ArticlePilot and feasibility studies2017
Promoting adherence to treatment for latent TB infection through mobile phone text messaging: study protocol for a pilot randomized controlled trial.
Article in Pilot and feasibility studies, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 10 papers.
What it found
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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.
Promoting Adherence to Treatment for Latent TB Infection Through Mobile Phone Text Messaging
A Randomized Cross-over Clinical Trial of Unfiltered Cigarettes
Who cites it
10 citing papers in PubMed.
- HOW CAN NEW TECHNOLOGIES HELP REDUCE ABSENTEEISM IN PEDIATRIC CONSULTATION?Revista paulista de pediatria : orgao oficial da Sociedade de Pediatria de Sao Paulo · 2020Trial
- Effectiveness of centralized hospitalization treatment on transmission in household contacts of pulmonary tuberculosis patients: a contact-traced study.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2025Article
- Challenges and the Way forward in Diagnosis and Treatment of Tuberculosis Infection.Tropical medicine and infectious disease · 2023Review
- Riminophenazine Derivatives as Potential Antituberculosis Agents: Synthesis, Biological, and Electrochemical Evaluations.Molecules (Basel, Switzerland) · 2021Article
- Activity of Riminophenazines against Mycobacterium tuberculosis: A Review of Studies that Might be Contenders for Use as Antituberculosis Agents.ChemMedChem · 2020Review
- Use of Digital Technology to Enhance Tuberculosis Control: Scoping Review.Journal of medical Internet research · 2020Article
- Isoniazid acetylation phenotypes in the Sudanese population; findings and implications.Journal of clinical tuberculosis and other mycobacterial diseases · 2019Article
- Predictors of Multidrug-Resistant Tuberculosis (MDR-TB) in Sudan.Antibiotics (Basel, Switzerland) · 2019Article
- Assessing the Cross-Cultural Adaptation and Translation of a Text-Based Mobile Smoking Cessation Program in Samoa (TXTTaofiTapaa): Pilot Study.JMIR mHealth and uHealth · 2018Article
- Tuberculosis Treatment Adherence of Patients in Kosovo.Tuberculosis research and treatment · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAn estimated two billion people, over one third of the world's population, have latent infection with METHODS/
designWe aim to determine the feasibility and acceptability of text reminders for improving adherence in latent TB patients using a randomized controlled single-blinded trial, measuring adherence through an increase in treatment completion rates. Forty adult LTBI participants will be randomized to either text messages plus phone call reminders or phone call reminders only (usual care). Recruitment, retention, and study acceptability will be assessed as primary outcomes. DISCUSSION: This pilot study will examine the feasibility of using text messaging for increasing adherence to treatment for latent tuberculosis infection. The study will allow for evaluation of process measures and challenges and development of a model for scaling up an effectiveness trial for increasing treatment adherence.
trial registrationNCT02690818 (Clinical Trials.gov).
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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.