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Record W4362504290 · doi:10.2196/41353

Bringing the Pediatric Endocrine Spanish Speaking Community Together: First Virtual Pediatric Endocrine Meeting in Low- and Middle-Income Countries in Central and South America

2023· article· en· W4362504290 on OpenAlexaffvenueabout
Roberto Bogarin, Luis Elizondo, Evangelia Kalaitzoglou, Jadranka Popovic, Alan D. Rogol, Erick Richmond, Jean‐Pierre Chanoine, José M. López-Pedrosa, Francis Ruiz Salazar, Patricia Vuguin

Bibliographic record

VenueInteractive Journal of Medical Research · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicConferences and Exhibitions Management
Canadian institutionsUniversity of British Columbia
FundersPediatric Endocrine Society
KeywordsPediatric endocrinologyMedicineFamily medicineHealth carePediatricsPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Pediatric endocrinology is a specialty that is struggling worldwide to maintain adequately trained professionals. Pediatric endocrine care in Central America and Caribbean countries is often performed by pediatricians or adult endocrinologists due to the limited number of pediatric endocrinologists. These health care providers are seldom members of endocrine societies and frequently lack formal training in the field. OBJECTIVE: In this study, we describe the scope of a virtual conference in pediatric endocrinology and diabetes targeted to low- and middle-income countries to provide equal opportunities for access to medical education for health care professionals. METHODS: The virtual conference was sponsored by the Pediatric Endocrine Society (North America), Asociación Costarricense de Endocrinología (previously, Asociación Nacional Pro Estudio de la Diabetes, Endocrinología y Metabolismo), and Asociacion Centroamericana y del Caribe de Endocrinologia Pediátrica. The conference was free to participants and comprised 23 sessions that were either synchronous with ability for real-time interactive sessions or asynchronous sessions, where content was available online to access at their convenience. Topics included idiopathic short stature, polycystic ovarian syndrome, diabetes mellitus, telemedicine, Turner syndrome, congenital adrenal hyperplasia, obesity, central precocious puberty, and subclinical hypothyroidism. The participants were asked to evaluate the conference after its completion with a questionnaire. RESULTS: A total of 8 speakers from Spain, Canada, Costa Rica, and the United States delivered the virtual event to 668 health care professionals from Guatemala, Venezuela, Dominican Republic, Costa Rica, Ecuador, Peru, Uruguay, Mexico, Honduras, Argentina, the United States, Bolivia, Chile, Panama, El Salvador, Nicaragua, Paraguay, Belize, Spain, and Colombia. Name, profession, and country were fully disclosed by 410 (61.4%) of the 668 health care professionals. The profession or level of training of participants were as follows: pediatric endocrinologists (n=129, 19.3%), pediatricians (n=116, 17.4%), general practitioners (n=77, 11.5%), adult endocrinologists (n=34, 5.1%), medical students (n=23, 3.4%), residents in various specialties (n=14, 2.1%), and others (n=17, 2.6%). A total of 23 sessions were offered, most of which were bilingual (Spanish and English). Feedback from the evaluation questionnaire indicated that the content of the conference was very relevant to the participants' professional practice. Additionally, the participants reported that they were very satisfied with the organization, the web-based platform, and the sessions of the conference. CONCLUSIONS: Lack of accessibility to the latest and cutting-edge medical education in pediatric endocrinology and diabetes for medical professionals from low- and middle-income countries can be overcome with a virtual conference. Online availability, low cost, and easy-to-use technology were well received from the participants, who were overall very satisfied by the quality and the relevance of the sessions to their professional practice.

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)0.008
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.056
GPT teacher head0.388
Teacher spread0.332 · 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

Citations2
Published2023
Admission routes3
Has abstractyes

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