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Record W2131508570

USING COMMUNITY MENTAL HEALTH PROJECT AS VENUE TO TRAIN PROFESSIONALISM: THE CYBERJAYA UNIVERSITY COLLEGE OF MEDICAL SCIENCES STUDENTS' EXPERIENCE

2012· article· en· W2131508570 on OpenAlexaboutno aff
Rafidah Bahari, Muhammad Najib Mohamed Alwi

Bibliographic record

VenueAsean Journal of Psychiatry · 2012
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsMedical educationQuarter (Canadian coin)TeamworkCommunity projectMental healthPsychologyMedicineSociologyPsychiatryManagementSocial science
DOInot available

Abstract

fetched live from OpenAlex

Objective: The aim of this paper is to examine medical students' views on the usefulness of a community project as a venue to train professionalism. Methods: Medical students at Cyberjaya University College of Medical Sciences (CUCMS) were surveyed following psychiatry community projects organized during year 4 undergraduate attachments in psychiatry. Results: A total of 176 students returned the survey forms. A majority of medical students thought that the psychiatry community project promotes teamwork and leadership skills. About a quarter thought that it helped foster their communication ability and encouraged them to be more reflective in their daily lives. These findings were translated into the potential of the community project to train collaborative and managerial affective domain learning outcomes of the university. Conclusions: The findings indicate that psychiatry community project or similar programmes may be useful tools to train several elements of medical professionalism. Future research however should utilise specific measurements to confirm this finding. ASEAN Journal of Psychiatry, Vol.13(1): January - June 2012: XX XX

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.503

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.134
GPT teacher head0.500
Teacher spread0.366 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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