While moral distress (MD) prevalence varies across practice areas, it is a phenomenon ubiquitous to health care that needs to be addressed.1 The complexity of today's nursing practice, in addition to the COVID-19 pandemic, creates an intense and stressful work environment2 contributing to physical and mental fatigue for registered nurses (RNs) who must balance patient care demands while managing their feelings.3 In our geographic region, COVID-19 cases remained relatively stable in the early months of the pandemic, with a 7-day average between 1.9 and 3.6 cases per 100 000 population.4 Cases increased significantly between July and August 2020, with a high 7-day average of 18 cases per 100 000 population.4 RNs argued this increase in cases, within a resource-restricted environment, may exacerbate MD and impact RNs' intent to seek employment elsewhere. In 2020, RN turnover in our Magnet and IBM Watson Health Top 100 Hospital was 8%, projected to increase to 13% in 2021, costing our organization $2.4 million in turnover expense. The turnover expense represents RN replacement salary (overtime and agency labor), recruitment (advertise, interview, and preemployment), and onboarding (orientation and training). Therefore, our RNs believed exploring factors influencing MD in our practice environment was critical to reversing the projected RN turnover.
AVAILABLE KNOWLEDGE
MD is a phenomenon that occurs when one knows the ethically correct action to take but is constrained from acting.1,5–8 MD has been expanded to include internal (eg, nurses' belief systems) and external constraints (eg, lack of time, institutional policy, legal considerations, and supervisory reluctance).9 Predictors of MD include staffing limitations, budget constraints, and higher patient acuity, which may be expressed through frustration, dissatisfaction, and burnout.10,11
MD has a direct relationship with RN turnover and quality of patient care.12 RNs with high MD are more likely to leave the organization, than those with low or moderate MD.13–18 One potential reason for RN turnover is the ongoing need to cope with moral dilemmas routinely experienced in nursing practice.10
Work environment is also a strong predictor of nursing burnout19–21 and MD.3,22 MD contributes to burnout and decreased job satisfaction, compounding patient quality and safety concerns.9,11,23,24 Continuous stressors such as increasing patient acuity and suboptimal staffing resources drain RNs' physical and emotional resources,25 which impact the quality of care RNs deliver. Quality of care is further diminished when MD is present as RNs may not address issues for fear of retaliation.7 Lack of a healthy nurse-patient relationship can negatively affect the quality and safety of patient care.26 Workplace stressors may prompt RNs to evaluate reasons to remain in the position and profession versus finding other less taxing opportunities.15
RATIONALE
The Measure of Moral Distress for Health Care Professionals (MMD-HP) was used to explore MD among RNs in our hospital.7 The MMD-HP7 was adapted from the Moral Distress Scale-Revised.27 Revisions by Epstein et al7 included enhancements in assessing team-level and system-level root causes of MD.
Specific aim
The main aim of this study was to explore the level of MD among RNs in our practice environment and inform our nurse leaders about the impact of MD on nursing turnover.
METHODS
Context
This study used an exploratory design to measure the frequency of MD and the level of MD related to situations RNs encounter. A global email was sent to 359 RNs in our hospital inviting them to complete the online, anonymous survey. Data were collected from 129 RNs who completed the survey. In addition to the MMD-HP, demographic data were collected. Targeted participants included RNs who were currently employed and between the ages of 18 and 89 years. Those who did not hold a valid RN license or did not meet the age requirement were excluded. The electronic survey software link was open between July 2020 and August 2020, only a few months into the COVID-19 pandemic within our geographic region. Reminders were sent every 3 weeks to encourage a higher response rate.
Measures
The MMD-HP is a valid and reliable tool (Cronbach α = 0.93) comprising 27 Likert-type items to measure MD for health care providers.7 The types of items include how often a situation occurs in practice (frequency: 0 = never, 4 = very frequently) and how distressing the situation is when it occurs (distress: 0 = none, 4 = very distressing). To generate a composite item score, the frequency score and distress scores for each item are multiplied, with item scores ranging from 0 to 16. The composite item scores are summed to obtain a total MD composite score. The resulting score based on 27 items ranges between 0 and 432. The higher the composite score totals, the higher the MD the provider experiences.7 Example scale items measuring both frequency and level of distress include “Experience lack of administrative action and support for a problem that is compromising patient care” and “Fear retribution if I speak up.”7
Data analysis
We used the Statistical Package for the Social Sciences, version 24.0 (IBM Corp, Armonk, New York) to characterize the study sample and explore group differences. Inferential statistical assumptions were checked before performing analyses. Independent samples t tests explored whether there was statistical evidence that the MMD-HP item and total score means differed significantly based on the responses of 107 direct care nurses, 41 of which were thinking about leaving and 66 were not.
Next, we performed an exploratory factor analysis (EFA) to provide orderly simplification of interrelated measures. Specifically, the EFA was used to explore the possible underlying factor structure of the set of 27 observed composite score variables without imposing a preconceived structure on the outcome. We used knowledge of the theoretical constructs and expert clinical face validity assessment to explore factor structure. We identified 2 factors according to the common item themes: (1) patient quality and safety and (2) work environment. Finally, to test the predictive ability of our 2 new factors, we ran a stepwise binary logistic regression examining the odds of RNs answering yes on the intent-to-leave question. For interpretability, we categorized the participant answers on the 2 factors as either average or below = 0 or above average = 1. We derived the average values by using frequency distributions (patient quality and safety average for this sample = 5; work environment average for this sample = 4).
Ethical considerations
The current study was approved by the local institutional review board.
RESULTS
Sample
Respondents were predominately female (90.7%) and White (92.5%), with 29% reporting nursing as a second career. The mean age for respondents was 44.2 years (SD = 12.8). Years of experience in nursing averaged 16.4 years (SD = 12.8), with 10.6 years (SD = 10.3) working in the current position. The most common unit represented was medical-surgical (27.1%), with respondents well distributed among the other units.
There were statistically significant differences in MD composite scores based on whether the respondent provides direct care at least 51% of the time (n = 107) and those who do not (n = 22). For that reason, the following analyses were done only with respondents who provide direct care at least 51% of the time. Scale reliability for this study was excellent with the Cronbach α = 0.92, consistent with the literature.7
Intent to leave due to moral distress
Significant differences between those who reported intent to leave versus those who did not are presented in the Table. Our results found that respondents who considered leaving their positions had significantly higher (t = −5.62, P < .001) MMD-HP mean composite scores (n = 41, M = 170.85) than those who did not (n = 66, M = 100.00).
Table. -
Differences in MMD-HP Between Groups
|
Thinking About Leaving |
|
| No (n = 66; 66.7%), M (SD) |
Yes (n = 41; 38.3%), M (SD) |
t test, P
|
| Witness health care providers giving “false hope” to a patient or family. |
4.35 (4.82) |
4.27 (4.57) |
.93 |
| Follow the family's insistence to continue aggressive treatment, even though I believe it is not in the best interest of the patient. |
6.82 (5.36) |
7.07 (5.12) |
.81 |
| Feel pressured to order or carry out orders for what I consider to be unnecessary or inappropriate tests and treatments. |
5.20 (4.82) |
6.90 (5.05) |
.08 |
| Be unable to provide optimal care due to pressures from administrators or insurers to reduce costs. |
6.12 (5.29) |
12.93 (4.45) |
<.001 |
| Continue to provide aggressive treatment for a person who is most likely to die regardless of this treatment when no one will make a decision to withdraw it. |
5.64 (5.30) |
5.17 (5.55) |
.67 |
| Be pressured to avoid taking action when I learn that a physician, nurse, or other team colleague has made a medical error and does not report it. |
1.05 (2.53) |
2.39 (3.84) |
.05 |
| Be required to care for patients whom I do not feel qualified to care for. |
1.96 (3.26) |
5.05 (5.75) |
.003 |
| Participate in care that causes unnecessary suffering or does not adequately relieve pain or symptoms. |
4.38 (4.74) |
4.51 (4.31) |
.88 |
| Watch patient care suffer because of a lack of provider continuity. |
4.32 (4.17) |
6.61 (5.36) |
.02 |
| Follow a physician's or family member's request not to discuss the patient's prognosis with the patient/family. |
2.64 (3.18) |
2.54 (2.95) |
.87 |
| Witness a violation of a standard of practice or a code of ethics and not feel sufficiently supported to report the violation. |
1.32 (2.71) |
5.02 (5.22) |
<.001 |
| Participate in care that I do not agree with, but do so because of fears of litigation. |
2.71 (4.18) |
3.85 (4.42) |
.18 |
| Be required to work with other health care team members who are not as competent as patient care requires. |
2.58 (3.37) |
5.78 (4.61) |
<.001 |
| Witness low quality of patient care due to poor team communication. |
3.09 (3.35) |
5.73 (4.91) |
.003 |
| Feel pressured to ignore situations in which patients have not been given adequate information to ensure informed consent. |
1.77 (2.96) |
2.90 (4.14) |
.10 |
| Be required to care for more patients than I can safely care for. |
7.29 (5.12) |
11.07 (5.46) |
<.001 |
| Experience compromised patient care due to lack of resources/equipment/bed capacity. |
5.30 (4.77) |
10.73 (5.48) |
<.001 |
| Experience lack of administrative action or support for a problem that is compromising patient care. |
4.94 (4.80) |
11.61 (4.86) |
<.001 |
| Have excessive documentation requirements that compromise patient care. |
4.86 (4.74) |
11.15 (5.50) |
<.001 |
| Fear retribution if I speak up. |
4.06 (4.50) |
10.51 (5.60) |
<.001 |
| Feel unsafe/bullied amongst my own colleagues. |
1.11 (2.66) |
3.98 (5.17) |
.002 |
| Be required to work with abusive patients/family members who are compromising quality of care. |
4.24 (4.59) |
6.66 (5.12) |
.01 |
| Feel required to overemphasize tasks and productivity or quality measures at the expense of patient care. |
5.41 (5.49) |
10.39 (5.59) |
<.001 |
| Be required to care for patients who have unclear or inconsistent treatment plans or who lack goals of care. |
2.73 (3.35) |
4.17 (3.77) |
.04 |
| Work within power hierarchies in teams, units, and my institution that compromise patient care. |
2.15 (3.45) |
4.68 (5.22) |
.01 |
| Participate on a team that gives inconsistent messages to a patient/family. |
2.49 (3.24) |
3.00 (3.18) |
.42 |
| Work with team members who do not treat vulnerable or stigmatized patients with dignity and respect. |
1.50 (3.28) |
2.17 (4.34) |
.37 |
Abbreviation: MMD-HP, Measure of Moral Distress for Health Care Professionals.
Exploratory factor analysis
We performed a parallel 1- to 3-factor EFA using an oblique rotation method allowing for correlation between factors. Our criteria for model consideration were eigenvalues larger than 1 and pattern matrix coefficients that round up to 0.7 or greater. We tested 1-factor, 2-factor, and 3-factor solutions, with a 1-factor solution yielding the worst result due to items of the scale not correlating with each other. The 3-factor solution had 2 acceptable factors and 1 factor with items that did not fit together well. Therefore, we chose the 2-factor solution as it contained pattern matrix coefficients that met our inclusion criteria (see Supplemental Digital Content, Table 1, available at: https://links.lww.com/JNCQ/A903).
Stepwise logistic regression
Our models were adjusted for age and years of nursing experience due to their significant relationship with our outcome on the binary level. In step 1, when considered together, age is not a significant predictor for the intent-to-leave question, while years of experience is (P = .02), with more experienced RNs having lower odds for selecting “yes” on intent to leave.
When adding patient quality and safety in step 2, we found that RNs who scored above average in MD due to perceived issues with patient quality and safety had 2.9 times the odds of replying that they are considering leaving their position due to MD (P = .019). The covariates are no longer statistically significant at step 2.
Finally, adding work environment in step 3 explained most of the variance in our model and the covariates and patient quality and safety are no longer significant predictors. In this final step, we found that RNs who score above average in MD due to perceived issues with work environment have 9.1 times the odds of replying that they are considering leaving their position due to MD (P < .001). Results of the final logistic regression are presented in Supplemental Digital Content, Table 2 (available at: https://links.lww.com/JNCQ/A904), with the final step explaining 40.3% of the variance in intent to leave.
DISCUSSION
Summary
Our main aim was to assess MD within the nursing practice environment to help nurse leaders mitigate nursing turnover. The total score and individual items of the MMD-HP were significant predictors of RNs considering leaving their position. When looking at the item-level results, we found that our RNs often experienced MD when they feel pressured by family and/or physicians to carry out what they believe to be aggressive or unnecessary treatment. Moreover, many of the issues related to quality and safety were ethical in nature. These results suggest that our RNs may not be aware of our current ethics consultation processes. Further investigation into RNs' knowledge and use of this process may provide valuable insight into how to integrate ethics consultation into practice and reduce MD.
We identified 2 main factors using EFAs: work environment and patient quality and safety. RNs who perceived their work environment as morally distressing had 9 times the odds of considering intent to leave their position compared with their corespondents. RNs who perceived our hospital's quality and safety practices as morally distressing had almost 3 times the odds of intent to leave.
Interpretation
The results of this study are in concordance with previous literature that highlights the importance of work environment in RN retention.20 Specifically, through the support of coworkers and nurse leaders, direct care RNs can learn and grow professionally and develop a sense of belongingness at work.11 A work environment where MD is minimized encourages RNs to feel united, share experiences, and learn coping strategies from each other and fosters an environment where the feelings of powerlessness shift and RNs begin to thrive.10
To our knowledge, this is the first study examining MD and RN turnover during the COVID-19 pandemic. The pandemic contributed to environmental constraints within our practice environment beyond our control, yet the relationships between the variables, MD and intent to leave, were like those of studies conducted before the pandemic.7,9 It is unknown whether our staff experienced higher MD due to the pandemic or whether MD develops over a longer period and thus is less vulnerable to external threats such as a global pandemic. Therefore, we recommended a longitudinal evaluation of MD for RNs within our hospital along with 11 more hospitals within our health system.
Limitations
This study had a few limitations. A convenience sample of RNs employed at one hospital may limit the generalizability of the findings. While the demographics were reflective of the RNs at our hospital, most respondents were White and female. Future research should allow for a more diverse RN population across geographic regions. Also, a larger sample confirmatory factor analysis (CFA) is needed to verify the 2-factor structure identified by the EFA performed in this study. The CFA would allow the researchers to test the hypothesis that a relationship between observed variables and their underlying latent constructs exists.
CONCLUSION
Our nurse executive reviewed study results and provided insightful action plans to work toward an enhanced healthy work environment. Aligned with the American Nurses Credentialing Center,28 our nurse executive planned individual meetings with RNs to address resource adequacy, practice autonomy, quality of care, leader responsiveness, interprofessional relationships, professional development, and RN-to-RN collegiality. During those conversations, our nurse executive explored areas of MD and communicated management strategies while ensuring a safe and nonjudgmental space. Staff were encouraged to contact the hospital ethics committee when an MD situation arises. Trained ethicists are on call 24/7 to help nurses explore their feelings and discuss solutions.
The nurse executive worked to ensure critical resources are readily available upon request, especially regarding personal protective equipment during the pandemic. Leveraging additional support staff to enhance the time RNs are available to engage each patient was a priority. This study highlighted concerns with patient quality and safety providing an opportunity for staff to become more engaged in ethical education and consultation. In late 2020, the nurse executive began check-in and stay interviews individually with new RNs to gain insight into experiences and maintain a transparent transformational leadership.
In conclusion, with the identification that the work environment has a high impact on RN retention, nurse leaders can work on additional support methods for their RNs. Interventions can be implemented to reduce the frequency and level of MD. Moreover, nurse leaders can assist with sustainability to improve the work environment by offering additional support to help RNs cope with moral dilemmas routinely experienced in their practice. Employee assistance programs can encourage RNs to communicate their feelings through difficult ethical decisions, balancing patient care demands while managing their feelings.
REFERENCES
1. Prentice T, Gillam L, Davis P, Janvier A. Always a burden? Healthcare providers' perspectives on moral distress. Arch Dis Child Fetal Neonatal Ed. 2018;103(5):F441–F445. doi:10.1136/archdischild-2017-313539
2. American Association of Critical Care Nurses (AACN). AACN position statement: moral distress in times of crisis. Published 2020. Accessed April 8, 2021.
https://www.aacn.org/policy-and-advocacy/aacn-position-statement-moral-distress-in-times-of-crisis
3. Rice EM, Rady MY, Hamrick A, Verheijde JL, Pendergast DK. Determinants of moral distress in medical and surgical nurses at an adult acute care hospital. J Nurs Manag. 2008;16(3):360–373. doi:10.1111/j.1365-2834.2007.00798.x
4. Virginia Department of Health. COVID-19 in Virginia. Accessed April 8, 2021.
https://www.vdh.virginia.gov/coronavirus/covid-19-in-virginia
5. Pendry P. Moral distress: recognizing it to retain nurses. Nurs Econ. 2007;25(4):217–221.
6. Hamric AB, Epstein EG. A health system-wide moral distress consultation service: development and evaluation. HEC Forum. 2017;29(2):127–143. doi:10.1007/s10730-016-9315-y
7. Epstein E, Whitehead P, Prompahakul C, Thacker L, Hamric A. Enhancing understanding of moral distress: the measure of moral distress for healthcare professionals. AJOB Empir Bioeth. 2019;10(2):113–124. doi:10.1080/23294515.2019.1586008
8. Trautmann J. Moral distress: recognition, diagnosis and treatment. J Infus Nurs. 2015;38(4):285–289. doi:10.1097/NAN.0000000000000111
9. Rathert C, May DR, Chung HS. Nurse moral distress: a survey identifying predictors and potential interventions. Int J Nurs Stud. 2016;53:39–49. doi:10.1016/j.ijnurstu.2015.10.007
10. Morley G. What is “moral distress” in nursing? How, can and should we respond to it? J Clin Nurs. 2018;27(19/20):3443–3445. doi:10.1111/jocn.14332
11. Mills M, Cortezzo DE. Moral distress in the neonatal intensive care unit: what is it, why it happens, and how we can address it. Front Pediatr. 2020;8:581. doi:10.3389/fped.2020.00581
12. Chiafery M, Hopkins P, Norton S, Shaw M. Nursing ethics huddles to decrease moral distress among nurses in the intensive care unit. J Clin Ethics. 2018;29(3):217–226.
13. Austin CL, Saylor R, Finley PJ. Moral distress in physicians and nurses: impact on professional quality of life and turnover. Psychol Trauma. 2017;9(4):399–406. doi:10.1037/tra0000201
14. Lusignani M, Gianni ML, Giuseppe L, Buffon ML. Moral distress among nurses in medical, surgical and intensive-care units. J Nurs Manag. 2017;25(6):477–485. doi:10.1111/jonm.12431
15. Laurs L, Blaževičienė A, Capezuti E, Milonas D. Moral distress and intention to leave the profession: Lithuanian nurses in municipal hospitals. J Nurs Scholarsh. 2020;52(2):201–209. doi:10.1111/jnu.12536
16. Whitehead P, Herbertson R, Hamric A, Epstein E, Fisher J. Moral distress among healthcare professionals: report of an institution-wide survey. J Nurs Scholarsh. 2015;47(2):117–125. doi:10.1111/jnu.12115
17. Karakachian A, Colbert A. Nurses moral distress, burnout, and intentions to leave: an integrative review. J Forensic Nurs. 2019;15(3):133–142. doi:10.1097/JFN.0000000000000249
18. Fernandez-Parsons R, Rodriguez L, Goyal D. Moral distress in emergency nurses. J Emerg Nurs. 2013;39(6):547–552. doi:10.1016/j.jen.2012.12.009
19. Swamy L, Mohr D, Blok A, et al. Impact of workplace climate on burnout among critical care nurses in the Veterans Health Administration. Am J Crit Care. 2020;29(5):380–389. doi:10.4037/ajcc2020831
20. Gensimore MM, Maduro RS, Morgan MK, McGee GW, Zimbro KS. The effect of nurse practice environment on retention and quality of care via burnout, work characteristics, and resilience: a moderated mediation model. J Nurs Adm. 2020;50(10):546–553. doi:10.1097/NNA.0000000000000932
21. Van Bogaert P, Clarke S, Roelant E, Meulemans H, Van de Heyning P. Impacts of unit-level nurse practice environment and burnout on nurse-reported outcomes: a multilevel modelling approach. J Clin Nurs. 2010;19(11/12):1664–1674. doi:10.1111/j.1365-2702.2009.03128.x
22. Schaefer R, Zoboli ELCP, Vierira M. Moral distress in nurses: a description of the risks for professionals. Texto Contexto Enferm. 2018;27(4):e4020017. doi:10.1590/0104-07072018004020017
23. Cimiotti JP, Aiken LH, Sloane DM, Wu ES. Nurse staffing, burnout, and health care–associated infection. Am J Infect Control. 2012;40(6):486–490. doi:10.1016/j.ajic.2012.02.029
24. Van Bogaert P, Peremans L, Van Heusden D, et al. Predictors of burnout, work engagement and nurse reported job outcomes and quality of care: a mixed method study. BMC Nurs. 2017;16:5. doi:10.1186/s12912-016-0200-4
25. Owens J, Singh G, Cribb A. Austerity and professionalism: being a good healthcare professional in bad conditions. Health Care Anal. 2019;27(3):157–170. doi:10.1007/s10728-019-00372-y
26. Hasanlo M, Azarm A, Asadi P, Amini K, Ebrahimi H, Jafarabadi MA. Analytical study of care quality and moral distress in clinical situations and patient care. Front Nurs. 2019;6(4):327–333. doi:10.2478/FON-2019-0037
27. Lamiani G, Setti H, Barlascini L, Vegni E, Argentero P. Measuring moral distress among critical care clinicians: validation and psychometric properties of the Italian Moral Distress Scale–Revised. Crit Care Med. 2017;45(3):430–437. doi:10.1097/CCM.0000000000002187
28. American Nurses Credentialing Center. Magnet model: creating a Magnet culture. Published 2021. Accessed April 8, 2021.
https://www.nursingworld.org/organizational-programs/magnet/magnet-model
