Purpose Nurse practitioners (NPs) have reported aspects of their jobs that they are more and less satisfied with. However, few studies have examined the factors that predict overall job satisfaction. This study uses a large national sample to examine the extent to which autonomy and work setting predict job satisfaction. Data sources The 2012 National Sample Survey of Nurse Practitioners (n = 8311) was used to examine bivariate and multivariate relationships between work setting and three autonomy variables (independent billing practices, having one's NP skills fully utilized, and relationship with physician), and job satisfaction. Conclusions NPs working in primary care reported the highest levels of autonomy across all three autonomy measures, while those working in hospital surgical settings reported the lowest levels. Autonomy, specifically feeling one's NP skills were fully utilized, was the factor most predictive of satisfaction. In multivariate analyses, those who strongly agreed their skills were being fully utilized had satisfaction scores almost one point higher than those who strongly disagreed. Work setting was only marginally related to job satisfaction. Implications for practice In order to attract and retain NPs in the future, healthcare organizations should ensure that NPs’ skills are being fully utilized.

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Background: Nurse practitioner (NP) residency/fellowship programs are an emerging industry across the country. Purpose: This study aimed to conduct an in-depth exploration about postgraduate NP residency/fellowship programs in the United States and to gain an understanding of program characteristics, educational content, and implementation methods to assist NPs to transition to practice. Methods: This exploratory study used a quantitative design to conduct an online survey of program directors of NP residency/fellowship programs to collect data about program characteristics to assist graduates to transition to practice. Descriptive statistics were calculated for continuous variables, whereas frequency and percentage were calculated for categorical variables. Results: Nurse practitioner residency/fellowship programs lack consistency in standards for educational content and delivery methods. Only 26% of the programs were accredited, and the programs were not consistently based on nationally recognized competencies. Ninety percent of the programs relied on didactic and clinical supervision delivery methods. More than 90% of the residents/fellows cared for adults older than 65 years of age and managed chronic diseases. Family Nurse Practitioner was the most commonly cited population track offered (73%). Nurse practitioner residency/fellowship programs are sparsely offered in the most rural states with underserved populations. Implications for practice: This study provides data and insight into the emerging industry of postgraduate NP residency/training programs for educators and employers. In addition, it informs regulators and decision makers about the quality and consistency of programs and the impact of programs on the care delivered by new graduate NPs.

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Class enrollment sizes for online learning in higher education, a topic of persistent interest in the academic literature, impact student learning, pedagogical strategies, school finances, and faculty workload. Yet in the research literature, class size is addressed with insufficient specificity to provide enrollment direction. Seeking guidelines for determining online class sizes, the authors conducted a qualitative research synthesis from 43 recent higher education journals, yielding 58 evidence-based articles. It is clear that no one size fits all. Findings reflect that large classes (≥ 40 students) are effective for foundational and factual knowledge acquisition requiring less individualized faculty-student interaction. Small classes (≤ 15 students) are indicated for courses intending to develop higher order thinking, mastery of complex knowledge, and student skill development. Pedagogical intent should dictate class size. Using well-established learning theories, the authors describe current understandings of online enrollments and propose an analytical framework for pedagogically driven, numerically specific class sizes. Highlights:• There is academic interest in online course sizes in higher education.• Research indicates "no one size fits all" online classes.• Class sizes should be based on learning level and identified pedagogical intent.• Large classes are appropriate for foundation-level learning.• Small classes are appropriate for learning requiring higher order thinking.