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Record W2301614974 · doi:10.1177/0706743715625943

Forty-Five Years of Civil Litigation Against Canadian Psychiatrists: An Empirical Pilot Study

2016· article· en· W2301614974 on OpenAlexaffvenueabout
Mansfield Mela, Glen Luther, Thomas G. Gutheil

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2016
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsUniversity of SaskatchewanRoyal University Hospital
Fundersnot available
KeywordsPsychologyPsychiatryMedicinePolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: To extract the themes pertaining to prudent psychiatric practice from written court judgments in Canada. METHODS: We searched the medical and legal literature for cases involving civil litigation against Canadian psychiatrist and reviewed all available written judgments. We completed a thematic analysis of the civil actions against psychiatrists as conveyed by those written court judgments. We classified the cases according to the disposal status and the essential lessons from the decisions on standard of care and practice by Canadian psychiatrists. RESULTS: Forty such cases were identified as involving psychiatrists over a 45-year period. A subgroup included those dealing with limitation periods and disclosure applications. Thirty of the 40 cases (75%) were decided in favour of the defendant psychiatrists, including 2 dismissed for running over the limitation period. The cases that actually went to trial suggest that documentation and obtaining second opinions are protective against claims of negligence. Inpatient cases resulting in successful litigation against psychiatrists involved fatal outcomes, but not all fatal outcomes led to successful litigation. CONCLUSIONS: The key lessons from these cases are the importance and relevance of regular best clinical practices, such as documentation, obtaining second opinions, following guidelines, and balancing competencies in the expert and manager or advocate roles. Incorporating these practices should allay concerns about litigation against psychiatrists.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.069
GPT teacher head0.406
Teacher spread0.337 · 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 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

Citations8
Published2016
Admission routes3
Has abstractyes

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