Background: Previous studies have revealed that functional health literacy plays a less important role than communicative and critical health literacy (CRHL) and that communicative literacy and CRHL contribute more to better patient self-management. Although improving health literacy has been identified as an approach to fostering community involvement and empowerment, CRHL may be regarded as the neglected domain of health literacy, rarely achieving any focus or interventions that claim to be working toward this outcome. Considering this research background, close scholarly attention needs to be paid to CRHL and its associated factors. Objective: This study aimed to assess CRHL and identify essential factors closely associated with the status of CRHL among Chinese patients and to provide some implications for clinical practice, health education, medical research, and public health policy making. Methods: We conducted this cross-sectional study, which lasted from April 8, 2022, to September 23, 2022, following the steps below. We first designed a 4-section survey questionnaire and then recruited Mandarin Chinese–speaking patients from Qilu Hospital of Shandong University, China, using randomized sampling. Subsequently, we administered the questionnaire via wenjuanxing, the most popular web-based survey platform in China, between July 20, 2022, and August 19, 2022. Finally, we used latent class modeling to analyze the valid data collected to classify the patient participants and identify the factors potentially associated with different CRHL levels. Results: All data in the 588 returned questionnaires were valid. On the basis of the collected data, we classified the patient participants into 3 latent classes of limited, moderate, and adequate CRHL and identified 4 factors associated with limited CRHL, including middle and old age, male sex, lower educational attainment, and low internal drive to maintain one’s health. Conclusions: Using latent class modeling, we identified 3 classes of CRHL and 4 factors associated with limited CRHL among the Chinese study participants. These literacy classes and the predicting factors ascertained in this study can provide some implications for clinical practice, health education, medical research, and health policy making.

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 the breast cancer burden in China. There is a pressing need to investigate the susceptibility to breast cancer misinformation among Chinese patients. However, no study has been performed in this respect. Objective: This study aims to ascertain whether some demographics (age, gender, and education), some health literacy skills, and the internal locus of control are significantly associated with the susceptibility to misinformation about all types of breast cancers among randomly sampled Chinese patients of both genders in order to provide insightful implications for clinical practice, health education, medical research, and health policy making. Methods: We first designed a questionnaire comprising 4 sections of information: 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 6-item General Health Numeracy Test (GHNT-6), and the “Internal” subscale 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 of Shandong University, China, using randomized sampling. The questionnaire was administered via wenjuanxing, the most popular online survey platform in China. The collected data were manipulated in a Microsoft 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 subsequent step, we calculated the sums of the subsections of the AAHLS and the sums of the 2 health literacy scales (the eHEALS and GHNT-6) and the 10 breast cancer myths. Finally, we applied logistic regression modeling to relate the scores in section 4 to the scores in sections 1-3 of the questionnaire to identify what significantly contributes to the susceptibility to breast cancer misinformation among Chinese patients. Results: All 447 questionnaires collected were valid according to the validity criterion. The participants were aged 38.29 (SD 11.52) years 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 a diploma (junior college). Of the 447 participants, 348 (77.85%) 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 subconstructs 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 the 6 questions in the GHNT-6 was 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 mean 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 is mainly attributed to 5 factors: (1) lower communicative health literacy, (2) certainty about self-assessed eHealth 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 modeling, we studied the susceptibility to breast cancer misinformation among Chinese patients. The predicting factors of the susceptibility to breast cancer misinformation identified in this study can provide insightful implications for clinical practice, health education, medical research, and health policy making.

Background: Long non-coding RNAs (lncRNAs) in extracellular vesicles (EVs) have been confirmed as effective non-invasive biomarkers for multiple diseases. However, their expression and clinical value in gastric cancer (GC) remain poorly understood.Materials and methods: Serum EV RNA was extracted from four patients with GC and four healthy controls, followed by high-throughput RNA sequencing. LncRNAs were further validated in training and validation sets using quantitative real-time reverse transcription polymerase chain reaction.Results: A total of 37,684 lncRNAs were obtained, and 10 lncRNAs were selected based on the criteria (P < 0.05 and |log₂FoldChange| ≥1). Serum EV lncRNA RMRP, RPPH1, and linc-ROR were significantly higher in patients with GC than in those with chronic gastritis, atypical hyperplasia, or healthy control (all P < 0.05). Three lncRNAs were also significantly correlated with tumor diameter, lymphatic metastasis, distal metastasis, and TNM stage (all P < 0.05). The area under the curve (AUC) values for lncRNA RMRP, RPPH1, and linc-ROR were 0.727, 0.774, and 0.811, respectively. Corresponding sensitivity and specificity were 63.4% and 85.4%, 50.7% and 89.6%, and 78.5% and 66.7%. The combination of these three lncRNAs with carcinoembryonic antigen (CEA) yielded an AUC of 0.909, with a sensitivity and specificity of 83.3% each. Furthermore, high EV linc-ROR and RMRP expression levels were associated with worse disease-free survival and overall survival (OS). Univariate and multivariate Cox regression analyses confirmed that linc-ROR was the only independent prognostic factor for GC. Finally, the lncRNA-miRNA-mRNA network showed that three lncRNAs were predicted to interact with 15 miRNAs and 69 mRNAs. In addition, lncRNA RMRP and linc-ROR were correlated with immune cell infiltration, including neutrophils, central memory CD4 T cells, macrophage, and natural kill T cells.Conclusion: EV lncRNAs are prospective biomarker and correlated with immune cell infiltration in GC. It provides a foundation for the development of serum EV-targeted novel biomarkers and immunotherapy targets of GC.

Background: Poor functional health literacy has been found to be independently associated with poor self-assessed health, poor understanding of one’s health condition and its management, and higher use of health services. Given the importance of functional health literacy, it is necessary to assess the overall status of functional health literacy in the general public. However, the literature review shows that no studies of functional health literacy have been conducted among the Chinese population in China. Objective: This study aimed to classify Chinese populations into different functional health literacy clusters and ascertain significant factors closely associated with low functional health literacy to provide some implications for health education, medical research, and public health policy making. Methods: We hypothesized that the participants’ functional health literacy levels were associated with various demographic characteristics. Therefore, we designed a four-section questionnaire including the following information: (1) age, gender, and education; (2) self-assessed disease knowledge; (3) 3 validated health literacy assessment tools (ie, the All Aspects of Health Literacy Scale, the eHealth Literacy Scale, and the 6-item General Health Numeracy Test); and (4) health beliefs and self-confidence measured by the Multidimensional Health Locus of Control Scales Form B. Using randomized sampling, we recruited survey participants from Qilu Hospital affiliated to Shandong University, China. The questionnaire was administered via wenjuanxing. A returned questionnaire was valid only when all question items included were answered, according to our predefined validation criterion. All valid data were coded according to the predefined coding schemes of Likert scales with different point (score) ranges. Finally, we used latent class analysis to classify Chinese populations into clusters of different functional health literacy and identify significant factors closely associated with low functional health literacy. Results: All data in the 800 returned questionnaires proved valid according to the predefined validation criterion. Applying latent class analysis, we classified Chinese populations into low (n=292, 36.5%), moderate-to-adequate (n=286, 35.7%), and low-to-moderate (n=222, 27.8%) functional health literacy groups and identified five factors associated with low communicative health literacy: (1) male gender (aged 40-49 years), (2) lower educational attainment (below diploma), (3) age between 38 and 68 years, (4) lower self-efficacy, and (5) belief that staying healthy was a matter of luck. Conclusions: We classified Chinese populations into 3 functional health literacy groups and identified 5 factors associated with low functional health literacy. These associated factors can provide some implications for health education, medical research, and health policy making.

Background: eHealth resources and interventions promise to promote favorable behavior change, self-efficacy, and knowledge acquisition, thereby improving health literacy. However, individuals with limited eHealth literacy may find it difficult to identify, understand, and benefit from eHealth use. It is necessary to identify the self-assessed eHealth literacy of those who use eHealth resources to classify their eHealth literacy levels and to determine the demographic characteristics associated with higher and lower eHealth literacy skills. Objective: This study aimed to identify notable factors closely associated with limited eHealth literacy among Chinese male populations to provide some implications for clinical practice, health education, medical research, and public health policy making. Methods: We hypothesized that participants’ eHealth literacy status was associated with various demographic characteristics. Therefore, we elicited the following information in the questionnaire: age and education, self-assessed disease knowledge, 3 well-developed health literacy assessment tools (ie, the All Aspects of Health Literacy Scale, eHealth Literacy Scale, and General Health Numeracy Test), and the 6 Internal items on health beliefs and self-confidence in the Multidimensional Health Locus of Control Scales. Using randomized sampling, we recruited survey participants from Qilu Hospital of Shandong University, China. After validating the data collected through a web-based questionnaire survey via wenjuanxing, we coded all valid data according to predefined coding schemes of Likert scales with different point (score) ranges. We then calculated the total scores of the subsections of the scales or the entire scale. Finally, we used logistic regression modeling to associate the scores of the eHealth Literacy Scale with the scores of the All Aspects of Health Literacy Scale, the General Health Numeracy Test-6, and age and education to ascertain factors considerably associated with limited eHealth literacy among Chinese male populations. Results: All data from the 543 returned questionnaires were valid according to the validation criteria. By interpreting these descriptive statistics, we found that 4 factors were significantly correlated with participants’ limited eHealth literacy: older age, lower education attainment, lower levels of all aspects of health literacy (functional, communicative, and critical), and weaker beliefs and self-confidence in internal drivers and strengths to stay healthy. Conclusions: By applying logistic regression modeling, we ascertained 4 factors that were significantly correlated with limited eHealth literacy among Chinese male populations. These relevant factors identified can inform stakeholders engaging in clinical practice, health education, medical research, and health policy making.

Previous observational studies have suggested a potential association between heart rate variability (HRV) and cerebrovascular disease. However, a causal relationship between the two has not yet been established. The objective of this study was to determine the causal relationship between heart rate variability (HRV) and stroke through a two-sample Mendelian randomization analysis. Three genetic predictive traits of heart rate variability standard deviation of the normal-to-normal interbeat intervals (SDNN), the root mean square of the successive differences of interbeat intervals (RMSSD), and the peak-valley respiratory sinus arrhythmia or high-frequency power (pvRSA/HF) were collected from publicly available genome-wide association studies (IEU Open GWAS). Additionally, stroke (STROKE) and its sub-types: ischemic stroke (IS), cardioembolic stroke (CES), small vessel stroke (SVS), large artery stroke (LAS), lacunar stroke (LS), and intracerebral hemorrhage (ICH)were also from this database. Two-sample Mendelian randomization and various sensitivity analyses were employed to explore the causal relationship between HRV and stroke and its sub-types. Inverse-variance weighted (IVW) was the primary method via which Mendelian randomization (MR) was conducted, and for the causal estimates determined by IVW, a series of sensitivity analyses were performed to assess the reliability of the results. (i) Four additional MR methods that complement IVW were utilized; (ii) Cochran's Q-test was employed for assessing heterogeneity; (iii) the MR-Egger's intercept test and MR-PRESSO global test were applied to assess the level of multivariate validity, and (iv) the "leave-one-out" method was utilized to assess stability. Two of the genetically predictive traits of HRV (standard deviation of the normal-to-normal interbeat intervals [SDNN]) and (the peak-valley respiratory sinus arrhythmia or high-frequency power [pvRSA/HF]) were associated with IS (OR 0.63,95 %CI 0.42-0.95, P = 0.03), (OR 0.84, 95 %CI: 0.72-1.00; P = 0.04), and LAS (OR 135.93, 95 %CI: 7.19-2569.22; P = 0.05), (OR 1.42, 95 %CI: 1.02-1.98; P = 0.04) were significantly correlated in addition to (pvRSA/HF) and LS (OR 0.84, 95 %CI: 0.72-1.00; P = 0.04) were also causally associated. Neither was causally associated with other sub-types of stroke or hemorrhagic stroke. Another genetically predictive trait of HRV (the root mean square of the successive differences of interbeat intervals [RMSSD]) was not found to be significantly associated with stroke, its subtypes, or Intracerebral hemorrhage. This study provides genetic evidence supporting the causal effects of HRV (SDNN) on ischemic stroke (IS) and large artery stroke (LAS), as well as (pvRSA/HF) on ischemic stroke (IS), large artery stroke (LAS), and lacunar stroke (LS).