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Record W2113851433

Capacity-building in family health: innovative in-service training program for teams in Latin America.

2009· article· en· W2113851433 on OpenAlexaffabout
Yves Talbot, Silvia Takeda, Monica Riutort, Onil Bhattacharyya

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLatin AmericansSoftware deploymentProgram evaluationMedical educationService (business)MedicineHealth careTraining (meteorology)NursingPolitical scienceComputer scienceBusiness
DOInot available

Abstract

fetched live from OpenAlex

PROBLEM BEING ADDRESSED: Brazil, Chile, and Canada are among the countries where development and deployment of human resources have been central to health reform; however, it is unclear how the education and training of primary care workers is best accomplished. OBJECTIVE OF THE PROGRAM To implement a model of in-service training in primary health care for interdisciplinary teams of primary health care professionals from Brazil and Chile. PROGRAM DESCRIPTION: This 5-module program targeted primary care providers from various disciplines who had at least 3 months of front-line experience. The program was offered in 2 formats: intermittent "in-country" training or an intensive course taught in Canada. In Brazil, the in-country training took place over a period of 8 to 12 months, during which 5 modules of 2 to 3 days each were interspersed with 2-month "action periods." The intensive course taught in Canada was delivered to Chilean participants in Toronto, Ont, where 3 modules were offered to a group of 12 to 20 primary health care professionals over a 6-week period. The educational methodology combined short didactic presentations, whole group learning exercises, and small group problem-based learning sessions, including team projects that were completed in between each module and presented at the beginning of the next one. During the course, the participants learned how to perform computer database searches and assess the best evidence in the management of common problems. CONCLUSION: Pretests, posttests, and evaluations of student projects demonstrated that participants had increased knowledge, as well as increased capacity to use the best evidence to address common problems in their communities. This is a promising model, adapted to the context of primary care reform in Latin America, with strong potential to support health human resource development and multidisciplinary care by front-line providers in other countries.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.162
GPT teacher head0.428
Teacher spread0.266 · 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

Citations18
Published2009
Admission routes2
Has abstractyes

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