The Journal of School Nursing
2021, Vol. 37(5) 343—352© The Author(s) 2019Article reuse guidelines:sagepub.com/journals-permissionsDOI: 10.1177/1059840519871606journals.sagepub.com/home/jsn
The prevalence and contributing factors of workplace bullying (WPB) are unknown among school nurses (SNs) in kindergarten to 12th grade programs. The aim of this cross-sectional study was to examine individual and organizational characteristics of WPB in a sample of SNs in Virginia. Based on the Short-Negative Acts Questionnaire, 40% of nurses did not experience bullying behavior, 34.8% of nurses faced occasional bullying (now and then or monthly), and 25.3% of nurses were frequently bullied (weekly or daily). Backward stepwise regression demonstrated the predictor variables of being non-White, a licensed practical nurse, or not involved in student individual education plans were significantly associated with being bullied. Administrators/supervisors need to be aware of the existence of WPB.
school nurse, workplace bullying, Short Negative Acts Questionnaire, quantitative
Among adults, workplace bullying (WPB) is a universal problem that exists in a diverse spectrum of occupations. The industries that experience WPB span to include health care, education, and even law enforcement (Fahie & Devine, 2014; Farr-Wharton, Shacklock, Brunetto, Teo, & Farr-Wharton, 2017; Sauer & McCoy, 2017). While it is well established that bullying is not acceptable in the workplace, it is a common occurrence of workplace violence, with one third of nurses experiencing WPB (Center for Disease Control and Prevention [CDC], 2018).
Both the education and health-care fields are impacted by WPB (Fahie & Devine, 2014; Sauer & McCoy, 2017). For classroom teachers, bullying may be directed at them in the form of verbal abuse and the creation and spreading of rumors by students as found in a study in Turkey (Ozkilic, 2012). Conversely, in the health-care industry, Sauer and McCoy (2017) found that in a sample of 309 hospital nurses in the United States, 40% of nurses working in direct patient care were bullied. Coupling the health-care and education fields, a unique role emerges in that of school nurses (SNs). SNs are specialized personnel who operate within school health offices supporting both teaching and wellness. No published research has been conducted about the impact of WPB on this profession despite their unique environmental circumstance (Cowell & Bergren, 2016). The complexity of bullying among SNs requires in-depth research to understand its contributing factors.
Bullying, a form of workplace violence, occurs when one or more persons show hostility or repeated negative behavior toward another person over time (CDC, 2018). Such behavior may include any form of verbal abuse, sabotage, and humiliation (Laschinger, Grau, Finegan, & Wilk, 2010). The impacts of WPB on an individual can include stress and a decrease in work productivity as indicated in a study of Australian nurses (Farrell & Shafiei, 2012). Being a victim to these forms of abuse is associated with poor psychological health which can be a catalyst for a number of larger mental or physical wellness symptoms (Neto, Ferreira, Martinez, & Ferreira, 2017; Verkuil, Atasayi, & Molendijk, 2015). As a result of WPB, retaining talent and skilled workers becomes difficult due to job turnover as found in studies conducted in Canada and Australia (Gillet, Forest, Benabou, & Bentein, 2015; Rodwell, Brunetto, Demir, Shacklock, & Farr-Wharton, 2014). The psychological as well as physical effects of WPB are ultimately associated with financial repercussions to the organization (Fattori et al., 2015).
Individual characteristics are associated with bullying (Buunk, Franco, Dijkstra, & Zurriaga, 2017). Buunk, Franco, Dijkstra, and Zurriaga (2017) examined school and hospital employees in Uruguay and reported that women were more likely to be bullied more than men in both professions. One reason for the difference might be women are less aggressive, thus exposing them to more acts of bullying (Eriksen & Einarsen, 2004). Age is associated with bullying, with younger and older individuals being most affected. Younger people were less likely to be bullied than older people (Buunk et al., 2017). Johnson (1988) found nursing education level was associated with effective communication and problem-solving skills, which are necessary when responding to WPB incidents. However, researchers in Korea and Brazil did not find level of education to be associated with WPB (An & Kang, 2016; Fontes, Santana, Pelloso, & Carvalho, 2013). As SNs may possess varying levels of education degree, education level was examined in this study.
WPB as it exists in the nursing profession has been explored to offer some important insights on its effect on individuals’ emotional and physical health (Houck & Colbert, 2017; Sauer & McCoy, 2017). The impact of bullying may include low self-esteem, physical symptoms, and psychological symptoms (McKenna, Smith, Poole, & Coverdale, 2003; Sauer & McCoy, 2017). Furthermore, those who experienced verbal abuse and humiliation report having headaches and weight loss (McKenna et al., 2003).
Harassment and negative behavior are also prevalent yet underreported among teachers, a profession closely associated with SNs (Espelage et al., 2013). School teachers experience physical abuse, verbal abuse, and theft in the workplace (Fahie & Devine, 2014; Galand, Lecocq, & Philippot, 2007; Sinha & Yadav, 2017). The ramifications of WPB on teachers in Ireland, Belgium, and India negatively impact the school environment, affecting both students and other school staff (Fahie & Devine, 2014; Galand et al., 2007; Sinha & Yadav, 2017). On a daily basis, the key agents who engage with students are teachers and other school staff. However, SNs work side by side with the academic staff and intervene when students have health- and medical-related conditions.
As a specialty of nursing, SNs have a critical role in the educational system (National Association of School Nurses [NASN], 2016). School nursing was established in 1902 for the sole purpose of having children return back to school after they were sent home for minor treatable medical conditions (Houlahan, 2018). Over the years, the role of nurses in schools has evolved to include overseeing the health needs of students, being a stakeholder of the student’s Individualized Education Plan (IEP), and serving as health educators (NASN, 2016). In 2017, more than 50 million students were registered to attend public schools with an additional 5 million in private schools (National Center for Educational Statistics, 2018). As minors, the majority of children’s day is spent in an institution where they rely on the school’s health office and the SNs’ medical expertise to support their health and well-being. If those staff are themselves suffering from the effects of being bullied, they may not be able to address the needs of students.
The socioecological model (Bronfenbrenner, 1979) provides the theoretical bases for this study. The model describes how an individual is continuously influenced by their environment through 4 nested layers: the microsystem, the mesosystem, the exosystem, and the macrosystem (Figure 1). The microsystem encompasses relationships between the SNs and their coworkers and supervisors within their immediate environment. Some nurses provide care in designated health office while others may use shared space within the one or more schools they are assigned. Additionally, SNs may have more than one supervisor, a nursing or health-related supervisor and a school supervisor (i.e., principal).
The second layer, mesosystem, encompasses the interactions between groups, including teachers, students, administration, social workers, school counselors, parents, food services staff, transportation staff, and external consultants who are involved with the student’s learning. The relationships within the said groups are part of the organizational characteristics and may vary depending on the number, size, level (elementary school, middle school, or high school), and type of school (public or private).
The microsystem and the mesosystem are both nested in the third layer, the exosystem. The exosystem comprises external factors of the environment, which affect the individual indirectly (Bronfenbrenner, 1979). For SNs, components of the exosystem would include the school board or unions. Finally, the macrosystem encompasses the societal characteristic ideologies that ultimately influence each of the internal layers (Bronfenbrenner, 1979). Financial decisions and laws instated at the district- or state-level affect the SNs work environment.
In line with more current research, the specific contextual variables described in Bronfenbrenner’s theory as well as the focus on proximal and distal factors surrounding the individual within an organization are relatively similar to more recent theories (Johns, 2006). In order to promote healthy interactions and relationships within the context of the school setting, SNs should be able to identify factors that interfere with their ability to provide care for students.
Utilizing Bronfenbrenner’s model offers a theoretical basis for understanding environmental layers contributing to WPB. The education system community in which SNs work and interact is complex. The SN is influenced by their interaction with work colleagues, parents, students, administration, the organization, physical work location, and laws. To fully explore WPB within the context of the SN’s environment, this study aimed to determine which organizational and demographic characteristics were associated with bullying among SNs employed in the state of Virginia.
This study used a cross-sectional, survey design and was approved by George Mason University’s Institutional Review Board (Protocol# 1326562).
Virginia was chosen as the state to conduct this research due to its accessibility and diversity of the population. The school districts service urban, suburban, and rural areas across multiple socioeconomic levels offering a racially and ethnically diverse population of citizens. Currently, there are 1,855 public schools and 923 private schools in Virginia (Virginia Department of Education [VDOE], 2018). The total number of SNs employed in Virginia is unknown as there are no standardized requirements for school systems to employee nurses. However, 527 SNs are current members of Virginia Association of School Nurses (VDOE, 2018).
A convenience sample of SNs from Virginia were recruited using the Virginia School Nurses Listserv, social media, and snowball sampling. Frontline registered nurses (RN), licensed practical nurses (LPN), and licensed nurse practitioners (NP) who provided direct care to students were included in the study. Individuals who functioned in the capacity as SNs but were not licensed practitioners, such as secretaries, nurse’s aides, teachers, nursing assistants, or clinic volunteers, were excluded. Additionally, nurse managers, supervisors, and administrators were also excluded. In order to sufficiently capture WPB over a period of time, participants had to be employed in their current school nursing position for at least 9 months. Screening questions at the beginning of the survey were used to establish eligibility.
The sample size was estimated by power analysis a priori using Cohen’s (f2) formula (Soper, 2019). In the absence of available research to support an effect size, a medium effect size (.15) was used in the power analysis. Based on a power of .80 and the conventional statistical significance level (α) of .05, 142 nurses were needed to detect the effect size in a multiple regression analysis using 16 predictors. The final sample size for this study was n = 178.
Demographics. Demographic and organizational characteristics were chosen based on the literature and the theoretical model. Eight items to measure demographic characteristics included age, sex, race, ethnicity, nursing education, years as a nurse, years working as a SN, and union membership (Virginia Education Association [VEA], 2019). Organizational characteristics were chosen based on the theoretical model for this study and included level of school (elementary, middle, and high school), number of schools for which the nurse is responsible, type of school (private/public), Title 1 school status (schools which receive federal funding based on a large majority of students coming from low income families. The funding is to meet the educational needs of students), involvement in IEP/504 meetings, supervision by a nursing supervisor, and supervision by a non-nursing leader.
WPB: Short Negative Acts Questionnaire (S-NAQ). WPB, the dependent variable, was measured by the S-NAQ. The S-NAQ was developed to measure exposure to bullying in the workplace among employees in Norway with Cronbach α of .85 by Einarsen, Hoel, and Notelaers (2009). The S-NAQ is composed of 9 items describing negative behavior statements that may be encountered in the workplace. The term bully is not used so as to ensure a more objective evaluation of the bullying behavior. The 9 items were rated on a 5-point Likert-type scale ranging from never (1) to daily (5). The total sum of the S-NAQ scores ranges from 9 to 45.
Conway and colleagues (2018) identified three optimal cutoff points for assessing the frequency of bulling for the S-NAQ: not bullied (<12), occasionally bullied (12–15), and frequently bullied (>16). For this study, cutoff points as identified by Conway et al. (2018) were used to measure the prevalence of bullying among SNs. After S-NAQ scale items, a single item on the questionnaire asked the participant whether he/she self-identified as being bullied on a 5-point Likert-type scale ranging from never to everyday based on a definition (Einarsen, Hoel, & Notelaers, 2009). This question was used to compare the S-NAQ results to the respondents’ self-labeling of WPB.
To measure the prevalence of WPB for our study, the respondents were asked to identify whether they had experienced bullying behavior in the past 9 months rarely, now and then, and several times per week or daily. Nine months was chosen, as SNs work according to the school academic calendar. The Cronbach’s α for the S-NAQ for this study was .888.
Data were collected through an online Internet-based survey platform, Qualtrics® (Qualtrics, Provo, UT). An electronic online survey link was embedded in a recruitment e-mail posted on the first author’s Facebook® page as well as emailed to SNs by the VASN. To ensure that all SNs were given the opportunity to participate, snowball sampling was also used. In order to provide a more objective evaluation of the bullying behavior as well as not influence study participants, the word “bullying” was not used in the recruitment script or consent form. The survey was open and available for participants for 4 weeks in October 2018. The participants were not able to return to questions previously completed. Two reminder messages were sent using Facebook® and VASN e-mail, 2 weeks apart after the first message. All data collected through Qualtrics® were secure and anonymous. Participants had the opportunity to be entered into a lottery for a US$25.00 gift card after completing the survey.
A total of 211 SNs completed the online questionnaire. Those participants who did not meet the screening eligibility questions (n = 18) were excluded from the analyses. Incomplete questionnaires (n = 4) and those who did not answer the S-NAQ survey (n = 11) were deleted from the study. The number of surveys included in the analysis was 178.
Data analysis was done using IBM Statistical Package for the Social Sciences (SPSS), Version 25.0 (IBM Corp, 2018). The data were assessed for missing data using frequency distributions. Two variables, race and working in a Title 1 school, were missing in two cases (1%); therefore, casewise deletion was used. Data were also assessed for outliers by visual inspection of boxplots or scatterplots. Descriptive statistics were computed on all study variables to determine the frequency of WBP among the sample of Virginia SNs.
Assumptions of multiple regression were evaluated for linearity, normality, homoscedasticity, and multicollinearity among the independent and dependent variables. The level of significance was set a priori as .05 for all statistical tests. To ensure normality, the variables were assessed by visually inspecting graphs and using the Shapiro—Wilk test. Three categorical variables were coded into dummy variables for the regression analysis. Race was regrouped to White and non-White as there was insufficient sample size to distinguish among the non-White group. Number of schools was collapsed into one or more than one school because those nurses who had more than two school were few therefore grouped together as more than one school. Finally, nursing education was regrouped into LPN, diploma/associate, and graduate, with bachelor’s as the reference.
Once assumptions were met, backward stepwise regression analyses were conducted. A backward stepwise regression model was built to predict the sum score of the S-NAQ based on the following factors: years of school nursing experience, whether the nurse was a union member, level of nursing education (LPN, diploma/associate, graduate degree), race, number of schools a nurse is responsible for, the level of school the nurse worked in (middle school, high school, or combination schools), whether the nurse was working in a Title 1 school, whether the nurse was involved in an IEP/504 meetings, total number of students the nurse was responsible in their individual school or combined schools, and whether the nurses were supervised by two supervisors. Gender and ethnicity were not included in the regression analysis due to lack of variability. All 16 variables were entered into the model at the same time. The predictor variables with the largest p value were eliminated from the model and those remaining variables that met the criterion of the regression model (p < .05) were retained.
Table 1 summarizes demographic characteristics of the sample of 178 SNs included in the study. Most of the nurse respondents were female (98.9%), non-Hispanic (97.2%), and White (90.4%), with at least a bachelor’s degree (62.3%). The mean age of nurses was 51 years (M = 51.45, SD = 8.69), and mean years of school nursing experience was 11 years (M = 11.10, SD = 7.16). There was a higher representation of nurses who worked in public schools (97.8%) as compared to those working in private schools (2.2%).
Table 2 shows the results of the organizational characteristics of the sample. Half (50.0%) of SNs worked in a pre-school/elementary school with most nurses assigned to one school (84.8%). Majority of the nurses (80.9%) were invited to be a part of a student’s IEP/504 meeting. Supervision of SNs may be from a nursing or non-nursing supervisor; however, 89.3% reported being managed by both.
The frequency of bullying exposure for S-NAQ was calculated by the sum score of the 9 items, with higher scores indicating a higher frequency of WPB. The mean scores of S-NAQ items are shown in Table 3. The sum score for the S-NAQ Scale for this study was 9–42, with an overall mean of 13.98 (SD = 5.58). Table 4 presents the frequency of bullying based on Conway et al. (2018) cutoff scores and the single item self-report of being bullied. According to the S-NAQ, the prevalence of bullying occasionally or frequently in Virginia SNs was 60.1%. Although 40% of SNs reported not being bullied based on the S-NAQ, 80% of nurses did self-identify based on the single question.
Table 5 shows the results of the first model (Model 1) of the multiple regression analysis, which includes all possible predictor variables from the list discussed previously, as well as the final model (Model 13), which includes only the statistically significant predictors of WPB. In this study, three variables were significant predictors of WPB among SNs: two individual characteristics, race (non-White) and education (LPN), and one organizational characteristic, invited to IEP/504 meetings. LPNs reported experiencing more bullying as compared to Bachelor’s prepared nurses, non-White nurses reported experiencing higher bullying behavior than White nurses. There was an inverse relationship with WBP and nurses who were involved in the IEP/504 meetings, which indicates those SNs experienced less bullying if they were invited to the meetings. The final model explained 14% of the variance in WPB, R2 = .144, F(1, 173) = 1.620, p < .01. The regression analysis did not show an association between the experience of bullying behavior, on the one hand, and years as a SN experience, union membership, level of school, total number of students, or having two different supervisors, on the other hand.
This is the first study to determine the prevalence of bullying among a sample of SNs in Virginia. Our study revealed that 60.1% of Virginia SNs experienced bullying, and 39.9% did not experience any bullying behavior according to the S-NAQ. School nurse data for Virginia alone were not available; however, the sample characteristics of this study, specifically the age, gender, and experience of the SNs along with the number and type of schools, are consistent with the findings of the national SN survey conducted by Willgerodt and colleagues (2018).
Our study found a lower prevalence of SNs who identified themselves as a victim of bulling behavior based on the single definition of being bullied in comparison to the S-NAQ. Studies have identified differences when reporting the prevalence of bullying using the self-reported method. Among athletic trainer, Pitney, Weuve, and Mazerolle (2016) identified a higher prevalence of those who selflabeled as being victims of bullying. On the contrary, Simons (2008) found a lower prevalence of those who self-labeled as being bullied in a study with new nurses over a 6-month period. This may be due to the stigma associated with being a victim of bulling leading to reticence regarding labeling the behavior as bullying, thus underreporting the bullying experience (Lutgen-Sandvik, Tracy, & Alberts, 2007). Additionally, the participant’s definition of bullying may be different than what was provided in the S-NAQ, as, it is unclear why, further investigation may need to be explored.
Due to the lack of bullying research in school nursing specifically, the findings were compared to nursing and education in general. Sauer and McCoy (2017) surveyed nurses across one state in the United States and reported 40% of nurses were bullied in the past 6 months. Yokoyama et al. (2016) reported the prevalence of bulling in Japanese nurses as 18.5% in the previous 6-month time frame. When examining bullying within K–12 education school systems, Druge, Schleider, and Rosati (2016) found 37.4% of teachers reported bullying. The prevalence of bullying against SNs is higher compared to other nursing specialties as well as the field of education. These differences could be explained by the use of the longer 22-item Negative Acts Questionnaire–Revised (NAQ-R) as compared to our using the shorter version of the NAQ-R. Another possible explanation of the differences in the results may be explained by the unique school nursing work environment and the absence of uniform standards for school nursing across the country.
Race was a significant predicting factor for WPB in this study. Bullying was reported at higher frequency by those who identified as a minority in comparison to their counterparts. These findings are consistent with results from a U.S.- based study conducted in various occupations and positions (n = 265) in which the authors reported lower incidents of general bullying behavior by White employees as compared to other races (Fox & Stallworth, 2005).
According to CDC (2017), only 22.4% of school districts have specific nursing education requirements for newly hired SNs. NASN recommends a bachelor’s degree as the minimum educational requirement for being employed as a SN. However, various education levels for entering the nursing workforce exist, including LPN, diploma, associate degree, or bachelor’s degree programs. In this study, LPNs experienced more frequent bullying than nurses with bachelor’s degree. However, An and Kang (2016) did not find education level to be a significant predictor of WPB in nurses. In schools, where the SN is not a RN, LPNs or unlicensed clinic aides are working in the role of the nurse. State laws usually require LPNs and clinic aides to be supervised by a RN due to their more limited scope of practice and assessment skills, particularly for students with complex health conditions (National Council of State Board of Nursing, 2012). The percentage of districts that hire LPN is much lower than those employing RN’s (CDC, 2017).
Another finding from the regression model was that nurses who were invited to IEP/504 meetings experienced less frequent bulling behaviors. Being invited to be part of the special education team may be evidence that the SN is more valued by the academic coworkers. Further, 67.4% of school districts have policies and guidelines that require SNs to participate in the development of IEP for students (CDC, 2017).
The socioecological model guided this study to explain the unique and complex work environment of SNs potentially contributing to WPB. Clearly, based on the model, there are many factors that could explain bullying outside of the demographic or organizational structure. The results of this study indicated that 14% of the variance in WBP was explained by the variables explored in the model. As such, there may be indications of additional contributing factors for WPB among SNs. For example, supervisor support may be an important factor for explaining bullying behavior despite our current findings that having two supervisors did not contribute to bullying behaviors (Desrumaux, Gillet, & Nicolas, 2018). Additional factors that may need to be explored, which may put SNs at risk for WBP, could include examining the contextual proximal factors compared to the distal factors based on the theoretical model.
There are several limitations to this study. The study was limited in terms of generalizability. Only SNs who work in the Commonwealth of Virginia were recruited, restricting the generalizability of the findings to one state. This may not be particularly problematic with regard to the demographic characteristics of SNs because the SNs in this sample exhibited demographic commonalities related with SNs nationally. However, the organizational structure for SNs in Virginia may not be consistent with other states nationally as there are no universal organization structure and employment standards.
Study participants were recruited by convenience sampling and thus may not be representative of the population resulting in sampling bias (Polit & Beck, 2012). The results may be skewed or may not be generalizable to the entire Virginia SN population. Additionally, self-report data collection has several challenges and recall bias is one of them (Polit & Beck, 2012).
Participants may not recognize or may be too embarrassed to admit that they were bullied, leading to inaccuracies in responses by either overstating or understating theirbullying experience. However, the use of the word “bullying” was not used in the study description, the informed consent, and the instrument used to assess being bullied in order to ensure that bullying was not the main focus of the survey. By using behavioral statements, we may have helped mitigate some of the issues of recall bias. Even though the S-NAQ is a robust tool, SNs may have a different definition of bullying than what was provided to them in the self-labeling question.
Nursing is predominately a female profession. Although every effort was made to include all SNs in Virginia, there may have been a possibility that male participants were not available or may not have volunteered to participate in the study. Therefore, the results may not be generalizable across genders. Furthermore, it is possible that there are perception differences of “being bullied” among the genders, and this may be worth exploring in future studies.
This was a cross-sectional survey design; causal relationships cannot be established between associated factors and WPB. A longitudinal study would be needed to better examine the variables of organizational characteristic, demographics, and WPB to determine causality.
This study provides an insight into the prevalence and frequency of WPB in SNs. The first implication is clearly that WPB is a problem in this nursing specialty. Even though the study only included Virginia, there is sufficient indication that the problem is a national issue. Moreover, based on the discrepancy between experiencing bullying behavior and self-labeling as having been bullied, SNs may not recognize or identify themselves as being bullied. The role of the SN is different than teachers, the school districts could cultivate a culture and environment of being more inclusive. Education regarding bullying programs should be included in the orientation process and yearly thereafter to change the organizational culture and provide a healthy workplace for employees. In addition, as race was a significant predictor to bullying, diversity training should be developed and reinforced at regular intervals, which may help in a more inclusive schoolwork environment. Although no federal laws exist for WPB at the organizational level, there are regulations against harassment in which employers have to provide a safe work environment.
School and health administrators should value the role of SNs in special education planning for students with special needs and thus include them in the process. By being engaged in the IEP/504 meetings, these nursing professionals can provide the necessary medical expertise for school personnel and parents to ensure the safety and success of students in schools. As nurses who were invited to IEP/504 meeting were bullied less, SNs can be more communicative and engaging with the educational team so the school staff and teachers can continue to understand their role. SNs can possibly influence the staff around them and change the behavior of a bullying culture if one exists in their workplace. Nurses are in the position to coordinate student care and should proactively education for the students and themselves to be included in the educational team meetings.
Currently, what is known about bullying is largely based on empirical studies among inpatient hospital nurses and K–12 school educators. What remained unknown until now was whether SNs were victims of bullying. Findings from this study fill the gap in the current school nursing literature by identifying the demographic and organizational factors associated with WPB. Furthermore, this study shows that bullying is not only limited to nurses working in the inpatient hospital setting but is also impacting nurses in the community as well. Future research is needed to better understand factors contributing to WPB in the unique school nursing environment. Bullying may affect the physical and psychological health of SNs, and if they are not able to perform in their jobs, the trickling effect would ultimately be the health of students they serve.
Shashi Sharma and Katherine Scafide contributed to conception/design and draft of the manuscript. All authors contributed to acquisition, analysis of data, critical revisions, gave final approval, and agreed to be accountable for all aspects of work ensuring integrity and accuracy.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Shashi Sharma, PhD, RN https://orcid.org/0000-0002-3017-0575
Erin Maughan, PhD, RN, PHNA-BC, FNASN, FAAN https://orcid.org/0000-0002-0176-1499
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Shashi Sharma, PhD, RN, was a doctoral student at George Mason University, Fairfax, VA, USA.
Katherine Scafide, PhD, RN, is a assistant professor at George Mason University, Fairfax, VA, USA.
Reeshad S. Dalal, PhD, is a associate professor of Industrial and Organizational Psychology at George Mason University, Fairfax, VA, USA.
Erin Maughan, PhD, RN, PHNA-BC, FNASN, FAAN, is the director of research at National Association of School Nurses, Silver Spring, MD, USA.
1 George Mason University, Fairfax, VA, USA
2 National Association of School Nurses, Silver Spring, MD, USA
Corresponding Author:Shashi Sharma, PhD, RN, George Mason University, 4400 University Drive, Fairfax, VA 22030, USA.Email: ssharm22@gmu.edu
