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Record W4297248779 · doi:10.1177/02692163221118204

<i>‘Mum, I think we might ring the ambulance, okay?’</i> A qualitative exploration of bereaved family members’ experiences of emergency ambulance care at the end of life

2022· article· en· W4297248779 on OpenAlexfundno aff
Natalie Anderson, Jackie Robinson, Hetty Goodwin, Merryn Gott

Bibliographic record

VenuePalliative Medicine · 2022
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsnot available
FundersNational Heart Foundation of New ZealandAuckland DHB Charitable TrustCancer Research Society
KeywordsMedicineContext (archaeology)Thematic analysisPalliative careEnd-of-life careAmbulance serviceQualitative researchMedical emergencyNursingEmergency medical servicesMajor trauma

Abstract

fetched live from OpenAlex

BACKGROUND: In the context of a sudden or unexpected event, people with a life-limiting illness and their family caregivers may be dependent on emergency ambulance services. AIM: To explore bereaved family members' experiences of emergency ambulance care at the end of life. DESIGN: A qualitative study using reflexive thematic analysis of data collected from semi-structured phone interviews. SETTING/PARTICIPANTS: A purposive sample of 38 family caregivers identified from a database of deaths in Aotearoa, New Zealand. RESULTS: Emergency ambulance personnel assist, inform and reassure patients and family caregivers managing distressing symptoms, falls, infections, unexpected events and death itself. Family members and patients are aware of the pressure on emergency services and sometimes hesitate to call an ambulance. Associating ambulances with unwanted transport to hospital is also a source of reluctance. CONCLUSIONS: The generalist palliative care provided by emergency ambulance personnel is a vital service for patients in the last year of life, and their caregivers. This must be acknowledged in palliative care policy and supported with training, specialist consultation and adequate resources.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.115
GPT teacher head0.412
Teacher spread0.297 · 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 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

Citations15
Published2022
Admission routes1
Has abstractyes

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