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Record W4386997487 · doi:10.3390/ijerph20196812

Coping, Supports and Moral Injury: Spiritual Well-Being and Organizational Support Are Associated with Reduced Moral Injury in Canadian Healthcare Providers during the COVID-19 Pandemic

2023· article· en· W4386997487 on OpenAlexafffundabout
Andrea M. D’Alessandro-Lowe, Mauda Karram, Kim Ritchie, Andrea Brown, Heather Millman, Emily Sullo, Yuanxin Xue, Mina Pichtikova, Hugo J. Schielke, Ann Malain, Charlene O’Connor, Ruth A. Lanius, Randi E. McCabe, Margaret C. McKinnon

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2023
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsSt. Joseph’s Healthcare HamiltonLawson Health Research InstituteWestern UniversityHomewood Research InstituteUniversity of TorontoMcMaster UniversityTrent University
FundersCanadian Institutes of Health ResearchPublic Health Agency of CanadaAtlas Institute for Veterans and Families
KeywordsShameMoral injuryCoping (psychology)Mental healthSocial supportPsychologyClinical psychologyHealth carePopulationReligiosityPandemicPsychiatryMedicineSocial psychologyCoronavirus disease 2019 (COVID-19)Disease

Abstract

fetched live from OpenAlex

Healthcare providers (HCPs) have described the onset of shame- and trust-violation-related moral injuries (MI) throughout the COVID-19 pandemic. Previous research suggests that HCPs may turn to various coping methods and supports, such as spirituality/religiosity, substance use, friends/family or organizational support, to manage workplace stress. It remains unknown, however, if similar coping methods and supports are associated with MI among this population. We explored associations between MI (including the shame and trust-violation presentations individually) and coping methods and supports. Canadian HCPs completed an online survey about their mental health and experiences during the COVID-19 pandemic, including demographic indices (e.g., sex, age, mental health history) and measures of MI, organizational support, social support, spiritual well-being, self-compassion, alcohol use, cannabis use and childhood adversity. Three hierarchical multiple linear regressions were conducted to assess the associations between coping methods/supports and (i) MI, (ii) shame-related MI and (iii) trust-violation-related MI, when controlling for age, mental health history and childhood adversity. One hundred and seventy-six (N = 176) HCPs were included in the data analysis. Spiritual well-being and organizational support were each significantly associated with reduced total MI (p’s < 0.001), shame-related MI (p = 0.03 and p = 0.02, respectively) and trust-violation-related MI (p’s < 0.001). Notably, comparison of the standardized beta coefficients suggests that the association between trust-violation-related MI and both spiritual well-being and organizational support was more than twice as great as the associations between these variables and shame-related MI, emphasizing the importance of these supports and the trust-violation outcomes particularly. Mental health history (p = 0.02) and self-compassion (p = 0.01) were additionally related to shame-related MI only. Our findings indicate that heightened levels of spiritual well-being and organizational support were associated with reduced MI among HCPs during the COVID-19 pandemic. Rather than placing sole responsibility for mental health outcomes on HCPs individually, organizations can instead play a significant role in mitigating MI among staff by implementing evidence-informed organizational policies and interventions and by considering how supports for spiritual well-being may be implemented into existing models of care where relevant for employees.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.090
GPT teacher head0.427
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2023
Admission routes3
Has abstractyes

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