Volume 12, Issue 2 (2024)
Health Educ Health Promot 2024, 12(2): 181-187 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Nomiko D, Bar A, Monalisa M. Development of an Android-Based Breast Cancer Risk Detector. Health Educ Health Promot 2024; 12 (2) :181-187
URL: http://hehp.modares.ac.ir/article-5-73433-en.html
URL: http://hehp.modares.ac.ir/article-5-73433-en.html
1- Department of Nursing, Health Polytechnic of Ministry of Health Jambi, Jambi, Indonesia
Abstract: (693 Views)
Aims: Breast cancer is among the most common cancer types. This study aimed to develop an Android-based detection application for assessing breast cancer risk.
Materials & Methods: This quasi-experimental study utilized a research and development approach, employing a pre- and post-test design with one group. The development and field-testing phase took place between July and August 2023, involving 59 women of childbearing age purposively selected within the operational vicinity of Puskesmas Simpang IV Sipin, Jambi City, Indonesia. The application successfully underwent testing, including evaluation by media and material validators. Subsequently, a comprehension test was conducted with three respondents individually, ten individuals in a small group, and 59 participants in a large group. In the field test, data are presented descriptively, including frequencies. The Wilcoxon test was utilized to determine a causal relationship between the product’s usage and the observed impact.
Findings: The development of the breast cancer risk assessment application involved several key stages, including the identification stage (comprising problem analysis, context, and literature), the application model design stage, and the material and media validation stage. The media validation process was conducted twice, with the findings yielding a score of 67, averaging 3.35 (meeting valid criteria), while material validation received an average score of 3.0 (also meeting valid criteria). A Wilcoxon test conducted on the knowledge variable revealed a significant increase, with the mean value before the intervention at 8.44 and post-intervention rising to 12.29.
Conclusion: Women of childbearing age readily accept Android-based breast cancer risk detection applications, and their usage has a positive impact on increasing their knowledge.
Materials & Methods: This quasi-experimental study utilized a research and development approach, employing a pre- and post-test design with one group. The development and field-testing phase took place between July and August 2023, involving 59 women of childbearing age purposively selected within the operational vicinity of Puskesmas Simpang IV Sipin, Jambi City, Indonesia. The application successfully underwent testing, including evaluation by media and material validators. Subsequently, a comprehension test was conducted with three respondents individually, ten individuals in a small group, and 59 participants in a large group. In the field test, data are presented descriptively, including frequencies. The Wilcoxon test was utilized to determine a causal relationship between the product’s usage and the observed impact.
Findings: The development of the breast cancer risk assessment application involved several key stages, including the identification stage (comprising problem analysis, context, and literature), the application model design stage, and the material and media validation stage. The media validation process was conducted twice, with the findings yielding a score of 67, averaging 3.35 (meeting valid criteria), while material validation received an average score of 3.0 (also meeting valid criteria). A Wilcoxon test conducted on the knowledge variable revealed a significant increase, with the mean value before the intervention at 8.44 and post-intervention rising to 12.29.
Conclusion: Women of childbearing age readily accept Android-based breast cancer risk detection applications, and their usage has a positive impact on increasing their knowledge.
Keywords: Knowledge [MeSH], Breast Self-Examination [MeSH], Mobile Applications [MeSH], Risk Assessment [MeSH]
Article Type: Original Research |
Subject:
Health Media
Received: 2024/01/16 | Accepted: 2024/04/5 | Published: 2024/04/27
Received: 2024/01/16 | Accepted: 2024/04/5 | Published: 2024/04/27
References
1. Memon ZA, Kanwal N, Sami M, Larik PA, Farooq MZ. Risk of breast cancer among young women and importance of early screening. Asian Pac J Cancer Prev. 2015;16(17):7485-9. [Link] [DOI:10.7314/APJCP.2015.16.17.7485]
2. Al Husaini MAS, Hadi Habaebi M, Gunawan TS, Islam MR. Self-detection of early breast cancer application with infrared camera and deep learning. Electronics. 2021;10(20):2538. [Link] [DOI:10.3390/electronics10202538]
3. UICC. GLOBOCAN 2020: New global cancer data [Internet]. Geneva: :union: for International Cancer Control. 2020 Dec 17 [2023-12-12]. Available from: https://www.uicc.org/news/globocan-2020-new-global-cancer-data [Link]
4. Kemenkes RI. Main results of RISKESDAS 2018. Jakarta: Kementerian Kesehatan Badan Penelitian dan Pengembangan Kesehatan; 2018. [Indonesian] [Link]
5. Kemenkes RI. Indonesia's health profile in 2021. Jakarta:Kementrian Kesehatan Republik Indonesia; 2023. [Indonesian] [Link]
6. Chowdhury D, Das A, Dey A, Sarkar S, Dwivedi AD, Rao Mukkamala R, et al. ABCanDroid: A cloud integrated android app for noninvasive early breast cancer detection using transfer learning. Sensors. 2022;22(3):832. [Link] [DOI:10.3390/s22030832]
7. Waks AG, Winer EP. Breast cancer treatment: A review. JAMA. 2019;321(3):288-300. [Link] [DOI:10.1001/jama.2018.19323]
8. Milosevic M, Jankovic D, Milenkovic A, Stojanov D. Early diagnosis and detection of breast cancer. Technol Health Care. 2018;26(4):729-59. [Link] [DOI:10.3233/THC-181277]
9. Gupta R, Gupta S, Mehrotra R, Sodhani P. Risk factors of breast cancer and breast self-examination in early detection: Systematic review of awareness among Indian women in community and health care professionals. J Public Health. 2020;42(1):118-31. [Link] [DOI:10.1093/pubmed/fdy228]
10. Moo TA, Sanford R, Dang C, Morrow M. Overview of breast cancer therapy. PET Clin. 2018;13(3):339-54. [Link] [DOI:10.1016/j.cpet.2018.02.006]
11. Suprapto, Anita KW. Breast cancer screening application based on android with the certainty factor method. IAIC Int Conf Ser. 2023;4(1):88-96. [Link] [DOI:10.34306/conferenceseries.v4i1.633]
12. Abo Al-Shiekh SS, Ibrahim MA, Alajerami YS. Breast cancer knowledge and practice of breast self-examination among female university students, Gaza. Sci World J. 2021;2021:6640324. [Link] [DOI:10.1155/2021/6640324]
13. Abd-Elaziz NM, Kamal HH, Abd-Elhady H. Effect of breast self examination programme on women's awareness for early detection of breast cancer. Minia Sci Nur J. 2021;10(1):132-40. [Link] [DOI:10.21608/msnj.2021.107542.1014]
14. Bener A, Barışık CC, Acar A, Özdenkaya Y. Assessment of the gail model in estimating the risk of breast cancer: Effect of cancer worry and risk in healthy women. Asian Pac J Cancer Prev. 2019;20(6):1765-71. [Link] [DOI:10.31557/APJCP.2019.20.6.1765]
15. Basegio DL, Corrêa MPA, Kuiava VA, De Quadros C, De Mattos MPB, Pavan NR, et al. The importance of breast self-examination as a diagnostic method of breast cancer. Mastology. 2019;29(1):14-9. [Link] [DOI:10.29289/2594539420190000424]
16. Ginsburg O, Yip C, Brooks A, Cabanes A, Caleffi M, Dunstan Yataco JA, et al. Breast cancer early detection: A phased approach to implementation. Cancer. 2020;126(Suppl 10):2379-93. [Link] [DOI:10.1002/cncr.32887]
17. Kapoor A, Nambisan P, Baker E. Mobile applications for breast cancer survivorship and self-management: A systematic review. Health Informatics J. 2020;26(4):2892-905. [Link] [DOI:10.1177/1460458220950853]
18. Öztürk ES, Kutlutürkan S. The effect of the mobile application-based symptom monitoring process on the symptom control and quality of life in breast cancer patients. Semin Oncol Nurs. 2021;37(3):151161. [Link] [DOI:10.1016/j.soncn.2021.151161]
19. Louro J, Posso M, Hilton Boon M, Román M, Domingo L, Castells X, et al. A systematic review and quality assessment of individualised breast cancer risk prediction models. Br J Cancer. 2019;121(1):76-85. [Link] [DOI:10.1038/s41416-019-0476-8]
20. American Cancer Society. Cancer facts and figures 2021. Atlanta: American Cancer Society; 2021. [Link]
21. Creswell JW. Steps in conducting a scholarly mixed methods study. DBER Speaker Series; 2013. 48. [Link]
22. Rusdi M. Indonesia's health profile in 2021. Depok: Raja Grafindo Persada PT; 2018. [Indonesian] [Link]
23. Imas Masturoh SKM, Nauri Anggita T. Health research methodology. Jakarta: Kementerian Kesehatan Republik Indonesia; 2018. [Indonesian] [Link]
24. Kementerian Kesehatan RI. Technical guidelines for controlling breast cancer and cervical cancer. Jakarta: Kementrian Kesehatan Republik Indonesia; 2013. [Indonesian] [Link]
25. Kamińska M, Ciszewski T, Łopacka-Szatan K, Miotła P, Starosławska E. Breast cancer risk factors. Prz Menopauzalny. 2015;14(3):196-202. [Link] [DOI:10.5114/pm.2015.54346]
26. Erbil N, Dundar N, Inan C, Bolukbas N. Breast cancer risk assessment using the Gail model: A Turkish study. Asian Pac J Cancer Prev. 2015;16(1):303-6. [Link] [DOI:10.7314/APJCP.2015.16.1.303]
27. Panigroro S, Hernowo BS, Purwanto H. Breast cancer treatment guideline. Jurnal Kesehatan Masyarakat. 2019;4(4):1-50. [Indonesian] [Link]
28. Almurshidi SH, Abu-Naser SS. Breast cancer knowledge based system. Int J Acad Health Med Res. 2018;2(12):7-22. [Link]
29. Cruz FOAM, Vilela RA, Ferreira EB, Melo NS, Reis PEDD. Evidence on the use of mobile apps during the treatment of breast cancer: Systematic review. JMIR Mhealth Uhealth. 2019;7(8):e13245. [Link] [DOI:10.2196/13245]
30. Wright A. Evaluation of two mobile health apps for patients with breast cancer using the Mobile Application Rating Scale. Mhealth. 2021;7:60. [Link] [DOI:10.21037/mhealth-20-161]
31. Bhan AD, Jayaram J. Screening, self-examination and awareness in breast cancer. In: Breast cancer: Comprehensive management. Singapore: Springer; 2022. p. 587-600. [Link] [DOI:10.1007/978-981-16-4546-4_29]
32. Yang S, Bui CN, Park K. Mobile health apps for breast cancer: Content analysis and quality assessment. JMIR Mhealth Uhealth. 2023;11:e43522. [Link] [DOI:10.2196/43522]
33. Panayi ND, Mars MM, Burd R. The promise of digital (mobile) health in cancer prevention and treatment. Future Oncol. 2013;9(5):613-7. [Link] [DOI:10.2217/fon.13.42]
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |