MétaCan
Menu
Back to cohort
Record W4413346166 · doi:10.1093/geront/gnaf184

“I know you didn’t want to stay”: emergency department conversations about disposition for people living with dementia

2025· article· en· W4413346166 on OpenAlexaboutno aff
Justine Seidenfeld, Matthew Tucker, Melissa Harris, Gemmae M. Fix, Nina Sperber, Susan N. Hastings

Bibliographic record

VenueThe Gerontologist · 2025
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsnot available
FundersNational Institute on AgingEmergency Medicine FoundationU.S. Department of Veterans Affairs
KeywordsDementiaDispositionEmergency departmentPsychologyMedicineNursingGerontologySocial psychologyDisease

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: When people living with dementia present to the emergency department (ED), the disposition decision-to admit them to the hospital or discharge them home-can be difficult for providers. However, little is known about current real-world practices in disposition conversations. RESEARCH DESIGN AND METHODS: This ethnographic study used direct observations of ED encounters with people living with dementia, their care partners, and ED providers at a Veteran Affairs facility in the Southeast United States. Follow-up interviews were conducted with patients and care partners. Interview guides and code book were informed by the Ottawa Decision Support Framework. Data were analyzed using the constant comparative method. RESULTS: Data were collected over 45 days, with 20 ED encounters, 18 follow-up interviews, and baseline surveys obtained. For the 20 Veteran participants living with dementia, all were male, mean age was 79.4, and 50% were Black or African American. Major themes included: (1) Disposition conversations had significant variation in depth and content, (2) patient and care partner participation varied with disposition, and (3) satisfaction was driven by alignment of disposition preferences. DISCUSSION AND IMPLICATIONS: Our study suggests that there are no consistent formats of disposition conversations for people living with dementia. Improving quality may be most needed when preferences are misaligned, and this should be identified early in the encounter.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score1.000

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 studies0.0010.000
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 head0.027
GPT teacher head0.368
Teacher spread0.341 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueThe GerontologistSame topicGeriatric Care and Nursing HomesFrench-language works237,207