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Record W2098320024 · doi:10.1177/1074840712462065

Supporting Rural Family Palliative Caregivers

2012· article· en· W2098320024 on OpenAlexaff
Carole A. Robinson, Barbara Pesut, Joan L. Bottorff

Bibliographic record

VenueJournal of Family Nursing · 2012
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsPalliative careNursingPsychologyMedicine

Abstract

fetched live from OpenAlex

There is urgent need to effectively support the well-being of rural palliative family caregivers (FCGs). A mixed method study was conducted with 23 FCGs. Data collection included completion of an assessment questionnaire and semistructured interviews. The most prevalent needs identified by questionnaire were caring for the patient's pain, fatigue, body, and nourishment; FCG's fatigue and need for respite. Yet few FCGs wanted more attention to these needs by healthcare providers. FCGs resisted considering their own personal needs. Instead, they focused on needs related to providing care including to be(come) a palliative caregiver, be skilled and know more, navigate competing wishes, needs, demands, and priorities, and for "an extra pair of hands." Gaps in rural palliative services contributed to low expectations for assistance; reluctance to seek assistance was influenced by FCGs' resourcefulness and independence. Findings suggest that supporting FCGs will most likely be successful when framed in relation to their caregiving role.

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)0.005
metaresearch head score (Gemma)0.014
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 score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.147
GPT teacher head0.459
Teacher spread0.312 · 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

Citations45
Published2012
Admission routes1
Has abstractyes

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