The Relationship Between User Ability Response (UAR) and Intentions and Attitudes Toward Vector Control Among Users of the Geplakkin Application

Azizah Nur Aini, Andri Dwi Hernawan, Elly Trisnawati, Barry Caesar Octariadi

Abstract


Background: Geplakkin is a digital application that enables the general public to report, monitor, and obtain information on Aedes mosquito density as part of a monitoring system. The objective of this study was to analyze the relationship between the level of use of the Aedes mosquito app (UAR) and the intention to eliminate mosquito breeding sites, as well as the relationship between the level of use and attitudes toward eliminating mosquito breeding sites among Geplakkin app users in Pontianak. Methods: The study population consisted of households in Pontianak. A total of 240 Geplakkin app users were selected through targeted sampling. The inclusion criterion was owning a smartphone capable of installing and using the app. Data were analyzed using univariate and bivariate analyses. Bivariate analysis was performed using Pearson’s product-moment correlation and Spearman’s rank correlation. Results: The results showed a weak but statistically significant positive relationship between the level of Geplakkin app usage and the intention to eliminate mosquito breeding sites (r = 0.310, p = 0.000). The variable attitude toward mosquito breeding site elimination showed a very weak but statistically significant positive correlation with UAR (r = 0.149, p = 0.021). Both variables exhibited a positive association, indicating that higher UAR values are associated with stronger intentions and more positive attitudes toward eliminating mosquito breeding sites. Conclusion: Continued use of the Geplakkin monitoring app is recommended, as users’ positive responses to the app have the potential to strengthen their intention to eliminate mosquito breeding sites and thereby foster a positive community attitude toward mosquito breeding site elimination (PSN) efforts as part of dengue vector control.


Full Text:

PDF

References


Paz-Bailey G, Adams LE, Deen J, Anderson KB, Katzelnick LC. Dengue. The Lancet. 2024;403(10427):667–682. http://dx.doi.org/10.1016/s0140-6736(23)02576-x

Wang Y, Zhao S, Wei Y, Li K, Jiang X, Li C, Ren C, Yin S, Ho J, Ran J, Han L, Zee BC-y, Chong KC. Impact of climate change on dengue fever epidemics in South and Southeast Asian settings: A modelling study. Infectious Disease Modelling. 2023;8(3):645–655. http://dx.doi.org/10.1016/j.idm.2023.05.008

Kolimenakis A, Heinz S, Wilson ML, Winkler V, Yakob L, Michaelakis A, Papachristos D, Richardson C, Horstick O. The role of urbanisation in the spread of Aedes mosquitoes and the diseases they transmit—A systematic review. PLOS Neglected Tropical Diseases. 2021;15(9):e0009631. http://dx.doi.org/10.1371/journal.pntd.0009631

Yang X, Quam MBM, Zhang T, Sang S. Global burden for dengue and the evolving pattern in the past 30 years. Journal of Travel Medicine. 2021;28(8):1-11. http://dx.doi.org/10.1093/jtm/taab146

Tsheten T, Gray DJ, Clements ACA, Wangdi K. Epidemiology and challenges of dengue surveillance in the WHO South-East Asia Region. Transactions of The Royal Society of Tropical Medicine and Hygiene. 2021;115(6):583–599. http://dx.doi.org/10.1093/trstmh/traa158

Leandro AS, de Castro WAC, Lopes RD, Delai RM, Villela DAM, de-Freitas RM. Citywide Integrated Aedes aegypti Mosquito Surveillance as Early Warning System for Arbovirus Transmission, Brazil. Emerging Infectious Diseases. 2022;28(4):701–706. http://dx.doi.org/10.3201/eid2804.211547

Leandro A, Maciel-de-Freitas R. Development of an Integrated Surveillance System to Improve Preparedness for Arbovirus Outbreaks in a Dengue Endemic Setting: Descriptive Study. JMIR Public Health and Surveillance. 2024;10:e62759–e62759. http://dx.doi.org/10.2196/62759

Herbuela VRDM, Karita T, Carvajal TM, Ho HT, Lorena JMO, Regalado RA, Sobrepeña GD, Watanabe K. Early Detection of Dengue Fever Outbreaks Using a Surveillance App (Mozzify): Cross-sectional Mixed Methods Usability Study. JMIR Public Health and Surveillance. 2021;7(3):e19034. http://dx.doi.org/10.2196/19034

Mahmud MAF, Abdul Mutalip MH, Lodz NA, Muhammad EN, Yoep N, Hasim MH, Abdul Rahim FA, Aik J, Rajarethinam J, Muhamad NA. The application of environmental management methods in combating dengue: a systematic review. International Journal of Environmental Health Research. 2022;33(11):1148–1167. http://dx.doi.org/10.1080/09603123.2022.2076815

Mahotra A, Pokhrel Y, Thapa TR, Arguni E, Andono RA. Feasibility of NepaDengue mobile application for dengue prevention and control: user and stakeholder perspectives in Nepal. BMJ Public Health. 2024;2(1):e000599. http://dx.doi.org/10.1136/bmjph-2023-000599

Holston J, Suazo-Laguna H, Harris E, Coloma J. DengueChat: A Social and Software Platform for Community-based Arbovirus Vector Control. The American Journal of Tropical Medicine and Hygiene. 2021;105(6):1521–1535. http://dx.doi.org/10.4269/ajtmh.20-0808

van de Werken HA, Rohrbach PJ, Bolman CAW. Explaining intention and use of Mhealth with the unified theory of acceptance and use of technology. Acta Psychologica. 2025;254:104819. http://dx.doi.org/10.1016/j.actpsy.2025.104819

Park JH, Lee CW, Do C. Examining Users’ Acceptance Intention of Health Applications Based on the Technology Acceptance Model. Healthcare. 2025;13(6):596. http://dx.doi.org/10.3390/healthcare13060596

Wang C, Qi H. Influencing Factors of Acceptance and Use Behavior of Mobile Health Application Users: Systematic Review. Healthcare. 9(3):357. http://dx.doi.org/10.3390/healthcare9030357

Park Y-E, Tak YW, Kim I, Lee HJ, Lee JB, Lee JW, Lee Y. User Experience and Extended Technology Acceptance Model in Commercial Health Care App Usage Among Patients With Cancer: Mixed Methods Study. Journal of Medical Internet Research. 2024;26:e55176 http://dx.doi.org/10.2196/55176

Jacob C, Sezgin E, Sanchez-Vazquez A, Ivory C. Sociotechnical Factors Affecting Patients’ Adoption of Mobile Health Tools: Systematic Literature Review and Narrative Synthesis. JMIR mHealth and uHealth. 2022;10(5):e36284. http://dx.doi.org/10.2196/36284

Adnan A, Irvine RE, Williams A, Harris M, Antonacci G. Improving Acceptability of mHealth Apps—The Use of the Technology Acceptance Model to Assess the Acceptability of mHealth Apps: Systematic Review. Journal of Medical Internet Research. 2025;27:e66432. http://dx.doi.org/10.2196/66432

Akritidi D, Gallos P, Koufi V, Malamateniou F. Using an Extended Technology Acceptance Model to Evaluate Digital Health Services. Advances in Informatics, Management and Technology in Healthcare. 2022:530-533. http://dx.doi.org/10.3233/shti220782

Wang T, Wang W, Liang J, Nuo M, Wen Q, Wei W, Han H, Lei J. Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis. npj Digital Medicine. 2022;5(1):145. http://dx.doi.org/10.1038/s41746-022-00692-9

Szinay D, Jone, A, Chadborn T, Brown J, Naughton F. Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review. Journal of Medical Internet Research. 2020;22(5):e17572. http://dx.doi.org/10.2196/17572

Iribarren SJ, Akande TO, Kamp KJ, Barry D, Kader YG, Suelzer E. Effectiveness of Mobile Apps to Promote Health and Manage Disease: Systematic Review and Meta-analysis of Randomized Controlled Trials. JMIR mHealth and uHealth. 2021;9(1):e21563. http://dx.doi.org/10.2196/21563

Kim K, Shin, S, Kim S, Lee E. The Relation Between eHealth Literacy and Health-Related Behaviors: Systematic Review and Meta-analysis. Journal of Medical Internet Research. 2023;25:e40778. http://dx.doi.org/10.2196/40778

Schroeer C, Voss S, Jung-Sievers C, Coenen M. Digital Formats for Community Participation in Health Promotion and Prevention Activities: A Scoping Review. Frontiers in Public Health. 2021;9:713159. http://dx.doi.org/10.3389/fpubh.2021.713159

Park Y-E, Tak YW, Kim I, Lee HJ, Lee JB, Lee JW, Lee Y. User Experience and Extended Technology Acceptance Model in Commercial Health Care App Usage Among Patients With Cancer: Mixed Methods Study. Journal of Medical Internet Research. 2024;26:e55176. http://dx.doi.org/10.2196/55176

Binyamin SS, Zafar BA. Proposing a mobile apps acceptance model for users in the health area: A systematic literature review and meta-analysis. Health Informatics Journal. 2021;27(1):1-27. http://dx.doi.org/10.1177/1460458220976737

Schomakers E-M, Lidynia C, Vervier LS, Calero Valdez A, Ziefle M. Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study. JMIR mHealth and uHealth. 2022;10(1):e27095. http://dx.doi.org/10.2196/27095

Jembai JVJ, Wong YLC, Bakhtiar NAMA, Lazim SNM, Ling HS, Kuan PX, Chua PF. Mobile health applications: awareness, attitudes, and practices among medical students in Malaysia. BMC Medical Education. 2022;22(1):544. http://dx.doi.org/10.1186/s12909-022-03603-4

König L, Suhr R. The Effectiveness of Publicly Available Web-Based Interventions in Promoting Health App Use, Digital Health Literacy, and Media Literacy: Pre-Post Evaluation Study. Journal of Medical Internet Research. 2023;25:e46336. http://dx.doi.org/10.2196/46336




DOI: https://doi.org/10.33846/hd30806

Refbacks

  • There are currently no refbacks.




____________________________________________________________________________________________________________________________________________

Health Dynamics || Open Access Journal || Online version only || Publisher: Knowledge Dynamics || ISSN: 3006-5518 (online) || Contact: healthdynamics.journal@gmail.com; +8801814901991; +6282136364408