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Record W2547352560 · doi:10.4103/0253-7613.193309

Assessment of knowledge and perceptions toward generic medicines among basic science undergraduate medical students at Aruba

2016· article· en· W2547352560 on OpenAlexaboutno aff
P Ravi Shankar, B Herz, ArunK Dubey, Mohamed Azmi Hassali

Bibliographic record

VenueIndian Journal of Pharmacology · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsRespondentTest (biology)Likert scaleFamily medicineNationalityMedical educationPsychologyPerceptionHealth careMedicineDemographyGeography

Abstract

fetched live from OpenAlex

OBJECTIVE: Use of generic medicines is important to reduce rising health-care costs. Proper knowledge and perception of medical students and doctors toward generic medicines are important. Xavier University School of Medicine in Aruba admits students from the United States, Canada, and other countries to the undergraduate medical (MD) program. The present study was conducted to study the knowledge and perception about generic medicines among basic science MD students. MATERIALS AND METHODS: -test to compare the total score for dichotomous variables, and analysis of variance for others were used for statistical analysis. RESULTS: Fifty-six of the 85 students (65.8%) participated. Around 55% of respondents were between 20 and 25 years of age and of American nationality. Only three respondents (5.3%) provided the correct value of the regulatory bioequivalence limits. The mean total score was 43.41 (maximum 60). There was no significant difference in scores among subgroups. CONCLUSIONS: There was a significant knowledge gap with regard to the regulatory bioequivalence limits for generic medicines. Respondents' level of knowledge about other aspects of generic medicines was good but could be improved. Studies among clinical students in the institution and in other Caribbean medical schools are required. Deficiencies were noted and we have strengthened learning about generic medicines during the basic science years.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.019
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.047
GPT teacher head0.381
Teacher spread0.334 · 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

Citations8
Published2016
Admission routes1
Has abstractyes

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