Digital health services have become increasingly important in health care, particularly since the COVID-19 pandemic necessitated the development of new digital consultation systems [1-4]. Previous research indicates that patients often use digital reviews to select health care providers [5]. However, there is limited understanding of how decisions are made when such reviews are not available. In traditional health care settings (ie, offline health care), patients typically choose or are assigned a general practitioner based on their geographical location. In contrast, digital health care settings remove these geographical restrictions, presenting patients with a vast array of choices and different information. This abundance of choices and inconsistent information can make it challenging for patients to compare and select health care providers [6]. For instance, the availability of digital information can lead patients to select doctors based on inherent biases, which can arise from their personal preferences or the way the information is presented on the platform. Given these limitations, patients may resort to evaluating health care providers based on available photographs. This situation raises questions about the influence of a health care provider’s appearance on patient choices and whether gender differences affect these decisions. Previous research indicates that attractive service providers can positively influence consumer attitudes and purchase intentions [7]. High physical attractiveness is often associated with greater credibility and professional ability, affecting consumer attitudes accordingly [8-10]. However, high attractiveness can also have negative effects, such as difficulty in forming same-gender friendships due to competition or eliciting envy and perceived threats among members of the same gender [11-14].

Much of the existing research focuses on general services such as fitness clubs and educational consulting [15]. These findings may not be directly transferable to specialized digital services, such as digital doctor consultations. Such services are categorized as credence services, which are difficult for patients to evaluate due to their complex and specialized nature [16,17]. The challenge of evaluation is further exacerbated in a digital setting where information about the provider’s abilities may be limited.

There is a research gap in understanding how physical appearance affects patient preferences in digital health care settings. This study aims to fill this gap by examining preferences for doctors of varying levels of physical attractiveness in digital consultations. We also consider the moderating effects of disease severity and the availability of information on health care providers’ qualifications to offer both theoretical and practical insights.

Research on doctor selection uses signal theory to explore how patients navigate information asymmetry [18,19]. Text-mining research identified key service features, such as overall service experience and personality traits, that affects patients’ trust and, consequently, consultation volumes [20]. Digital doctor consultation platforms typically display limited information about doctors, such as their names, profile pictures, and titles. The appearance of the doctor may influence patients’ preferences. Prior studies have shown that the attire of physicians influenced patients’ perceptions [21-23]. For example, physicians in white coats were viewed as more experienced and professional than those in casual jackets [24]. Despite this, there is still scant research on how such visual and textual information affect patients’ decision-making.

In non–health care service settings, the impact of physical attractiveness on performance evaluation has shown mixed results. While some studies indicate that higher levels of attractiveness positively influence performance evaluations [25,26], others suggest a negative effect [27]. These mixed outcomes may be attributed to various contextual factors such as gender [28] and service quality conditions [29]. In digital settings, service providers’ physical appearance has been shown to influence customer choice, preference, and purchase intent [30]. For example, in the sharing economy, such as Airbnb, facial characteristics contribute to reputation mechanisms [31]. Studies have found that the perceived trustworthiness and attractiveness of a host’s profile photograph significantly affect Airbnb prices [32,33]. Physical attractiveness also influences digital consumer shopping, with more attractive avatars correlating with higher sales when product involvement is moderate [34].

Previous research indicates that gender differences significantly influence how patients perceive doctors [24,35,36]. The sexual attribution bias (SAB) offers an explanatory framework for these gender effects [37]. SAB leads individuals to attribute the success of same-gender individuals with high attractiveness to luck rather than ability, whereas for opposite-gender individuals, high attractiveness is attributed to ability [38]. This bias manifests in 2 ways: demeaning attractive individuals of the same gender and praising attractive individuals of the opposite gender. Studies have shown that negative vigilance against attractive same-gender individuals is strong and automatic due to intragender competition [39-42].

Unlike general services where attractiveness universally enhances provider popularity [43,44], we posit that in digital doctor platforms, gender plays a significant role in shaping preferences for providers with varying levels of attractiveness. Influenced by same-gender competition, consumers may perceive same-gender providers with high attractiveness as less qualified. Conversely, influenced by mating motivation, consumers may prefer highly attractive providers of the opposite gender. Given the importance of competence in selecting credence service providers [45], SAB suggests that individuals may make derogatory attributions about the competence of same-gender providers with high physical attractiveness.

We anticipate that disease severity will modulate the effects of gender and attractiveness on provider selection. Previous research has established a relationship between disease severity and behavior in various health care contexts [46-49]. The Elaboration Likelihood Model posits 2 routes of information processing: central and peripheral, determined by the individual’s level of involvement [50]. In low-involvement situations, attitudes are influenced by simple cues, whereas high involvement leads to a deeper consideration of complex information. Applying this model and stereotype theory, we suggest that in high-involvement scenarios, consumers will scrutinize providers’ abilities more closely, potentially leading to greater influence of SAB on their choices. For example, women may question the competence of attractive women providers, suspecting that their success is due to their appearance rather than merit [51]. This aligns with research showing that physical attractiveness elicits more jealousy among women than men [14]. Conversely, in low-involvement scenarios, the impact of gender on preferences for providers’ physical attractiveness is expected to be less pronounced.

Furthermore, a foundational assumption for the effects discussed earlier is that consumers lack additional information about the service providers’ abilities. This is often the case in credence services, where consumers typically have less expertise and access to information compared with noncredence services, making them more reliant on extra information supplied by the provider [52]. Research has shown that the provision of such information can mitigate consumer-perceived risk or uncertainty [53].

Study 1 provided evidence to support hypothesis 1. In the context of digital doctor consultation, gender influences people’s preferences for attractive health care providers. People are more likely to select a more (vs less) attractive doctor of the opposite (vs same) gender. This can be explained by the perceived competence of the doctor. In study 1, we adopted a separate evaluation method. On one hand, this method helps to rule out confounding factors and provides strong support for the hypothesis. However, in reality, when patients search for a digital doctor consultation, they may see a list of all available doctors and select the one they prefer. Therefore, in study 2, we adopted a joint evaluation method. Furthermore, we also manipulated the level of disease severity. The results of the second study show that when a service provider’s profile picture was provided to consumers, the consumers’ preferences were greatly influenced by the provider’s gender. The impact of this gender stereotype existed only in the high-involvement condition. If involvement was low, consumers did not have higher requirements for the abilities of medical service providers and thus relied less on their physical attractiveness to infer the ability of the service provider. The results of study 3 illustrated that when extra qualification information was provided, the influence of gender on individual preferences for the service provider’s attractiveness disappeared in both the high- and low-involvement conditions. It is important to note that the context of the research was based in China, a leading country in providing digital consultation services. According to data from the China Internet Network Information Center, by June 2023, the number of users accessing digital medical services in China had surged to 364 million, a rise of 1.62 million since December 2022. The data further reveal that the number of digital hospitals in China has surpassed 3000. These hospitals have offered digital diagnostic and treatment services to more than 25.9 million patients [59]. Thus, the participants in this study were familiar with digital doctor consultations. With the COVID-19 pandemic, an increasing number of European countries have started developing digital consultation services in health care. For instance, Estonia has already begun offering digital services to patients in remote areas. Therefore, the findings from this study can offer significant insights to other countries.

This research contributes to the literature on medical information systems research. First, this study further enhances our understanding of patients’ behavior in digital doctor consultations. As a result of the information asymmetry, patients are always looking for other signals to aid in their decision-making [18]. The lack of trust is one of the biggest barriers to digital services [60]. Besides professional status and service feedback, which are known as important signals for patients’ doctor selection [47], this study has shown that physical attractiveness is also a crucial signal for decision-making in the digital doctor consultation context. This study also helps to deepen the understanding of SAB in the context of digital health care services. Previous studies on SAB focus on contexts such as job interviews [61]. More recently, the literature has increasingly focused on general services, such as education services [15]. In addition, this study sheds light on the boundary condition of SAB. Our findings indicate that the degree of disease severity influences the effect of gender on preferences for attractive service providers. Based on the elaboration likelihood model, consumers with low disease involvement tend to rely on peripheral cues to make choices, which means that they may automatically choose a more attractive service provider. Nevertheless, our research points out that this assumption only holds for both men and women when qualification information is present. When qualification information is absent and information asymmetry exists, men and women react differently to attractive service providers when they are highly involved.

These research findings have some crucial implications for digital health care service management. Providing qualification information of service providers on digital health consultation platforms can mitigate the effect of gender on the individual preference for the attractiveness of a service provider, regardless of the scenario’s level of involvement. In the health care service sector, providing sufficient information to eliminate bias is a useful strategy. In the context of information asymmetry, patients may be influenced by the doctor’s physical attractiveness and make irrational decisions. When marketing telehealth services, hospitals should focus on highlighting doctor expertise, patient satisfaction, and health outcomes instead of relying on doctor attractiveness or demographic characteristics to promote their services. Furthermore, hospitals should develop patient education materials that explain the importance of choosing a doctor based on their qualifications and expertise, rather than their appearance. Also, digital health care platforms could consider implementing features that allow patients to filter and search for doctors based on their qualifications, expertise, and patient satisfaction ratings. This can help patients to make more rational decisions.

This study has some clear limitations, which point, in turn, to avenues for future research. One notable limitation of this study is the restricted age range of both the health care providers depicted in the images and the study participants, who were predominantly younger than 25 years. This lack of age diversity could potentially limit the generalizability of the findings, as perceptions of physical attractiveness and professionalism may vary across different age groups. Although supplementary analyses controlling for age did not significantly alter the results, it remains an open question whether these findings would hold in a more age-diverse sample. Future research should aim to include a broader age range of both health care providers and participants to explore the potential moderating effect of age on the relationships examined in this study.

Another limitation of this study pertains to the clinical scenario presented, which focuses on an acute condition that could potentially be resolved in a single consultation. This may not fully capture the complexities involved when patients are seeking long-term care for chronic conditions. In such cases, the level of disease involvement is likely to be higher, and patients may seek more comprehensive information to assess a doctor’s competence. The dynamics of how gender match and physical attractiveness influence patient choices could thus differ in a chronic care setting. Future research could benefit from exploring these nuances to provide a more holistic understanding.

Another limitation of this study is its focus on China. To enhance the generalizability of our research and generate a more worldwide impact, replication in various countries and across different cultures is necessary. Future research should, for instance, involve recruiting subjects from diverse nations. This is because health care systems vary significantly among countries. Systematic differences in health care structures, policies, and practices can substantially influence how patients evaluate doctors digitally. Consequently, these contextual differences should be carefully controlled for and considered in future studies to ensure the validity and applicability of research findings across different health care systems and cultural backgrounds. Furthermore, the cultural orientation of the patient can also play a role in this situation. Future studies should investigate how varying cultural dimensions, such as collectivism, power distance, and uncertainty avoidance, influence patient preferences and decision-making processes in digital health care settings. For instance, individuals from countries with high uncertainty avoidance may require more concrete information in the doctor’s description to feel comfortable with their choice.

Another important research direction involves examining the impact of other forms of information asymmetry in digital health care settings. For instance, the availability and quality of digital reviews can play a significant role in shaping patient choices. By analyzing the content and credibility of web-based reviews, researchers can better understand how they contribute to patients’ decision-making processes and their perceptions of service providers. In addition, assessing the role of digital reputation management and its influence on patient choices can offer valuable insights into digital health care.