Results supported the influence of nurse attitude on job satisfaction relative to other contributing factors.

The purpose of this predictive nonexperimental study was to investigate the influence of registered nurse (RN) job satisfaction, context of care, structure of care, patient-perceived nurse caring, and patient characteristics on patient satisfaction with inpatient hospital nursing care in an academic medical center in north-central West Virginia. Convenience samples of patients (N = 362) and RNs (N = 90) were recruited from two medical units, two surgical units, and three intensive care step-down units. Causal modeling identified patient-perceived nurse caring as the major predictor of patient satisfaction, with nurse/physician (RN/MD) collaboration as the only other direct predictor. Age had an indirect influence on patient satisfaction. Strategies to achieve and maintain patient satisfaction should address the enhancement of patient-perceived nurse caring and RN/MD collaboration.

Practitioners need skills and resources to appraise, synthesize, and diffuse the best evidence into practice. Patient outcomes must reflect discipline-specific and interdisciplinary accountabilities. Collaboration between researchers and practitioners within and among disciplines will enhance the diffusion of evidence-based practice innovations.

I gratefully acknowledge my dissertation committee members, who shared their expertise, challenged me intellectually, guided my development as a researcher, gave me encouragement, and enabled my

Many patient satisfaction instruments are not based on patient perceptions, theoretically limiting their validity. This qualitative study identified good nursing care from the patient's perspective, using a convenience sample of 199 hospitalized adult patients in a public hospital in South Central United States. Content analysis yielded five themes: providing for my needs, treating me pleasantly, caring about me, being competent, and providing prompt care. Similarities and differences were found between these themes and themes identified in other qualitative studies, as well as instruments, for which item generation was based upon qualitative patient data. Implications for providers, administrators, and researchers are discussed.

Registered nurse (RN) job satisfaction is a major predictor of intent to stay and job turnover, serious concerns to health care leaders. Predictors of job satisfaction include autonomy, control over daily practice, nurse-physician collaboration, transformational leadership, group cohesion, job stress, structural empowerment, and psychological empowerment. In the model of psychological empowerment, stress resiliency is the product of persons' interpretive styles and influences psychological empowerment. This study has evaluated the influence of stress resiliency on job stress, psychological empowerment, job satisfaction, and intent to stay using causal modeling. Participants are 464 RNs employed in five acute care hospitals in West Virginia. The final model has provided a very good fit to the data. Stress resiliency is a predictor of psychological empowerment, situational stress, and job satisfaction. This study provides the first evidence of the influence of stress resiliency on job stress, psychological empowerment, job satisfaction, and intent to stay in a sample of RNs.

This phenomenological study explored (a) the lived experience of rheumatoid arthritis (RA), (b) the patient's view of the nurse's role, and (c) the patient as comanager of RA. The purposive sample consisted of 6 Caucasian women living in West Virginia. Using Colaizzi's methodology, a rich, exhaustive description of living with RA emerged. Recommendations for nursing care quality focus on providing personalized, holistic, and humanistic care, which may ultimately improve the patient's quality of life.

CBI-24 appears to be equivalent to the 42-item CBI in psychometric properties, validity, reliability, and scoring for caring behaviors among patients and nurses. These results recommend the use of CBI-24 to reduce response burden and research costs.