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Record W2923830999 · doi:10.5430/jnep.v9n7p56

Dementia and elder abuse: Understanding public health nurses’ experiences

2019· article· en· W2923830999 on OpenAlexvenueno aff
Paris Cooke, Mary Rose Day, Helen Mulcahy

Bibliographic record

VenueJournal of Nursing Education and Practice · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsnot available
Fundersnot available
KeywordsSafeguardingElder abuseDementiaInterpretative phenomenological analysisPublic healthPopulationMedicinePsychologyGerontologyNursingQualitative researchSuicide preventionPoison controlSociologyMedical emergencyDiseaseEnvironmental health

Abstract

fetched live from OpenAlex

Elder abuse (EA) within the population of community dwelling older people living with dementia is significantly more prevalent when compared with the population of older adults without cognitive impairment. Public Health Nurses (PHNs) in Ireland are a key professional service provider group in safeguarding vulnerable populations. Interpretative Phenomenological Analysis (IPA) was utilized to explore the experiences of PHNs in identifying and addressing abuse, among community dwelling older adults living with dementia that was perpetrated by informal caregivers. Semi-structured interviews were conducted with PHNs (n = 5) in Ireland that had in the previous 12 months dealt with a case of elder abuse involving an older adult living with dementia. Analysis of the data revealed three super-ordinate themes; identifying hidden abusive relationships; Complexity – ‘where do I start’; and Isolation. This study provides unique insights from PHNs relevant to safeguarding this particularly vulnerable group. Specific implications for practice and recommendations are presented.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.414

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.177
GPT teacher head0.473
Teacher spread0.296 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2019
Admission routes1
Has abstractyes

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