Most nurses will encounter dying patients at some point in their career, particularly with the increasing use of end-of-life (EOL) care services (Teno et al., 2013). Nevertheless, it is widely acknowledged that nurses and nursing students are often inadequately prepared to care for this population (Kent, Anderson, & Owens, 2012; Zheng, Lee, & Bloomer, 2016). Adequate preparation of the health care workforce in this area has become a national concern. The National Institutes of Health (2004) reported that research is needed to address health–systems issues regarding health care provider education to ensure patients receive high-quality EOL care. Consequently, the focus on educational needs regarding EOL issues among nurses and the associated gaps in nursing education has intensified.
Ineffective educational preparation in the care of dying patients may adversely affect patient care quality, safety, and satisfaction. Given the significant role academic nursing programs play in preparing the workforce to care for this vulnerable population, it is imperative that they engage in rigorous program evaluation and improvement efforts regarding EOL care. The CIPP (Context, Input, Process, Product) model by Stufflebeam et al. (1971) is a highly regarded evaluation model among education scholars and provides a useful lens for evaluating nursing education programs. The CIPP model recognizes four components of program evaluation: context, inputs, processes, and products. Evaluations based on the product component are used to identify and evaluate program outcomes (intended and unintended) against stakeholder needs. Presumably, dying patients need nurses who are knowledgeable about their health care needs, are competent to deliver the care they need safely, and can communicate compassionately. However, academic nursing programs are not consistently producing outcomes that support these needs.
Baseline knowledge assessments demonstrate that nursing students' lack content familiarity in many domains of EOL care, such as psychological, spiritual, and basic principles of palliative care (Al Qadire, 2014; Wochna Loerzel & Conner, 2014). Although knowledge about care of the dying increases as nursing students progress through their academic programs (Wallace et al., 2009), some deficits remain on entering practice (Brajtman, Fothergill-Bourbonnais, Casey, Alain, & Fiset, 2007). Nursing students report low perceived competence in caring for dying patients, particularly in the early stages of their education (Adesina, DeBellis, & Zannettino, 2014). Although self-efficacy regarding the care of dying patients among nursing students is lower than that of practicing nurses, even experienced nurses report feeling situational deficiencies (Pfister et al., 2013). Targeted educational strategies focused on teaching students about EOL care can help to enhance perceived competence (Efstathiou & Walker, 2013; Moreland, Lemieux, & Myers, 2012).
Nursing students report high fear and anxiety levels toward death and caring for dying patients, particularly in the early phases of academic programs (Smith-Stoner, Hall-Lord, Hedelin, & Petzäll, 2011). The effects of targeted education on attitudes toward death and care of the dying are mixed. For example, some studies reported that targeted education resulted in improved attitudes about caring for dying patients (Bailey & Hewison, 2014; Conner, Wochna Loerzel, & Uddin, 2014; Dobbins, 2011; Lippe & Becker, 2015); however, another study found that EOL education may adversely affect students' attitudes via increasing awareness of the scope of EOL care or enhanced abilities to evaluate their capabilities and competence (Mutto, Cantoni, Rabhansl, & Villar, 2012).
This limited evidence suggests that some improvement in the areas of knowledge, perceived competence, and attitudes regarding EOL care occurs among nursing students as they progress in academic nursing programs. However, it appears that not all deficits are resolved by the end of formal educational programs. In addition, specific trajectories of improvement in these student outcomes within all students enrolled in nursing education programs, as opposed to solely students at opposite ends of the curriculum, have not been identified. Knowledge about patterns of change in students is needed to identify the effectiveness of various components of nursing education programs and guide curriculum development in the areas of EOL care. Consequently, this study was designed to examine the differences in student outcomes regarding EOL care within and between subgroups of nursing students in a single bachelor of science in nursing (BSN) program.
An exploratory, descriptive, observational study design involving cross-sectional surveys of five subgroups of nursing students in a BSN program was applied to address the study aim. The study was conducted at a large, state-funded, research-intensive university in the southern region of the United States. Nursing students are admitted to the BSN program twice per year, with approximately 60 students admitted per cycle. In addition to the BSN program, the university offers BSN completion and multiple graduate programs at both master's and doctoral levels. The nursing curriculum at the study site integrates EOL content throughout the curricula instead of being concentrated in a single course. Students are not admitted into the nursing program until lower division prerequisite courses are completed. Students were naturally grouped into subgroups based on the date of admission and status of progression in the curriculum. The five subgroups included prenursing students (PNs), first-semester juniors (J1s), second-semester juniors (J2s), first-semester seniors (S1s), and second-semester seniors (S2s). These naturally occurring subgroups were used as the basis for the cross-sectional comparison of three educational outcomes: knowledge of EOL care, perceived competency in meeting standards of care for dying patients, and attitudes toward caring for dying patients. These outcomes were assessed in a convenience sample of students in each subgroup at the beginning of the fall 2015 academic semester. Students were eligible to participate in the study if they were first-time enrollees in at least one required nursing course. Students repeating any required course for any reason were excluded.
Consistent with Desbiens and Fillion (2011), perceived competence was defined as “a cognitive construct that refers to nurses' judgment of their capabilities to provide quality care to patients and family experiencing a life-limiting illness or at end of life” (p. 230) and was measured using the Perceived Competence in Meeting End of Life Nursing Education Consortium Standards (PC-ELNEC) instrument (Lippe & Becker, 2015). Attitudes toward care of the dying was defined as student anxiety regarding caring for individuals in the final 6 months of life and was measured using the Frommelt Attitudes Toward Care of the Dying (FATCOD) instrument (Frommelt, 1991). Acceptable psychometric properties for these instruments has been previously reported for PC-ELNEC (Cronbach α = .94) and FATCOD [(Cronbach α = .83); (Lippe & Becker, 2015). Knowledge was defined as retention of sufficient information on all key aspects of EOL care and was measured using the ELNEC Knowledge Assessment Test (KAT) (Lange, Shea, Grossman, Wallace, & Ferrell, 2009). Acceptable discriminant validity and internal consistency (Cronbach α = .84) for the KAT has been reported (Lange et al., 2009).
Additional study variables included age, previous experiences with death (e.g., loved ones, friends, and pets) and caring for dying patients, religious affiliation, previous education on EOL care, and engagement in EOL simulations. These variables were measured by items developed for this study and combined with instruments for the outcome variables into survey packets. Students required 20 to 45 minutes to complete each survey. The survey packets also included eight items used to create unique identification codes (Damrosch, 1986).
Data Collection Procedures
This study was approved by the university's institutional review board. Students in each subgroup were informed about the study by the principal investigator (M.L.) during their required courses at the beginning of the semester. Completion of surveys was accepted as informed consent in lieu of signed consent documents. No incentives for participation were provided. At the discretion of individual course faculty, students were either allowed to complete paper surveys during scheduled class time or provided a link to electronic surveys that were completed outside of scheduled class time.
A total of 176 of 290 eligible students completed the surveys for an overall response rate of 60%. Subgroup specific responses were as follows: PN = 29 of 49; J1 = 49 of 59; J2 = 14 of 60; S1 = 30 of 64; and S2 = 54 of 58. Participants were primarily young (mean age = 21.3 years) women. The majority (73.3%) perceived an integration of EOL educational content throughout completed coursework. The majority of the PN subgroup (58.6%) reported no previous content regarding EOL care. The most commonly reported religious affiliations were Catholic (30.5%) and Protestant (22%). Most students (n = 144, 81.82%) experienced at least one personal death (e.g., loved one, friend, or pet) prior to or during the semester; fewer students (n = 103, 37.32%) experienced a patient death. Exposure to death increased across subgroups, with students increasingly acting as care provider: PN = 32 (25% as care provider); S2 = 80 (54% as care provider).
During the study's implementation, data were collected from students at the beginning and end of the semester with the intention of analyzing between group differences, using mixed ANOVAs, to determine the differences between each subgroups at baseline and at the end of the curriculum and within subgroup change over time. However, only 32 students (11%) completed end-of-semester surveys: PN = 3; J1 = 4; J2 = 5; S1 = 4; and S2 = 16, reflecting an overall 82% attrition rate. Thus, only differences between subgroups for baseline data were able to be calculated.
Statistical analyses were conducted using IBM® SPSS® version 23 software. Internal consistency was high across instruments: KAT (α = .88), FATCOD (α = .85), and PC-ELNEC (α = .91). Means and standard deviations for each subgroup across both measurement time points are provided in the Table. Three one-way ANOVA analyses with five groups were applied to examine differences in baseline data outcomes across subgroups. The statistical significance threshold was set at p < .02, based on a Bonferroni correction for multiple testing. The Games Howell test was used for post hoc analyses. Significant subgroup differences were supported for the attitudes (FATCOD F[4, 171] = 8.55, p < .02, partial eta squared = .17) and knowledge (KAT, F[4,126] = 9.393, p < .02, partial eta squared = .23) outcomes (Figure). The PN subgroup reported more negative attitudes about caring for dying patients than all other subgroups. Knowledge increased slightly across subgroups, with significant differences supported for PN and J2, PN and S2, J1 and J2, and J1 and S2. No significant subgroup effects were identified for the PC-ELNEC (F[4,171] = .984, p < .02, partial eta squared = .02).
Descriptive Statistics of Outcome Measures by Subgroup and Time Point
Outcome measures for Time 1 by subgroup. KAT = Knowledge Assessment Test; FATCOD = Frommelt Attitudes Toward Care of the Dying scale; PC-ELNEC = Perceived Competence in Meeting End of Life Nursing Education Consortium Standards.
The pattern of between subgroup differences identified in this study suggests that students experience positive changes in knowledge and attitudes regarding EOL care as they progress through the curriculum. These findings are consistent with knowledge gains and improvements in attitude reported by others (Al Qadire, 2014; Bailey & Hewison, 2014; Wallace et al., 2009). In contrast, the pattern of between subgroup differences in perceived competency in this study was inconsistent with previous reports (Chow, Wong, Chan, & Chung, 2014; Efstathiou & Walker, 2013); perceived competence was not higher among subgroups farther along in the program. Yet, overall the findings are consistent with another study, suggesting that content integration within a program, as opposed to a dedicated course, can positively affect student outcomes (Barrere, Durkin, & LaCoursiere, 2008). Perceived competency was high across all subgroups in this study, essentially creating a high “floor” effect, leaving little opportunity for growth.
The results of the study did not allow for the identification of the source of specific deficits regarding knowledge, attitudes, or perceived competence. In addition, research from psychology supports that individuals use their knowledge appropriately to assess competence of others, but not when assessing their own competence (Balcetis & Dunning, 2013); therefore, assessment of actual competence may be more appropriate in educational outcomes research than perceived competence. Future research is needed to identify associations between deficits, outcome measures, and curriculum content.
Throughout the program, no student obtained a perfect score on the KAT, suggesting that complete mastery of EOL content was not achieved at any point across the curriculum. Targeted teaching solutions are needed to address the pervasive knowledge gaps. However, rather than devoting large amounts of class time to these specific topics, strategies must be carefully selected that could address knowledge gaps while also enhancing attitudes and perceived competence for students. For example, EOL simulations can address multiple topics, such as communication, interprofessional collaboration, pain management, symptom management, loss, grief, and bereavement, and final hours of life (Lippe & Becker, 2015). Integration of strategies such as this within curricula are needed to help ensure that all students graduate with adequate knowledge, high perceived competence, and positive attitudes. Future research is needed to develop teaching strategies with a targeted focus on addressing multiple aspects of EOL care.
The results of this study must be interpreted in the context of study limitations. This was a single-site study with a small sample size and a high attrition rate. Three explanations for the high attrition are: (a) participants had no incentives to complete the voluntary survey, (b) the surveys contained multiple instruments, resulting in fatigue and lack of incentive to complete repeated surveys, and (c) no instructors were able to provide in-class time for survey completion at the end of semester, resulting in students being asked to complete surveys on their own time. The high attrition poses a threat to internal validity of the results; therefore, results must be interpreted cautiously. In addition, the measure of competency was based on self-report; therefore, some bias may have been introduced to the perceived competency scores.
Educators have a responsibility to train nursing students to provide EOL care to meet the needs of an aging population. Only through education can nursing students be prepared to provide safe, competent, evidence-based, compassionate care that facilitates individuals experiencing a peaceful death. Identification of deficiencies in student outcomes can help educators and researchers develop targeted teaching strategies to improve students' knowledge, attitudes, and perceived competence. The findings of this study have paved the way for future research studies in the field of EOL care education, particularly identification of gaps in student preparation and subsequent development and testing of targeted teaching strategies.
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Descriptive Statistics of Outcome Measures by Subgroup and Time Point
|Outcomes Measures and Time Points||Total||PN||J1||J2||S1||S2|
|N||M (SD)||N||M (SD)||N||M (SD)||N||M (SD)||N||M (SD)||N||M (SD)|
| Time 1||131||35.1 (8.9)||20||27.4 (8.3)||36||32.5 (8.3)||7||41.7 (3.2)||15||37 (9.7)||53||38.4 (7.4)|
| Time 2||21||42 (3.4)||3||37 (5)||1||43 (n/a)a||3||42.7 (2.1)||3||44 (1.7)||11||42.6 (2.6)|
| Time 1||176||120.4 (10.5)||29||111.9 (10.4)||49||119.9 (9.8)||14||121.9 (9.1)||30||120.83 (9.2)||54||124.9 (9.6)|
| Time 2||32||122.9 (7.2)||3||118 (5.3)||4||121.5 (8.9)||5||118.8 (5.7)||4||122.5 (4.8)||16||125.6 (7.4)|
| Time 1||176||61.5 (6.7)||29||60.9 (7.2)||49||62.3 (7.7)||14||60 (5.9)||30||59.9 (6)||54||62.3 (6.1)|
| Time 2||30||61.2 (7)||3||64.7 (9.1)||3||57.3 (5.7)||5||58.4 (7.4)||4||53 (3.2)||15||64.4 (5.3)|