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Record W2328857448 · doi:10.1017/idm.2014.40

Perceived injustice contributes to poor rehabilitation outcomes in individuals who have sustained workplace injuries

2014· article· en· W2328857448 on OpenAlexaff
Heather Adams

Bibliographic record

VenueInternational Journal of Disability Management · 2014
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsInjusticePsychologyDistressEmotional distressRehabilitationIntervention (counseling)Presentation (obstetrics)PerceptionEconomic JusticeMedicineNursingSocial psychologyClinical psychologyPsychiatryPolitical scienceAnxiety

Abstract

fetched live from OpenAlex

The experience of unnecessary suffering as a result of another's actions or the experience of irreparable losses are likely to give rise to perceptions of injustice. Until recently, little systematic research had been conducted on the effects of perceptions of injustice on recovery outcomes following injury. It is now becoming clear that justice-related appraisals can have a dramatic impact on the physical and emotional consequences of injury. High levels of perceived injustice have been associated with more severe pain, more severe emotional distress, and more pronounced disability. Research has also pointed to multiple sources of a client's perceptions of injustice including, the person responsible for the accident, the insurance representative, as well as the health care provider. This presentation will summarize what is currently known about the relation between perceived injustice and recovery outcomes. The presentation will also address the processes by which perceptions of injustice might contribute to adverse health and mental health outcomes consequent to injury. Implications for prevention and intervention will be discussed.

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)0.006
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.443
Teacher spread0.419 · 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.

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

Citations0
Published2014
Admission routes1
Has abstractyes

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