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Masruroh, Maruroh, Susanto, Agus, Wijayanti, Heny. (1405). The Role of Chatbot Literacy, AI Trust, and HIV/AIDS Sensitivity in Shaping HIV/AIDS Literacy among Adolescents. , 11(3), 89-100. doi: 10.22038/jhl.2026.91443.1866
Maruroh Masruroh; Agus Susanto; Heny Noor Wijayanti. "The Role of Chatbot Literacy, AI Trust, and HIV/AIDS Sensitivity in Shaping HIV/AIDS Literacy among Adolescents". , 11, 3, 1405, 89-100. doi: 10.22038/jhl.2026.91443.1866
Masruroh, Maruroh, Susanto, Agus, Wijayanti, Heny. (1405). 'The Role of Chatbot Literacy, AI Trust, and HIV/AIDS Sensitivity in Shaping HIV/AIDS Literacy among Adolescents', , 11(3), pp. 89-100. doi: 10.22038/jhl.2026.91443.1866
Masruroh, Maruroh, Susanto, Agus, Wijayanti, Heny. The Role of Chatbot Literacy, AI Trust, and HIV/AIDS Sensitivity in Shaping HIV/AIDS Literacy among Adolescents. , 1405; 11(3): 89-100. doi: 10.22038/jhl.2026.91443.1866

The Role of Chatbot Literacy, AI Trust, and HIV/AIDS Sensitivity in Shaping HIV/AIDS Literacy among Adolescents

Journal of Health Literacy
مقاله 7، دوره 11، شماره 3 - شماره پیاپی 42، مهر 2026، صفحه 89-100    اصل مقاله (1.25 M)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22038/jhl.2026.91443.1866
نویسندگان
Maruroh Masruroh1؛ Agus Susanto* 2؛ Heny Noor Wijayanti1
1Diploma in Midwifery, Universitas Respati Yogyakarta, Indonesia.
2Bachelor of Applied Media Production, Politeknik Indonusa Surakarta, Indonesia.
چکیده
Background and Objective: Adolescents represent a crucial population for HIV/AIDS prevention, yet their literacy and engagement with digital health resources remain inadequate. Purpose: This study aimed to examine the influence of chatbot literacy, trust in artificial intelligence, and HIV/AIDS sensitivity on HIV/AIDS literacy among late adolescents. 

Material and Methods: A cross-sectional survey was conducted in August 2025 involving 926 students from senior and vocational high schools, recruited through stratified random sampling. Data were obtained via a validated questionnaire assessing HIV/AIDS literacy, chatbot literacy, AI trust, AI openness, chatbot choice, and HIV/AIDS sensitivity. The digital survey was distributed using QR codes. Descriptive statistics summarized characteristics; Chi-square tests identified associations; logistic regression determined independent predictors (odds ratios, 95% confidence intervals). Ethical clearance and informed consent/assent were secured. 

Results: HIV/AIDS literacy differed significantly by age, gender, school type, and internet access (p < 0.05). Bivariate analysis showed that chatbot literacy, AI trust, and HIV/AIDS sensitivity were significantly associated with HIV/AIDS literacy (p < 0.001). Multivariate analysis confirmed that AI trust (p < 0.001), chatbot literacy (p = 0.032), and HIV/AIDS sensitivity (p<0.001) remained significant independent predictors. 

Conclusion: HIV/AIDS literacy among adolescents is shaped by digital competence, AI trust, and health awareness. Strengthening these aspects may enhance youth engagement with health information and support preventive behaviors.
کلیدواژه‌ها
Adolescents؛ AI trust؛ Digital literacy؛ HIV/AIDS literacy
مراجع
  1. Bossonario PA, Ferreira MRL, Andrade RL de P, Sousa KDL de, Bonfim RO, Saita NM, et al. Risk factors for HIV infection among adolescents and the youth: A systematic review. Rev Lat Am Enfermagem. 2022;30(spe):e3697. https://doi.org/10.1590/1518-8345.6264.3697 PMid:36197391 PMCid:PMC9647917
  2. Mathur S, Pilgrim N, Patel SK, Okal J, Mwapasa V, Chipeta E, et al. HIV vulnerability among adolescent girls and young women: A multi-country latent class analysis approach. Int J Public Health. 2020;65(4):399-411. https://doi.org/10.1007/s00038-020-01350-1 PMid:32270233 PMCid:PMC7274997
  3. Gamarel KE, King WM, Operario D. Behavioral and social interventions to promote optimal HIV prevention and care continua outcomes in the United States. Curr Opin HIV AIDS. 2022;17(2):65-71. https://doi.org/10.1097/COH.0000000000000717 PMid:35067595 PMCid:PMC8885930
  4. UNAIDS. Global HIV & AIDS statistics - Fact sheet 2024 [Internet]. Geneva: UNAIDS; 2024 [cited 2025 Sept 12]. Available from: https://www.unaids.org/en/resources/fact-sheet
  5. Fields EL. Realizing the promise of PrEP Globally for vulnerable adolescent and young adult populations. J Adolesc Heal. 2023;73(6):S1-3. https://doi.org/10.1016/j.jadohealth.2023.09.007 PMid:37953002
  6. UNAIDS. The path that ends AIDS: UNAIDS global AIDS update 2023. Geneva; 2023.
  7. Schaefer R, Peralta H, Radebe M, Baggaley R. Young People Need More HIV Prevention Options, Delivered in an Acceptable Way. J Adolesc Heal. 2023;73(6):S8-10. https://doi.org/10.1016/j.jadohealth.2023.08.046 PMid:37953013
  8. Jocelyn, Nasution FM, Nasution NA, Asshiddiqi MH, Kimura NH, Siburian MHT, et al. HIV/AIDS in Indonesia: current treatment landscape, future therapeutic horizons, and herbal approaches. Front Public Heal. 2024;12:1298297. https://doi.org/10.3389/fpubh.2024.1298297 PMid:38420030 PMCid:PMC10899510
  9. Wijayanti F, Tarmizi SN, Tobing V, Nisa T, Akhtar M, Trihandini I, et al. From the millennium development goals to sustainable development goals. The response to the HIV epidemic in Indonesia: challenges and opportunities. J Virus Erad. 2016;2(Suppl 4):27. https://doi.org/10.1016/S2055-6640(20)31096-7 PMid:28275447 PMCid:PMC5337410
  10. Obeagu EI. Youth-Friendly HIV Prevention: Tailoring Interventions for Young Populations. Int J Med Sci Pharma Res. 2024;10(4):62-7. https://doi.org/10.22270/ijmspr.v10i4.125
  11. Johnston LG, Soe P, Widihastuti AS, Camellia A, Putri TA, Rakhmat FF, et al. Alarmingly high HIV prevalence among adolescent and young men who have sex with men (MSM) in Urban Indonesia. AIDS Behav. 2021;25(11):3687-94. https://doi.org/10.1007/s10461-021-03347-0 PMid:34143341 PMCid:PMC8560664
  12. Bumgarner KF, Pharr J, Buttner M, Ezeanolue E. Interventions that increase the intention to seek voluntary HIV testing in young people: A review. Aids Care-psychological Socio-medical Asp Aids. 2017;29(3):365-71. https://doi.org/10.1080/09540121.2016.1259456 PMid:27871185
  13. Nugrahawati REPC, Hernayanti MR, Purnamaningrum YE, Petphong V. Factors related to adolescent behavior towards HIV/AIDS prevention. Kesmas. 2019;13(4):195-201. https://doi.org/10.21109/kesmas.v13i4.2698
  14. Dinas Kesehatan DIY. Laporan kinerja perangkat daerah dinas kesehatan tahun 2022 (Regional health office performance report, 2022). 2022..
  15. Zahrah F, Linda O, Novianus C. Factors Affecting HIV/AIDS Prevention Behavior in Adolescents at SMA Negeri 10 Depok in 2022. ICSDH 2022 - Int Conf Soc Determ Heal. 2023;(Icsdh 2022):5-12. https://doi.org/10.5220/0011643100003608
  16. Ni Z, Oh S, Saifi R, Azwa I, Altice FL. Evaluating the usability of an HIV prevention artificial intelligence Chatbot in Malaysia: National observational study. JMIR Hum Factors. 2025;12:e70034. https://doi.org/10.2196/70034 PMid:40663792 PMCid:PMC12283058
  17. Wah JNK. Revolutionizing e-health: the transformative role of AI-powered hybrid chatbots in healthcare solutions. Front Public Heal. 2025:13:1530799. https://doi.org/10.3389/fpubh.2025.1530799 PMid:40017541 PMCid:PMC11865260
  18. Maher C, Singh B, Wylde A, Chastin S. Virtual health assistants: A grand challenge in health communications and behavior change. Front Digit Heal. 2024;6(May):1-4. https://doi.org/10.3389/fdgth.2024.1418695 PMid:38827384 PMCid:PMC11140094
  19. Crowley T, Weyers L, Petinger C, Tokwe L. Digital health interventions for adolescents living with HIV in low- and middle-income countries: A narrative review and logic model. Inf Dev, 2025; 22(1):2. https://doi.org/10.1177/02666669241299768
  20. Gogishvili M, Arora AK, White TM, Lazarus J V. Recommendations for the equitable integration of digital health interventions across the HIV care cascade. Commun Med. 2024;4(1):1-3. https://doi.org/10.1038/s43856-024-00645-1 PMid:39489853 PMCid:PMC11532406
  21. Choung H, David P, Ross A. Trust in AI and its role in the acceptance of AI technologies. Int J Human-Computer Interact. 2023;39(9):1727-39. https://doi.org/10.1080/10447318.2022.2050543 PMCid:PMC11754992
  22. Seif SJ, Oguma ED, Joho AA. Using health belief model to assess the determinants of HIV/AIDS prevention behavior among university students in Central, Tanzania: A cross-sectional study. PLOS Glob Public Heal. 2025;5(2):e0004305. https://doi.org/10.1371/journal.pgph.0004305 PMid:40009612 PMCid:PMC11864508
  23. Wilbourn B, Howard-Howell T, Castel A, D'Angelo L, Trexler C, Carr R, et al. Barriers and facilitators to HIV testing among adolescents and young adults in Washington, District of Columbia: Formative research to inform the development of an mHealth intervention. JMIR Form Res. 2022;6(3).https://doi.org/10.2196/29196 PMid:35275083 PMCid:PMC8956991
  24. Ng DTK, Wu W, Leung JKL, Chiu TKF, Chu SKW. Design and validation of the AI literacy questionnaire: The affective, behavioural, cognitive and ethical approach. Br J Educ Technol. 2024;55(3):1082-104. https://doi.org/10.1111/bjet.13411
  25. Kurniawan MD, Arifin B, Rokhman MR, Perwitasari DA. Validity and reliability of the Indonesian Version of HIV-KQ-18 in assessing public knowledge about HIV/AIDS in the special region of Yogyakarta. Media Farm J Ilmu Farm. 2022;19(2):112. https://doi.org/10.12928/mf.v19i2.22107
  26. Sisk BA, Antes AL, Lin SC, Nong P, DuBois JM. Validating a novel measure for assessing patient openness and concerns about using artificial intelligence in healthcare. Learn Heal Syst. 2025;9(1):e10429. https://doi.org/10.1002/lrh2.10429 PMid:39822920 PMCid:PMC11733432
  27. Yam EA, Namukonda E, McClair T, Souidi S, Chelwa N, Muntalima N, et al. Developing and testing a chatbot to integrate HIV education into family planning clinic waiting areas in Lusaka, Zambia. Glob Heal Sci Pract. 2022;10(5). https://doi.org/10.9745/GHSP-D-21-00721 PMid:36316140 PMCid:PMC9622293
  28. Aybar-Flores A, Talavera A, Espinoza-Portilla E. Predicting the HIV/AIDS knowledge among the adolescent and young adult population in Peru: Application of quasi-binomial logistic regression and machine learning algorithms. Int J Environ Res Public Heal. 2023;20(7):5318. https://doi.org/10.3390/ijerph20075318 PMid:37047934 PMCid:PMC10093875
  29. Stauch L, Renninger D, Rangnow P, Hartmann A, Fischer L, Dadaczynski K, et al. Digital health literacy of children and adolescents and its association with sociodemographic factors: representative study findings from Germany. J Med Internet Res. 2025;27(1):e69170. https://doi.org/10.2196/69170 PMid:40324766 PMCid:PMC12089873
  30. You MA, Ahn JA. Health information orientation and health literacy as determinants of health promotion behaviors in adolescents: A cross-sectional study. Front Public Heal. 2024 Jan 20;12:1522838. https://doi.org/10.3389/fpubh.2024.1522838 PMid:39901914 PMCid:PMC11789532
  31. Gazibara T, Cakic M, Cakic J, Grgurevic A, Pekmezovic T. Familiarity with the internet and health apps, and specific topic needs are amongst the factors that influence how online health information is used for health decisions amongst adolescents. Heal Inf Libr J . 2024;41(3):283-97. https://doi.org/10.1111/hir.12440 PMid:35652454
  32. Gray NJ, Klein JD, Noyce PR, Sesselberg TS, Cantrill JA. The Internet: A window on adolescent health literacy. J Adolesc Heal. 2005;37(3):243.e1-243.e7. https://doi.org/10.1016/j.jadohealth.2004.08.023 PMid:16109345
  33. Jain A V., Bickham D. Adolescent health literacy and the Internet: Challenges and opportunities. Curr Opin Pediatr. 2014;26(4):435-9. https://doi.org/10.1097/MOP.0000000000000119 PMid:24886952
  34. Amanu Asari A, Godesso A, Birhanu Z. Health literacy profiles and disparities among adolescents and implications in Ethiopia. J Multidiscip Healthc. 2025;18:5025-38. https://doi.org/10.2147/JMDH.S532819 PMid:40862265 PMCid:PMC12374705
  35. Lee J, Jung K, Newman EG, Chow E, Chen Y. Understanding adolescents' perceptions of benefits and risks in health AI technologies through design fiction. CHI Conf Hum Factors Comput Syst (CHI '25), 2025, Yokohama, Japan. 2025;1. https://doi.org/10.1145/3706598.3713244
  36. Zhao J, Yang Y, Miao J, Wang X, Qi D, Zang S. Factors associated with the level of trust in health information robots among the general population from a socioecological model perspective: Network analysis. J Med Internet Res. 2025;27(1):e68299. https://doi.org/10.2196/68299 PMid:40513089 PMCid:PMC12205264
  37. Su J, Wang Y, Liu H, Zhang Z, Wang Z, Li Z. Investigating the factors influencing users' adoption of artificial intelligence health assistants based on an extended UTAUT model. Sci Rep. 2025;15(1):1-19. https://doi.org/10.1038/s41598-025-01897-0 PMid:40414992 PMCid:PMC12104380
  38. Darabi F, Maheri M, Shadmani MN. The effect of educational intervention based on the health belief model on promoting perceived self-efficacy to prevent HIV/AIDS among the high school students. J Educ Community Heal. 2023;10(1):8-15. https://doi.org/10.34172/jech.2023.1991
  39. Joorbonyan H, Ghaffari M, Rakhshanderou S. Peer-led theoretically Desinged HIV/AIDS prevention intervention among students: A case of health belief model. BMC Public Health. 2022;22(1):1-10. https://doi.org/10.1186/s12889-021-12445-6 PMid:34983478 PMCid:PMC8728909
  40. Zhang D, Wijaya TT, Wang Y, Su M, Li X, Damayanti NW. Exploring the relationship between AI literacy, AI trust, AI dependency, and 21st century skills in preservice mathematics teachers. Sci Rep. 2025;15(1):1-15. https://doi.org/10.1038/s41598-025-99127-0 PMid:40275054 PMCid:PMC12022015
  41. Ng SWT, Zhang R. Trust in AI chatbots: A systematic review. Telemat Informatics. 2025;97:102240. https://doi.org/10.1016/j.tele.2025.102240
  42. Labadze L, Grigolia M, Machaidze L. Role of AI chatbots in education: Systematic literature review. Int J Educ Technol High Educ. 2023;20(1):1-17. 023-00426-1 https://doi.org/10.1186/s41239-023-00426-1
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