Social media platforms such as Facebook, Twitter, and YouTube have revolutionized the distribution of health information by facilitating rapid dissemination and extensive outreach to general populations.Reference Moorhead, Hazlett and Harrison 1 WeChat, a popular social media platform in China, serves as a significant health information hub for its 1 billion monthly users.Reference Tso 2 It supports diverse content like text, images, and videos and allows sharing through public accounts and group chats for easy access to health-related information.Reference Ma, Lu and Liu 3 Research indicates that WeChat effectively delivers health information, with 90.6% of users obtaining it through health-related public accounts and group chats.Reference Zhang, Wen and Liang 4 Previous studies have explored the feasibility of using WeChat for educational purposes, such as problem-based learning in dental practical clerkships, and found that it improves students’ learning experience and outcomes.Reference Zhang, Li and Li 5 However, misinformation is a challenge on WeChat, as false health information can spread rapidly.Reference Wang, McKee and Torbica 6
Knowledge, Attitude, and Practice (KAP) studies are essential tools for understanding how a population acquires and processes information and how this information influences their behavior. KAP studies provide valuable insights into public health awareness, policy implementation, and the efficacy of health promotion campaigns.Reference Raina 7 , Reference Goldstein, MacDonald and Guirguis 8 Several KAP studies have been conducted to assess the impact of WeChat public accounts on health-related knowledge, attitudes, and practices in China and internationally.
For instance, Zhang et al. investigated the utilization of WeChat public accounts for health information acquisition among the general public in China and reported that 74.6% of respondents accessed health information via these accounts.Reference Zhang, Wen and Liang 4 Similarly, Li et al. conducted a KAP study on COVID-19 among Chinese workers and identified WeChat as one of the 3 primary sources of COVID-19-related information.Reference Li, Zhang and Zhong 9 Additionally, a study has demonstrated that a WeChat health education program Significantly enhanced malaria health literacy among Chinese expatriates in Niger.Reference Li, Han and Guo 10 These findings highlight the necessity of conducting comparable KAP assessments in China to elucidate the role of WeChat in disseminating health-related information to the general public.
Existing research on WeChat and health-related information has predominantly addressed its effectiveness and prevalence; however, there is a lack of studies examining the KAP regarding the acceptance of health science information. This study aims to evaluate the KAP of WeChat users concerning health-related public accounts and their receptiveness to health-related information. Additionally, the study seeks to identify factors associated with these dimensions.
Methods
Study Design and Participants
This cross-sectional study was conducted at Shandong Provincial Third Hospital, Jinan, Shandong, China, from April 2022 to November 2022. Participants included WeChat users who were able and willing to complete the survey. Exclusion criteria comprised individuals who were unconscious, unable to communicate effectively, or unwilling to participate. A QR code for the questionnaire was generated using Questionnaire Star.Reference Zhu, Sun and Jin
11 A QR code distribution center was established at Shandong Provincial Third Hospital, where WeChat users could scan the code to access the questionnaire and provide informed consent. The minimum sample size was calculated using the formula for sample size determination:
$ \mathrm{n}={\left(\frac{Z_{1-\alpha /2}}{\delta}\right)}^2\times p\times \left(1-p\right) $
, with a significance level (α) set at 0.05, a standard normal deviate (Z1-2/α) of 1.96, a margin of error (δ) of 0.05, and an estimated proportion (p) of 0.5.Reference Serdar, Cihan and Yücel
12 The required minimum sample size was determined to be 384 respondents. Participants completed the questionnaire voluntarily. Data were recorded in an Excel spreadsheet, and a member of the research team verified the completeness, consistency, and validity of all questionnaires. Ethical exemption for this study was obtained from the Medical Ethics Committee of Shandong Provincial Third Hospital, and informed consent was obtained from all participants prior to questionnaire completion.
Questionnaire
The questionnaire was designed based on previous studies.Reference Powell, Inglis and Ronnie 13 , Reference Bender, Cyr and Arbuckle 14 A pilot study involving a sample of 51 participants was conducted to test the reliability and validity of the questionnaire. The reliability test demonstrated a high internal consistency among the questions, as evidenced by a Cronbach’s α value of 0.892. Additionally, the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy for factor analysis was 0.636, confirming the suitability of the questionnaire for factor analysis.
The final questionnaire, presented in Chinese, contained 4 dimensions: demographic information (gender, age, marital status, education, monthly household income, occupation type, and physical condition), knowledge, attitude, and practice.
The knowledge dimension comprised 10 questions, scored with 1 point for a correct answer and 0 points for an incorrect or unclear answer. The attitude dimension included 16 questions, each rated on a 5-point Likert scale ranging from strongly agree (5 points) to strongly disagree (1 point), except for questions A5, A6, and A7, which were reverse-scored. The practice dimension consisted of 6 questions, with P1 and P2 scoring from 5 (always) to 1 (never), P3 and P4 scoring from 5 (Yes) to 1 (No and Not Sure), and P5 and P6 being open-ended questions without assigned scores. These scoring differences reflect the diverse assessment objectives of each dimension: knowledge was evaluated based on factual accuracy using a binary scoring system, attitude was measured through opinions with a Likert scale, and practice was assessed based on behaviors using frequency and yes/no response scales. The total raw scores for knowledge (ranged from 0 to 10), attitude (16 to 80), and practice (4 to 20) were converted into percentages. Scores were classified as good (75% and above), moderate (51-74%), and poor (50% or less) for knowledge, attitude, and practice, respectively.Reference Baig, Jameel and Alzahrani 15 , Reference Al-Mutawaa, Farghaly and Nasir 16
Statistical Analysis
Statistical analysis was conducted using Stata 17.0. Descriptive analyses were performed on the demographic information and KAP scores of the respondents. For normally distributed data, the mean and standard deviation were utilized, while the median and range or interquartile range were employed for non-normally distributed data. The count information for each question answer, stratified by different demographic characteristics, was expressed as n (%).
To compare differences in scores on the knowledge, attitude, and practice dimensions among respondents with varying demographic characteristics, continuous variables were first tested for normality. If the data conformed to a normal distribution, t tests were used to compare scores between the 2 groups. For data that did not conform to a normal distribution, Wilcoxon-Mann-Whitney tests were employed. For continuous variables with 3 or more groups that met the criteria of normal distribution and homogeneous variances, the Kruskal-Wallis analysis of variance was utilized to compare scores across multiple groups. Data were presented as mean ± standard deviation. Pearson correlation analysis was conducted to evaluate the correlation among the 3 dimensions. Variables with P values <0.05 in univariate regression were included in the multivariate analysis, using a 70% score cutoff and incorporating all baseline informative variables.
Results
Participant Characteristics and Scores on Knowledge, Attitude, and Practice Dimensions
The demographic characteristics and scores of the participants on knowledge, attitude, and practice dimensions are summarized in Table 1. A total of 980 questionnaires were distributed. After excluding responses with conflicting answers to the trap question, 567 questionnaires remained, resulting in a valid response rate of 57.9%. Following data collection, the reliability and validity of the questionnaire were re-examined, yielding a Cronbach’s α coefficient of 0.934 and a KMO value of 0.877.
Knowledge, attitude, and practice scores by demographic variables
The mean scores for knowledge, attitude, and practice were 6.12 ± 2.29 (61.2% of the total), 55.83 ± 7.33 (69.8% of the total), and 14.07 ± 3.72 (70.4% of the total), respectively. Significant associations were observed between participants’ demographic characteristics and their scores on the knowledge and practice dimensions. Specifically, age (P < 0.001 for knowledge, P = 0.003 for practice), marital status (P < 0.001 for knowledge, P = 0.008 for practice), education level (both P < 0.001), income (both P < 0.001), occupation type (P < 0.001 for knowledge, P = 0.019 for practice), and physical condition (both P < 0.001) were significantly associated with knowledge and practice scores.
Participants aged 31-40 years, those with postgraduate education, a monthly household income exceeding 20 001 Chinese Yuan, good physical condition, and those employed as professional and technical personnel demonstrated higher mean scores for knowledge and practice compared to their counterparts (all P < 0.01). Moreover, participants with excellent physical conditions exhibited significantly more positive attitudes than other groups (P < 0.001).
An Assessment of Participants’ Knowledge, Attitude, and Practice Toward Health-Related Public Accounts
As shown in Table S1, participants demonstrated higher knowledge on questions related to the categorization and functions of health-related WeChat public accounts (correct rates = 68.61% and 69.49%, respectively), risk factors for diseases (correct rates = 65.26% and 78.66%, respectively), the definition of “three highs” (correct rate = 76.01%), and the benefits of regular physical examinations (correct rate = 75.13%). Conversely, participants exhibited lower knowledge on questions concerning the positive effects and drawbacks of health-related public accounts (correct rates = 13.23% and 43.92%, respectively).
The majority of participants expressed a positive attitude towards utilizing medical-related public accounts, as evidenced by their responses of “strongly agree” and “agree” for most positively scored questions (Figure 1). However, several questions raised concerns, such as over 60% of participants agreeing that they had no doubts about the professionalism and authenticity of the content provided by public accounts and a strong desire for timely news updates (questions A5, A6, and A7). Questions A8 to A12 assessed the level of trust respondents had for content provided by government departments, medical institutions, traditional health media, internet media, and personal medical accounts, with trust decreasing in order from government departments to personal medical accounts. Personal medical accounts exhibited the lowest level of trust and tended towards neutrality regarding the content they disseminated.
Attitudes of WeChat users towards health-related public accounts.
In the practice assessment (Table S2), the majority of WeChat users frequently read health-related articles (87.4% in total) and verify the authenticity of health information released by these accounts (71.61% in total). Additionally, a high percentage of participants were willing to apply health behavior recommended by these accounts to their daily lives (70.19%) and share this information with others (66.14%).
The majority of participants followed and subscribed to medical institution public accounts, with 75.49% (428/567) of responses, followed by government departmental public accounts, with 67.20% (381/567) of responses. Traditional media public accounts had 51.85% (294/567) of responses, certified internet institution public accounts had 45.68% (259/567) of responses, and personal public accounts had the fewest followers, with only 23.63% (134/567) of participants following and subscribing to them. The primary reasons for following and subscribing to health-related public accounts were to gain knowledge (79.01%), followed by finding treatment options for oneself or family members (53.97%). The least common reason was to pass the time (27.51%). Overall, the results suggest that WeChat public account users have a positive attitude towards accepting health science information and are willing to apply it to their daily lives and share it with others.
Correlation Analysis of Knowledge, Attitude, and Practice
As shown in Table 2, the analysis revealed a non-significant positive correlation between knowledge and attitude (r = 0.047, P = 0.263). However, significant positive correlations were observed between knowledge and practice (r = 0.392, P < 0.001) and between attitude and practice (r = 0.319, P < 0.001).
Correlation coefficients between knowledge, attitude, and practice scores
Identification of Independent Factors Related to Knowledge, Attitudes, and Practices
To identify independent factors associated with knowledge, attitudes, and practices, we performed univariate analysis, and variables with a P value < 0.05 were included in a multivariate analysis (Table 3–5). As shown in Table 3, age, marital status, education, income, occupation type, and physical condition were all significantly associated with knowledge scores. Specifically, individuals with a higher level of education [OR = 7.09 (2.30, 21.87), P = 0.001] and higher monthly household income were more likely to have higher knowledge scores [OR = 3.30 (1.63, 6.70), P = 0.001), while individuals aged over 60 years [OR = 0.07 (0.01, 0.56), P = 0.012] or with poor physical condition [OR = 0.20 (0.05, 0.72), P = 0.014] were more likely to have lower knowledge scores. Regarding attitudes, participants with good [OR = 0.42 (0.26, 0.68), P < 0.001] or average [OR = 0.29 (0.16, 0.51), P < 0.001] physical condition were less likely to have positive attitudes compared to those with excellent physical condition (Table 4). In terms of practice scores, participants over 60 years old [OR = 0.29 (0.09, 0.91), P = 0.034], married [OR = 2.11 (1.04, 4.29), P = 0.038], and with a monthly income exceeding 20,000 yuan [OR = 2.42 (1.23, 4.75), P = 0.010] were more likely to have higher practice scores. Physical condition was negatively correlated with practice scores, with individuals in average [OR = 0.45 (0.24, 0.85), P = 0.014] or poor [OR = 0.20 (0.07, 0.58), P = 0.003] physical condition being less likely to engage in health-related practices (Table 5).
Univariate and multivariate analysis of knowledge scores
Univariate and multivariate analyses of attitude scores
Univariate and multivariate analyses of practice scores
Strengths and Limitations
The strengths of this study lie in its comprehensive assessment of KAP regarding health-related public accounts on WeChat among Chinese users. This study not only provides insights into participants’ KAP towards health information dissemination on WeChat but also identifies demographic factors associated with these dimensions. The rigorous data collection methods and statistical analyses, including Cronbach’s α coefficient and correlation analysis, ensure the reliability and validity of the findings. Furthermore, the multivariate analysis identifies independent factors influencing participants’ KAP, thereby enhancing the robustness of the results.
However, several limitations should be acknowledged. Firstly, the study was conducted in Shandong province, China, and the results may not be generalizable to other regions or countries. Future studies should aim to increase the sample size and include participants from multiple regions and diverse backgrounds to improve the generalizability of the results. Secondly, the study relied on self-reported measures, which may be subject to response bias. Future research should consider using more objective measures to assess participants’ knowledge, attitudes, and practices. Thirdly, as a cross-sectional, and thus, causality cannot be inferred. Longitudinal designs should be employed in future studies to examine the causal relationships between exposure to health-related public accounts and health outcomes.
Discussion
Statement of Principal Findings
In this study, we analyzed 567 valid questionnaires to assess WeChat users’ KAP towards health-related public accounts. The mean scores for knowledge, attitude, and practice were 61.2%, 69.8%, and 70.4%, respectively. Significant positive correlations were observed between knowledge and practice, and between between attitude and practice. Independent factors associated with KAP scores included age, marital status, education, income, occupation type, and physical condition. These findings corroborate previous research, suggesting that sociodemographic and physical health factors significantly influence eHealth engagement.Reference Reiners, Sturm and Bouw 17
Interpretation Within the Context of the Wider Literature
Our findings align with the concept of eHealth, which involves the use of information and communication technologies for health-related purposes.Reference Smith, Thomas and Snoswell 18 Social media platforms, such as Twitter, Facebook, and WeChat, can serve as eHealth tools for various health-related objectives.Reference Smailhodzic, Hooijsma and Boonstra 19 Our results demonstrated that higher education, increased monthly household income, better physical condition, and professional or technical occupations were associated with higher knowledge and practice scores regarding health-related public accounts. Consistent with our findings, previous studies have identified positive associations between higher education, income, and better self-reported health with eHealth usage.Reference Kontos, Blake and Chou 20 Higher education and better self-rated health have also been linked to online health information-seeking behavior.Reference Nolke, Mensing and Kramer 21 However, one study noted that while higher income was positively associated with eHealth literacy, education level did not show a significant relationship among baby boomers and older adults.Reference Tennant, Stellefson and Dodd 22 These variations suggest that the relationship between these factors and social media usage may vary across different demographics.
Our study demonstrated a positive association between good physical condition and higher knowledge and practice scores. Similarly, a study focused on Chinese college students found that female students in good health, who spent more time browsing social media and frequently used official and public social media, were more likely to exhibit high levels of knowledge, attitudes, and practices regarding COVID-19 vaccination.Reference Qin, Shi and Duan 23 Both studies indicated that good physical condition is an important factor associated with health-related knowledge and behaviors, highlighting the importance of considering physical health status when designing health promotion programs and interventions.
The majority of participants in this study exhibited a preference for following and subscribing to medical institutions and government departmental public accounts, suggesting that social media users tend to trust and seek health-related content from authoritative sources. This inclination may stem from an awareness of the potential for misinformation.Reference Suarez-Lledo and Alvarez-Galvez 24 Consistent with our findings, a systematic review revealed that users generally prefer obtaining health information from reliable sources such as health professionals, government health departments, and reputable organizations.Reference Moorhead, Hazlett and Harrison 1 Additionally, Kalyanam et al. have found that Twitter users engaged with health-related content from credible sources, such as health organizations, government agencies, and individual experts.Reference Kalyanam and Katsuki 25 These results collectively suggest a general preference for credible sources among social media users.Reference Song, Omori and Kim 26
However, a study on the spread of news on Twitter discovered that false information tended to spread more quickly and widely than true information, implying that users sometimes prioritize sensational or engaging content over the credibility of the source.Reference Vosoughi, Roy and Aral 27 Additionally, another study found that medical fake news was widely shared and engaged with on social media, indicating that users may not consistently consider the credibility of the source when interacting with health information.Reference Waszak, Kasprzycka-Waszak and Kubanek 28 Our study revealed that most WeChat users frequently read health-related articles and verify the authenticity of health information. However, over 60% of participants agreed that they had no doubts about the professionalism and authenticity of the content pushed by public accounts. While these findings may appear contradictory, they reflect the complexity of user behavior, trust, and health information verification on social media. Users may be proactive in seeking accurate health information, but their trust in reputable sources could lead to less scrutiny of the content they follow.Reference Majerczak and Strzelecki 29 A study by Park et al. examined Reddit users’ engagement with health-related content and found that users preferred to receive health information from reputable sources and frequently verified the accuracy of the information by fact-checking and questioning dubious claims.Reference Park, Conway and Chen 30 These findings highlight the importance of disseminating reliable health information through trustworthy WeChat health-related public accounts while encouraging users to critically evaluate content, thereby ensuring the reliability and usefulness of information shared and consumed on the platform.
Implications for Policy, Practice, and Research
In our study, the main reasons for following and subscribing to health-related public accounts were to acquire knowledge and to find treatment options for oneself or family members. Similar studies have demonstrated that health information-seeking is a primary motivation for social media use, with users frequently searching for information for themselves or others.Reference Chou, Prestin and Lyons 31 Additionally, users engage with social media for various health-related purposes, such as obtaining knowledge, sharing experiences, and providing support to others.Reference Korda and Itani 32 Both patients and health professionals use social media primarily for health-related purposes like gaining knowledge, exchanging experiences, and accessing emotional and practical support.Reference Antheunis, Tates and Nieboer 33 These findings suggest that users primarily follow health-related public accounts on social media to acquire health knowledge and seek treatment options. This highlights the importance of accessing credible sources and accurate information to prevent the spread of misinformation.
Conclusions
In conclusion, the study suggests that WeChat public account users in China exhibit a positive attitude towards accepting health science information and are willing to apply it to their daily lives and share it with others. While highlighting the effectiveness of WeChat as a health communication platform in China, the study emphasizes the need for strategies tailored to demographic characteristics to enhance engagement and trust. By focusing on the quality and interactivity of content, these strategies can improve the dissemination and application of health information among users. Future research plans should aim to expand the demographic scope to ensure broader generalizability.
Supplementary material
The supplementary material for this article can be found at http://doi.org/10.1017/dmp.2024.154.
Data availability statement
The data presented in this study are available in the article.
Acknowledgments
We thank all the staff for their efforts in subject recruitment, data collection, and statistical analysis, and all the participants who took part in this study. We also acknowledge the project funding support from the Health Commission of Shandong Province and Shandong Provincial Third Hospital.
Author contribution
Yanan Wang and Qiong Zhang carried out the studies, participated in data collection, and drafted the manuscript. Qiong Zhang, Yanan Wang, and Peiqiang Liu performed the statistical analysis and participated in the study design. All authors read and approved the final manuscript.
Funding statement
This work was supported by “The Key Project of Health Policy Research of Shandong Province in 2022 by the Health Commission of Shandong Province” (WZY202243).
Competing interest
No known conflict of interest.
Ethical standard
This was conducted in accordance with the Declaration of Helsinki (2000) of the World Medical Association. The ethical exemption was granted by the Medical Ethics Committee of Shandong Provincial Third Hospital. Informed consent was obtained from all participants before they completed the questionnaire.
Open access
