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Record W4404412439 · doi:10.1177/09697330241299536

Associations between self-compassion and moral injury among healthcare workers: A cross-sectional study

2024· article· en· W4404412439 on OpenAlexafffundabout
Mahée Gilbert‐Ouimet, Azita Zahiri Harsini, L Y Lam, Manon Truchon

Bibliographic record

VenueNursing Ethics · 2024
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversité LavalThe Quebec Population Health Research NetworkUniversité du Québec à Rimouski
FundersMinistère de la Défense Nationale
KeywordsSelf-compassionMoral injuryEmpathyPsychologyMindfulnessHealth careCross-sectional studyContext (archaeology)CompassionClinical psychologyMedicineSocial psychology

Abstract

fetched live from OpenAlex

Background Healthcare workers (HCWs) can face situations that conflict with their moral beliefs, leading to moral injury, an adverse psychological consequence that was more frequent during the COVID-19 pandemic. Self-compassion is a potential coping mechanism for moral injury by encouraging acceptance of human limitations and suffering. Objectives This study aimed to examine the associations between self-compassion components and moral injury prevalence among HCWs in Quebec, Canada, during the COVID-19 pandemic. Research design A cross-sectional study design was employed. Participants : and research context: The sample of this study consisted of HCWs and leaders from the Quebec province. Participants completed validated self-administered questionnaires assessing both positive and negative self-compassion components (self-kindness vs self-judgment; common humanity vs isolation; and mindfulness vs overidentification) and moral injury dimensions (self-oriented and other-oriented). Prevalence ratios (PRs) and 95% confidence intervals (CIs) for the associations between self-compassion components and moral injury dimensions were modeled using Poison robust regressions. The models were adjusted for various covariates, including sex, age, gender, and socio-demographic and lifestyle factors. Ethical considerations Ethical approval for this study was obtained from the ethics committee of the Centre intégré universitaire de santé et de services sociaux de la Capitale-Nationale in Quebec, Canada. All participants provided written informed consent prior to participating in the study. Additionally, permission was sought and obtained from the original authors of the tools used in this study, including the self-compassion and moral injury scales. Results The study involved 572 HCWs (60.5% nurses) and leaders. Around half of the participants (50.70%) exhibited moderate levels of self-compassion, while the prevalence of low levels of self-compassion ranged from 21.68% to 48.08% for the positive subscales and from 23.78% to 44.41% for the negative subscales. Regarding moral injury, 10.14% of participants reported moderate to high self-oriented moral injury, 29.19% reported moderate to high other-oriented moral injury, and 13.81% demonstrated moderate to high total moral injury. Higher self-compassion levels were associated with lower moral injury prevalence. HCWs with high self-compassion had a 93% lower likelihood of experiencing moral injury (PR: 0.07, 95% CI: 0.03–0.19). Self-kindness demonstrated the strongest association with reduced moral injury (PR: 0.24, 95% CI: 0.11–0.52), followed by mindfulness (PR: 0.37, 95% CI: 0.18–0.75). However, common humanity did not show a statistically significant association with moral injury prevalence. Conclusion These findings suggest a potential association between self-compassion and reduced prevalence of moral injury among HCWs, highlighting promising interventions to manage moral injury during crises. Such initiatives could promote the mental wellbeing of HCWs and preventing the negative consequences of moral injury, including anxiety, depression, and burnout.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.035
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.284
GPT teacher head0.557
Teacher spread0.273 · 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 teacher head, 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

Citations7
Published2024
Admission routes3
Has abstractyes

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