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Record W1517841986 · doi:10.5772/31687

Health Care Under the Influence: Substance Use Disorders in the Health Professions

2012· book-chapter· en· W1517841986 on OpenAlexaff
Diane Kunyk, Charl Els

Bibliographic record

VenueInTech eBooks · 2012
Typebook-chapter
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHealth careSubstance abuseMedicineVulnerability (computing)Mental healthNursingPsychiatryPsychologyPolitical science

Abstract

fetched live from OpenAlex

Substance use disorders are expressed within most age, economic, cultural, gender, and occupational groupings. They come to expression in individuals who may be considered vulnerable on biological, psychological, social, family, or spiritual levels. As with other mental disorders, vulnerability differs between individuals with both nature and nurture influencing their risk. Some health care professionals will also develop these chronic disorders regardless of any special knowledge or experience they may have. When substance use disorders are expressed within the health care professions, the delivery of safe, competent, compassionate, and ethical care is threatened. The health of the health care professional is also at risk as the substance use disorders typically progress in severity and may result in premature death. This is often a sensitive issue to address yet its importance demands the concerted attention of the health care professions. The following chapter begins with background on the issue of substance use disorders within the health care professions, followed by a discussion of mitigating associated risks, and an exploration of disciplinary and alternative to discipline policies. This chapter is focused primarily on literature on physicians and nurses because of the predominance of research in these disciplines. The argument will be made that creating conditions that encourage early identification, reduce barriers to treatment, and that include long-term monitoring programs provide the best conditions for ameliorating the risks resulting from substance use disorders amongst the health care professions to patient safety and health care professional health.

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: none
Teacher disagreement score0.683
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.333
Teacher spread0.284 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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