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Record W4389966897 · doi:10.1111/ijn.13224

Methodological and ethical challenges in designing and conducting research at the end of life: A systematic review of qualitative and textual evidence

2023· review· en· W4389966897 on OpenAlexafffund
Karolína Vlčková, Silvia Gonella, Laura Bavelaar, Gary Mitchell, Tamara Sussman

Bibliographic record

VenueInternational Journal of Nursing Practice · 2023
Typereview
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsMcGill University
FundersMinisterstvo Školství, Mládeže a TělovýchovyCanadian Institutes of Health ResearchEU Joint Programme – Neurodegenerative Disease ResearchZonMwAlzheimer's SocietyHealth Research Board
KeywordsEngineering ethicsSystematic reviewQualitative researchMEDLINESociologyPsychologyMedicineManagement scienceEngineeringPolitical scienceSocial scienceLaw

Abstract

fetched live from OpenAlex

AIM: This systematic review aims to identify methodological and ethical challenges in designing and conducting research at the end of life from the perspective of researchers and provide a set of recommendations. BACKGROUND: Conducting research with patients and family carers facing end-of-life issues is ethically and methodologically complex. DESIGN: A systematic review was conducted. DATA SOURCES: Four databases (MEDLINE, EMBASE, CINAHL, PsycInfo) were searched from inception until the end of 2021 in February 2022. REVIEW METHODS: The Preferred Reporting Items for Systematic Reviews was followed, and the JBI Approach to qualitative synthesis was used for analysis. RESULTS: Seventeen of 1983 studies met inclusion criteria. Data were distilled to six main themes. These included (1) the need for flexibility at all stages of the research process; (2) careful attention to timing; (3) sensitivity in approach; (4) the importance of stakeholder collaboration; (5) the need for unique researcher skills; and (6) the need to deal with the issue of missing data. CONCLUSION: The findings illuminate several considerations that can inform training programmes, ethical review processes and research designs when embarking on research in this field.

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)0.036
metaresearch head score (Gemma)0.255
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.219
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0360.255
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.976
GPT teacher head0.766
Teacher spread0.210 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

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

Citations1
Published2023
Admission routes2
Has abstractyes

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