structures of the concept of professional engagement in nursing.

○ Compilation of relevant and suitable items with professional engagement structures in nurses to be included in a tool and assess its psychometric properties.

Method

Study Design

This is a mixed-method design employing a sequential exploratory approach, starting with an initial qualitative phase followed by a transition into a quantitative phase (Doyle et al., 2016). The philosophical basis of this research is rooted in the pragmatism approach, utilizing the advantages of both quantitative and qualitative perspectives to achieve the research goal. Using a combination of qualitative and quantitative approaches, a greater understanding of the research concept is achieved than when each one is used separately (Polit & Beck, 2020). Therefore, an engagement tool will be designed and validated to provide a comprehensive and context-specific definition of the concept, explaining professional engagement in clinical nurses and establishing both its theoretical and practical definitions. Data will be collected using semi-structured interviews that will be analyzed using qualitative content analysis with a conventional approach (Graneheim & Lundman, 2004). Next, a tool for measuring professional engagement will be designed based on the 4-stage approach of Waltz et al. (2017) consisting of the selection of a conceptual model, explication of objectives for the measure, development of a blueprint construction of the measure including administration procedures, an item set, and scoring rules and procedures (Waltz et al., 2017). Also, the psychometric properties of the tool will be evaluated consisting of validity and reliability assessments (Figure 1). This research will be reported following the guidelines for presenting findings from research on instrument and scale development and evaluation, as suggested by Streiner and Kottner (Streiner & Kottner, 2014).

Figure 1.

The Process of Developing an Instrument for Assessing Professional Engagement in Clinical Nurse.

A team of researchers specializing in instrument design, qualitative research, nursing, and biostatistics will conduct this study. Health and nursing policy makers, high and middle level nursing managers, supervisors and clinical nurses are considered key beneficiaries of this project.

The Qualitative Phase

The concept and dimensions of professional engagement in clinical nurses will be explained and the key items of the tool will be identified using a qualitative research design employing a conventional content analysis approach.

Participants will be selected using purposive sampling (Polit & Yang, 2016). Nurses with extensive knowledge and a willingness to participate in the research will be recruited. Inclusion criteria are clinical nurses in various educational levels with at least 6 months of work experience in various clinical wards in hospitals and willingness to participate in the study. Maximum variation in sampling will be employed to ensure diversity in age, gender, department, work experience, organizational position, work shift status and educational level. Therefore, the participants are gradually recruited into the study and individual face-to-face semi-structured interviews will be conducted until data saturation is reached—that is, when no new information emerges and the existing data begin to repeat.

The time and location of the interviews will be chosen based on the participants’ convenience, and all interviews will be audio-recorded. The interviews will begin with open-ended questions, allowing participants to freely and thoroughly describe their experiences related to the study phenomenon. Subsequently, the participants will be guided toward more specific questions aligned with the research aim. Examples of the questions include: ‘will you please share your experience of love and interest in the nursing profession’, ‘what does engagement mean from your perspective?’ Probing questions will be asked to improve the depth of interviews: ‘please explain more in this context’. The interviews will continue until the participants indicate that they have no further information to share. If necessary, to clarify or elaborate on responses, a follow up interview may be conducted with the same participant. In addition to audio recording, participants’ emotions, facial changes, and tone of voice will be documented during the interviews to enrich the data analysis. The data collection and data analysis will be conducted concurrently using a conventional content analysis approach. The interviews will be transcribed verbatim and read several times to gain a comprehensive understanding of their content. Meaning units and codes will be identified and created based on semantic units. Similarities and differences between the codes will be analyzed to develop categories and themes (Vaismoradi et al., 2013), which will represent the dimensions that shape the concept of professional engagement in clinical nurses and inform the structure of the tool (Graneheim & Lundman, 2004).

Trustworthiness

The accuracy of the qualitative study will be evaluated according to the Johnson’s five criteria: creditability, confirmability, dependability, transferability and authenticity (Schaufeli et al., 2006). Creditability or believability means how much the findings match the reality (Johnson & Rasulova, 2017; William et al., 2019). Allocating enough time to collect data, immersing in data, combining data sources and theories and the maximum diversity in sampling will be used to ensure credibility.

Confirmability refers to the verification of the research findings by others, ensuring that the results are consistent and can be corroborated through a transparent and systematic process (Polit & Beck, 2020; William et al., 2019). As part of peer-checking, a nurse researcher not involved in the data collection and analysis will review the findings and will provide feedback. For member-checking, a brief report of the interviews and codes will be returned to participants to ensure that their perspectives are accurately reflected. To ensure verifiability, a conscious effort wil be made to avoid influencing the data collection process and analysis based on prior assumptions.

Credibility depends on reliability (Bang, 2024). An external observer will review the study process to ensure its consistency and accuracy (Polit & Yang, 2016; Sharma, 2022). Additionally, audit trail will be conducted by an expert panel to assess the research process and provide feedbacks on the research’s accuracy. The researchers’ initial perceptions, thoughts, and analyses of the texts being studied will be documented as part of the audit trail to ensure that personal bias does not influence the research process.

Transferability refers to the extent to which the findings of the study can be applied or adapted to similar situations or contexts, allowing others to derive comparable meanings in similar settings (Polit & Yang, 2016). However, due to the nature of qualitative research, it is challenging to directly apply the findings and conclusions to other populations (William et al., 2019). In this research, diverse participants will be selected based on factors such as age, gender, workplace, education, work experience, and cultural and social conditions to enhance transferability and ensure that the findings are applicable to a broader range of contexts (Bang, 2024; Johnson & Rasulova, 2017).

Authenticity is the degree of neutrality in the presentation of the range of realities. The main driver of this principle is the need to negotiate (Johnson & Rasulova, 2017). In this process, participants’ perspectives will be respected. Measures such as purposive sampling and with maximum diversity, along with maintaining a neutral stand during the data collection and analysis, will be implemented.

The Quantitative Phase

The findings of the qualitative study will be used to develop a tool and evaluate its psychologic properties. This will involve explaining a conceptual model, outlining measurement objectives, designing a blueprint, constructing the tool with item generation, developing dimensions, and establishing a scoring rule (Johnson & Rasulova, 2017).

Preparing a Conceptual Model

The theoretical basis outlines the necessary content areas for a new tool. In this research, given the subjectivity of the concept of professional engagement, a conceptual model will be derived through an inductive method. Consequently, the final operational definitions developed from the themes identified during the conventional content analysis in the qualitative phase will serve as the foundation for extracting the items and defining the purpose of the tool.

Determining Research Objectives

Goals as a communication bridge connect theories and concepts and their measurement. In this research, the goals of the tool will be defined based on the dimensions and areas identified in the qualitative concept of professional engagement in clinical nurses.

Blueprint Design

The specific areas of the measurable dimensions of the concept will be developed in the qualitative phase through identifying and proposing the necessary items to accurately measure each structure, which will later be tested and validated.

Extracting and Generating Items

To convert the concepts and features into suitable items, the theoretical definitions of each dimension or theme will be identified based on the general definition of the concept. The practical definition of each dimension will be developed using the objective and measurable characteristics of that dimension. Based on these practical definitions, appropriate items will be generated (Polit & Yang, 2016). After conceptualizing inductively and after extracting final themes, the concept of professional engagement in clinical nurses will be explained and its nature will be determined. To enhance understanding and increase the validity of the items, the participants’ own words will be used as much as possible. A pool of items will be created and suitable items will be selected after re-examining the pool. Conceptually similar items will be merged, and the structures of the professional engagement tool will be developed and evaluated based on existing definitions in the international literature.

Psychometric Properties of the Tool

The validity and reliability of the tool for measuring professional engagement in clinical nurses will be assessed in terms of validity and reliability testing.

Face and Content Validity

Face validity refers to the degree to which a test appears logical from the perspective of respondents. For qualitative face validity, 10 participants will be asked to provide feedback on the level of difficulty, comprehensibility and clarity of each item. After summarizing and analyzing their responses, necessary revisions will be made to the tool. For quantitative face validity, participants will be asked to rate the importance of each item based on a Likert scale from 1 to 5. The impact score for each item will be calculated by multiplying its importance rating by the number of times it is repeated, providing a measure of its relevance. The percentage of participants who rate each item with a score of 4 or 5 will be calculated by multiplying the average score obtained for each item. Items with an impact factor greater than 1.5 will be considered suitable for the next stage of analysis, while items with a lower impact factor will be reconsidered or removed from the tool (Polit & Yang, 2016).

Content validity is measured both quantitatively and qualitatively. It evaluates whether the content of the instrument accurately represents the concept it is intended to measure (Polit & Yang, 2016). The number of experts to check content validity varies from two to twenty people (Roebianto et al., 2023). In this research, the opinions of 10 experts and 10 participants will be sought. To evaluate the validity of the qualitative content of the instrument, an expert panel consisting of nurse experts and human resource managers with experience in psychometrics will assess the instrument. They will review aspects such as grammar, scoring methods, transparency, and simplicity of the items. Necessary corrections will be made based on their feedback. For quantitative content validity, both the content validity ratio (CVR) and content validity index (CVI) will be calculated. For the CVR, 10 experts will be asked to comment on the necessity of the tool items based on the three-part spectrum: ‘necessary’, ‘useful but not necessary’, and ‘not necessary’. The CVR will be the number of experts who have chosen the necessary option minus half of the total number of evaluators divided by half of the total number of evaluators. According to Lawshe (1975) scores above 0.62 are considered appropriate for the CVR.

To calculate the CVI, experts will be asked to evaluate the degree of relevance of each item to the desired structure using four response options: ‘not relevant’, ‘relatively relevant’, ‘relevant’ and ‘completely relevant’. The R-CVI will be calculated by dividing the number of experts who assign a score of 3 (relevant) or 4 (completely relevant) to each item by the total number of experts. Scores higher than 0.79 are considered appropriate, while scores between 0.7 and 0.8 suggest that the revisions and corrections may be necessary for the item to better align with the intended concept. Also, the S-CVI above 0.9 will be considered acceptable. The validity index of each item will be determined using modified kappa statistic (K*), which measures the agreement between respondents or evaluators while adjusting for chance agreement. The kappa statistic ranges from −1 to +1, with a score below zero indicating that the agreement between evaluators is worse than chance agreement (Polit & Yang, 2016).

Analysis of Items

The loop method will be used for item analysis. The reliability coefficient of the entire questionnaire will be calculated, and if removing a question increases the reliability level, this indicates that the item does not contribute effectively to the overall coherence with other items, suggesting it is not suitable. The criterion for removing an item will be if its correlation with the total score is negative or less than 0.3. At this stage, the finalized tool will be provided to 50 nurses, and the correlation of each item with the total score will be measured. Items with a negative correlation or a correlation less than 0.3 will be removed.

Construct Validity

Convergent and discriminant validity as two types of construct validity will be assessed (Bang, 2024). The factor analysis method will be used to assess the differential validity of the tool. The exploratory factor analysis will be used to identify the relationships between the items and the main variable under investigation—the professional engagement in clinical nurses—as well as the constructs that make up the tool.

Sampling adequacy is evaluated using the Kaiser-Meyer-Olkin (KMO) test. Additionally, the Bartlett’s test of sphericity will be conducted to confirm that the correlation matrix, which forms the foundation of factor analysis, is equal to zero in the population. Following the calculation of the correlation matrix between variables, factors will be extracted and variables with high correlations will be grouped into categories or factors (Polit & Yang, 2016).

A minimum of 5 samples per item is necessary to assess the construct validity of an instrument using the factor analysis test. In this study, the required sample size for exploratory factor analysis will be set at 5 times the number of items on the instrument (Sharma, 2022).

Reliability

The reliability of the instrument will be assessed using two methods: internal consistency and stability. The Cronbach’s alpha method will be used, based on the same sample used for construct validity. To assess stability, the test-retest reliability method will be employed, with a two-week interval between administrations (Zare & Tagharrobi, 2023).

The Cronbach’s alpha method evaluates the appropriateness of the items in relation to the instrument’s structure. The minimum Cronbach’s alpha coefficient of 0.7 will be considered acceptable (Polit & Yang, 2016).

After calculating the standard deviation of the measurement for both the minimum difference change (MDC) index and the minimum important change (MIC) index, the percentage of the minimum detectable change will also be calculated using mean scores before and after the test. For stability, the correlation between responses will be assessed using the Pearson correlation coefficient, with a value above 0.74 considered suitable to demonstrate reliability over time.

Weighting of Items

After conducting the exploratory factor analysis to determine the factor load of each item, the factor load of each item will be multiplied by the ratio of the total variance explained by the factor on which the item is placed. To assign a weight to each item within the entire subscale, the ratio of each secondary value to the total of the secondary values will be calculated. The average weight of each item will be determined by using a fixed weight of 1 for all items and weighting the items according to their factor analysis results (Polit & Yang, 2016).

Interpretability of the Tool

It will be assessed based on the floor and ceiling effects, responsiveness, feasibility, and scoring (Kieffer et al., 2021).

Ceiling and floor effects aim to minimize response biases, which are assessed by calculating the percentage of participants who achieve the highest or lowest possible score. If the frequency of unanswered statements is between 10% and 20%, it is considered suitable. However, it is preferable to have all items answered, supported by clear explanations and justifications through examples.

Feasibility refers to the ease of the use of the tool which can be evaluated by ensuring the use of brief, understandable sentences and the short time required to respond to the items. Feasibility will be determined by calculating the relative frequency of unanswered items for each question and describing the answer of each item (Polit & Yang, 2016).

Scoring rules will be established after the items are created and organized. In most cases, the structure of the items will dictate the scoring method. The selection of appropriate response options tailored to the nature of the items and the dimensions of the questionnaire will be made in consultation with the research team and subject-matter experts, using a 5-point Likert scale. Also, a 100-point linear transformation standard will be applied to standardize the scoring (Polit & Yang, 2016). The resulting score will range from 0 to 100, with a score of zero indicating no professional engagement, and higher scores approaching 100 representing greater levels of professional engagement.

S c o r e o u t o f 100 = \frac{M i n i m u m P o s s i b l e R o w S c o r e - O p t a i n e d R o w S c o r e}{M i n i m u m P o s s i b l e R o w S c o r e - M a x i m u m P o s s i b l e R o w S c o r e}

Data Analysis

The data will be analyzed using SPSS software, applying both descriptive and inferential statistics. Exploratory factor analysis will be conducted to examine the factor structure of the nurses’ professional engagement measurement tool. This method is particularly useful when limited information is available about the factor structure, and the aim is to uncover the underlying dimensions of the construct (Kieffer et al., 2021). It allows for the identification of the number of underlying dimensions within the tool. It also helps uncover hidden variables, assess their weight, and evaluate the relationships between these variables, providing a clearer understanding of the factor structure.

Discussion

This protocol outlines a research study that aims to develop and validate a reliable and valid instrument for assessing professional engagement among clinical nurses. There is a critical link between nurse engagement and the quality of patient care. High levels of professional engagement among nurses are associated with improved patient outcomes, enhanced safety, and reduced turnover rates. To foster this engagement, measurement tools are required to identify areas for improvement and effectively boost it. By utilizing such tools, nurse managers can drive improvements in care quality, enhance patient safety, and retain skilled nursing staff (Zare & Tagharrobi, 2023).

Work engagement, a thoroughly researched concept in commercial sectors such as finance and industry, remains relatively underexplored within the healthcare field, particularly in nursing. While extensive studies have measured work engagement in areas like commercial companies and banks, the nursing profession, with its distinct demands and characteristics, has not been as thoroughly examined. Existing research largely consists of descriptive and correlational studies, and there is a notable lack of specialized tools designed to assess professional engagement within nursing. Addressing this gap is essential for developing targeted strategies to enhance nurse engagement and, consequently, improve patient care. As a result of this deficiency, nurses have been compelled to use generic tools for measuring engagement. However, experts in the field emphasize that work engagement is a crucial and enduring concept that warrants greater focus from both researchers and practitioners. They advocate for the development and use of specialized tools tailored to the unique aspects of nursing to more accurately assess and enhance professional engagement in this vital sector (Schaufeli, 2012).

To address this gap, our upcoming research aims to define and elucidate professional engagement specifically within the nursing profession, particularly within the cultural context of Iran. The findings will have implications for other healthcare settings with similar cultural and contextual characteristics, offering valuable insights that can enhance nurse engagement and improve patient care across diverse environments. Recognizing the lack of specialized tools for assessing nurses’ professional engagement, we plan to develop a valid and reliable instrument tailored to this unique setting. Our goal is to enhance patient care quality by effectively leveraging human resources through a better understanding and measurement of nurse engagement.

This study adheres to ethical principles to ensure the dignity and well-being of the participants. Prior to data collection, ethical approval will be obtained from the relevant institutional review board or ethics committee, in accordance with the Declaration of Helsinki (World Medical Association, 2025). Detailed information about the research aim and procedure will be provided to the participants, and informed consent will be obtained voluntarily before commencing the study. Confidentiality and anonymity will be strictly maintained by using de-identified data and secure data storage practices. The participants will have the right to withdraw from the study at any stage without consequences, reinforcing ethical research conduct (Tolich, 2023). In the qualitative phase, the participants’ narratives will be handled sensitively, ensuring their responses are accurately represented while protecting their identities (Dempsey et al., 2016). In the quantitative phase, data integrity will be upheld through rigorous reporting and validation procedures as well as minimizing biases using appropriate sampling and recruitment techniques (Bond et al., 2023).

Conclusion

Since the concept of engagement in nursing has not been investigated with a specific tool, this research has been planned to create a valid and reliable tool to measure the professional engagement of nurses so that it can help improve the quality of care. Designing professional engagement tools for nurses based on the social and cultural background governing the profession is an urgent and fundamental need, especially since nursing is considered a profession and not a job, and the prevalence and factors related to engagement are not known. If there is no comprehensive information about nurses’ professionalism, there will be no possibility of targeted interventions to increase the promotion of engagement. Therefore, this research, with the innovation in designing a special tool for nurses’ professional engagement, can be a practical solution to accurately assess the nurses’ engagement status, so that health policy makers can take a big step in the direction of improving mental and physical health of nurses and help promote health in the society.

Footnotes

Acknowledgments

This study is one part of the Ph.D. dissertation by the first author (S.R), and is supported by Tarbiat Modares University (decree code: IR.MODARES.REC. 1402.163).

ORCID iDs

Somayeh Rezaie

Mojtaba Vaismoradi

Ethical Statement

Author Contributions

Study design and conceptualization: SR, FA, MKH, AK, MV; data collection: SR; data analysis and interpretation: SR, FA, MKH, AK, MV; manuscript writing: SR, FA, MKH, AK, MV; study supervision: FA, MKH, MV. All authors have fully participated in the design and conceptualization of the study and have read and approved the draft version of the article.

Funding

The authors disclosed receipt of the financial support for the research and authorship of this article from Tarbiat Modares University, Tehran, Iran.

Declaration of Conflicting Interests

The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Restrictions apply to the availability of data from this research because of the anonymity of the participants and confidentiality matters.*

Appendix

References

Alkorashy

Alanazi

(2023). Personal and job-related factors influencing the work engagement of hospital nurses: A cross-sectional study from Saudi Arabia. Healthcare, 11(4), 572. https://doi.org/10.3390/healthcare11040572

Bang

T. C.

(2024). Applied linguistics and language education research methods: Fundamentals and innovations. IGI Global.

Bond

Fox

Wise

Heaton

(2023). Quantitative assessment of systematic bias: A guide for researchers. Journal of Dental Research, 102(12), 1288–1292. https://doi.org/10.1177/00220345231193314

Cao

Song

Chen

Wang

Yang

(2023). What is nursing professionalism? A concept analysis. BMC Nursing, 22(1), 34. https://doi.org/10.1186/s12912-022-01161-0

Dempsey

Dowling

Larkin

Murphy

(2016). Sensitive interviewing in qualitative research. Research in Nursing & Health, 39(6), 480–490. https://doi.org/10.1002/nur.21743

Doyle

Brady

A.-M.

Byrne

(2016). An overview of mixed methods research–revisited. Journal of Research in Nursing, 21(8), 623–635. https://doi.org/10.1177/1744987116674257

Giusti

E. M.

Ferrario

M. M.

Veronesi

D'amato

Gianfagna

Iacoviello

(2024). Perceived work stressors and the transition to burnout among nurses in response to the pandemic: Implications for healthcare organizations. Scandinavian Journal of Work, Environment & Health, 50(3), 158–167. https://doi.org/10.5271/sjweh.4148

Graneheim

U. H.

Lundman

(2004). Qualitative content analysis in nursing research: Concepts, procedures and measures to achieve trustworthiness. Nurse Education Today, 24(2), 105–112. https://doi.org/10.1016/j.nedt.2003.10.001

Hisel

M. E.

(2020). Measuring work engagement in a multigenerational nursing workforce. Journal of Nursing Management, 28(2), 294–305. https://doi.org/10.1111/jonm.12921

10.

Johnson

Rasulova

(2017). Qualitative research and the evaluation of development impact: Incorporating authenticity into the assessment of rigour. Journal of Development Effectiveness, 9(2), 1–14. https://doi.org/10.1080/19439342.2017.1306577

11.

Kanungo

R. N.

(1982). Measurement of job and work involvement. Journal of Applied Psychology, 67(3), 341–349. https://doi.org/10.1037//0021-9010.67.3.341

12.

Kieffer

J. M.

Starreveld

D. E.

Boekhout

Bleiker

E. M.

(2021). A questionable factor structure of the multidimensional fatigue inventory in the general Dutch population. Journal of Clinical Epidemiology, 137, 266–276. https://doi.org/10.1016/j.jclinepi.2021.05.005

13.

Kim

Seo

(2021). Impact of job engagement on the quality of nursing services: The effect of person-centered nursing in South Korean nurses. Healthcare, 9(7), 826. https://doi.org/10.3390/healthcare9070826

14.

Miller

B. K.

Adams

Beck

(1993). A behavioral inventory for professionalism in nursing. Journal of Professional Nursing: Official Journal of the American Association of Colleges of Nursing, 9(5), 290–295. https://doi.org/10.1016/8755-7223(93)90055-h

15.

Polit

Beck

(2020). Essentials of nursing research: Appraising evidence for nursing practice (10th Edition). Lippincott Williams & Wilkins.

16.

Polit

D. F.

Yang

F. M.

(2016). Measurement and the measurement of change: A primer for the health professions. New York: Wolters Kluwer.

17.

Ranjbar

Yazdanpanah

Jeihooni

A. K.

(2018). The relationship between issues related to occupational attachment of nurses in health and medical centers of Estahban City. Journal of Pharmaceutical and Biological Sciences, 6(1), 11–15. https://doi.org/10.18231/2320-1924.2018.0003

18.

Roebianto

Savitri

S. I.

Aulia

Suciyana

Mubarokah

(2023). Content validity: Definition and procedure of content validation in psychological research. TPM, 30(1), 5–18. https://doi.org/10.4473/TPM30.1.1

19.

Sabokro

Allahyari

Ebrahimzadehpezeshki

(2017). Job burnout in nurses and its impact on their negligence. Nursing and Midwifery Journal, 15(2), 86–94. http://unmf.umsu.ac.ir/article-1-2998-en.html.

20.

Schaufeli

(2012). Work engagement: What do we know and where do we go? Romanian journal of applied psychology, 14(1), 3–10.

21.

Schaufeli

(2021). The burnout enigma solved? Scandinavian Journal of Work, Environment & Health, 47(3), 169–170. https://doi.org/10.5271/sjweh.3950

22.

Schaufeli

Bakker

(2003). Utrecht Work Engagement Scale: Preliminary Manual. UWES. Occupational Health Psychology Unit Utrecht University.

23.

Schaufeli

W. B.

Bakker

A. B.

Salanova

(2006). The Measurement of Work Engagement With a Short Questionnaire: A Cross-National Study. Educational and Psychological Measurement, 66(4), 701–716. https://doi.org/10.1177/0013164405282471

24.

Schaufeli

W. B.

Shimazu

Hakanen

Salanova

De Witte

(2017). An ultra-short measure for work engagement: The UWES-3 Validation Across Five Countries. European Journal of Psychological Assessment, 35(4), 577–591. https://doi.org/10.1027/1015-5759/a000430

25.

Sharma

(2021). Potter and Perry’s fundamentals of nursing: Third South Asia edition EBook. Elsevier Health Sciences.

26.

Sharma

(2022). Nursing research and statistics-E-book (2th Edition). Elsevier Health Sciences.

27.

Soodani

Mostafavirad

Chinaveh

(2016). Assessing the simple and multiple relationships between individual and organizational variables and job involvement among nurses. Quarterly Journal of Nursing Management, 4(3), 42–53. http://ijnv.ir/article-1-333-en.html.

28.

Streiner

D. L.

Kottner

(2014). Recommendations for reporting the results of studies of instrument and scale development and testing. Journal of Advanced Nursing, 70(9), 1970–1979. https://doi.org/10.1111/jan.12402

29.

Lawshe

C. H.

(1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x.

30.

Lodahl

T. M.

Kejner

(1965). The definition and measurement of job involvement. Journal of Applied Psychology, 49(1), 24–33. https://doi.org/10.1037/h0021692

31.

Tolich

In: Poff, D.C., Michalos, A.C. (eds) . (2023). Anonymity, confidentiality and de-identified data. Encyclopedia of business and professional ethics. Springer.

32.

Torabinia

Mahmoudi

Dolatshahi

Abyaz

M. R.

(2017). Measuring engagement in nurses: The psychometric properties of the Persian version of utrecht work engagement scale. Medical Journal of the Islamic Republic of Iran, 31(1), 83–89. https://doi.org/10.18869/mjiri.31.15

33.

Vaismoradi

Turunen

Bondas

(2013). Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study. Nursing and Health Sciences, 15(3), 398–405. https://doi.org/10.1111/nhs.12048

34.

Waltz

C. F.

Strickland

Lenz

E. R.

(2017). Measurement in nursing and health research (5th Edition). Springer Publishing Company.

35.

William

A. P.

Parker

Singe

S. M.

Potteiger

(2019). Qualitative research in the health professions (1st Edition). New York: Taylor & Francis.

36.

Woo

Tang

Tam

(2020). Global prevalence of burnout symptoms among nurses: A systematic review and meta-analysis. Journal of Psychiatric Research, 123, 9–20. https://doi.org/10.1016/j.jpsychires.2019.12.015

37.

World Health Organization (WHO) (2018). A vision for primary health care in the 21st century: Towards universal health coverage and the sustainable development goals. World Health Organization.

38.

World Medical Association (2025). World Medical Association Declaration of Helsinki: ethical principles for medical research involving human participants. JAMA, 333(1), 71–74. https://doi.org/10.1001/jama.2024.21972

39.

Zare

Tagharrobi

(2023). The framework of designing, reporting, and evaluating the methodological quality for psychometric studies: The revised COSMIN checklists. Qom University of Medical Sciences Journal, 16(10), 786–803. https://doi.org/10.32598/qums.16.10.2751.1

Designing and Psychometric Properties Evaluation of the Tool for Measuring Professional Engagement in Clinical Nurses: Protocol of a Mixed-Methods Study

Abstract

Keywords

Introduction

Aim

Method

Study Design

The Qualitative Phase

Trustworthiness

The Quantitative Phase

Preparing a Conceptual Model

Determining Research Objectives

Blueprint Design

Extracting and Generating Items

Psychometric Properties of the Tool

Face and Content Validity

Analysis of Items

Construct Validity

Reliability

Weighting of Items

Interpretability of the Tool

Data Analysis

Discussion

Conclusion

Footnotes

Acknowledgments

ORCID iDs

Ethical Statement

Author Contributions

Funding

Declaration of Conflicting Interests

Data Availability Statement

Appendix

References