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Record W2029384886 · doi:10.1159/000286623

Organization of Psychosocial Care in a Teaching Hospital

2010· article· en· W2029384886 on OpenAlexaff
John M. Cleghorn

Bibliographic record

VenuePsychotherapy and Psychosomatics · 2010
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsPsychosocialPsychologyNursingHealth careMedical educationMedicinePsychiatry

Abstract

fetched live from OpenAlex

This paper describes a method of organizing the psychosocial aspects of medical care in a new teaching hospital. An attempt is made to prevent some of the problems in care identified by the Duff and Hollingshead study (8). In order to be effective, however, psychiatrists must take major steps to overcome their marginal position in the medical profession. In addition, education of medical students to comprehend and manage psychosocial problems must begin at the outset of their medical educational experience and continue throughout. These are the prerequisites for a program of psychosocial care which then faces a major organizational challenge: to transfer aspects of psychosocial care from psychiatrists to others. Ordinary problems of living as distinct from psychiatric problems should not be referred to psychiatrists. In order to accomplish this aim, stable organizational structures ramifying throughout the health care system will be required. Such structures must support informal relationships based on personal respect and the achievements of good education. Psychosocial care in teaching hospitals is not likely to improve until it has representation in the power structure of the institution. Specific goals and methods of organizing psychosocial aspects of medical care are outlined.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.272
Threshold uncertainty score0.807

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 integrity0.0000.001
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 head0.008
GPT teacher head0.321
Teacher spread0.313 · 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

Citations4
Published2010
Admission routes1
Has abstractyes

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