BACKGROUND:Prior international collaborative studies indicated that job satisfaction, a factor of nursing work wellbeing (WWB), is closely linked to retention, with notable cross-country differences. However, limited regional comparisons, especially between Central and Eastern Europe (CEE), North America, and the Middle East and North Africa (MENA), restrict understanding of nurse wellbeing and retention regional impacts, limiting tailored strategy development. AIMS:This secondary analysis study compared the effects of region on nursing WWB and job satisfaction factors in CEE, MENA, and North America, aiming to identify those CEE region-specific predictors associated with and effects on job satisfaction and, in turn, WWB. METHODS:CEE (n = 1616), MENA (n = 1562), and North America (n = 1386) data were analyzed using descriptive and linear regression analytics (p < 0.001). The CEE sample included nursing staff from Croatian (n = 301), Polish (n = 215), Serbian (n = 489), and Slovenian (n = 611) nurses and nursing assistants. Six job satisfaction factors were examined: coworkers, patient care, participative management, autonomy, professional growth, and organizational rewards. RESULTS:The CEE region reported statistically significant lower mean scores and negative effects across all six job satisfaction factors compared to MENA and North America. Satisfaction with coworkers had the largest effect within the CEE region when compared to MENA and North America (ϐ = -0.26), while satisfaction with participative management had the smallest regional effect (ϐ = -0.10). Findings informed operational discussions for CEE-targeted retention interventions. LINKING EVIDENCE TO ACTION:Job satisfaction subscale factors facilitate the identification of empirically- and theoretically-informed operational actions to improve CEE nursing job satisfaction as an important factor of WWB and contribute to nursing retention.

BACKGROUND:Global research on nurse work wellbeing (WWB) has produced internationally-informed outcome models, yet few studies examine how these models apply within specific countries. Understanding WWB in the national context is essential to shape effective, locally relevant nursing policies and practices. OBJECTIVES:To explore WWB characteristics among hospital nurses in the Middle East and North Africa (MENA) and identify country-specific opportunities to improve nurse WWB. METHODS:A secondary analysis was conducted using WWB data from nurses in Jordan, Israel, and Türkiye, extracted from a broader 9-country study (2022-2023) involving 2546 nurses. The original study employed the 35-item Profile of Caring instrument to measure a 9-factor model of WWB. This analysis used descriptive statistics and linear regression to examine country-specific patterns among MENA nurses (n = 429). RESULTS:Data from Jordan (n = 136), Israel (n = 175), and Türkiye (n = 118) revealed statistically significant differences (p < 0.001) across five of nine WWB factors by country. Country, as a variable, predicted 33% of the variance of caring-for-self and 20% of caring-of-manager, with Türkiye and Jordan reporting the lowest scores, respectively. Country explained 18% of satisfaction with professional growth and 16% in autonomy, with Türkiye scoring lowest on both. Fifteen percent of participative management was predicted by country, with both Türkiye and Jordan having lower scores than Israel. LINKING EVIDENCE TO ACTION:Findings inform country-specific policy and operational improvements to support nurse WWB: strengthening manager-staff engagement, fostering self-care among nurses and caring and communicative behaviors from managers, supporting professional development, and enhancing autonomy and role clarity.

BACKGROUND:This 2022-2023 study across nine countries builds on a 2019-2021 ten-country study exploring nurse work well-being (WWB) and its associated outcomes. WWB, as assessed using the Profile of Caring (PoC) survey, is conceptualized as a multifactorial construct encompassing caring for self, caring of manager, clarity of role/system, and job satisfaction. AIMS:To explore relationships between WWB and staff outcomes by evaluating the PoC construct validity within an international nursing population in the post-pandemic context. METHODS:Nursing staff (n = 2546) from 128 facilities participated. Mixed methods, including thematic analysis, descriptive statistics, regression analyses, and path analysis, were employed to develop a WWB outcome model. Reliability was assessed with Cronbach's alpha, and construct validity was assessed through exploratory factor analysis. RESULTS:The final model had good model fit, explaining 76% of nurse WWB. Feeling rewarded for work well done, total direct effect had a positive relationship with job satisfaction (β = 0.415, p = < 0.001) and a negative effect on intent to leave (β = -0.242, p = 0.003). Job satisfaction total direct effect negatively related to intent to leave (β = -0.584, p = < 0.001). Relationship direction, strength, and significance varied by country. Caring of manager explained one-third of WWB. Job satisfaction subscales explained intent to leave (25.2%). The PoC showed high reliability (Cronbach's alpha ≥ 0.80), and robust construct validity was confirmed through exploratory factor analysis (KMO = 0.950, factor loadings ≥ 0.40). LINKING EVIDENCE TO ACTION:Conclusions suggest that understanding job satisfaction and intent to leave predictors is complex, requiring complex models to globally and contextually explain nurse WWB outcomes.

BACKGROUND:Work wellbeing, also known as workplace wellbeing, is a global concern for nurses, particularly because excessive stress and exhaustion contribute to burnout. OBJECTIVE:The Caring Science International Collaborative (CSIC), an international research network, empirically investigates nurse work wellbeing using the Profile of Caring, a psychometrically validated and reliable instrument. FRAMEWORK:The CSIC framework defines wellbeing intrinsically-as caring and clarity-and extrinsically-as the social and technical resources needed to work efficiently and effectively. The Profile of Caring explains 80% of work wellbeing in nursing without bias across 10 countries. STUDY DESIGN:This research protocol describes an international multicenter observational study that measures nurse work wellbeing using the Profile of Caring and other concepts and outcomes measures.

Clergy play an important role in the health of their congregations and communities. Unfortunately, high rates of chronic disease and burnout exist, and health promotion programs have been limited in their ability to change behaviors. This study psychometrically tested the Caring Factor Survey—Caring for Self (CFS-CS), developed to understand self-care among nurses, with clergy. Initially, five experts established face validity of the survey. Ordained Christian clergy actively ministering in the United States were then recruited for a two-phase study. In phase 1, six clergy assessed the content validity of the survey using the Content Validity Index (CVI). In phase 2, 70 clergy completed the CFS-CS, demographic questions, and two Likert scale questions assessing the importance of and their effort to care for themselves daily. Cronbach’s alpha, average inter-item correlations, and exploratory factor analysis were conducted , as were correlations between the survey and the Likert scale items. During phase 1, individual CVI ranged from 1.00 to 0.83 and scale-level CVI was 0.95 , indicating that the content of the scale was adequate. During phase 2, one item, Teaching & Learning, did not perform well. When removed, Cronbach’s alpha and the average inter-item correlation were 0.81 and 0.33, respectively. Correlations between the nine-item survey (CFS-CS, Clergy) and the measures of importance and effort towards caring for self were r = 0.50 and 0.68, respectively, p < 0.001 for both. The CFS-CS, Clergy was found to be a valid and reliable measure for future studies to assess self-care beliefs and attitudes of clergy and their impact on clergy health.

Objective: Faith leaders often serve as health-related role models yet many struggle with obesity and self-care engagement. The purpose of this scoping review was to examine how the faith leader literature has defined self-care and examined obesity and obesity-related chronic disease.Data Source: Studies were identified through database (eg, PubMed, CINAHL, PsycINFO), backward, and grey literature (eg, dissertations) searches.Inclusion/Exclusion Criteria: Studies published in English with participants who were 18 years or older and examined leaders across all faiths. Studies also included an examination of self-care behaviors among faith leaders within the context of obesity or obesity-related chronic diseases.Data Extraction/Synthesis: Data synthesis was qualitative and informed by the six-step framework developed by Arksey and O'Malley (2005) as well as updated recommendations by Daudt et al (2013). Of the 418 studies identified and screened, 20 met the eligibility criteria.Results: Studies were primarily cross-sectional and participants Christian faith-leaders in the US. Most studies did not define self-care or incorporate theory, but focused on vegetarian diets and physical activity engagement. Other self-care related behaviors (eg, sleep, days off), some unique to faith leaders (eg, sabbatical), were included but not systematically.Conclusions: Research with more diverse faith leaders and that uses theory is needed to guide development of strategies for engaging this population in self-care to reduce obesity and related chronic diseases.

Amaç: Bu metodolojik çalışma, Bakım Faktörü Ölçeği’nin Öz Bakım (BFÖ-ÖB) ve Yöneticinin Bakımı (BFÖ-YB) sürümlerini, hemşire örnekleminde Türkçe’ye uyarlayarak, geçerlik ve güvenirliklerini belirlemek amacıyla yapılmıştır. Yöntem: Şubat-Nisan 2019 tarihleri arasında, Akdeniz Üniversitesi Hastanesi’nde görevli olan 400 hemşire, çalışmanın örneklemini oluşturmuştur. Veriler, her biri 7’li likert tipinde, 10 maddelik BFÖ-ÖB ve BFÖ-YB kullanılarak, öz bildirim yöntemiyle toplanmıştır. Türkçeye uyarlanma sürecinde; çeviri, anlamsal inceleme, uzman paneli, geri çeviri, pilot uygulama, son sürüm ve dokümantasyon adımları izlenmiştir. Geçerlilik için Kapsam Geçerlilik İndeksi (KGİ) ve eğik dönüştürme ile Temel Eksen Faktör analizi kullanılmıştır. Güvenilirlik için Chronbach alfa ve test-tekrar test değerleri hesaplanmıştır. Bulgular: BFÖ-ÖB ve BFÖ-YB sürümlerinin KGİ değerleri sırasıyla 1.00 ve 0.99 bulunmuştur. BFÖ-ÖB 373 hemşire tarafından yanıtlanmış (%93), Kaiser Mayer Olkin (KMO) değeri 0.93, açıklanan varyans % 57 ve faktör yükleri .63-.84 arasındadır. BFÖ-YB, 389 hemşire yanıtlamış (% 97), geçerlilik analiz sonucu KMO değeri 0.96 olup, tek faktörlü yapı varyansın %78’ini açıklamış, maddelerin faktör yükleri .85-.93 arasında bulunmuştur. İki ölçeğin Cronbach alfa katsayısı sırasıyla 0.97 ve 0.92 olarak belirlenmiştir. Test-tekrar test korelasyonlarının BFÖ-ÖB için 0.77, BFÖ-YB için 0.79 olduğu belirlenmiştir. BFÖ-ÖB puan ortalaması 5.87±0.82, BFÖ-YB’nin puan ortalaması 5.81±1.10 bulunmuştur. Sonuç: BFÖ-ÖB ve BFÖ-YB sürümlerinin Türkçe uyarlaması, araştırmacılar ve yöneticilerin kullanımı için uygun, geçerli ve güvenilir araçlardır.

Aim To evaluate the properties of a reduced-item Healthcare Environment Survey measuring nurses' job satisfaction across eight countries. Background There is currently no rigorously tested international measure of nurses' job satisfaction that can be used internationally to improve the nurse work environment. Methods Nursing staff from 11 hospitals in eight countries participated in this study. The original 57-item, 11-facet Healthcare Environment Survey was evaluated for reliability, validity, and measurement invariance: Cronbach's alpha was used to test for reliability; construct, discriminate, and convergent testing were used to test validity; and invariance testing including configural, metric, and scalar tests were used to study measurement invariance between the countries. Results 2,046 nursing staff completed the survey. Reliability was established for all six subscales and the combined composite score. Both validity and measurement invariance were supported in every test conducted. An excellent model fit was found for the final 19-item, 6-facet Healthcare Environment Survey that explained 82% of the variance of nurses' job satisfaction. Conclusions Findings suggest the instrument is an efficient measure of nurses' job satisfaction across multiple countries. Longitudinal testing for invariance will be needed to ensure the model remains a good fit. Testing more countries will also verify model fit. Implications for nursing The instrument can be used to measure nurse job satisfaction globally. Implications for nursing policy The instrument can be used to assess interventions to improve the social (patient, unit manager, and coworker) and technical (professional rewards, autonomy, and professional growth) aspects of nurse job satisfaction.

https://doi.org/10.14528/snr.2023.57.2.3248 Decades of research by Gallup in wellbeing reveals among the five types of wellbeing, it is wellbeing at work that is the most important, and this importance is highlighted post covid (Clifton & Harter, 2021). That is because we spend so much of our time at work and wellbeing at work influences all other four types of wellbeing. The most important predictor of wellbeing at work is the interaction the worker has with their immediate manager (Clifton & Harter, 2021). This finding is also pronounced post covid (Clifton & Harter, 2021). The Caring Science International Collaborative (CSIC), an international collaborative, is helping to examine latent constructs like caring and satisfaction in models that provide insight into more complex constructs like wellbeing at work. Understanding how different constructs relate to outcomes like turnover intent, within rigorous and collaborative researchbased organization like this will help nurses move to a more self-directed position in healthcare. CSIC has been studying constructs aligned with wellbeing at work for nurses to develop and scientifically test a model of wellbeing at work that can be used globally to rebuild nursing post pandemic with wellbeing as the foundation. This model of wellbeing at work can be used to add to models that study outcomes, to specify measurement models that not only measure system and patient variables, but importantly include nurses' wellbeing at work as a central predictor of outcomes. Concepts the CSIC has been studying within this 35item model of wellbeing at work include assessment of job satisfaction, clarity of role and system, nurse's report of caring for self, and if the nurse perceives their direct manager acts in a caring way toward them. This brief article is about the research of a group of nurses from 18 countries and the findings they are discovering in their collaborative work about wellbeing at work, and how this relates to nurse outcomes, including intent for turnover. Job satisfaction, according to CSIC, is based on sociotechnical systems theory (Trist & Bamforth, 1951). According to this theory, workers report job satisfaction when they have the social and technical resources to perform their work. A recent study of the CSIC reveals there are six factors of job satisfaction, including three social and three technical (Nelson et al., 2022b). Social factors include satisfaction with relationships with coworkers, communication with their direct manager, and being able to care and plan for patients throughout their stay on their respective unit of care. Technical variables include satisfaction with professional growth, autonomy to perform their work using their education and experience, and how the organization rewards them for the effort and good work put forth. Clarity within this international study is based on the work by Felgen (Nelson & Felgen, 2021). According to this writing, clarity includes understanding not only what their tasks are but also how to manage their time in relationship to these tasks. Possibly most importantly, is clarity on how the system works so they can successfully navigate the resources within the organization so they can fully realize how to enact the role and provide continuous oversight of the patients they care for, to ensure the plan of care is followed through and carried out. This not only helps the patient speed toward recovery, but it helps build trust with the patient which ultimately adds to the Editorial/Uvodnik

In Watson’s Theory of Transpersonal Caring, it is mentioned that the concept of caring can be assessed by ten Caritas processes®. Initial psychometric evaluation of Slovenian instruments for measuring the Caritas process showed adequate psychometric properties. However, a further validation and testing the construct validity in a larger sample was suggested. Therefore, the study aimed to further evaluate the psychometrics of three Slovene versions of the Caring Factor Survey (CFS) among nursing staff. A cross-sectional study was carried out. A total of 1,295 nursing staff in 11 Slovenian hospitals were requested to take part in the study. Slovene version of the 20-item CFS-Care Provider Version, 10-item CFS-Caring of Manager, and 10-item CFS-Caring of Co-workers were used to collect data. Descriptive and inferential statistics were used. The study provided a shorter, valid, and reliable version of the CFS-Care Provider Version for Slovene hospital environments. The study also confirmed that the Slovene CFS for assessing the caring of managers and co-workers, as asserted in Watson’s theory, are valid and reliable instruments. These instruments can be used for the evaluation of measuring caring in hospital settings.

gradient bottom PMS 1815C C13 M96 Y81 K54 on dark backgrounds on light backgrounds standard no gradients watermark stacked logo (for sharing only) standard no gradients watermark stacked logo (for sharing only) white WHITE C0 M0 Y0 K0

This session will explore Dr. Nelson’ predictive analytical process applied to the development of a predictive model to Improve Recovery from OUD. The model applies a hunch considering the relationship of the concept of the “trusted other” to improve sustained recovery from OUD. Attend this session to learn more about predictive analytics and the OUD model.

The Caring Factor Survey - Caring for Self and the Caring Factor Survey - Caring of the Manager are 10-item instruments used to assess nurses' self-report of caring for self and nurses' perception of caring as demonstrated by their unit or department manager, respectively. Each 10-item survey assesses the 10 processes of caring described within Watson's Theory of Transpersonal Caring. Structural equation modeling was used to assess for item mis-specification (for items that did not belong among the 10 items) among the responses from 1,650 nursing staff from six countries. Three types of invariance testing were then used to assess whether the same items were equally relevant across all participating countries. Results revealed that each survey had six items specified to measure that type of caring relationship (i.e., caring for self and caring by the manager), including five items that were the same in both surveys and one unique item in each. Final items were found to be equally relevant across all participating countries. In a global model, both caring relationships were found to relate to nurses' clarity about their role and about the system in which they work, as well as their job satisfaction. Implications for a global study of caring and for impacts on work environments are discussed.

Objective: In this study, it was aimed to perform the validity and reliability study of the Professional Role Clarity and System Clarity Scales. Methods: The purposeful sampling method was used in the study, and a sample of 403 nurses working in a University Hospital was formed between February and April 2019. Data were collected with Professional Role Clarity and System Clarity. In the process of adapting the scales to Turkish, translation, semantic review, expert panel evaluation, back translation, pilot implementation, final version, and documentation steps were followed. Results: The Content Validity Index values of the Professional Role Clarity and System Clarity scales were 0.99 and 1.00, respectively. Both scales were answered by 397 nurses. Kaiser Meier Olkin value was 90.2, variance was 53.65%, and the factor loads were between 0,55 and 0,91, and the scale was valid. The Cronbach's alpha coefficients of both scales are 0.90 and 0.89, respectively, and they have a high degree of reliability. It was determined that both scales with testretest correlations of 1.00 had strong invariance reliability against time. Conclusion: The Turkish version of the Professional Role Clarity and System Clarity scales are suitable, valid, and reliable tools for use.

The psychological impact of the COVID-19 pandemic on nurses, and subsequent increases in turnover, have been extensively documented. This article examines a profile of nurses which included (1) the degree to which direct-care nurses are caring for themselves, (2) the degree to which their manager acts in a caring way, (3) the degree to which nurses have clarity about their professional role and about how the system works, and (4) the degree to which nurses are satisfied with essential social and technical dimensions of their jobs, to help understand how some of the critical internal states and working relationships of nurses fit together as a model. To test the model, authors used structural equation modeling with a 35-item measurement tool in three countries (Russia, Serbia, and Turkey; n = 984), replicating a recent 8-country study. Results revealed a good model fit, similar to the original study, despite statistically significant differences in mean scores between the countries studied. Good model fit with a second group of countries, despite differences in mean scores, suggests that results from both studies can be used for a global conversation about how caring, clarity, and job satisfaction in nursing relate to one another. These results provide evidence that health facilities should study variables such as caring for self, caring by the unit or department manager, clarity of role and system, and job satisfaction to learn about, recover, and monitor nurses' health and experience of work as they emerge from the pandemic.

The Caring Factor Survey – Caring for Self and the Caring Factor Survey – Caring of the Manager are 10-item instruments used to assess nurses ‘self-report of caring for self and nurses ‘perception of caring as demonstrated by their unit or department manager, respectively. Each 10-item survey assesses the 10 processes of caring described within Watson's Theory of Transpersonal Caring. Structural equation modeling was used to assess for item mis-specification (for items that did not belong among the 10 items) among the responses from 1,650 nursing staff from six countries. Three types of invariance testing were then used to assess whether the same items were equally relevant across all participating countries. Results revealed that each survey had six items specified to measure that type of caring relationship (i.e., caring for self and caring by the manager), including five items that were the same in both surveys and one unique item in each. Final items were found to be equally relevant across all participating countries. In a global model, both caring relationships were found to relate to nurses ‘clarity about their role and about the system in which they work, as well as their job satisfaction. Implications for a global study of caring and for impacts on work environments are discussed.

This chapter examines lessons learned by clinicians and researchers in a 650-bed urban hospital in the Northeastern United States when they trained staff members in data management, concepts of research essential for the collection of accurate data, and the use of predictive analytics to improve outcomes.

Chapter 18 Measuring the Effectiveness of a Care Delivery Model in Western Scotland Theresa Williamson, Theresa WilliamsonSearch for more papers by this authorSusan Smith, Susan SmithSearch for more papers by this authorJacqueline Brown, Jacqueline BrownSearch for more papers by this authorJohn W. Nelson, John W. NelsonSearch for more papers by this author Theresa Williamson, Theresa WilliamsonSearch for more papers by this authorSusan Smith, Susan SmithSearch for more papers by this authorJacqueline Brown, Jacqueline BrownSearch for more papers by this authorJohn W. Nelson, John W. NelsonSearch for more papers by this author Book Editor(s):John W. Nelson, John W. Nelson Healthcare EnvironmentSearch for more papers by this authorJayne Felgen, Jayne Felgen Creative Health Care ManagementSearch for more papers by this authorMary Ann Hozak, Mary Ann Hozak St. Joseph's HealthSearch for more papers by this author First published: 16 June 2021 https://doi.org/10.1002/9781119747826.ch18 AboutPDFPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShareShare a linkShare onFacebookTwitterLinked InRedditWechat Summary This chapter examines how the instruments used to measure caring in Western Scotland, described in Chapter 17, were used to test changes in caring and quality throughout the implementation of a framework of care delivery called the Caring Behaviors Assurance System (CBAS). The instrument to measure caring was used in conjunction with two other instruments specified to measure the effectiveness of CBAS. Results provided a convincing scientific argument that CBAS was an effective strategy to support caring and quality standards consistent with the National Health Service of Scotland. Using Predictive Analytics to Improve Healthcare Outcomes RelatedInformation

Chapter 14 Theory and Model Development to Improve Recovery from Opioid Use Disorder Alicia House, Alicia HouseSearch for more papers by this authorKary Gillenwaters, Kary GillenwatersSearch for more papers by this authorTara Nichols, Tara NicholsSearch for more papers by this authorRebecca Smith, Rebecca SmithSearch for more papers by this authorJohn W. Nelson, John W. NelsonSearch for more papers by this author Alicia House, Alicia HouseSearch for more papers by this authorKary Gillenwaters, Kary GillenwatersSearch for more papers by this authorTara Nichols, Tara NicholsSearch for more papers by this authorRebecca Smith, Rebecca SmithSearch for more papers by this authorJohn W. Nelson, John W. NelsonSearch for more papers by this author Book Editor(s):John W. Nelson, John W. Nelson Healthcare EnvironmentSearch for more papers by this authorJayne Felgen, Jayne Felgen Creative Health Care ManagementSearch for more papers by this authorMary Ann Hozak, Mary Ann Hozak St. Joseph's HealthSearch for more papers by this author First published: 16 June 2021 https://doi.org/10.1002/9781119747826.ch14 AboutPDFPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShareShare a linkShare onFacebookTwitterLinked InRedditWechat Summary This chapter examines the presence or absence of a "trusted other" as the most significant factor in reducing opioid use disorder. This chapter reviews how, after a study of cognitive therapy and medication-assisted therapy failed to produce adequate outcomes, the existing literature was used to develop a respecified model for addressing, measuring, and treating the disorder. Using Predictive Analytics to Improve Healthcare Outcomes RelatedInformation

Chapter 1 Using Predictive Analytics to Move from Reactive to Proactive Management of Outcomes John W. Nelson, John W. NelsonSearch for more papers by this author John W. Nelson, John W. NelsonSearch for more papers by this author Book Editor(s):John W. Nelson, John W. Nelson Healthcare EnvironmentSearch for more papers by this authorJayne Felgen, Jayne Felgen Creative Health Care ManagementSearch for more papers by this authorMary Ann Hozak, Mary Ann Hozak St. Joseph's HealthSearch for more papers by this author First published: 16 June 2021 https://doi.org/10.1002/9781119747826.ch1 AboutPDFPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShareShare a linkShare onFacebookTwitterLinked InRedditWechat Summary In this chapter, you will learn an analytical process that begins with a mere hunch about what is going on related to the outcomes you want to change, helps you build a model of measurement, and reviews how that model can be respecified after findings from the initial model have been used to refine operations and improve outcomes. Using Predictive Analytics to Improve Healthcare Outcomes RelatedInformation