Journal of Nursing Education

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Major Articles 

Predicting NCLEX-RN Success in a Diverse Student Population

Marshall D. Alameida, PhD, RN, CNS; Alice Prive, PhD, RN; Harvey C. Davis, PhD, RN, CARN; Lynette Landry, PhD, RN; Andrea Renwanz-Boyle, PhD, RN, BC; Michelle Dunham, PhD

Abstract

Many schools of nursing have implemented standardized testing using platforms such as those developed by Assessment Technologies Institute (ATI) to better prepare students for success on the National Council Licensure Examination for Registered Nurses® (NCLEX-RN). This study extends and replicates the research on standardized testing to predict first-time pass success in a diverse student population and across two prelicensure program types. The final sample consisted of 589 students who graduated between 2003 and 2009. Demographic data, as well as academic performance and scores on the ATI RN Comprehensive Predictor, were analyzed. The findings in this study indicate that scores on the ATI RN Comprehensive Predictor were positively, significantly associated with first-time pass success. Students in jeopardy of failing the NCLEX-RN on their first attempt can be identified prior to graduation and remediation efforts can be strengthened to improve their success.

Abstract

Many schools of nursing have implemented standardized testing using platforms such as those developed by Assessment Technologies Institute (ATI) to better prepare students for success on the National Council Licensure Examination for Registered Nurses® (NCLEX-RN). This study extends and replicates the research on standardized testing to predict first-time pass success in a diverse student population and across two prelicensure program types. The final sample consisted of 589 students who graduated between 2003 and 2009. Demographic data, as well as academic performance and scores on the ATI RN Comprehensive Predictor, were analyzed. The findings in this study indicate that scores on the ATI RN Comprehensive Predictor were positively, significantly associated with first-time pass success. Students in jeopardy of failing the NCLEX-RN on their first attempt can be identified prior to graduation and remediation efforts can be strengthened to improve their success.

Drs. Alameida and Prive are Assistant Professors, and Drs. Davis, Landry, and Renwanz-Boyle are Associate Professors, San Francisco State University, San Francisco, California. Dr. Dunham is Research Specialist, Assessment Technologies Institute, LLC, Stillwell, Kansas.

The authors have no financial or proprietary interest in the materials presented herein.

Address correspondence to Marshall D. Alameida, PhD, RN, CNS, Assistant Professor, San Francisco State University, 1600 Holloway Avenue, Burk Hall 363, San Francisco, CA 94132; e-mail: malameid@sfsu.edu.

Received: March 22, 2010
Accepted: July 29, 2010
Posted Online: February 28, 2011

An urban university nursing program implemented the RN Content Mastery Series from Assessment Technologies Institute (ATI RN) in the spring of 2003. The ATI RN Comprehensive Predictor, an integral element of the ATI standardized testing package, was used to provide graduating nursing students with a method to test their knowledge in preparation for the National Council Licensure Examination for Registered Nurses® (NCLEX-RN), to predict student success on the NCLEX-RN, and to advise those students in jeopardy of failure.

The decision to incorporate a standardized testing process into the curriculum was initiated following review of the university’s NCLEX-RN pass rates. Various products that purported to prepare students for the examination were reviewed by the nursing faculty. The criteria for selection of the instrument considered numerous factors. First, the instrument needed to be developed under the same test blueprint as the NCLEX-RN. Second, the instrument had to be available in a computerized format. Third, the instrument had to have the capability to provide students with immediate feedback so that continued and focused knowledge development could commence through remediation. Fourth, the instrument had to be able to provide nursing faculty with individual, summary, and longitudinal reports that could be used for curricular evaluation. The faculty selected the ATI RN Content Mastery Series as a matter of preference and to maintain consistency with other nursing programs within the same university system.

Many schools of nursing have implemented standardized testing using platforms such as those developed by ATI to better prepare students for success on the NCLEX-RN. However, little documentation exists in the literature regarding the association between test scores on these standardized tests and success on the NCLEX-RN. ATI has developed predictive probability scores for their ATI RN Comprehensive Predictor, using a normative population, to assist faculty in identifying students in jeopardy of failing the NCLEX-RN on their first attempt. However, the nursing student population at this urban university is very diverse and, therefore, there was some question as to whether the normative data was applicable in this setting. It was determined that an independent evaluation of the predictive power of the ATI RN Comprehensive Predictor needed to be undertaken.

Literature Review

Successful graduation from a nursing program is the first step in becoming an RN. However, graduates are required to successfully pass the NCLEX-RN to be practicing RNs. The nursing literature indicates a decline in NCLEX-RN scores for first-time test takers (Newman, Britt, & Lauchner, 2005; Sayles, Shelton, & Powell, 2003) after an increased passing standard was established by the National Council of State Boards of Nursing in 1998 (NCSBN, 2009). As a result, the 1999 NCSBN statistics reported that first-time test takers educated in the United States had an 84.8% pass rate. This rate has improved, and in 2009 the first-time pass rate was 88.4% (NCSBN, 2009).

Although improving, first-time pass rates are still lower than many nurse educators would like and are of concern. Many nurse educators are interested in identifying at-risk students early in their studies so that interventions can be put in place to improve first-time pass success. Factors associated with success include race, gender, and grade point average (GPA) as measures of academic performance. Standardized tests such as the Health Education Systems, Inc. (HESI) and the ATI RN Comprehensive Predictor have also been used to predict graduates’ success rate on the NCLEX-RN. In addition, although the HESI standardized test results and predictability for NCLEX-RN have been investigated, the predictive ability of the ATI RN Comprehensive Predictor has been evaluated only to a limited degree (DeBartolo & Seldomridge, 2005).

A review of the literature found several studies that explored factors associated with student performance in nursing educational programs and first-time pass success, and the studies will be discussed here. Of particular interest to the researchers were studies exploring demographic variables (including age, gender, and race), academic variables (including student grade point averages), and student performance on standardized tests. Each of these areas will be briefly discussed.

Research investigating the role of specific demographic characteristics of the students in NCLEX-RN performance has yielded varied results. Research indicates that age is not a predictor of first-time pass success (Beeson & Kissling, 2001; Giddens & Gloeckner, 2005). The relationship between gender and first-time pass success is less understood. Haas, Nugent, and Rule (2004) concluded that gender affected NCLEX-RN pass rates, with men failing the examination at a significantly higher rate than women. Conversely, several studies indicate that gender is not significantly different for students passing or failing the examination (Beeman & Waterhouse, 2001; Beeson & Kissling, 2001; Giddens & Gloeckner, 2005; Higgins, 2005; Sayles et al., 2003). As with gender, the relationship between race and first-time pass success is not fully understood. Studies indicate that race may affect pass rates. Sayles et al. (2003) studied predictors for success in nursing, noting that graduates who were successful on the NCLEX-RN were overwhelmingly Caucasian. In addition, Haas et al. (2004) found that failure rates for African American and Asian students were significantly higher than those for Caucasian students. Thus, in previous studies that have evaluated predictors of success, there does not appear to be any group of demographic variables consistently and significantly associated with success for first-time test takers.

Many studies have identified academic performance as being significantly associated with first-time pass success, including factors such as individual class performance, cumulative GPA, and nursing course GPA (Arathuzik & Aber, 1998; Beeson & Kissling, 2001; Sayles et al., 2003; Ukpabi, 2008). Ukpabi (2008) found that higher grades in psychiatric/mental health, pharmacology, and nursing fundamentals were predictive of success. Beeson and Kissling (2001) identified several cognitive factors, including course grades at sophomore, junior, and senior levels of their nursing curriculum (specific courses not identified) and high cumulative GPAs at graduation, that were associated with first-time pass success. Sayles et al. (2003) explored predictors of success in nursing education as determined by first-time pass success, noting that grades in a senior-level nursing course were statistically significant in predicting first-time pass success. Haas et al. (2004) found that a mean cumulative nursing GPA of 3.33 was predictive of success. Beeson and Kissling (2001) also found, in bivariate analysis, that cumulative GPA and cumulative nursing GPA were associated with first-time pass success. Many authors have discussed the predictive value of several standardized tests and first-time pass success. Two of the most widely used examinations are the HESI and the ATI RN Comprehensive Predictor (DeBartolo & Seldomridge, 2005). Research supporting the connections between these two examinations and first-time pass success will be reviewed.

Several studies have found an association between first-time pass success with successful completion of the HESI exit examination (Morrison, Adamson, Nibert, & Hsia, 2005). In addition, Lauchner, Newman, and Britt (2008) studied nursing students in practical nursing, diploma, associate degree, and baccalaureate nursing (BSN) programs (N = 2,809) to determine the predictive abilities of the HESI exit examinations on first-time pass success. The researchers found that the HESI exit examinations were significantly predictive of student success (p < 0.001) and that success rates were unchanged for graduates of all types of nursing programs (associate degree, BSN, and master’s entry) studied. The researchers also found that the HESI exit examination results were slightly more accurate when students completed proctored or monitored examinations compared with students who completed the examinations at home.

There are few studies that examine the relationship between scores on the ATI RN Comprehensive Examination with first-time pass success. Jacobs and Koehn (2006) compared nursing students’ scores on the ATI RN Comprehensive Predictor and success on the NCLEX-RN for those students graduating from a nursing program in 2005. They found that of the 13% of students who scored less than the national (20th) percentile on the ATI RN Comprehensive Predictor, half of the low-scoring group also failed the NCLEX-RN. The researchers noted that the ATI RN Comprehensive Predictor was helpful in the identification of students at risk for failing the NCLEX-RN on their first attempt.

The current research presents a mixed view of demographic and academic factors contributing first-time pass success on the NCLEX-RN. Research on the predictive value of standardized examinations is more conclusive. Data support success on the HESI exit examination with first-time pass success on the NCLEX-RN. There is limited data on the association between success on the ATI RN Comprehensive Predictor and the NCLEX-RN, indicating the need for additional study regarding the predictive value of this examination.

The purpose of this study was to determine whether there was a relationship between the predictive probability on the ATI RN Comprehensive Predictor (taken at the end of the last semester in the nursing program) and first-time pass success on the NCLEX-RN for groups of nursing students. The research questions for the study were:

  • Does a significant relationship exist between the ATI predictive probability and first-time pass success on the NCLEX-RN?
  • Does a significant relationship exist between select academic variables (cumulative GPA, nursing GPA, nursing course grades, and program type) or select sociodemographic variables (age, gender, and race) and first-time pass success on the NCLEX-RN?
  • What is the ATI RN Comprehensive Predictor mean predictive probability score that is associated with first-time pass success on the NCLEX-RN?

Method

ATI RN Comprehensive Predictor

ATI RN Comprehensive Predictor Version 3.0 is the third version of an assessment that is intended to evaluate readiness for the NCLEX-RN (ATI, 2003). Version 3.0 contained 155 multiple choice, four-option questions that required a single response within the 180 questions on the examination. The remaining 25 questions are presented as alternate format questions (ATI, 2003). Version 3.0 preceded Forms A and B, which are fixed at 150 scored items and contain 30 pretest items that are not scored (ATI, 2007).

The ATI RN Comprehensive Predictor is administered to all students during their last semester of the nursing program. Students enrolled in the study took either Form A, Form B, or Version 3.0. Version 3.0 was administered to students between May 2005 and December 2007, Form A was administered once in April 2008, and Form B was administered between April 2008 and May 2009. In this study, the research questions were statistically investigated separately for Version 3.0 and Forms A and B. Forms A and B test data were combined and analyzed together because they are based on the same NCLEX-RN test plan and, thus, have similar content.

Data Collection

The predictive nature of Forms A and B and Version 3.0 were examined using a retrospective, descriptive study design. Prior to data collection and analysis, approval for the study was obtained from the university’s Committee on Human Research. Student data, including demographic information, GPA, course grades, first-time NCLEX-RN results, and scores on the ATI RN Comprehensive Predicator, were collected for students enrolled in the nursing program from spring 2005 to spring 2009. SPSS version 17 software was used for data analysis.

Sample

A total of 627 students were identified for this study. For inclusion in the study, student records needed to include an ATI RN Comprehensive Predictor result and a first-time NCLEX-RN result. The study sample consisted of 589 students who met the inclusion criteria.

Variables of Interest

The dependent variable was a dichotomous variable for first-time pass success: either yes (student passed the NCLEX-RN on first attempt) or no (student failed the NCLEX-RN on first attempt). Independent variables included were nursing courses GPA; cumulative GPA; program type (BSN, satellite BSN or master’s entry); score on the ATI RN Comprehensive Predictor; ATI predictive probability of first-time pass success; and course grades for each course in the curriculum. Also, selected sociodemographic variables were considered (age, gender, and race).

Data Analysis

The total number of students in the global dataset was 589. A total of 367 students took Version 3.0 and 222 students took Form A or B. Because two versions of the ATI RN Comprehensive Predictor were included in the database, initial analysis using a t test of the global dataset (N = 589) was done to determine whether the two groups were similar. There was a significant difference between the two groups (t = 3.19, df = 587, p = 0.000) as demonstrated by t test analysis. Because each version of the ATI RN Comprehensive Predictor was developed for a different NCLEX-RN test plan, it was decided that each version would be analyzed separately.

Initial analysis of the global data set (N = 589) included running sample descriptive statistics. Furthermore, t test and one-way analysis of variance (ANOVA) comparisons were done to evaluate differences between the groups on the demographic variables (age, gender, and race) under consideration. For each version of the ATI RN Comprehensive Predictor, Pearson’s correlations for all variables were calculated and the independent variables that were moderately to highly correlated (r ≥ 0.30) to the dependent variable (first-time pass success) were entered into the initial bivariate analysis. For initial bivariate analysis of the dependent variable, chi-square analysis was performed. Independent variables were entered into the logistic regression equations in blocks—first demographic variables, then course grades for individual courses in the curriculum, followed by nursing program GPA and predictive probability of the examination (e.g., all nursing course grades were grouped together and then entered into the equation as a block). A significance level of p = 0.05 was set for each block to remain in the model.

Results

This urban university has a racially diverse student body, and the nursing student body mirrors that diversity. In this sample (N = 589), the predominant racial group was Asian, non-Hispanic (n = 224, 38%), whereas 180 (30.6%) students identified as White, non-Hispanic. The remaining students self-identified as African American, non-Hispanic (n = 43, 7.3%), Native American/Alaskan Native (n = 5, 0.8%), Native Hawaiian/Other Pacific Islander (n = 7, 1.2%), Hispanic (n = 64, 10.9%), and other (n = 24, 4.1%). Racial information was missing for 42 students. Students in the nursing program were predominately women (n = 452, 76.7%); however, the percentage of male students (23.3%) is greater than the percentage of men typically found in other nursing programs and in the nursing profession as a whole. The remaining sample demographics are described in Table 1. For the two groups defined by first-time pass or failure (Version 3.0, n = 367; Forms A and B, n = 222), there were significant differences between group means for cumulative GPA (t = −7.46, df = 587, p = 0.000), ATI predictive probability (t = −16.7, df = 587, p = 0.000), ATI RN Comprehensive Predictor score (t = −13.9, df = 587, p = 0.000), and nursing GPA (t = −12.65, df = 587, p = 0.000). There was no difference between the two groups with regard to age (t = −0.60, df = 587, p = 0.55). Furthermore, one-way ANOVA found that there were no differences between groups by students’ gender (F = 2.24, df = 1, p = 0.135) and program type (F = 3.48, df = 1, p = 0.06). However, there was a significant difference between groups with regard to race/ethnicity (F = 4.62, df = 1, p = 0.03)

Sample Demographic Characteristics and Academic Performance

Table 1: Sample Demographic Characteristics and Academic Performance

In initial correlation matrices for the entire sample, it was noted that the ATI RN Comprehensive Predictor score and the ATI predictive probability were highly correlated (r = 0.87, p = 0.000). The correlation was high (r = 0.89, p = 0.000) in the group that took Version 3.0 of the examination and even higher (r = 0.95, p = 0.000) in the group that took either Form A or B. Therefore, it was decided that only the ATI predictive probability would be considered in the analysis of predictors of first-time pass success. Both cumulative GPA and nursing course GPA were included in the analysis of the predictors of first-time pass success because they were only moderately correlated.

Relationship Between Independent Variables and NCLEX-RN Success

To answer the first two research questions regarding the relationship between first-time pass success and the independent variables (ATI RN Comprehensive Predictor score, academic performance, and student demographic characteristics) Version 3.0 and Forms A and B were analyzed independently. Pearson’s correlations, chi-square analysis, and logistic regression equations were performed to determine whether there was a statistically significant relationship between any of the independent variables and first-time pass success.

ATI RN Comprehensive Predictor Version 3.0

The total number of students who took Version 3.0 was 367. For this group, the following variables were found to be moderately to highly correlated (r ≥ 0.30) with first-time pass success: ATI predictive probability, nursing program GPA, and five individual nursing courses (health assessment, medical/surgical nursing theory, pharmacology, pathophysiology, and community/public health nursing theory). In chi-square analysis, nursing program GPA was significantly associated with first-time pass success (χ2 = 187.26, df = 97, p < 0.001). The five individual nursing course grades were also significantly associated with first-time pass success in chi-square analysis (Table 2). Finally, this examination ATI predictive probability was significantly associated with first-time pass success in the bivariate analysis (χ2 = 119.68, df = 11, p < 0.001).

Chi-Square Analysis of Courses Moderately to Highly Correlated with First-Time NCLEX-RN Success (ATI RN Comprehensive Predictor Version 3.0)

Table 2: Chi-Square Analysis of Courses Moderately to Highly Correlated with First-Time NCLEX-RN Success (ATI RN Comprehensive Predictor Version 3.0)

The final logistic regression model for this group included nursing GPA, the five individual nursing courses, and ATI predictive probability. Only the results for the final model are reported (Table 3). In the final regression model, only predictive probability remained significantly associated with first-time pass success (odds ratio [OR] = 1.04, 95% confidence interval [CI] = 1.03–1.05, p = 0.000), although the community/public health nursing theory course approached significance (OR = 1.87, 95% CI = 0.98–3.6, p = 0.059). Results of the Hosmer and Lemeshow Test indicate a good model fit (p = 0.945).

Logistic Regression Equation NCLEX-RN Successa (ATI RN Comprehensive Predictor Version 3.0)

Table 3: Logistic Regression Equation NCLEX-RN Success (ATI RN Comprehensive Predictor Version 3.0)

ATI RN Comprehensive Predictor Forms A and B

The total number of students who took Forms A or B of the ATI RN Comprehensive Predictor was 222. For this group, the following variables were moderately to highly correlated (r ≥ 0.30) with first-time pass success: ATI predictive probability, nursing program GPA, and six individual nursing courses (health assessment, medical/surgical nursing theory, medical/surgical nursing practicum, pathophysiology, maternal/child nursing theory, and nursing fundamentals). Nursing program GPA was significantly associated in bivariate analysis with first-time pass success (χ2 = 150.04, df = 69, p < 0.001). All six individual nursing course grades were also significantly associated with first-time pass success (Table 4). Finally, ATI predictive probability was significantly associated with first-time pass success in bivariate analysis (χ2 = 136.54, df = 40, p < 0.001).

Chi Square Analysis of Courses Moderately to Highly Correlated with First-Time Pass Success (ATI RN Comprehensive Predictor Forms A or B)

Table 4: Chi Square Analysis of Courses Moderately to Highly Correlated with First-Time Pass Success (ATI RN Comprehensive Predictor Forms A or B)

The final logistic regression model for this group included nursing GPA, health assessment, medical/surgical nursing theory and practicum, pathophysiology, maternal/child nursing theory and nursing fundamentals, and predictive probability. Only results of the final logistic regression model are identified (Table 5). In the final logistic regression model, two nursing courses (medical/surgical nursing practicum and pathophysiology) and ATI predictive probability remained significantly associated with first-time pass success (OR = 5.96, 95% CI = 10.5–33.74, p = 0.043; OR = 3.92, 95% CI = 1.32–11.27, p = 0.011; OR = 1.07, 95% CI = 1.04–1.11, p < 0.001, respectively). Results of the Hosmer and Lemeshow Test indicate a good model fit (p = 0.91).

Logistic Regression Equation NCLEX–RN® Successa (ATI RN Comprehensive Predictor Forms A and B)

Table 5: Logistic Regression Equation NCLEX–RN® Success (ATI RN Comprehensive Predictor Forms A and B)

Mean Predictive Probability Score and NCLEX-RN Success

To answer the third research question, a two-step cluster analysis was performed on the entire sample (N = 589) to identify the range of values on the ATI RN Comprehensive Predictor that were predictive of first-time pass success. The mean ATI predictive probability score that indicated first-time pass success was 80.47 (SD = 22.75), whereas the mean ATI predictive probability score that indicated of first-time pass failure was 36.34 (SD = 28.26). Scores within each of these clusters were 100% predictive of performance on the NCLEX-RN.

Two-step cluster analysis of Version 3.0 (n = 367) identified three groups of students on the range of values on the ATI predictive probability score that indicated first-time pass success or failure. Group 1 had a mean ATI predictive probability score of 92.04 (SD = 7.72), and this score was indicative of first-time pass success. Group 2 had a mean ATI RN Comprehensive Predicator score of 37.55 (SD = 17.16), and this score was also indicative of first-time pass success, although according to the ATI examination these students should have failed the NCLEX-RN on their first attempt. Group 3 had a mean ATI predictive probability score of 35.06 (SD = 28.39), and this score was indicative of first-time pass failure. Scores within each of these groups were 100% predictive of performance on the NCLEX-RN.

In contrast, two-step cluster analysis of the range of values on the ATI RN Comprehensive Predictor Forms A and B (n = 222) found that a score of 83.94 (SD = 15.64) was predictive of first-time pass success, whereas the mean ATI RN Comprehensive Predictor score of 39.31 (SD = 28.24) was predictive of first-time pass failure. Scores within each of these clusters were 100% predictive of performance on the NCLEX-RN.

Conclusion

The purpose of this study was to answer three questions:

  • Does a significant relationship exist between the ATI predictive probability and first-time pass success on the NCLEX-RN?
  • Does a significant relationship exist between select academic variables (cumulative GPA, nursing GPA, nursing course grades, and program type) or select sociodemographic variables (age, gender, and race) and first-time pass success on the NCLEX-RN?
  • What is the ATI RN Comprehensive Predictor mean predictive probability score that is associated with first-time pass success on the NCLEX-RN?

With regard to research question one, the logistic regression analysis from the RN Comprehensive Predictor Version 3.0 (n = 367) and Forms A and B (n = 222) found that a significant relationship exists between the ATI predictive probability and first-time pass success. As relates to research question two, the statistical analysis did not find a significant relationship between the demographic variables and first-time pass success and either of the ATI RN Comprehensive Predictor examinations administered to students in this study. Statistical analysis of the relationship between academic performance and first-time pass success results for students who took Forms A and B found that there was a significant relationship between the medical/surgical nursing practicum and pathophysiology nursing courses and first-time pass success.

As in other studies, we found that the ATI predictive probability may vary slightly between studies (or program type), but a significant predictive relation exists with first-time pass success. In this sample, which was more racially/ethnically diverse than the samples included in similar studies and investigated two program types (BSN and master’s entry), no significant association was found between any of the demographic variables examined and first-time pass success.

Master’s entry students comprise approximately 30% of the student population at the university. In terms of the ATI RN Comprehensive Predictor Forms A and B normative sample, the examinees were predominantly women, White, non-Hispanic, and enrolled in associate’s degree programs. In comparison, the student population in this study was primarily women; Asian, non-Hispanic; and White, non-Hispanic. Thus, the study results indicate that the ATI RN Comprehensive Predictor has utility in predicting first-time pass success even in a racially diverse student population. This has implications for use of the examination in curricular development and student advising.

A unique finding in this sample was related to the cluster analysis from the ATI RN Comprehensive Predictor Version 3.0, which indicated that there were three groups of students: Group 1 included students whose score on the ATI RN Comprehensive Predictor predicted first-time pass success and passed the NCLEX-RN on the first attempt; group 2 included students whose score on the ATI examination predicted first-time pass failure but passed the NCLEX-RN on the first attempt; and group 3 included students whose score on the ATI RN Comprehensive Predictor predicted first-time pass failure and failed the NCLEX-RN on the first attempt. We speculate that this version of the ATI RN Comprehensive Predictor was used during the initial implementation of the standardized testing platform, at which time performance on the ATI RN Comprehensive Predictor accounted for only 3% of the course grade, and thus students in group 2 were those who did not take the testing seriously. This hypothesis is strengthened by the fact the when the percentage of the course grade assigned to performance on the ATI RN Comprehensive Predictor was increased to 10% of the course grade students took the examination more seriously and the cluster analysis revealed only two groups: one predictive of passing and the other of failure.

Furthermore, the GPAs of only two courses (conducted in the second semester of the curriculum for Forms A and B) in the regression analyses were associated with ATI predictive probability: pathophysiology and medical/surgical nursing practicum. We contemplated that high-risk students can be identified during this semester and remediation efforts strengthened. We also considered that, at this juncture in the curriculum, students who begin to integrate theory with practice and gain insights on the ability to be critical thinkers are more successful versus those who do not make this transition.

This study strongly underscores the importance for nursing faculty to avail themselves of data associated with standardized testing modules that are predicated on the NCLEX-RN test plan. These modules often include information about which content areas students perform well on and which they do not. By reviewing student performance on key content areas, deficits can be identified and reinforcement of the content within a particular course can be done to increase students’ understanding. Moreover, identification of students at risk for failure of NCLEX-RN is possible, and thus students can be advised to remediate until understanding of key concepts is attained.

Data from the ATI RN Comprehensive Predicator can be used in a school of nursing quality improvement program. Because the ATI RN Comprehensive Predictor was found to be predictive of first-time pass success at an urban university with a diverse student population with two different RN program types, the ATI RN Comprehensive Predictor has use in identifying the need for curricular revision to assure that concepts key to the NCLEX-RN test plan are incorporated into the curriculum. However, further research into the use of other examinations within the ATI Content Mastery series is needed to identify how the ATI examinations can be used to improve student success on the NCLEX-RN.

Limitations

A limitation of this study was that three program types were included in which admission criteria varied. Master’s entry students and approximately 50% of the BSN students already had a baccalaureate degree, yet all progressed through the same curricula. Variation in prior educational preparation was not controlled for in this analysis and could have influenced scores on the ATI RN Comprehensive Predictor. Moreover, generalizability may be limited to schools of nursing that have programs similar to the programs at this urban university. Finally, the nursing curriculum at this university was revised in 2005 (implemented in 2007). The effects of the curricular revision on cumulative GPA, nursing GPA, individual course GPAs, and ATI RN Comprehensive Predictor scores is unknown.

References

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Sample Demographic Characteristics and Academic Performance

VariablesEntire Sample
Version 3.0
Forms A and B
MeanSDMeanSDMeanSD
Age (y)34.18.0633.98.7834.27.59
Cumulative grade point average3.530.423.650.233.460.48
Nursing grade point average3.650.243.720.223.600.25
Score on ATI RN Comprehensive Predictor63.89.8868.89.0670.431.32
ATI RN Comprehensive Predictor predictive probability73.328.7878.123.2660.89.13

Chi-Square Analysis of Courses Moderately to Highly Correlated with First-Time NCLEX-RN Success (ATI RN Comprehensive Predictor Version 3.0)

Courseχ2dfp
Health Assessment Theory48.07100.000
Medical/Surgical Nursing Theory50.50110.000
Pharmacology51.4280.000
Pathophysiology56.82110.000
Community/Public Health Nursing Theory83.1480.000

Logistic Regression Equation NCLEX-RN Successa (ATI RN Comprehensive Predictor Version 3.0)

Independent VariableBExp (B)SEWalddfCIp
Health Assessment Theory0.141.160.340.1810.59–0.230.67
Pharmacology0.431.540.361.4510.76–3.130.23
Medical/Surgical Nursing Theory0.611.060.390.0310.49–2.290.88
Pathophysiology0.581.780.362.5410.88–3.630.11
Community Health Nursing Theory0.631.880.333.5510.98–3.600.059
Nursing grade point average–0.120.991.470.0010.56–17.480.99
ATI Comprehensive Predictor predictive probability0.371.040.0138.111.03–1.050.000

Chi Square Analysis of Courses Moderately to Highly Correlated with First-Time Pass Success (ATI RN Comprehensive Predictor Forms A or B)

Courseχ2dfp
Health Assessment Theory96.21120.000
Medical/Surgical Nursing Theory57.8870.000
Medical/Surgical Nursing Practicum35.3360.000
Pathophysiology79.36150.000
Foundations of Nursing Theory44.7670.000
Maternal/Child Nursing Theory35.0150.000

Logistic Regression Equation NCLEX–RN® Successa (ATI RN Comprehensive Predictor Forms A and B)

Independent VariableBExp (B)SEWalddf95% CIp
Health Assessment Theory1.052.870.821.6310.57–14.420.201
Medical/Surgical Nursing Theory course0.101.110.980.0110.16–7.620.918
Medical/Surgical practicum1.896.590.884.5611.17–37.140.033
Pathophysiology course1.342.440.556.0111.31–11.170.014
Foundations of Nursing course–1.550.211.062.1310.03–1.700.145
Nursing grade point average–1.990.142.710.5410.00–27.630.461
Test predictive probability0.071.070.1619.7411.04–1.110.000
Authors

Drs. Alameida and Prive are Assistant Professors, and Drs. Davis, Landry, and Renwanz-Boyle are Associate Professors, San Francisco State University, San Francisco, California. Dr. Dunham is Research Specialist, Assessment Technologies Institute, LLC, Stillwell, Kansas.

The authors have no financial or proprietary interest in the materials presented herein.

Address correspondence to Marshall D. Alameida, PhD, RN, CNS, Assistant Professor, San Francisco State University, 1600 Holloway Avenue, Burk Hall 363, San Francisco, CA 94132; e-mail: .malameid@sfsu.edu

10.3928/01484834-20110228-01

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