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Record W4391127212 · doi:10.46747/cfp.700141

Patient experiences with requests for medical assistance in dying

2024· article· en· W4391127212 on OpenAlexaffvenueabout
Clark Fruhstorfer, Michaela Kelly, Laura Spiegel, Peter J. Baylis, Justine Dembo, Ellen Wiebe

Bibliographic record

VenueCanadian Family Physician · 2024
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsSunnybrook HospitalSunnybrook Health Science CentreUniversity of CalgaryUniversity of British ColumbiaPenticton Regional Hospital
Fundersnot available
KeywordsThematic analysisFibromyalgiaQualitative researchMedicineEmpathyFamily medicinePsychologyPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To explore experiences of patients who have complex chronic conditions (CCCs), such as fibromyalgia and chronic fatigue syndrome, when they request medical assistance in dying (MAID) in Canada. DESIGN: Qualitative study using semistructured interviews. SETTING: Canada. PARTICIPANTS: Individuals with CCCs who had contacted any 1 of 4 advocacy organizations between January 21, 2021, and December 20, 2022, about requesting MAID for suffering related to CCCs or who had applied and been assessed for MAID. METHODS: Interviews were conducted virtually (by video or audio) and recordings were transcribed. Thematic analysis was conducted in an iterative manner with abductive analysis. As interviews were completed, transcripts were reviewed and emerging themes were discussed at regular intervals. MAIN FINDINGS: Sixteen individuals were interviewed. All spoke of long-lasting suffering that was unresponsive to an array of medical treatments. Although some participants had hoped to receive MAID immediately following the 90-day assessment period, many mentioned that approval would provide or had provided validation of their illness and a sense of control, especially should their illness become unbearable. Participants sharply distinguished between MAID and suicide, saying they preferred MAID because it offered greater certainty and caused less emotional pain to others. Many said that participating in this research was beneficial because they believed the interviewers truly listened to them. CONCLUSION: Participants described experiences with CCCs and requests for MAID. This information may provide family doctors with new insight to inform interactions with patients with CCCs.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.678

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 head0.020
GPT teacher head0.290
Teacher spread0.270 · 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 designNot applicable
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

Citations6
Published2024
Admission routes3
Has abstractyes

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