Development and Validation of a Multidimensional Tool to Assess Nurses’ Clinical Decision-Making

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While various tools have been developed to assess decision-making skills in healthcare providers, a comprehensive, validated tool specifically for nurses' clinical decision-making is lacking. This study aims to develop and validate a multidimensional tool designed to assess nurses’ clinical decision-making. Methods The tool was developed through an extensive literature review, interviews with nurses, and expert consultations. A sample of 200 Iranian nurses participated in the validation process. Face validity and content validity were assessed using expert feedback and the Content Validity Index (CVI) and Content Validity Ratio (CVR). Construct validity was evaluated using Confirmatory Factor Analysis (CFA), while reliability was assessed through internal consistency (Cronbach’s alpha) and stability (Intraclass Correlation Coefficient - ICC). Results The final tool includes 40 items across six dimensions: Identification and Definition of Problem, Data Collection, Data Processing, Identifying and Evaluating Options, Selecting the Best Option, Planning for Action, and Implementation and Re-evaluation. The CVI was 0.95, and the CVR was 0.78, indicating strong content validity. CFA confirmed a six-factor structure with good model fit (Chi-square/df = 1.586, RMSEA = 0.054). The tool demonstrated excellent reliability, with a Cronbach’s alpha of 0.937 and an ICC indicating stability. Conclusions This newly developed tool provides a reliable, valid, and multidimensional measure for assessing nurses' clinical decision-making abilities. It can be used in clinical practice and research to better understand this critical skill, contributing to improved patient care and safety. Clinical Decision-Making Nurses Human Factor Validation Factor Figures Figure 1 Introduction Clinical decision-making is a fundamental aspect of professional nursing practice. It extends beyond the application of theoretical knowledge, involving the ability of nurses to systematically evaluate patient data, consider relevant evidence, and make informed, patient-centered decisions about care and treatment [ 1 , 2 ]. Nurses’ decisions, from selecting medication routes to planning complex care in critical units, directly impact patient safety, treatment outcomes, and the overall effectiveness of healthcare systems [ 3 , 4 ]. The quality of these decisions is crucial to providing safe, effective, and patient-centered care [ 1 ] . The dynamic healthcare environment requires nurses to apply sound clinical judgments to address patient needs within a multidisciplinary team framework [ 5 ]. Barriers to clinical decision-making are often categorized into three main groups: Professional Factors (knowledge, skills, emotional stress); Organizational and Environmental Factors (inefficient management, poor resources, socio-cultural constraints); and Interpersonal Factors (team conflicts, poor communication) [ 6 – 8 ] . Given the critical role of clinical decision-making in nursing, there is an increasing need for reliable, standardized instruments to measure this skill. Extensive research has been dedicated to developing and validating assessment tools to accurately measure nurses’ decision-making abilities, such as the widely used Clinical Decision-Making Questionnaire by Laurie et al. [ 9 ]. A study by Moradi and Sharifi highlighted the diversity of methods used to assess clinical decision-making among Iranian nurses, including Laurie's Questionnaire, the Participation in Decision Activities Questionnaire (PDAQ), and various researcher-made tools. The findings consistently pointed to a predominant use of analytical-intuitive or interpretive-intuitive decision-making approaches.[ 10 ] Given the complexity of clinical decision-making and the various influencing factors, accurately assessing this ability is essential for identifying nurses' cognitive strengths and weaknesses. This allows for the design of targeted educational programs and interventions to enhance their decision-making skills [ 11 , 12 ]. Moreover, a valid and reliable assessment tool is crucial for healthcare managers and policymakers to evaluate current educational programs, anticipate future training needs, and ultimately improve patient safety and care quality. Without such tools, evaluating and improving nurses’ decision-making capabilities becomes a significant challenge. Despite substantial efforts in this area, a gap remains for a comprehensive, standardized, and validated instrument that can assess all dimensions of nurses’ clinical decision-making within their professional and cultural context [ 13 ]. Existing instruments, such as the Laurie Questionnaire, CDMNS, and NDMI, primarily focus on cognitive or analytical models, often overlooking the cultural and professional realities of nursing practice in Iran. These limitations highlight the need for a comprehensive, culturally aligned instrument that can assess all aspects of the decision-making process. In this regards, the primary objective of this study is to design and validate a reliable, comprehensive, and culturally appropriate instrument to evaluate nurses’ clinical decision-making skills. The innovation of this tool lies in its multidimensional and localized approach, incorporating factors critical to the local context, such as unique working conditions, emerging technologies, and inter-departmental interactions. The development process combines qualitative and quantitative methods, including literature review, expert interviews, and advanced statistical validation. The resulting instrument is expected to make a significant contribution to nursing education, research, and management, thereby enhancing the quality of care and patient outcomes. Materials and Methods Study design and participants This study was conducted in 2024/2025 using a mixed-methods sequential exploratory design, focusing on the development and validation of a new instrument to assess nurses' clinical decision-making. The study comprised two phases: a qualitative phase to identify factors influencing clinical decision-making through literature review, field observations, and expert opinions, followed by a quantitative phase to evaluate the psychometric properties of the instrument.The study population consisted of nurses employed at a teaching hospital affiliated with Shahid Beheshti University of Medical Sciences in Tehran. To ensure an adequate sample size for Confirmatory Factor Analysis (CFA), 200 nurses were selected using stratified random sampling. This method ensured proportional representation across age groups, genders, and years of experience.Inclusion criteria required participants to be actively employed, with at least one year of clinical experience in various hospital units, a Bachelor's degree in nursing or higher, and the ability to provide informed consent. Nurses with less than one year of experience or those unwilling to continue participation were excluded. Additionally, questionnaires with more than 10% of missing responses or those not completed within the specified time frame were excluded from the analysis. Design of the questionnaire items In the first stage, the research team identified factors influencing clinical decision-making by studying all hospital units. Based on prior research and a review of relevant articles, these factors were categorized into four groups: nurse characteristics, patient characteristics, environmental factors, and organizational determinants. A 14-member expert panel, including specialists from occupational health, medicine, nursing, and ergonomics, was formed. The panel reached a consensus to design the preliminary framework of the questionnaire, which consisted of 41 items across six domains: problem identification and definition, data collection, data processing, identifying and evaluating options, action planning, and decision implementation and re-evaluation Face and content validity To establish face and content validity, the instrument was reviewed by the expert panel to assess the wording, grammar, and item allocation. Revisions were made based on expert feedback. Additionally, the questionnaire was presented to five nurses with diverse experience to identify any ambiguities. The questionnaire was revised based on their feedback, including rewording questions, modifying options, and adjusting explanations. The responses were formatted using a 5-point Likert scale: Very Low, Low, Moderate, High, and Very High. A higher score indicated a higher level of clinical decision-making. Content validity was assessed using two indices: the Content Validity Ratio (CVR) and the Content Validity Index (CVI). Items with a CVR greater than 0.51 (for 14 experts) were considered acceptable, and items with a CVI greater than 0.79 were confirmed as valid. [ 15 – 16 ]. Construct Validity To assess construct validity, Confirmatory Factor Analysis (CFA) was employed. CFA is an advanced statistical technique used to test theoretical models and evaluate their compatibility with the data. Unlike Exploratory Factor Analysis (EFA), which is data-driven, CFA allows for testing the alignment of a hypothesized model with the observed data. Several indices were used to evaluate model fit, including the Chi-Square/Degrees of Freedom Ratio (χ²/df) and the Root Mean Square Error of Approximation (RMSEA). A χ²/df ratio of 2 or less indicated a good fit, while RMSEA values below 0.08 were considered acceptable, and values under 0.05 indicated a very good fit [ 17 ]. Reliability Reliability was evaluated using Cronbach’s alpha to determine the internal consistency of the instrument. A Cronbach’s alpha value of 0.58 or higher is generally considered satisfactory. In this study, Cronbach’s alpha was calculated to assess the reliability of the entire instrument and its subscales.[ 18 ]. Ethical Considerations The study was approved by the Research Ethics Committee of Shahid Beheshti University of Medical Sciences (IR.SBMU.PHNS.REC.1403.106). Informed verbal consent was obtained from all participants, ensuring their voluntary participation. The confidentiality of participants' data was maintained, and they were informed of their right to withdraw from the study at any stage without any consequences. Data collection &Statistical Analyses Data were collected anonymously through face-to-face interviews, ensuring participants' privacy. The data were analyzed using SPSS version 25 and AMOS 23 software for statistical analysis and CFA, respectively. Results The statistical population of the study consisted of 200 nurses( 140 female and 60 male). The mean and standard deviation of age were (35.38 ± 7.47) and work experience (1.32 ± 2.55). Other characteristics are presented below (Table 1 ). Table 1 Demographic Characteristics of the Nurses Participating in the Study (N = 200) Variable Category Frequency (N) Percentage (%) Marital Status Single Married 62 138 31 69 Education Bachelor's (BSc) Master's (MSc) Doctorate (PhD) 169 29 2 84.5 14.5 1 Number of Children 0 1 2 3 118 42 36 4 59 21 18 2 Type of Employment Official (permanent) Official (temporary) Contract 126 33 41 63 16.5 20.5 Shift Type Day Shift Night Shift Rotating 73 50 77 36.5 25 38.5 Tool validity To ensure the instrument’s validity, the face validity of the questionnaire was initially established with revisions based on expert and nurse feedback, which resulted in high scores for all items. Subsequently, content validity was assessed using expert opinions. The results demonstrated that the overall mean CVI was 0.95 and CVR was 0.78; both values were substantially higher than their minimum acceptable thresholds. Furthermore, the quantitative results for face validity indicated that all questions achieved a high validity score in this section. CFA was utilized to examine the factorial structure of the proposed measurement model, which consisted of 6 domains and 41 items. Before performing the factor analysis, the correlation coefficient between the score of each item and the total score within its respective dimension was examined. The findings from the initial CFA model revealed that the factor loading of one item (Item 37) in the Implementation and Re-evaluation domain was lower than the predetermined cut-off point. This item lacked the necessary discriminatory power to measure the intended dimension and consequently contributed to a low overall Cronbach's Alpha. Therefore, this item was deleted, resulting in the development of an optimal model with high reliability. The for the CFA model, along with the standardized factor loadings of the items, is presented in Fig. 1 . All factor loadings for the items across the six examined domains were statistically significant, confirming the construct validity of the instrument. (Table 2 ). Table 2 Goodness-of-Fit Indices of the Nurses' Clinical Decision-Making Questionnaire Model fit index Modified model Chi-square 1150.11 degrees of freedom 725 Chi-square/degrees of freedom (χ2/df) 1.586 Root mean square error of approximation 0.054 Goodness-of-fit index 0.911 Reliability Internal consistency was examined using Cronbach's Alpha for the total scale and each domain. The total scale demonstrated excellent reliability (α = 0.937), while subscale values ranged from 0.67 to 0.82, indicating acceptable to good reliability across domains. Measurement stability was further confirmed using the Intraclass Correlation Coefficient (ICC), which showed results consistent with Cronbach's Alpha (Table 3 ). The final validated instrument for assessing nurses’ clinical decision-making is provided in Table 4 . Table 3 Results of the Instrument's Reliability Based on Cronbach's Alpha and ICC Dimension Item Corrected Item-total Correlation Cronbach’s Alpha if Item Deleted Cronbach’s (CI 95%) Alpha Identification and Definition of Problem q1 0.35 0.79 0.798 (0.75–0.83) q2 0.57 0.76 q3 0.38 0.79 q4 0.44 0.78 q5 0.55 0.77 q6 0.60 0.76 q7 0.50 0.77 q8 0.51 0.77 q9 0.47 0.78 Data Collection q10 0.57 0.70 0.766 (0.70–0.81) q11 0.69 0.63 q12 0.63 0.66 q13 0.38 0.79 Data Processing q14 0.57 0.79 0.823( 0.78–0.85) q15 0.62 0.79 q16 0.59 0.79 q17 0.63 0.79 q18 0.47 0.81 q19 0.60 0.79 q20 0.44 0.81 q21 0.42 0.81 Identifying, Evaluating Options, and Selecting the Best Option q22 0.56 0.69 0.738 (0.67–0.78) q23 0.26 0.85 q24 0.56 0.69 q25 0.63 0.68 q26 0.49 0.70 q27 0.54 0.69 q28 0.60 0.68 q29 0.56 0.69 Planning for Action q30 0.61 0.76 0.809 (0.76–0.84) q31 0.64 0.76 q32 0.61 0.76 q33 0.56 0.78 q34 0.50 0.79 q35 0.48 0.79 Implementation and Re-evaluation q36 0.55 0.84 0.844 (0.80–0.87) q37 0.71 0.79 q38 0.71 0.79 q39 0.78 0.77 q40 0.51 0.84. Table 4 The final Questionnaire for the Evaluation of Nurses' Clinical Decision-Making Dimensions Items Identification and Definition of Problem 1. How skillful are you in identifying patients' clinical issues (e.g., abnormal vital signs, pain, or behavioral changes)? 2. How skillful are you in identifying the early signs of significant diseases and disorders in patients before the manifestation of clinical problems? 3. How confident are you in the accuracy of your diagnoses concerning patients' problems? 4. To what extent do you utilize specialized tools (e.g., sphygmomanometer, pulse oximeter, etc.) and credible scientific resources (such as checklists and databases) in the process of problem diagnosis? 5. To what extent do you utilize clinical knowledge informed by the latest scientific evidence to explain and interpret patient symptoms? 6. To what extent do you utilize your communication skills (e.g., active listening and empathy) to identify patients' problems? 7. To what extent do you utilize the opinions and experiences of your colleagues to enhance the diagnostic and decision-making process? 8. To what extent are you able to align care practices with the patient's cultural and religious values? 9. How skillful are you in identifying problems that may stem from the family's influence on the patient's condition (e.g., family pressure to select specific treatment methods)? Data Collection 10. How skillful are you in gathering comprehensive and accurate data regarding the patients' clinical status? 11. How skillful are you in the Regular use of various tools and methods for clinical data collection (e.g., interviews, physical examination, checklists, assessment forms, and observation)? 12. How skillful are you in identifying and prioritizing the collected information relevant to the patient's condition for care decision-making? 13. How skillful are you in the accurate and timely recording of patient information within documentation systems (electronic or paper)? Data Processing 14. How skillful are you in processing and interpreting the patient care data? 15. How skillful are you in integrating various patient data to form a comprehensive picture of their condition? 16. How skillful are you in comparing trends in changes between the patient's current and previous care data? 17. How skillful are you in identifying and separating crucial information from irrelevant data for clinical decision-making? 18. How skillful are you in utilizing electronic tools (e.g., Electronic Health Records) for data processing? 19. To what extent do you utilize various sources of information (such as laboratory results, medical reports) to interpret the patient's condition? 20. How skillful are you in processing data while considering the patient's cultural limitations (e.g., reluctance to disclose certain information)? 21. How skillful are you in utilizing information provided by the patient's family and significant others in data processing? Identifying, Evaluating Options, and Selecting the Best Option 22. How skillful are you in identifying appropriate available care methods (e.g., pharmacological treatments, patient education, or vital signs monitoring) for the patient? 23. How skillful are you in accurately evaluating the benefits and drawbacks of each care method and their potential outcomes? 24. How skillful are you in prioritizing care options based on each patient's specific needs and scientific evidence? 25. How skillful are you in selecting the best care methods, considering scientific evidence, the patient's opinion, and their values? 26. How skillful are you in making decisions in ambiguous and emergency situations with limited information? 27. How skillful are you in establishing effective communication with the patient and their family for participation in the care decision-making process? 28. How skillful are you in selecting care methods that account for the patient's religious or cultural limitations (e.g., reluctance to use certain therapeutic approaches)? 29. How skillful are you in clinical decision-making while considering patient family pressure (e.g., family preference for specific treatment methods)? Planning for Action 30. How skillful are you in designing care plans that adhere to the latest national guidelines while addressing patients' specific needs and circumstances? 31. How skillful are you in adapting the treatment plan to the patient's condition and available resources while maintaining the quality of care? 32. How skillful are you in collaborating effectively with other members of the care team to integrate the patient's clinical plan? 33. How skillful are you in the accurate and complete documentation of the care plan and patient progress? 34. How skillful are you in planning therapeutic interventions while considering the patient's religious or cultural limitations (e.g., fasting or reluctance to use certain treatment methods)? 35. How skillful are you in collaborating with the patient's family for care planning (e.g., providing instruction for home care)? Implementation and Re-evaluation 36. How skillful are you in the accurate implementation of treatment plans (e.g., administering medications, performing nursing interventions, and adhering to protocols) while considering the patient's individual needs? 37. How skillful are you in the continuous assessment of the patient and implementing necessary changes to the treatment plan, based on the evaluation results? 38. How skillful are you in the accurate documentation of care intervention evaluation results? 39. How skillful are you in identifying factors influencing the success or failure of the treatment plan and analyzing their causes? 40. To what extent do you utilize feedback from the patient and their family to improve the quality of care and your own performance? 1 = Very Low, 2 = Low,3 = Moderate,4 = High, 5 = Very High. Response Discussion The present study aimed to develop and validate an instrument for assessing nurses' clinical decision-making (CDM). Given the pivotal role of nursing decisions in ensuring patient safety and healthcare quality, there is a clear need for a reliable tool to evaluate nurses' competencies and educational needs [ 19 , 20 ]. A robust mixed-method design was employed, following the COSMIN checklist recommendations for new measurement instruments [ 21 ]. The developed questionnaire exhibits structural and conceptual similarities with standardized tools such as the CDMN-S and NDMI [ 9 , 22 ]; however, it also incorporates critical distinctions tailored to the cultural, social, and professional context of Iranian nurses. These include cultural adaptation, consideration of specific working conditions, attention to emerging technologies, and an emphasis on inter-sectoral interactions. Expert input from medical, occupational health, and nursing professionals was incorporated throughout item development and reduction, ensuring the final instrument was concise and relevant [ 23 ]. Face validity assessment confirmed that all items were fully endorsed by nurses, the primary stakeholders, while quantitative and theoretical evaluations demonstrated high-quality items. Content validity was also confirmed using standard indices (CVI and CVR), with all items exceeding cutoff thresholds, highlighting the value of expert involvement in enhancing the precision and quality of the instrument [ 24 , 25 ]. CFA validated the six-domain structure: Identification and Definition of Problem, Data Collection, Data Processing, Identifying and Evaluating Options, Selecting the Best Option, Planning for Action, and Implementation and Re-evaluation. Standardized factor loadings (Q1–Q40) were statistically significant, with most exceeding 0.5, supporting convergent validity. High but sub-maximal inter-factor correlations indicated conceptual overlap without compromising discriminant validity. Unique dimensions reflecting inter-sectoral interactions, novel technology use, and sociocultural considerations underscore the instrument’s indigenous focus and relevance to contemporary practice. Reliability analyses demonstrated excellent internal consistency, with high Cronbach's Alpha values for the total scale and subdomains, indicating cohesive item performance and confirming data reliability. Compared to existing instruments, particularly translated tools, this instrument shows superior validity and reliability, mitigating semantic and cultural limitations often encountered in non-Western clinical settings [ 26 , 27 ]. Strengths and Limitations The instrument effectively captured all hypothesized concepts with high factor loadings, owing to its localized focus on clinical scenarios and terminology. This approach maximized content and face validity and minimized irrelevant variance. Limitations include the cross-sectional design and data collection from a single city and academic-medical center, as well as potential social desirability bias from self-reported responses, though anonymity was ensured. Future studies should employ longitudinal designs and broader sampling across multiple regions. Conclusion The findings derived from the development, validation, and reliability phases strongly support an authentic and reliable instrument for evaluating the clinical decision-making of nurses, which has been specifically tailored to the cultural context and working environment of Iranian nurses. The significance of this instrument lies in its capacity to provide an authentic and accurate depiction of nurses' competencies within the decision-making process—an advantage that standard international tools like the NDMI and CDMNS may lack due to cultural and environmental discrepancies. Consequently, this questionnaire can be utilized as a strong reference tool for nursing managers and clinical educators to systematically assess and monitor the decision-making competence of personnel, thereby is expected to contribute significantly to enhancing patient safety and improving the quality of care throughout the country's healthcare system. Abbreviations CVI Content Validity Index CVR Content Validity Ratio CFA Confirmatory Factor Analysis PDAQ Participation in Decision Activities Questionnaire CDMNS Clinical Decision-Making in Nursing Scale NDMI Nursing Decision-Making Instrument EFA Exploratory Factor Analysis RMSEA Root Mean Square Error of Approximation ICC Intraclass Correlation Coefficient CDM Nurses' Clinical Decision-making Declarations Ethics approval and consent to participate The study was approved by the Research Ethics Committee of Shahid Beheshti University of Medical Sciences (IR.SBMU.PHNS.REC.1403.106). All procedures adhered to institutional, national, and Helsinki Declaration ethical standards.All participants provided written informed consent for participation in the study. Clinical trial number : not applicable Competing interests The authors declare no competing interests. Availability of data and materials Data supporting the findings are available from the corresponding author upon reasonable request; they are not publicly available due to privacy and ethical restrictions. Funding This research received no specific grant from any funding agency. Authors’ contributions All authors read and approved the final manuscript. V.F., M.Gh., H.R., and R.Z. contributed to conceptualization, project administration, formal analysis, and original draft writing. H.M. and A.S. contributed to methodology and review/editing . Professional language and style editing was assisted using artificial intelligence tools. Acknowledgements The authors would also like to thank all the participants for taking time to participat References Zainal NH, et al. Critical Thinking and Clinical Decision Making Among Registered Nurses in Clinical Practice: A Systematic Review and Meta-Analysis. Nurs Rep. 2025;15(5):175. Latifi N, Roohi G, Tatari M. Nurses’ clinical decision-making models in the care of older adults: A cross-sectional study, in 2. 2024. Patrician PA, et al. Quality and safety in nursing: recommendations from a systematic review. J Healthc Qual (JHQ). 2024;46(4):203–19. Parveen Z et al. The Impact of Nurses Clinical Decisions on Patient Safety and Quality of Care: Nurses' Clinical Decisions on Patient Safety and Quality of Care. NURSEARCHER (Journal Nurs Midwifery Sciences), 2025: pp. 31–6. Abu Arra AY, et al. The factors influencing nurses’ clinical decision-making in emergency department. INQUIRY: J Health Care Organ Provis Financing. 2023;60:00469580231152080. Bijani M, et al. Major challenges and barriers in clinical decision-making as perceived by emergency medical services personnel: a qualitative content analysis. BMC Emerg Med. 2021;21(1):11. Gholipour M et al. Challenges of Clinical Decision-making in Emergency Nursing: An Integrative Review. Open Nurs J, 2025. 19(1). Eftekharian F, et al. Explaining the experiences of internal medicine department assistants of Jahrom University of Medical Sciences regarding the factors and obstacles affecting clinical decision-making: a qualitative study. Pars J Med Sci. 2023;21(3):1–10. Lauri S, Salanterä S. Developing an instrument to measure and describe clinical decision making in different nursing fields. J Prof Nurs. 2002;18(2):93–100. Moradi T, Sharifi, Kh. Clinical decision making in Iranian nurses: systematic review. Q J Nurs Manage. 2022;11:2. Arkan B, et al. Clinical decision-making levels of nursing students and affecting factors. Cyprus Journal of Medical Sciences; 2023. Matsumoto K, et al. Factors influencing multidisciplinary clinical decision-making in the critical care unit: a systematic review and mixed-methods meta-synthesis. BJA Open. 2025;16:100488. Lavoie P, et al. Measurement properties of self-reported clinical decision-making instruments in nursing: a COSMIN systematic review. Int J Nurs Stud Adv. 2023;5:100122. Ten Ham W, et al. An integrative literature review of the factors that contribute to professional nurses and midwives making sound clinical decisions. Int J Nurs Knowl. 2017;28(1):19–29. Lawshe CH. A quantitative approach to content validity. Personnel Psychol. 1975;28:563–75. Kalteh HO, Mortazavi SB, Mohammadi E, Salesi M. Psychometric properties of the Persian version of Neal and Griffin’s safety performance scale. Int J Occup Saf Ergon. 2021;27:41–7. Nazari M, et al. Development and validation of the tool for the evaluation of the behavioral factors affecting the prevalence of musculoskeletal disorders in Iranian students. BMC Pediatr. 2020;20(1):551. Taber KS. The use of Cronbach’s alpha when developing and reporting research instruments in science education. Res Sci Educ. 2018;48(6):1273–96. Shabestari MM et al. Nurses’ perception of uncertainty in clinical decision-making: A qualitative study. Heliyon, 2024. 10(16). Ghazi SF, Mashayekhi M, Asgari P. Iranian Intensive Care Unit Nurses' Experience of Patient Safety Culture: A Qualitative Study. Iran J Nurs. 2024;37(149):210–25. Mokkink LB et al. COSMIN Study Design checklist for Patient-reported outcome measurement instruments. Amsterdam, The Netherlands, 2019. 2019: pp. 1–32. Jenkins HM. A research tool for measuring perceptions of clinical decision making. J Prof Nurs. 1985;1(4):221–9. Akbari M, et al. Development and validation of a resilience skills questionnaire for health sector professionals based on social cognitive theory. Biomed Res Int. 2024;2024(1):5660620. Jalali O, et al. Validation of the Oswestry disability index in adult spinal deformity. Spine. 2024;49(10):682–8. Bahmaniar S, Amirfakhraie A, Zarei E. The Development and Validation of a Job Burnout Questionnaire for Iranian Nurses: A Case Study of Nurses Working in Hormozgan Province. J Crit Care Nurs. 2025;17(3):37–48. Ulku HH, Saracaloglu AS. Development and Validation of a Clinical Decision-Making Scale for Medical Students. The Medical Bulletin of Haseki; 2024. Bae J, et al. Development of the clinical reasoning competency scale for nurses. BMC Nurs. 2023;22(1):138. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8747707","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":602771751,"identity":"9f2b97be-e4c4-45e7-b51c-f5d40485bf51","order_by":0,"name":"Vafa Feyzi","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Vafa","middleName":"","lastName":"Feyzi","suffix":""},{"id":602771753,"identity":"177f1f1a-3b39-4a3c-8c51-f29e0651606d","order_by":1,"name":"Hamidreza Mokarami","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIiWNgGAWjYBACAyA+wAPlMDaASGbmA1AW8VrYEghqYUDVwsBjgFeLOfvpxANv99jY8zdwJz6cUXNPXred55vEzx02cgzsh49uwKLFsid3w8E5z9KYJQ7wbjbccKzYcNth3m2SvWfSjBl40tJuYHPYgdwNh3kOHGZjOABU+YAtgRGkRYK37XBigwSPGVYt59+CtPznkQdr+Zdgv+0wzzPJv/i03ADbckDCAKRlY1tCIlALmzReW268BfrlQLKB4WGgX2b2JSRvO8xmbC3blmbMhssv53M3f3hzwM5e7njvxoc93xJst50//PDm2zYbOX72w8ewaUEAZgSTRQJEsuFVjq77AymqR8EoGAWjYNgDAJ8bb8yMazMBAAAAAElFTkSuQmCC","orcid":"","institution":"Shiraz University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Hamidreza","middleName":"","lastName":"Mokarami","suffix":""},{"id":602771755,"identity":"f4935b89-d15c-455c-bd6a-69b72a41c490","order_by":2,"name":"Rezvan Zendehdel","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Rezvan","middleName":"","lastName":"Zendehdel","suffix":""},{"id":602771757,"identity":"40bac651-fd46-4edf-b786-fcc48174513a","order_by":3,"name":"Mehran Ghaffari","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mehran","middleName":"","lastName":"Ghaffari","suffix":""},{"id":602771759,"identity":"77072a80-344d-4752-ba48-f49cfc3e877e","order_by":4,"name":"Ali Salehi Sahlabadi","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"Salehi","lastName":"Sahlabadi","suffix":""}],"badges":[],"createdAt":"2026-01-31 07:53:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8747707/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8747707/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104374839,"identity":"e1223c4b-4586-4719-af6d-21404eba6ce5","added_by":"auto","created_at":"2026-03-11 06:11:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":218150,"visible":true,"origin":"","legend":"\u003cp\u003eThe Measurement Model of the CFA in the Standardized State\u003c/p\u003e\n\u003cp\u003eProble: Identification and Definition of Problem; Data: Data Collection; Processing: Data Processing; Identifying: Identifying, Evaluating Options, and Selecting the Best Option; Planning: Planning for Action; ImRe: Implementation and Re-evaluation\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8747707/v1/99605ba4917c0ad2b2abde75.png"},{"id":104374884,"identity":"fd9e8ad4-7480-47bf-b137-78cd4e02b294","added_by":"auto","created_at":"2026-03-11 06:11:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1045662,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8747707/v1/19f97e71-227a-4e0a-818b-2ac2360d40f2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Development and Validation of a Multidimensional Tool to Assess Nurses’ Clinical Decision-Making","fulltext":[{"header":"Introduction","content":"\u003cp\u003eClinical decision-making is a fundamental aspect of professional nursing practice. It extends beyond the application of theoretical knowledge, involving the ability of nurses to systematically evaluate patient data, consider relevant evidence, and make informed, patient-centered decisions about care and treatment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Nurses\u0026rsquo; decisions, from selecting medication routes to planning complex care in critical units, directly impact patient safety, treatment outcomes, and the overall effectiveness of healthcare systems [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The quality of these decisions is crucial to providing safe, effective, and patient-centered care [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] .\u003c/p\u003e \u003cp\u003eThe dynamic healthcare environment requires nurses to apply sound clinical judgments to address patient needs within a multidisciplinary team framework [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Barriers to clinical decision-making are often categorized into three main groups: Professional Factors (knowledge, skills, emotional stress); Organizational and Environmental Factors (inefficient management, poor resources, socio-cultural constraints); and Interpersonal Factors (team conflicts, poor communication) [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] .\u003c/p\u003e \u003cp\u003eGiven the critical role of clinical decision-making in nursing, there is an increasing need for reliable, standardized instruments to measure this skill. Extensive research has been dedicated to developing and validating assessment tools to accurately measure nurses\u0026rsquo; decision-making abilities, such as the widely used Clinical Decision-Making Questionnaire by Laurie et al. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. A study by Moradi and Sharifi highlighted the diversity of methods used to assess clinical decision-making among Iranian nurses, including Laurie's Questionnaire, the Participation in Decision Activities Questionnaire (PDAQ), and various researcher-made tools. The findings consistently pointed to a predominant use of analytical-intuitive or interpretive-intuitive decision-making approaches.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eGiven the complexity of clinical decision-making and the various influencing factors, accurately assessing this ability is essential for identifying nurses' cognitive strengths and weaknesses. This allows for the design of targeted educational programs and interventions to enhance their decision-making skills [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Moreover, a valid and reliable assessment tool is crucial for healthcare managers and policymakers to evaluate current educational programs, anticipate future training needs, and ultimately improve patient safety and care quality. Without such tools, evaluating and improving nurses\u0026rsquo; decision-making capabilities becomes a significant challenge.\u003c/p\u003e \u003cp\u003eDespite substantial efforts in this area, a gap remains for a comprehensive, standardized, and validated instrument that can assess all dimensions of nurses\u0026rsquo; clinical decision-making within their professional and cultural context [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Existing instruments, such as the Laurie Questionnaire, CDMNS, and NDMI, primarily focus on cognitive or analytical models, often overlooking the cultural and professional realities of nursing practice in Iran. These limitations highlight the need for a comprehensive, culturally aligned instrument that can assess all aspects of the decision-making process. In this regards, the primary objective of this study is to design and validate a reliable, comprehensive, and culturally appropriate instrument to evaluate nurses\u0026rsquo; clinical decision-making skills. The innovation of this tool lies in its multidimensional and localized approach, incorporating factors critical to the local context, such as unique working conditions, emerging technologies, and inter-departmental interactions. The development process combines qualitative and quantitative methods, including literature review, expert interviews, and advanced statistical validation. The resulting instrument is expected to make a significant contribution to nursing education, research, and management, thereby enhancing the quality of care and patient outcomes.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eThis study was conducted in 2024/2025 using a mixed-methods sequential exploratory design, focusing on the development and validation of a new instrument to assess nurses' clinical decision-making. The study comprised two phases: a qualitative phase to identify factors influencing clinical decision-making through literature review, field observations, and expert opinions, followed by a quantitative phase to evaluate the psychometric properties of the instrument.The study population consisted of nurses employed at a teaching hospital affiliated with Shahid Beheshti University of Medical Sciences in Tehran. To ensure an adequate sample size for Confirmatory Factor Analysis (CFA), 200 nurses were selected using stratified random sampling. This method ensured proportional representation across age groups, genders, and years of experience.Inclusion criteria required participants to be actively employed, with at least one year of clinical experience in various hospital units, a Bachelor's degree in nursing or higher, and the ability to provide informed consent. Nurses with less than one year of experience or those unwilling to continue participation were excluded. Additionally, questionnaires with more than 10% of missing responses or those not completed within the specified time frame were excluded from the analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDesign of the questionnaire items\u003c/h3\u003e\n\u003cp\u003eIn the first stage, the research team identified factors influencing clinical decision-making by studying all hospital units. Based on prior research and a review of relevant articles, these factors were categorized into four groups: nurse characteristics, patient characteristics, environmental factors, and organizational determinants. A 14-member expert panel, including specialists from occupational health, medicine, nursing, and ergonomics, was formed. The panel reached a consensus to design the preliminary framework of the questionnaire, which consisted of 41 items across six domains: problem identification and definition, data collection, data processing, identifying and evaluating options, action planning, and decision implementation and re-evaluation\u003c/p\u003e\n\u003ch3\u003eFace and content validity\u003c/h3\u003e\n\u003cp\u003eTo establish face and content validity, the instrument was reviewed by the expert panel to assess the wording, grammar, and item allocation. Revisions were made based on expert feedback. Additionally, the questionnaire was presented to five nurses with diverse experience to identify any ambiguities. The questionnaire was revised based on their feedback, including rewording questions, modifying options, and adjusting explanations. The responses were formatted using a 5-point Likert scale: Very Low, Low, Moderate, High, and Very High. A higher score indicated a higher level of clinical decision-making. Content validity was assessed using two indices: the Content Validity Ratio (CVR) and the Content Validity Index (CVI). Items with a CVR greater than 0.51 (for 14 experts) were considered acceptable, and items with a CVI greater than 0.79 were confirmed as valid. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eConstruct Validity\u003c/h3\u003e\n\u003cp\u003eTo assess construct validity, Confirmatory Factor Analysis (CFA) was employed. CFA is an advanced statistical technique used to test theoretical models and evaluate their compatibility with the data. Unlike Exploratory Factor Analysis (EFA), which is data-driven, CFA allows for testing the alignment of a hypothesized model with the observed data. Several indices were used to evaluate model fit, including the Chi-Square/Degrees of Freedom Ratio (χ\u0026sup2;/df) and the Root Mean Square Error of Approximation (RMSEA). A χ\u0026sup2;/df ratio of 2 or less indicated a good fit, while RMSEA values below 0.08 were considered acceptable, and values under 0.05 indicated a very good fit [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eReliability\u003c/h3\u003e\n\u003cp\u003eReliability was evaluated using Cronbach\u0026rsquo;s alpha to determine the internal consistency of the instrument. A Cronbach\u0026rsquo;s alpha value of 0.58 or higher is generally considered satisfactory. In this study, Cronbach\u0026rsquo;s alpha was calculated to assess the reliability of the entire instrument and its subscales.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEthical Considerations\u003c/h2\u003e \u003cp\u003e The study was approved by the Research Ethics Committee of Shahid Beheshti University of Medical Sciences (IR.SBMU.PHNS.REC.1403.106). Informed verbal consent was obtained from all participants, ensuring their voluntary participation. The confidentiality of participants' data was maintained, and they were informed of their right to withdraw from the study at any stage without any consequences.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection \u0026Statistical Analyses\u003c/h3\u003e\n\u003cp\u003eData were collected anonymously through face-to-face interviews, ensuring participants' privacy. The data were analyzed using SPSS version 25 and AMOS 23 software for statistical analysis and CFA, respectively.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe statistical population of the study consisted of 200 nurses( 140 female and 60 male). The mean and standard deviation of age were (35.38\u0026thinsp;\u0026plusmn;\u0026thinsp;7.47) and work experience (1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;2.55). Other characteristics are presented below (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic Characteristics of the Nurses Participating in the Study (N\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBachelor's (BSc)\u003c/p\u003e \u003cp\u003eMaster's (MSc)\u003c/p\u003e \u003cp\u003eDoctorate (PhD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e169\u003c/p\u003e \u003cp\u003e29\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.5\u003c/p\u003e \u003cp\u003e14.5\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e118\u003c/p\u003e \u003cp\u003e42\u003c/p\u003e \u003cp\u003e36\u003c/p\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59\u003c/p\u003e \u003cp\u003e21\u003c/p\u003e \u003cp\u003e18\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of Employment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOfficial (permanent)\u003c/p\u003e \u003cp\u003eOfficial (temporary)\u003c/p\u003e \u003cp\u003eContract\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e126\u003c/p\u003e \u003cp\u003e33\u003c/p\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63\u003c/p\u003e \u003cp\u003e16.5\u003c/p\u003e \u003cp\u003e20.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShift Type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDay Shift\u003c/p\u003e \u003cp\u003eNight Shift\u003c/p\u003e \u003cp\u003eRotating\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003cp\u003e50\u003c/p\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003cp\u003e25\u003c/p\u003e \u003cp\u003e38.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTool validity\u003c/h2\u003e \u003cp\u003eTo ensure the instrument\u0026rsquo;s validity, the face validity of the questionnaire was initially established with revisions based on expert and nurse feedback, which resulted in high scores for all items. Subsequently, content validity was assessed using expert opinions. The results demonstrated that the overall mean CVI was 0.95 and CVR was 0.78; both values were substantially higher than their minimum acceptable thresholds. Furthermore, the quantitative results for face validity indicated that all questions achieved a high validity score in this section.\u003c/p\u003e \u003cp\u003eCFA was utilized to examine the factorial structure of the proposed measurement model, which consisted of 6 domains and 41 items. Before performing the factor analysis, the correlation coefficient between the score of each item and the total score within its respective dimension was examined. The findings from the initial CFA model revealed that the factor loading of one item (Item 37) in the Implementation and Re-evaluation domain was lower than the predetermined cut-off point. This item lacked the necessary discriminatory power to measure the intended dimension and consequently contributed to a low overall Cronbach's Alpha. Therefore, this item was deleted, resulting in the development of an optimal model with high reliability. The for the CFA model, along with the standardized factor loadings of the items, is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. All factor loadings for the items across the six examined domains were statistically significant, confirming the construct validity of the instrument. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGoodness-of-Fit Indices of the Nurses' Clinical Decision-Making Questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel fit index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModified model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChi-square\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1150.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edegrees of freedom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e725\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChi-square/degrees of freedom (χ2/df)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.586\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoot mean square error of approximation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGoodness-of-fit index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eReliability\u003c/h2\u003e \u003cp\u003eInternal consistency was examined using Cronbach's Alpha for the total scale and each domain. The total scale demonstrated excellent reliability (α\u0026thinsp;=\u0026thinsp;0.937), while subscale values ranged from 0.67 to 0.82, indicating acceptable to good reliability across domains. Measurement stability was further confirmed using the Intraclass Correlation Coefficient (ICC), which showed results consistent with Cronbach's Alpha (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The final validated instrument for assessing nurses\u0026rsquo; clinical decision-making is provided in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the Instrument's Reliability Based on Cronbach's Alpha and ICC\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDimension\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCorrected Item-total Correlation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCronbach\u0026rsquo;s Alpha if Item Deleted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCronbach\u0026rsquo;s\u003c/p\u003e \u003cp\u003e(CI 95%) Alpha\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003eIdentification and Definition of Problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003e0.798 (0.75\u0026ndash;0.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eData Collection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.766 (0.70\u0026ndash;0.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eData Processing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003e0.823( 0.78\u0026ndash;0.85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eIdentifying, Evaluating Options, and Selecting the Best Option\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003e0.738 (0.67\u0026ndash;0.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003ePlanning for Action\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.809 (0.76\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eImplementation and Re-evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.844 (0.80\u0026ndash;0.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eq40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.84.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe final Questionnaire for the Evaluation of Nurses' Clinical Decision-Making\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDimensions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003eIdentification and Definition of Problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1. How skillful are you in identifying patients' clinical issues (e.g., abnormal vital signs, pain, or behavioral changes)?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2. How skillful are you in identifying the early signs of significant diseases and disorders in patients before the manifestation of clinical problems?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3. How confident are you in the accuracy of your diagnoses concerning patients' problems?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4. To what extent do you utilize specialized tools (e.g., sphygmomanometer, pulse oximeter, etc.) and credible scientific resources (such as checklists and databases) in the process of problem diagnosis?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5. To what extent do you utilize clinical knowledge informed by the latest scientific evidence to explain and interpret patient symptoms?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6. To what extent do you utilize your communication skills (e.g., active listening and empathy) to identify patients' problems?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7. To what extent do you utilize the opinions and experiences of your colleagues to enhance the diagnostic and decision-making process?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8. To what extent are you able to align care practices with the patient's cultural and religious values?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9. How skillful are you in identifying problems that may stem from the family's influence on the patient's condition (e.g., family pressure to select specific treatment methods)?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eData Collection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10. How skillful are you in gathering comprehensive and accurate data regarding the patients' clinical status?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11. How skillful are you in the Regular use of various tools and methods for clinical data collection (e.g., interviews, physical examination, checklists, assessment forms, and observation)?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12. How skillful are you in identifying and prioritizing the collected information relevant to the patient's condition for care decision-making?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13. How skillful are you in the accurate and timely recording of patient information within documentation systems (electronic or paper)?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eData Processing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14. How skillful are you in processing and interpreting the patient care data?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15. How skillful are you in integrating various patient data to form a comprehensive picture of their condition?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16. How skillful are you in comparing trends in changes between the patient's current and previous care data?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17. How skillful are you in identifying and separating crucial information from irrelevant data for clinical decision-making?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18. How skillful are you in utilizing electronic tools (e.g., Electronic Health Records) for data processing?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19. To what extent do you utilize various sources of information (such as laboratory results, medical reports) to interpret the patient's condition?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20. How skillful are you in processing data while considering the patient's cultural limitations (e.g., reluctance to disclose certain information)?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21. How skillful are you in utilizing information provided by the patient's family and significant others in data processing?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eIdentifying, Evaluating Options, and Selecting the Best Option\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22. How skillful are you in identifying appropriate available care methods (e.g., pharmacological treatments, patient education, or vital signs monitoring) for the patient?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23. How skillful are you in accurately evaluating the benefits and drawbacks of each care method and their potential outcomes?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24. How skillful are you in prioritizing care options based on each patient's specific needs and scientific evidence?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25. How skillful are you in selecting the best care methods, considering scientific evidence, the patient's opinion, and their values?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26. How skillful are you in making decisions in ambiguous and emergency situations with limited information?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27. How skillful are you in establishing effective communication with the patient and their family for participation in the care decision-making process?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28. How skillful are you in selecting care methods that account for the patient's religious or cultural limitations (e.g., reluctance to use certain therapeutic approaches)?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29. How skillful are you in clinical decision-making while considering patient family pressure (e.g., family preference for specific treatment methods)?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003ePlanning for Action\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30. How skillful are you in designing care plans that adhere to the latest national guidelines while addressing patients' specific needs and circumstances?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31. How skillful are you in adapting the treatment plan to the patient's condition and available resources while maintaining the quality of care?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32. How skillful are you in collaborating effectively with other members of the care team to integrate the patient's clinical plan?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33. How skillful are you in the accurate and complete documentation of the care plan and patient progress?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34. How skillful are you in planning therapeutic interventions while considering the patient's religious or cultural limitations (e.g., fasting or reluctance to use certain treatment methods)?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35. How skillful are you in collaborating with the patient's family for care planning (e.g., providing instruction for home care)?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eImplementation and Re-evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36. How skillful are you in the accurate implementation of treatment plans (e.g., administering medications, performing nursing interventions, and adhering to protocols) while considering the patient's individual needs?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37. How skillful are you in the continuous assessment of the patient and implementing necessary changes to the treatment plan, based on the evaluation results?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38. How skillful are you in the accurate documentation of care intervention evaluation results?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39. How skillful are you in identifying factors influencing the success or failure of the treatment plan and analyzing their causes?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40. To what extent do you utilize feedback from the patient and their family to improve the quality of care and your own performance?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e1\u0026thinsp;=\u0026thinsp;Very Low, 2\u0026thinsp;=\u0026thinsp;Low,3\u0026thinsp;=\u0026thinsp;Moderate,4\u0026thinsp;=\u0026thinsp;High, 5\u0026thinsp;=\u0026thinsp;Very High. Response\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study aimed to develop and validate an instrument for assessing nurses' clinical decision-making (CDM). Given the pivotal role of nursing decisions in ensuring patient safety and healthcare quality, there is a clear need for a reliable tool to evaluate nurses' competencies and educational needs [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. A robust mixed-method design was employed, following the COSMIN checklist recommendations for new measurement instruments [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe developed questionnaire exhibits structural and conceptual similarities with standardized tools such as the CDMN-S and NDMI [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]; however, it also incorporates critical distinctions tailored to the cultural, social, and professional context of Iranian nurses. These include cultural adaptation, consideration of specific working conditions, attention to emerging technologies, and an emphasis on inter-sectoral interactions. Expert input from medical, occupational health, and nursing professionals was incorporated throughout item development and reduction, ensuring the final instrument was concise and relevant [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFace validity assessment confirmed that all items were fully endorsed by nurses, the primary stakeholders, while quantitative and theoretical evaluations demonstrated high-quality items. Content validity was also confirmed using standard indices (CVI and CVR), with all items exceeding cutoff thresholds, highlighting the value of expert involvement in enhancing the precision and quality of the instrument [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCFA validated the six-domain structure: Identification and Definition of Problem, Data Collection, Data Processing, Identifying and Evaluating Options, Selecting the Best Option, Planning for Action, and Implementation and Re-evaluation. Standardized factor loadings (Q1\u0026ndash;Q40) were statistically significant, with most exceeding 0.5, supporting convergent validity. High but sub-maximal inter-factor correlations indicated conceptual overlap without compromising discriminant validity. Unique dimensions reflecting inter-sectoral interactions, novel technology use, and sociocultural considerations underscore the instrument\u0026rsquo;s indigenous focus and relevance to contemporary practice.\u003c/p\u003e \u003cp\u003eReliability analyses demonstrated excellent internal consistency, with high Cronbach's Alpha values for the total scale and subdomains, indicating cohesive item performance and confirming data reliability. Compared to existing instruments, particularly translated tools, this instrument shows superior validity and reliability, mitigating semantic and cultural limitations often encountered in non-Western clinical settings [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThe instrument effectively captured all hypothesized concepts with high factor loadings, owing to its localized focus on clinical scenarios and terminology. This approach maximized content and face validity and minimized irrelevant variance. Limitations include the cross-sectional design and data collection from a single city and academic-medical center, as well as potential social desirability bias from self-reported responses, though anonymity was ensured. Future studies should employ longitudinal designs and broader sampling across multiple regions.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings derived from the development, validation, and reliability phases strongly support an authentic and reliable instrument for evaluating the clinical decision-making of nurses, which has been specifically tailored to the cultural context and working environment of Iranian nurses. The significance of this instrument lies in its capacity to provide an authentic and accurate depiction of nurses' competencies within the decision-making process\u0026mdash;an advantage that standard international tools like the NDMI and CDMNS may lack due to cultural and environmental discrepancies. Consequently, this questionnaire can be utilized as a strong reference tool for nursing managers and clinical educators to systematically assess and monitor the decision-making competence of personnel, thereby is expected to contribute significantly to enhancing patient safety and improving the quality of care throughout the country's healthcare system.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCVI \u0026nbsp; \u0026nbsp; Content Validity Index \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; CVR \u0026nbsp; \u0026nbsp;Content Validity Ratio \u0026nbsp; \u0026nbsp; \u0026nbsp;CFA \u0026nbsp; \u0026nbsp; Confirmatory Factor Analysis\u003c/p\u003e\n\u003cp\u003ePDAQ \u0026nbsp; \u0026nbsp;Participation in Decision Activities Questionnaire \u0026nbsp; \u0026nbsp; \u0026nbsp; CDMNS \u0026nbsp; \u0026nbsp;Clinical Decision-Making in Nursing Scale \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; NDMI \u0026nbsp; \u0026nbsp; Nursing Decision-Making Instrument \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;EFA \u0026nbsp; \u0026nbsp; \u0026nbsp;Exploratory Factor Analysis\u003c/p\u003e\n\u003cp\u003eRMSEA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Root Mean Square Error of Approximation \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;ICC \u0026nbsp; \u0026nbsp; \u0026nbsp; Intraclass Correlation Coefficient\u003c/p\u003e\n\u003cp\u003eCDM \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Nurses\u0026apos; Clinical Decision-making\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Research Ethics Committee of Shahid Beheshti University of Medical Sciences (IR.SBMU.PHNS.REC.1403.106). All procedures adhered to institutional, national, and Helsinki Declaration ethical standards.All participants provided written informed consent for participation in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e: not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData supporting the findings are available from the corresponding author upon reasonable request; they are not publicly available due to privacy and ethical restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript. V.F., M.Gh., H.R., and R.Z. contributed to conceptualization, project administration, formal analysis, and original draft writing. H.M. and A.S. contributed to methodology and review/editing\u003cstrong\u003e. Professional language and style editing was assisted using artificial intelligence tools.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would also like to thank all the participants for \u0026nbsp;taking time to participat\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZainal NH, et al. Critical Thinking and Clinical Decision Making Among Registered Nurses in Clinical Practice: A Systematic Review and Meta-Analysis. Nurs Rep. 2025;15(5):175.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLatifi N, Roohi G, Tatari M. Nurses\u0026rsquo; clinical decision-making models in the care of older adults: A cross-sectional study, in 2. 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatrician PA, et al. Quality and safety in nursing: recommendations from a systematic review. J Healthc Qual (JHQ). 2024;46(4):203\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParveen Z et al. The Impact of Nurses Clinical Decisions on Patient Safety and Quality of Care: Nurses' Clinical Decisions on Patient Safety and Quality of Care. NURSEARCHER (Journal Nurs Midwifery Sciences), 2025: pp. 31\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbu Arra AY, et al. The factors influencing nurses\u0026rsquo; clinical decision-making in emergency department. INQUIRY: J Health Care Organ Provis Financing. 2023;60:00469580231152080.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBijani M, et al. Major challenges and barriers in clinical decision-making as perceived by emergency medical services personnel: a qualitative content analysis. BMC Emerg Med. 2021;21(1):11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGholipour M et al. Challenges of Clinical Decision-making in Emergency Nursing: An Integrative Review. Open Nurs J, 2025. 19(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEftekharian F, et al. Explaining the experiences of internal medicine department assistants of Jahrom University of Medical Sciences regarding the factors and obstacles affecting clinical decision-making: a qualitative study. Pars J Med Sci. 2023;21(3):1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLauri S, Salanter\u0026auml; S. Developing an instrument to measure and describe clinical decision making in different nursing fields. J Prof Nurs. 2002;18(2):93\u0026ndash;100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoradi T, Sharifi, Kh. Clinical decision making in Iranian nurses: systematic review. Q J Nurs Manage. 2022;11:2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArkan B, et al. Clinical decision-making levels of nursing students and affecting factors. Cyprus Journal of Medical Sciences; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsumoto K, et al. Factors influencing multidisciplinary clinical decision-making in the critical care unit: a systematic review and mixed-methods meta-synthesis. BJA Open. 2025;16:100488.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLavoie P, et al. Measurement properties of self-reported clinical decision-making instruments in nursing: a COSMIN systematic review. Int J Nurs Stud Adv. 2023;5:100122.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTen Ham W, et al. An integrative literature review of the factors that contribute to professional nurses and midwives making sound clinical decisions. Int J Nurs Knowl. 2017;28(1):19\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLawshe CH. A quantitative approach to content validity. Personnel Psychol. 1975;28:563\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKalteh HO, Mortazavi SB, Mohammadi E, Salesi M. Psychometric properties of the Persian version of Neal and Griffin\u0026rsquo;s safety performance scale. Int J Occup Saf Ergon. 2021;27:41\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNazari M, et al. Development and validation of the tool for the evaluation of the behavioral factors affecting the prevalence of musculoskeletal disorders in Iranian students. BMC Pediatr. 2020;20(1):551.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaber KS. The use of Cronbach\u0026rsquo;s alpha when developing and reporting research instruments in science education. Res Sci Educ. 2018;48(6):1273\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShabestari MM et al. Nurses\u0026rsquo; perception of uncertainty in clinical decision-making: A qualitative study. Heliyon, 2024. 10(16).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhazi SF, Mashayekhi M, Asgari P. Iranian Intensive Care Unit Nurses' Experience of Patient Safety Culture: A Qualitative Study. Iran J Nurs. 2024;37(149):210\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMokkink LB et al. COSMIN Study Design checklist for Patient-reported outcome measurement instruments. Amsterdam, The Netherlands, 2019. 2019: pp. 1\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJenkins HM. A research tool for measuring perceptions of clinical decision making. J Prof Nurs. 1985;1(4):221\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkbari M, et al. Development and validation of a resilience skills questionnaire for health sector professionals based on social cognitive theory. Biomed Res Int. 2024;2024(1):5660620.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJalali O, et al. Validation of the Oswestry disability index in adult spinal deformity. Spine. 2024;49(10):682\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBahmaniar S, Amirfakhraie A, Zarei E. The Development and Validation of a Job Burnout Questionnaire for Iranian Nurses: A Case Study of Nurses Working in Hormozgan Province. J Crit Care Nurs. 2025;17(3):37\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUlku HH, Saracaloglu AS. Development and Validation of a Clinical Decision-Making Scale for Medical Students. The Medical Bulletin of Haseki; 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBae J, et al. Development of the clinical reasoning competency scale for nurses. BMC Nurs. 2023;22(1):138.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Clinical Decision-Making, Nurses, Human Factor, Validation, Factor","lastPublishedDoi":"10.21203/rs.3.rs-8747707/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8747707/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eClinical decision-making is a critical aspect of nursing practice, influencing patient safety, care quality, and treatment outcomes. While various tools have been developed to assess decision-making skills in healthcare providers, a comprehensive, validated tool specifically for nurses' clinical decision-making is lacking. This study aims to develop and validate a multidimensional tool designed to assess nurses\u0026rsquo; clinical decision-making.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe tool was developed through an extensive literature review, interviews with nurses, and expert consultations. A sample of 200 Iranian nurses participated in the validation process. Face validity and content validity were assessed using expert feedback and the Content Validity Index (CVI) and Content Validity Ratio (CVR). Construct validity was evaluated using Confirmatory Factor Analysis (CFA), while reliability was assessed through internal consistency (Cronbach\u0026rsquo;s alpha) and stability (Intraclass Correlation Coefficient - ICC).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe final tool includes 40 items across six dimensions: Identification and Definition of Problem, Data Collection, Data Processing, Identifying and Evaluating Options, Selecting the Best Option, Planning for Action, and Implementation and Re-evaluation. The CVI was 0.95, and the CVR was 0.78, indicating strong content validity. CFA confirmed a six-factor structure with good model fit (Chi-square/df\u0026thinsp;=\u0026thinsp;1.586, RMSEA\u0026thinsp;=\u0026thinsp;0.054). The tool demonstrated excellent reliability, with a Cronbach\u0026rsquo;s alpha of 0.937 and an ICC indicating stability.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis newly developed tool provides a reliable, valid, and multidimensional measure for assessing nurses' clinical decision-making abilities. It can be used in clinical practice and research to better understand this critical skill, contributing to improved patient care and safety.\u003c/p\u003e","manuscriptTitle":"Development and Validation of a Multidimensional Tool to Assess Nurses’ Clinical Decision-Making","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-11 06:10:03","doi":"10.21203/rs.3.rs-8747707/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-03-05T09:48:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-04T08:00:50+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-11T02:51:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-07T09:59:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nursing","date":"2026-02-07T09:51:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f01b13fb-4146-484d-b844-8ec314cb3093","owner":[],"postedDate":"March 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-11T06:10:07+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-11 06:10:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8747707","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8747707","identity":"rs-8747707","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}