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Record W2002094918 · doi:10.12968/ijpn.2009.15.2.39804

The meaning of Friday afternoon tea for informal caregivers on a palliative care unit

2009· article· en· W2002094918 on OpenAlexaboutno aff
Sheila Parsons, Colleen Anderson

Bibliographic record

VenueInternational Journal of Palliative Nursing · 2009
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPalliative careMeaning (existential)Thematic analysisIntervention (counseling)NursingUnit (ring theory)DistressParticipant observationEthnographyNarrativePsychologyMedicineQualitative researchSociologyPsychotherapist

Abstract

fetched live from OpenAlex

PURPOSE: This study was carried out to determine the meaning of an established intervention called 'Friday afternoon tea' for family members and patients on a palliative care unit. METHOD: A mini-ethnographic study was undertaken in a rural hospital in Newfoundland, Canada, to explore the meaning of 'Friday afternoon tea' as a sub-culture of the palliative care unit. Data were collected using semi-structured, audio-taped interviews with eight family members whose loved ones were receiving end-of-life or symptom management treatment. Data collection also included participant observation and field notes. Thematic analysis of the narratives revealed three themes: more than a cup of tea, a welcomed distraction, and caring and comfort. DISCUSSION AND CONCLUSION: The degree of distress experienced by family members reinforced the importance of the type of supportive intervention that 'Friday afternoon tea' provides. It was found that this bedside care provided additional opportunities for social interaction for family caregivers. This study contributes to evidence-based knowledge concerning the benefits of a cost-effective intervention which can easily be replicated by other palliative care units. This study acknowledges the importance of healthcare team members carrying out informal social initiatives.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.351
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.102
GPT teacher head0.444
Teacher spread0.342 · 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 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

Citations7
Published2009
Admission routes1
Has abstractyes

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