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Background <p>In the digital age, the proliferation of information frequently leads to Cancer Information Overload (CIO) among breast cancer (BC) patients. CIO results in difficulties with decision-making and compromises patients’ quality of life. Previous studies have primarily focused on the adverse outcomes of CIO, but research on its antecedents remains limited. Therefore, this study investigates the factors influencing CIO among BC patients.</p> Methods <p>A single-center, cross-sectional study was conducted from February to August 2025. A convenience sampling method was employed to recruit 598 patients with BC from a tertiary traditional Chinese medicine (TCM) hospital in Guangdong Province. Participants completed a sociodemographic questionnaire, the Cancer Information Overload Scale (CIOS), the Digital Health Literacy Scale (DHLS), an asthenopia questionnaire, and the Depression, Anxiety, and Stress Scale (DASS-21). Data were analyzed using independent-samples t-tests, one-way analysis of variance, Pearson correlation analysis, and multiple linear regression analysis in SPSS.</p> Results <p>Univariate analysis identified several significant influencing factors, including occupation, location, education level, caregiver, disease course, treatment, and comorbidities. Bivariate analysis revealed positive correlations between CIO and both asthenopia and depression. Multiple linear regression analysis further demonstrated that asthenopia, digital health literacy, education level, comorbidities, disease course, depression, and type of caregiver were significant predictors. Collectively, these variables explained 74.9% of the total variance in CIO.</p> Conclusion <p>CIO is highly prevalent among BC patients. Tailored intervention strategies based on the identified predictive factors are essential. These include optimizing health information delivery channels, incorporating multi-subject social resources, and delivering psychocognitive interventions.</p> Clinical trial number <p>Not applicable.</p>

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Factors influencing information overload among breast cancer patients in the information explosion era: a cross-sectional study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月9日

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  • Jiahao Wei,
  • Enqing Liu,
  • Jing Xie,
  • Pengfei Wang,
  • Ziye Bai,
  • Honglang Jiang,
  • Yue Xiong,
  • Liu Bai,
  • Jin Zhou

摘要

Background

In the digital age, the proliferation of information frequently leads to Cancer Information Overload (CIO) among breast cancer (BC) patients. CIO results in difficulties with decision-making and compromises patients’ quality of life. Previous studies have primarily focused on the adverse outcomes of CIO, but research on its antecedents remains limited. Therefore, this study investigates the factors influencing CIO among BC patients.

Methods

A single-center, cross-sectional study was conducted from February to August 2025. A convenience sampling method was employed to recruit 598 patients with BC from a tertiary traditional Chinese medicine (TCM) hospital in Guangdong Province. Participants completed a sociodemographic questionnaire, the Cancer Information Overload Scale (CIOS), the Digital Health Literacy Scale (DHLS), an asthenopia questionnaire, and the Depression, Anxiety, and Stress Scale (DASS-21). Data were analyzed using independent-samples t-tests, one-way analysis of variance, Pearson correlation analysis, and multiple linear regression analysis in SPSS.

Results

Univariate analysis identified several significant influencing factors, including occupation, location, education level, caregiver, disease course, treatment, and comorbidities. Bivariate analysis revealed positive correlations between CIO and both asthenopia and depression. Multiple linear regression analysis further demonstrated that asthenopia, digital health literacy, education level, comorbidities, disease course, depression, and type of caregiver were significant predictors. Collectively, these variables explained 74.9% of the total variance in CIO.

Conclusion

CIO is highly prevalent among BC patients. Tailored intervention strategies based on the identified predictive factors are essential. These include optimizing health information delivery channels, incorporating multi-subject social resources, and delivering psychocognitive interventions.

Clinical trial number

Not applicable.