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Objectives <p>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.</p> Methods <p>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.</p> Results <p>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 (<i>P</i> &lt; 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 (<i>β</i> = 0.230, <i>P</i> &lt; 0.001, 95%CI 1.214–1.500), not accepting receiving notifications everyday (<i>β</i> = −&#xa0;0.144, <i>P</i> = 0.001, 95%CI 0.797–0.940), preferred reminders containing positive information (<i>β</i> = 0.159,<i>P</i> = 0.001,95%CI1.068–1.288), opted for screening notifications 1&#xa0;month in advance (<i>β</i> = 0.208, <i>P</i> &lt; 0.001, 95%CI 1.133–1.339), and preferred the image form of education for missionary form (<i>β</i> = 0.118, <i>P</i> &lt; 0.001, 95%CI 1.102–1.322).</p> Conclusion <p>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.</p>

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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

  • 期刊论文

  • 发表日期：

    2026年4月3日

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  • Wei Jin,
  • Xue Wang,
  • Yingxuan Fan,
  • Chunxia Huang,
  • Nian Zhang,
  • Yamei Wei,
  • Xiaoling Ma,
  • Jiesong Wang,
  • Yaxin Li,
  • Huaimiao Jia,
  • Mei Zhang

摘要

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.