MétaCan
Menu
← Back to cohort
Record W2946995528 · doi:10.1093/pch/pxz066.014

15 The Experiences of Bereaved Family Caregivers with Advance Care Planning for Children with Medical Complexity

2019· article· en· W2946995528 on OpenAlexaffabout
Sarah Lord, Clara Moore, Kathy Netten, Reshma Amin, Adam Rappaport, Jonathan Hellman, Eyal Cohen‬‏, Julia Orkin

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of TorontoSickKids Foundation
Fundersnot available
KeywordsNonprobability samplingThematic analysisFeelingQualitative researchPopulationMedicineAdvance care planningNursingPsychologyFamily caregiversEnd-of-life carePalliative careFamily medicineSocial psychology

Abstract

fetched live from OpenAlex

Medical technologies and technological advances have resulted in a growing number of children with medical complexity (CMC), many of whom would not have survived previously. Despite these advances CMC are still at high risk of morbidity and mortality during childhood. Advance Care Planning (ACP) is defined by the Canadian Paediatric Society as “the process of discussing life-sustaining treatments and establishing long-term care goals.” Currently the pediatric literature regarding ACP has been largely limited to the intensive care setting and the oncology population. There is a dearth of information focussing on ACP for CMC and that includes bereaved family caregiver’s views. Bereaved caregivers have the unique ability to reflect upon ACP through their child’s whole disease course and end of life experience. To explore the ACP experiences of bereaved family caregivers of CMC who have experienced the entire illness trajectory, including their child’s death. A qualitative approach was applied, allowing for in-depth data collection through semi-structured interviews. Purposive sampling was used to recruit bereaved caregivers of CMC until thematic saturation was reached. The interview guide was developed through expert consultation and was refined iteratively throughout the interviews. Questions assessed caregivers’ experiences with ACP discussions, their feelings about those conversations and their perceptions about whether ACP affected the end of life experience. Each participant provided written, informed consent and interviews were recorded and transcribed verbatim. Three research team members used content analysis to independently code the interviews. 13 bereaved caregivers of CMC completed 12 interviews ranging from 40–80 minutes in length. All caregivers of CMC had participated in ACP discussions and sometimes found them to be overwhelming and frustrating in the moment. However, all caregivers reported that they now understand and appreciate the importance of the discussions. Four major themes emerged from the data describing caregiver’s feelings and experiences regarding Advance Care Planning: 1) influencers of the ACP experience, 2) positive experiences, 3) negative experiences and 4) the influence of ACP on end of life. Bereaved caregivers provided a unique perspective, highlighting the importance and the benefits of ACP discussions. They also revealed various ways in which ACP conversations could be improved. These insights will be helpful in guiding educational tools for health care providers working with CMC in the future.

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)0.007
metaresearch head score (Gemma)0.018
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 score0.018
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0130.006
Scholarly communication0.0040.003
Open science0.0020.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.355
Teacher spread0.320 · 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
Published2019
Admission routes2
Has abstractyes

Explore more

Same venuePaediatrics & Child Health→Same topicFamily and Disability Support Research→French-language works237,207→