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Record W4400291626 · doi:10.1080/01634372.2024.2373289

A Qualitative Study of Adult Protective Services Practitioners Responding to Allegations of Elder Abuse and Self-Neglect

2024· article· en· W4400291626 on OpenAlexafffund
Andie MacNeil, Erin Salvo, David Burnes

Bibliographic record

VenueJournal of Gerontological Social Work · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of CanadaAdministration for Community LivingU.S. Department of Health and Human Services
KeywordsNeglectElder abusePsychologyQualitative researchPsychiatryClinical psychologyMedicineMedical emergencySuicide preventionPoison controlSociology

Abstract

fetched live from OpenAlex

Adult Protective Services (APS) practitioners play an essential role in supporting older adults experiencing elder abuse and self-neglect (EASN), however, very little research has examined their experiences, from their perspectives. The purpose of this study was to examine the experiences of APS practitioners responding to allegations of EASN. Qualitative interviews were conducted with APS practitioners (n = 14) from the state of Maine. A descriptive phenomenological approach involving two independent assessors was used to code transcripts into themes. Two domains, each with various subthemes, were identified: (1) rewarding elements of role and (2) challenging aspects of role. The findings of this study emphasize how APS practitioners are motivated by their capacity to help elicit positive change in the lives of their clients and support the well-being of older adults experiencing EASN. However, APS practitioners must navigate numerous challenges and barriers in their role, including time constraints, high and complex caseloads, limited resources, and broader misconceptions on APS. These findings highlight the importance of addressing these stressors to support the well-being of APS practitioners, which, in turn, can help support the vulnerable older adults they serve.

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 score0.017
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.040
GPT teacher head0.404
Teacher spread0.364 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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