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 2

3. Path 3: Moral Learning as the Main Mechanism

While we did not find support for the fact that memories of PMIEs can predict the increase in moral learning found for SMTs [7], we know that thwarted autonomy could impair learning from failures by leading to more controlled work motivation [10,14] (path b*c in Figure 1. 

Frustration is an inevitable part of life, and everyone will experience setbacks and disappointments as they grow up. However, how we deal with setbacks has a huge impact on our autonomy and memory.

First, frustration can enhance our autonomy. When we face challenges and difficulties, we need to pick ourselves up and solve problems in our own way. This experience can make us more confident and give us confidence in our ability to take control of our lives.

In addition, frustration can also promote memory development. When we overcome setbacks, we need to find ways to solve problems and learn from our mistakes. This process enhances our memory, allowing us to handle future challenges more effectively.

However, we need a positive attitude when facing setbacks. Instead of getting stuck in our frustrations and disappointments, we should learn from them and get rid of negative emotions. We should have confidence and confidence that we can overcome difficulties.

In summary, setbacks can enhance our autonomy and memory, but the key to success lies in how we handle them. We need to stay positive, look for solutions to problems, and learn from them. Through such efforts, we can become stronger and more confident to face any challenges in life. It can be seen that we need to improve our memory. Cistanche deserticola can significantly improve memory, because Cistanche deserticola can also regulate the balance of neurotransmitters, such as increasing the levels of acetylcholine and growth factors. These substances are very important for memory and learning. In addition, meat can also improve blood flow and promote oxygen delivery, which can ensure that the brain receives sufficient nutrients and energy, thus improving brain vitality and endurance.

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Thus, we hypothesized that the differences between memories of PMIEs and SMTs in autonomy thwarting and work motivation would lead to differences in moral learning (H4; path a*b*c in Figure 1). 

Given all the above and the fact that a higher number of upward counterfactuals without a moral valence increased adaptive performance [29] (path g in Figure 1), our seventh hypothesis was that the type of memory recall, autonomy thwarting, and work motivation should differentially affect adaptive performance through moral learning (H7; path a*b*c*g in Figure 1).

Overall, memories of PMIEs should impair adaptive performance more than recalling SMTs.

2. Materials and Methods

2.1. Sample

2.1.1. Participants Recruiting

We conducted an experimental study on a convenience sample of nurses working in hospitals across Romania during February 2022. The data was collected after the fourth wave of the COVID-19 pandemic had a catastrophic impact on the Romanian healthcare system, leading to a sharp increase in infection and mortality, with more than 500 daily deaths and close to 20,000 daily new cases, for a population of 19 million inhabitants [30]. Given the unpreparedness of the medical system to handle this crisis and based on past results obtained in previous waves in Romania [5], we expected that nurses in all health specialties may have been exposed to morally challenging work events, often amounting to PMIEs.

For this research, 608 nurses were contacted via e-mail and/or phone and invited to participate in our study. They were also asked to forward the invitation to fellow nurses meeting the criteria for inclusion in our study: having worked as a nurse during the COVID-19 pandemic in a hospital for more than 6 months. Phone numbers and addresses were collected for previous research conducted by the authors when participants consented to be contacted for future research. 

Out of the 608 nurses contacted, 590 confirmed their availability, and 106 nurses, invited by the participants, e-mailed or messaged us to confirm their willingness to participate as well. Upon randomization in the two experimental conditions (memories of PMIEs and SMTs), we sent all 696 participants online questionnaires created in Google Forms. We received 654 complete answers and eliminated 16 participants who failed the attention checks from both experimental conditions (10 from the SMT condition and 6 from the PMIE condition). Also, we excluded 24 participants from the PMIE condition who did not recall a PMIE, according to their answers on the Moral Injury Events Scale.

2.1.2. Final Sample Description

Our final sample included 614 nurses (85.3% identifying as female and 14.7% as male, with ages ranging from 21 to 57 years (M = 38.1, SD = 8.6) and with an overall work experience of M = 12.7 years (SD = 8.29). Concerning education, 91.2% of our participants had completed post-secondary studies, with 5% of them having completed bachelor’s studies and 3.7% having had a master’s degree. 

While all our participants worked in hospital settings, their specialties were diverse, with 13% working in Palliative Care, 12.7%—in Oncology, 10.5%—in Internal Medicine, 10.4%—in Surgery, 8.5%—in Emergency Rooms, 8.5%—in Neurology, 7%—in Psychiatry, 6.7% in Intensive Care Units, 6.4%—in Infectious Diseases, 6%—in Pneumology, 3.9%—in Obstetrics-Gynecology, 2.8%—in Hematology, 2.6%—in Gastroenterology, 1%—in Radiology and 0.2%—in Dentistry.

The final number of participants in the PMIE condition was 297. 

The final number of participants in the SMT condition was 317. To test our conceptual model, which estimated 37 parameters (Figure 1), a sufficient sample size would comprise 370 participants, according to the criteria of [31], who stated that the ideal goal for Structural Equation Modelling was to have a 20 to 1 ratio for the number of participants to the number of model parameters, but a ratio of 10 to 1 was acceptable if the sample size exceeded 200.

With 614 participants, our sample is closer to the ideal ratio (740) than to the acceptable ratio (370).

2.1.3. Ethics

Our research adhered to the ethical guidelines outlined in the Declaration of Helsinki and was approved by the ethics committee of our faculty. All participants were over 18 and were instructed about their voluntary involvement and data confidentiality concerns. Specifically, given the sensitive nature of the data requested (episodes of severe past moral violations at their workplace), we assured participants that their anonymity would be kept and none of their data would be made public or shared with anyone other than the two main investigators (i.e., the first two authors). 

We adopted this policy due to our participants raising issues that they may face drastic consequences if their identities were discernable. The data collected was securely stored by the two first authors for statistical analysis. As a reward for their participation, five cash prizes of 100 RON were offered through a draw.

2.2. Procedure and Instruments

Data was collected with an online survey which comprised, in order, the following: informed consent, socio-demographic information, experimental task (presented in detail in Appendix A), the Moral Injury Events Scale, three items for manipulation check, two items to assess the autonomy thwarting component of their memories, two items assessing the personal importance and centrality of the memories to the self, one item to assess moral learning, the Work Extrinsic and Intrinsic Motivation Scale, the Adapted Satisfaction with Life Scale, the Emotional Exhaustion sub-scale of the Maslach Burnout Inventory, the Adaptive Performance Scale and an attention check.

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 [29,32]. 

Then, following [6,8], we presented all participants with definitions and examples for the roles of “moral victims”, “moral transgressors”, and for PMIEs. Participants in the SMT condition recalled and described a work event during which they felt like moral transgressors which occurred during the COVID-19 pandemic, while participants in the PMIE condition recounted an event during which they felt like both moral victims and transgressors from the same period. For more details on the experimental procedure, please see Appendix A.

Then, we administered the 9-item Moral Injury Events Scale (MIES) modified to assess PMIEs among healthcare workers during the COVID-19 pandemic [33] (e.g., “I acted in a way that violated my moral code or values in this instance”). 

The scale was tested and used on Romanian healthcare workers [5]. Answers ranged from 1—“Strongly Agree” to 6—“Strongly Disagree”. To assess whether memories were perceived as PMIEs, we dichotomized the total scores, with responses of “Moderately Agree” to “Strongly Agree” on any of the 9 items coded as exposure to a PMIE [33], excluding participants not recalling PMIEs.

All participants were asked to provide their moral judgment on the events recalled (“How morally wrong was your behavior in this instance?”), from 1—“Slightly Morally Wrong” to 7—“Very Morally Wrong” [7]. As a manipulation check, we asked participants to what extent they perceived themselves as moral victims and transgressors in those situations. Answers to the two items ranging from 1—“Not at All” to 7—“Very Much”.

The autonomy thwarting component of their memories was assessed with two items (e.g., “I felt free to do things and to think how I wanted”), with answers ranging from −3—“Strongly Disagree” to 3—“Strongly Agree”, and 0-“Do Not Agree nor Disagree/Not Applicable”. To reflect need thwarting, items were reversed, and scores were averaged [11,12]. The scale's internal consistency was good (Cronbach’s alpha = 0.817). The Alpha Cronbach value found by Philippe et al. [11] was 0.84.

We measured with one item each the personal importance and centrality of the events to the self [8,13]: “How important is the event to you personally (it involves an important episode in your life)?” 1—” Not at All Important” to 7—“Very important”; “Is the event in your memory a central part of your life story?” 1—“Not at All Central” to 7—“Very Central”. Other phenomenological characteristics of the irrelevant memories were assessed, but not analyzed here.

Moral learning was measured as the frequency of morally upward counterfactual thinking [7], with the question: “Since it happened, how often have you thought about or talked about morally better ways in which you could have acted?” (1-“Never” to 7- “Very Often”).

Self-determined work motivation was assessed with the Work Extrinsic and Intrinsic Motivation Scale (WEIMS) [34]. The scale evaluates six types of motivation with three items each, reflecting the continuum of self-determination: intrinsic motivation (e.g., “Because I derive much pleasure from learning new things.”), integrated regulation (e.g., “Because it has become a fundamental part of who I am.”), identified regulation (e.g., “Because this is the type of work, I chose to do to attain a certain lifestyle.”), introjected regulation (e.g., “Because I want to succeed at this job, if not I would be very ashamed of myself.”), external regulation (e.g., “Because this type of work provides me with security.”) and motivation (e.g., “I don’t know why, we are provided with unrealistic working conditions.”). 

Answers to items range from 1-“Does Not Correspond at All” to 7-“Corresponds Exactly”. The reliability of the sub-scales was acceptable, with Cronbach’s alpha coefficients greater than 0.7 (0.935 for intrinsic motivation, 0.819 for integrated motivation, 0.771 for identified motivation, 0.848 for introjected motivation, 0.808 for external motivation, and 0.960 for motivation). The Alpha Cronbach’s values found by [34] were 0.80 for intrinsic motivation, 0.83 for integrated motivation, 0.67 for identified motivation, 0.70 for introjected motivation, 0.77 for external motivation, and 0.64 for motivation. 

By SDT [10] and with SDT research [11], we computed the final scores with the following weighting procedure: (intrinsic × 3) + (integrated × 2) + (identified × 1) − (introjected × 1) − (external × 2) − (motivation × 3). Higher scores reflected more self-determined work motivation, while lower scores − more controlled work motivation. Instrument reliability was also acceptable, with a Cronbach’s alpha of 0.841, very similar to the one found by Tremblay et al. [34], of 0.84.

Work satisfaction was measured with the 5-item Adapted Satisfaction with Life Scale [35,36], (e.g., “I am satisfied with the type of work I do.”), with individual answers ranging from 1-“Strongly Disagree” to 7-“Strongly Agree”. Reliability was good (Cronbach’s alpha = 0.879). The Cronbach’s Alpha coefficient value found by Bérubé et al. [35] was 0.87. Higher total scores indicated greater work satisfaction.

Burnout was assessed with the 8-item Emotional Exhaustion sub-scale of the Maslach Burnout Inventory [37], (e.g., “I feel emotionally drained from my work.”) with answers from 0-“Never” to 6-“Every Day”, adapted for Romanian healthcare providers, with a Cronbach’s alpha of 0.88 [38]. High scores indicate higher burnout. The reliability was good (Cronbach’s alpha = 0.927).

Adaptive performance was measured with the 19-item scale developed by CharbonnierVoirin and Roussel [39] (e.g., “I develop new tools and methods to resolve new problems”), with responses from 1-“Strongly Agree” to 7-“Strongly Disagree”. 

Higher total scores indicated higher adaptive performance. The scale was reliable according to the Cronbach’s alpha of 0.946 we computed, greater than the ones obtained by Charbonnier-Voirin and Roussel [39] on their two different samples: 0.84 and, respectively, 0.88.

We employed the attention check used by Stanley et al. [7]: “Do you feel that you paid attention, avoided distractions, and took the survey seriously? Participants were assured that their answers would not affect their participation and prize draw or their opportunity to participate in future studies and they were asked to choose from among one of the following: 1-“No, I was distracted”; 2-“No, I had trouble paying attention”; 3-“No, I did not take this study seriously”; 4-“No, something else effected my participation negatively”; 5-“Yes”. Only participants who selected “5” were included in our analysis.

2.3. Data Analyses Strategy

Data analyses were conducted in Jamovi 2 (The Jamovi group, Sydney, Australia) and R (R Core Team, Vienna, Austria). To test our model (Figure 1), we employed path analysis, a subset of Structural Equation Modelling used to estimate and assess direct, indirect, and mediation relationships between variables [31]. 

Path analyses simultaneously run sets of regression equations to determine parameter estimates and model fit. The most commonly employed estimation method is Maximum Likelihood (ML), but its estimated standard errors are less reliable when the model includes non-normally distributed, ordinal (moral learning, in our model), or categorical variables (experimental condition, in our model) [40]. 

The distributions of our endogenous variables departed significantly from normality (adaptive performance: W = 0.99, p = 0.004; burnout: W = 0.98, p < 0.001; work satisfaction: W = 0.99, p < 0.001; work motivation: W = 0.99, p < 0.001; autonomy: W = 0.95, p < 0.001). The diagonally weighted least-squares estimation method (DWLS, or robust WLS) generates more accurate results for ordinal, categorical, and/or non-normally distributed variables (e.g., [40]), which is why we employed it using lavaan [41]. 

The DWLS method does not require large samples, with 200–300 participants sufficing for accurate assessments (e.g., [40]). With 614 participants and 37 estimated parameters, employing the DWLS method further enhanced the accuracy of parameter estimation for our data. Other hypotheses were explored with Pearson correlations, Independent Samples t-tests, and General Linear Models.

3. Results

We checked our experimental manipulation and tested whether memories of PMIEs and memories of SMTs differed in terms of moral severity, perceived moral transgressor status, and perceived moral victim status, as judged by the participants. Our results showed that there were no significant differences between the perceived moral severity of the recalled PMIEs (M = 5.58, SD = 1.11) and recalled SMTs (M = 5.51, SD = 1.14), t(612) = −0.67, p = 0.499, Cohen’s d = 0.054, 95% CI [−0.10; 0.21]. 

Also, there were no significant differences in perceived moral transgressor status between the participants who recalled PMIEs (M = 5.55, SD = 1.11) and the ones who recalled SMTs (M = 5.51, SD = 1.14), t(612) = −0.343, p = 0.732, Cohen’s d = −0.028, 95% CI [−0.19; 0.13]. Participants who recalled PMIEs perceived themselves as having higher moral victim status (M = 4.99, SD = 1.47) than those who recalled SMTs (M = 2.02, SD = 0.83): Welch’s t(459) = −30.6, p < 0.001, Cohen’s d = −2.49. These results supported the equivalence between the two experimental groups in terms of perceived moral severity.

3.1. Socio-Demographic Differences

To assess whether nurses’ burnout, work satisfaction, thwarted autonomy, moral learning, work motivation, and adaptive performance varied with age, experience, gender, and education, we ran Pearson’s correlations, Independent Samples t-tests, and One-way ANOVAs.

Age and Work Experience. Participants’ age was positively correlated with autonomy thwarting, burnout, and work experience: the older our participants were, the more they felt their autonomy thwarted during the experiences recalled and the more work experience they had (Table 1). 

Negative correlations with participants’ age were found for work motivation, work satisfaction, and adaptive performance: the younger the nurses, the more self-determined their motivation, and the higher their work satisfaction and their adaptive performance.

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