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Record W4415219154 · doi:10.1155/jare/8896040

The Experiences and Expectations of Older Adults and Close Family in Nursing Home and Emergency Department Transitions: A Qualitative Study

2025· article· en· W4415219154 on OpenAlexaff
Elin Høyvik, Malcolm Doupe, Gudmund Ågotnes, Frode F. Jacobsen

Bibliographic record

VenueJournal of Aging Research · 2025
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of Manitoba
FundersNorges Forskningsråd
KeywordsEmergency departmentQualitative researchNursing homesHealth careFamily caregiversMEDLINEFamily health

Abstract

fetched live from OpenAlex

Aim: To identify the experiences, expectations, and preferred transitional care expressed by nursing home residents and close family, thus mapping perceived barriers and facilitators to improve this identification process. Design: In this study, a qualitative design was employed. Methods: Individual, semistructured interviews were conducted. Data Sources: Interviews of 12 participants (3 residents and 9 close family) were conducted. The data were analyzed using thematic analysis to identify underlying themes. Results: The following three themes were identified: (1) changes in life situations, (2) dimensions of transfer quality, and (3) interactions with staff. Conclusion: Nursing home residents and close family emphasize that proper medical care is necessary. However, this is insufficient without addressing multiple ongoing life changes of individuals transitioning between nursing homes and emergency departments. Yet, this effort to manage life changes is significantly insufficient without the support of healthcare professionals.

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)0.009
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0030.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.542
Teacher spread0.474 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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