JMIR Publications

ABSTRACT

Background:

Currently, breast cancer is the most commonly diagnosed cancer and the sixth leading cause of cancer-related deaths among Chinese women. Worse still, misinformation contributes to the aggravation of breast cancer burden in China. There is a pressing need to investigate susceptibility to breast cancer misinformation among Chinese patients. However, no study has been performed in this respect.

Objective:

This study aimed to ascertain Chinese patients’ susceptibility to breast cancer misinformation to inform clinical practice, health education, medical research, and public health policy-making.

Methods:

We first designed a questionnaire comprising information in 4 sections: age, gender, and education (Section 1), self-assessed disease knowledge (Section 2), the All Aspects of Health Literacy Scale (AAHLS), the eHealth Literacy Scale (eHEALS), the General Health Numeracy Test (GHNT-6), and the ‘Internal’ sub-scale of the Multidimensional Health Locus of Control (MHLC) Scales (Section 3), and 10 breast cancer myths collected from some officially registered and authenticated websites (Section 4). Subsequently, we recruited patients from Qilu Hospital Affiliated to Shandong University, China, using randomized sampling. And then, the questionnaire was administered via wenjuanxing, the most popular online survey platform in China. The collected data were manipulated in an EXCEL file. We manually checked the validity of each questionnaire using the predefined validity criterion. After that, we coded all valid questionnaires according to the predefined coding scheme, based on Likert scales of different point (score) ranges for different sections of the questionnaire. In the following step, we calculated the sums of the subsections of the AAHLS, and the sums of the 2 health literacy scales (eHEALS and GHNT-6) and the 10 breast cancer myths. Finally, we applied the logistic regression modelling to relate the scores in Section 4 to the scores in Sections 1-3 of the questionnaire, to identify what significantly contributed to susceptibility to breast cancer misinformation among Chinese patients.

Results:

All 447 questionnaires collected were valid according to the validity criterion. The patient participants were aged 38.29 (SD=11.52) on average. The mean score for their education was 3.68 (SD=1.46), implying that their average educational attainment was between Year 12 and diploma (junior college). 77.85% of the 447 participants were women. The mean score for their self-assessed disease knowledge was 2.50 (SD=0.92), indicating that their self-assessed disease knowledge status was between ‘knowing a lot’ and ‘knowing some.’ The mean scores of the sub-constructs in the AAHLS were 6.22 (SD=1.34) for functional health literacy, 5.22 (SD=1.54) for communicative health literacy, and 11.19 (SD=1.99) for critical health literacy. The mean score for eHealth literacy was 24.21 (SD=5.49). The mean score for each question in the GHNT was determined at 1.57 (SD=0.49), 1.21 (SD=0.41), 1.24 (SD=0.43), 1.90 (SD=0.30), 1.82 (SD=0.39), and 1.73 (SD=0.44), respectively. The mean score for the patients’ health beliefs and self confidence was 21.19 (SD=5.63). The average score for their response to each myth ranged from 1.24 (SD=0.43) to 1.67 (SD=0.47), and the mean score for responses to the 10 myths was 14.03 (SD=1.78). Through interpreting these descriptive statistics, we found that Chinese female patients’ limited ability to rebut breast cancer misinformation was mainly attributed to 5 factors, including (1) lower communicative health literacy, (2) certainty about self-assessed digital health literacy skills, (3) lower general health numeracy (4) positive self-assessment of general disease knowledge, and (5) more negative health beliefs and lower levels of self confidence.

Conclusions:

Drawing on logistic regression modelling, we studied susceptibility to breast cancer misinformation among Chinese patients. These predicting factors of susceptibility to breast cancer misinformation identified in this study can provide insightful implications for clinical practice, health education, medical research, and health policy-making.