MétaCan
Menu
Back to cohort
Record W2376328541 · doi:10.4103/2347-5625.164999

Achieving Excellence in Palliative Care: Perspectives of Health Care Professionals

2015· review· en· W2376328541 on OpenAlexaff
Margaret I. Fitch, Tracey DasGupta, Bill Ford

Bibliographic record

VenueAsia-Pacific Journal of Oncology Nursing · 2015
Typereview
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsPalliative careDebriefingNursingExcellenceFocus groupEnd-of-life careHealth careMedicinePsychologyMedical education

Abstract

fetched live from OpenAlex

Caring for individuals at the end of life in the hospital environment is a challenging proposition. Understanding the challenges to provide quality end of life care is an important first step in order to develop appropriate approaches to support and educate staff members and facilitate their capacity remaining "caring." Four studies were undertaken at our facility to increase our understanding about the challenges health professionals experience in caring for patients at end of life and how staff members could be supported in providing care to patients and families: (1) In-depth interviews were used with cancer nurses (n = 30) to explore the challenges talking about death and dying with patients and families; (2) Surveys were used with nurses (n = 27) and radiation therapists (n = 30) to measure quality of work life; (3) and interprofessional focus groups were used to explore what it means "to care" (five groups held); and (4) interprofessional focus groups were held to understand what "support strategies for staff" ought to look like (six groups held). In all cases, staff members confirmed that interactions concerning death and dying are challenging. Lack of preparation (knowledge and skill in palliative care) and lack of support from managers and colleagues are significant barriers. Key strategies staff members thought would be helpful included: (1) Ensuring all team members were communicating and following the same plan of care, (2) providing skill-based education on palliative care, and (3) facilitating "debriefing" opportunities (either one-on-one or in a group). For staff to be able to continue caring for patients at the end of life with compassion and sensitivity, they need to be adequately prepared and supported appropriately. Caring for individuals at the end of life in the hospital environment is a challenging proposition. Understanding the challenges to provide quality end of life care is an important first step in order to develop appropriate approaches to support and educate staff members and facilitate their capacity remaining "caring." Four studies were undertaken at our facility to increase our understanding about the challenges health professionals experience in caring for patients at end of life and how staff members could be supported in providing care to patients and families: (1) In-depth interviews were used with cancer nurses (n = 30) to explore the challenges talking about death and dying with patients and families; (2) Surveys were used with nurses (n = 27) and radiation therapists (n = 30) to measure quality of work life; (3) and interprofessional focus groups were used to explore what it means "to care" (five groups held); and (4) interprofessional focus groups were held to understand what "support strategies for staff" ought to look like (six groups held). In all cases, staff members confirmed that interactions concerning death and dying are challenging. Lack of preparation (knowledge and skill in palliative care) and lack of support from managers and colleagues are significant barriers. Key strategies staff members thought would be helpful included: (1) Ensuring all team members were communicating and following the same plan of care, (2) providing skill-based education on palliative care, and (3) facilitating "debriefing" opportunities (either one-on-one or in a group). For staff to be able to continue caring for patients at the end of life with compassion and sensitivity, they need to be adequately prepared and supported appropriately.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.792
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.234
GPT teacher head0.555
Teacher spread0.321 · 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.

Study designOther design
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

Citations15
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueAsia-Pacific Journal of Oncology NursingSame topicPalliative Care and End-of-Life IssuesFrench-language works237,207