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Record W7143711674 · doi:10.20569/00005850

在宅で看取りの実現に至った家族の思い ―意思決定の背景に焦点をあてて―

2021· article· ja· W7143711674 on OpenAlexaboutno aff
Naoko Kita, Yoriko Nakamura

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2021
Typearticle
Languageja
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsInterviewQuarter (Canadian coin)Family memberImmediate familyFamily lifePatient care

Abstract

fetched live from OpenAlex

Objective: To ascertain the thoughts of families that chose and realized end-of-life care at home based on events that occurred to the families until the realization of such care and thoughts related to such events. Methods: We conducted semi-structured interviews of family members (primary caregivers) who had played a central role in end-of-life care at home after the cessation of home care for the patient and lost the patient one year before the interview. We then analyzed the data qualitatively and inductively. Results: On interviewing eight family members involved in seven cases, one core category and five other categories were identified. The thoughts of the families that realized end-of-life care at home represented a culmination reflecting family members' thoughts with regard to the end-of-life care, the time that the family had spent together with the patient, the history built together, and the bond between the patient and family members. Thus, the core category was “end-of-life care was possible because the family worked together.” Conclusion: The results suggest that the participants decided to select the patient's home as the place for end-oflife care because they believed that it was the appropriate place for the patient to receive medical care while helping him/her live his/her life as he/she wishes and for the family members to spend time together with the patient until the patient's final moments.

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)0.004
metaresearch head score (Gemma)0.010
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 score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.002

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 head0.014
GPT teacher head0.233
Teacher spread0.219 · 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
Published2021
Admission routes1
Has abstractyes

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