ArticleChina CDC weekly2022
Acceptability of Tuberculosis Preventive Treatment Strategies Among Healthcare Workers Using an Online Survey - China, 2021.
Article in China CDC weekly, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Challenges in implementing preventive treatment for latent tuberculosis infection: a narrative review from provider and demand-side perspectives.Frontiers in public health · 2025Pooled it
- Concerns, Priorities, and Pathways: Healthcare Provider Perspectives on Implementing Tuberculosis Preventive Treatment for People with HIV in Indonesia and the Philippines.medRxiv : the preprint server for health sciences · 2026Article
- Between Achievement and Challenge: Examining China's Tuberculosis Control Pathway and Future Directions from a Global Perspective.China CDC weekly · 2026Article
- Acceptance, completion, and safety of the 3HR regimen for latent tuberculosis infection: a prospective cohort study in China.Frontiers in public health · 2026Observational
- Impact of detection rate and preventive treatment of latent tuberculosis infection on the future burden of tuberculosis among students in shanghai: a predictive study using Markov modeling.BMC public health · 2025Article
- Influence of tuberculosis knowledge on acceptance of preventive treatment and the moderating role of tuberculosis stigma among China's general population: cross-sectional analysis.BMC public health · 2024Article
- TB-DROP: deep learning-based drug resistance prediction of Mycobacterium tuberculosis utilizing whole genome mutations.BMC genomics · 2024Article
- Large gap between attitude and action in tuberculosis preventive treatment among tuberculosis-related healthcare workers in eastern China.Frontiers in cellular and infection microbiology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
What is already known about this topic?: In the absence of effective vaccines, tuberculosis preventive treatment (TPT) is essential for the rapid decrease in incidences of tuberculosis (TB), and healthcare workers' acceptability is vital to implementing TPT. What is added by this report?: Overall, 86.5% of healthcare workers knew what TPT was. Most (56.3%) healthcare workers agreed to implement TPT among high-risk groups with latent tuberculosis infection. Drug resistance, adverse events, and unguaranteed efficacy were three main barriers for healthcare workers in accepting TPT. What are the implications for public health practice?: To further promote and implement TPT in China, practical measures included policy support, high-quality training for healthcare workers, and enhanced public awareness of TB prevention and control.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.