Review Article
Student nurses’ unethical behavior, social media, and year of birth
Nursing Ethics 1–9 ª The Author(s) 2015 Reprints and permission: sagepub.co.uk/journalsPermissions.nav 10.1177/0969733015590009 nej.sagepub.com
Gloria Copeland Smith Central Texas College, USA
Troy Keith Knudson InGenesis Contingent Workforce Solutions, USA
Abstract Background: This study is the result of findings from a previous dissertation conducted by this author on Student Nurses’ Unethical Behavior, Boundaries, and Social Media. The use of social media can be detrimental to the nurse–patient relationship if used in an unethical manner. Method: A mixed method, using a quantitative approach based on research questions that explored differences in student nurses’ unethical behavior by age (millennial vs nonmillennial) and clinical cohort, the relationship of unethical behavior to the utilization of social media, and analysis on year of birth and unethical behavior. A qualitative approach was used based on a guided faculty interview and common themes of student nurses’ unethical behavior. Participants and Research Context: In total, 55 Associate Degree nursing students participated in the study; the research was conducted at Central Texas College. There were eight faculty-guided interviews. Ethical considerations: The main research instrument was an anonymous survey. All participants were assured of their right to an informed consent. All participants were informed of the right to withdraw from the study at any time. Findings: Findings indicate a significant correlation between student nurses’ unethical behavior and use of social media (p ¼ 0.036) and a significant difference between student unethical conduct by generation (millennials vs nonmillennials (p ¼ 0.033)) and by clinical cohort (p ¼ 0.045). Further findings from the follow-up study on year of birth and student unethical behavior reveal a correlation coefficient of 0.384 with a significance level of 0.003. Discussion: Surprisingly, the study found that second-semester students had less unethical behavior than first-, third-, and fourth-semester students. The follow-up study found that this is because second-semester students were the oldest cohort. Conclusion: Implications for positive social change for nursing students include improved ethics education that may motivate ethical conduct throughout students’ careers nationally and globally for better understanding and promotion of ethics and behavior. Keywords Confidentiality, ethics, Health Insurance Portability Accountability Act, privacy, professionalism, social media, teaching ethics, unethical conduct
Corresponding author: Gloria Copeland Smith. Email: [email protected]
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Introduction Nursing departments across the United States have had several instances where millennial-age nursing students in Associate Degree Nursing programs have been disciplined or expelled because of behavior that violated patient’s confidentiality, privacy, and the Health Insurance Portability Accountability Act (HIPAA). HIPAA protects patient privacy by defining individual identifiable information and establishes how this information is used. Nursing students who violate HIPAA laws, whether intentionally or unintentionally, share protected health information. According to Kuhns,1 HIPAA laws protect patient rights, privacy, and confidentiality.2 Examples of inappropriate activity while using social media include nurses taking pictures of patient health records for homework, posting patients’ pictures on Facebook, and posting patient information or comments on Facebook. HIPAA violations have resulted in expulsions, suspensions, and fines. According to Hader and Brown,3 two nurses in Wisconsin faced FBI investigation, HIPAA privacy violations, and pending charges from the licensing board for photographing an X-ray image showing a device lodged inside a patient. The primary purpose of this study was to better understand and clarify findings from a previous study regarding student use of social media by clinical cohort. Based on evidence from the principal researcher’s study on Student Nurses’ Unethical Behavior, Boundaries, and Social Media, findings showed that second-semester cohort students behaved more ethically than first-, third-, and fourth-semester cohorts. Because this was somewhat surprising, the principal researcher felt this warranted future research. The guided faculty interviews were further analyzed to assess faculty’s perception regarding clinical cohorts and unethical behavior. Faculty noted that first-semester students are normally thought to engage in the most unethical behavior and that students who had exhibited the most unethical conduct were in the firstsemester cohort. These findings lead to further examination as to why second-semester students were more ethically behaved than the third- and fourth-semester combined cohorts, as well as the first. Moreover, most faculty members perceived that younger students would have the most unethical behavior and that younger students would more than likely be in the earlier semester cohorts. However, this study has shown that this is not necessarily the case, as second-semester students had an earlier average year of birth than the third- and fourth-semester combined cohort. Faculty shared the main commonality that most students who engaged in unethical behavior were younger students who lacked experience. It is clear that social media policies are still evolving at institutions of higher education. Moreover, accredited schools of medicine report using different venues of social media but noted only 10% of the schools had any policies or guidelines.2 Cain and Fink4 observed that cultural mores relative to the use of social media devices have widened the intergenerational gap. Social media devices, observed by Cain and Fink, include Twitter, Facebook, Internet, and LinkedIn. Additionally, Fraser5 noted that students should approach the use of social media venues with policies, guidance, HIPAA, and disclaimers.6
Rationale A recent Gallup poll (2014) suggests that nursing is one of the most trusted professions.7 Because of this public trust, and the nurse–patient relationship, nurses have an ethical duty to do, or cause, no harm to patients. Nevertheless, a gap in practice concerning unethical conduct often emerges at clinical sites once students begin practicing. Breaching patient confidentiality and privacy has become increasingly common for nurses and students since the advent of social media. According to the National Council of State Boards of Nursing (NCSBN)8 and Ginory et al.,9 there are serious consequences of inappropriate use of social media. Aylott10 suggested that unethical online conduct and behavior have now become common practice. It is essential that nurses
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continue to avoid situations that compromise the nurse–patient relationship. There have been more than 400 breaches of confidentiality incidents affecting more than 19 million individuals since 2009.3
Literature To support a foundation for the study, theories and related topics of ethics, professionalism, confidentiality, privacy, and teaching ethics were reviewed. The review also explored literature on social media and its connection to unethical conduct. According to Lachman,11 social media and Internet participants go beyond the millennial age (1982– 2004), and age groups vary in how they share information. For example, Schmitt et al.12 reported that the millennial generation’s use of social media is typical with 75% millennials using it in some form. Millennial users have always had the availability of technology, so sharing information is with a different perspective. Pelling and White13 also noted a direct correlation to the age of users and their expression in peer groups who share similarities. Atlas reported that millennial students are confident and unconcerned with the opinions of others and often approached social media with immaturity. Atlas’14 study also suggested that individual attitudes could contribute to unethical behavior on social media sites. Older students were more comfortable with nursing ethics standards when compared to younger students who had a greater likelihood of engaging in academic misconduct.14 The most significant contribution of McCrink’s15 study, for example, is the student’s perception of the relationship between ethics and professionalism in their commitment to the standard of care for patients. Younger nurses had identity and value issues with the knowledge of ethics and what they valued as right or wrong, while more experienced nurses had fewer issues. Englund et al.16 also noted that more than two-thirds of adults between the ages of 18 and 32 years frequent electronic social networking sites. However, Barker17 investigated the relationship between age and use of social networking sites, highlighting more similarities than differences in the ways that millennials and baby boomers use social media sites. Nevertheless, Barker noted that group identification influenced transfers to social networking sites, and younger cohorts tended to score higher for self-esteem as a precursor to social networking.
Data collection This study investigated student nurses’ ethical and unethical behavior and use of social media at an Associate Degree Nursing program in Texas. Table 1 illustrates the quantitative data collection methods taken by this study. The use of a quantitative survey allowed all nursing students in the Associate Degree Nursing program to give their perceptions of, and attitudes on, unethical behavior and allowed comparisons of their comments. Table 2 displays the following descriptive statistics related to student number of unethical behavior: mean, standard deviation, and range. Table 3 shows survey participant responses, ranging from 0 to 106. Even though the mean response was 6.61, this is not an accurate reflection of the data, as more than half of the respondents reported no unethical behavior. This large number of zero responses is reflected in the median response, which was 0.00; 60.8% of all responses were zero. Moreover, that the standard deviation of 19.004 is three times higher than the mean indicates that few responses were dispersed around the mean. The survey captured student perceptions and attitudes regarding unethical behavior. An understanding of student nurse perceptions, thoughts, attitudes, utilization of social media, and different communication venues were also determined. The quantitative design originally compared millennial and nonmillennial students as well as clinical cohorts and correlated behavior with social media use. Based on the results from
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Table 1. Quantitative data collection methodology. Data collection
Type of data
Instrument: Hilbert Unethical Behavior Survey–Modified (HUBS-M) Population (approximate) of Associate Degree Nursing (ADN) program Additional questions for independent variables
Numerical data Number of times unethical behavior occurred Dependent variable
Sample
Adjusted sample size per sample calculator Margin of error Confidence level
Data description
200
Entire Associate Degree Nursing student body
Nominal Ordinal Interval Convenience
Age (millennial vs nonmillennial) Clinical cohort Utilization of social media in minutes Based on similar characteristics such as enrollment in ADN program, multi-culture, age, utilization of social media Yields a 66% response rate—will strive for 70% response rate which would require 140 responses Statistical amount of random error Interval estimate of upper and lower ranges of observed data
132 5% 95%
Table 2. Descriptive statistics of unethical behavior. N
Mean
Standard deviation
Range
51
6.61
19.004
0–106
Table 3. Sum of responses to questions 5 through 27. Unethical behavior 0 1 2 3 4 6 7 8 9 10 18 20 47 75 106 Total Missing Total
Frequency
Percent
Valid percent
Cumulative percent
31 3 2 2 2 1 1 1 1 2 1 1 1 1 1 51
56.4 5.5 3.6 3.6 3.6 1.8 1.8 1.8 1.8 3.6 1.8 1.8 1.8 1.8 1.8 92.7 4 55
60.8 5.9 3.9 3.9 3.9 2.0 2.0 2.0 2.0 3.9 2.0 2.0 2.0 2.0 2.0 100.0 7.3 100.0
60.8 66.7 70.6 74.5 78.4 80.4 82.4 84.3 86.3 90.2 92.2 94.1 96.1 98.0 100.0
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Table 4. Differences in unethical behavior by age (millennial vs nonmillennial).
Millennial Nonmillennial
N
M (SD)
Range
Mann–Whitney
22 27
10.8 (23.8) 0.36 (14.3)
0–6 0–75
0.033 p < 0.05
these analyses and commonalities in the faculty interviews, a follow-up analysis correlated behavior with year of birth.
Analysis of generation First, the difference between millennial and nonmillennial students in terms of their frequency of unethical behavior was investigated. The level of measurement for the independent variable (generation) was nominal, while the dependent variable (unethical behavior) was interval. Millennials were defined as being born between 1982 and 1999. It was hypothesized that there would be a significant difference between student unethical conduct by generation. Descriptive statistics such as population, mean, and standard deviation were observed. Of the 51 respondents who provided their year of birth, 27 were nonmillennials and 24 were millennials. Two respondents, one millennial and one nonmillennial, ended the survey after providing their years of birth. This left 49 valid responses (26 nonmillennials and 23 millennials) for this analysis. Comparing the two populations, the mean response of the 26 nonmillennials was 3.77, while the mean response of the 23 millennials was 10.39. These means are supportive of the hypothesis and indicate that on average millennials reported almost three times as many instances of unethical behavior as nonmillennials. To determine the significance of the difference between the two populations, a Mann–Whitney test, which ranks the values of the summed responses before testing whether the two groups are drawn from the same population, was conducted. The null hypothesis for the Mann–Whitney test was that there would be no significant difference in unethical behavior by age. This hypothesis was rejected by the Mann–Whitney test, with a significance level of 0.033, indicating that the two populations offered significantly different responses to questions concerning their unethical behavior. Table 4 indicates differences in ethical behavior by generation.
Analysis of clinical cohorts A comparative design was also used to determine whether student clinical cohorts differed in their responses to questions concerning unethical behavior. It was hypothesized that there would be a significant difference between student unethical conduct by clinical cohort. Respondents were separated into three clinical cohorts according to their year of study: first-semester students, second-semester students, and a combination of thirdand fourth-semester students. Of the 51 respondents who provided their year of study, 21 were first-semester students (Cohort 1), 16 were second-semester students (Cohort 2), and 14 were third- and fourth-semester students (Cohort 3). Two respondents from Cohort 3 ended the survey after providing their years of study. This left 49 valid responses (21 from Cohort 1, 16 from Cohort 2, and 12 from Cohort 3) for this analysis. Comparing the three populations, the mean response from Cohort 1 was 12.38, the mean response from Cohort 2 was 0.44, and the mean response from Cohort 3 was 5.83. The means were supportive of the hypothesis and indicate that students in different clinical cohorts reported different numbers of instances of unethical behavior. To determine the significance of these differences, a Kruskal–Wallis test, which is an extension of the Mann–Whitney test that allows for the comparison of more than two populations, was conducted. The option to conduct multiple comparisons, pair-wise, between each population was selected.
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Table 5. Differences in unethical behavior by clinical cohort.
Cohort 1 Cohort 2 Cohort 3 Cohorts
N
M (SD)
Range
Kruskal–Wallis test
21 16 12 All
12.38 (27.127) 0.44 (1.094) 5.83 (13.210)
0–106 0–4 0–47
0.045
p value < 0.05
The null hypothesis for the Kruskal–Wallis test was that there would be no significant difference between student instances of ethical and unethical conduct by clinical cohort. This hypothesis was rejected by the Kruskal–Wallis test with a significance level of 0.045, indicating that the three populations offered significantly different responses to questions concerning their unethical behavior. Findings (Table 5) show that Cohort 1 had the most unethical behavior, while Cohort 2 was the best-behaved group. Cohort 3 exhibited more unethical behavior than Cohort 2 but not as much as Cohort 1. These initial findings raised a question as to why Cohort 2 was the best-behaved group, which was answered in the ‘‘Analysis of year of birth’’ section below.
Analysis of utilization of social media The next analysis sought to determine whether the amount of time respondents spend using social media correlated with their frequency of unethical behavior. It was hypothesized that there would be a significant relationship between student unethical behavior and utilization of social media. In total, 51 respondents provided valid responses for both unethical behavior and social media use. Comparing the two variables, the mean response for instances of unethical behavior in the past academic year was 6.61, with a standard deviation of 19.004, while the mean response for minutes spent using social media per day was 84.41, with a standard deviation of 78.814. Because both variables had relatively high standard deviations compared to the means, it was expected that Spearman’s nonparametric test for correlation would be most appropriate for these data. Spearman’s test uses the same equation as Pearson’s test, but first ranks the values in each variable to eliminate outliers. Nevertheless, as Pearson’s test does not assume that the data are normally distributed, Pearson’s test was conducted first. The null hypothesis for the correlation tests was that there would be no significant relationship between student ethical and unethical behavior in relation to utilization of social media. Pearson’s test revealed a very low correlation coefficient of 0.043, with a significance level of 0.381. As these results suggested the absence of any correlation, Spearman’s test was conducted to mitigate the data’s volatility. Spearman’s test (Table 6) revealed a higher correlation coefficient of 0.254 with a significance level of 0.036. Squaring the coefficient indicated that 6.45% of the variance in reported instances of unethical behavior can be explained by usage of social media. This means that 93.55% of the variance in reported instances of unethical behavior can be explained by factors other than social media use.
Analysis of year of birth Because the data in the first study indicated that second-semester cohort students behaved more ethically than first-semester and third- or fourth-semester cohorts, further examination was warranted. This analysis seeks to determine whether the respondents’ years of birth correlate with their degree of unethical behavior. It is hypothesized that there will be a significant relationship between student unethical conduct and year of birth.
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Table 6. Utilization of social media and unethical behavior: Spearman’s rho correlation. Sum of survey responses Sum of survey responses
Min spent using social media per day
Correlation coefficient Sig. (one-tailed) N Correlation coefficient Sig. (one-tailed) N
Min spent using social media per day
1.000 51 0.254 0.036 51
0.254 0.036 51 1.000 51
Correlation is significant at the 0.05 level (one-tailed).
Table 7. Student unethical conduct and year of birth: Spearman’s rho correlation.
In which year were you born? (enter four-digit year) Sum of survey responses
Correlation coefficient Sig. (one-tailed) N Correlation coefficient Sig. (one-tailed) N
In which year were you born? (enter four-digit birth year)
Sum of survey responses
1.000
0.384 0.003 49 1.000
51 0.384 0.003 49
51
Correlation is significant at the 0.05 level (one-tailed).
In review of the quantitative data, the cohort data were filtered for the average year of birth (Table 7). Below are the average birth years of the three cohorts: Cohort 1, 1981.48, Cohort 2, 1976.73, and Cohort 3, 1977. 38. These data, coupled with the fact that second-semester students were the best behaved, agrees with faculty’s perceptions and the current literature. Second-semester students were the oldest of all three cohorts, supporting the evidence that age is a reliable variable with students and unethical behavior. In total, 51 respondents provided valid responses for both unethical behavior and year of birth. As mentioned above, the mean response for instances of unethical behavior in the past academic year was 6.61 with a standard deviation of 19.004. The mean response for year of respondents’ birth was 1978.90 with a standard deviation of 8.310. For reasons stated in the previous section, Spearman’s nonparametric test for correlation would be most appropriate for these data. The null hypothesis for the correlation test was that there would be no significant relationship between student unethical conduct and year of birth. Spearman’s test revealed a correlation coefficient of 0.384 with a significance level of 0.003, which rejects the null hypothesis. Squaring the coefficient indicates that 14.75% of the variance in reported instances of unethical behavior can be explained by a respondent’s year of birth. This percentage is higher than the utilization of social media variable analyzed in the previous section ‘‘Analysis of utilization of social media.’’
Conclusion Findings from the previous study on Student Nurses’ Unethical Behavior, Boundaries, and Social Media indicate that the utilization of social media is significantly correlated with nursing students’ unethical
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behavior. The percentage explained by social media use may be low, but by being significant, it adds to our understanding of unethical behavior among nursing students. It could be that students who grew up with modern technology underreported instances of unethical conduct because this is their norm. Heilferty18 reported that millennials have always had technology available so their behavior would not necessarily change because of technology, but with any misconduct information would be quickly disseminated with technology. It was mentioned in the original study that future studies should be taken to reduce the large percentage of unexplained variance in reported instances of unethical behavior. The follow-up analysis on year of birth was taken as a first step in this variance reduction due to the fact that the original study could also not answer the question of why second-semester students were the most ethically behaved. This analysis sought to determine whether the respondents’ year of birth correlates with their degree of unethical behavior. Findings indicated that the second-semester cohort were the oldest students of all three cohorts. The percentage of variance explained by year of birth is higher and more significant than that explained by social media use, which adds more value to the original study and to our understanding of unethical behavior among nursing students. Additionally, the fact that second-semester students were the oldest of all three cohorts is supportive evidence that age is a reliable variable with students and unethical behavior. Conflict of interest The authors declare that there is no conflict of interest. Funding This research received no specific grant from any funding agency in the public, commercial, or not-forprofit sectors. References 1. Kuhns K. Social media and professional nursing: friend or foe? Pa Nurse 2011; 67(1): 4–7. 2. Kind T, Genrich G, Sodhi A, et al. Social media policies at US medical schools [Internet]. Med Educ Online 2010 [cited April 2, 2015]; 15: 19. Available from: PubMed Central. 3. Hader A and Brown E. Legal briefs: patient privacy and social media. Am Assoc Nurse Anesth 2010; 78(4): 1–5. 4. Cain J and Fink J. Legal and ethical issues regarding social media and pharmacy education. Am J Pharm Educ 2010; 74(10): 1–9. 5. Fraser R. The nurse’s social media advantage: how making connections and sharing ideas can enhance your nursing practice. Indianapolis, IN: Sigma Theta Tau International, 2011. 6. Two HIPAA breaches show continuing weaknesses. Healthc Risk Manag 2012; 34(6): 63–65. 7. Nurses again ranked No. 1 in honesty, ethics by Gallup Poll. Mass Nurs Advocate 2014; 85(1): 2. 8. National Council of State Boards of Nursing (NCSBN). A nurse’s guide to the use of social media, August 2011, https://www.ncsbn.org/Social_Media.pdf 9. Ginory A, Sabatier L and Spencer E. Addressing therapeutic boundaries in social networking. Psychiatry 2012; 75(1): 40–48. 10. Aylott M. Blurring the boundaries: technology and the nurse-patient relationship. Br J Nurs 2011; 20(13): 812–816. 11. Lachman VD. Social media: managing the ethical issues. Medsurg Nurs 2013; 22(5): 326–329. 12. Schmitt T, Sims-Giddens S and Booth R. Social media use in nursing education. Online J Issues Nurs 2012; 17(3): 2. 13. Pelling E and White K. The theory of planned behavior applied to young people’s use of social networking Web sites. Cyberpsychol Behav 2009; 12(6): 755–759. 14. Atlas M. Miss Manners for social networking: a new role for medical librarians. J Med Libr Assoc 2012; 100(4): 239–243.
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15. McCrink A. Nursing students’ attitudes towards academic misconduct, the code of ethics for nurses, and their commitment to the ethic of caring. PhD Dissertation, Dowling College, Oakdale, NY, 2008. 16. Englund H, Chappy S, Jambunathan J, et al. Ethical reasoning and online social media. Nurse Educ 2012; 37(6): 242–247. 17. Barker V. A generational comparison of social networking site use: the influence of age and social identity. Int J Aging Hum Dev 2012; 74(2): 163–187. 18. Heilferty C. Ethical considerations in the study of online illness narratives: a qualitative review. J Adv Nurs 2010; 67(5): 945–953.
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Student nurses’ unethical behavior, social media, and year of birth
Nursing Ethics 1–9 ª The Author(s) 2015 Reprints and permission: sagepub.co.uk/journalsPermissions.nav 10.1177/0969733015590009 nej.sagepub.com
Gloria Copeland Smith Central Texas College, USA
Troy Keith Knudson InGenesis Contingent Workforce Solutions, USA
Abstract Background: This study is the result of findings from a previous dissertation conducted by this author on Student Nurses’ Unethical Behavior, Boundaries, and Social Media. The use of social media can be detrimental to the nurse–patient relationship if used in an unethical manner. Method: A mixed method, using a quantitative approach based on research questions that explored differences in student nurses’ unethical behavior by age (millennial vs nonmillennial) and clinical cohort, the relationship of unethical behavior to the utilization of social media, and analysis on year of birth and unethical behavior. A qualitative approach was used based on a guided faculty interview and common themes of student nurses’ unethical behavior. Participants and Research Context: In total, 55 Associate Degree nursing students participated in the study; the research was conducted at Central Texas College. There were eight faculty-guided interviews. Ethical considerations: The main research instrument was an anonymous survey. All participants were assured of their right to an informed consent. All participants were informed of the right to withdraw from the study at any time. Findings: Findings indicate a significant correlation between student nurses’ unethical behavior and use of social media (p ¼ 0.036) and a significant difference between student unethical conduct by generation (millennials vs nonmillennials (p ¼ 0.033)) and by clinical cohort (p ¼ 0.045). Further findings from the follow-up study on year of birth and student unethical behavior reveal a correlation coefficient of 0.384 with a significance level of 0.003. Discussion: Surprisingly, the study found that second-semester students had less unethical behavior than first-, third-, and fourth-semester students. The follow-up study found that this is because second-semester students were the oldest cohort. Conclusion: Implications for positive social change for nursing students include improved ethics education that may motivate ethical conduct throughout students’ careers nationally and globally for better understanding and promotion of ethics and behavior. Keywords Confidentiality, ethics, Health Insurance Portability Accountability Act, privacy, professionalism, social media, teaching ethics, unethical conduct
Corresponding author: Gloria Copeland Smith. Email: [email protected]
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Introduction Nursing departments across the United States have had several instances where millennial-age nursing students in Associate Degree Nursing programs have been disciplined or expelled because of behavior that violated patient’s confidentiality, privacy, and the Health Insurance Portability Accountability Act (HIPAA). HIPAA protects patient privacy by defining individual identifiable information and establishes how this information is used. Nursing students who violate HIPAA laws, whether intentionally or unintentionally, share protected health information. According to Kuhns,1 HIPAA laws protect patient rights, privacy, and confidentiality.2 Examples of inappropriate activity while using social media include nurses taking pictures of patient health records for homework, posting patients’ pictures on Facebook, and posting patient information or comments on Facebook. HIPAA violations have resulted in expulsions, suspensions, and fines. According to Hader and Brown,3 two nurses in Wisconsin faced FBI investigation, HIPAA privacy violations, and pending charges from the licensing board for photographing an X-ray image showing a device lodged inside a patient. The primary purpose of this study was to better understand and clarify findings from a previous study regarding student use of social media by clinical cohort. Based on evidence from the principal researcher’s study on Student Nurses’ Unethical Behavior, Boundaries, and Social Media, findings showed that second-semester cohort students behaved more ethically than first-, third-, and fourth-semester cohorts. Because this was somewhat surprising, the principal researcher felt this warranted future research. The guided faculty interviews were further analyzed to assess faculty’s perception regarding clinical cohorts and unethical behavior. Faculty noted that first-semester students are normally thought to engage in the most unethical behavior and that students who had exhibited the most unethical conduct were in the firstsemester cohort. These findings lead to further examination as to why second-semester students were more ethically behaved than the third- and fourth-semester combined cohorts, as well as the first. Moreover, most faculty members perceived that younger students would have the most unethical behavior and that younger students would more than likely be in the earlier semester cohorts. However, this study has shown that this is not necessarily the case, as second-semester students had an earlier average year of birth than the third- and fourth-semester combined cohort. Faculty shared the main commonality that most students who engaged in unethical behavior were younger students who lacked experience. It is clear that social media policies are still evolving at institutions of higher education. Moreover, accredited schools of medicine report using different venues of social media but noted only 10% of the schools had any policies or guidelines.2 Cain and Fink4 observed that cultural mores relative to the use of social media devices have widened the intergenerational gap. Social media devices, observed by Cain and Fink, include Twitter, Facebook, Internet, and LinkedIn. Additionally, Fraser5 noted that students should approach the use of social media venues with policies, guidance, HIPAA, and disclaimers.6
Rationale A recent Gallup poll (2014) suggests that nursing is one of the most trusted professions.7 Because of this public trust, and the nurse–patient relationship, nurses have an ethical duty to do, or cause, no harm to patients. Nevertheless, a gap in practice concerning unethical conduct often emerges at clinical sites once students begin practicing. Breaching patient confidentiality and privacy has become increasingly common for nurses and students since the advent of social media. According to the National Council of State Boards of Nursing (NCSBN)8 and Ginory et al.,9 there are serious consequences of inappropriate use of social media. Aylott10 suggested that unethical online conduct and behavior have now become common practice. It is essential that nurses
Downloaded from nej.sagepub.com at UNIV NEBRASKA LIBRARIES on August 30, 2015
Smith and Knudson
3
continue to avoid situations that compromise the nurse–patient relationship. There have been more than 400 breaches of confidentiality incidents affecting more than 19 million individuals since 2009.3
Literature To support a foundation for the study, theories and related topics of ethics, professionalism, confidentiality, privacy, and teaching ethics were reviewed. The review also explored literature on social media and its connection to unethical conduct. According to Lachman,11 social media and Internet participants go beyond the millennial age (1982– 2004), and age groups vary in how they share information. For example, Schmitt et al.12 reported that the millennial generation’s use of social media is typical with 75% millennials using it in some form. Millennial users have always had the availability of technology, so sharing information is with a different perspective. Pelling and White13 also noted a direct correlation to the age of users and their expression in peer groups who share similarities. Atlas reported that millennial students are confident and unconcerned with the opinions of others and often approached social media with immaturity. Atlas’14 study also suggested that individual attitudes could contribute to unethical behavior on social media sites. Older students were more comfortable with nursing ethics standards when compared to younger students who had a greater likelihood of engaging in academic misconduct.14 The most significant contribution of McCrink’s15 study, for example, is the student’s perception of the relationship between ethics and professionalism in their commitment to the standard of care for patients. Younger nurses had identity and value issues with the knowledge of ethics and what they valued as right or wrong, while more experienced nurses had fewer issues. Englund et al.16 also noted that more than two-thirds of adults between the ages of 18 and 32 years frequent electronic social networking sites. However, Barker17 investigated the relationship between age and use of social networking sites, highlighting more similarities than differences in the ways that millennials and baby boomers use social media sites. Nevertheless, Barker noted that group identification influenced transfers to social networking sites, and younger cohorts tended to score higher for self-esteem as a precursor to social networking.
Data collection This study investigated student nurses’ ethical and unethical behavior and use of social media at an Associate Degree Nursing program in Texas. Table 1 illustrates the quantitative data collection methods taken by this study. The use of a quantitative survey allowed all nursing students in the Associate Degree Nursing program to give their perceptions of, and attitudes on, unethical behavior and allowed comparisons of their comments. Table 2 displays the following descriptive statistics related to student number of unethical behavior: mean, standard deviation, and range. Table 3 shows survey participant responses, ranging from 0 to 106. Even though the mean response was 6.61, this is not an accurate reflection of the data, as more than half of the respondents reported no unethical behavior. This large number of zero responses is reflected in the median response, which was 0.00; 60.8% of all responses were zero. Moreover, that the standard deviation of 19.004 is three times higher than the mean indicates that few responses were dispersed around the mean. The survey captured student perceptions and attitudes regarding unethical behavior. An understanding of student nurse perceptions, thoughts, attitudes, utilization of social media, and different communication venues were also determined. The quantitative design originally compared millennial and nonmillennial students as well as clinical cohorts and correlated behavior with social media use. Based on the results from
Downloaded from nej.sagepub.com at UNIV NEBRASKA LIBRARIES on August 30, 2015
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Nursing Ethics
Table 1. Quantitative data collection methodology. Data collection
Type of data
Instrument: Hilbert Unethical Behavior Survey–Modified (HUBS-M) Population (approximate) of Associate Degree Nursing (ADN) program Additional questions for independent variables
Numerical data Number of times unethical behavior occurred Dependent variable
Sample
Adjusted sample size per sample calculator Margin of error Confidence level
Data description
200
Entire Associate Degree Nursing student body
Nominal Ordinal Interval Convenience
Age (millennial vs nonmillennial) Clinical cohort Utilization of social media in minutes Based on similar characteristics such as enrollment in ADN program, multi-culture, age, utilization of social media Yields a 66% response rate—will strive for 70% response rate which would require 140 responses Statistical amount of random error Interval estimate of upper and lower ranges of observed data
132 5% 95%
Table 2. Descriptive statistics of unethical behavior. N
Mean
Standard deviation
Range
51
6.61
19.004
0–106
Table 3. Sum of responses to questions 5 through 27. Unethical behavior 0 1 2 3 4 6 7 8 9 10 18 20 47 75 106 Total Missing Total
Frequency
Percent
Valid percent
Cumulative percent
31 3 2 2 2 1 1 1 1 2 1 1 1 1 1 51
56.4 5.5 3.6 3.6 3.6 1.8 1.8 1.8 1.8 3.6 1.8 1.8 1.8 1.8 1.8 92.7 4 55
60.8 5.9 3.9 3.9 3.9 2.0 2.0 2.0 2.0 3.9 2.0 2.0 2.0 2.0 2.0 100.0 7.3 100.0
60.8 66.7 70.6 74.5 78.4 80.4 82.4 84.3 86.3 90.2 92.2 94.1 96.1 98.0 100.0
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Table 4. Differences in unethical behavior by age (millennial vs nonmillennial).
Millennial Nonmillennial
N
M (SD)
Range
Mann–Whitney
22 27
10.8 (23.8) 0.36 (14.3)
0–6 0–75
0.033 p < 0.05
these analyses and commonalities in the faculty interviews, a follow-up analysis correlated behavior with year of birth.
Analysis of generation First, the difference between millennial and nonmillennial students in terms of their frequency of unethical behavior was investigated. The level of measurement for the independent variable (generation) was nominal, while the dependent variable (unethical behavior) was interval. Millennials were defined as being born between 1982 and 1999. It was hypothesized that there would be a significant difference between student unethical conduct by generation. Descriptive statistics such as population, mean, and standard deviation were observed. Of the 51 respondents who provided their year of birth, 27 were nonmillennials and 24 were millennials. Two respondents, one millennial and one nonmillennial, ended the survey after providing their years of birth. This left 49 valid responses (26 nonmillennials and 23 millennials) for this analysis. Comparing the two populations, the mean response of the 26 nonmillennials was 3.77, while the mean response of the 23 millennials was 10.39. These means are supportive of the hypothesis and indicate that on average millennials reported almost three times as many instances of unethical behavior as nonmillennials. To determine the significance of the difference between the two populations, a Mann–Whitney test, which ranks the values of the summed responses before testing whether the two groups are drawn from the same population, was conducted. The null hypothesis for the Mann–Whitney test was that there would be no significant difference in unethical behavior by age. This hypothesis was rejected by the Mann–Whitney test, with a significance level of 0.033, indicating that the two populations offered significantly different responses to questions concerning their unethical behavior. Table 4 indicates differences in ethical behavior by generation.
Analysis of clinical cohorts A comparative design was also used to determine whether student clinical cohorts differed in their responses to questions concerning unethical behavior. It was hypothesized that there would be a significant difference between student unethical conduct by clinical cohort. Respondents were separated into three clinical cohorts according to their year of study: first-semester students, second-semester students, and a combination of thirdand fourth-semester students. Of the 51 respondents who provided their year of study, 21 were first-semester students (Cohort 1), 16 were second-semester students (Cohort 2), and 14 were third- and fourth-semester students (Cohort 3). Two respondents from Cohort 3 ended the survey after providing their years of study. This left 49 valid responses (21 from Cohort 1, 16 from Cohort 2, and 12 from Cohort 3) for this analysis. Comparing the three populations, the mean response from Cohort 1 was 12.38, the mean response from Cohort 2 was 0.44, and the mean response from Cohort 3 was 5.83. The means were supportive of the hypothesis and indicate that students in different clinical cohorts reported different numbers of instances of unethical behavior. To determine the significance of these differences, a Kruskal–Wallis test, which is an extension of the Mann–Whitney test that allows for the comparison of more than two populations, was conducted. The option to conduct multiple comparisons, pair-wise, between each population was selected.
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Table 5. Differences in unethical behavior by clinical cohort.
Cohort 1 Cohort 2 Cohort 3 Cohorts
N
M (SD)
Range
Kruskal–Wallis test
21 16 12 All
12.38 (27.127) 0.44 (1.094) 5.83 (13.210)
0–106 0–4 0–47
0.045
p value < 0.05
The null hypothesis for the Kruskal–Wallis test was that there would be no significant difference between student instances of ethical and unethical conduct by clinical cohort. This hypothesis was rejected by the Kruskal–Wallis test with a significance level of 0.045, indicating that the three populations offered significantly different responses to questions concerning their unethical behavior. Findings (Table 5) show that Cohort 1 had the most unethical behavior, while Cohort 2 was the best-behaved group. Cohort 3 exhibited more unethical behavior than Cohort 2 but not as much as Cohort 1. These initial findings raised a question as to why Cohort 2 was the best-behaved group, which was answered in the ‘‘Analysis of year of birth’’ section below.
Analysis of utilization of social media The next analysis sought to determine whether the amount of time respondents spend using social media correlated with their frequency of unethical behavior. It was hypothesized that there would be a significant relationship between student unethical behavior and utilization of social media. In total, 51 respondents provided valid responses for both unethical behavior and social media use. Comparing the two variables, the mean response for instances of unethical behavior in the past academic year was 6.61, with a standard deviation of 19.004, while the mean response for minutes spent using social media per day was 84.41, with a standard deviation of 78.814. Because both variables had relatively high standard deviations compared to the means, it was expected that Spearman’s nonparametric test for correlation would be most appropriate for these data. Spearman’s test uses the same equation as Pearson’s test, but first ranks the values in each variable to eliminate outliers. Nevertheless, as Pearson’s test does not assume that the data are normally distributed, Pearson’s test was conducted first. The null hypothesis for the correlation tests was that there would be no significant relationship between student ethical and unethical behavior in relation to utilization of social media. Pearson’s test revealed a very low correlation coefficient of 0.043, with a significance level of 0.381. As these results suggested the absence of any correlation, Spearman’s test was conducted to mitigate the data’s volatility. Spearman’s test (Table 6) revealed a higher correlation coefficient of 0.254 with a significance level of 0.036. Squaring the coefficient indicated that 6.45% of the variance in reported instances of unethical behavior can be explained by usage of social media. This means that 93.55% of the variance in reported instances of unethical behavior can be explained by factors other than social media use.
Analysis of year of birth Because the data in the first study indicated that second-semester cohort students behaved more ethically than first-semester and third- or fourth-semester cohorts, further examination was warranted. This analysis seeks to determine whether the respondents’ years of birth correlate with their degree of unethical behavior. It is hypothesized that there will be a significant relationship between student unethical conduct and year of birth.
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Table 6. Utilization of social media and unethical behavior: Spearman’s rho correlation. Sum of survey responses Sum of survey responses
Min spent using social media per day
Correlation coefficient Sig. (one-tailed) N Correlation coefficient Sig. (one-tailed) N
Min spent using social media per day
1.000 51 0.254 0.036 51
0.254 0.036 51 1.000 51
Correlation is significant at the 0.05 level (one-tailed).
Table 7. Student unethical conduct and year of birth: Spearman’s rho correlation.
In which year were you born? (enter four-digit year) Sum of survey responses
Correlation coefficient Sig. (one-tailed) N Correlation coefficient Sig. (one-tailed) N
In which year were you born? (enter four-digit birth year)
Sum of survey responses
1.000
0.384 0.003 49 1.000
51 0.384 0.003 49
51
Correlation is significant at the 0.05 level (one-tailed).
In review of the quantitative data, the cohort data were filtered for the average year of birth (Table 7). Below are the average birth years of the three cohorts: Cohort 1, 1981.48, Cohort 2, 1976.73, and Cohort 3, 1977. 38. These data, coupled with the fact that second-semester students were the best behaved, agrees with faculty’s perceptions and the current literature. Second-semester students were the oldest of all three cohorts, supporting the evidence that age is a reliable variable with students and unethical behavior. In total, 51 respondents provided valid responses for both unethical behavior and year of birth. As mentioned above, the mean response for instances of unethical behavior in the past academic year was 6.61 with a standard deviation of 19.004. The mean response for year of respondents’ birth was 1978.90 with a standard deviation of 8.310. For reasons stated in the previous section, Spearman’s nonparametric test for correlation would be most appropriate for these data. The null hypothesis for the correlation test was that there would be no significant relationship between student unethical conduct and year of birth. Spearman’s test revealed a correlation coefficient of 0.384 with a significance level of 0.003, which rejects the null hypothesis. Squaring the coefficient indicates that 14.75% of the variance in reported instances of unethical behavior can be explained by a respondent’s year of birth. This percentage is higher than the utilization of social media variable analyzed in the previous section ‘‘Analysis of utilization of social media.’’
Conclusion Findings from the previous study on Student Nurses’ Unethical Behavior, Boundaries, and Social Media indicate that the utilization of social media is significantly correlated with nursing students’ unethical
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behavior. The percentage explained by social media use may be low, but by being significant, it adds to our understanding of unethical behavior among nursing students. It could be that students who grew up with modern technology underreported instances of unethical conduct because this is their norm. Heilferty18 reported that millennials have always had technology available so their behavior would not necessarily change because of technology, but with any misconduct information would be quickly disseminated with technology. It was mentioned in the original study that future studies should be taken to reduce the large percentage of unexplained variance in reported instances of unethical behavior. The follow-up analysis on year of birth was taken as a first step in this variance reduction due to the fact that the original study could also not answer the question of why second-semester students were the most ethically behaved. This analysis sought to determine whether the respondents’ year of birth correlates with their degree of unethical behavior. Findings indicated that the second-semester cohort were the oldest students of all three cohorts. The percentage of variance explained by year of birth is higher and more significant than that explained by social media use, which adds more value to the original study and to our understanding of unethical behavior among nursing students. Additionally, the fact that second-semester students were the oldest of all three cohorts is supportive evidence that age is a reliable variable with students and unethical behavior. Conflict of interest The authors declare that there is no conflict of interest. Funding This research received no specific grant from any funding agency in the public, commercial, or not-forprofit sectors. References 1. Kuhns K. Social media and professional nursing: friend or foe? Pa Nurse 2011; 67(1): 4–7. 2. Kind T, Genrich G, Sodhi A, et al. Social media policies at US medical schools [Internet]. Med Educ Online 2010 [cited April 2, 2015]; 15: 19. Available from: PubMed Central. 3. Hader A and Brown E. Legal briefs: patient privacy and social media. Am Assoc Nurse Anesth 2010; 78(4): 1–5. 4. Cain J and Fink J. Legal and ethical issues regarding social media and pharmacy education. Am J Pharm Educ 2010; 74(10): 1–9. 5. Fraser R. The nurse’s social media advantage: how making connections and sharing ideas can enhance your nursing practice. Indianapolis, IN: Sigma Theta Tau International, 2011. 6. Two HIPAA breaches show continuing weaknesses. Healthc Risk Manag 2012; 34(6): 63–65. 7. Nurses again ranked No. 1 in honesty, ethics by Gallup Poll. Mass Nurs Advocate 2014; 85(1): 2. 8. National Council of State Boards of Nursing (NCSBN). A nurse’s guide to the use of social media, August 2011, https://www.ncsbn.org/Social_Media.pdf 9. Ginory A, Sabatier L and Spencer E. Addressing therapeutic boundaries in social networking. Psychiatry 2012; 75(1): 40–48. 10. Aylott M. Blurring the boundaries: technology and the nurse-patient relationship. Br J Nurs 2011; 20(13): 812–816. 11. Lachman VD. Social media: managing the ethical issues. Medsurg Nurs 2013; 22(5): 326–329. 12. Schmitt T, Sims-Giddens S and Booth R. Social media use in nursing education. Online J Issues Nurs 2012; 17(3): 2. 13. Pelling E and White K. The theory of planned behavior applied to young people’s use of social networking Web sites. Cyberpsychol Behav 2009; 12(6): 755–759. 14. Atlas M. Miss Manners for social networking: a new role for medical librarians. J Med Libr Assoc 2012; 100(4): 239–243.
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15. McCrink A. Nursing students’ attitudes towards academic misconduct, the code of ethics for nurses, and their commitment to the ethic of caring. PhD Dissertation, Dowling College, Oakdale, NY, 2008. 16. Englund H, Chappy S, Jambunathan J, et al. Ethical reasoning and online social media. Nurse Educ 2012; 37(6): 242–247. 17. Barker V. A generational comparison of social networking site use: the influence of age and social identity. Int J Aging Hum Dev 2012; 74(2): 163–187. 18. Heilferty C. Ethical considerations in the study of online illness narratives: a qualitative review. J Adv Nurs 2010; 67(5): 945–953.
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