BACKGROUND: Data-driven tobacco control policies are essential for effectively managing Local Administration Organizations (LAOs). This research aimed to develop and implement the Tobacco Use Monitoring (TUM) mobile application to facilitate the systematic and convenient collection of high-quality tobacco use data.
METHODS: The TUM application is a data entry tool designed through focus group discussions addressing LAOs’ challenges in formulating tobacco control policies based on data-driven approaches. Development included drafting the layout regarding features and their operational design, validation, pilot testing, and refinement for actual use through free download via iOS and Android. The application was developed from October 2021 to June 2022.
RESULTS: TUM features a user-friendly interface with menus for interviewing tobacco use, observing compliance with tobacco control law, monitoring daily data collection, and generating reports on progress by collectors and LAOs, along with summary statistics, news, and contact information. It functions online and offline, allowing data collection even in remote areas without internet access. Once reconnected to an internet-enabled area, data is automatically stored and transmitted to the admin. In 2022 – 2023, 86 LAOs in the smoke–free LAOs project under ASH, covering 32 provinces throughout Thailand, voluntarily participated. 780 LAO personnel were trained as quality control supervisors and community data collectors to ensure data accuracy and reliability. 74.0% of villages from 86 LAOs were surveyed. Daily monitoring through LINE groups and video calls focused on application use and accessing target samples. Each LAO achieved the development of a smoke-free community plan based on data from TUM.
CONCLUSIONS: TUM has proven to be an effective and user-friendly tool for systematically collecting high-quality data to inform tobacco control policies in LAOs. To enhance its scalability and sustainability, TUM should be refined by incorporating additional features for field preparation, such as sample size calculation and sampling techniques.