The Moral Impact Of The COVID-19 Pandemic On Nurses’ Burnout, Work Satisfaction And Adaptive Work Performance: The Role Of Autobiographical Memories Of Potentially Morally Injurious Events And Basic Psychological Needs Part 3

Education. Education significantly influenced work motivation, with post-hoc tests showing that nurses with bachelor’s degrees were significantly more satisfied with their work as compared to nurses with post-secondary studies (Table 3).

According to research, learning has a significant positive impact on improving memory. In this regard, a bachelor's degree strengthens our cognitive abilities, improves memory function, and enhances concentration and problem-solving abilities. Therefore, it can be said that there is a close connection between a bachelor's degree and memory. Through learning, you can not only gain knowledge but also improve your cognitive abilities and memory.

A bachelor's degree not only provides a wide range of subject knowledge, but more importantly, through learning, we can develop our learning habits and ways of thinking. These often require deeper thinking and memory support.

Furthermore, a bachelor's degree requires students to master a large amount of knowledge and skills, which requires us to put in more effort and continue to learn. This kind of continuous learning can not only strengthen the accumulation of knowledge but also train our thinking and memory.

In addition, the curriculum of a bachelor's degree also helps improve our memory. We need to make connections, identify different concepts, and apply them as we take many major and elective courses. These require us to integrate and summarize the knowledge we have learned, thereby improving learning effects and memory abilities.

In summary, there is a strong connection between a bachelor's degree and memory. Not only can you gain knowledge through learning, but you can also improve your cognitive abilities and memory. People with a bachelor's degree usually have higher thinking skills and creativity and are better able to adapt to social and work environments. Therefore, we should actively pursue a bachelor's degree and pay attention to spiritual training to give full play to our potential, improve our memory and learning abilities, and pave the way for future success. It can be seen that we need to improve our memory. Cistanche deserticola can significantly improve memory because Cistanche deserticola is a traditional Chinese medicinal material with many unique effects, one of which is to improve memory. The efficacy of minced meat comes from the various active ingredients it contains, including acid, polysaccharides, flavonoids, etc. These ingredients can promote brain health in various ways.

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3.2. Self-Defining Memories of PMIEs and SMTs

As hypothesized in H1, memories of both PMIEs and SMTs were quite important (MPMIE = 5.19; MSMT = 4.44) and quite central to the self (MPMIE = 5.4; MSMT = 4.73), since the means indicate ‘important’ and ‘rather important’ on the 1 to 7 scales used [13].

3.3. Path Analysis of the Conceptual Model

Although some correlations between variables (Figure 1) were strong (Table 4), VIF values were under 5, and Tolerance values were over 0.2 (Tables 4 and A1, in Appendix B), while skewness and kurtosis were between −3 and 3 (Table 4). For information about outliers, please consult Appendix C and Tables A2 and A3. Since multicollinearity was not problematic and internal consistency was acceptable, we ran the path analysis with DWLS estimation and percentile bootstrapping using 10,000 resamples on our data.

Our exogenous variables were “Experimental Condition” and socio-demographic characteristics for which we controlled. Our endogenous variables comprised the proposed mediators (“Autonomy Thwarting”, “Work Motivation”, “Moral Learning”, “Burnout” and “Work Satisfaction”) and our dependent variable, “Adaptive Performance” (Figure 1). Our model included both serial (“Experimental Condition → Autonomy Thwarting → Work motivation → Moral Learning”) and parallel mediation (“Moral Learning → Burnout → Adaptive Performance” and, respectively, “Moral Learning → Work Satisfaction → Adaptive Performance”). A direct path from “Experimental Condition” to “Adaptive Performance” was also included (i).

We controlled for the effects of our participants’ age on autonomy, work motivation, adaptive performance, and work satisfaction, as well as for the effects of gender on work motivation, moral learning, and adaptive performance. The variable “Experimental Condition” was dummy-coded, so that the reference group was the one who recalled SMT events. 

This way, we could interpret path coefficients relative to the group having recalled SMTs, and make inferences regarding memories of PMIEs, the main focus of our investigation. Residual covariances between exogenous variables (“Gender”, “Age”, and “Experimental Condition”) were included in the model. Consequently, the regression equations included in our model were:

Direct and indirect effects were estimated by multiple regression analyses, with unstandardized coefficients B and standardized coefficients β for all variables. Standard Errors (SEs), Test Statistics (z-values), and p-values (p>|z|) were computed based on the unstandardized coefficients, and we assessed significance based on the 95% Confidence Intervals computed for the Standard Errors with the 10,000 re-draws percentile bootstrapping procedure. To assess the hypothesized mediation relationships, we modeled (a). 

Direct effects for Adaptive Performance (i), Burnout (k), and Work Satisfaction (j); indirect effects (by multiplying the path coefficients connecting the independent variables to their proposed outcomes); (c). total effects (the sum of direct and indirect effects) (Table 5). A good model fit would involve the model converges, resulting in CFI and TLI values exceeding 0.950, SRMR values below 0.05, RMSEA values below 0.08, GFI values over 0.95, AGFI values above 0.9, and CMIN/df below 3, with a non-significant chi-square test [31].

In our case, lavaan’s algorithm converged. We found a good model fit, suggesting that our specified paths may correspond to the observed data we collected (CFI = 0.999, TLI = 0.997, GFI = 1; AGFI = 1; SRMR = 0.019, RMSEA = 0.021, 95% CI [0.00; 0.05]; χ 2 (8) = 10.08, p = 0.259; χ2/df = 1.26). The R 2 values suggested that the model accounted for 11% of the variance in autonomy thwarting (R 2 = 0.109), 37.2%—in Work Motivation (R 2 = 0.372), 42%—in Burnout (R 2 = 0.42), 44%—in Moral Learning (R 2 = 0.44), 39.7%—in Work Satisfaction (R 2 = 0.397) and 66.7%—in Adaptive Performance (R 2 = 0.667).

The parameter estimation confirmed our hypotheses regarding the effects of recalling PMIEs as compared to recalling SMTs on autonomy thwarting (H2), Work Motivation (H3), and Moral Learning (H4), as illustrated in Table 5. 

Thus, autonomy thwarting was significantly higher in memories of PMIEs than in memories of SMTs (H2). Memories of PMIEs were followed by more controlled work motivation when accounting for the contribution of autonomy thwarting as compared to memories of SMTs (H3). 

Recalling PMIEs was followed by lower moral learning than recalling SMTs, with a lower frequency of morally upward counterfactuals for the PMIE group than for the SMT group, when accounting for autonomy thwarting and work motivation (H4). Also, work motivation significantly predicted work satisfaction when accounting for autonomy thwarting, and for the difference between the two experimental conditions (Table 5). PMIE recall was associated with less work satisfaction as compared to SMT recall when accounting for work motivation and autonomy thwarting. 

Work motivation was negatively associated with burnout, and participants recalling PMIEs had higher levels of burnout and lower levels of adaptive performance than participants recalling SMTs. Adaptive performance was significantly predicted by autonomy thwarting, work motivation, work satisfaction, moral learning, and burnout, with lower burnout being associated with less autonomy thwarting, higher moral learning, and higher adaptive performance—with higher moral learning, work satisfaction, and work motivation. The estimates for age—one of our control variables—were significant only in predicting work satisfaction, with younger nurses experiencing more of it as compared to their older counterparts (Table 5). Participants identifying as female reported higher work motivation and moral learning than participants identifying as male (Table 5).

Mediation analyses were run to test H5, H6, and H7 (Table 6). Recalling PMIEs led to higher levels of burnout than recalling SMTs, a relationship mediated by autonomy thwarting and work motivation: participants recalling PMIEs had experienced more autonomy thwarting and more controlled work motivation, which led to higher burnout, in comparison to participants recalling SMTs. The indirect effect of the experimental condition on work satisfaction was also significant, with participants having recalled PMIEs, and having experienced more autonomy thwarting and more controlled work motivation, leading to less work satisfaction. 

Recalling PMIEs decreased nurses’ adaptive performance more as compared to recalling SMTs, following the three mediational paths proposed. First, recalling PMIEs was associated with more autonomy thwarting, leading to more controlled work motivation, higher burnout, and, consequently, lower adaptive performance. Also, recalling PMIEs decreased adaptive performance as compared to recalling SMTs through autonomy thwarting, more controlled work motivation, and less moral learning. Finally, PMIE recall resulted in lower adaptive performance than SMT recall, by thwarting autonomy, leading to more controlled work motivation and less work satisfaction (Table 6). In conclusion, H5, H6, and H7 were confirmed.

4. Discussion

The COVID-19 pandemic affected nurses the most in terms of physical and mental health, occupational well-being, and work performance [1–4]. Moral injury is the consequence of exposure to PMIEs, which has soared during this time due to individual, social, and organizational factors [5,24,42]. At the individual level, we could mention the initial lack of theoretical and procedural medical knowledge about the new coronavirus, conflicts about prioritizing personal and family health versus prioritizing patient care, as well as moral conflicts between patients’ rights to freedom versus the public health demand for their isolation [43,44].
At the social level, moral stressors included frequent personnel displacement leading to poor coordination among medical teams and divergent opinions on treatment plans, along with a perceived lack of competence of colleagues and fear that they were not respecting safety standards [43]. Organizationally, institutional unpreparedness was reflected in insufficient PPE, time, and personnel [42]. This left nurses with feelings of guilt and shame stemming from their perceived inability to save sufficient lives and protect themselves and their families [1–4]. 

PMIEs and moral injuries were traditionally researched in war veterans, and thus insufficiently explored in healthcare and, specifically, in nurses [23]. By drawing upon recent studies on moral autobiographical memories [6–8] and self-determination theory [9–12], our study explored how memories of PMIEs can impact the psycho-social functioning, mental health, and adaptive performance of nurses, thus highlighting a previously unexplored area of long-term effects of the COVID-19 pandemic.

We tested the fit of a conceptual model describing the mechanisms through which memories of PMIEs may affect nurses’ adaptive performance by increasing burnout and decreasing work satisfaction (Figure 1). Our findings show that exposure to PMIEs, autonomy thwarting, work motivation, burnout, moral learning, and work satisfaction can independently and jointly decrease nurses’ adaptive performance. Despite its relevance during the current pandemic, the study of adaptive performance in healthcare has been largely neglected [45]. 

Adaptive performance is one of the most important dimensions of work performance in constantly changing environments. The rapid spread of the new coronavirus created unprecedented pressure, stress, and radical practice transformations in global healthcare systems, largely unprepared to handle a health crisis of this magnitude (e.g., [3]). According to our results, exposure to work-related PMIEs could have dramatically affected this ability in nurses, emphasizing the necessity of organizations to engage in moral repair after PMIE exposure [46]. Notably, to our knowledge, this is also the first study to show that moral learning can affect nurses’ adaptive performance as well, adding to the calls to provide them with an ethically safe climate [42].

Burnout and work satisfaction were also negatively influenced by recalling PMIEs through the proposed mediational paths (Figure 1). The COVID-19 pandemic exerted a great toll on these occupational health parameters in nurses, with high levels of burnout and low work satisfaction deemed as urgent issues in healthcare [20]. Our results suggest that exposure to PMIEs, along with autonomy thwarting and controlled work motivation may have contributed to this increase, in line with previous results [11]. However, we found that work motivation mediates the relationship between the autonomy-thwarting component of PMIE memories and burnout, respectively work satisfaction, which has not been shown before, to our knowledge. Therefore, our findings highlight the importance of cultivating self-determined motivation in nurses to increase job satisfaction and decrease burnout, which could also lower turnover intentions and heightens affective commitment [47], both problematic areas during the pandemic [48].

According to our findings and previous literature [10], organizational support for nurses’ autonomy could improve their self-determined motivation, and thus capitalize on their full potential [49]. Consequently, nurses should be supported in taking pride in their work, given more autonomy, encouraged to voice their opinions, and acknowledged as an invaluable part of the medical team [49].

Nurses recalling PMIEs perceived themselves as moral transgressors and as moral victims, whereas nurses recalling SMTs mainly saw themselves as moral transgressors, in line with previous studies and theoretical perspectives which emphasize that PMIEs are moral transgressions performed unwillingly, as they violate personal/professional moral values [2,23]. Since memories of PMIEs and SMTs could constitute self-defining memories according to our findings, an assumption that should be further tested, they could negatively affect how nurses perceive their work environment and their profession [11–13].

Furthermore, self-defining memories anchor work identities [11], and memories of PMIEs could lead to developing a sense of an immoral self-concept more than memories of SMTs, due to the perceived lack of agency during PMIEs, which impaired moral learning in our sample. When people remember severe moral wrongdoing, they learn from it by mentally simulating alternative ways of action, which would have made them feel as if they were morally good (i.e., upward moral counterfactuals) [7]. In turn, this leads to strong intentions to behave differently in the future (i.e., moral improvement), which ensures a future morally good self-concept. The differences in moral learning that emerged in our results suggest that while this process occurred for nurses who recalled SMTs, in line with previous research [7], it did not follow the experiences of PMIEs. Then, having experienced a PMIE may alter both the present and the future morally good self-concept in nurses, essential for a positive professional identity [50]. 

The consequences of this alteration may extend beyond occupational self-concept and outcomes (i.e., burnout, work satisfaction, and adaptive performance) and reach the personal self-concept since morality is an essential component of self-identity [51]. Furthermore, they could also lead to other negative health outcomes, as observed in members of armed forms exposed to PMIEs, including self-harm, suicidality, substance use, social problems, and increased risk of PTSD and depression (e.g., [23]). Future studies should examine these assumptions empirically.

Our findings are also relevant for policymakers. Supporting nurses’ autonomy organizationally and including them in the decision-making processes could have beneficial effects on the perceived impact of exposure to PMIEs [42]. Preparing nurses beforehand by providing them with an honest, direct account of the incoming ethical difficulties might decrease the risk of subsequent mental health problems [4]. Routine briefings on PMIEs, organized between peers or including a supportive supervisor, may help to reframe how they recall those incidents and their deleterious effects. Finally, healthcare organizations should engage in moral repair, rebuilding trust for nurses who have witnessed severe moral transgressions perpetrated by their superiors [46]. After the crisis passes, staff should be actively monitored to identify members who are suffering and refer them to services of psychological assistance, where they may get the necessary help to alleviate their guilt, shame, and other psychological symptoms [4].

Our research is not without limitations. Our sample comprised an unequal number of nurses identifying as female and nurses identifying as male. Although the ratio in our sample is fairly representative of the one found in the general population of nurses in Romania [52] and around the world [53], which comprised only approximately 10% of nurses identifying as male, thus increasing our external validity, it may have influenced our results. Future studies that have a primary goal of gender differences in adaptive performance should address this when choosing their participants. 

Also, we had a few participants with bachelor’s and master’s degrees in our samples, which is also fairly representative of nurses in Romania. However, in other contexts, this may constitute a limit to the generalizability of our results in this regard. Although considered adequate by some, our sample may be considered modest by others, so future studies could increase the number of participants when investigating this topic. Finally, due to ethical considerations, we could not provide a thematic analysis of the incidents recalled by our participants, as they would not volunteer information that could have negative consequences for them if made public, especially when recounting SMT transgressions, which could also include medical errors. However, past research has shown that self-reported judgments of morality are very reliable, with people finding it easy to detect what constitutes an (im)moral act [54]. Given that we checked our experimental manipulations, we are confident in our results in this regard. 

Future research should also investigate whether perceptions of intentionality play a part in autonomy thwarting for PMIEs since past research showed that unintentional offenses are perceived as less negative [6]. It could be that PMIEs perceived as devoid of intentionality do not have such a strong impact on burnout, work satisfaction, or adaptive performance. For instance, if a fellow nurse stayed at home after contracting the new coronavirus and a patient died because of a shortage of staff, the lack of intentionality characterizing the incident lessens the psychological impact on the nurse who remembers this incident.

5. Conclusions

Nurses have suffered greatly from exposure to PMIEs during the COVID-19 pandemic. This was due to higher workloads and infection rates, insufficient medical supplies, and additional challenging ethical dilemmas (e.g., resource allocation when patient needs surpass available supplies), along with the guilt and shame associated with the perceived inability to save sufficient lives [1,2,4,46]. 

The accumulation of the moral residue left behind by PMIEs can have a detrimental effect on work performance, undermining and dehumanizing the caregiving practice. Our findings showed that unique incidents of PMIEs when recalled, can hurt their work motivation, work satisfaction, moral learning, burnout, and adaptive performance. Other studies confirm the importance of the ethical challenges faced by nurses worldwide due to the pandemic and call for both action and more research into this phenomenon [1–3,5,25,42]. 

For instance, in the UK, self-identified burnout in NHS staff includes a significant moral component, with failure to engage in moral repair leading to long-term loss of trust and deteriorated relationships with one’s work establishment [46]. In the USA, a longitudinal study showed that nurses’ moral injury remained stable over three months during the pandemic, while psychological distress decreased, especially in unsupportive work environments [55]. In Italy and Austria, moral distress and moral injury were the main stressors with which healthcare workers were confronted, and organizational justice and decentralized decision-making were essential for mitigating their negative effects [56]. In Israel, exposure to PMIEs was high during the COVID-19 pandemic in healthcare, leading to depression, anxiety, increased self-criticism, and decreased self-compassion [57]. 

In China, during the COVID-19 pandemic, nurses found that organizational autonomy and connectedness support were essential for managing the wide array of ethical problems that arose [43], leading to depression, anxiety, low well-being, and emotional exhaustion [58]. In Australia, the pandemic brought about a similar host of problems, with moral stressors leading to anxiety, depression, posttraumatic stress disorder, and burnout, and with targeted interventions required to prevent or minimize exposure to PMIEs and their negative effects [44]. We join the authors above in recommending that healthcare leadership at all levels be trained to identify and prevent betrayal-based moral injury and to implement moral repair organizational practices to reduce turnover intentions and promote mutual trust.

Appendix A. Experimental Procedure

The study was self-paced. After reading and agreeing with the informed consent, participants filled in socio-demographic information concerning the socio-cultural gender with which they identified, their age, and their job experience, as previous research showed that being younger, having more experience, and identifying as a woman fosters adaptive performance [29,59,60]. Then, following [6,8], we provided definitions and examples for the roles of “moral victims” and “moral transgressors” to participants in both experimental conditions. Moral transgressors were defined as “individuals whose intentions and actions bring about harmful events” and moral victims as “individuals who experience feelings and emotions brought about by the moral transgressor’s actions” [6]. We also informed participants that the same individual can be a moral transgressor or a moral victim at different times or even at the same time. We adapted the examples of moral transgressors and victims used by the authors in their study to better-fit nurses’ work environments and to reflect more severe moral transgressions. We operationalized the severity of moral transgressions by the magnitude of the harmful effects it had on the patient [61]. The transgressions used as examples were devised according to Brüggemann et al. [62].

“Laura is a nurse at a hospital in Romania. One morning during the 4th wave of the COVID-19 pandemic, she woke up feeling sick and tested herself for COVID-19 at home with three rapid tests. Although all three tests were positive, she went to work anyway, because she had the opportunity to work an extra shift and make more money. Patients and colleagues contracted the infection from her and several of them are still in the ICU, with reserved prognoses. Laura felt guilty and ashamed about the consequences of her action”.

Then, they were presented with a different example, which flipped the moral victim/transgressor roles of the first example:
“Laura is a nurse at a hospital in Romania. During the 4th wave of the COVID-19 pandemic, she unknowingly cared for a patient who was infected with COVID-19. The patient knew about the infection, but lied about it, taking advantage of the fact that patients were not tested before being committed. Laura, along with several other patients and colleagues, contracted COVID-19 from the patient, and she is now in the ICU, with a reserved prognosis. Laura felt betrayed and angered about the consequences of the patient’s action”.

Finally, we presented them with a definition of PMIEs: “events or action during which you felt as both a moral victim and a moral transgressor when you did or witnessed something you felt was morally wrong not because you wanted to, but because you felt as if you did not have a choice” [2,23]. We then followed with an example of PMIE reflecting an issue with which many nurses and healthcare providers in Romania were confronted during the 4th wave of the pandemic:

“Laura is a nurse at a hospital in Romania. During the 4th wave of the COVID-19 pandemic, the beds in the ICU were all occupied, and she had to care for a patient in the ER. The patient was rapidly deteriorating, and he badly needed access to a ventilator. None were available, and the necessary procedures for transferring the patient to another hospital were stalled due to bureaucracy issues. The patient’s oxygen saturation dropped quickly, and, despite Laura’s and the doctor’s best efforts, he died before the papers for the transfer were ready. Laura felt both guilty for not having saved the patient’s life and betrayed by the medical system which allowed for this to happen”.

All the examples presented to the participants referenced work-related situations in which the main actants were nurses and patients, both for equivalency between the two experimental conditions (episodic memory of SMT and episodic memory of PMIE) and to prepare our participants to recall memories central to their main work activity—caring for patients.

“Please describe a personal memory of a specific event related to your work during the COVID-19 pandemic in which you were a moral transgressor, as defined and exemplified above. Select a memory significant to you which is at least three-month-old, and which often comes to your mind. This memory should be of the most morally wrong thing you have done during the pandemic with harmful consequences for a patient. Describe in a general fashion what happened, where it happened, who you were with (if anyone), and how you and other people reacted. 

Please remember we are not interested in the identities of anybody involved, so feel free to use phrases such as a colleague, a boss’, ‘a patient’, and other generic denominators. What is important to us is for you to remember specific details, not for us to know them. Describe your role and what have been the consequences of your reaction or your actions during this event. Please provide enough details so that we can fully understand what happened as if you were telling a story to someone. We would also like to assure you that the content of your memories will not be shared with anybody outside of the two first authors and it will not be used in our analyses”.

Participants in the PMIE condition received the same instruction, with the first sentence modified as such: “Please describe a personal memory of a specific event related to your work during the COVID-19 pandemic in which you were both a moral transgressor and a moral victim, a PMIE, as defined and exemplified above”.

Appendix C. Outliers Treatment

To detect multivariate outliers, we employed Cook’s Distance Test [63], to evaluate the influence of outliers on the regression coefficients by measuring the change in parameter estimates when extreme cases are deleted. Usually, Cook’s values greater than one are considered influential and eliminated from the dataset [64]. A more restrictive criterion is eliminating the observations with a Cook’s distance over four times the mean [62,63]. With M = 0.00190 (SD = 0.01), the computed reference value for our model was 0.0076. We did not find any observation with a Cook’s value over 1. However, 28 observations exceeded the reference value, ranging from 0.139 to 0.007.

We excluded them from the analysis and ran the model again. We did not find differences in parameter and effect estimations compared to the model including the 28 cases (Tables A2 and A3), so we decided to keep the initial results (Tables 5 and 6), to retain the advantage of having a larger dataset. The model fit was slightly improved after removing the outliers (CFI = 1, TLI = 0.998, GFI = 1; AGFI = 1; SRMR = 0.019, RMSEA = 0.018, 95% CI [0.02; 0.05]; χ2(8) = 9.56, p = 0.297; χ2/df = 1.195). The R 2 values suggested that the model accounted for 12.2% of the variance in autonomy thwarting (R 2 = 0.122), 39%—in Work Motivation (R 2 = 0.390), 43.7%—in Burnout (R 2 = 0.437), 45.9%—in Moral Learning (R 2 = 0.459), 44.9%—in Work Satisfaction (R 2 = 0.449) and 71.2%—in Adaptive Performance (R 2 = 0.712).

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