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Record W4407560504 · doi:10.4314/ejhs.v34i5.11

The Prolonged Hospital Stays at Nigerian Teaching Hospitals: Roles of Medical Social Workers

2024· article· en· W4407560504 on OpenAlexaff
Oluwagbemiga Oyinlola, Raimi Olalekan Adeleke, Abimbola Afolabi

Bibliographic record

VenueEthiopian Journal of Health Sciences · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineFamily medicineNursingMedical emergency

Abstract

fetched live from OpenAlex

Prolonged hospital stays in Nigerian teaching hospitals pose a significant challenge to patient care and hospital management, exacerbated by socio-economic and systemic factors. This case study report looked at the multifaceted role of medical social workers in addressing these challenges, focusing on their efforts in providing psychosocial support, coordinating care, and advocating for patients within a strained healthcare system. This case-study highlights the impact of resource constraints and inadequate hospital practices on patient outcomes, emphasizing the psychological toll on patients and their families. It underscores the critical role of medical social workers as they navigate complex healthcare landscapes to mitigate the adverse effects of extended hospitalizations. This calls for a comprehensive approach to address these systemic issues, including policy reforms, increased healthcare funding, and strategic improvements in hospital administration. Hence the urgency of systemic change to ensure a more resilient and compassionate healthcare environment for all Nigerians.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.047
GPT teacher head0.458
Teacher spread0.411 · 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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes1
Has abstractyes

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