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Record W2891917194 · doi:10.1177/2333721418801373

At Risk for Emotional Harm in the Emergency Department: Older Adult Patients’ and Caregivers’ Experiences, Strategies, and Recommendations

2018· article· en· W2891917194 on OpenAlexafffund
Donna Goodridge, Steven Martyniuk, James Stempien

Bibliographic record

VenueGerontology and Geriatric Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsUniversity of Saskatchewan
FundersRoyal College of Emergency MedicineUniversity of Saskatchewan
KeywordsEmergency departmentFocus groupHarmMedicineComplaintHealth careGerontologyPopulationNursingPsychologyFamily medicineSocial psychology

Abstract

fetched live from OpenAlex

Background: Emergency departments (ED) serve a critical role in addressing the health care needs of older adults, although organizational and provider characteristics can result in unintended negative outcomes for this population, such as emotional harm. This study aimed to describe the patient experience of older adults in the ED and generate recommendations for enhancing their experience. Methods: Data from focus groups and individual interviews of older adults and caregivers who had visited the ED were thematically analyzed. Results: Ten focus groups and individual interviews of 41 older adults and 15 caregivers were conducted. Health system and provider factors affecting the patient experience were identified. Participants negotiated their experience using diverse strategies. Recommendations for improving the ED experience were generated. Conclusions: Older adults attending the ED are at risk for health care-related emotional harm unrelated to their entrance complaint, which could be mitigated by addressing organizational and attitudinal factors.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.457

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)0.0000.000

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 head0.023
GPT teacher head0.310
Teacher spread0.287 · 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 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

Citations16
Published2018
Admission routes2
Has abstractyes

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