Public Policies and Programs for the Prevention and Control of Breast Cancer in Latin American Women: Scoping Review
Bibliographic record
Abstract
BACKGROUND: Breast cancer has positioned itself worldwide as one of the main public health problems, especially in Latin America. In some countries, several programs for the prevention and control of breast cancer in women have been developed and implemented on a permanent basis, but there are no public reports on the policies that originated such programs. OBJECTIVE: A scoping review of scientific publications that identify the type, extent, and scope of policies and programs for the prevention and control of breast cancer in Latin American women was performed, and the main results were presented in this paper. METHODS: This scoping review was carried out according to the method by Arksey and O'Malley based on 3 fundamental questions about breast cancer prevention and control policies in Latin America: their type, extent and scope, and reference framework. The search period was from 2000 to 2019, and the search was carried out in the following databases: MEDLINE (PubMed), MEDLINE (EbscoHost), CINAHL (EbscoHost), Academic Search Complete (EbscoHost), ISI Web of Science (Science Citation Index), and Scopus in English, Spanish, and Portuguese, and Scielo, Cochrane, and MEDES-MEDicina in Spanish and Portuguese. Of the 743 studies found, 20 (2.7%) were selected, which were analyzed using descriptive statistics and qualitative content analysis. RESULTS: The selected studies identified several Latin American countries that have generated policies and programs to prevent and control breast cancer in women, focusing mainly on risk communication, prevention and timely detection, effective access to health services, improvement of the screening process, and evaluation of screening programs. Evaluation criteria and greater participation of civil society in policy design and program execution are still lacking. This could undoubtedly help eliminate existing barriers to effective action. CONCLUSIONS: Although several Latin American countries have generated public policies and action programs for the prevention and control of breast cancer, a pending issue is the evaluation of the results to analyze the effectiveness and impact of their implementation given the magnitude of the public health problem it represents and because women and civil society play an important role in its prevention and control. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/12624.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".