Relationship between nurse leader emotional intelligence and registered nurse job satisfaction

Aim: To determine the relationship between nurse leader emotional intelligence and registered nurse job satisfaction. ^ Background: Nurse leaders influence the work environments of nurses working at the bedside. Nursing leadership plays an important role in fostering work environments that attract and retain nurses. ^ Methods: A non-experimental, predictive design study conducted in 5 hospitals evaluated relationships between 31 nurse leaders and 799 registered nurses. The nurse leaders were administered the MSCEIT and MBTI. The registered nurses participated in the 2010 NDNQI RN Job Satisfaction Survey. ^ Measurements and Results: The sample population completed two online instruments, the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and the Myers Brigg Trait Inventory (MBTI). Nurse leader demographic data was collected consisting of age, sex, race, educational level, certification status and years in the profession of nursing. The relationships among characteristics of the nurse leader and staff nurses were examined using regression analysis and stepwise deletion. The results from the MBTI were obtained electronically from CPP. Inc. and the results of MSCEIT were obtained electronically from MHS, Inc. The nurse leader response rate was 46% and the NDNQI RN Job Satisfaction response rate was 62%. The sample of 31 nurse leaders were 65 percent female and 67.7% were White, 12.9% Black, and 19.4% Hispanic. The most prevalent MBTI type was ESTJ (19.35%), followed by ENFJ and ISFJ (9.68% each). The nurse leader sample was primarily extroverts (n=20), sensing (n=18), thinking (n=16) and judging (n=19). The nurse leaders' overall MSCEIT scores ranged from 69 to 111 (implying a range from those who should consider development to competent) with a mean score of 89.84 (consider improvement). The nurse leaders scored highest in the MSCEIT Facilitating subscale with scores ranging from 69 to 121 (consider development to strength) and a mean score of 95.19 (low average score). The overall mean MSCEIT mean scores for the entire sample ranged from 89.90 to 95.19 (consider emotional intelligence improvement to low average score) Overall, staff nurse participants in the NDNQI RN Job Satisfaction Survey were moderately satisfied with the nurse leaders as noted by a mean t score of 55.03 of 60 and this score was consistent with the comparison hospitals that participated in the 2010 NDNQI RN Job Satisfaction Survey (American Nurses Association, 2010). Staff nurses gave nurse leaders a mean score of 4.50 for patient assignments appropriate, and rated a mean score of 4.35 and moderately agreeing to recommend the hospital to a friend. ^ Conclusions: Future research is needed to determine if there is a relationship between nurse leader emotional intelligence ability and registered nurse job satisfaction. Additional research is also needed to determine what to measure in regards to nurse leader emotional intelligence, ability or behavior. Another issue that emerged in the examination of EI is the moderating relationship between the nurse leaders span of control and staff nurse satisfaction on the NDNQI. ^

Blended Learning: Integrating an e-Learning Component for Competency Validation

Introduction: Emergency care providers are required to demonstrate competency in the management of life-threatening situation. The care provider’s ability to manage an emergency situation depends upon his/her knowledge and skills in basic CPR; and the use of emergency equipment and supplies. The education department at our healthcare facility is responsible for CPR/Emergency Management competency validation of over 2500 employees annually. Historically each employee was scheduled to attend 4 hours of class every year to review the content, complete the post-test and demonstrate skills. It was resource-intensive, time consuming, stressful and often difficult to schedule the 24/7 employees for the sessions. [See PDF for complete abstract]

The Houston Academy of Medicine--Texas Medical Center Library management information system.

A management information system (MIS) provides a means for collecting, reporting, and analyzing data from all segments of an organization. Such systems are common in business but rare in libraries. The Houston Academy of Medicine-Texas Medical Center Library developed an MIS that operates on a system of networked IBM PCs and Paradox, a commercial database software package. The data collected in the system include monthly reports, client profile information, and data collected at the time of service requests. The MIS assists with enforcement of library policies, ensures that correct information is recorded, and provides reports for library managers. It also can be used to help answer a variety of ad hoc questions. Future plans call for the development of an MIS that could be adapted to other libraries' needs, and a decision-support interface that would facilitate access to the data contained in the MIS databases.

Self-Assessment in a Competency-Based Curriculum: Preliminary Findings

Introduction: The introduction of the ACGME core competency framework brought challenges of developing appropriate evaluation tools (i.e. self assessment) to provide evidence of competency. Baylor College of Medicine has 43 competency goals organized within the 6 ACGME domains, each domain having 4-10 goals. [See PDF for complete abstract]

Is Our Business Family-Centered?

Human Services agencies often claim to be family-centered, but continue to implement “Service Integration” in a way that supports their mission rather than supporting families. David Berns, guest editor for this issue of the Journal of Family Strengths, presents a framework for redefining the role of governmental agencies beyond their day-to-day delivery of services to one that prevents the need for more intrusive and more costly interventions. Under this philosophy, agencies must consider how families functioned before they requested assistance, and how they will function if services are not successful. By taking the time to truly understand a family’s needs, caseworkers often discover that they may need a service for which they are not eligible and may be eligible for services that they don’t want or need. Instead of focusing entirely on what their agency can do for the family, caseworkers should consider all types of support that might produce better results. Families often need support from friends and communities rather than, or in addition to, a formalized service. Facilitating natural supports in the community may prevent the need for a governmental program. It is only when basic supports break down that families must use ever more intensive and costly programs. The author gives examples of how this framework is guiding the redesign of the TANF Program in Washington, D.C.

New algorithms for automated phylogenetic reconstruction using artificial intelligence and data mining techniques

Academic and industrial research in the late 90s have brought about an exponential explosion of DNA sequence data. Automated expert systems are being created to help biologists to extract patterns, trends and links from this ever-deepening ocean of information. Two such systems aimed on retrieving and subsequently utilizing phylogenetically relevant information have been developed in this dissertation, the major objective of which was to automate the often difficult and confusing phylogenetic reconstruction process. ^ Popular phylogenetic reconstruction methods, such as distance-based methods, attempt to find an optimal tree topology (that reflects the relationships among related sequences and their evolutionary history) by searching through the topology space. Various compromises between the fast (but incomplete) and exhaustive (but computationally prohibitive) search heuristics have been suggested. An intelligent compromise algorithm that relies on a flexible “beam” search principle from the Artificial Intelligence domain and uses the pre-computed local topology reliability information to adjust the beam search space continuously is described in the second chapter of this dissertation. ^ However, sometimes even a (virtually) complete distance-based method is inferior to the significantly more elaborate (and computationally expensive) maximum likelihood (ML) method. In fact, depending on the nature of the sequence data in question either method might prove to be superior. Therefore, it is difficult (even for an expert) to tell a priori which phylogenetic reconstruction method—distance-based, ML or maybe maximum parsimony (MP)—should be chosen for any particular data set. ^ A number of factors, often hidden, influence the performance of a method. For example, it is generally understood that for a phylogenetically “difficult” data set more sophisticated methods (e.g., ML) tend to be more effective and thus should be chosen. However, it is the interplay of many factors that one needs to consider in order to avoid choosing an inferior method (potentially a costly mistake, both in terms of computational expenses and in terms of reconstruction accuracy.) ^ Chapter III of this dissertation details a phylogenetic reconstruction expert system that selects a superior proper method automatically. It uses a classifier (a Decision Tree-inducing algorithm) to map a new data set to the proper phylogenetic reconstruction method. ^

For-profit business safety interventions: A systematic, descriptive review of the literature

The purpose of this research was to determine if principles from organizational theory could be used as a framework to compare and contrast safety interventions developed by for-profit industry for the time period 1986–1996. A literature search of electronic databases and manual search of journals and local university libraries' book stacks was conducted for safety interventions developed by for-profit businesses. To maintain a constant regulatory environment, the business sectors of nuclear power, aviation and non-profits were excluded. Safety intervention evaluations were screened for scientific merit. Leavitt's model from organization theory was updated to include safety climate and renamed the Updated Leavitt's Model. In all, 8000 safety citations were retrieved, 525 met the inclusion criteria, 255 met the organizational safety intervention criteria, and 50 met the scientific merit criteria. Most came from non-public health journals. These 50 were categorized by the Updated Leavitt's Model according to where within the organizational structure the intervention took place. Evidence tables were constructed for descriptive comparison. The interventions clustered in the areas of social structure, safety climate, the interaction between social structure and participants, and the interaction between technology and participants. No interventions were found in the interactions between social structure and technology, goals and technology, or participants and goals. Despite the scientific merit criteria, many still had significant study design weaknesses. Five interventions tested for statistical significance but none of the interventions commented on the power of their study. Empiric studies based on safety climate theorems had the most rigorous designs. There was an attempt in these studies to address randomization amongst subjects to avoid bias. This work highlights the utility of using the Updated Leavitt's Model, a model from organizational theory, as a framework when comparing safety interventions. This work also highlights the need for better study design of future trials of safety interventions. ^

The Role of the Clinical Educator in Evaluating Nursing Competency

INTRODUCTION: Evaluation of nursing competency is critical to assuring patient safety and maintaining high professional standards in the practice of nursing. All nurses must graduate from an approved nursing program and successfully pass the national board exam before receiving initial licensure. State boards of nursing fulfill the role of gatekeeper, seeking to assure the public that nurses provide safe, competent care. In turn, high public awareness and patient advocacy initiatives require close monitoring of nursing competency. [See PDF for complete abstract]