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Record W2954512172 · doi:10.12927/hcq.2019.25840

How Do Older Adults Decide to Visit the Emergency Department? Patient and Caregiver Perspectives

2019· article· en· W2954512172 on OpenAlexaffvenue
Sharon Marr, Loretta M. Hillier, Diane Simpson, Sigrid Vinson, Sarah Goodwill, David Jewell

Bibliographic record

VenueHealthcare Quarterly · 2019
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsHamilton Regional Laboratory Medicine ProgramJuravinski HospitalHamilton Health Sciences
Fundersnot available
KeywordsEmergency departmentHealth careMedicineBest practiceFamily medicineMedical emergencyNursingPsychologyManagement

Abstract

fetched live from OpenAlex

Seniors account for a high number of emergency department (ED) visits, yet little is known about how they decide to visit the ED. This paper reports on the results of surveys completed by 264 seniors who visited the ED and their caregivers and interviews with a subset (N = 51) of survey respondents, aimed at understanding how they decide to visit the ED. Although older adults rely on others to help them decide whether to visit the ED, only a small proportion consult healthcare providers in doing so. Opportunities exist for enhancing seniors' decision-making process regarding ED visits and access to community-based healthcare to avoid ED visits.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.275
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2019
Admission routes2
Has abstractyes

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