Development and evaluation of an application-based system with LINE chatbot for pesticide-exposure risk assessment among sugarcane farmers 10.55131/jphd/2026/240311

Main Article Content

Peanthip Srisutam
Rattana Leerungnavarat
Chan Pattama Polyong

Abstract

This study developed and evaluated a mobile application integrated with a LINE chatbot for assessing pesticide-use behaviors and related health risks among rice and sugarcane farmers in Thailand. A research and development (R&D) design combined with a quasi-experimental approach was applied, using the standardized assessment tool of the Department of Disease Control. Expert evaluation (n=3) confirmed strong content validity (IOC =0.67–1.00) and reliability testing with30participants(n=30), including health officers and volunteers (Cronbach’s alpha 0.729), Indicated very high satisfaction, particularly regarding convenience, clarity of results, and applicability. Field testing with 125 farmers (n=125) showed that unsafe practices were highly prevalent, including self-spraying herbicides (85.6%), not reading labels (82.4%), and not washing hands before meals (81.6%). Symptom monitoring revealed that 74.6% of farmers reported health problems, mainly at moderate severity (55.1%), with dizziness, nausea, and abdominal pain being common. Overall risk assessment classified 38.9% of farmers as high risk, 27.1% as moderately high risk, and only 7.9% as low risk. The application significantly reduced assessment and reporting time compared with paper-based methods (mean total time: 22.6 vs. 3.2 minutes, p<0.001).  These findings suggest that the developed tool enhances efficiency, supports real-time health risk communication, and can serve as a scalable digital health prototype for agricultural occupational safety.

Article Details

How to Cite
1.
Peanthip Srisutam, Rattana Leerungnavarat, Polyong CP. Development and evaluation of an application-based system with LINE chatbot for pesticide-exposure risk assessment among sugarcane farmers: 10.55131/jphd/2026/240311. J Public Hlth Dev [internet]. 2026 Aug. 31 [cited 2026 Sep. 4];24(3):147-62. available from: https://he01.tci-thaijo.org/index.php/AIHD-MU/article/view/283562
Section
Original Articles
Author Biographies

Peanthip Srisutam, Information Technology and Data Science program, Bansomdejchaopraya Rajabhat University, Bangkok, Thailand

Information Technology and Data Science program, Bansomdejchaopraya Rajabhat University, Bangkok, Thailand

Rattana Leerungnavarat, Information Technology and Data Science program, Bansomdejchaopraya Rajabhat University, Bangkok, Thailand

Information Technology and Data Science program, Bansomdejchaopraya Rajabhat University, Bangkok, Thailand

Chan Pattama Polyong, Occupational Health and Safety Program, Bansomdejchaopraya Rajabhat University, Bangkok, Thailand

Occupational Health and Safety Program, Bansomdejchaopraya Rajabhat University, Bangkok, Thailand

References

Ong-Artborirak P, Boonchieng W, Juntarawijit Y, Juntarawijit C. Potential effects on mental health status associated with occupational exposure to pesticides among Thai farmers. Int J Environ Res Public Health. 2022;19(15):9654.

World Bank/WITS. Thailand chemicals imports by country, HS 28–38. Washington, DC: World Bank; 2022. Available from: https://wits.worldbank.org.

Desye B, Hunegnaw MT, Adane M, Alemseged EA, Angaw Y, Ebrahim M. Pesticide safe use practice and acute health symptoms among farmers in developing countries: a systematic review and meta-analysis. BMC Public Health. 2024;24:20817.

Laohaudomchok W, Nankongnab N, Siriruttanapruk S, Klaimala P, Lianchamroon W, Ousap P, et al. Pesticide use in Thailand: current situation, health risks, and gaps in research and policy. Hum Ecol Risk Assess. 2021;27(5):1147–69.

Gerken J, Vincent GT, Zapata D, Barron IG, Zapata I. Comprehensive assessment of pesticide use patterns and increased cancer risk. Front Cancer Control Soc. 2024;2: 1368086.

Department of Disease Control. Manual for assessing pesticide use behaviors among farmers. Bangkok: Ministry of Public Health; 2019.

Thai-u K. Evaluation of the health surveillance system for farmers at risk of pesticide exposure, Bureau of Occupational and Environmental Diseases, 2016. Weekly Epidemiol Surveil Rep. 2017;48:737–43.

Akkouch NH, Halwani J, Shaarani I, Ziadeh F. Randomized controlled trial on improving pesticide label interpretation among farmers in Akkar Governorate, Lebanon: the impact of a WhatsApp-delivered educational video. PLoS One. 2025;20(9):e0331842.

Ayaz D, Öncel S. Determining the association between pesticide safety behaviors and health literacy of farmers registered in WhatsApp groups of Antalya Provincial Agriculture and Forest Directorate: a descriptive-correlational study. Clin Exp Health Sci. 2025;15:48–55.

Li S, Sun S, Zhang C. Internet-based information acquisition, technical knowledge and farmers’ pesticide use: evidence from rice production in China. Agriculture. 2024;14(9):1447.

Pereira-Azevedo N, Carrasquinho E, Cardoso de Oliveira E, Cavadas V, Osório L, Fraga A, et al. mHealth in urology: a review of experts’ involvement in app development. PLoS One. 2015;10(5):e0125547.

Free C, Phillips G, Watson L, Galli L, Felix L, Edwards P, et al. The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review. PLoS Med. 2013;10(1):e1001362.

World Health Organization. Global strategy on digital health 2020–2025. Geneva: WHO; 2021.

Labrique AB, Vasudevan L, Kochi E, Fabricant R, Mehl G. mHealth innovations as health system strengthening tools: 12 common applications and a visual framework. Glob Health Sci Pract. 2013;1(2): 160–71.

Kiatkitroj K, Arphorn S, Tangtong C, Maruo SJ, Ishimaru T. Risk factors associated with heat-related illness among sugarcane farmers in Thailand. Ind Health. 2022;60(5): 447–58.

Satzinger JW, Jackson RB, Burd SD. Systems analysis and design in a changing world. 6th ed. Boston: Cengage Learning; 2012.

Gould JD, Lewis C. Designing for usability: key principles and what designers think. Commun ACM. 1985;28(3):300–11.

Kannisto KA, Koivunen MH, Välimäki MA. Use of mobile phone text message reminders in health care services: a narrative literature review. J Med Internet Res. 2014;16(10): e222.

Zhang Y, Milinovich GJ, Xu Z, Bambrick H, Mengersen K, Tong S, Hu W. Monitoring pertussis infections using internet search queries. Sci Rep. 2017;7:10437.

Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989;13(3):319–40.

Holden RJ, Karsh BT. The technology acceptance model: its past and its future in health care. J Biomed Inform. 2010;43(1):159–72.

Chen J, Lieffers J, Bauman A, Hanning R, Allman-Farinelli M. The use of smartphone health apps and other mobile health (mHealth) technologies in dietetic practice: a three-country study. J Hum Nutr Diet. 2020;33(5):644–54.

Keleb A, Ademas A, Abebe M, Berihun G, Desye B, Bezie AE. Knowledge of health risks, safety practices, acute pesticide poisoning, and associated factors among farmers in rural irrigation areas of northeastern Ethiopia. Front Public Health. 2024;12:1474487.