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Record W6926357671 · doi:10.25384/sage.c.5199952

How a shared humanity model can improve provider well-being and client care: An evaluation of Fraser Health’s Trauma and Resiliency Informed Practice (TRIP) training program

2020· other· en· W6926357671 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSage Journals Data · 2020
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolism and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthBurnoutCompassion fatigueEmpathyCompassionTraining (meteorology)Service providerMental healthcareHealth care

Abstract

fetched live from OpenAlex

Stress in the healthcare sector is an important concern, with worrying trends in provider burnout, secondary traumatic stress, and lower mental health. Importantly, provider stress is also connected to patient care, with recent research on Canada’s opioid crisis finding that compassion satisfaction and burnout are linked to the perpetuation of negative attitudes and behaviours towards people with opioid use problems. In 2017, the Fraser Health Authority developed a training program for direct service providers designed to address this important connection—a mental health and resiliency program based in the principles of trauma-informed practice and care. This article reports the results of an evaluation of this program. Findings suggest that embedding resiliency and self-compassion within trauma-informed training programs is a promising approach for cultural change in healthcare practice. Leaders are encouraged to explore how such a model may be implementable for their own organizations and departments.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.902

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.071
GPT teacher head0.376
Teacher spread0.305 · 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