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Record W2993638946 · doi:10.7759/cureus.257

How, When and Where to Discuss Do Not Resuscitate: A Prospective Study to Compare the Perceptions and Preferences of Patients, Caregivers, and Health Care Providers in a Multidisciplinary Lung Cancer Clinic

2015· article· en· W2993638946 on OpenAlexaff
Naseer Ahmed, Michelle Lobchuk, William Hunter, Pam Johnston, Zoann Nugent, Ankur Sharma, Shahida Ahmed, Jeff Sisler

Bibliographic record

VenueCureus · 2015
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsMedicineMultidisciplinary approachDo not resuscitateDo Not Resuscitate OrderLung cancerFamily medicineProspective cohort studyCancerPerceptionHealth careIntensive care medicineNursingOncologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Do Not Resuscitate (DNR) is a significant but challenging part of end-of-life discussions when dealing with incurable lung cancer patients. We have explored the perceptions and preferences of patients, their caregivers (CGs), and health care providers (HCPs) and the current practice and opinions on DNR discussions in a multidisciplinary lung cancer clinic. MATERIALS AND METHODS: This is a prospective descriptive study with a mixed quantitative and qualitative methodology to capture perceptions of the participants. To obtain a rich description of participant responses to questionnaire items, we employed a 'think aloud' process that prompted participants to immediately verbalize their thoughts when responding to questionnaire items. We used content analysis and constant comparison techniques to identify, code and categorize primary themes in the captured data. RESULTS: Ten patients with advanced-stage lung cancer; nine CGs from the lung clinic and ten HCPs from the Thoracic Disease Site Group (DSG) were enrolled in the study. Most patients had only a limited understanding of DNR. Most CGs had a fair to good understanding of DNR. Most HCPs perceived their patients to have understood DNR most of the time. When patients were interviewed, a theme of "anticipated discussion" about DNR was identified. Patients and CGs expressed having faith in the system and responsible physicians as to when to discuss DNR. HCPs embraced a clinician preference-based decision-making approach to engaging in DNR discussions. They desired more resources, more knowledge, more structure and more time to discuss DNR. Most HCPs felt that it would be worth conducting a prospective clinical trial to determine the best time to discuss DNR. CONCLUSIONS: This pilot study provides a unique mixed quantitative and qualitative understanding of the perceptions of patients with lung cancer and their CGs and HCPs regarding DNR discussion. Our findings will help further the development of evidence-based guidelines and a broad prospective study that would have important implications for policies and practices around DNR discussions in order to reduce the emotional pain of dying patients, their CGs and HCPs.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.961

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 communication0.0000.000
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 head0.126
GPT teacher head0.444
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 designObservational
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

Citations12
Published2015
Admission routes1
Has abstractyes

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