A preference study for applying mHealth to improve the quality of cervical cancer screening management from a supply and demand perspective: a discrete choice experiment.
Clinical Snapshot
PICO Framework
| P — Population | Women of cervical cancer screening age residing in rural areas of Xinjiang, China |
| I — Intervention | Mobile health (mHealth) technologies for cervical cancer screening management |
| C — Comparator | Different mHealth attributes and delivery methods (WeChat vs other platforms, notification frequencies, content types, timing, educational formats) |
| O — Outcomes | User preferences for mHealth attributes measured through discrete choice experiment responses and willingness to accept different mHealth configurations |
Bottom Line
This discrete choice experiment provides valuable insights into women's preferences for mHealth-supported cervical cancer screening, demonstrating clear preferences for WeChat-based platforms, monthly rather than daily notifications, positive messaging, advance notice timing, and image-based education. The study's rigorous methodology strengthens confidence in findings, though generalisability beyond rural Chinese populations remains uncertain. For Australian practice, these findings suggest that personalised, culturally appropriate mHealth interventions could improve cervical screening adherence, particularly in rural areas where access barriers exist. However, direct application requires careful adaptation to Australian healthcare contexts, communication preferences, and existing screening infrastructure. The research supports avoiding one-size-fits-all approaches and emphasises the importance of user-centred design in digital health interventions. While promising for improving screening uptake, implementation should be accompanied by evaluation of actual behaviour change and screening completion rates rather than relying solely on stated preferences.
Key Findings
P Value: All significant attributes P < 0.05, with strongest preferences P < 0.001
Effect Size: WeChat preferred (β = 0.230), monthly notifications preferred (β = 0.208), positive messaging preferred (β = 0.159)
Primary Outcome: User preferences for mHealth attributes in cervical cancer screening
Nnt Or Sensitivity: Not applicable for preference study - effect sizes indicate relative preference strength
Confidence Interval: 95% CIs provided for all significant results (ranging from 1.068-1.500)
Clinical Application
High feasibility given widespread smartphone adoption, though requires culturally appropriate adaptation Relevant for improving cervical screening participation, especially in rural Australia. Could complement National Cervical Screening Program initiatives and align with TGA-approved digital health tools. May require adaptation for Australian cultural preferences and integration with existing reminder systems. Women eligible for cervical cancer screening, particularly in rural or underserved areas
Abstract
OBJECTIVES: This study aims to investigate the preferences of women of cervical cancer screening age regarding the use of mobile health (mHealth) technologies in Xinjiang. The purpose is to enhance adherence and acceptance of mHealth applications, thereby improving the quality of cervical cancer screening follow-up for women residing in rural areas of Xinjiang. METHODS: The attributes and levels were established based on a comprehensive literature review and qualitative interviews. The choice set questionnaire was developed using SAS 9.4 through D-efficiency analysis. The research site was identified using a multi-stage sampling method, and the survey was launched in December 2024. An Optimal Logit model was selected for preference analysis, utilizing Stata 17.0. RESULTS: A total of six attributes were identified through the literature review and subsequently combined with qualitative interviews. The mixed logit regression results indicated that, among the six attributes, five were statistically significant (P < 0.05): mHealth approach, frequency of receiving notifications, reminder content, screening notification time, missionary form, and mission strategy. The results demonstrated a preference for WeChat as the mHealth approach (β = 0.230, P < 0.001, 95%CI 1.214-1.500), not accepting receiving notifications everyday (β = - 0.144, P = 0.001, 95%CI 0.797-0.940), preferred reminders containing positive information (β = 0.159,P = 0.001,95%CI1.068-1.288), opted for screening notifications 1 month in advance (β = 0.208, P < 0.001, 95%CI 1.133-1.339), and preferred the image form of education for missionary form (β = 0.118, P < 0.001, 95%CI 1.102-1.322). CONCLUSION: A one-size-fits-all approach should be avoided in the design of mHealth solutions to effectively address the diverse needs of individuals with varying preferences, thereby promoting the adoption of mHealth and improving the feasibility of its application.
References
- 1.Jin, W., Wang, X., Fan, Y., Huang, C., Zhang, N., Wei, Y., Ma, X., Wang, J., Li, Y., Jia, H., & Zhang, M. (2026). A preference study for applying mHealth to improve the quality of cervical cancer screening management from a supply and demand perspective: a discrete choice experiment. Cancer Causes & Control. https://doi.org/10.1136/bmjopen-2020-036995
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