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Record W4402318553 · doi:10.3390/traumacare4030020

What Comes after Moral Injury?—Considerations of Post-Traumatic Growth

2024· article· en· W4402318553 on OpenAlexafffund
Tanzi D. Hoover, Gerlinde A. S. Metz

Bibliographic record

VenueTrauma Care · 2024
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMoral injuryPsychologyTraumatic brain injuryMedical emergencyMedicineSocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

Moral injury is a psychological wound resulting from deep-rooted traumatic experiences that corrode an individual’s sense of humanity, ethical compass, and internal value system. Whether through witnessing a tragic event, inflicting injury on others, or failing to prevent a traumatic injury upon others, moral injury can have severe and detrimental psychological and psychosomatic outcomes that may last a lifetime. Post-traumatic experiences do not have to be a permanent affliction, however. From moral injury can come post-traumatic growth—the recovery from trauma in which personal betterment overshadows moral injury. Moral injury may lead to substantial personal growth, improved capacity and resilience. Based on these observations, it seems that from struggles and darkness, there can be positivity and hope. This review will summarize the current concepts of post-traumatic growth and consider potential mechanisms leading to resilience and recovery through post-traumatic growth. These considerations are gaining more importance in light of a growing number of existential threats, such as violent conflicts, natural disasters and global pandemics.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0090.001

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 head0.062
GPT teacher head0.386
Teacher spread0.324 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations6
Published2024
Admission routes2
Has abstractyes

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