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Impact of Increasing Nurse Attrition Rates

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Published: 11th Sep 2017 in Nursing

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Schools and nursing departments all across the United States suffer from decreasing number of nurse graduates and increasing attrition rates (Beacham, Askew, & Williams, 2009). Researchers have pegged the average attrition rates to 50 percent among nursing students in the baccalaureate programs and 47 percent among associate degree students (Newton & Moore, 2009). The attrition rates are higher among minority nursing students (Gardner, 2005) and among non-traditional nursing students (Gilchrist & Rector, 2007).

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High attrition rates in nursing programs reflect a public health concern. As the health care demands of the population grow with an aging population with diverse health care needs, the current population of nurses is too small to meet this demand. As of now, a steady stream of competent nurses is not possible with the high attrition rates (American Association of Colleges of Nursing [AACN], 2012).  Without arresting this problem, a nursing shortage may be imminent. It is thus vital to investigate the causes of increasing attrition rates in nursing programs, understand what students experience in order to identify what strategies would enhance student success.

Nontraditional students are especially prone to high attrition (Rudel, 2006). Nontraditional students refers to students who are older and enter university with diverse levels of academic ability (Jeffreys, 2007; Rudel, 2006). Studies show that nontraditional students are at higher risk of attribution due to financial difficulty, employment burdens, and family responsibilities (Bednarz et al., 2010; Jeffreys, 2007). Moreover, ethnically diverse students are also at higher risk for attrition (Kennedy et al., 2008; Love, 2010) because of added barriers such as cultural constraints, language difficulty, lack of faculty guidance, academic ability, and feelings of isolation. Another factor is the lack of academic preparation required among nontraditional students in order to pursue college degrees since most of them arrive in universities with the need for remediation (Rudel, 2006).

The importance of statistics in nursing cannot be overemphasized. Without statistics, Florence Nightingale would not have been able to prove the relationship between sanitary conditions and military deaths during the Crimean War. Hence, her effort as a nurse statistician led to the standardization of data and the practice of benchmarking. As the demands of the nursing profession grow, nursing students need to have a working knowledge of statistics to contribute to evidence-based practice and improve the quality of the profession in general. Nurses need to involve themselves with clinical research so that evidence-based practices may find their way in hospitals and health institutions. Competency in statistics is a vital element of the scientific method and has been of tremendous use to improving the professional knowledge in all academic disciplines, including the health sciences (Davenport & Harris, 2007).

Unfortunately, akin to the general perception about mathematics, statistics is not a well-loved subject. Many students treat the study of statistics with anxiety, fear, and worry. Dykeman (2010) conducted a random survey among graduate students and considered statistics to be the least desirable among all of the subjects they have enrolled in. Several studies involving graduate students of the social sciences reflect that around 75% to 80% of them experience statistics anxiety which led to poor learning outcomes (Onwuegbuzie, Slate, et al., 2000; Onwuegbuzie & Seaman, 1995). Hence, in fear of statistics, students either delay taking the course or drop out of the program.

Statistics anxiety, compared to a similar phenomenon mathematics anxiety, is relatively underresearched. While there have been studies investigating statistics anxiety, these have focused generally on social science and education disciplines. Existing studies show that several factors contribute to statistics anxiety, especially student characteristics, nontraditional students, and self-efficacy levels. Central to the study of statistics anxiety is a student’s self-efficacy or confidence in their ability to learn and understand statistics.

At present, a search on electronic databases EBSCO and ProQuest reveal no studies yet have been conducted focusing on statistics anxiety among nursing students. Since statistics is one of the least popular and most feared subjects among students, this study intends to explore the relationship between statistics anxiety, attrition rates, self-efficacy, and learner type among undergraduate nursing students in a University.

Research Problem

The problem being addressed in this study is the high attrition rates in the nursing program of a university where anxiety in taking a course in statistics is considered to be a primary cause. This study wants to investigate the relationship among statistics anxiety, attrition rates, and student characteristics (self-efficacy and type of learner) in the context of a nursing program in a University.

The research questions are:

  1. What is the relationship between statistics anxiety and attrition rates in undergraduate baccalaureate nursing students?
  2. What is the relationship between statistics anxiety and self-efficacy among the nursing students?
  3. What is the relationship between self-efficacy and attrition rates?
  4. How do statistics anxiety and self-efficacy among traditional students compare with statistics anxiety and self-efficacy among non-traditional students?

Theoretical Framework

Providing guidance to this study is Bandura’s (1997) social cognition theory. Self-efficacy pertains to a person’s belief that he or she is capable of executing behaviors required to achieve a specific outcome (1997). Self-efficacy may be defined as the confidence a person has over their ability to exercise control over personal and cognitive factors, the environment, and their behaviors. While all three factors are important to self-efficacy, cognitive factors are the most crucial.

Elaborating more on the concept of self-efficacy, Bandura (1977) stated that there are four primary sources of influence through which a person acquires and maintains self-efficacy: “(a) performance accomplishments or mastery experiences; (b) vicarious experiences; (c) verbal or social persuasion; and (d) physiological or emotional states” (p. 23). Mastery experiences provide a person with a strong self-efficacy level because successes boost beliefs about one’s competency while failures weaken it. Vicarious experiences are those which enhance a person’s self-efficacy through the influence of a role model. Verbal or social persuasion also influence self-efficacy by strengthening a person’s belief that they possess the necessary skills and attitudes to accomplish a task (Bandura, 1994). Lastly, individuals are depending on physiological or emotional states when they need to judge their ability to perform. People may interpret tension and stress as signals that they are about to perform poorly. Experiencing moods, pains, and fatigue may also weaken a person’s perception of his or her ability (Bandura, 1994).

Conceptual Framework

In the present investigation, direct and indirect relationships between self-efficacy, type of learner, statistics anxiety and attrition rates in nursing programs are investigated in the context of a nursing program which requires a statistics course for completion. For the study, a working conceptual model is developed which assumes the following relationships (see Figure 1).

It is assumed that self-efficacy elements (mastery experiences, vicarious experience, verbal or social persuasion and) physiological or emotional states) and type of learner are related to statistics anxiety (Perepiczka et al., 2011). Adult learners should report higher levels of statistics anxiety than traditional learners and are expected to report lower levels of self-efficacy than traditional learners (Bui & Alvaro, 2011). Self-efficacy in statistics should be negatively related to statistics anxiety (Hsuang et al., 2009). This means that traditional earners who have high levels of self-efficacy will have lower statistics anxiety and conversely, traditional learners who have low levels of self-efficacy will have higher statistics anxiety. Due to the negative relationship between adult learners and self-efficacy, adult learners are expected to have lower self-efficacy and hence higher statistics anxiety.

It is expected that via their relationships to statistics anxiety, these variables will also be related to the attrition rates in nursing program, measured in terms of students dropping out of the program. Therefore, those who have higher self-efficacy levels will less likely suffer statistics anxiety and will have lesser likelihood of attrition. As a result, this investigation also assumes attrition rates will be higher among adult learners than traditional learners. Statistics anxiety is expected to be positively related to attrition rates. The indirect negative effect of statistics anxiety and nursing shortage is also assumed.

Figure 1. Conceptual Model on the Relationship of Self-Efficacy, Statistics Anxiety, and Attrition Rates in a Nursing Program


American Association of Colleges of Nursing. (2012). Nursing shortage fact sheet. Retrieved from http://www.aacn.nche.edu/media-relations/ NrsgShortageFS.pdf

Bandura, A. (1997). Self-Efficacy: The exercise of control. New York, NY: W. H. Freeman.

Bui, N. & Alfaro, M. A. (2011). Statistics anxiety and science attitudes: age, gender and ethnicity factors. College Student Journal, 573-585. Retrieved from EBSCO Host.

Dykeman, B. F. (2010). Statistics anxiety: antecedents and instructional interventions. Education. Retrieved from EBSCO Host.

Finney, S. J. & Schraw, G. (2003). Self-efficacy beliefs in college statistics courses. Contemporary Educational Psychology, 28, 161-186.

Gilchrist, K.L., & Rector, C. (2007). Can you keep them? Strategies to attract and retain nursing students from diverse populations: Best practices in nursing education. Journal of Transcultural Nursing, 18, 277-285. doi:10.1177/1043659607301305

Hsua, M. K., Wang, S., & Chiu, K. K. (2009).Computer attitude, statistics anxiety and self-efficacy on statistical software adoption behavior: An empirical study of online MBA learners. Computers in Human Behavior 25(2), 412-420.

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Newton, S.E., & Moore, G. (2009). Use of aptitude to understand bachelor of science in nursing student attrition and readiness for the National Council Examination-Registered Nurse. Journal of Professional Nursing, 25, 273-278. doi:10.1016/j.profnurs.2009.01.016

Onwuegbuzie, A. J. (2004). Academic procrastination and statistics anxiety. Assessment & Evaluation in Higher Education, 29, 3-19.

Onwuegbuzie, A. J., & Wilson, V. (2003). Statistics anxiety: Nature, etiology, antecedents, effects, and treatments-a comprehensive review of the literature. Teaching in Higher Education, 8(2), 195-209.

Onwuegbuzie, A. J., DaRos, D., & Ryan, J. (1997). Perfectionism and statistics anxiety: A phenomenological study. Focus on Learning Problems in Mathematics, 19(4), 11-35.

Perepiczka, M., Chandler, N., & Becerra, M. (2011). Relationship between graduate students’ statistics self-efficacy, statistics anxiety, attitude towards statistics and social support. The Professional Counselor Journal. Retrieved from: http://tpcjournal.nbcc.org/relationship-between-graduate-students-statistics-self-efficacy-statistics-anxiety-attitude-toward-statistics-and-social-support/

Rudel, R.J. (2006). Nontraditional nursing students: The social influences on retention. Teaching and Learning in Nursing, 1, 47-54. doi:10.1016/j. teln.2006.06.002   


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