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Bullying, high-risk behaviors, and rejection from family and friends leave lesbian, gay, bisexual, transgender, queer/questioning, and other (LGBTQ+) students feeling unsafe and unsupported at school. These adverse events can lead to serious physical, social, and mental health challenges including depression and suicidal ideation. This clinical nursing change project examined the effects of an educational intervention on school staff knowledge, confidence, and self-efficacy in supporting LGBTQ+ youth at school. Project findings suggest that gender inclusive education may be an effective way to increase knowledge, confidence, and self-efficacy among school staff members, thus promoting a safe and inclusive school environment.
This scholarly project evaluates the effect of a leadership development program (LDP) on healthcare leaders. The impact of leadership competence on organizational success has become an important topic. Leadership development programs equip leaders to perform with increased competence and confidence, thereby improving quality, safety, and overall organizational effectiveness.
The LDP was an educational intervention to increase comprehension of effective transformational leadership strategies to improve the healthcare leader’s knowledge, style, and performance. The setting for the project was an academic health center in western North Carolina. Out of 33 participants, 28 (85%) completed the pre and post Multifactor Leadership Questionnaire (MLQ). The MLQ includes 45 Likert-scale items that allow leaders to complete a self-assessment of transformational, transactional and laissez faire leadership characteristics. The participants who completed the pre and post MLQ had significantly higher scores in the transformational leadership principles of idealized attributes, inspirational motivation, and intellectual stimulation, with p-values of less than 0.05 and t-value greater than 1.96. They had significantly lower scores in management by exception, active, and passive or laissez-faire leadership style. The results show that participants perceived that their transformational leadership qualities improved or that they became more transformational
Notwithstanding the limitations (self-reported outcomes that may be over or under-rated, a small sample size (n=28) that may limit generalizability, a lack of gender balance amongst participants), the study contributes to the body of research on leadership development programs and demonstrates that LDPs can have a positive impact on leaders in healthcare organizations.
Less than 50% of adults aged 65 and older complete preventive care. Preventive care is important since older adults are at higher risk for cancer. Colon cancer occurs in more than 70% of people aged 65 and older and is the second most common cause of death in men and women respectively. Breast cancer is mostly diagnosed in women aged 55 and older and is the most common cancer among U.S. women. The study examined completion rates of breast and/or colon cancer screening in adults 66 to 75 years of age who complete two different types of office visits. The study included 20 participants (14 were in the nurse only visit group and 6 were in the CHA visit group). The average age was 70.75 years old. The age range was 66 to 75. (SD = 2.83). 18 were female, 2 were male; 6 were African Americans, 14 were Caucasians; 10 completed college; and 9 were married. The rates of breast cancer screening between the two groups were not statistically significant, χ2 (2) = 0.09, p = .958. The rates of colon cancer screening between the two groups were not statistically significant, χ2 (2) = 0.16, p = .923.
Hospital-acquired pressure injuries (HAPIs) are nursing-sensitive indicators that can lead to extended hospital stays, infection, and even death. A quality improvement project utilizing Kamishibai Cards (K-Cards) with HAPI prevention interventions was implemented at one hospital to determine if implementing K-Cards would decrease HAPI frequency counts. The project occurred on two adult units with two non-intervention units for comparison. K-Cards listing HAPI prevention interventions were placed outside each patient room as visual cues. HAPI frequency counts were collected and compared for 12 weeks before and after K-Card implementation. One project unit experienced a 66% reduction in HAPI frequency counts [n = 6 (pre), 2 (post)], while their comparison unit experienced a 200% increase [n = 0 (pre), 2 (post)]. The other project unit experienced a 15% reduction in HAPI frequency counts [n = 13 (pre), 11 (post)], while their comparison unit experienced no change [n = 2 (pre), 2 (post)]. The decrease in HAPI frequency counts post-K-Card implementation, with no changes or increases in the comparison units, indicates that K-Cards are a promising HAPI reduction strategy warranting further exploration. Further projects with modified K-Cards, longer implementation timeframes, and different settings are recommended to better assess K-Cards' impact on preventing HAPIs.
This three-article dissertation aims to address three methodological challenges to ensure comparability in educational research, including scale linking, test equating, and propensity score (PS) weighting. Under the item response theory (IRT), the first study aims to improve test scale comparability by evaluating the effect of six missing data handling approaches on scale linking accuracy when missing responses occur within common items. The second study aims to provide a new equating method to account for rater errors in rater-mediated assessments. Specifically, the performance of using an IRT observed-score equating method with a hierarchical rater model is investigated under various conditions as compared to a traditional IRT observed-score equating method. The third study examines the performance of six covariate balance diagnostics when using PS weighting method with multilevel data. Specifically, a set of simulated conditions is used to examine the ability of within-cluster and pooled absolute standardized bias, variance ratio, and percent bias reduction methods in identifying a correct PS model. In addition, the association between the balance statistics and the bias in treatment effect is explored. By advancing the methodology for addressing comparability issues, the dissertation intends to enhance the validity and improve the quality of educational research.
The significance of this study was its ability to further inform district and state levels on the supports of the advancement and service of North Carolina’s Latinx educators in school leadership roles. More specifically, this study shed light on the barriers and supports faced by Latinx public school administrators in North Carolina during their professional advancement into school leadership and within their current leadership roles. The purpose of this qualitative study was to use an equity lens to explore the experiences/testimonios of Latinx administrators: their perceptions and experiences as public-school administrators in North Carolina. This study sought to explore the lived experiences of Latinx school administrators in North Carolina in order to foster understanding about the importance of racial and ethnic representation among teachers and school administrators for all students. A basic interpretative qualitative study, the researcher’s data sources for this study involved semi-structure, open-ended, one-on-one interviews with six Latinx North Carolina PK-12 public school administrators. Results of the study indicate that participants were supported by colleagues, partnership programs, mentoring, and networking as aspiring and practicing administrators. Results also indicated that participants faced a variety of biases, systemic racism, and lack of mentoring and networking opportunities both as aspiring and practicing administrators. Implications included the need for additional administrative supports, changes within hiring practices and school/district cultures, an increase in Latinx recruitment programs, and increased partnerships with higher education programs for Latinx educators.
The purpose of this study was to understand whether students who took computer science courses in a prescribed sequence during middle school developed a strong enough computing identity to show an interest in continuing to take computing courses in high school and possibly pursue a career in software development. This study was quantitative and non-experimental. The participants consisted of 184 sixth through eighth grade students, across 15 middle schools enrolled in one of five computer science courses in a large urban district in the southeast region of the United States. The instrument used to analyze a student’s overall computing identity was a survey form that consisted of 11 statements, of which nine were slightly modified from the model research by Mahadeo et al. (2020). Two questions were added to investigate a student’s aspirations to take more software development in high school and their intention of pursuing a career in software development. All questions were answered on a five-point Likert-type scale. Six research questions were constructed for this study to compare computing identity development regarding courses, pathways, race, Title I status, and interest in coding beyond middle school. This study used descriptive statistics, F-test, and ANOVA to capture a broad understanding of the development of computing identity in middle school students who were taking computer science courses in a sequenced pathway. There were three findings: modification of the statements did not impact the overall structure of the tool, computer science pathways were not implemented with fidelity, and there was a strong likelihood students with a high computing identity would also have a high interest in taking more courses in high school and pursuing a career in software development.
Modern power systems are complex in nature. Accurate knowledge and estimation of the electro-mechanical modes in the power system are of great importance since a system-wide outage can be caused by one single unstable mode of oscillation. Hence, advanced mathematical tools and signal processing methods are necessary to estimate the electro-mechanical modes of the power system. There have been several incidences where system breakups and power outages happened due to an undamped mode and all of these events exhibited sustained low-frequency inter-area oscillations which typically are in the range of 0.15Hz to 1Hz. Model-based frequency studies have been established for a long time. However, model-based studies cannot anticipate every kind of event in real-time because the power system is nonlinear, time-varying and difficult to represent in its full higher-order dynamics. Besides, the power grid is stochastic with the advent of renewables and changing load dynamics, which means that it is expected to be excited by random signals all the time; most of them come from random load changes and noises. Due to these factors, Recently, measurement-based power grid mode estimation has attracted great attention.
Through this research work, first a comparison of various measurement-based electro-mechanical oscillation mode detection methods are studied. Several techniques can identify oscillatory modes from ring-down data or ambient data obtained from measurement. Generally, ring-down events occur during the sudden changes in grid operation due to faults, generator outages, or controller operations of the generator. Ambient data changes are rather slow varying close to the steady-state operation of the grid due to small changes in the load or such events. Among the measurement-based techniques, Prony analysis, Eigenvalue Realization Algorithm (ERA) and Matrix Pencil (MP) methods are noteworthy. These methods have successfully been used to determine low-frequency oscillatory modes from measurement data. Recently Subspace Identification (SSI) methods have become popular as they are robust to variations, and can be represented in state-space form thus making it easier for designing time-domain control approaches. As a result, an online wide-area direct coordinated control architecture for power grid transient stability enhancement based on subspace identification and Lyapunov energy functions has been studied. Also, a novel combined deterministic-stochastic online measurement-based identification framework using subspace theory is introduced. The novelty of the design using a fully recursive algorithm and the effectiveness of combined treatment are further discussed. Third, an approach for power system oscillatory mode estimation and classification based on the proposed method are discussed. For controlling electro-mechanical oscillations of power system effectively, identifying the location of oscillation source is very important. Identifying the location of oscillatory mode based on Lyapunov energy functions is also being explored in this work. Identifying oscillation source location is as important as identifying the mode itself. The most commonly used method for identifying oscillation source location based on measurement data is dissipated energy flow (DEF) method. In this work, a new method is proposed and performance against dissipated energy flow method is being explored. Finally this work explores grid following and grid forming control architecture and their usage for integrating distributed energy resources (DERs) into existing grid technology. Integrating different distributed energy resources into current grid can cause some stability issue. This work explains grid following and grid forming technologies and use of identification method to observe low frequency oscillation for DER connection.
Accurate knowledge and estimation of the electro-mechanical modes in the power system are of great importance since a system-wide outage can be caused by one single unstable mode of oscillation. Most of these unstable mode of oscillations are inter-area oscillations which typically are in the range of 0.15Hz to 1Hz. Generally oscillation identification and damping are performed based on Model-based frequency studies. However, the stochastic nature of modern power grid with the advent of renewables and changing load dynamics, and nonlinear interactions makes the oscillation study with apriori models inaccurate and inefficient. Due to these factors, recently, measurement-based power grid mode estimation has attracted great attention.
In this research work, a series of measurement-based oscillation identification methods are proposed. First, a comparison of various measurement-based electro-mechanical oscillation mode detection methods is studied. Among the measurement-based techniques, Prony analysis, Eigenvalue Realization Algorithm (ERA), and Matrix Pencil (MP) methods are found to be very useful. These methods have successfully been used to determine low-frequency oscillatory modes from measurement data. Recently, Subspace Identification (SSI) methods have become popular as they are robust to variations, and can be represented in state-space form, thus making it easier for designing time-domain control approaches. Thus, second, an online wide-area direct coordinated control architecture for power grid transient stability enhancement based on subspace identification and Lyapunov energy functions has been designed and studied. Third, a novel hybrid deterministic-stochastic online measurement-based identification framework using subspace theory is introduced. The novelty of the design using a fully recursive algorithm and the effectiveness of combined treatment are further discussed. For controlling electro-mechanical oscillations of the power system effectively, identifying the location of the oscillation source is very important. Thus, fourth, an approach for power system oscillatory mode estimation and classification and source location identification based on Lyapunov energy functions are proposed. This new method is then compared with the most commonly used method known as dissipated energy flow (DEF). Finally, this work explores grid following and grid forming control architecture of battery energy storage and the use of identification methods to observe low-frequency oscillation with Distributed Energy Resource (DER) connections.
Accurate knowledge and estimation of the electro-mechanical modes in the power system are of great importance since a system-wide outage can be caused by one single unstable mode of oscillation. Most of these unstable mode of oscillations are inter-area oscillations which typically are in the range of 0.15Hz to 1Hz. Generally oscillation identification and damping are performed based on Model-based frequency studies. However, the stochastic nature of modern power grid with the advent of renewables and changing load dynamics, and nonlinear interactions makes the oscillation study with apriori models inaccurate and inefficient. Due to these factors, recently, measurement-based power grid mode estimation has attracted great attention.
In this research work, a series of measurement-based oscillation identification methods are proposed. First, a comparison of various measurement-based electro-mechanical oscillation mode detection methods is studied. Among the measurement-based techniques, Prony analysis, Eigenvalue Realization Algorithm (ERA), and Matrix Pencil (MP) methods are found to be very useful. These methods have successfully been used to determine low-frequency oscillatory modes from measurement data. Recently, Subspace Identification (SSI) methods have become popular as they are robust to variations, and can be represented in state-space form, thus making it easier for designing time-domain control approaches. Thus, second, an online wide-area direct coordinated control architecture for power grid transient stability enhancement based on subspace identification and Lyapunov energy functions has been designed and studied. Third, a novel hybrid deterministic-stochastic online measurement-based identification framework using subspace theory is introduced. The novelty of the design using a fully recursive algorithm and the effectiveness of combined treatment are further discussed. For controlling electro-mechanical oscillations of the power system effectively, identifying the location of the oscillation source is very important. Thus, fourth, an approach for power system oscillatory mode estimation and classification and source location identification based on Lyapunov energy functions are proposed. This new method is then compared with the most commonly used method known as dissipated energy flow (DEF). Finally, this work explores grid following and grid forming control architecture of battery energy storage and the use of identification methods to observe low-frequency oscillation with Distributed Energy Resource (DER) connections.
