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Record W2890563765 · doi:10.1097/njh.0000000000000463

Exploration of Families’ Experiences Caring for Loved Ones With Advanced Ovarian Cancer

2018· article· en· W2890563765 on OpenAlexaff
Kalli Stilos, Margaret I. Fitch, Amy Nolen, Tracey DasGupta, Marilyn Sapsford, Alison McAndrew, Shari Moura

Bibliographic record

VenueJournal of Hospice and Palliative Nursing · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsCancer Care OntarioSunnybrook Health Science Centre
Fundersnot available
KeywordsFamily caregiversDiseaseOvarian cancerMedicinePsychologyTurning pointEmotional supportCancerGerontologySocial supportPsychotherapistInternal medicine

Abstract

fetched live from OpenAlex

Ovarian cancer is challenging, both physically and psychologically, because of the advanced nature of the disease at diagnosis, adverse effects of the disease and treatment, and impact on roles and responsibilities. The family plays an integral role in promoting and maintaining the health of family caregivers, as well as providing physical and emotional support. The purpose of this study was to explore the experience of family caregivers caring for their loved ones with advanced ovarian cancer. Thirteen family caregivers were interviewed. The analysis of the data revealed 4 significant challenges that characterized the caregiving experience over time: confronting the initial diagnosis, dealing with fluctuations in physical status, confronting a turning point, and facing decline and death. Woven throughout these challenges, family caregivers routinely described difficulties in accessing information and navigating the health care system, which caused them added concern and frustration.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.262

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.056
GPT teacher head0.373
Teacher spread0.318 · 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

Citations8
Published2018
Admission routes1
Has abstractyes

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