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Record W3108841484 · doi:10.1891/crnr-d-19-00086

“Compassion Fatigue” is a Misnomer: How Compassion Can Increase Quality of Life

2020· article· en· W3108841484 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCreative Nursing · 2020
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsCARE Canada
Fundersnot available
KeywordsMindfulnessCompassion fatiguePsychologyEmpathyMisnomerCompassionDistressMental healthQuality of life (healthcare)BurnoutHealth carePsychotherapistClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

Health-care workers are at risk of experiencing negative consequences for their own health and job performance due to a wide variety of stressors. Care providers suffer from varying expressions of a generalized symptom set that has been termed "burnout" or "compassion fatigue." These terms can help us understand the phenomenon that is happening in our health system, but a strong understanding of the physical, mental, emotional, and psychological implications will increase the efficacy of treatment and benefit of preventive care. This article asserts that the term "compassion fatigue" is a misnomer, resulting in a misunderstanding of the causes and effects of compassion on the individual. This article challenges the term, positing that it has become outdated based on what we now know about the neuroscience of compassion, empathy, and mindfulness. Instead, this discussion offers the relevance of the term "empathic distress leading to empathic distress fatigue," suggesting that contemplative practice, mindfulness, and compassion training can protect and empower health-care providers.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.751
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.000

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 head0.170
GPT teacher head0.412
Teacher spread0.242 · 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