The psychological impact of moral decision making during COVID-19.
Bibliographic record
Abstract
The objectives of the current study are to examine traits and situational factors that lead some individuals to experience distress as a result of the moral stressors faced during the current COVID-19 pandemic. There are two goals for this project. Objective 1: Given that many individuals are currently experiencing heightened moral stressors as a result of COVID-19, our first goal is to examine the degree to which individuals are currently experiencing moral distress from such experiences during the COVID-19 pandemic. Objective 2: The second goal of this study is to examine predictors of distress arising from these potentially morally injurious experiences. Specifically we want to examine if mental health outcomes (i.e., depression and PTSD) are predicted by a) self-reported tendencies to experience guilt, shame, anger, anxiety, religiosity, and sense of duty and b) the degree of exposure to COVID-related moral stressors and current distress arising from these moral stressors. This research will be important in understanding the degree to which moral injury could potentially be experienced in the general population, as to date it has mostly been studied in the military context, and to develop a better understanding of the causes and consequences of experiencing moral stressors. During the current COVID-19 pandemic many individuals will face difficult moral decisions. Individuals must choose whether or not to social distance and/or to self-isolate; policy makers must choose between forcing businesses to shut down and causing economic hardship or limiting the spread of the pandemic virus, business owners may have to make decisions about which employees to keep and which ones to let go, physicians may have to make the difficult decision as to which patient receives a ventilator or which patients do not. In many of these situations, these decisions and associated outcomes may be ambiguous and morally challenging. Such decisions have been highlighted in the media, from public outrage at snowbirds refusing to self-isolate after returning from the United States (Cotnam, 2020) to personal experiences faced by physicians in Italy who have to decide which patients will get a ventilator (Mortillaro, 2020). Such types of events resemble potentially morally injurious events (PMIEs), defined as experiences associated with the perpetration, failure to prevent, witnessing of, or learning about acts that transgress deeply held moral beliefs and expectations (Litz et al., 2009), as well as instances of betrayal of what is “right” by an authority figure in a high-stakes situation (Shay, 2014). PMIEs and their moral injury outcomes (MIOs) have mostly been studied in the context of military mental health. Relatively little is known about the impact of PMIEs in civilian populations. Outcomes of PMIEs: In studies of veterans and military personnel, outcomes as a result of PMIEs, referred to as moral injury outcomes (MIOs) include significant psychological and social distress and dysfunction including increased risk of psychopathology, suicide, and substance use (Griffin et al., 2019; Houle et al., 2020; Maguen et al., 2012; Maguen & Burkman, 2013; Nazarov et al., 2018). In one qualitative study of interviews with treatment seeking Canadian Armed Forces members and veterans, exposure to PMIEs resulted significant disruptions in identity and interpersonal relatedness, spirituality, significant rumination, and internalizing and externalizing emotions (Houle et al., 2020). In another Canadian study, exposure to PMIEs increased the risk of developing depression and PTSD (Nazarov et al., 2018). Risk Factors of PMIES: Models of MIO (e.g., Litz et al., 2009) propose that traits such as shame proneness and a rigid moral code will increase the likelihood of experiencing MIOs. Additionally, researchers suggest that exposure to more serious moral stressors will increase the likelihood of experiencing MIOs (Litz & Kerig, 2019). Finally, researchers have emphasized that not all PMIEs will result in MIOs (Griffin et al., 2019), and that it is the appraisals and distress of the PMIE that lead to negative psychological impacts (Griffin et al., 2019; Litz et al., 2009). However, little research has examined these assertions empirically.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".