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Record W4404017999 · doi:10.1097/nhh.0000000000001302

Reducing Violence Risk

2024· review· en· W4404017999 on OpenAlexaff
Paula Lambert

Bibliographic record

VenueHome Healthcare Now · 2024
Typereview
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsCARE Canada
Fundersnot available
KeywordsCaregiver burdenPsychological interventionHealth careHuman factors and ergonomicsNursingSuicide preventionOccupational safety and healthPsychologyPoison controlMedicineEnvironmental healthDementiaPolitical science

Abstract

fetched live from OpenAlex

An expanding body of literature suggests that informal caregiver burden is a growing issue that negatively impacts care recipients, informal caregivers, and formal care providers. Costs associated with informal caregiver burden include risk to the informal caregiver's physical, emotional, and psychological well-being and increased potential to perpetrate violence. By identifying interventions to support informal caregivers, home healthcare nurses can help decrease the risk of negative outcomes and reduce the burden on informal caregivers. This paper examines home healthcare nurses' role in helping reduce the impact of informal caregiver burden, thereby reducing the risk for violence. By prioritizing caregiver burden as a critical area of focus in reducing violence risk, home healthcare organizations and the nurses who work for them can help address gaps in care while also recognizing the informal caregivers' critical role in caring for their loved ones.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.088
GPT teacher head0.436
Teacher spread0.348 · 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 designOther design
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

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