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Record W1764160976 · doi:10.5430/jnep.v5n10p16

Effect of an HIV/AIDS tailored health education program in Western China: An intervention study

2015· article· en· W1764160976 on OpenAlexvenueno aff
Wanxia Yao, Ming Yao, Xiaoping Liu, Hua Fang, Zhao Shu-min, Ruijun Wang, Cong Yao, Di-Mao Wang

Bibliographic record

VenueJournal of Nursing Education and Practice · 2015
Typearticle
Languageen
FieldHealth Professions
TopicPediatric health and respiratory diseases
Canadian institutionsnot available
FundersFourth Military Medical UniversityXi’an Jiaotong University
KeywordsHuman immunodeficiency virus (HIV)ChinaIntervention (counseling)MedicineHealth educationFamily medicineEnvironmental healthGerontologyNursingPublic healthGeography

Abstract

fetched live from OpenAlex

This study is to explore the effect of a tailored health education program (THEP) to enhance knowledge of human immunodeficiency virus infection/acquired immunodeficiency syndrome (HIV/AIDS) among migrant construction workers (MCWs) in Western China. The THEP was given to 434 MCWs working at three construction sites in Xi’an city, Shaanxi province from December 2011 to May 2012. The MCWs were invited to complete identical baseline and follow-up questionnaire surveys. Before the THEP was conducted, awareness of HIV/AIDS was poor among these MCWs. Knowledge and attitudes among the MCWs significantly improved after implementation of the program. In conclusions: THEPs that educate people regarding HIV/AIDS are urgently needed in China, especially for itinerant workers. THEPs can significantly improve knowledge and attitudes regarding HIV/AIDS.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.112
GPT teacher head0.586
Teacher spread0.474 · 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 designNon-randomized trial
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

Citations1
Published2015
Admission routes1
Has abstractyes

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