Jennifer Saylor

Prof. Dr. Jennifer Saylor

School of Nursing, University of Delaware, Newark, California, USA
orcid

Research Focus & Metrics

Academic Career Length

22Years (2005-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2016 in Nurse Educator
Verified
Journal Article
Closed access
Jennifer SaylorJennifer Saylor
Jennifer Saylor
SVStephanie Bsn Vernoony
Stephanie Bsn Vernoony
JSJanice Dnsc Selekman
Janice Dnsc Selekman
ACAmy Msn Cowperthwait
Amy Msn Cowperthwait
This quasi-experimental pretest-posttest study measured self-efficacy, attitudes toward physician-nurse collaboration, and interprofessional competencies as outcomes of a palliative care simulation. Based on experience level, teams of participants, 1 consisting of nursing/medical students and the other of nursing/medical health care professionals, completed a palliative care simulation as part of their education. Self-efficacy and attitudes toward physician-nurse collaboration were measured before and after simulation. Interprofessional competency was measured during the simulation. The results revealed a significant improvement in the previously mentioned measures, and interprofessional competency scores varied by profession and evaluator.

25 August 2021 in Journal of Nursing Management
Verified
Journal Article
Open access
PDF file
MNMichelle M. Ness
Michelle M. Ness
Jennifer SaylorJennifer Saylor
Jennifer Saylor
LDLeigh Ann DiFusco
Leigh Ann DiFusco
KEKristen Evans
Kristen Evans
Aim: To understand the impact of professional stressors on nurses’ and other health care providers’ professional quality of life and moral distress as they cared for patients during the COVID-19 pandemic. Background: Healthcare providers caring for patients during the COVID-19 pandemic are at increased risk of decreased professional quality of life and increased moral distress. Methods: A convergent mixed-methods design and snowball sampling was used to collect survey data (n=171) and semi-structured interviews (n=23) among healthcare providers working in the inpatient setting. Results: Perceived lack of support from executive leadership, access to personal protective equipment, and constantly changing guidelines led to decreased professional quality of life and increased moral distress among healthcare providers. Conclusion: Findings from this study indicate that shared governance, disaster management training, and enhanced communication can assist executive leadership to reduce the likelihood of decreased professional quality of life and increased moral distress in front line healthcare providers. Implications for Nursing Management: Executive leadership must acknowledge the significance of the role of healthcare providers at the bedside. Following the principles of shared governance, disaster management training, and open communication are crucial to ensure that healthcare providers are adequately informed and supported at the bedside.


1 May 2012 in Nursing Research
Verified
Journal Article
Closed access
Jennifer SaylorJennifer Saylor
Jennifer Saylor
EFErika Friedmann
Erika Friedmann
HLHyeon Joo Lee
Hyeon Joo Lee
The National Center for Health Statistics conducts the National Health and Nutrition Examination Survey and other national surveys with probability-based complex sample designs. Goals of national surveys are to provide valid data for the population of the United States. Analyses of data from population surveys present unique challenges in the research process but are valuable avenues to study the health of the United States population. The aim of this study was to demonstrate the importance of using complex data analysis techniques for data obtained with complex multistage sampling design and provide an example of analysis using the SPSS Complex Samples procedure. Illustration of challenges and solutions specific to secondary data analysis of national databases are described using the National Health and Nutrition Examination Survey as the exemplar. Oversampling of small or sensitive groups provides necessary estimates of variability within small groups. Use of weights without complex samples accurately estimates population means and frequency from the sample after accounting for over- or undersampling of specific groups. Weighting alone leads to inappropriate population estimates of variability, because they are computed as if the measures were from the entire population rather than a sample in the data set. The SPSS Complex Samples procedure allows inclusion of all sampling design elements, stratification, clusters, and weights. Use of national data sets allows use of extensive, expensive, and well-documented survey data for exploratory questions but limits analysis to those variables included in the data set. The large sample permits examination of multiple predictors and interactive relationships. Merging data files, availability of data in several waves of surveys, and complex sampling are techniques used to provide a representative sample but present unique challenges. In sophisticated data analysis techniques, use of these data is optimized.

1 February 2018 in Nurse Education Today
Verified
Journal Article
Closed access
Jennifer SaylorJennifer Saylor
Jennifer Saylor
LHLindsey Hertsenberg
Lindsey Hertsenberg
MMMalissa McQuillan
Malissa McQuillan
AOAshley O'Connell
Ashley O'Connell
KSKimberly Shoe
Kimberly Shoe
CCChristina J. Calamaro
Christina J. Calamaro

27 June 2018 in The Diabetes Educator
Verified
Journal Article
Closed access
PDF file
Jennifer SaylorJennifer Saylor
Jennifer Saylor
SLSara Lee
Sara Lee
MNMichelle Ness
Michelle Ness
JAJodie M. Ambrosino
Jodie M. Ambrosino
EIEmily Ike
Emily Ike
CCChristina Calamaro
Christina Calamaro
Purpose: The purpose of this study is to examine the characteristics and health outcomes of college students with type 1 diabetes mellitus (T1DM) as it relates to membership in a local university-based diabetes student organization. Methods: This descriptive, correlational research design is a secondary analysis of data. The sample consisted of nationally representative young adults in college (n = 317) between 18 and 30 years of age who were diagnosed with T1DM. Data were collected during April 2017 using a secure electronic diabetes management survey to inquire about self-reported barriers to diabetes management, hypoglycemia, and diabetic ketoacidosis of members of a diabetes organization. Results: Students were evenly distributed from freshman to senior year of college with a slight decrease at the graduate level. Students who were affiliated members of a student-led diabetes student organization were less likely to report increased levels of isolation, depressive symptoms, and anxiety related to their diabetes than were general members. Conclusion: Participation in a university-based diabetes student organization on campus and connecting with other college students with diabetes may have health benefits. In conclusion, the current study underscores the potential importance of peer-led, diabetes-specific support for adolescents emerging into adulthood.