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Record W2901962863 · doi:10.1093/inthealth/ihy081

Guatemala City youth: an analysis of health indicators through the lens of a clinical registry

2018· article· en· W2901962863 on OpenAlexaboutno aff
Sarah Golub, Juan Carlos Maza Reyes, Catherine Stamoulis, Alejandra Leal Pensabene, Pablo Alejandro Tijerino Cordón, Erwin Calgua, Areej Hassan

Bibliographic record

VenueInternational Health · 2018
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
FundersMaternal and Child Health BureauHealth Resources and Services AdministrationBoston Children's Hospital
KeywordsSocioeconomic statusMental healthDemographyMedicineConfidence intervalQuarter (Canadian coin)Public healthOdds ratioPsychological interventionEthnic groupPsychologyGerontologyPopulationEnvironmental healthPsychiatryGeography

Abstract

fetched live from OpenAlex

BACKGROUND: Despite the inclusion of adolescent health in recent global frameworks, limited data exist on health indicators in low-income countries. Our objective was to identify socioeconomic measures, risk behaviors and health indicators of young people in Guatemala. METHODS: We conducted a secondary data analysis of the Pan American Health Organization's Sistema Informático del Adolescente of 2831 participants ages 10-24 y from 2008 to 2014. We examined frequencies for a core set of items, and generalized regression models assessed correlations between age, sex and ethnicity with health outcomes of interest. RESULTS: Fewer than 17% of participants reported a history of chronic illness (16.6%) and severe psychological problems (16.8%). While 66.1% of participants' mothers and 36.6% of fathers reported job instability, far fewer families had housing instability (1.9% with no electricity, 6.3% with no running water). Fewer than one-third (29.1%) were sexually active and the majority (76.0%) routinely used condoms. About one-quarter (22.6%) reported abnormal mood. Indigenous participants were significantly more likely to have experienced psychological problems (odds ratio [OR] 1.75 [confidence interval {CI} 1.65-1.86]) and violence (OR 1.34 [CI 1.27-1.42]) compared with whites. CONCLUSIONS: The prevalence of risk behaviors and mental health concerns is low compared with other sources of national and regional data. Further work is needed to examine the benefits and limitations of this system in order to improve health surveillance.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.438
GPT teacher head0.605
Teacher spread0.167 · 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.

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

Citations2
Published2018
Admission routes1
Has abstractyes

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