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Record W4416933942 · doi:10.3329/mumcj.v8i2.85807

‘Goals of Care’ Discussion in Surgical Settings: A Pilot Curriculum for the Training of the Faculty Members and Residents under Faculty of Surgery

2025· article· W4416933942 on OpenAlexaff
Abu Sadat Mohammad Nurunnabi, Abul Bashar Md Jamal, Riffat Rahim, Md Mamun Ur Rashid, Muhammad Anwar Hossain, Quazi Shahid ul Alam, Kaisar Haroon

Bibliographic record

VenueMugda Medical College Journal · 2025
Typearticle
Language
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsPublic Health Ontario
Fundersnot available
KeywordsBeneficenceCurriculumPsychological interventionAutonomyEconomic JusticeResource (disambiguation)Health careQuality (philosophy)

Abstract

fetched live from OpenAlex

Early consideration and communication about goals, values, and treatment preferences in the surgical settings can prevent patients (who are suffering from incurable disease e.g., terminal stages of cancer) from undergoing unwanted and unnecessary interventions and help them discuss their priorities (themselves, or along with family members or through surrogate decision-makers). However, there is no (bio)ethics curriculum/training in clinical education in Bangladesh to address the specific needs of the professionals to gain knowledge and skills in ‘goals of care’ discussion. Hence, this (bio)ethics education and training is intended to train surgical faculties and residents to enhance their knowledge, skills, and attitude towards ‘goals of care’ (GOC) conversations (near end of life). Ethics and values play crucial roles in ‘goals of care’ discussion. High quality care can only be achieved when a patient’s care is aligned with their goals, preferences, and values. Physicians do have thoroughly entrenched values like promoting health and reducing suffering, while patients may have some values of life, family connections, and religious or cultural beliefs. The prominent ethical principles behind the ‘goals of care’ discussion are: patient’s autonomy (patient’s choices and preferences based on his/her values of life, engagement of family members, or living in according with religious beliefs or cultural norms), beneficence (care planning aligning with patient’s disease course and prognosis), non-maleficence (avoiding unnecessary and unwanted interventions in terms of surgery or other therapies and resuscitation procedures) and distributive justice (in terms of resource allocation, e.g., unnecessary occupancy of hospital bed/ICU). This curriculum has been designed in a way that it is expected to enhance awareness about those ethical challenges based on ‘principlism’, and ways to overcome those challenges, which will ultimately lead to better communication skill, physician-patient relationship, improve patient safety and outcomes, and optimize the cost-effectiveness of organizational resources. Mugda Med Coll J. 2025; 8(2): 133-137

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)0.006
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
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 head0.231
GPT teacher head0.447
Teacher spread0.216 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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