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Record W4221131948 · doi:10.1177/07067437221087052

Irremediable Psychiatric Suffering in The Context of Medical Assistance in Dying: A Delphi-Study

2022· article· en· W4221131948 on OpenAlexvenueaboutno aff
Sisco van Veen, Natalie Evans, A.M. Ruissen, Joris Vandenberghe, Aartjan T.F. Beekman, Guy Widdershoven

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2022
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)PsychiatryBiopsychosocial modelDelphi methodNarrativeMedicineMental illnessPsychologyMental health

Abstract

fetched live from OpenAlex

OBJECTIVE: Patients with a psychiatric disorder are eligible to request medical assistance in dying (MAID) in a small but growing number of jurisdictions, including the Netherlands and Belgium. In Canada, MAID for mental illness will become possible in 2023. For this request to be granted, most of these jurisdictions demand that the patient is competent in her request, and that the suffering experienced is unbearable and irremediable. Especially the criterion of irremediability is challenging to establish in patients with psychiatric disorders. The aim of this research is to establish what criteria Dutch and Belgian experts agree to be necessary in characterising irremediable psychiatric suffering (IPS) in the context of MAID. METHODS: A two-round Delphi procedure among psychiatrists with relevant experience. RESULTS: Thirteen consensus criteria were established: five diagnostic and eight treatment-related criteria. Diagnostically, the participants deem a narrative description and attention to contextual and systemic factors necessary. Also, a mandatory second opinion is required. The criteria concerning treatment show that extensive biopsychosocial treatment is needed, and the suffering must be present for several years. Finally, in the case of refusal, the participants agree that there are limits to the number of diagnostic procedures or treatments a patient must undergo. CONCLUSIONS: Consensus was found among a Dutch and Belgian expert group on potential criteria for establishing IPS in the context of MAID. These criteria can be used in clinical decision-making and can inform future procedural demands and research.

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)0.008
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 score0.702
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.355
Teacher spread0.312 · 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

Citations19
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueThe Canadian Journal of PsychiatrySame topicHealthcare Decision-Making and RestraintsFrench-language works237,207