Effectiveness of doctors’ advice on non-prescription antibiotic use: a randomized controlled trial, China

The family doctor-led, community-based intervention demonstrated promising effectiveness and feasibility. This study provides valuable insights for the design and implementation of such interventions aimed at promoting rational use of antibiotics.

Authors

Institutions

Publication Details

Journal
Bulletin of the World Health Organization
Published
2025-12-31
DOI
https://doi.org/10.2471/blt.25.293840
Primary Topic
Antibiotic Use and Resistance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effectiveness of doctors’ advice on non-prescription antibiotic use: a randomized controlled trial, China

Zuxun Lu, Yanhong Gong, Qihua Song, Xiaoxv Yin et al.
Bulletin of the World Health Organization
Antibiotic Use and Resistance
article

Effectiveness of doctors’ advice on non-prescription antibiotic use: a randomized controlled trial, China

Zuxun Lu, Yanhong Gong, Qihua Song, Xiaoxv Yin, Tenghao Wang, Minzhi Xu, Xiaolin Wei, Jianxiong Wu, Yuxin Zhao, Hui Li, C Y Qiu
article en

Abstract

The family doctor-led, community-based intervention demonstrated promising effectiveness and feasibility. This study provides valuable insights for the design and implementation of such interventions aimed at promoting rational use of antibiotics.

Bulletin of the World Health OrganizationVol. 104(01)
University of Toronto (CA), Anhui Medical University (CN), Public Health Ontario (CA)
Openalex Percentile: Top 51%
Antibiotic Use and Resistance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.