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Evaluation of the geriatric curriculum implemented at Shiraz University of Medical Sciences, Iran, since 2017: A qualitative study

2019· preprint· en· W4236650051 on OpenAlexaff
Faezeh Jaafari, Somayeh Delavari, Leila Bazrafkan

Bibliographic record

VenueF1000Research · 2019
Typepreprint
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of Alberta
FundersShiraz UniversityShiraz University of Medical Sciences
KeywordsNonprobability samplingCurriculumMedical educationQualitative researchPromotion (chess)PopulationGerontologyMedicinePsychologySociologySocial sciencePolitical sciencePedagogyEnvironmental health

Abstract

fetched live from OpenAlex

<ns4:p> <ns4:bold>Background:</ns4:bold> Recently, there has been an increase in life expectancy due to improvements in nutrition, health, and sanitation. The aim of this study was to evaluate the geriatric curriculum in the field of general medicine at Shiraz University of Medical Sciences (SUMS), Iran to improve the quality of services provided to this population in the community. </ns4:p> <ns4:p> <ns4:bold>Methods:</ns4:bold> This was a qualitative study­­. Six educational hospitals and ambulatory centers of Shiraz University of Medical Sciences participated in this study. Within these centers, 15 medical education faculty members and educational experts, 6 medical students, 6 elderly patients and 6 nurses working in the university related to the geriatric field were selected using purposive sampling. Data were gathered through semi-structured interviews, focus group discussion and field observations in the teaching hospital and ambulatory setting of SUMS from June 2017 to May 2018. Based on the qualitative research, the data underwent conventional content analysis and the main themes were developed from this. </ns4:p> <ns4:p> <ns4:bold>Results:</ns4:bold> Three main themes were extracted from the data: effective clinical education, geriatrics curriculum challenges and promotion strategies for geriatric medicine. Subcategories that emerged were a competent curriculum teacher, a challenging program, management of resources, promotion of the program, and the revision required in the curriculum, which were related to other concepts and described in the real-world situation of the geriatric curriculum in the university, as observed in field observations. </ns4:p> <ns4:p> <ns4:bold>Conclusions:</ns4:bold> This study identified three concepts as main themes that can be used to explain how to implement a geriatric curriculum in a medical university. The main contributing factor to different views of the participants was identified as the revision required to the curriculum for integrative care in a geriatric patient. This should be taken into consideration while planning any programs and decisions aimed at education of medical students on this topic. </ns4:p>

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)0.024
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.269
GPT teacher head0.512
Teacher spread0.243 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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