Online health communities (OHCs) provide a platform for the public to seek health information and health care, communicate with physicians, and interact with other users through posts and web-based messages, breaking the limitations of time and space [1]. There are multiple forms of OHCs in China, and they can be divided into the following three categories according to their functions: (1) For patients, to communicate with physicians to seek health care and health information, such as “haodaifu”; (2) For patients, to communicate with other patients, such as “tianmijiayuan”; and (3) For physicians, to communicate with other physicians, such as “dingxiangyuan.” Patients with simple and minor symptoms can consult physicians and also ask for help from physicians in other regions through OHCs instead of visiting health care institutions. Therefore, OHCs can help people maintain a healthy lifestyle and reduce the burden on the health care system and are beneficial for alleviating the situation in which the distribution of medical resources is uneven, use is low, and hospital congestion is serious in China [2]. For example, during the COVID-19 outbreak, OHCs took advantage of the telemedicine function [3] to provide medical services and health information for Chinese people under mandatory home or centralized social isolation [4].

For patient rehabilitation and health maintenance, following medical prescriptions and maintaining a healthy lifestyle are critical [5]. Without face-to-face meetings and physician monitoring, self-management plays an important role in rehabilitation. Patient compliance is a critical factor that influences the effectiveness of self-management, especially for chronic diseases [6]. Haynes et al [7] defined patient compliance as “the extent to which a person’s behavior (in terms of taking medications, following diets or executing lifestyle changes) coincides with medical or health advice.” Tustin [8] corroborated that treatment regimens can be effective only if patients are highly compliant with the physicians’ advice. Therefore, people who comply with treatment are healthier than their peers [9,10]. Khera et al [11] showed that patient compliance is conducive to the prevention of cardiovascular diseases.

Patient compliance has significant effects on the economy and society [12]. For example, physicians advise the public to isolate themselves at home during the COVID-19 outbreak, but some people do not comply and insist on going out without wearing a mask. Such noncompliance may cause the spread of COVID-19 and social panic, leading to economic losses. Fortunately, patient compliance can be improved through guidance and intervention because this parameter is dynamic [13]. In general, most patients may not intentionally refuse to comply with treatments and physicians’ advice but do not comply because of cognitive deficiency [13]. At times, psychosocial stress may cause individuals to have insufficient energy to conduct compliant activities.

Web-based health information can be divided into the following two categories [14-16]: (1) medical-related information, which can help patients choose suitable hospitals and physicians and cooperate with physicians to make decisions and address medical issues and (2) lifestyle-related information, such as maintaining a balanced diet, controlling weight, and exercising, which can help patients maintain a healthy lifestyle in daily life. Individual information behaviors have been extended to the context of the internet. As Wilson [17] defined, individual health information behaviors in OHCs include health information seeking, health information use, communication, and passive receiving health information behaviors. Patients are likely to seek health information before or after visiting physicians [18], which may substantially affect their cognition, health literacy, decision-making preferences, and health-related behaviors [19,20] such as patient compliance. For example, patients may be unwilling to comply with their physicians’ advice if they find that the health information from physicians is inconsistent with that obtained by themselves. Therefore, this study intends to explore ways to improve patient compliance by guiding patient health information–seeking behavior through OHCs.

In the OHCs discussed in this study, patients engage in social activities with other users (physicians and patients) [21]. Social factors are closely related to patient health-related behaviors, health outcomes, and adherence [22,23]. The perception of social presence enables patients to continuously use OHCs, trust other users [24], and gain positive emotions [25]. In addition, web-based social presence has a positive effect on offline health behaviors [26]. Perceived responsiveness encourages patients to repeatedly seek health information and share experiences through OHCs and also enhances their self-efficacy [27], thereby improving their health literacy and ability to manage themselves. The physician-patient relationship is an important social relationship in OHCs [28] and can exert a significant effect on patient compliance [29]. Through social interactions, patients can share their experiences and knowledge with other users and subsequently obtain health information in return [30].

Considerable research has focused on OHCs from a social perspective, but few have explored the effect of health information–seeking behavior on patient compliance from the mediating perspective of social factors. Moreover, this study was conducted in China, where health care system development differs from that in other countries and regions. Therefore, this study aims to identify the effect of patients’ health information–seeking behavior in OHCs on their compliance, considering the mediating effects of patients’ perceived social support, social presence, and responsiveness.

This study used multiple-item scales validated in previous studies to measure constructs covering the research variables. As shown in Multimedia Appendix 1, the survey items were measured using a 7-point Likert-type response format (strongly disagree=1, strongly agree=7). Specifically, the way patients seek health information in OHCs refers to “the way people search for and apply both active and passive information,” which was measured using a 4-item scale from Khazaee-Pool et al [63]. The effectiveness of health information–seeking in OHCs was measured using a 5-item scale adopted from Nambisan [49] combined with 2 previous studies [58,59]. Nambisan [49] likewise adapted a 5-item scale from Zimet et al [64] to measure social support. Perceived social presence was measured using a 5-item scale developed by Gefen and Detmar [65]. Perceived responsiveness was measured using a 3-item scale developed by Ridings et al [47]. A 5-item scale adopted by Laugesen et al [66] from Hausman [67] was used to measure patient compliance.

Before the investigation, we translated the English questionnaire into Chinese and considered the cross-cultural adaptation. In addition, several people with experience seeking health information through OHCs were invited to fill out the questionnaire and provide advice for revising the instrument in Chinese. Finally, we back-translated the Chinese questionnaire into English to evaluate whether the concepts between the 2 versions were consistent [68-70].

Considering the possible effects of demographic variables on patient health information–seeking behavior and other health-related behaviors, this study regarded age, gender, living area, and education level as control variables in the analysis. Age was self-reported by year. Gender (man=1, woman=2); living area (urban=1, rural=2); and education level (junior middle school or below=1, high school=2, junior college=3, bachelor’s degree=4, master’s degree=5, and PhD=6) were dummy coded.

The investigation was conducted anonymously in several Chinese OHCs in March 2020. The participants were Chinese people who had sought health information through OHCs within the previous month such that they could recall their relevant experiences and feelings. Of the 403 responses received, 332 were valid, with a validity rate of 82.4% (332/403). Table 1 shows that among the sample, 78.6% (261/332) were aged between 20 and 40 years, 59.3% (197/332) were woman, 69.9% (232/332) lived in urban areas, and 50% (166/332) had at least a bachelor’s degree. The demographics of our sample were consistent with those of OHC users characterized as young, woman, living in urban regions, and highly educated [28,71,72]. Thus, the sample can be used to analyze the research model.

Data analysis was conducted using the SPSS software (version 22.0; IBM Corp) and SmartPLS software (version 3.2.8; SmartPLS GmbH). Despite validation in previous studies, the scales were re-evaluated for reliability and validity because the specific background and participants of this study differ from those of previous studies. The Cronbach α was used to assess the reliability of scales. Table 2 presents the results, where each value was greater than the threshold of .700, indicating acceptable reliability [73]. Confirmatory factor analysis was used to analyze convergent and discriminant validity. The Kaiser-Meyer-Olkin value was .961, so the data could be used for factor analysis [74].

Tables 3 and 4 show the validity results, including composite reliability, average variance extracted (AVE), and correlations between constructs. All composite reliability values were greater than the cutoff value of .700, and the AVEs were greater than the cutoff value of .500. Therefore, convergent validity was acceptable [75]. The square root of the AVE of each construct exceeded the correlation coefficients between this construct and the other constructs [75]. Therefore, the discriminant validity of the instrument used in this study was acceptable.

In this study, we proved that the way and effectiveness of patients seeking health information in OHCs have positive effects on patient compliance, and patients’ perceived social support, social presence, and responsiveness from OHCs played mediating roles in the research model. This study presents theoretical contributions to future studies on patients’ web-based information behaviors, social factors of OHCs, and patient compliance. In addition, patient information seeking behavior in OHCs is investigated by using the social exchange theory together with the social information processing perspective, which enriches the application of the social exchange theory and the social information processing approach in the context of OHCs and the field of health care.

This study has several practical implications for improving patient compliance and guiding patient health information–seeking behaviors through OHCs. First, the effectiveness of patients seeking health information is the preferred perspective for improving patient compliance. As Nambisan’s [49] survey shows, the information-seeking effectiveness has an effect on patients’ perceived empathy in OHCs, and then Lu and Zhang [77] further proved that patients’ perceived empathy in OHCs has an effect on patient compliance. Therefore, the readability, reliability, relevance, and timeliness of the health information provided to OHC users require priority. For example, OHCs can strengthen the management and monitoring of information quality so that the effectiveness of seeking health information can be improved accordingly and make platforms easy and friendly to use to help patients seek information conveniently and quickly. In addition, physicians can help develop their patients’ ability to seek health information with high effectiveness.

Second, patient compliance can be improved by enriching the ways patients seek health information through OHCs. As summarized by Lu and Zhang [2], there are various ways for patients to seek health information through OHCs, such as communicating with physicians, interacting with other members (ie, posts and web-based private messages), and browsing consultation text and posts, which can help prompt patients’ social feelings. Jiang and Street [56], Li and Mao [78], and Resnick et al [46] proved that patients communicating with physicians through web-based platforms would perceive more social support, social presence, and responsiveness, respectively, supporting our findings. In addition, as diagnoses and therapies vary from person to person, simply browsing others’ posts and consultation text might not help patients seek suitable and reliable high-quality health information and may even cause misdiagnosis. For example, Guan et al [79] proved that the predictors of severe scrub typhus in pediatric patients are different from those in elderly patients and that therapies are also different. Hence, physicians can encourage their offline patients to seek health information through OHCs in various ways, and OHCs can provide detailed guidelines regarding different methods of seeking health information for users.

Patients using OHCs is a necessary prerequisite for improving effectiveness and enriching the ways of patient information–seeking behavior. Undoubtedly, patients do not have to use OHCs, especially those who do not have adequate eHealth literacy. Lu and Zhang [80] found that patients with inadequate eHealth literacy might be unable to achieve high effectiveness in seeking health information through OHCs. However, patients may inevitably contact OHCs because of the convenience of the internet, especially in China. To specify, on the one hand, physicians who practice in some Chinese OHCs, such as “haodaifu,” must pass the real-name and professional authentication. Patients can comment on physicians, send web-based gifts, and vote on physicians after web-based treatment, which constitutes physicians’ web-based word-of-mouth feedback. Accordingly, in offline treatment, physicians may encourage their patients to use OHCs in follow-up treatments to improve their web-based word of mouth. By contrast, Chinese people tend to seek information about their symptoms through search engines when they feel ill, and the top results of some Chinese search engines such as Baidu are often linked to OHCs (Figure 2). In such cases, patients are more likely to visit the OHC portals. Moreover, Chinese people who live in some regions may be less likely to seek offline health care services because of the uneven distribution of medical resources [81,82] and the serious hospital congestion, so they would like to ask for help through OHCs.

Therefore, patients with limited eHealth literacy may also need OHCs. In addition, as supported by the survey by Kim et al [83], some individuals with inadequate eHealth literacy might not be aware of their limited level of eHealth literacy. In other words, some patients have high self-efficacy in seeking health information but do not have sufficient ability to accurately judge information quality and describe their symptoms and feelings. Moreover, these patients may misunderstand physicians’ advice and believe in false advertisements, which can decrease the effectiveness of health information–seeking through OHCs. Accordingly, patients may need to improve their eHealth literacy.

Third, patient compliance can be improved by guiding patient health information–seeking behavior from the following 3 social factors: social support, social presence, and responsiveness; social support is the most important factor related to interpersonal interactions in current and developing OHCs. This finding is consistent with the study by Bronstein [35], who proposed that providing or seeking social support is an important motivation for individuals to participate in OHCs’ activities. Furthermore, according to Audrain-Pontevia and Menvielle [28] and Hajli et al [30], social support is beneficial for self-management and strengthens the physician-patient relationship. Therefore, physicians should provide patients with informational and emotional social support through OHCs to improve patient compliance.

Similarly, social presence and responsiveness are important factors influencing OHC users’ behaviors and can be considered to improve patient compliance in this study. Zhang et al [84] corroborated that increasing the frequency and quality of social interactions between physicians and patients and adopting various interaction methods (ie, text, image, and video) are useful for improving patients’ perceptions of social presence and responsiveness. This finding inspired us to propose that OHCs can develop several interaction tools to improve the social presence perceived by users, which was also supported by Hajli et al [24]. For example, OHCs can adopt some incentives such as providing reward points that can offset the cost of web-based consultation, encouraging users to create posts, sharing health information and interacting with others, and seeking health care services on the web to improve the sense of social presence.

In terms of responsiveness, Resnick et al [46] proposed that forums’ staff can respond when members have not received a timely response, which inspired us to suggest that OHCs can develop a recommendation algorithm to automatically recommend health information according to users’ information seeking histories and preferences. In that case, OHC users can receive social support and perceive responsiveness even though they cannot quickly receive responses from physicians or other members.

This study has several limitations and prospects. First, in addition to social factors, other angles can be considered to explore how to improve patient compliance with treatment and physician’s advice by guiding patient health information–seeking behavior through OHCs in future studies. Second, this study paid attention to the way and effectiveness of patient health information–seeking behavior in a broad sense but ignored the types of this behavior. In fact, patients who engage in different types of health information–seeking behaviors may adopt different ways and achieve different levels of effectiveness. For example, some patients who prefer to seek health information related to self-management skills and lifestyles are likely to browse web-based posts and articles; some, meanwhile, would prefer to browse physicians’ homepages, patient comments, and question and answer blocks to obtain information related to hospitals, physicians, and therapies. Moreover, patients with different potential illnesses may focus on different topics. Therefore, in future studies, we can investigate web-based health information behavior in the context of specific diseases such as diabetes. In addition, the type of health information–seeking behavior can be included in the research model to examine its effect on patient compliance. Third, we tested the hypotheses by analyzing data collected from a cross-sectional survey in the context of China but did not perform external validation, so the generalizability of our research model should be further determined [85]. In addition, the research model needs to be examined outside of China, and the similarities and differences between other countries and regions and China should be explored. Fourth, this study statically investigated the association between patient health information–seeking behavior (way and effectiveness) in OHCs and patient compliance from social perspectives but did not capture the dynamic changes in participants’ behaviors and attitudes in the longitudinal section, and the temporal sequence was questionable [85].

This study proposes a research model to corroborate that patient health information–seeking behavior (way and effectiveness) in OHCs exerts positive effects on patient compliance with the treatment and physician’s advice from the mediations of patients’ perceived social support, social presence, and responsiveness. This study provides suggestions for patients, physicians, and OHC service providers in China to help guide patient health-related behaviors through OHCs to improve patient compliance, patient satisfaction, treatment efficiency, and health outcomes. In the follow-up work, this model should undergo examinations with populations from other countries and regions to further assess its acceptability.